This paper studies the endogenous formation of intersibling altruism. The theory suggests that parental incentive to foster children’s fraternal love is positively related to efficiency gains from more human capital investment in the more gifted child. The empirical analyses explore the plausibly exogenous within-twin difference in birth weight, a proxy for prenatal endowment. Consistent with the theory, the estimation results show that a larger difference in children’s birth weight leads to more intensive parenting practice to foster children’s fraternal love and that when such practice is more intensive, the heavier child obtains more investment relative to the other child.
We use a résumé audit study to investigate the role of employment and unemployment histories in callbacks to job applications. We find that applicants with 52 weeks of unemployment have a lower callback rate than those with shorter spells. There is no relationship, however, between spell length and callback among applicants with spells of 24 weeks or less. We also find that both younger and older applicants have a lower callback probability than prime-aged applicants. Finally, we find that applicants who are employed at the time of application have a lower callback rate than do unemployed applicants.
We provide evidence that constraints that prevent highly skilled women from working long hours hinder gender pay equality. We show that relaxing one such constraint by increasing the supply of substitutes for household production—proxied by intercity variation in predicted low-skilled immigration—increases the relative earnings of women in occupations that disproportionately reward overwork. Low-skilled immigration inflows induce young women to enter occupations with higher returns to overwork and shift women toward higher quantiles of the male wage distribution. The share of women in the top decile remains unaffected, suggesting that other barriers prevent women from reaching the very top.
This paper studies wage determination using the first longitudinal data set containing job-level task information for individual workers. Novel quantitative task measures detail the amount of time spent performing people, information, and objects tasks at different skill levels. These measures suggest natural proxies for on-the-job human capital accumulation and provide new insights about wage determination. Current job tasks are quantitatively important, with high-skilled tasks being paid substantially more than low-skilled tasks. There is no evidence of learning by doing for low-skilled tasks but strong evidence for high-skilled tasks. Current and past high-skilled information tasks are particularly valuable.
While much research has investigated peer effects in education, less is known about peer influence at work, particularly how bad peers affect other workers. I study soldiers during a time when the US Army granted large numbers of morality waivers to recruits with felony or misdemeanor convictions that normally preclude enlistment. I find that soldiers randomly assigned to larger shares of peers with criminal backgrounds are more likely to commit major misconduct. Additionally, that misconduct often occurs in the same month a waivered peer commits misconduct, suggesting that influence occurs through both exposure to adverse peers and their contemporaneous behavior.
A displaced worker might rationally prefer to wait through a long spell of unemployment instead of seeking employment at a lower wage in a job he is not trained for. I evaluate this trade-off using micro data on displaced workers. To achieve identification, I exploit the fact that the more a worker has invested in occupation-specific human capital, the more costly it is for him to switch occupations and therefore the higher is his incentive to wait. I find that between 9% and 17% of total unemployment in the United States can be attributed to wait unemployment.
The Post-9/11 GI Bill brought about the largest expansion in veteran education benefits since the end of World War II, increasing annual benefit expenditures from $3 billion to more than $13 billion. Leveraging variation over time, geography, and type of veterans, I explore the effect of financial aid on degree attainment. I find that the aid expansion increased degree attainment by 5–6 percentage points (25%), roughly 0.4 percentage points per $1,000 of additional maximum aid. These findings indicate that financial aid can increase degree attainment, even for individuals with high levels of initial support.
This paper compares the performance of teachers hired on the basis of a standardized exam to those hired at the union’s discretion in Mexico. My results show that the discretionary hires perform considerably worse than the rule-based hires (as measured by value added to student achievement). The evidence presented here shows the impact of personnel selection mechanisms on the quality of public service delivery.
Young children are thought to be vulnerable to separation from their primary caregiver. This raises concern about whether early childcare enrollment may harm child development. We use childcare assignment lotteries to estimate the effect of enrollment at age 1–2 on cognitive development in Norway. Estimates show significant gains in language and mathematics at age 6–7 and a substantial drop in scores below publicly set thresholds for low performance. Across subsamples, we find a pattern of stronger effects on underperforming groups. We find little support for childcare quality or family income as drivers of our results.
We present results of a randomized trial testing alternative approaches of mapping student achievement into rewards for teachers. Teachers in 216 schools in western China were assigned to performance pay schemes where teacher performance was assessed by one of three different methods. We find that teachers offered “pay-for-percentile” incentives outperform teachers offered simpler schemes based on class-average achievement or average gains over a school year. Moreover, pay-for-percentile incentives produced broad-based gains across students within classes. That teachers respond to relatively intricate features of incentive schemes highlights the importance of paying close attention to performance pay design.
This paper investigates whether interracial contact in childhood impacts adult romantic relationships. We exploit quasi-random variation in the share of black students across cohorts within US schools. We find that more black peers of the same gender lead whites to have more relationships with blacks as adults. While we do not find impacts on labor market outcomes, there are significant effects on reported racial attitudes. Furthermore, an increase in meeting opportunities is unlikely to explain the increased interracial relationships, since the effect is persistent across time, space, and social networks. Overall, interracial contact during childhood has important long-term behavioral consequences.
Labor markets become more efficient in theory if job seekers direct their search. Using online job board data, we show that high-wage ads attract more applicants as in directed search models. Due to distinctive data features, we also estimate significant but milder directed search for hidden (or implicit) wages, suggesting that ad texts and requirements tacitly convey wage information. Since explicit-wage ads often target unskilled workers, other estimates in the literature ignoring hidden-wage ads may suffer from selection bias. Moreover, job ad requirements are aligned with their applicants’ traits, as predicted in directed search models with heterogeneity.
This paper is the first to present direct evidence showing how localized knowledge spillovers arise from workers changing jobs within the same local labor market. Using a unique data set combining Social Security earnings records and balance sheet information for the Veneto region of Italy, I first identify a set of highly productive firms, then show that hiring workers with experience at these firms significantly increases the productivity of other firms. My findings imply that worker flows explain around 10% of the productivity gains experienced by incumbent firms when new highly productive firms are added to a local labor market.
This paper reports the results from a large-scale laboratory experiment that compared the impacts of a performance bonus and a wage gift on output from a creative task and a simple task. We find that the performance bonus substantially increases output in both the creative task and the simple task. By comparison, the wage gift increases output only in the simple task. Additional experimental treatments suggest that reciprocity in the creative task is inhibited because agents are uncertain about how their efforts affect the payments that accrue to the principal as a result of the agents’ work.
This paper introduces a spatial equilibrium model that relates earnings, employment, and internal migration responses to minimum wage increases. Population moves to or away from regions that increase minimum wages depending on the labor demand elasticity and on the financing of unemployment benefits. The empirical evidence shows that increases in minimum wages lead to increases in wages and decreases in employment among the low skilled. The labor demand elasticity is estimated to be around 1, which in the model is in line with the migration responses observed in the data. Low-skilled workers tend to leave regions that increase minimum wages.
This paper analyzes a new explanation of the “ripple effect” of minimum wages based on how minimum wages affect hedonic compensation. Minimum wage hikes lower compensating differentials at low-skill undesirable jobs because they raise wages at the most desirable low-skill job, the minimum wage job. This change in hedonic compensation may cause some individuals to optimally leave low-wage undesirable jobs and seek more desirable employment. If labor supply falls at low-wage undesirable jobs, employers would raise wages, consistent with the ripple effect. Empirically, I provide evidence that hedonic-based labor supply substitution is taking place and contributing to the ripple effect.
Labor markets become more efficient in theory if job seekers direct their search. Using online job board data, we show that high-wage ads attract more applicants as in directed search models. Due to distinctive data features, we also estimate significant but milder directed search for hidden (or implicit) wages, suggesting that ad texts and requirements tacitly convey wage information. Since explicit-wage ads often target unskilled workers, other estimates in the literature ignoring hidden-wage ads may suffer from selection bias. Moreover, job ad requirements are aligned with their applicants’ traits, as predicted in directed search models with heterogeneity.
This paper reports the results from a large-scale laboratory experiment that compared the impacts of a performance bonus and a wage gift on output from a creative task and a simple task. We find that the performance bonus substantially increases output in both the creative task and the simple task. By comparison, the wage gift increases output only in the simple task. Additional experimental treatments suggest that reciprocity in the creative task is inhibited because agents are uncertain about how their efforts affect the payments that accrue to the principal as a result of the agents’ work.
This paper introduces a spatial equilibrium model that relates earnings, employment, and internal migration responses to minimum wage increases. Population moves to or away from regions that increase minimum wages depending on the labor demand elasticity and on the financing of unemployment benefits. The empirical evidence shows that increases in minimum wages lead to increases in wages and decreases in employment among the low skilled. The labor demand elasticity is estimated to be around 1, which in the model is in line with the migration responses observed in the data. Low-skilled workers tend to leave regions that increase minimum wages.
This paper analyzes a new explanation of the “ripple effect” of minimum wages based on how minimum wages affect hedonic compensation. Minimum wage hikes lower compensating differentials at low-skill undesirable jobs because they raise wages at the most desirable low-skill job, the minimum wage job. This change in hedonic compensation may cause some individuals to optimally leave low-wage undesirable jobs and seek more desirable employment. If labor supply falls at low-wage undesirable jobs, employers would raise wages, consistent with the ripple effect. Empirically, I provide evidence that hedonic-based labor supply substitution is taking place and contributing to the ripple effect.
“Daddy quotas” that reserve some parental leave for fathers are increasingly common in developed nations, but it is unclear whether fathers respond to the binding constraints or the labeling effects they produce. Furthermore, little is known about their long-term effects on household behavior. I examine the Quebec Parental Insurance Plan, which improved compensation and reserved 5 weeks of leave for fathers. I find that fathers’ participation increased by 250%, driven by higher benefits and the framing effect of labeling some weeks as “daddy only.” I also present causal evidence that paternity leave reduces sex specialization long after the leave period.
A point of contention in the refugee crisis involves possible adverse effects on host communities associated with poor, low-skilled migrants with low host-community language knowledge. We use unique matched birth and schooling records to examine the effects of a large influx of poor, non-English-speaking Haitian migrants into Florida public schools immediately following the devastating 2010 earthquake. We find zero or modestly positive estimated effects of these migrants on the educational outcomes of incumbent students in the year of the earthquake or in the 2 years that follow, regardless of the socioeconomic status, grade level, ethnicity, or birthplace of incumbent students.
We exploit cross-cohort variation in the prevalence of teacher strikes within and across provinces in Argentina to examine how teacher strikes affect student long-run outcomes. Being exposed to the average incidence of strikes during primary school reduces labor earnings of males and females by 3.2% and 1.9%, respectively. A back-of-the-envelope calculation suggests that this amounts to an aggregate annual earnings loss of $2.34 billion. We also find an increase in unemployment and a decline in the skill levels of the occupations into which students sort. These effects are driven, at least in part, by a reduction in educational attainment.
Despite great focus on and public investment in STEM education, little causal evidence connects quantitative coursework to students’ economic outcomes. I show that state changes in minimum high school math requirements substantially increase black students’ completed math coursework and their later earnings. The marginal student’s return to an additional math course is 10%, roughly half the return to a year of high school, and is partly explained by a shift toward more cognitively skilled occupations. White students’ coursework and earnings are unaffected. Rigorous standards for quantitative coursework can close meaningful portions of racial gaps in economic outcomes.
In this paper we focus on a classic idea concerning span of control, which is that a prime driver is the scale of operations effect. We extend the theory concerning the scale of operations effect by allowing firms’ beliefs concerning a manager’s ability to evolve over the manager’s career. We empirically investigate the resulting testable predictions using a unique single-firm data set that contains detailed information concerning the reporting relationships at the firm. Our empirical analysis supports the notion that the scale of operations effect and learning are both important determinants of a firm’s span of control.
Conventional estimates of Frisch labor supply elasticities are biased in the presence of borrowing constraints. We develop an incomplete-markets model with two-earner households and derive a new estimation approach for the Frisch elasticity that yields unbiased estimates even in samples that include borrowing-constrained households. Our approach exploits that the strength of the estimation bias depends on individuals’ relative contribution to household earnings. It takes the form of a simple interaction term model with minimum data requirements. Using Panel Study of Income Dynamics data, we estimate Frisch elasticities of about 0.7 for men and rather homogeneous Frisch elasticities across the population.
Referrals can improve screening and self-selection of applicants during the hiring process. We model and estimate how referral information affects the selection of employees through job offers, acceptances, and turnover. Using data from a call center company, we show that referrals help employers attract applicants of superior performance. Yet performance differences between referred and nonreferred workers diminish with tenure through selective turnover. Our estimates reveal that referrals allow employers to screen on hard-to-observe but performance-relevant attributes for employees of high performance and high propensity to stay. Thus, referred applicants complete much of the sorting during the hiring process.
Children whose parents were self-employed before China’s socialist transformation were more likely to become self-employed after the economic reform, even though they had no direct exposure to their parents’ businesses. The effect is statistically significant only for sons. The lack of direct exposure to family businesses impedes the transfer of business human capital and motivates us to explore personality traits as the underlying mechanisms. We find that children with self-employed parents are also more likely to invest in risky assets and to consume cigarettes. This suggests that children of self-employed parents inherit personality traits that induce risky behaviors.
This paper studies labor supply responses to transitory income, exploiting the differential timing of the 2008 tax rebates. While an influential literature finds that rebates encourage consumer spending, it has ignored the ramifications on labor supply. I estimate that each rebate dollar reduces monthly earnings by 9 cents with smaller but significant lagged effects. This responsiveness is primarily concentrated in the second quartile of the earnings distribution and among hourly workers. The results imply that the $96 billion in stimulus payments had a partial equilibrium effect of reducing short-term national labor earnings by more than $26 billion.
Conscription forces young men to serve in the military, irrespective of their opportunity costs. Using random assignment in the Danish draft lottery, we find a negative average effect of peacetime military service on earnings, an effect varying by ability, with high-ability men facing a $23,000 lifetime earnings penalty but with low-ability men facing none. This gradient is robust to different measures of labor market prospects. Educational disruption is an important mechanism, while service has little effect on health or criminal activity. The opportunity costs of conscription are borne by men with the best labor market prospects.
The fraction of the US workforce identified as involuntary part-time workers rose to new highs during the US Great Recession and came down only slowly in its aftermath. We assess the determinants of involuntary part-time work using an empirical framework that accounts for business cycle effects and persistent structural features of the labor market. We conduct regression analyses using state-level panel data for the years 2003–16. The results indicate that structural factors, notably shifts in the industry composition of employment, have held the incidence of involuntary part-time work slightly more than 1 percentage point above its prerecession level.
Little is known about the role birth order plays in delinquency and adult crime outcomes that carry significant externalities. We use rich data sets from Denmark and Florida to examine these outcomes and explore potential mechanisms. Despite large environmental differences between the areas, we find remarkably consistent results: in families with two or more children, secondborn boys are 20%–40% more likely to be disciplined in school and enter the criminal justice system than are their firstborn male siblings. We rule out health at birth and school quality as mechanisms but find evidence for the role of parental time investment.
This paper examines whether the introduction of birthright citizenship in Germany affected immigrant children’s educational outcomes at the first three stages of the education system: preschool, primary school, and secondary school. Using a birth date cutoff as a source of exogenous variation, we find that the policy (i) increased immigrant children’s participation in noncompulsory preschool education, (ii) had positive effects on key developmental outcomes measured at the end of the preschool period, (iii) caused immigrant children to progress faster through primary school, and (iv) increased the likelihood of them attending the academic track of secondary school.
This paper investigates the relationship between aspirations and inequality in higher education participation. Using a regression discontinuity design, I evaluate the impact of a national-scale United Kingdom policy aimed at raising the aspirations toward college education of pupils from disadvantaged backgrounds by involving them in outreach activities. The results show that the policy successfully raised the aspirations of the target students and their participation in postcompulsory education. However, its final effect on college enrollment was on the whole negligible, thus casting doubt on the effectiveness of policies that uniquely leverage aspirations to reduce inequality in educational attainment.
We study how parental leave benefit levels affect household labor supply, family income, and child outcomes, exploiting the speed premium (SP) in the Swedish leave system. The SP grants mothers higher benefits for a subsequent child without reestablishing eligibility through market work if two births occur within a prespecified interval. We use the spacing eligibility cutoffs in a regression discontinuity framework and find that the SP improves educational outcomes of the older child but not those of the younger. Impacts are likely driven by increased maternal time and the quality of maternal time relative to the counterfactual mode of care.
Jurisdictions across the United States have adopted “ban the box” (BTB) policies preventing employers from asking about job applicants’ criminal records until late in the hiring process. Their goal is to improve employment outcomes for those with criminal records, with a secondary goal of reducing racial disparities in employment. However, removing criminal history information could increase statistical discrimination against demographic groups that include more ex-offenders. We use variation in the timing of BTB policies to test BTB’s effects on employment. We find that BTB policies decrease the probability of employment by 3.4 percentage points (5.1%) for young, low-skilled black men.
Informational asymmetries between employers may inhibit optimal worker mobility. However, researchers rarely observe shocks to employers’ information. I exploit two school districts’ adoptions of value-added (VA) measures of teacher effectiveness—informational shocks to some, but not all, employers—to provide direct tests of asymmetric employer learning. I develop a learning model and test its predictions for teacher mobility. I find that adopting VA increases within-district mobility of high-VA teachers, while low-VA teachers move out of district to uninformed principals. These patterns are consistent with asymmetric employer learning. This sorting from widespread VA adoption exacerbates inequality in access to effective teaching.
How do alternative job opportunities affect teacher quality? We provide causal evidence on this question by exploiting business cycle conditions at career start as a source of exogenous variation in the outside options of potential teachers. Unlike prior research, we directly assess teacher quality with value-added measures of impacts on student test scores, using administrative data on over 30,000 Florida public school teachers. Consistent with a Roy model of occupational choice, teachers entering the profession during recessions are significantly more effective in raising student test scores. Results are supported by robustness tests and unlikely to be driven by differential attrition.
This paper reports findings from a randomized evaluation of an intensive tutoring program conducted in underprivileged high schools. Within each school, the intervention targets students identified as having the ability to pursue a college education. The program is designed to strengthen their readiness for higher education. We demonstrate that such an intervention can have negative effects on a large fraction of participants, even though participation is entirely voluntary. This result is consistent with a simple model where time invested in extracurricular programs and time invested in homework represent imperfect substitutes in the education production function.
On the leading job board CareerBuilder.com, high-wage job postings unexpectedly attract fewer applicants, and this is the case even within a detailed occupation. Viewed through the lens of our directed search model, this negative relationship is indicative of substantial applicant heterogeneity within an occupation. Empirically, we find that job title heterogeneity is key: within a job title, jobs with 10% higher wages do attract 7.7% more applicants. Furthermore, our findings are consistent with a higher return to worker quality for hires in “manager” and “senior” job titles. Overall, our findings demonstrate the power of words in the matching process.
This paper examines the transmission of human capital from parents to children using variation in parental influence due to parental death, divorce, and the increasing specialization of parental roles in larger families. All three sources of variation yield strikingly similar patterns that show that the strong parent-child correlation in human capital is largely causal. In each case, the parent-child correlation in education is stronger with the parent who spends more time with the child and weaker with the parent who spends relatively less time parenting. These findings help us understand why educated parents spend more time with their children.
Hurricanes Katrina and Rita devastated the US Gulf Coast in 2005. We use job-level data to compare the evolution of earnings for affected workers in four states with workers from matched control counties. We attribute short-term earnings losses to job separations and long-term gains to wage growth in the affected areas. Wages rose due to reduced labor supply and increased labor demand in the affected labor markets. Damage to a worker’s residence or workplace accentuated short-term earnings losses. Effects varied by prestorm industry, with larger gains for workers in sectors related to rebuilding.
Low-skill workers are comparatively immobile. This paper estimates the role of housing prices and social transfers in accounting for this fact using a spatial equilibrium model. Reduced-form estimates using US census data show that positive local labor demand shocks increase population more than negative shocks reduce population, that this asymmetry is larger for low-skill workers, and that such an asymmetry is absent for average wages, housing values, and rental prices. Generalized method of moments estimates reveal that the comparative immobility of low-skill workers is due not to higher mobility costs but to a lower incidence of adverse labor demand shocks.
We investigate the effect of Head Start on education and wage income for individuals in their 30s in the NLSY79. We contribute to the existing literature by examining effects across outcome distributions, using an approach that relies on two weak stochastic dominance assumptions that can be checked using pre–Head Start cohorts. We find that Head Start has positive and statistically significant effects on years of education and wage income. We also uncover important heterogeneity in the program’s effectiveness; the effects are concentrated at the lower end of the distribution, and the effects are strongest for women, blacks, and Hispanics.
Increasing access to education may have consequences that go beyond effects on marginal students encouraged to enroll. It may change peer effects, school quality, and returns to skill. This paper studies how classmates and teaching inputs affect learning of university students, exploiting an educational expansion in Italian STEM majors. Newly collected data on 27,236 students indicate that less prepared classmates and congestion of teaching resources lowered learning of incumbent students in STEM fields. Their learning, however, increased in courses in which the new classmates raised average preparedness. These effects might have had long-lasting consequences on the returns to STEM degrees.
The purpose of this paper is to examine how social environment affects women’s STEM choices as early as high school. Using administrative data from China, we find that exposure to high-performing female peers in mathematics increases the likelihood that women choose a science track during high school, while exposure to more high-performing males decrease this likelihood. We also find that peer quality has persistent effects on college outcomes. Overall, there is little evidence of peer effects for boys. Our results suggest that girls doing well in mathematics provide an affirmation effect that encourages female classmates to pursue a STEM track.
This paper presents findings from a national experimental evaluation of performance bonuses funded by the Teacher Incentive Fund grant program. The study finds no robust evidence of positive impacts of bonuses on student achievement, although some specifications suggest a small positive effect that compares favorably with other education interventions. When controlling for covariates, we find that offering bonuses of an average yearly cost of $100 per student had a small significant impact of about 0.04 standard deviations. However, these impacts are smaller (0.01 standard deviations) and become insignificant when not controlling for covariates or using an alternative method of inference.
Low-skill workers are comparatively immobile. This paper estimates the role of housing prices and social transfers in accounting for this fact using a spatial equilibrium model. Reduced-form estimates using US census data show that positive local labor demand shocks increase population more than negative shocks reduce population, that this asymmetry is larger for low-skill workers, and that such an asymmetry is absent for average wages, housing values, and rental prices. Generalized method of moments estimates reveal that the comparative immobility of low-skill workers is due not to higher mobility costs but to a lower incidence of adverse labor demand shocks.
We investigate the effect of Head Start on education and wage income for individuals in their 30s in the NLSY79. We contribute to the existing literature by examining effects across outcome distributions, using an approach that relies on two weak stochastic dominance assumptions that can be checked using pre–Head Start cohorts. We find that Head Start has positive and statistically significant effects on years of education and wage income. We also uncover important heterogeneity in the program’s effectiveness; the effects are concentrated at the lower end of the distribution, and the effects are strongest for women, blacks, and Hispanics.
Increasing access to education may have consequences that go beyond effects on marginal students encouraged to enroll. It may change peer effects, school quality, and returns to skill. This paper studies how classmates and teaching inputs affect learning of university students, exploiting an educational expansion in Italian STEM majors. Newly collected data on 27,236 students indicate that less prepared classmates and congestion of teaching resources lowered learning of incumbent students in STEM fields. Their learning, however, increased in courses in which the new classmates raised average preparedness. These effects might have had long-lasting consequences on the returns to STEM degrees.
The purpose of this paper is to examine how social environment affects women’s STEM choices as early as high school. Using administrative data from China, we find that exposure to high-performing female peers in mathematics increases the likelihood that women choose a science track during high school, while exposure to more high-performing males decrease this likelihood. We also find that peer quality has persistent effects on college outcomes. Overall, there is little evidence of peer effects for boys. Our results suggest that girls doing well in mathematics provide an affirmation effect that encourages female classmates to pursue a STEM track.
This paper presents findings from a national experimental evaluation of performance bonuses funded by the Teacher Incentive Fund grant program. The study finds no robust evidence of positive impacts of bonuses on student achievement, although some specifications suggest a small positive effect that compares favorably with other education interventions. When controlling for covariates, we find that offering bonuses of an average yearly cost of $100 per student had a small significant impact of about 0.04 standard deviations. However, these impacts are smaller (0.01 standard deviations) and become insignificant when not controlling for covariates or using an alternative method of inference.
The Self-Sufficiency Project (SSP) was a well-known welfare-to-work experiment that provided a generous but time-limited financial incentive to leave welfare and enter the workforce. Experimental evidence showed large short-term impacts but no lasting effects. We argue that these conclusions need to be reassessed. Policy changes implemented during the SSP implied that the control group’s behavior did not provide an appropriate counterfactual. We estimate the impacts the financial incentive would have had in an unchanging policy environment. This reassessment leads to significant changes in the lessons previously reached. Our study demonstrates that experimental findings need to be interpreted with care.
We estimate the impact of charter schools on early-life labor market outcomes in Texas. We find that, at the mean, charter schools have no impact on test scores and a negative impact on earnings. No Excuses charter schools increase test scores and 4-year college enrollment but have a statistically insignificant impact on earnings, although the coefficient is almost identical to what one would expect given the correlation between test scores and wages. Other types of charter schools decrease test scores, 4-year college enrollment, and earnings, and surprisingly the decrease in wages is more negative than one would anticipate.
We study the labor market returns to a state-guaranteed loan used to finance university degrees in Chile. Using a regression discontinuity design, we show that marginally eligible students forgo vocational education in favor of university education but reduce their probability of graduation. Even though university loan takers accumulate more student debt, their labor market outcomes are not different from those of ineligible students. We find suggestive evidence that the lower quality of the receiving institutions accounts for these results. Finally, we extrapolate the effects away from the eligibility cutoff and show that supramarginal students benefit from this policy.
We investigate how high school gender composition affects students’ participation in STEM at college. Using Danish administrative data, we exploit idiosyncratic within-school variation in gender composition. We find that having a larger proportion of female peers reduces women’s probability of enrolling in and graduating from STEM programs. Men’s STEM participation increases with more female peers present. In the long run, women exposed to more female peers are less likely to work in STEM occupations, earn less, and have more children. Our findings show that the school peer environment has lasting effects on occupational sorting, the gender wage gap, and fertility.
We use population-level data on all Florida children born between 1994 and 2002 to examine the long-term effects of prenatal exposure to environmental toxicants from a Superfund (toxic waste) site. We compare siblings who faced different toxic exposures during gestation because of Superfund site cleanup (or, in other specifications, because of a family move). Children exposed to toxic waste while gestating have substantially worse cognitive and behavioral outcomes than do their unaffected siblings. These results are much larger than what would have been predicted were the effects of Superfund site exposure operating solely through standard measures of birth outcomes.
We present experimental evidence on four US reemployment programs targeting unemployment insurance (UI) recipients during the Great Recession. All programs reduced UI spells, produced UI savings that exceeded program costs, and increased employment rates. The services referral program had the smallest effects, occurring because of voluntary UI exits by participants to avoid requirements. The two programs reviewing participants’ UI eligibility produced greater effects because they induced voluntary exits and disqualified participants who did not meet UI requirements. The program requiring participation in both eligibility review and job-counseling services was the most effective, suggesting that services improved participants’ job search efforts.
This paper examines the long-run impacts of income shocks by exploiting variation in coffee cultivation patterns within Colombia and world coffee prices during cohorts’ school-going years. The results indicate that cohorts that faced higher returns to coffee-related work in childhood completed fewer years of schooling and have lower adult earnings scores. Several pieces of evidence suggest that these results reflect changes in educational decisions induced by temporary changes in the opportunity cost of schooling. These findings are consistent with the possibility that students may ignore or heavily discount the future consequences of dropout decisions when faced with immediate income gains.
This paper provides evidence for why individuals join unions instead of free riding. I model membership as legal insurance. To test the model, I use the incidence of news stories concerning allegations against teachers in the United Kingdom as a plausibly exogenous shock to demand for such insurance. I find that for every five stories occurring in a region, teachers are 2.2 percentage points more likely to be members in the subsequent year. These effects are larger when teachers share characteristics with the news story and can explain 45% of the growth in teacher union membership between 1992 and 2010.
Caseworkers are the main human resources used to provide social services. This paper asks whether and how much caseworkers matter for the outcomes of unemployed individuals. Using large-scale administrative data, I exploit exogenous variation in unplanned absences among Swiss unemployment insurance caseworkers. I find that individuals who lose a meeting with their caseworker stay unemployed 5% longer. Results show large heterogeneity in the personal impact of caseworkers: the effect of a forgone meeting is zero for caseworkers in the lower half of the productivity distribution but is more than twice the average effect for caseworkers in the upper half.
In many settings, a policy discontinuity comprises several treatments that cannot be separately identified using a standard regression discontinuity design. I propose a method for identifying distinct treatment components from a single discontinuity by exploiting the asymmetry between entities entering versus exiting treatment. Using data from New York City for 2009–13, I apply my strategy to the discontinuity associated with the introduction of class size caps—a widespread approach for reducing class sizes. I find that class size reductions increase student achievement, although these gains are counteracted by a newly hired teacher effect. The method has broad potential applicability.
There is concern that the risky behaviors of teenagers, such as truancy, negatively influence the behaviors of others through their social networks. We use administrative data to construct social networks based on students who are truant together. We simulate these networks to document that certain students systematically coordinate their absences. We validate them by showing that a parent information intervention on student absences has spillover effects from treated students onto their peers. Excluding these effects understates the intervention’s cost-effectiveness by 43%. We show that there is potential to use networks to target interventions more efficiently given a budget constraint.
We construct the first long-term comparison of cross-sectional and panel estimates of immigrant earnings assimilation in the United States from a single data source. Unlike previous results, we find that selective out-migration of higher-earning immigrants biases downward cross-sectional estimates for all education groups. Cross-sectional estimates dramatically understate earnings growth for high-skilled foreign-born workers. The bias stems from both selective out-migration and selective employment; among high-skilled immigrants, low earners find employment with a substantial delay, while high earners work immediately on arrival. We present suggestive evidence that the H-1B visa program may play a role in estimated immigrant earnings dynamics.
This paper uses administrative employment and conviction data to evaluate laws that restrict access to job seekers’ criminal records. Convictions generate decreases in employment and earnings, partly due to shifts toward lower-paying industries less likely to check criminal histories. However, a 2013 Seattle law barring employers from examining job seekers’ records until after an initial screening had negligible impacts on ex-offenders’ labor market outcomes. The results are consistent with employers deferring background checks until later in the interview process or ex-offenders applying only to jobs where clean records are not required, a pattern supported by survey evidence.
The composition of immigrants depends not only on immigrant choice but also on immigration policy, because slots are rationed. Policy determines immigrant attainment, as evidenced by immigrants from Algeria having higher educational attainment than those from Israel or Japan. Theory predicts and evidence confirms that immigrant attainment is inversely related to the number admitted from a source country and positively related to population and education levels at home. A parsimonious specification has only two variables yet explains a majority of the variation in educational attainment of US immigrant groups. The theory and predictions are bolstered by Swedish data.
We document that individuals who grow up in high firm density areas are more likely to become entrepreneurs, given firm density in their current location, and to run businesses in the sector with the highest density when young. Firm density at an entrepreneur’s young age drives current firm profitability and is more important than current density for business performance. Results hold in a sample of movers, which allows addressing endogeneity concerns. These results are consistent with entrepreneurial skills being partly learnable through social contacts. Accordingly, entrepreneurs who grow up in high firm density areas adopt better managerial practices.
We report the results of a field experiment in which treated employers could not observe the compensation history of their job applicants. Treated employers responded by evaluating more applicants and evaluating those applicants more intensively. They also responded by changing what kind of workers they evaluated: treated employers evaluated workers with 5% lower past average wages and hired workers with 13% lower past average wages. Conditional on bargaining, workers hired by treated employers struck better wage bargains for themselves.
Choosing where to apply to college is a complex problem with long-term consequences, but many students lack the guidance necessary to make optimal choices. I show that a technology that provides low-cost personalized college admissions information to more than 40% of high schoolers significantly alters college choices. Students shift applications and attendance to colleges for which they can observe information on schoolmates’ admissions experiences. Responses are largest when such information suggests a high admissions probability. Disadvantaged students respond the most, and information on in-state colleges increases their 4-year college attendance. Data features and framing, however, deter students from selective colleges.
We study the impact of trade exposure on the job biographies of 2.4 million manufacturing workers in Germany. Rising export opportunities lead to two equally important sources of earnings gains: on the job and employer switches within the same industry. Highly skilled workers benefit the most. Import shocks mostly hurt low-skilled workers, especially when they possess lots of industry-specific human capital. They also destroy workers’ rents when separating from high-wage plants, and they leave strongly scarring effects in the event of a mass layoff. We connect our results to the growing theoretical literature on the labor market effects of trade.
We estimate the returns to a broad set of graduate degrees. To control for heterogeneity in preferences and ability, we use fixed effects for combinations of field-specific undergraduate and graduate degrees obtained by the last time we observe an individual. Basically, we compare earnings before the graduate degree to earnings after it. Using National Science Foundation data, we find large differences across graduate fields in earnings effects. The returns often depend on the undergraduate major. The contribution of occupational upgrading to the earnings gain varies across degrees. Finally, simple regression-based estimates of returns to graduate fields are often highly misleading.
Using data from a Canadian field experiment on financial barriers to higher education, we estimate the distribution of the value of financial aid for prospective students. We find that a considerable share of prospective students perceive significant credit constraints. Most individuals are willing to pay a sizable interest premium above the prevailing market rate for the option to take up a loan, with a median interest rate wedge equal to 6.8 percentage points for a $1,000 loan. The willingness to pay for financial aid is heterogeneous across students, with discount factors playing a key role in accounting for this variation.
This paper establishes five new facts about instructional costs in higher education using department-level data from a broad range of institutions. Costs vary widely across fields, ranging from electrical engineering (90% higher than English) to math (25% lower). This pattern is largely explained by differences in class size and faculty pay. Some STEM fields experienced steep declines in expenditures over the past 17 years, while others saw increases. Changes in class size and teaching loads alongside a shift toward contingent faculty explain these trends. Finally, the association between online instruction and instructional costs is statistically indistinguishable from zero.
We estimate turnover costs in small retail sales teams using daily sales data and an advance notice requirement to address endogeneity concerns. In addition to short-staffing and onboarding costs, we identify two less familiar sources of turnover costs: incumbent workers’ recruitment activities and reductions in team morale after a departure is announced. Our estimates of total turnover costs are relatively modest, however: 10% higher turnover is about as costly as a 0.6% wage increase. We attribute these low costs to a set of complementary personnel policies that ensure that only 25% of departures result in a short-staffing spell.
We analyze how the formal recognition of foreign qualifications affects immigrants’ labor market outcomes. The empirical analysis is based on a novel German data set that links respondents’ survey information to their administrative records, allowing us to observe immigrants at monthly intervals before, during, and after their application for occupational recognition. We find that 3 years after obtaining recognition, immigrants earn 19.8% higher wages and are 24.5 percentage points more likely to be employed than immigrants in the control group. We further document that occupational recognition leads to full convergence of immigrants’ earnings to those of their native counterparts.
How does school quality affect health amid multiple behavioral responses? The Rosenwald schools transformed school quality for rural southern African Americans in the early 1900s. Research shows that the schools made black migration northward more likely and that the Great Migration shortened life expectancy for these migrants. Besides the hypothesized health-enhancing effects of school quality, negative health effects might also occur through migration. We disentangle behavioral mechanisms and find complete exposure to the Rosenwald schools increased life expectancy by 2–3 months; a more naive approach finds no relationship. Results are robust to heterogeneous treatment effects and various measurement issues.
Noncognitive characteristics and personality traits can be strong predictors of economic and social outcomes of individuals. In this paper, using data on cognitive ability and psychologist-assessed “sociability” and “adaptability” linked to administrative data for the male 1932–33 birth cohort in Norway, we analyze how these three characteristics affect men’s probability to migrate across labor markets. We find that higher adaptability, the capacity to adjust to new environments and situations, and higher cognitive ability are significant predictors of the probability to migrate. Adaptability is a particularly strong migration predictor for individuals with low cognitive ability or low socioeconomic background.
One concern regarding US immigration policies is that skilled workers on temporary visas may be bound to their employers in “indentured servitude,” giving rise to monopsony power. I investigate this concern by estimating the effect of acquiring permanent residency on the job mobility and earnings of these workers. Using fixed effects models, I find an immediate upsurge in mobility upon permanent residency receipt, primarily driven by voluntary moving being depressed during the employer-sponsored immigration process. Job lock reduces the earnings of male workers by 4.7%, which translates to a 2% surplus for firms after extra hiring costs are subtracted.
We use administrative payroll data to estimate the effect of the minimum wage on employment and wages. We find that both effects are nuanced. While the overall number of low-wage workers in firms declines, incumbent workers are no less likely to remain employed. We find that firms reduce employment primarily through hiring, and there is significant heterogeneity across the nontradable and tradable sectors. For wages, we find modest spillovers extending up to $2.50 above the minimum wage. Spillovers accrue to both incumbent workers and new hires, but only within firms that employ a significant fraction of low-wage workers.
We investigate whether increased animosity toward Muslims after 9/11 had spillover effects on Black and Hispanic individuals in the federal criminal justice system. Using linked administrative data tracking defendants from arrest through sentencing, we find that after 9/11, sentence and presentence outcomes for Hispanic defendants significantly worsened. Outcomes for Black defendants were unchanged. The findings are consistent with judges and prosecutors displaying social preferences characterized by contagious animosity from Muslims to Hispanics. Our findings provide among the first field evidence of contagious animosity, indicating that social preferences across out-groups are interlinked and malleable.
We combine extremely granular information on the location and timing of homicides with a number of large administrative educational data sets from Brazil to estimate the effect of exposure to homicides around schools, around students’ residences, and on their way to school. We show that violence has a detrimental effect on both school attendance and standardized test scores and that it increases the dropout rates of students substantially. We use exceptionally rich information from student- and parent-background questionnaires to investigate the effect of violence on aspirations and attitudes toward education. We find that boys systematically report lower educational aspiration.
Good information on self-employment is needed to inform the ongoing discussion of the rise of the gig economy and its implications for workers. Tax data show significant growth in self-employment not captured in the Annual Social and Economic Supplement to the Current Population Survey (CPS-ASEC). The growing gap reflects both self-employment in tax data missing from the CPS-ASEC and self-employment misreported as wage and salary work. We document consistent patterns in the discrepancies between the tax and survey data but are able to explain only a modest share of the growing disagreement between them.
This study presents new evidence on the impacts of unionization using administrative data matching workers to employers in a regression discontinuity design. Close union elections exhibit substantial nonrandom selection or manipulation. Estimates accounting for this selection show that unionization substantially decreases payroll, employment, average worker earnings, and establishment survival. Payroll and earnings decreases are driven by composition changes, with older and higher-paid workers leaving unionizing establishments and younger workers joining or staying. Worker-level effects on earnings are small and are reconciled with large negative establishment-level effects in a model of employer and employee selection into union jobs.
Building on earlier work that shows that the Earned Income Tax Credit (EITC) has a substantial positive effect on maternal labor supply, we show that labor supply effects are concentrated among mothers with children under age 3, with only moderate effects of the EITC on the labor supply of mothers with teenagers. These increases in labor supply are coupled with large increases in the use and cost of child care among mothers with children under age 3. Results highlight the importance of considering heterogeneous treatment effects of policy and have implications for child care policy and other family policy.
This paper investigates the wage returns to schooling and actual early work experiences and how these returns have changed over the past 20 years. Using the NLSY surveys, we develop and estimate a dynamic model of the joint schooling and work decisions that young men make in early adulthood and quantify how they affect wages using a generalized Mincerian specification. Our results highlight the need to account for dynamic selection and changes in composition when analyzing changes in wage returns. In particular, we find that ignoring the selectivity of accumulated work experiences results in overstatement of the returns to education.
We study the impacts of a major reform to vocational secondary education that aimed to move beyond the trade-off between providing occupational skills and closing off academic opportunities. Norway’s Reform 94 integrated more general education into the vocational track, offered vocational students a pathway to college, and increased access to apprenticeships. We identify reform impacts through a difference-in-discontinuity research design applied to linked population registries. The reform substantially increased initial vocational enrollment, but with divergent consequences by gender. Overall, the reform succeeded at improving social mobility, particularly for disadvantaged men, but it somewhat exacerbated the gender gap in adult earnings.
We study how firms’ personnel practices react to labor market regulation. While a company is compelled to comply with a new law, what is the ripple effect of the change on existing personnel policies and practices? We provide evidence using passage of the Age Discrimination in Employment Act and nearly two decades of administrative data from a large US firm. In line with theory, we find a weakening of long-term implicit incentives and movement toward pay for performance. Furthermore, the data are consistent with the firm carefully managing its personnel practices according to economic principles to preserve incentives for employees.
How does personal exposure to economic conditions affect individual human capital investment choices? Focusing on bachelor’s degree recipients, we find that cohorts exposed to higher unemployment rates during typical schooling years select majors that earn higher wages, have better employment prospects, and lead to work in a related field. Conditional on expected earnings, recessions also encourage women to enter male-dominated fields, and students of both genders pursue more difficult majors. We conclude that economic environments change how students select majors, and we find evidence that students who respond to the business cycle enjoy earnings typical of their new majors.
This paper exploits county-level variation in exposure to news about labor markets impacted by fracking to show that access to information about employment opportunities affects migration. Exposure to newspaper articles about fracking increased migration to areas mentioned in the news by 2.4% on average, concentrated among young, unmarried, less educated men. Commuting also increased, sentiment of the news matters, and TV news has an impact. Google searches for “fracking” and names of states specifically mentioned spike after news broadcasts about fracking. Counties experiencing weak labor markets are the most responsive, suggesting that these areas see large benefits to information provision.
Deciding which field to study is one of the most consequential decisions college students make, but most research on the topic focuses on students attending 4-year colleges. To understand how students attending community colleges make field-of-study decisions, I link administrative educational records of recent high school graduates with local mass layoff and plant-closing announcements. I find that declines in local employment deter students from entering closely related community college programs and instead induce them to enroll in other vocationally oriented programs. Students predominantly shift enrollment between programs that lead to occupations requiring similar skills.
This paper reports on a field experiment in 82 high schools trialing a low-cost intervention in schools’ operations: teachers working in the same school observed and scored each other’s teaching. Students in treatment schools scored 0.07 student standard deviations higher on math and English exams. Teachers were further randomly assigned to roles—observer and observee—and students of both types benefited, observers’ students perhaps more so. Doubling the number of observations produced no difference in student outcomes. Treatment effects were larger for otherwise low-performing teachers.
I show that firm location decisions create barriers to accessing high-wage employers for students at distant universities. I collect office locations and campus recruiting strategies for more than 70 banking and consulting firms from 2000 to 2013. After firms open an office, students at nearby universities are nearly four times more likely to have on-campus access to the firm. Access increases for universities across a wide range of selectivity. Additional data from universities, LinkedIn, and mobility report cards suggest effects on hires and longer-run income success.
We investigate how demand conditions affect employers’ provision of safety—something about which theory is ambivalent. Positive demand shocks relax financial constraints that limit safety investment but simultaneously raise the opportunity cost of increasing safety rather than production. We study the US metals mining sector, leveraging exogenous demand shocks from short-term variation in global commodity prices. We find that positive price shocks substantially increase workplace injury rates and safety regulation noncompliance. While these results indicate the general dominance of the opportunity cost effect, shocks that only increase mines’ cash flow lower injury rates, illustrating that financial constraints also affect safety.
We use public documents from the Students for Fair Admissions v. Harvard University lawsuit to examine admissions preferences for recruited athletes, legacies, those on the dean’s interest list, and children of faculty and staff (ALDCs). More than 43% of white admits are ALDC; the share for African American, Asian American, and Hispanics is less than 16%. Our model of admissions shows that roughly three-quarters of white ALDC admits would have been rejected absent their ALDC status. Removing preferences for athletes and legacies would significantly alter the racial distribution of admitted students away from whites.
We conduct a field experiment paying students according to relative performance on a mathematics exam and tracking study efforts on a mathematics website to test the incentive effects of affirmative action (AA) policies on study effort and math proficiency. AA increases study effort and exam performance for the majority of disadvantaged students targeted by the policy. While the performance of the highest-ability students targeted by the AA policy declines, on average study activity and exam performance rise under AA. Overall, the experimental evidence suggests that AA can promote greater equality of market outcomes while narrowing achievement gaps.
How widespread are social network effects? To answer this, I introduce a page-based approach for identifying individuals living in close proximity and compare how the propensity to work in the same industry varies among worker pairs residing in the same versus different areas. Across the 70 largest cities in the early twentieth-century United States, those from the same area are more likely to work in the same industry. On average, the increase in propensity is around 14%–20% of the baseline mean. These effects also tend to be stronger among single women and migrants from the same country of origin.
We analyze the long-term effects of a high school remedial education program almost two decades after its implementation. Treated students experienced an 11% increase in completed years of postsecondary schooling, a 4% increase in annual earnings, and a significant increase in intergenerational income mobility. These gains reflect improvement of students mainly from below-median-income families. We conclude that the program had gains beyond the short-term significant improvements in high school matriculation exams. A cost-benefit analysis of the program suggests that the government will recover its cost within 7–8 years, implying a very high rate of return.
Female workers earn $0.89 for each male-worker dollar even in a unionized workplace, where tasks, wages, and promotion schedules are identical for men and women by design. Using administrative time-card data on bus and train operators, we show that this earnings gap can be explained by female operators taking fewer hours of overtime and more hours of unpaid time off than male operators. Female operators, especially those with dependents, pursue schedule conventionality, predictability, and controllability more than male operators. While reducing schedule controllability can limit the earnings gap, it can also hurt female workers and their productivity.
I examine worker effort as a potential margin of adjustment to a minimum wage hike using unique data on piece rate workers who perform a homogenous task and whose individual output is rigorously recorded. By employing a difference-in-differences strategy that exploits the increase in Florida’s minimum wage from $6.79 to $7.21 on January 1, 2009, and worker location on the pre-2009 productivity distribution, I provide evidence consistent with incumbent workers’ positive effort responses.
We present the first analysis of the effect of grade retention on adult criminal convictions, exploiting test cutoffs for ninth-grade promotion in Louisiana. Eighth-grade retention increases the likelihood of violent crime conviction by 1.05 percentage points (58.44%) and increases the number of violent crime convictions at first conviction. The effects are likely driven by declines in high school peer quality and reduced educational investments that result in lower noncognitive skill acquisition. Extrapolating effects away from the cutoff shows that our results are generalizable to a larger group of low-performing students and are evident for both property and drug crimes.
We study the effects of peer gender composition in STEM doctoral programs on persistence and degree completion. Leveraging unique new data and quasi-random variation in gender composition across cohorts within programs, we show that women entering cohorts with no female peers are 11.7 percentage points less likely to graduate within 6 years than their male counterparts. A 1 standard deviation increase in the percentage of female students differentially increases women’s probability of on-time graduation by 4.4 percentage points. These gender peer effects function primarily through changes in the probability of dropping out in a PhD program’s first year.
This paper examines the impact of male casualties due to World War II on fertility and female employment in the United States. We rely on the number of casualties at the county level and use a difference-in-differences strategy. While most counties in the United States experienced a baby boom following the war, we find that the increase in fertility was lower in high-casualty-rate counties than in low-casualty-rate counties. Analyzing the channels through which male casualties could have decreased fertility, we provide evidence that county male casualties are positively related to 1950s female employment and household income.
Firms often impose constraints on working hours. While many believe that these constraints shape labor supply decisions, little evidence exists to support such views. We explore this relationship using linked employer-employee data on hours worked and the variation in tax rates derived from the 2010 Danish tax reform. We show that hours worked are unresponsive to individual tax changes in firms with strict constraints, whereas they respond to these changes, directly and through spillovers, in firms with looser constraints. Starting from these findings, we discuss the determinants of hours constraints, distinguishing between firms’ technologies and coordination of hours among coworkers.
We analyze the impact of Ford Motor Company’s compensation practices on the Detroit-area labor market from 1918 to 1947. Previous studies imply that Ford paid race-independent wages, but its Black workers were sorted into undesirable departments. We extend these results using propensity score reweighting of census data and Ford’s records and confirm that Ford paid equal wages. We then develop a search model with discriminatory and equal wage firms to assess the impact of Ford’s policy on the larger labor market. Calibrated simulations suggest that Ford may have reduced the wage gap in southeastern Michigan by as much as 50%.
In a professional services firm, top management unexpectedly adjusted the pay of consultants in some divisions to the pay in other divisions. In this quasi experiment, fixed wages increased and bonuses decreased, reducing pay for the high performers and increasing it for the low performers. Individual outputs and efforts decreased by 30%, and attrition and absenteeism increased. The effects were driven by those who were rationally expecting to lose from the pay change. Observing a period of more than 3 years, we show long-term negative reciprocity of those affected but no negative selection effects of new hires.
Parents spend considerable time and resources investing in their children’s development. Given evidence that the Earned Income Tax Credit (EITC) affects maternal labor supply, we investigate how the maximum available EITC amount affects a broad array of time use activities, focusing on the amount and nature of time spent with children. Using 2003–18 time use data, we find that federal and state EITC expansions increase maternal work time, reducing time devoted to home production, leisure, and time with children. However, almost none of the reduction comes from time devoted to “investment” activities, such as active learning and development activities.
This study provides evidence on the relative effectiveness of computer-assisted learning (CAL) software and traditional teaching. Based on a field experiment in Salvadoran primary schools, we evaluate three interventions that aim to improve learning in mathematics: (i) additional teacher-led classes, (ii) additional CAL classes monitored by a supervisor, and (iii) additional CAL classes instructed by a teacher. We find that CAL lessons lead to larger learning gains and are less sensitive to class size as well as student ability than teacher-centered classes. Our results highlight the value of CAL in an environment with heterogeneous classes and poorly qualified teachers.
Empirical peer effects research often employs censored peer data. Individuals may list only a fixed number of links, implying mismeasured peer variables. I first document that censoring is widespread in network data. I then introduce an estimator and characterize its inconsistency analytically; an assumption on the ordering of peers implies that censoring causes attenuated peer effects estimates. Next, I demonstrate the effect of censoring in two data sets, showing that estimates with censored data underestimate peer influence. I discuss interpretation of estimates, propose methods for correction and bounding, and give implications for the design of network surveys.
This paper examines inequalities in the match between student and degree quality using linked administrative data from schools, universities, and tax authorities. We analyze two measures of match at the university subject level: undergraduate enrollment qualifications and graduate earnings. We find for both that disadvantaged students match to lower-quality degrees across the entire distribution of achievement in a setting with uniform fees and a generous financial aid system. While there are negligible gender gaps in academic match, high-attaining women systematically undermatch in terms of expected earnings, driven by subject choice. These inequalities in match are largest among the most undermatched.
Recent work situates gender norms as a key driver of the sexual division of labor. But the explanatory power of Beckerâs comparative advantage explanation is still not well understood. Drawing on unique data, we test the predictions of a formal Beckerian model. We complement this by proposing and analyzing new measures of specialization. We show that comparative advantage plays little or no role in the sexual division of labor within couple households. Absolute advantage also plays no role in specialization for same-sex couples, and this is not explained by having fewer children.
Although from the viewpoint of social psychology task commitment is a driving force for intrinsic motivation in the workplace, this topic has been widely ignored in labor and personnel economics so far. Our paper reduces this gap in the literature by offering a theoretical analysis of worker empowerment and task commitment. This approach also helps to explain the observed variety of compensation schemes across workers and firms. By using a large-scale linked employer-employee panel data set, we present empirical evidence that is consistent with the predicted patterns of our theoretical model.
Little is known about the costs of crime to victims. We use unique and detailed register data on victimizations and monthly labor market outcomes from the Netherlands and estimate event study designs to assess short- and long-term effects of criminal victimization. Across offenses, both males and females experience significant decreases in earnings (up to â12.9%) and increases in benefit receipt (up to +6%) after victimization. The negative labor market responses are lasting (up to 4 years) and accompanied by shorter-lived responses in health expenditure. Heterogeneity results suggest that most groups of victims, including the noninjured, suffer nontrivial losses.
New parenthood causes large decreases in labor market incomes for mothers but not fathers, a stylized fact known as the âchild penalty.â We combine a simple household model with estimates of child penalties in heterosexual nonadopting, adopting, and same-sex couples to better understand what causes the child penalty in heterosexual nonadopting couples. Our results largely rule out giving birth and the fatherâs advantage in the labor market as mechanisms, leaving preferences, gender norms, and discrimination as the main explanations. In addition, our paper provides novel evidence on the impact of children on labor market outcomes of adopting and same-sex couples.
Measuring occupational mobility from the Current Population Survey using retrospective or longitudinal methods generates substantially different outcomes, in both levels and trends. Using a generalized method of moments technique, we estimate the level of occupational mobility and the measurement error in both of these measures for 1981â2018. We estimate that occupational mobility has been trending down, particularly since 2000, consistent with retrospective measures of occupational mobility. However, estimated mobility is 2â3 percentage points or 60%â70% higher than retrospective measures. Measurement error in longitudinal measures is large and has been worsening over time.
During the 1940s, a substantial share of southern Black men moved from low-skilled to much better paying semiskilled jobs. Using newly digitized military data, I show that counties with higher World War II casualty rates among semiskilled White soldiers saw an increase in the share of semiskilled Black workers. These deaths opened new employment opportunities for Black southerners and, together with learning effects by employers, can explain 35% of the occupational upgrading at mid-century. I provide evidence that the casualty-induced labor shortages reduced racial barriers to entry, leading to a positive selection of Black workers into semiskilled employment.
This paper estimates the causal effect of equalizing revenues across school districts on studentsâ intergenerational mobility. I exploit cohort differences in exposure to equalization generated by state-level reforms. To address the endogeneity of postreform revenues due to household sorting after a reform, I use a simulated-instruments approach that uses newly collected data on statesâ funding formulas to simulate revenues without sorting. I find that equalization has a large effect on the mobility of low-income students. Reductions in input gaps between low-income and high-income districts are likely channels behind this effect.
Workfare can impact child development by inducing parents to spend less time at home. I study the mechanisms by which workfare policies affect children using the New Hope workfare experiment. The program randomly assigned individuals to a policy bundle including income and childcare subsidies conditional on full-time work. For families with young children, the program had positive effects on child academic performance and classroom behavior. Counterfactual experiments from a dynamic discrete choice model indicate that most of the effect of New Hope on young children is explained by parents enrolling their children in center-based childcare.
Has the geography of intergenerational mobility in the United States changed over time? Constructing a large historical linked sample, I show that upward mobility in the early twentieth century was greater for those who grew up in the coastal and industrial regions, in contrast to more recent times, where mobility is higher among persons who were raised in the middle of the country. The historical patterns are not driven by imperfections in record linkage or measurement error in economic status.
This paper estimates the effect of minimum wage increases on work that is not covered by minimum wage laws. I find that minimum wage increases in the early 2000s resulted in small reductions in engagement in traditional self-employment. Following the development of the online gig economy in the 2010s, a 10% increase in the minimum wage increased the number of nonemployer establishments classified as transportation and warehousing services by approximately 2.7%. The counties most likely to exhibit a positive relationship between the minimum wage and participation in uncovered work are those with low labor market concentration and active Uber marketplaces.
We propose a model of intergenerational transmission of education wherein children belong to either highly educated or low-educated families. Children choose the intensity of their social activities, while parents decide how much educational effort to exert. Using Add Health data, we find that, on average, childrenâs homophily acts as a complement to the educational effort of highly educated parents but as a substitute for the educational effort of low-educated parents. We also find that policies that subsidize kidsâ socialization efforts can backfire for low-educated students because they tend to increase their interactions with other low-educated students.
From 2002 to 2018, the fraction of minority-segregated public schools in the United States roughly doubled, but the fraction of White-segregated schools decreased at an even faster rate. Endogenous segregation fueled by parents choosing schools on the basis of their racial compositions can in principle dwarf all other determinants of segregation over time because of social multiplier effects. However, we find that demographic change from Hispanic immigration has been the biggest driver of these trends. These findings are particularly pronounced in urban areas, which experienced the largest changes in segregation and are where policy makers are most concerned about the pernicious effects of segregation.
As wages in migrant-sending countries catch up with those in destinations, migrants adjust on several margins, including their duration of stay, the number of migrations they undertake, and the amount saved while abroad. This paper combines Mexican and US data to estimate a dynamic model of consumption, emigration, and remigration, accounting for financial constraints. An increase in Mexican household earnings shortens migration duration but raises the number of trips per migrant. For lower-income migrants, a rise in Mexican wages leads to a more than proportional effect on consumption expenditure in Mexico, arising from repatriated savings.
In the United States, age at first marriage was lowest and the education gap between husbands and wives was highest during the 1950s. The conventional explanation for such a negative correlation is that early marriage leads to earlier and higher fertility, which in turn prevents women from acquiring education. Here, we propose that early marriages enabled couples to overcome credit constraints in education. A model that includes this motive and mechanism can replicate not only the marriage and education patterns observed in the middle of the century in the United States but also the overall trends over the twentieth century.
Many studies use matched employer-employee data to estimate a statistical model of earnings determination with worker and firm fixed effects. Estimates based on this model have produced influential yet controversial conclusions. The objective of this paper is to assess the sensitivity of these conclusions to the biases that arise because of limited mobility of workers across firms. We use employer-employee data from the United States and several European countries while taking advantage of both fixed effects and random effects methods for bias correction. We find that limited mobility bias is severe and that bias correction is important.
We investigate how sizes of professional networks affect the probability of appointment to a supervisory board and whether the effect is gendered. Using an employer-employee data set of the Danish labor market, 1995–2011, we find larger networks to associate with a higher probability of becoming a first-time director. The effect is larger for men. One explanation is that men, compared with women, have more connections to larger and listed firms and to other males—attributes that increase the appointment probability. Women who have connections to incumbent directors before being appointed director have more labor market experience than other directors.
China shifted its controversial one-child policy (1979–2015) to a two-child policy in 2016. We take advantage of this unexpected policy change and the heterogeneities in the prechange environment to investigate labor market discrimination against expected family responsibilities. In a two-wave correspondence study before and after the policy change, we sent 8,848 fictitious resumes with ages 22–29 in response to online job advertisements. Their gender and only-child/siblinged status were systematically varied. We find that women—but not men—are subject to labor market discrimination for expected family responsibilities. This discrimination worsens with the increase in women’s reproductive age.
Increasing mother’s labor supply during a child’s preschool years may reduce time investments, yielding a negative direct effect on midchildhood and teenage outcomes. But as mother’s work hours increase, income will rise. Can income compensate for the negative effect of hours? Our mediation analysis exploits exogenous variation in both mother’s hours and family income. Results suggest a negative, insignificant direct effect from increasing mother’s hours on child test scores. However, the positive mediating effect of income creates a positive total effect on test scores (26% of a standard deviation) for a 10-hour increase in mother’s weekly hours in preschool years.
Using a natural experiment induced by COVID-19, we test how the sudden absence of fans at football games impacts player performance in Italy. We find that African players, who are most commonly targeted by racial harassment, play better when fans are no longer at the stadium. A similar, albeit weaker, effect is detected among black players. Using official records of racist behavior by fans, we show that performance improves the most on teams that were subject to abuse before the lockdown. Our evidence suggests that racist pressure can harm discriminated groups and lower the overall quality of the game.
This paper studies learning among coworkers when incentives change. We use a simple principal-agent model to show that when workers are not fully informed on the global shape of the production function, (1) their effort choice changes over time as information is disclosed and processed and (2) changing incentives can trigger this learning process. We test this prediction using personnel data from an egg production plant in Peru. Exploiting a sudden change in the contract parameters, we find that workers learn from each other over the shape of the production function. This adjustment process is costly for the firm.
We model optimal treatment assignment in programs with a limited number of seats and study how the presence of peer effects impacts the optimal allocation rule. We then use data from a randomized control trial to show evidence that there are large peer effects in the context of job training for disadvantaged adults in the United States. Finally, we combine the model and the empirics to show that the program would have had a much greater impact if the assignment choices had accounted for the peer effects.
Do foreign students affect the likelihood that domestic students obtain a STEM degree and occupation? Using administrative student records from a US university, we exploit idiosyncratic variation in the share of foreign classmates in introductory math classes and find that foreign classmates displace domestic students from STEM majors and occupations. However, displaced students gravitate toward high-earning social science majors, so their expected earnings are not penalized. We explore several mechanisms. Results indicate that displacement is concentrated in classes where foreign classmates possess weak English language ability, suggesting that diminished in-class communication and social interactions might play an important role.
I study the consequences of letter grades serving as coarse measures of academic achievement using university administrative data that record both the letter grade and the precise mark (0–100) received for each course that a given student takes. I exploit a regression discontinuity design with marks as the running variable. I find that receiving a better grade in a single class results in USD 32 greater monthly earnings after graduation, a 1.4% increase. I also find that marginal students who receive a worse grade take significantly easier courses and earn lower grades in future semesters.
We study the effect of hearing cases alongside female judicial colleagues on the probability that a federal judge hires a female law clerk. Federal judges are assigned to judicial panels at random and have few limitations on their choices of clerks. Using a unique dataset of federal case records merged with judicial hiring information, we find a significant effect of the fraction of copanelists who are female on a male judge’s likelihood of hiring a female clerk. This finding suggests that increases in the diversity of the upper rungs of a profession can create opportunities at the entry level.
This paper estimates the causal impacts of workers’ compensation income benefits on workers’ health and welfare outcomes. Using claims data from 2004 to 2016, I explore the variation in benefits due to a reform of New York workers’ compensation that increased the maximum weekly benefits. I find that a $77 increase in the weekly benefits led to an additional 3.4 days off work. Medical utilization did not increase. Each extra day off work decreased the reinjury likelihood by 2.9%. The current benefit level in New York is close to optimal in balancing payer cost and worker health outcomes.
This paper assesses the importance of school and neighborhood peers in shaping educational achievement, adolescent misbehavior, and adult crime. Using cohort variation within Charlotte-Mecklenburg County, we focus on the impact of peers whose parents have been arrested, which is strongly and independently predictive of worse outcomes. Results indicate that a 5 percentage point increase in school peers linked to parental arrest reduces educational achievement by 0.016 standard deviations and increases adult arrest rates by 5%. Additional evidence indicates that peer effects are primarily driven by interactions in schools rather than in neighborhoods.
We estimate the effect of an unexpected institutional financial aid (IFA) award on student outcomes using administrative data collected from nine universities, exploiting variation in IFA schedules within and across university-entry cohorts. Each £1,000 of IFA during the first year of college increases the chances of completing that year by 1.4 percentage points, improves test scores by 0.059 standard deviations, and increases the chances of graduating with a good degree by 3.4 percentage points. We find that high-ability and low-income students benefit the most and calculate outcome-maximizing and cost-minimizing IFA schedules for each university.
Social and emotional learning (SEL) programs that target disruptive students aim to improve their classroom behavior. Small-scale programs in high-income countries have demonstrated positive effects. Using a randomized experiment, we show that a nationwide SEL program in Chile has no effect. Very disruptive students seem to reduce the program’s effectiveness. With attention deficit hyperactivity disorder being more prevalent in middle- than high-income countries, very disruptive students may be more present there, which could diminish the effectiveness of SEL programs. Moreover, implementation fidelity seems lower in this program than in the small-scale ones considered earlier, which could also explain the program’s null effect.
There are two essential mechanisms in the canonical model of the transmission of income across generations—parents’ financial resources and parental education. I provide novel empirical evidence to disentangle the significance of these two mechanisms in explaining the intergenerational transmission of income. Utilizing two reforms and administrative data from Sweden, I find that parents’ financial resources amount to about 25% of the effect of parental education on children’s income. Additionally, I show that parents’ financial resources matter less for sons. Overall, my findings suggest a comparatively modest impact of parental financial resources on children’s income.
Monthly wage inequality in Germany continued to increase in the early 2000s, which is mainly explained by a rising part-time employment share. After 2010, inequality returned to the level of 2000. About half of the recent decrease is due to the introduction of the national minimum wage in 2015. While employment effects of the minimum wage are negligible, we find strong wage increases among the existing workforce. The minimum wage lowered wage inequality within eastern and western Germany but also led to a convergence of the east-west wage differential. The increased labor incomes were not offset by decreasing social benefits.
This study investigates the effects of unobserved earnings-related endowments on marital outcomes, focusing on potential gender differences. Using a less stringent, more plausible assumption that monozygotic twins share more similar endowments relative to dizygotic twins, we develop a novel identification strategy from the twins experiment. Using unique Chinese twins survey data, we find that men with genetic endowments related to higher earnings marry earlier and have younger, taller wives; such women marry later and have older husbands with higher education and income. Results cast doubt on the conventional assumption of independence between unobservables and observable marital attributes.
We study how active labor market policies affect the exchange of information and support among job seekers. Leveraging a unique social network survey in Ethiopia, we find that a randomized job search assistance intervention reduces information sharing and support between treated job seekers and their active job search partners. Because of lower job search support, untreated individuals search less and, suggestively, have worse employment outcomes. These results are consistent with a model of networks where unemployed individuals form job search partnerships to exploit the complementarities of job search.
We investigate the impact on work absences of a large reduction in paid sick leave benefits in Spain. Our results highlight substantial decreases in frequency (number of spells) mostly offset by increases in duration (length of spells). Overall, the policy did reduce the number of days lost to sick leave. For some, however, return to work was premature, as we document large increases in both the proportion of relapses and the number of working accidents. Displacement toward this unaffected benefit scheme cancels out almost two-fifths of the gains in terms of estimated absence reductions from the sick leave benefit cut.
We examine the labor market effects of Secure Communities (SC), a police-based immigration enforcement policy implemented in 2008–13. Using variation in implementation across local areas and over time, we find that SC decreased the employment of likely undocumented immigrants. These effects are driven not only by deportations but also by adjustments among immigrants who remain in the United States. Importantly, SC also decreased the employment and hourly wages of US-born individuals. We provide support for two mechanisms that could explain this decline in labor demand: an increase in labor costs that decreases job creation and a reduction in local consumption.
We provide evidence that short-term shocks to student cognitive performance have long-lasting consequences for human capital development. We use administrative data from Mexico City to show that students’ exposure to violent crime in the week immediately prior to a high-stakes exam lowers females’ test scores by 11% of a standard deviation. As a result, 19% of female students exposed to violent crime are subsequently assigned to less preferred, lower-quality high schools. We find no such effect for males and show that crime-induced concentration problems are an underlying mechanism behind the detrimental effects on females’ test scores.
Workers struggle to understand prospective employers. Through experienced workers’ volunteered reviews, Glassdoor is a platform seeking to provide information about prospective employers to job seekers. We find that the content most valuable to job seekers (negative information) is the kind most risky to supply, pointing to a catch-22. Higher ratings increase job applications to smaller firms only, creating an incentive for them to discourage negative reviews. Concerns about employer retaliation discourage negative reviews and motivate employees who do disclose to conceal aspects of their identity, degrading the information’s value. Reputation institutions provide valuable but partial solutions to workers’ information problems.
We explore how access to Head Start affects maternal labor supply. By relaxing childcare constraints, public preschools like Head Start might lead mothers to reallocate time among employment, childcare, and other activities. Using the 1990s enrollment and funding expansions and the 2002 Head Start Impact Study randomized controlled trial, we show that Head Start increases short-run employment and wage earnings of single mothers without reducing quality parent-child interactions. Even before including long-run benefits to children, the short-run benefit to single mothers and the government is $0.93 per dollar. Head Start is a family-level treatment with impacts beyond children.
We investigate how reforms of Canada’s child allowances affected household poverty and maternal employment—the 2015 increase and expansion of the Universal Child Care Benefit and the 2016 introduction of a new Canada Child Benefit (CCB). We document that both reforms reduced child poverty, although the CCB had greater effect. By 2018, we estimate that the CCB reduced poverty by 11% in families headed by a single mother and by nearly 17% in two-parent families. We find no evidence, on either the extensive or the intensive margin, of a negative labor supply response to either of the program reforms.
There is evidence showing racial bias in firms’ hiring decisions, but less is known about bias in career recognition. We construct a dataset from the second-largest US police department to estimate the Black-white gap in award nominations. Leveraging institutional features, we find that white supervisors are less likely to nominate Black officers conditional on work performance. This appears to be driven by supervisor bias in advocacy decisions rather than statistical discrimination. Given the reliance on subjective evaluations for promotions in many organizations, our findings have important implications for the Black-white promotion gap and the lack of diversity in upper-management positions.
This paper empirically analyzes how universities decide which courses to offer and the implications of these decisions for students. At a sample university, course offerings significantly impact student course choices and implicitly sacrifice student utility to increase enrollment in STEM and business and occupational courses. This is because new course sections in these fields have slightly smaller effects on student utility and cost substantially more than new offerings in other fields. The university changes its course offerings in counterfactual scenarios, and ignoring these responses leads to understating the effects of interventions.
We study the link between firm productivity and the wages that firms pay. Guided by a search-matching model with large firms, worker and firm heterogeneity, and production complementarities, we infer firm productivity by estimating firm-level production functions. Using German data, we find that the most productive firms do not pay the highest wages. Worker transitions from high- to medium-productivity firms are on average associated with wage gains. Productivity sorting—that is, the sorting of high-ability workers into high-productivity firms—is less pronounced than the sorting into high-wage firms.
Economic shocks occur frequently and may cause individuals to reevaluate key life decisions in ways that have lasting consequences for themselves and the broader economy. These decisions are tied to life stages, and the effect of economic shocks may differ depending on when they occur. We exploit exogenous job separations to study the impact of adverse shocks across the life cycle on labor market outcomes and major life decisions: education, mobility, family structure, and retirement. We find significant heterogeneity across the life cycle and conclude that focusing on average effects among workers across the life cycle misses a great deal.
We study how a significant relaxation of internal migration restrictions affects labor market outcomes of incumbent migrants and natives, exploiting the 2014 hukou reform in China, which substantially removed the migration barriers of cities with an urban population below 5 million (nonmegacities). Using a difference-in-differences method, we find that migrants’ wages in nonmegacities experienced approximately a 2.6%–7.9% decline relative to that in megacities after the policy. The policy had nonnegative impacts on the wages of natives in nonmegacities. These results suggest that the downward wage pressure imposed by new migrants falls primarily on incumbent migrants rather than on natives.
We study the relationship among occupational employment, occupational wages, and wage inequality. In all occupations, entrants and leavers earn less than stayers, suggesting negative selection effects for growing occupations and positive effects for shrinking ones. We estimate a model of occupational prices and skills that includes specific skill accumulation and endogenous switching. Contrary to uncorrected wages, prices and employment growth are positively related. Forty percent of selection is due to age, as entrants and leavers have had less time to accumulate skills. The remainder is Roy-type selection. Skill prices establish a quantitative connection of occupational changes with surging wage inequality.
The COVID-19 pandemic resulted in major declines in employment of women. We provide projections of impacts of this reduction on less educated women’s future human capital framed within the traditional Mincerian model. We find that wage losses one year out from 2020 are relatively modest on average, generally less than 1%, with the largest for married women without children in the home. But losses are greater for young married women, mothers with very young children, and those working in COVID-impacted industries. School and childcare closures increase negative wage impacts for married mothers by an additional 50%.
We study the extent to which employer heterogeneity affects gender gaps in earnings across the distribution, over time, and over the life cycle, accounting for cohort effects. Using a linked employer-employee dataset for Italy, we show that the gender gap in firm pay premia explains 34% of the mean gender pay gap, mainly due to between-firm components. Within-firm differences are more important at the top of the distribution and have become more relevant over time. Gender differences in mobility toward firms with higher pay premia and within-firm gender inequality partly explain the gender gap in firm pay premia.
Children exposed to pollutants like lead have lower academic achievement and are more likely to engage in risky behavior. However, little is known about whether lead-exposed children affect the long-run outcomes of their peers. We estimate these spillover effects using unique data on preschool blood lead levels (BLLs) matched to education data for all students in North Carolina public schools. We compare siblings whose school-grade cohorts differ in the proportion of children with elevated BLLs, holding constant school and peers’ demographics. Having more lead-exposed peers is associated with lower high school graduation and SAT-taking rates and increased suspensions and absences.
This paper quantifies the causal negative impact of age on women’s marriage market appeal using an experiment where real online daters rate hypothetical profiles with randomly assigned ages. Truthfulness is incentivized through the experiment’s compensation: participants receive professional dating advice customized according to their ratings. The experiment shows that for every year a woman ages, she must earn $7,000 more annually to remain equally attractive to potential partners. This preference appears driven by women’s asymmetric fertility decline with age, as it is present only for men without children and who have accurate knowledge of the age-fertility trade-off.
The income maintenance experiments have received renewed attention due to growing international interest in a basic income. Proponents of a negative income tax (NIT) viewed it as a replacement for traditional welfare with stronger work incentives. However, existing labor supply estimates for single mothers (those eligible for welfare) are uniformly negative. We reassess the experimental evidence and find randomization failure in two NITs (Gary and Seattle). In Denver and Manitoba, we find positive labor supply responses for those on welfare before random assignment. Our results provide strong evidence that an NIT can increase work activity among single mothers on welfare.
This paper offers the first study of how changes in corporate R&D investment affect labor mobility. We show that increases in R&D spur employee departures to join start-ups’ founding teams. This appears to reflect employees taking the ideas, skills, or technologies created through the R&D process but not especially valuable to the R&D-investing firm to start-ups. The employee-founded start-ups tend to be outside the R&D-investing employer’s industry, suggesting that the underlying ideas would impose diversification costs on the R&D-investing firm. The start-ups are more likely to be VC backed, high tech, and high wage, pointing to substantial spillover benefits.
There is substantial variation in working time even within employer-employee matches, yet estimates of the Frisch elasticity of labor supply can be near zero. This paper proposes a tractable theory of earnings and working time to interpret these observations. Production complementarities attenuate the response of working time to idiosyncratic, or worker-specific, shocks, but firm-wide shocks are mediated by preference parameters. The model can be identified using firm-worker matched data, revealing a Frisch elasticity of around 0.5. A quasi-experimental approach that exploits only idiosyncratic variation would find an elasticity less than half this.
I study the long-term effects of landing a first job at a large firm versus a small one using Spanish administrative data. Size could be a relevant employer attribute for inexperienced workers since large firms are associated with greater productivity, wages, and training. The key empirical challenge is selection into first jobs based on unobserved worker characteristics. I develop an instrumental variable approach that, keeping business cycle conditions fixed, leverages variation in the composition of labor demand that labor market entrants face. Initially matching with a larger firm persistently improves long-term outcomes, even through subsequent jobs. Mechanisms suggest better skill development at large firms.
This paper studies the relationship between industrial robots and employment in Japan on the basis of a unique dataset that allows us to calculate the unit price of robots. Our model combines standard factor demand theory with a recent task-based approach to derive a simple estimation equation between robot prices and employment, and our identification strategy leverages heterogeneous applications of robots across industries and heterogeneous price changes across applications. We find that the decline in robot prices increased both the number of robots and employment by raising the productivity and production scale of robot-adopting industries.
Many countries impose job search requirements on unemployment benefit recipients. Existing studies have mainly focused on the impact of incremental changes to requirements on the recipients. Australian reforms in 1995 saw groups of partnered welfare recipients newly subjected to job search requirements, allowing us to produce causal estimates of the effects on family welfare receipt of introducing such requirements. Using a quasi-experimental design and administrative data, we find large negative effects on welfare receipt for the mature-age partnered women targeted by the reforms and similar effects on welfare receipt of their partners, suggesting that family labor supply decisions were considerably affected.
We identify the labor market returns to university grade point average (GPA) by leveraging a nationwide change in the scaling of grades in Danish universities. Our results show that a reform-induced increase in GPA that is unrelated to ability causes higher earnings immediately after graduation, but the effect fades in subsequent years. The effect at labor market entry is largest for individuals with fewer alternative signals. Although employers initially screen candidates on the basis of skill signals, our findings are consistent with a model in which employers rapidly learn about worker productivity.
The evolution of rent sharing is studied. Based on a panel of the top 300 publicly quoted British companies over 35 years and using excess stock market returns to patenting activity as an instrument for economic rents, the paper reports evidence of a significant fall over time in the pass-through from rents to wages. It confirms that wages do respond to firm-level shocks to economic rents, but by significantly less after 2000 than during the 1980s and 1990s. The evidence of decline is robust, corroborated with alternative instruments and industry-level analysis for the United States and the European Union.
We estimate the longer-run effects of attending an effective high school (one that improves a combination of test scores, survey measures of socioemotional development, and behaviors in ninth grade) for students who are more versus less educationally advantaged. All students benefit from attending effective schools, but the least advantaged students experience larger improvements in high school graduation, college going, and school-based arrests. Test score value-added understates the long-run importance of effective schools, particularly for less advantaged populations. Patterns suggest that this may, in part, reflect less advantaged students being relatively more responsive to non-test-score dimensions of school quality.
We show that score inflation yields residential sorting around what households expect to be better schools, with long-term consequences for the economic geography of neighborhoods. We consider primary school exams in England, where grading standards have triggered an inflation of indicators in the national performance tables since the mid-1990s. Local neighborhoods were gentrified because of school improvements artificially signaled by score inflation. Competition between schools increased, yielding a real improvement in their quality. Effects of score inflation on house prices, deprivation, and local economic activities are identifiable through to the present day.
This paper studies the speed at which workers’ pretax earnings respond to tax changes along the intensive margin. We do so in the context of Germany, where a large notch in the tax schedule induces sharp bunching in the earnings distribution. We analyze earnings responses to two policy reforms that shift this notch outward and find clear evidence that frictions delay the earnings responses of more than 38% of workers. We propose that heterogeneity in firm labor demand plays a key role in generating the observed differences in the speed of workers’ earnings responses and provide supporting evidence.
We analyze how skill transferability and the local industry mix affect the adjustment costs of workers hit by a trade shock. Using German administrative data and novel measures of economic distance, we construct an index of labor market absorptiveness that captures the degree to which workers from a particular industry are able to reallocate into other jobs. Among manufacturing workers, we find that the earnings loss associated with increased import exposure is much higher for those who live in the least absorptive regions. We conclude that the local industry composition plays an important role in the adjustment processes of workers.
We document that the US marriage market is characterized by two systematic empirical patterns. First, there is a quantitatively large, strong, and persistent negative relationship between changes in cohort size and marriage rates of women. Second, the same negative correlation holds for men. We then establish the features a model should possess to generate these patterns. A standard matching model with search frictions is rejected by the data because it produces a negative relationship for women but a positive relationship for men. We generalize the standard model to show under what conditions it rationalizes both patterns.
Tournaments are often used to improve performance in innovation contexts. Tournaments provide monetary incentives but also render teams’ identity and image concerns salient. We study the effects of tournaments on team performance in a nonroutine task and identify the importance of these behavioral aspects. In a field experiment (n>1,700 participants), we vary the salience of team identity, social image concerns, and whether teams face monetary incentives. Increased salience of team identity does not improve performance. Social image motivates the top performers. Additional monetary incentives improve all teams’ outcomes without crowding out teams’ willingness to explore or perform similar tasks again.
How much can employers in low- and middle-income countries suppress wages below marginal productivity? Using plant and customs data from Colombia, we exploit predetermined variation across plants in sales export destinations combined with variation in exchange rates to generate plant-specific shocks to marginal revenue productivity and labor demand. We estimate a firm-level labor supply elasticity of around 2.5, implying that workers produce about 40% more than their wage level. This result is driven by plants that account for a large share of local employment, consistent with an oligopsonistic labor market model.
We introduce new measurement tools to understand the sources of earnings differences across space. Based on the natural language employers use in job ads, we develop granular measures of job tasks and of worker specialization. We find that jobs in larger commuting zones involve greater interpersonal interactions and have higher computer software requirements. Between 10% and 50% of task and technology variation between large and small commuting zones exists within occupations. Furthermore, workers in larger markets are more specialized. Tasks, technologies, and worker specialization account for a substantial portion of the market size premium even within occupations.
This paper asks whether reducing the informativeness of college admission exams reduces inequality in postcollege earnings. I examine a 2000 reform of the Colombian college admission exam that sought to reduce bias in scores. The reform reduced test score gaps between high- and low-income students by nearly 50% in some subjects, but it also decreased the exam’s predictive power for abilities that matter in college. I find that the reform caused students to attend colleges where they were more likely to drop out, which reduced earnings for both high- and low-income students.
Inequality in access to high-quality teachers is an important driver of socioeconomic student achievement gaps. We experimentally evaluate a novel nationwide low-cost government program that deployed two behavioral strategies to motivate teachers to apply to job vacancies in disadvantaged schools. These strategies consisted of an “altruistic identity” treatment, which primed teachers’ altruistic identity by making it more salient, and an “extrinsic incentives” treatment, which simplified the presentation and increased the salience of an existing government monetary incentive scheme that rewards teachers who work in underprivileged institutions. Both strategies successfully encouraged teaching candidates to apply to disadvantaged schools.
Using Michigan Panel Study of Income Dynamics data, we study selection bias and the gender wage gap. Employing several methods, we find large declines in the total and unexplained gender gaps in wage offers between 1981 and 2015. Under our preferred selection correction method, the median total and unexplained gaps fell by 0.378 and 0.204 log points, respectively. These are larger declines than if we had not corrected for selection and simply measured convergence in observed wage gaps. However, substantial selectivity-corrected median gender wage gaps remain in 2015: 0.242 log points (total gap) and 0.206 log points (unexplained gap).
We estimate the effect of a female employee giving birth and taking parental leave on small firms and coworkers in Denmark using a dynamic difference-in-differences design. We find little evidence that parental leave take-up has negative effects on firms and coworkers overall. This is because most firms are very effective in compensating for the worker on leave by hiring temporary workers and by increasing other employees’ hours. In contrast, we do find evidence that parental leave has negative effects on a small subsample of firms that are less able to use their existing employees to compensate for absent workers.
Using data on applied-for jobs for the universe of Danish unemployment insurance recipients, we examine variation in job search behavior both across individuals and over time during unemployment spells. We find large differences in the level of applied-for wages across individuals, but over time all individuals adjust wages downward in the same way. The decline in applied-for wages over time is descriptively small but economically important in standard models of job search. We find similar results when examining variation in the nonwage characteristics of applied-for jobs and in the search methods used to find them. We discuss implications for theory.
We use the medical specialties of physician-patients with advanced cancer to study the role of knowledge versus networks in treatment choices and patient survival by matching comparable patients with doctors and admission periods to control unobserved doctor quality. Physician-patients are less likely to have surgery, radiation, or checkups and more likely to receive targeted therapy, spend more on drugs, enjoy a higher survival rate, and spend less on coinsurance than nonphysician-patients. Knowledge mechanisms play a crucial role because the network effect explains some, but not all, patterns. For less informed physician-patients, possessing a network is equivalent to reducing medical knowledge.
We exploit the natural experiment provided by the Vietnam lottery draft to evaluate the intergenerational effects of fathers’ draft eligibility on children’s propensity to engage in risky behaviors during adolescence using the National Longitudinal Survey of Youth 1997. Draft eligibility increases measures of substance use, increases intensity of use, decreases age of initiation—particularly for marijuana—and increases measures of delinquency. We also show that draft eligibility led to changes in parenting that are conducive to these risky behaviors among children: it affects paternal parenting styles and attitudes toward the respondent, environmental aspects, and even maternal factors. Results are robust to alternative specifications and falsification diagnostics.
We analyze an immigration reform in Denmark that tightened refugee immigrants’ eligibility criteria for permanent residency to incentivize their labor market attachment and acquisition of local language skills. Contrary to what the reform intended, the overall employment of those affected decreased, while their average language proficiency remained largely unchanged. This was caused by a disincentive effect, where individuals with low prereform labor market performance reduced their labor supply. Our findings suggest that stricter permanent residency rules, rather than incentivizing refugees’ skill investment, may decrease the efforts of those who believe they cannot meet the new requirements.
We document a causal relationship between business uncertainty and workforce management at the firm level by leveraging litigation-generated quasi-experimental variation in business uncertainty. The causal effects of business uncertainty on turnover, hiring, and separations are of the expected negative direction and of sizable magnitude. These consequences are stronger among firms that operate in sectors in which business uncertainty is intrinsically higher and can be attributed to the effect of regulation-induced business risk on normal operations. In particular, employee turnover, hiring, and separations are ratcheted down to reduce the risk of additional wrongful termination lawsuits.
This paper explores whether a 1990 reform that eliminated gender-segregated and gender normative industrial arts and home economics classes in Japanese junior high schools led to behavioral changes two decades later, when students were married and in their early 40s. Using a regression discontinuity design and Japanese time use data from 2016, we find that the reform narrowed gender gaps in weekend home production and job-related activities by increasing (decreasing) men’s engagement in traditionally female (male) activities, reduced the gender income gap by increasing women’s access to better jobs, delayed men’s fertility, and relaxed women’s attitudes toward traditional gender roles.
We examine the effects of an affirmative action policy at an elite Brazilian university that reserved 45% of admission slots for Black and low-income students. We find that marginally admitted students who enrolled through the affirmative action tracks experienced a 14% increase in early-career earnings. But the adoption of affirmative action also caused a large decrease in earnings for the university’s most highly ranked students. We present evidence that the negative spillover effects on highly ranked students’ earnings were driven by both a reduction in human capital accumulation and a decline in the value of networking.
We study the impact of classroom rank on children’s learning using a unique experiment from Ecuador. Within each school, students were randomly assigned to classrooms in every grade between kindergarten and sixth grade. Students with the same ability can have different classroom ranks because of the (random) peer composition of their classroom. Children with higher beginning-of-grade classroom rank have significantly higher test scores at the end of that grade. The impact of classroom rank is larger for younger children and grows over time. Higher classroom rank also improves executive function, child happiness, and teacher perceptions of student ability.
I investigate high school tracking policies using a dynamic discrete choice model of study programs and unobserved effort. I estimate the model using data from Flanders (Belgium) and perform an ex ante evaluation of a policy that encourages underperforming students to switch to less academically oriented programs. This reduces grade retention by a third and dropout by 11%. Although it decreases college enrollment, the decrease in college graduation is small and insignificant. I also show that modeling effort is important; otherwise, smaller decreases in grade retention and dropout and larger decreases in college enrollment and graduation would be predicted.
This paper analyzes whether technological change improves equality of labor market opportunities by increasing the returns to skills relative to the returns to parental background. We find that in Germany during the 1990s, the introduction of computer technologies improved the access to technology-adopting occupations for workers with low-educated parents and reduced their wage penalty within these occupations. We also show that this significantly contributed to a decline in the overall wage penalty experienced by workers from disadvantaged parental backgrounds over this time period. Competing mechanisms, such as skill-specific labor supply shocks and skill upgrading, do not explain these findings.
Severe gender imbalances coupled with stark income differences across countries are driving an increase in cross-border marriages in many Asian countries. I theoretically and empirically study who marries whom and how couples allocate marital surplus in Taiwanese and Vietnamese marriage markets. I find that Taiwanese men are selected from the middle level of the human capital distribution and that Vietnamese women are positively selected for cross-border marriages. I show that changes in the costs of cross-border marriage affect the welfare of Taiwanese and Vietnamese who do not participate in cross-border marriages by altering marriage rates, matching partners, and intrahousehold allocations.
This paper estimates a dynamic life cycle model to study the long-term impacts of housing vouchers on employment and examine how policy reforms affect labor supply and well-being. I show that the current program decreases female employment by 17% and male employment by 7%. Compared with the current program, a proposed reform that provides every recipient with a flat-rate subsidy increases female employment by 4% and leads to higher welfare. Policies that offer a lower subsidy to a larger population decrease employment by 3%–4% and increase welfare. Time-limited subsidies increase female employment by 4% and improve overall welfare.
Economists analyzing a well-conducted randomized controlled trial or natural experiment and finding a statistically significant effect conclude that the null of no effect is unlikely to be true. But how frequently is this conclusion warranted? The answer depends on the proportion of tested nulls that are true and the test's power. I model the distribution of t-statistics in leading economics journals. Using my preferred model, 65% of narrowly rejected null hypotheses and 41% of all rejected null hypotheses with |t|<10 are likely to be false rejections. For the null to have only a .05 probability of being true requires a t of 5.48.
How much of the foreclosure crisis can be explained by the large number of high-leverage mortgages originated during the housing boom? In our model, heterogeneous households select from mortgages with different down payments and choose whether to default given income and housing shocks. The use of low–down payment loans is initially limited by payment-to-income requirements but becomes unrestricted during the boom. The model approximates key housing and mortgage market facts before and after the crisis. A counterfactual experiment suggests that the increased number of high-leverage loans originated prior to the crisis can explain over 60 percent of the rise in foreclosure rates.
We present a theory and experimental evidence on pricing and portfolio choices under asymmetric reasoning. We show that under asymmetric reasoning, prices do not reflect all (types of) reasoning. Some agents who observe prices that cannot be reconciled with their reasoning switch from perceiving the environment as risky to perceiving it as ambiguous. If they are ambiguity-averse, these agents become price-insensitive. Results from an experiment show that, consistent with the theory, (i) without aggregate risk, mispricing decreases as the fraction of price-sensitive agents increases; and (ii) with aggregate risk, price-insensitive agents trade to more balanced portfolios.
Analyzing the savings behavior of a large sample of identical and fraternal twins, we find that genetic differences explain about 33 percent of the variation in savings propensities across individuals. Individuals are born with a persistent genetic predisposition to a specific savings behavior. Parenting contributes to the variation in savings rates among younger individuals, but its effect decays over time. The environment when growing up (e.g., parents’ wealth) moderates genetic effects. Finally, savings behavior is genetically correlated with income growth, smoking, and obesity, suggesting that the genetic component of savings behavior reflects genetic variation in time preferences or self-control.
We consider whether hospitals that receive higher payments from Medicare improve patient outcomes, using exogenous variation in ambulance company assignment among patients who live near one another. Using Medicare data from 2002–10 on assignment across ambulance companies and New York State data from 2000–6 on assignment across area boundaries, we find that patients who are brought to higher-cost hospitals achieve better outcomes. Our estimates imply that a one standard deviation increase in Medicare reimbursement leads to a 4 percentage point (or 10 percent) reduction in mortality; the implied cost per at least 1 year of life saved is approximately $80,000.
We model demand for noninstrumental information, drawing on the idea that people derive entertainment utility from suspense and surprise. A period has more suspense if the variance of the next period’s beliefs is greater. A period has more surprise if the current belief is further from the last period’s belief. Under these definitions, we analyze the optimal way to reveal information over time so as to maximize expected suspense or surprise experienced by a Bayesian audience. We apply our results to the design of mystery novels, political primaries, casinos, game shows, auctions, and sports.
We derive a formula to determine the degree to which a school choice program may harm public school stayers by luring the best students to other schools. The “cream skimming” effect is increasing in the degree of heterogeneity within schools, the school choice take-up rate of strong students relative to weak students, and the dependence of school outcomes on student body quality. We use the formula to investigate the cream skimming effect of hypothetical voucher programs on the high school graduation rate and other outcomes of the students who would remain in public school. We find small effects across a wide variety of model specifications and types of modest voucher programs.
This paper evaluates the impact of three different performance incentive schemes using data from a social experiment that randomized 88 Mexican high schools with over 40,000 students into three treatment groups and a control group. Treatment 1 provides individual incentives for performance on curriculum-based mathematics tests to students only, treatment 2 to teachers only, and treatment 3 gives both individual and group incentives to students, teachers, and school administrators. Program impact estimates reveal the largest average effects for treatment 3, smaller impacts for treatment 1, and no impact for treatment 2.
We study a change in maternity leave entitlements in Norway. Mothers giving birth before July 1, 1977, were eligible for 12 weeks of unpaid leave, while those giving birth after that date were entitled to 4 months of paid leave and 12 months of unpaid leave. The increased time spent with the child led to a 2 percentage point decline in high school dropout rates and a 5 percent increase in wages at age 30. These effects were larger for the children of mothers who, in the absence of the reform, would have taken very low levels of unpaid leave.
The literature on treatment effects focuses on gross benefits from program participation. We extend this literature by developing conditions under which it is possible to identify parameters measuring the cost and net surplus from program participation. Using the generalized Roy model, we nonparametrically identify the cost, benefit, and net surplus of selection into treatment without requiring the analyst to have direct information on costs. We apply our methodology to estimate the gross benefit and net surplus of attending college.
This paper provides a systematic analysis of identification in linear social interactions models. This is a theoretical and econometric exercise as the analysis is linked to a rigorously delineated model of interdependent decisions. We develop an incomplete information game for individual choice under social influences that nests standard models as special cases. We consider identification of both endogenous and contextual social effects under alternative assumptions regarding an analyst’s a priori knowledge of social structure or access to individual-level or aggregate data. Finally, we discuss potential ramifications for identification of endogenous formation of social structure.
This study investigates the antipoverty efficacy of minimum wage policies. Proponents of these policies contend that employment impacts are negligible and suggest that consumers pay for higher labor costs through imperceptible increases in goods prices. Adopting this empirical scenario, the analysis demonstrates that an increase in the national minimum wage produces a value-added tax effect on consumer prices that is more regressive than a typical state sales tax and allocates benefits as higher earnings nearly evenly across the income distribution. These income-transfer outcomes sharply contradict portraying an increase in the minimum wage as an antipoverty initiative.
This study investigates the antipoverty efficacy of minimum wage policies. Proponents of these policies contend that employment impacts are negligible and suggest that consumers pay for higher labor costs through imperceptible increases in goods prices. Adopting this empirical scenario, the analysis demonstrates that an increase in the national minimum wage produces a value-added tax effect on consumer prices that is more regressive than a typical state sales tax and allocates benefits as higher earnings nearly evenly across the income distribution. These income-transfer outcomes sharply contradict portraying an increase in the minimum wage as an antipoverty initiative.
A major policy issue in standard setting is that patents that are ex ante not that important, by being included into a standard, may become standard-essential patents. In an attempt to curb the monopoly power that they create, most standard-setting organizations require the owners of patents covered by the standard to make a loose commitment to grant licenses on reasonable terms. Such commitments unsurprisingly are conducive to litigation. This paper builds a framework for the analysis of these patents, identifies several types of inefficiencies attached to the lack of price commitments, and shows how structured price commitments restore competition and why such commitments may not arise spontaneously in the marketplace.
We consider infinite-horizon economies populated by a continuum of agents subject to idiosyncratic shocks. This framework contains models of saving and capital accumulation with incomplete markets in the spirit of works by Bewley, Aiyagari, and Huggett; models of entry, exit, and industry dynamics in the spirit of Hopenhayn’s work; and dynamic models of occupational choice and search models as special cases. Robust and easy-to-apply comparative statics results are established with respect to exogenous parameters as well as various kinds of changes in the Markov processes governing the law of motion of the idiosyncratic shocks.
We use Spain’s Equality Law to test for the existence of agency problems between party leaders and their constituents. The law mandates a 40 percent female quota on electoral lists in towns with populations above 5,000. Using pre- and postquota data by party and municipality, we implement a triple-difference design. We find that female quotas resulted in slightly better electoral results for the parties that were most affected by the quota. Our evidence shows that party leaders were not maximizing electoral results prior to the quota, suggesting the existence of agency problems that hinder female representation in political institutions.
We study the implications of preference heterogeneity for asset pricing. We use recursive preferences in order to separate heterogeneity in risk aversion from heterogeneity in the intertemporal elasticity of substitution and an overlapping-generations framework to obtain a nondegenerate stationary equilibrium. We solve the model explicitly up to the solutions of ordinary differential equations and highlight the effects of overlapping generations and each dimension of preference heterogeneity on the market price of risk, interest rates, and the volatility of stock returns. We find that separating intertemporal elasticity of substitution and risk aversion heterogeneity can have a substantive impact on the model’s (qualitative and quantitative) ability to address some key asset-pricing issues.
Emission regulations become more prevalent in developing countries, but they may be compromised by corruption. This paper documents the prevalence of corruption and the effectiveness of vehicle emission regulations in Mexico City. I develop a statistical test for identifying a specific type of cheating that involves bribing center technicians. I also estimate a structural model of car owner retesting and cheating decisions. Results suggest that 9.6 percent of car owners paid US$20 to circumvent the regulation. Eliminating cheating and increasing the cost of retests would reduce emissions by 3,708 tons at a high cost for vehicle owners.
Leading equilibrium concepts require agents’ beliefs to coincide with the model’s true probabilities and thus be free of systematic errors. This implicitly assumes a criterion that tests beliefs against the observed outcomes generated by the model. We formalize this requirement in stationary environments. We show that there is a tension between requiring that beliefs can be tested against systematic errors and allowing agents to disagree or be uncertain about the long-run fundamentals. We discuss the application of our analysis to asset pricing, Markov perfect equilibria, and dynamic games.
We study the internal organization of French manufacturing firms. We divide the employees of each firm into “layers” using occupational categories. Layers are hierarchical in that the typical worker in a higher layer earns more, and the typical firm occupies less of them. The probability of adding/dropping a layer is positively/negatively correlated with value added. Reorganization, through changes in layers, is essential to understanding how firms grow. Firms that expand substantially add layers and pay lower average wages in all preexisting layers. In contrast, firms that expand little and do not reorganize pay higher average wages in all preexisting layers.
This paper theoretically and empirically analyzes the financing terms that support international trade. The choice of trade finance terms balances the risk that an importer defaults on an exporter and the possibility that an exporter does not deliver goods as specified. Analysis of transaction-level data from a US exporter reveals that importers located in countries with weak enforcement of contracts typically finance transactions, but these firms are able to overcome the constraints of such environments if they can establish a relationship with the exporter. Furthermore, the manner in which trade is financed shapes the impact of crises.
We study the effects of a contraction in financial intermediation on nonfinancial firms. The Panic of 1907 originated in the shadow banks of the time, New York’s trust companies. The runs were caused by a shock unrelated to the trust companies’ nonfinancial corporate clients. In the years following the panic, corporations affiliated with the worst-affected trusts made fewer capital investments, paid lower dividends, and suffered lower profitability and higher borrowing costs relative to firms without such connections. The shock to New York’s trust companies accounted for at least 18.4 percent of the decline in corporate investment in the United States in 1908.
I study the role of social security in providing insurance when there is adverse selection in the annuity market. I calculate welfare gain from mandatory annuitization in the social security system relative to a laissez-faire benchmark, using a model in which individuals have private information about their mortality. I estimate large heterogeneity in mortality using the Health and Retirement Study. Despite that, I find small welfare gain from mandatory annuitization. Social security has a large effect on annuity prices because it crowds out demand by high-mortality individuals. Welfare gain would have been significantly larger in the absence of this effect.
I study the role of social security in providing insurance when there is adverse selection in the annuity market. I calculate welfare gain from mandatory annuitization in the social security system relative to a laissez-faire benchmark, using a model in which individuals have private information about their mortality. I estimate large heterogeneity in mortality using the Health and Retirement Study. Despite that, I find small welfare gain from mandatory annuitization. Social security has a large effect on annuity prices because it crowds out demand by high-mortality individuals. Welfare gain would have been significantly larger in the absence of this effect.
Using survey data from the Promise Academy in the Harlem Children’s Zone, we estimate the effects of high-performing charter schools on human capital, risky behaviors, and health outcomes. Six years after the random admissions lottery, youths offered admission to the Promise Academy middle school score 0.279 (0.073) standard deviations higher on academic achievement outcomes, 0.067 (0.076) standard deviations higher on an index of academic attainment, and 0.313 (0.091) standard deviations higher on a measure of on-time benchmarks. Females are 10.1 percentage points less likely to be pregnant as teenagers, and males are 4.4 percentage points less likely to be incarcerated.
We provide a general framework for the analysis of institutional dynamics in an environment in which payoffs and political powers change stochastically. Assuming that economic and political institutions as well as individual types can be ordered, and preferences and the distribution of political power satisfy natural “single-crossing” (increasing differences) conditions, we prove existence of a pure-strategy Markov voting equilibrium, provide conditions for its uniqueness, and present a number of comparative static results. We then use this framework to study the dynamics of political rights and repression in the presence of threats from extremist groups and the dynamics of collective experimentation.
We provide a model of conflict and mass killing decisions to identify the key variables and situations that make mass killings more likely to occur. We predict that mass killings are most likely in countries with large amounts of natural resource rents, polarization, institutional constraints regarding rent sharing, and low productivity of labor. The role of resources such as oil, gas, and diamonds and other key determinants of mass killings is confirmed by our empirical results based on country-level as well as ethnic group–level analysis.
How do entrepreneurs vary firm size, capital structure, and default to manage risk? We show that more risk-averse entrepreneurs run smaller, more highly leveraged firms and default less, because running a smaller firm with higher debt reduces personal funds at risk in the firm. Optimal default depends on ex ante debt, consumption forgone from firm liquidation, and owner capacity to inject funds. We show that entrepreneurs sacrifice current consumption in the hope of future success that never materializes for the bottom 25 percent, but entrepreneurship is a path toward great wealth and high consumption for the top quartile.
We provide evidence suggesting that the cross-sectional distributions of US consumption and its growth rate obey the power law in both the upper and lower tails, with exponents approximately equal to four. Consequently, high-order moments are unlikely to exist, and the generalized method of moments estimation of Euler equations that employs cross-sectional moments may be inconsistent. Through bootstrap studies, we find that the power law appears to generate spurious nonrejection of heterogeneous-agent asset pricing models in explaining the equity premium. Dividing households into age groups, we propose an estimation approach that appears less susceptible to fat tail issues.
The benefits of endowment destruction documented by Ljungqvist and Uhlig (2015), and the related possibility that consumption can lower habits, are fragile. Both issues result from a particular way of discretely approximating the underlying continuous-time model or of adapting it to jumps. Other ways of calculating the discrete-time approximation or extending the model to jumps easily overturn the results, while making no difference to the model's description of asset prices and quantities. This analysis gives an example of how to extend models so that the jump gives the same result as a jump limit of continuous-sample-path movements.
Self-control problems change the logic of agency theory by partly aligning the interests of the firm and worker: both now value contracts that elicit future effort. Findings from a year-long field experiment with full-time data entry workers support this idea. First, workers increase output by voluntarily choosing dominated contracts (which penalize low output but give no additional rewards for high output). Second, effort increases closer to (randomly assigned) paydays. Third, the contract and payday effects are strongly correlated within workers, and this correlation grows with experience. We suggest that workplace features such as high-powered incentives or effort monitoring may provide self-control benefits.
Evidence showing that individual behavior often deviates from the classical principle of preference maximization has raised at least two important questions: (1) How serious are the deviations? (2) What is the best way to analyze choice behavior in order to extract information for the purpose of welfare analysis? This paper addresses these questions by proposing a new way to identify the preference relation that is closest, in terms of welfare loss, to the revealed choice.
To fight evasion, many developing countries use production-inefficient tax policies. This includes minimum tax schemes whereby firms are taxed on either profits or turnover, depending on which tax liability is larger. Such schemes create nonstandard kink points, which allow for eliciting evasion responses to switches between profit and turnover taxes using a bunching approach. Using administrative data on corporations in Pakistan, we estimate that turnover taxes reduce evasion by up to 60–70 percent of corporate income. Incorporating this in a calibrated optimal tax model, we find that switching from profit to turnover taxation increases revenue by 74 percent without reducing aggregate profits.
This paper studies how private information is incorporated into prices, using a unique setting from the eighteenth century that is closer to stylized models of price discovery than modern-day markets. Specifically, the paper looks at English securities traded in both London and Amsterdam. Private information reached Amsterdam through sailing boats that sailed only twice a week and in adverse weather could not sail at all. Results are consistent with a Kyle model in which informed agents trade strategically. Most importantly, the speed of information revelation in Amsterdam depended on the expected time until the private signal would become public.
We derive a tractable nonlinear earnings function that we estimate separately                      individual by individual using NLSY79 data. We obtain three ability measures, a                      rate of skill depreciation, a time discount rate, and a population-wide estimate                      of the human capital rental rate. We utilize these parameters to verify a number                      of heretofore untested theorems based on the life cycle model. We show how these                      human capital production function parameters relate to cognitive ability,                      personality traits, and family background. Finally, we show that accounting for                      individual-specific heterogeneity dramatically reduces estimates of                      population-wide persistence of permanent and transitory shocks by over 50                      percent.
Recent models of reference-dependent preferences indicate that expectations may play a prominent role in the presence of behavioral anomalies. A subset of such expectations-based models predicts an “endowment effect for risk”: that risk attitudes differ when reference points change from certain to stochastic. In two purposefully simple risk preference experiments, eliminating often-discussed confounds, I demonstrate both between and within subjects such an endowment effect for risk. These results provide needed separation between expectations-based reference-dependent models, allow for evaluation of recent theoretical extensions, and may help to close a long-standing debate in decision science on inconsistency between utility elicitation methodologies.
Can directed technical change be used to combat climate change? We construct new firm-level panel data on auto industry innovation distinguishing between “dirty” (internal combustion engine) and “clean” (e.g., electric, hybrid, and hydrogen) patents across 80 countries over several decades. We show that firms tend to innovate more in clean (and less in dirty) technologies when they face higher tax-inclusive fuel prices. Furthermore, there is path dependence in the type of innovation (clean/dirty) both from aggregate spillovers and from the firm’s own innovation history. We simulate the increases in carbon taxes needed to allow clean technologies to overtake dirty technologies.
We develop an endogenous growth model in which clean and dirty technologies compete in production. Research can be directed to either technology. If dirty technologies are more advanced, the transition to clean technology can be difficult. Carbon taxes and research subsidies may encourage production and innovation in clean technologies, though the transition will typically be slow. We estimate the model using microdata from the US energy sector. We then characterize the optimal policy path that heavily relies on both subsidies and taxes. Finally, we evaluate various alternative policies. Relying only on carbon taxes or delaying intervention has significant welfare costs.
This paper examines the temperature-mortality relationship over the course of the twentieth-century United States both for its own interest and to identify potentially useful adaptations for coming decades. There are three primary findings. First, the mortality impact of days with mean temperature exceeding 80°F declined by 75 percent. Almost the entire decline occurred after 1960. Second, the diffusion of residential air conditioning explains essentially the entire decline in hot day–related fatalities. Third, using Dubin and McFadden’s discrete-continuous model, the present value of US consumer surplus from the introduction of residential air conditioning is estimated to be $85–$185 billion (2012 dollars).
We analyze participation in international environmental agreements in a dynamic game in which countries pollute and invest in green technologies. If complete contracts are feasible, participants eliminate the holdup problem associated with their investments; however, most countries prefer to free ride rather than participate. If investments are noncontractible, countries face a holdup problem every time they negotiate; but the free-rider problem can be mitigated and significant participation is feasible. Participation becomes attractive because only large coalitions commit to long-term agreements that circumvent the holdup problem. Under well-specified conditions even the first-best outcome is possible when the contract is incomplete.
A large agronomic literature models the implications of climate change for a variety of crops and locations around the world. The goal of the present paper is to quantify the macro-level consequences of these micro-level shocks. Using an extremely rich micro-level data set that contains information about the productivity—both before and after climate change—of each of 10 crops for each of 1.7 million fields covering the surface of the earth, we find that the impact of climate change on these agricultural markets would amount to a 0.26 percent reduction in global GDP when trade and production patterns are allowed to adjust. Since the value of output in our 10 crops is equal to 1.8 percent of world GDP, this corresponds to about one-sixth of total crop value.
We assess the static and dynamic implications of alternative market-based policies limiting greenhouse gas emissions in the US cement industry. Our results highlight two countervailing market distortions. First, emissions regulation exacerbates distortions associated with the exercise of market power in the domestic cement market. Second, emissions “leakage” in trade-exposed markets offsets domestic emissions reductions. Taken together, these forces can result in social welfare losses under policy regimes that fully internalize the emissions externality. Market-based policies that incorporate design features to mitigate the exercise of market power and emissions leakage deliver welfare gains when damages from carbon emissions are high.
To analyze the impact of labor market competition on the structure of compensation, we embed multitasking and screening within a Hotelling framework. Competition for talent leads to an escalation of performance pay, shifting effort away from long-term investments, risk management, and cooperation. Efficiency losses can exceed those from a single principal, who dulls incentives to extract rents. As competition intensifies, monopsonistic underincentivization of low-skill agents first decreases and then gives way to growing overincentivization of high-skill ones. Aggregate welfare is thus hill-shaped, while inequality tends to rise monotonically. Bonus caps can help restore balance in incentives but may generate other distortions.
This paper shows that adding a small application cost to a transfer program can substantially improve targeting through self-selection. Our village-level experiment in Indonesia finds that requiring beneficiaries to apply for benefits results in substantially poorer beneficiaries than automatic enrollment using the same asset test. Marginally increasing application costs on an experimental basis does not further improve targeting. Estimating a model of the application decision implies that the results are largely driven by the nonpoor, who make up the bulk of the population, forecasting that they are unlikely to pass the asset test and therefore not bothering to apply.
This study explores the consequences and origins of between-ethnicity inequality for a large sample of countries. First, combining satellite images of nighttime luminosity with the homelands of ethnolinguistic groups, we construct measures of ethnic inequality. Second, we uncover a strong inverse association between ethnic inequality and contemporary development above and beyond its relationship with cross-region and cross–administrative unit inequality. Third, we establish that differences in geographic endowments across ethnic homelands explain a sizable fraction of the variation in economic disparities across groups. Fourth, we show that inequality in geographic endowments across ethnic homelands is a negative correlate of development.
Banking crises are rare events that break out in the midst of credit-intensive booms and bring about deep and long-lasting recessions. This paper presents a textbook dynamic stochastic general equilibrium model to explain these phenomena. The model features a nontrivial banking sector, where bank heterogeneity gives rise to an interbank market. Moral hazard and asymmetric information in this market may lead to sudden market freezes, banking crises, credit crunches, and severe “financial” recessions. Those recessions follow credit booms and are not necessarily triggered by large exogenous adverse shocks.
Some technologies save lives—new vaccines, new surgical techniques, safer highways. Others threaten lives—pollution, nuclear accidents, global warming, and the rapid global transmission of disease. How is growth theory altered when technologies involve life and death instead of just higher consumption? This paper shows that taking life into account has first-order consequences. Under standard preferences, the value of life may rise faster than consumption, leading society to value safety over consumption growth. As a result, the optimal rate of consumption growth may be substantially lower than what is feasible, in some cases falling all the way to zero.
Many macroeconomists argue that productivity is low in developing countries because of frictions that impede the adoption of modern technologies. I argue that in the retail trade sector, developing countries rationally choose technologies with low measured labor productivity. My theory is that the adoption of modern retail technologies is optimal only when household ownership of complementary durable goods, such as cars, is widespread. Because income is low in the developing world, households own few such durables. The theory implies that policies that increase measured retail productivity do not necessarily increase welfare.
We evaluate returns to General Educational Development (GED) certification for high school dropouts using state administrative data. We apply a fuzzy regression discontinuity method to account for test takers retaking the test. For women we find that GED certification has no statistically significant effect on either employment or earnings. For men we find a significant increase in earnings in the second year after taking the test but no impact in subsequent years. GED certification increases postsecondary school enrollment by 4–8 percentage points. Our results differ from regression discontinuity approaches that fail to account for test retaking.
Maternal mortality was the second-largest cause of death for women in childbearing years until the mid-1930s in the United States. For each death, 20 times as many mothers suffered pregnancy-related conditions, which made it hard for them to engage in market work. Between 1930 and 1960 there was a remarkable improvement in maternal health. We argue that this development, by enabling women to reconcile work and motherhood, was essential for the joint rise in women’s labor force participation and fertility over this period. We also show that the diffusion of infant formula played an important auxiliary role.
Relying on diversity measures computed at the apartment block level under conditions of exogenous allocation of public housing in France, this paper identifies the effects of ethnic diversity on social relationships and housing quality. Housing Survey data reveal that diversity induces social anomie. Through the channel of anomie, diversity accounts for the inability of residents to sanction others for vandalism and to act collectively to demand proper building maintenance. However, anomie also lowers opportunities for violent confrontations, which are not related to diversity.
I investigate how teamwork may reduce moral hazard by joint monitoring and management. I study two organizational systems differing in the extent to which physicians may mutually manage work: Physicians are assigned patients in a “nurse-managed” system but divide patients between themselves in a “self-managed” system. The self-managed system increases throughput productivity by reducing a “foot-dragging” moral hazard, in which physicians prolong patient stays as expected future work increases. I find evidence that physicians in the same location have better information about each other and that, in the self-managed system, they use this information to assign patients.
We propose a theory of self-fulfilling unemployment fluctuations. When a firm increases its workforce, it raises demand and weakens competition facing other firms, as employed workers spend more and have less time to search for low prices than unemployed workers. These effects induce other firms to hire more labor in order to scale up their presence in the product market. The feedback between employment and product market conditions generates multiple equilibria—and the possibility of self-fulfilling fluctuations—if differences in shopping behavior between employed and unemployed are large enough. Evidence on spending, shopping, and prices suggests that this is the case.
We explore the relation between a country’s income and the mix of products it exports. Both are simultaneously determined by countries’ capabilities, that is, by countries’ productivity and quality levels for each good. Our theoretical setup has two features. (1) Some goods have fewer high-quality producers/countries than others, meaning that there is comparative advantage. (2) Imperfect competition allows high- and low-quality producers to coexist. These two features generate an inverted-U, general equilibrium relationship between a country’s export mix and its GDP per capita. We show that this inverted-U permeates the international data on trade and GDP per capita.
This paper examines the macroeconomic implications of sovereign risk in a model in which banks hold domestic government debt. News of a future sovereign default hampers financial intermediation. First, it tightens the funding constraints of banks, reducing their resources to finance firms (liquidity channel). Second, it generates a precautionary motive to deleverage (risk channel). I estimate the model using Italian data, finding that sovereign risk was recessionary and that the risk channel was sizable. I also use the model to measure the effects of subsidized long-term loans to banks. Precautionary motives at the height of the crisis imply that bank lending to firms responds little to these interventions.
Exploiting regression discontinuity designs in Brazilian, Indian, and Canadian first-past-the-post elections, we document that second-place candidates are substantially more likely than close third-place candidates to run in, and win, subsequent elections. Since both candidates lost the election and had similar electoral performance, this is the effect of being labeled the runner-up. Selection into candidacy is unlikely to explain the effect on winning subsequent elections, and we find no effect of finishing in third place versus fourth place. We develop a simple model of strategic coordination by voters that rationalizes the results and provides further predictions that are supported by the data.
We study the efficiency of premarital investments when parents care about their child’s marriage prospects, in a large frictionless marriage market with nontransferable utility. Stochastic returns to investment ensure that equilibrium is unique. We find that, generically, investments exceed the Pareto-efficient level, unless the sexes are symmetric in all respects. Girls will invest more than boys if their quality shocks are less variable than shocks for boys or if they are the abundant sex. The unique equilibrium in our continuum agent model is the limit of the equilibria of finite models, as the number of agents tends to infinity.
A seller wishes to sell multiple goods by a deadline, for example, the end of a season. Potential buyers enter over time and can strategically time their purchases. Each period, the profit-maximizing mechanism awards units to the buyers with the highest valuations exceeding a sequence of cutoffs. We show that these cutoffs are deterministic, depending only on the inventory and time remaining; in the continuous-time limit, the optimal mechanism can be implemented by posting anonymous prices. When incoming demand decreases over time, the optimal cutoffs satisfy a one-period-look-ahead property and prices are defined by an intuitive differential equation.
Some booms in housing prices are followed by busts. Others are not. It is generally difficult to find observable fundamentals that are useful for predicting whether a boom will turn into a bust or not. We develop a model consistent with these observations. Agents have heterogeneous expectations about long-run fundamentals but change their views because of “social dynamics.” Agents with tighter priors are more likely to convert others to their beliefs. Boom-bust episodes typically occur when skeptical agents happen to be correct. The booms that are not followed by busts typically occur when optimistic agents happen to be correct.
We analyze a bargaining situation in which preferences evolve over time and the previous agreement becomes the next status quo. The endogeneity of the status quo exacerbates the players’ conflict of interest: Players disagree more often than under exogenous status quo. This leads to inefficiencies and status quo inertia. Under certain conditions, the negotiations can come to a complete gridlock: Players never reach an agreement. Gridlock can occur between players with arbitrarily similar preferences, provided they are sufficiently patient. In legislative settings, our model predicts polarization and explains why legislators may fail to react promptly to economic shocks.
A key problem with solar energy is intermittency: solar generators produce only when the sun is shining, adding to social costs and requiring electricity system operators to reoptimize key decisions. We develop a method to quantify the economic value of large-scale renewable energy. We estimate the model for southeastern Arizona. Not accounting for offset carbon dioxide, we find social costs of $138.40 per megawatt hour for 20 percent solar generation, of which unforecastable intermittency accounts for $6.10 and intermittency overall for $46.00. With solar installation costs of $1.52 per watt and carbon dioxide social costs of $39.00 per ton, 20 percent solar would be welfare neutral.
This paper develops a price-theoretic framework for matching markets with heterogeneous preferences. The model departs from the Gale and Shapley model by assuming that a finite number of agents on one side (colleges) are matched to a continuum of agents on the other side (students). We show that stable matchings correspond to solutions of supply and demand equations, with the selectivity of each college playing a role similar to that of prices. We apply the model to an analysis of how competition induced by school choice gives schools incentives to invest in quality and to asymptotics of school choice mechanisms.
Incumbent politicians tend to receive more votes when economic conditions are good. In this paper we explore the source of this correlation, exploiting the exceptional evidence provided by the Spanish Christmas Lottery. Because winning tickets are typically sold by one lottery outlet, winners tend to be geographically clustered. This allows us to study the impact of exogenous good economic conditions on voting behavior. We find that incumbents receive significantly more votes in winning provinces. The evidence is consistent with a temporary increase in happiness making voters more lenient toward the incumbent, or with a stronger preference for the status quo.
We study decentralized college admissions with uncertain student preferences. Colleges strategically admit students likely to be overlooked by competitors. Highly ranked students may receive fewer admissions or have a higher chance of receiving no admissions than those ranked below. When students’ attributes are multidimensional, colleges avoid head-on competition by placing excessive weight on school-specific attributes such as essays. Restricting the number of applications or wait-listing alleviates enrollment uncertainty, but the outcomes are inefficient and unfair. A centralized matching via Gale and Shapley’s deferred acceptance algorithm attains efficiency and fairness but may make some colleges worse off than under decentralized matching.
We exploit the randomness of weather and the relationship between weather and moviegoing to quantify social spillovers in movie consumption. Instrumenting for early viewership with plausibly exogenous weather shocks captured in LASSO-chosen instruments, we find that shocks to opening weekend viewership are doubled over the following five weekends. Our estimated momentum arises almost exclusively at the local level, and we find no evidence that it varies with either ex post movie quality or the precision of ex ante information about movie quality, suggesting that the observed momentum is driven in part by a preference for shared experience, and not only by social learning.
We measure the effects of debt dilution on sovereign default risk and study debt covenants that could mitigate these effects. We calibrate a baseline model with endogenous debt duration and default risk (in which debt can be diluted) using data from Spain. We find that debt dilution accounts for 78 percent of the default risk in the baseline economy and that eliminating dilution increases the optimal duration of sovereign debt by almost 2 years. Eliminating dilution also increases consumption volatility but still produces welfare gains. The debt covenants we study could help enforcing fiscal rules.
We study how firms differ from their competitors using new time-varying measures of product similarity based on text-based analysis of firm 10-K product descriptions. This year-by-year set of product similarity measures allows us to generate a new set of industries in which firms can have their own distinct set of competitors. Our new sets of competitors explain specific discussion of high competition, rivals identified by managers as peer firms, and changes to industry competitors following exogenous industry shocks. We also find evidence that firm R&D and advertising are associated with subsequent differentiation from competitors, consistent with theories of endogenous product differentiation.
This paper analyzes the inefficiencies arising from the combination of fixed exchange rates, nominal rigidity, and free capital mobility. We document that nominal wages are downwardly rigid in emerging countries. We develop an open-economy model that incorporates this friction. The model predicts that the combination of a currency peg and free capital mobility creates a negative externality that causes overborrowing during booms and high unemployment during contractions. Optimal capital controls are shown to be prudential. For plausible calibrations, they reduce unemployment by around 5 percentage points. The optimal exchange rate policy eliminates unemployment and calls for large devaluations during crises.
This paper analyzes the inefficiencies arising from the combination of fixed exchange rates, nominal rigidity, and free capital mobility. We document that nominal wages are downwardly rigid in emerging countries. We develop an open-economy model that incorporates this friction. The model predicts that the combination of a currency peg and free capital mobility creates a negative externality that causes overborrowing during booms and high unemployment during contractions. Optimal capital controls are shown to be prudential. For plausible calibrations, they reduce unemployment by around 5 percentage points. The optimal exchange rate policy eliminates unemployment and calls for large devaluations during crises.
A firm considers hiring an agent who may be competent for a potential project or not. The agent can prove her competence but faces a holdup problem. We propose a model of persuasion and show how gradualism helps mitigate the holdup problem. We show when it is optimal to give away part of the information at the beginning of the bargaining and sell the remainder in dribs and drabs. The agent can appropriate only part of the value of information. Introducing a third party allows her to extract the maximum surplus.
The flow opportunity cost of moving from unemployment to employment consists of forgone public benefits and the forgone consumption value of nonworking time. We construct a time series of the opportunity cost of employment using detailed microdata and administrative or national accounts data to estimate benefits levels, eligibility, take-up, consumption by labor force status, hours, taxes, and preference parameters. The opportunity cost is procyclical and volatile over the business cycle. The estimated cyclicality implies far less unemployment volatility in leading models of the labor market than that observed in the data, irrespective of the level of the opportunity cost.
We investigate how cognitive ability and character skills influence the evolution of play toward Nash equilibrium in repeated strategic interactions. We find that more cognitively able subjects choose numbers closer to equilibrium, earn more, and converge more frequently to equilibrium play. We estimate a structural model of learning based on level k reasoning and find a positive relationship between cognitive ability and levels. Furthermore, the average level of more cognitively able subjects responds positively to the cognitive ability of their opponents. More agreeable and emotionally stable subjects also learn faster, although the effect of cognitive ability is stronger than that of personality.
We study how an improvement in market transparency affects seller exit and continuing sellers’ behavior in a market setting that involves informational asymmetries. The improvement was achieved by reducing strategic bias in buyer ratings. It led to a significant increase in buyer satisfaction with seller performance, but not to an increase in seller exit. When sellers had the choice between exiting—a reduction in adverse selection—and staying but improving behavior—a reduction in moral hazard—they preferred the latter. Increasing market transparency led to better market outcomes.
The year 1946 has been seen as a pivotal year of transition by historians of the Chicago Economics Department, in large part as a result of the arrival of Milton Friedman that year. This essay examines new evidence on department deliberations on faculty hiring in February of 1946. It argues that Friedman’s recruitment reflected a compromise between Frank Knight and his followers on the one hand and those associated with the Cowles Commission on the other.
By exploiting a reform in the United Arab Emirates that relaxed restrictions on employer transitions, we provide new estimates of the monopsony power of firms over migrant workers. Our results show that the reform increased incumbent migrants’ earnings and firm retention. This occurs despite an increase in employer transitions and is driven by a fall in country exits. While the outcomes of incumbents improved, the reform decreased demand for new migrants and lowered their earnings. These results are consistent with a model of monopsony in which firms face upward-sloping labor supply curves for both new recruits in source countries and incumbent migrants.
Referred workers are more likely than nonreferred workers to be hired, all else equal. In three field experiments in an online labor market, we examine why. We find that referrals contain positive information about worker performance and persistence that is not contained in workers’ observable characteristics. We also find that referrals perform particularly well when working directly with their referrers. However, we do not find evidence that referrals exert more effort because they believe their performance will affect their relationship with their referrer or their referrer’s position at the firm.
Referred workers are more likely than nonreferred workers to be hired, all else equal. In three field experiments in an online labor market, we examine why. We find that referrals contain positive information about worker performance and persistence that is not contained in workers’ observable characteristics. We also find that referrals perform particularly well when working directly with their referrers. However, we do not find evidence that referrals exert more effort because they believe their performance will affect their relationship with their referrer or their referrer’s position at the firm.
We conduct an experiment in which subjects face the same questions repeated multiple times, with repetitions of two types: (1) following the literature, the repetitions are distant from each other; (2) in a novel treatment, the repetitions are in a row, and subjects are told that the questions will be repeated. We find that a large majority of subjects exhibit stochastic choice in both cases. We discuss the implications for models of stochastic choice.
We study competition in matching markets with random heterogeneous preferences and an unequal number of agents on either side. First, we show that even the slightest imbalance yields an essentially unique stable matching. Second, we give a tight description of stable outcomes, showing that matching markets are extremely competitive. Each agent on the short side of the market is matched with one of his top choices, and each agent on the long side either is unmatched or does almost no better than being matched with a random partner. Our results suggest that any matching market is likely to have a small core, explaining why small cores are empirically ubiquitous.
This paper studies a quantitative general equilibrium model of housing. The model has two key elements not previously considered in existing quantitative macro studies of housing finance: aggregate business cycle risk and a realistic wealth distribution driven in the model by bequest heterogeneity in preferences. These features of the model play a crucial role in the following results. First, a relaxation of financing constraints leads to a large boom in house prices. Second, the boom in house prices is entirely the result of a decline in the housing risk premium. Third, low interest rates cannot explain high home values.
We study the distributional consequences of trade in a world with two industries and two heterogeneous factors of production. Productivity in each production unit reflects the ability of the manager and the abilities of the workers, with complementarity between the two. We begin by examining the forces that govern the sorting of worker and manager types to industries and the matching of workers and managers within industries. We then consider how changes in relative output prices generated by changes in the trading environment affect sorting, matching, and the distributions of wages and salaries.
We propose a model consistent with two observations. First, the tax rates adopted by different countries are generally uncorrelated with their growth performance. Second, countries that drastically reduce private incentives to invest severely hurt their growth performance. In our model, the effects of taxation on growth are highly nonlinear. Low tax rates have a very small impact on long-run growth rates. But as tax rates rise, their negative impact on growth rises dramatically. The median voter chooses tax rates that have a small impact on growth prospects, making the relation between tax rates and economic growth difficult to measure empirically.
We estimate a dynamic life cycle model of labor supply, fertility, and savings, incorporating occupational choices, with specific wage paths and skill atrophy that vary over the career. This allows us to understand the trade-off between occupational choice and desired fertility, as well as sorting both into the labor market and across occupations. We quantify the life cycle career costs associated with children, how they decompose into loss of skills during interruptions, lost earnings opportunities, and selection into more child-friendly occupations. We analyze the long-run effects of policies that encourage fertility and show that they are considerably smaller than short-run effects.
We study the causal effect of school curricula on students’ political attitudes, exploiting a major textbook reform in China between 2004 and 2010. The sharp, staggered introduction of the new curriculum across provinces allows us to identify its causal effects. We examine government documents articulating desired consequences of the reform and identify changes in textbooks reflecting these aims. A survey we conducted reveals that the reform was often successful in shaping attitudes, while evidence on behavior is mixed. Studying the new curriculum led to more positive views of China’s governance, changed views on democracy, and increased skepticism toward free markets.
After the fall of the Berlin Wall, East Germany experienced an unprecedented temporary drop in fertility driven by economic uncertainty. We show that the children born during this transition period performed worse on a range of educational outcomes from an early age onward. The mothers of these children exhibit personal characteristics and family structures consistent with negative parental selection. Investigating the underlying mechanisms reveals that parental educational input and emotional attachment were also lower for these children. Finally, our ability to compare siblings means that we can reject that our results stem from a time of birth effect.
We show that financial knowledge is a key determinant of wealth inequality in a stochastic life cycle model with endogenous financial knowledge accumulation, where financial knowledge enables individuals to better allocate lifetime resources in a world of uncertainty and imperfect insurance. Moreover, because of how the US social insurance system works, better-educated individuals have most to gain from investing in financial knowledge. Our parsimonious specification generates substantial wealth inequality relative to a one-asset saving model and one in which returns on wealth depend on portfolio composition alone. We estimate that 30–40 percent of retirement wealth inequality is accounted for by financial knowledge.
Using newly collected data on association density in 229 towns and cities in interwar Germany, we show that denser social networks were associated with faster entry into the Nazi Party. The effect is large: one standard deviation higher association density is associated with at least 15 percent faster Nazi Party entry. Party membership, in turn, predicts electoral success. Social networks thus aided the rise of the Nazis that destroyed Germany’s first democracy. The effects of social capital depended on the political context: in federal states with more stable governments, higher association density was not correlated with faster Nazi Party entry.
Higher wages are generally thought to increase human capital production, particularly in the developing world. We introduce a simple model of human capital production in which investments and time allocation differ by age. Using data on test scores and schooling from rural India, we show that higher wages increase human capital investment in early life (in utero to age 2) but decrease human capital from age 5 to 16. Children switch out of school into productive work when rainfall is higher. The opportunity cost of schooling, even for fairly young children, is an important factor in determining overall human capital investment.
Does access to credit explain the gap in schooling attainment between children from richer and poorer families? I present new evidence on this important question based on the causal effects of two college loan programs in Chile that are available to students scoring above a threshold on the national college admission test, enabling a regression discontinuity design. I find that credit access leads to a 100 percent increase in immediate college enrollment and a 50 percent increase in the probability of ever enrolling. Moreover, access to loans effectively eliminates the income gap in enrollment and number of years of college attainment.
Does access to credit explain the gap in schooling attainment between children from richer and poorer families? I present new evidence on this important question based on the causal effects of two college loan programs in Chile that are available to students scoring above a threshold on the national college admission test, enabling a regression discontinuity design. I find that credit access leads to a 100 percent increase in immediate college enrollment and a 50 percent increase in the probability of ever enrolling. Moreover, access to loans effectively eliminates the income gap in enrollment and number of years of college attainment.
If people enjoy giving, then why do they avoid fund-raisers? Partnering with the Salvation Army at Christmastime, we conducted a randomized field experiment placing bell ringers at one or both main entrances to a supermarket, making it easy or difficult to avoid the ask. Additionally, bell ringers either were silent or said “please give.” Making avoidance difficult increased both the rate of giving and donations. Paradoxically, the verbal ask dramatically increased giving but also led to dramatic avoidance. We argue that this illustrates sophisticated awareness of the empathy-altruism link: people avoid empathic stimulation to regulate their giving and guilt.
We evaluate the effects of the 2009 Home Affordable Modification Program (HAMP) that provided intermediaries with sizable financial incentives to renegotiate mortgages. HAMP increased intensity of renegotiations and prevented a substantial number of foreclosures but reached just one-third of its targeted indebted households. This shortfall was in large part due to low renegotiation intensity of a few large intermediaries and was driven by intermediary-specific factors. Exploiting regional variation in the intensity of program implementation by intermediaries suggests that the program was associated with a lower rate of foreclosures, consumer debt delinquencies, house price declines, and an increase in durable spending.
We introduce a “bad environment–good environment” (BEGE) technology for consumption growth in a consumption-based asset pricing model with external habit formation. The model generates realistic non-Gaussian features of consumption growth and fits standard salient features of asset prices including the means and volatilities of equity returns and a low risk-free rate. BEGE dynamics additionally allow the model to generate realistic properties of equity index options prices and their comovements with the macroeconomic outlook. In particular, when option-implied volatility is high—as measured, for instance, by the VIX index—the distribution of consumption growth is more negatively skewed.
Minority and disadvantaged students are typically underrepresented in selective programs that use merit-based admission. Urban school districts may set different referral and admission thresholds based on income and race (affirmative action), and they may exploit differences in achievement relative to ability across race and income groups (profiling). We develop and estimate a model that provides a unified treatment of affirmative action and profiling. We find profiling by race and income and affirmative action for low-income students. Counterfactual analysis reveals that these policies achieve more than 80 percent of African American enrollment that could be attained by race-based affirmative action.
This paper studies strategic industry dynamics of creative destruction in which firms and technologies experience turnover. Theories predict that cannibalization between existing and new products delays incumbents’ innovation, whereas preemptive motives accelerate it. Incumbents’ cost (dis)advantage relative to that of entrants would further reinforce these tendencies. To empirically assess these three forces, I estimate a dynamic oligopoly model using a unique panel data set of hard disk drive manufacturers. The results suggest that despite strong preemptive motives and a substantial cost advantage over entrants, cannibalization makes incumbents reluctant to innovate, which can explain at least 57 percent of the incumbent-entrant innovation gap.
This paper examines the long-term impacts of early childhood exposure to air pollution on adult outcomes using US administrative data. We exploit changes in air pollution driven by the 1970 Clean Air Act to analyze the difference in outcomes between cohorts born in counties before and after large improvements in air pollution relative to those same cohorts born in counties that had no improvements. We find a significant relationship between pollution exposure in the year of birth and later-life outcomes. A higher pollution level in the year of birth is associated with lower labor force participation and lower earnings at age 30.
How does political unrest influence public policy? We assume that protests are an emotional reaction to unfair treatment. Individuals have a consistent view of fairness that internalizes government constraints. Individuals accept lower welfare if the government is more constrained. This resignation effect induces a benevolent government to delay unpleasant choices and accumulate public debt to mitigate social unrest. More radical and homogeneous groups are more prone to unrest and hence more influential. Even if the government is benevolent and all groups are identical in their propensity to riot, equilibrium policy can be distorted. The evidence is consistent with these implications.
How does political unrest influence public policy? We assume that protests are an emotional reaction to unfair treatment. Individuals have a consistent view of fairness that internalizes government constraints. Individuals accept lower welfare if the government is more constrained. This resignation effect induces a benevolent government to delay unpleasant choices and accumulate public debt to mitigate social unrest. More radical and homogeneous groups are more prone to unrest and hence more influential. Even if the government is benevolent and all groups are identical in their propensity to riot, equilibrium policy can be distorted. The evidence is consistent with these implications.
Pathways to Education is a comprehensive support program developed to improve academic outcomes of high school students from very poor social-economic backgrounds. The program includes proactive mentoring, daily tutoring, and group activities, combined with intermediate and long-term incentives to reinforce a minimum degree of mandatory participation; it began in 2001 for entering grade 9 students living in Regent Park, the largest public housing project in Toronto. It expanded in 2007 to include two additional Toronto projects. Comparing students from other housing projects before and after the introduction of the program, high school graduation and postsecondary enrollment rates rose dramatically for Pathways-eligible students, in some cases by more than 50 percent.
We show how a discrete instrument can be used to identify the marginal treatment effects under a functional structure that allows for treatment heterogeneity among individuals with the same observed characteristics and self-selection based on the unobserved gain from treatment. Guided by this identification result, we perform a marginal treatment effect analysis of the interaction between the quantity and quality of children. Our estimates reveal that the family size effects vary in magnitude and even sign and that families act as if they possess some knowledge of the idiosyncratic effects in the fertility decision.
This paper estimates the impact of globalization on markups, and the effect of changing markups on US welfare, in a monopolistic competition model. We work with symmetric translog preferences, which allow for endogenous markups and firm entry and exit, thereby changing product variety. We find that between 1992 and 2005, US import shares rose and US firms exited, leading to an implied fall in markups, while variety went up because of imports. US welfare rose by nearly 1 percent as a result of these changes, with product variety contributing one-half of that total and declining markups the other half.
A new information aggregation mechanism (IAM), developed via laboratory experimental methods, is implemented inside Intel Corporation in a long-running field test. The IAM, incorporating features of pari-mutuel betting, is uniquely designed to collect and quantize as probability distributions dispersed, subjectively held information. IAM participants’ incentives support timely information revelation and the emergence of consensus beliefs over future outcomes. Empirical tests demonstrate the robustness of experimental results and the IAM’s practical usefulness in addressing real-world problems. The IAM’s predictive distributions forecasting sales are very accurate, especially for short horizons and direct sales channels, often proving more accurate than Intel’s internal forecast.
We prove a new identification theorem showing nonparametric identification of the joint distribution of random coefficients in general nonlinear and additive models. This differs from existing random coefficients models by not imposing a linear index structure for the regressors. We then model unobserved preference heterogeneity in consumer demand as utility functions with random Barten scales. These Barten scales appear as random coefficients in nonlinear demand equations. Using Canadian data, we compare estimated energy demand functions with and without random Barten scales. We find that unobserved preference heterogeneity substantially affects the estimated consumer surplus costs of an energy tax.
We prove a new identification theorem showing nonparametric identification of the joint distribution of random coefficients in general nonlinear and additive models. This differs from existing random coefficients models by not imposing a linear index structure for the regressors. We then model unobserved preference heterogeneity in consumer demand as utility functions with random Barten scales. These Barten scales appear as random coefficients in nonlinear demand equations. Using Canadian data, we compare estimated energy demand functions with and without random Barten scales. We find that unobserved preference heterogeneity substantially affects the estimated consumer surplus costs of an energy tax.
This paper documents the gender gap in performance among high-skilled professionals in the United States. On the basis of widely used performance measures in law firms, we find that male lawyers bill 10 percent more hours and bring in more than twice as much new client revenue as female lawyers. The differential impact across genders in the presence of young children and differences in aspirations to become a law firm partner account for a large share of the difference in performance. We show that accounting for performance has important consequences for gender gaps in lawyers’ earnings and subsequent promotion.
This paper documents the gender gap in performance among high-skilled professionals in the United States. On the basis of widely used performance measures in law firms, we find that male lawyers bill 10 percent more hours and bring in more than twice as much new client revenue as female lawyers. The differential impact across genders in the presence of young children and differences in aspirations to become a law firm partner account for a large share of the difference in performance. We show that accounting for performance has important consequences for gender gaps in lawyers’ earnings and subsequent promotion.
We analyze high-frequency micro panel data on customers of a major Korean credit card company before and after the 2003 Korean credit crisis and find evidence of pervasive precommitment behavior that is difficult to explain using standard economic theories: (1) customers voluntarily reduce their credit card borrowing limits without any compensation, (2) customers turn down interest-free installment loan offers with high probability, and (3) of the small fraction of customers who do accept interest-free loan offers, most precommit to pay off the loan over a shorter term than the maximum allowed term under the offer.
We analyze high-frequency micro panel data on customers of a major Korean credit card company before and after the 2003 Korean credit crisis and find evidence of pervasive precommitment behavior that is difficult to explain using standard economic theories: (1) customers voluntarily reduce their credit card borrowing limits without any compensation, (2) customers turn down interest-free installment loan offers with high probability, and (3) of the small fraction of customers who do accept interest-free loan offers, most precommit to pay off the loan over a shorter term than the maximum allowed term under the offer.
We reinvestigate the delayed overshooting puzzle. Using a method of sign restrictions, we find that delayed overshooting is primarily a phenomenon of the 1980s when the Fed was under the chairmanship of Paul Volcker. Related findings are as follows: (1) Uncovered interest parity fails to hold during the Volcker era and tends to hold during the post-Volcker era; (2) US monetary policy shocks have substantial impacts on exchange rate variations but misleadingly appear to have small impacts when monetary policy regimes are pooled. In brief, we confirm Dornbusch’s overshooting hypothesis.
We reinvestigate the delayed overshooting puzzle. Using a method of sign restrictions, we find that delayed overshooting is primarily a phenomenon of the 1980s when the Fed was under the chairmanship of Paul Volcker. Related findings are as follows: (1) Uncovered interest parity fails to hold during the Volcker era and tends to hold during the post-Volcker era; (2) US monetary policy shocks have substantial impacts on exchange rate variations but misleadingly appear to have small impacts when monetary policy regimes are pooled. In brief, we confirm Dornbusch’s overshooting hypothesis.
Taxation affects the allocation of talented individuals across professions by blunting material incentives and thus magnifying nonpecuniary incentives of pursuing a “calling.” Estimates from the literature suggest that high-paying professions have negative externalities, whereas low-paying professions have positive externalities. A calibrated model therefore prescribes negative marginal tax rates on middle-class incomes and positive rates on the rich. The welfare gains from implementing such a policy are small and are dwarfed by the gains from profession-specific taxes and subsidies. These results depend crucially on externality estimates and labor substitution patterns across professions, both of which are very uncertain given existing empirical evidence.
This paper asks whether pay disclosure in the public sector changes wage setting at the top of the distribution. I examine a 2010 California mandate that required municipal salaries to be posted online. Among top managers, disclosure led to approximately 7 percent average compensation declines, and a 75 percent increase in their quit rate, relative to managers in cities that had already disclosed salaries. The wage cuts were largely nominal. Wage cuts were larger in cities with higher initial compensation, but not in cities where compensation was initially out of line with (measured) fundamentals. The response is more consistent with public aversion to high compensation than the effects of increased accountability.
This paper asks whether pay disclosure in the public sector changes wage setting at the top of the distribution. I examine a 2010 California mandate that required municipal salaries to be posted online. Among top managers, disclosure led to approximately 7 percent average compensation declines, and a 75 percent increase in their quit rate, relative to managers in cities that had already disclosed salaries. The wage cuts were largely nominal. Wage cuts were larger in cities with higher initial compensation, but not in cities where compensation was initially out of line with (measured) fundamentals. The response is more consistent with public aversion to high compensation than the effects of increased accountability.
This paper derives optimal income tax and human capital policies in a life cycle model with risky human capital. The government faces asymmetric information regarding agents’ ability, its evolution, and labor supply. When the wage elasticity with respect to ability is increasing in human capital, the optimal subsidy involves less than full deductibility of human capital expenses on the tax base and falls with age. Income-contingent loans or a deferred deductibility scheme can implement the optimum. Numerical results suggest that full deductibility of expenses is close to optimal and that simple linear age-dependent policies perform very well.
This paper investigates the origin and propagation of balance sheet recessions. I first show that in standard models driven by TFP shocks, the balance sheet channel disappears when agents can write contracts on the aggregate state of the economy. Optimal contracts sever the link between leverage and aggregate risk sharing, eliminating the concentration of aggregate risk that drives balance sheet recessions. I then show that uncertainty shocks can help explain this concentration of aggregate risk and drive balance sheet recessions, even with contracts on aggregate shocks. The mechanism is quantitatively important, and I explore implications for financial regulation.
Financial constraints are considered an important impediment to growth for small businesses. We study theoretically and empirically the relationship between the financial constraints of agents and the organizational decisions and growth of principals, in the context of franchising. We find that a 30 percent decrease in average collateralizable housing wealth in an area is associated with a delay in chains’ entry into franchising by 0.33 year on average, or 10 percent of the average waiting time, and a reduction in chain growth and hence a reduction in franchised chain employment of about 9 percent.
To study the impact of macroprudential policy on credit supply cycles and real effects, we analyze dynamic provisioning. Introduced in Spain in 2000, revised four times, and tested in its countercyclicality during the crisis, it affected banks differentially. We find that dynamic provisioning smooths credit supply cycles and, in bad times, supports firm performance. A 1 percentage point increase in capital buffers extends credit to firms by 9 percentage points, increasing firm employment (6 percentage points) and survival (1 percentage point). Moreover, there are important compositional effects in credit supply related to risk and regulatory arbitrage by nonregulated and regulated but less affected banks.
I provide new evidence on the relative “powers” of contraception and abortion policy in effecting the dramatic social transformations of the 1960s and 1970s. Trends in sexual behavior suggest that young women’s increased access to the birth control pill fueled the sexual revolution, but neither these trends nor difference-in-difference estimates support the view that this also led to substantial changes in family formation. Rather, the estimates robustly suggest that it was liberalized access to abortion that allowed large numbers of women to delay marriage and motherhood.
This paper derives optimal income tax and human capital policies in a life cycle model with risky human capital. The government faces asymmetric information regarding agents’ ability, its evolution, and labor supply. When the wage elasticity with respect to ability is increasing in human capital, the optimal subsidy involves less than full deductibility of human capital expenses on the tax base and falls with age. Income-contingent loans or a deferred deductibility scheme can implement the optimum. Numerical results suggest that full deductibility of expenses is close to optimal and that simple linear age-dependent policies perform very well.
Financial constraints are considered an important impediment to growth for small businesses. We study theoretically and empirically the relationship between the financial constraints of agents and the organizational decisions and growth of principals, in the context of franchising. We find that a 30 percent decrease in average collateralizable housing wealth in an area is associated with a delay in chains’ entry into franchising by 0.33 year on average, or 10 percent of the average waiting time, and a reduction in chain growth and hence a reduction in franchised chain employment of about 9 percent.
To study the impact of macroprudential policy on credit supply cycles and real effects, we analyze dynamic provisioning. Introduced in Spain in 2000, revised four times, and tested in its countercyclicality during the crisis, it affected banks differentially. We find that dynamic provisioning smooths credit supply cycles and, in bad times, supports firm performance. A 1 percentage point increase in capital buffers extends credit to firms by 9 percentage points, increasing firm employment (6 percentage points) and survival (1 percentage point). Moreover, there are important compositional effects in credit supply related to risk and regulatory arbitrage by nonregulated and regulated but less affected banks.
I provide new evidence on the relative “powers” of contraception and abortion policy in effecting the dramatic social transformations of the 1960s and 1970s. Trends in sexual behavior suggest that young women’s increased access to the birth control pill fueled the sexual revolution, but neither these trends nor difference-in-difference estimates support the view that this also led to substantial changes in family formation. Rather, the estimates robustly suggest that it was liberalized access to abortion that allowed large numbers of women to delay marriage and motherhood.
The arrival of global retail chains in developing countries is causing a radical transformation in the way households source their consumption. This paper draws on a rich collection of Mexican microdata to estimate the effect of foreign supermarket entry on household welfare and decomposes this effect into six channels. We find that foreign entry causes large welfare gains for the average household predominantly driven by a reduction in the cost of living—both through price reductions at domestic stores and through the direct consumer gains from foreign stores. These gains are, on average, positive for all income groups but are regressive.
Suppose that, when evaluating two alternatives x and y by means of a parametric utility function, low values of the parameter indicate a preference for x and high values indicate a preference for y. We say that a stochastic choice model is monotone whenever the probability of choosing x is decreasing in the preference parameter. We show that the standard use of random utility models in the context of risk and time preferences may sharply violate this monotonicity property and argue that their use in preference estimation may be problematic. They may pose identification problems and could yield biased estimations. We then establish that the alternative random parameter models are always monotone.
Suppose that, when evaluating two alternatives x and y by means of a parametric utility function, low values of the parameter indicate a preference for x and high values indicate a preference for y. We say that a stochastic choice model is monotone whenever the probability of choosing x is decreasing in the preference parameter. We show that the standard use of random utility models in the context of risk and time preferences may sharply violate this monotonicity property and argue that their use in preference estimation may be problematic. They may pose identification problems and could yield biased estimations. We then establish that the alternative random parameter models are always monotone.
The gravity equation in international trade states that bilateral exports are proportional to economic size and inversely proportional to geographic distance. While the role of size is well understood, that of distance remains mysterious. I offer an explanation for the role of distance: If (i) the distribution of firm sizes is Pareto, (ii) the average squared distance of a firm’s exports is an increasing power function of its size, and (iii) a parameter restriction holds, then the distance elasticity of trade is constant for long distances. When the firm size distribution follows Zipf’s law, trade is inversely proportional to distance.
Auctions were very popular in the early days of internet commerce, but today online sellers mostly use posted prices. We model the choice between auctions and posted prices as a trade-off between competitive price discovery and convenience. Evidence from eBay fits the theory. We then show that the decline in auctions was not driven by compositional shifts in seller experience or items sold, but by changing seller incentives. We estimate the demand facing sellers and document falling sale probabilities and falling relative demand for auctions. Both favor posted prices; our estimates suggest the latter is more important for the auction decline. Survey evidence provides further support.
This paper provides new evidence that Medicaid’s introduction reduced infant and child mortality in the 1960s and 1970s. Mandated coverage of all cash welfare recipients induced substantial cross-state variation in the share of children immediately eligible for the program. Before Medicaid, higher- and lower-eligibility states had similar infant and child mortality trends. After Medicaid, public insurance utilization increased and mortality fell more rapidly among children and infants in high-Medicaid-eligibility states. Mortality among nonwhite children on Medicaid fell by 20 percent, leading to a reduction in aggregate nonwhite child mortality rates of 11 percent.
This paper quantitatively assesses time inconsistency, moral hazard, and political ideology in monopoly regulation of electricity distribution. We specify and estimate a dynamic model of utility regulation featuring investment and moral hazard. We find underinvestment in electricity distribution capital aiming to reduce power outages and use the estimated model to quantify the value of regulatory commitment in inducing greater investment. Furthermore, more conservative political environments grant higher regulated returns but have higher rates of electricity loss. Using the estimated model, we quantify how conservative regulators thus mitigate welfare losses due to time inconsistency but worsen losses from moral hazard.
Why do firms pay different wages? Empirical evidence suggests the presence of substantial differences in firm pay controlling for worker skill. Moreover, these differences are uncorrelated with skills, indicating the absence of sorting. I show that the face value interpretation is inconsistent with evidence on coworker segregation. I interpret the evidence by applying a sorting model and show that the correlation is biased. I identify nonmonotonicities in wages as the reason for this bias and show that a measure of worker-coworker sorting is more accurate. By calibrating the model to US data, I confirm that the model matches many job market characteristics.
Why do firms pay different wages? Empirical evidence suggests the presence of substantial differences in firm pay controlling for worker skill. Moreover, these differences are uncorrelated with skills, indicating the absence of sorting. I show that the face value interpretation is inconsistent with evidence on coworker segregation. I interpret the evidence by applying a sorting model and show that the correlation is biased. I identify nonmonotonicities in wages as the reason for this bias and show that a measure of worker-coworker sorting is more accurate. By calibrating the model to US data, I confirm that the model matches many job market characteristics.
Exploiting the discontinuity in advertising along the borders of television markets, I estimate that television advertising of prescription antidepressants exhibits significant positive spillovers on rivals’ demand. I apply this identification in a demand model, where estimated parameters indicate significant and persistent spillovers driven by market expansion. Using the demand estimates to calibrate a stylized supply model, I explore the consequences of the positive spillovers on firm advertising choice. Compared with a competitive benchmark in which firms optimally free ride, simulations suggest that a category-wide advertising cooperative would produce a significant increase in total advertising.
Blacks and whites in the United States adopt widely different parental behaviors, but the underlying causes of these differences are not well understood. This paper documents large-scale increases in cognitively stimulating parenting among southern black mothers who came of age in the period immediately following the civil rights movement. The total magnitude of these improvements was approximately 0.5 standard deviations between the 1957 and 1964 birth cohorts, while no significant trends occurred among blacks outside of the South or among whites from any region.
Blacks and whites in the United States adopt widely different parental behaviors, but the underlying causes of these differences are not well understood. This paper documents large-scale increases in cognitively stimulating parenting among southern black mothers who came of age in the period immediately following the civil rights movement. The total magnitude of these improvements was approximately 0.5 standard deviations between the 1957 and 1964 birth cohorts, while no significant trends occurred among blacks outside of the South or among whites from any region.
Redistribution programs in developing countries often “leak” because local officials do not implement programs as the central government intends. We study one approach to reducing leakage. In an experiment in over 550 villages, we test whether mailing cards with program information to targeted beneficiaries increases the subsidy they receive from a subsidized rice program. On net, beneficiaries received 26 percent more subsidy in card villages. Ineligible households received no less, so this represents substantially lower leakage.
We show that supply-side financial shocks have a large impact on firms’ investment. We develop a new methodology to separate firm borrowing shocks from bank supply shocks using a vast sample of matched bank-firm lending data. We decompose aggregate loan movements in Japan for the period 1990–2010 into bank, firm, industry, and common shocks. The high degree of financial institution concentration means that individual banks are large relative to the size of the economy, which creates a role for granular shocks as in Gabaix’s (2011) study. We show that idiosyncratic granular bank supply shocks explain 30–40 percent of aggregate loan and investment fluctuations.
Collateral constraints widely used in models of financial crises feature a pecuniary externality: Agents do not internalize how borrowing decisions made in “good times” affect collateral prices during a crisis. We show that under commitment the optimal financial regulator’s plans are time inconsistent and study time-consistent policy. Quantitatively, this policy reduces sharply the frequency and magnitude of crises, removes fat tails from the distribution of asset returns, and increases social welfare. In contrast, constant debt taxes are ineffective and can be welfare reducing, while an optimized “macroprudential Taylor rule” is effective but less so than the optimal time-consistent policy.
A randomized control trial with 432 small and medium enterprises in Mexico shows positive impact of access to 1 year of management consulting services on total factor productivity and return on assets. Owners also had an increase in “entrepreneurial spirit” (an index that measures entrepreneurial confidence and goal setting). Using Mexican social security data, we find a persistent large increase (about 50 percent) in the number of employees and total wage bill even 5 years after the program. We document large heterogeneity in the specific managerial practices that improved as a result of the consulting, with the most prominent being marketing, financial accounting, and long-term business planning.
We quantify the effect of deliberation on the decisions of US appellate courts. We estimate a model in which strategic judges communicate before casting their votes and then compare the probability of mistakes in the court with deliberation with a counterfactual of no communication. The model has multiple equilibria, and preferences and information parameters are only partially identified. We find that there is a range of parameters in the identified set—when judges tend to disagree ex ante or their private information is imprecise—in which deliberation can be beneficial; otherwise, deliberation reduces the effectiveness of the court.
Since the early 1990s, as the United States borrowed heavily from the rest of the world, employment in the US goods-producing sector has fallen. We construct a dynamic general equilibrium model with several mechanisms that could generate declining goods-sector employment: foreign borrowing, nonhomothetic preferences, and differential productivity growth across sectors. We find that only 15.1 percent of the decline in goods-sector employment from 1992 to 2012 stems from US trade deficits; most of the decline is due to differential productivity growth. As the United States repays its debt, its trade balance will reverse, but goods-sector employment will continue to fall.
This paper documents how life cycle wage growth varies across countries. We harmonize repeated cross-sectional surveys from a set of countries of all income levels and then measure how wages rise with potential experience. Our main finding is that experience-wage profiles are on average twice as steep in rich countries as in poor countries. In addition, more educated workers have steeper profiles than the less educated; this accounts for around one-third of cross-country differences in aggregate profiles. Our findings are consistent with theories in which workers in poor countries accumulate less human capital or face greater search frictions over the life cycle.
We investigate whether US government spending multipliers are higher during periods of economic slack or when interest rates are near the zero lower bound. Using new quarterly historical US data covering multiple large wars and deep recessions, we estimate multipliers that are below unity irrespective of the amount of slack in the economy. These results are robust to two leading identification schemes, two different estimation methodologies, and many alternative specifications. In contrast, the results are more mixed for the zero lower bound state, with a few specifications implying multipliers as high as 1.5.
We develop a dynamic spatial growth theory with realistic geography. We characterize the model and its balanced-growth path and propose a methodology to analyze equilibria with different levels of migration frictions. Different migration scenarios change local market size, innovation incentives, and the evolution of technology. We bring the model to the data for the whole world economy at a 1° × 1° geographic resolution. We then use the model to quantify the gains from relaxing migration restrictions. Our results indicate that fully liberalizing migration would increase welfare about threefold and would significantly affect the evolution of particular regions of the world.
We show that oil production from existing wells in Texas does not respond to oil prices, while drilling activity and costs respond strongly. To explain these facts, we reformulate Hotelling’s classic model of exhaustible resource extraction as a drilling problem: firms choose when to drill, but production from existing wells is constrained by reservoir pressure, which decays as oil is extracted. The model implies a modified Hotelling rule for drilling revenues net of costs, explains why the production constraint typically binds, and rationalizes regional production peaks and observed patterns of prices, drilling, and production following demand and supply shocks.
Technological change can increase the productivity of the various factors of production in equal terms, or it can be biased toward a specific factor. We directly assess the bias of technological change by measuring, at the level of the individual firm, how much of it is labor augmenting and how much is factor neutral. To do so, we develop a framework for estimating production functions when productivity is multidimensional. Using panel data from Spain, we find that technological change is biased, with both its labor-augmenting and its factor-neutral components causing output to grow by about 1.5 percent per year.
Politicians may strategically time unpopular measures to coincide with newsworthy events that distract the media and the public. We test this hypothesis in the context of the Israeli-Palestinian conflict. We find that Israeli attacks are more likely to occur when US news on the following day is dominated by important predictable events. Strategic timing applies to attacks that bear risk of civilian casualties and are not too costly to postpone. Content analysis suggests that Israel’s strategy aims at minimizing next-day coverage, which is especially charged with negative emotional content. Palestinian attacks do not appear to be timed to US news.
We study favoritism via hometown ties, a common source of favor exchange in China, in fellow selection of the Chinese Academies of Sciences and Engineering. Hometown ties to fellow selection committee members increase candidates’ election probability by 39 percent, coming entirely from the selection stage involving an in-person meeting. Elected hometown-connected candidates are half as likely to have a high-impact publication as elected fellows without connections. CAS/CAE membership increases the probability of university leadership appointments and is associated with a US$9.5 million increase in annual funding for fellows’ institutions, indicating that hometown favoritism has potentially large effects on resource allocation.
House prices exhibit substantially more momentum, positive autocorrelation in price changes, than existing theories can explain. I introduce an amplification mechanism to reconcile this discrepancy. Sellers do not set a unilaterally high or low list price because they face a concave demand curve: increasing the price of an above-average-priced house rapidly reduces its sale probability, but cutting the price of a below-average-priced house only slightly improves its sale probability. The resulting strategic complementarity amplifies frictions because sellers gradually adjust their price to stay near average. I provide empirical evidence for concave demand using a quantitative search model that amplifies momentum two- to threefold.
We propose an original model of human capital investments after leaving school in which individuals differ in their initial human capital obtained at school, their rates of return and costs of human capital investments, and their terminal values of human capital at an arbitrary date in the future. We derive a tractable reduced-form Mincerian model of log earnings profiles along the life cycle that is written as a linear factor model in which levels, growth, and curvature of earnings profiles are individual specific. This provides a structural interpretation of results obtained in the empirical literature on the dynamics of earnings and acknowledges its limitations.
I study intermediation via sequential bilateral bargaining in markets with a network structure. A partition of the network into layers captures intermediation power. Competition governs trade within layers, and hold-ups generate intermediation rents in transactions between layers. Each trader’s intermediation power reflects the competition among intermediation chains as measured by the number of layers separating the trader from buyers. Trade does not maximize welfare or minimize intermediation. The interplay between competition and hold-ups determines the level of inefficiency. Eliminating middlemen or transferring intermediation costs downstream increases seller profits. Downstream and upstream competition respond oppositely to either horizontal or vertical integration.
This paper examines the extent to which tariff cooperation is observed among World Trade Organization members. With the help of a simple political economy model, we show that tariffs are positively correlated with the importer’s market power when they are set noncooperatively but negatively correlated when set cooperatively. We use this prediction to empirically identify the extent of cooperation in the WTO and find that more than three-quarters of WTO members’ tariffs are set noncooperatively.
We build a tractable growth model in which multiproduct incumbents invest in internal innovations to improve their existing products, while new entrants and incumbents invest in external innovations to acquire new product lines. External and internal innovations generate heterogeneous innovation qualities, and firm size affects innovation incentives. We analyze how different types of innovation contribute to economic growth and the role of the firm size distribution. Our model aligns with many observed empirical regularities, and we quantify our framework with Census Bureau and patent data for US firms. Internal innovation scales moderately faster with firm size than external innovation.
The increasing availability of data derived from linked consumer financial accounts has the potential to dramatically expand the potential for research. Examining the most comprehensive existing set of linked-account data, consisting of transaction and balance sheet data for millions of Americans, I demonstrate the power and versatility of such sources. I discuss advantages and concerns arising from this type of data and match a range of distributional moments to external sources. As one application, I test consumption elasticities across households with varying levels, and types, of debt. I find that heterogeneity in consumption elasticity can be explained entirely by credit and liquidity.
Revealed preference theory is brought to bear on the problem of recovering approximate parametric preferences from consistent and inconsistent consumer choices. We propose measures of the incompatibility between the revealed preference ranking implied by choices and the ranking induced by the considered parametric preferences. These incompatibility measures are proven to characterize well-known inconsistency indices. We advocate a recovery approach that is based on such incompatibility measures and demonstrate its applicability for misspecification measurement and model selection. Using an innovative experimental design, we empirically substantiate that the proposed revealed-preference-based method predicts choices significantly better than a standard distance-based method.
We use a rich new body of data on the experiences of unemployed job seekers to determine the sources of wage dispersion and to create a search model consistent with the acceptance decisions the job seekers made. We identify the distributions of four key variables: offered wages, offered nonwage job values, job seekers’ nonwork alternatives, and job seekers’ personal productivities. We find that, conditional on personal productivity, the standard deviation of offered log wages is moderate, at 0.24, whereas the dispersion of the offered nonwage component is substantially larger, at 0.34. The resulting dispersion of offered job values is 0.38.
I argue that firms use referrals from current workers to mitigate a moral hazard problem. I develop a model in which referrals relax a limited liability constraint by allowing the firm to punish the referral provider if the recipient has low output. I test the model’s predictions using household survey data that I collected in Bangladesh. I can control for correlated wage shocks within a network and correlated unobserved type between the recipient and provider. I reject the testable implications of models in which referrals help firms select unobservably good workers or are solely a nonwage benefit to providers.
This paper defines the power of a media organization as its ability to induce voters to make electoral decisions they would not make if reporting were unbiased. It derives a robust upper bound to media power over a range of assumptions about the beliefs and attention patterns of voters. The paper then presents estimates of the power index for the United States and shows how these can inform merger analysis and other policy debates.
Top income inequality rose sharply in the United States over the last 40 years but increased only slightly in France and Japan. Why? We explore a model in which heterogeneous entrepreneurs, broadly interpreted, exert effort to generate exponential growth in their incomes, which tends to raise inequality. Creative destruction by outside innovators restrains this expansion and induces top incomes to obey a Pareto distribution. Economic forces that affect these two mechanisms—including information technology, taxes, and policies related to innovation blocking—may explain the varied patterns of top income inequality that we see in the data.
We develop a model of consumption and income that allows for pervasive heterogeneity in the parameters of both processes. Introducing codependence between household income parameters and preference parameters, we also allow for heterogeneity in the impact of income shocks on consumption. We estimate the parameters of the model using a sample from the Panel Study of Income Dynamics, covering the period 1968–2009. We find considerable codependent heterogeneity in the parameters governing income and consumption processes. Our results suggest a great deal of heterogeneity in the reaction of consumption to income shocks, highlighting the heterogeneity in the self-insurance available to households.
We evaluate the impact of a randomized educational intervention on children’s intertemporal choices. The intervention aims to improve the ability to imagine future selves and encourages forward-looking behavior using a structured curriculum delivered by children’s own trained teachers. We find that treated students make more patient intertemporal decisions in incentivized experimental tasks. The results persist almost 3 years after the intervention, replicate well in a different sample, and are robust across different experimental elicitation methods. The effects also extend beyond experimental outcomes: we find that treated students are significantly less likely to receive a low “behavior grade.”
This paper examines the extent to which government audits of public resources can reduce corruption by enhancing political and judiciary accountability. We do so in the context of Brazil’s anticorruption program, which randomly audits municipalities for their use of federal funds. We find that being audited in the past reduces future corruption by 8 percent, while also increasing the likelihood of experiencing a subsequent legal action by 20 percent. We interpret these reduced-form findings through a political agency model, which we structurally estimate. Our results suggest that the reduction in corruption comes mostly from the audits increasing the perceived nonelectoral costs of engaging in corruption.
This paper examines the extent to which government audits of public resources can reduce corruption by enhancing political and judiciary accountability. We do so in the context of Brazil’s anticorruption program, which randomly audits municipalities for their use of federal funds. We find that being audited in the past reduces future corruption by 8 percent, while also increasing the likelihood of experiencing a subsequent legal action by 20 percent. We interpret these reduced-form findings through a political agency model, which we structurally estimate. Our results suggest that the reduction in corruption comes mostly from the audits increasing the perceived nonelectoral costs of engaging in corruption.
Concave hiring rules imply that firms respond more to bad shocks than to good shocks. They provide a unified explanation for several seemingly unrelated facts about employment growth in macro- and microdata. In particular, they generate countercyclical movement in both aggregate conditional “macro” volatility and cross-sectional “micro” volatility, as well as negative skewness in the cross section and in the time series at different levels of aggregation. Concave establishment-level responses of employment growth to total factor productivity shocks estimated from census data induce significant skewness, movements in volatility, and amplification of bad aggregate shocks.
Teachers affect a variety of student outcomes through their influence on both cognitive and noncognitive skill. I proxy for students’ noncognitive skill using non–test score behaviors. These behaviors include absences, suspensions, course grades, and grade repetition in ninth grade. Teacher effects on test scores and those on behaviors are weakly correlated. Teacher effects on behaviors predict larger impacts on high school completion and other longer-run outcomes than their effects on test scores. Relative to using only test score measures, using effects on both test score and noncognitive measures more than doubles the variance of predictable teacher impacts on longer-run outcomes.
Teachers affect a variety of student outcomes through their influence on both cognitive and noncognitive skill. I proxy for students’ noncognitive skill using non–test score behaviors. These behaviors include absences, suspensions, course grades, and grade repetition in ninth grade. Teacher effects on test scores and those on behaviors are weakly correlated. Teacher effects on behaviors predict larger impacts on high school completion and other longer-run outcomes than their effects on test scores. Relative to using only test score measures, using effects on both test score and noncognitive measures more than doubles the variance of predictable teacher impacts on longer-run outcomes.
We explore how television broadcasting of unrelated criminal justice events affects sentencing. Exploiting as-good-as-random variation in news content before a verdict, we find that sentences are 3 months longer when the verdict is reached after coverage of crime. Sentences increase with media exposure to crime, not crime itself, and the effect tapers off quickly. Our results suggest that professional experience and expertise mitigate the effect of irrelevant external information. This paper highlights the influence of noise in the news cycle: media can temporarily influence decisions by changing what is top of the mind rather than signaling deeper changes in offending or societal concerns.
We explore how television broadcasting of unrelated criminal justice events affects sentencing. Exploiting as-good-as-random variation in news content before a verdict, we find that sentences are 3 months longer when the verdict is reached after coverage of crime. Sentences increase with media exposure to crime, not crime itself, and the effect tapers off quickly. Our results suggest that professional experience and expertise mitigate the effect of irrelevant external information. This paper highlights the influence of noise in the news cycle: media can temporarily influence decisions by changing what is top of the mind rather than signaling deeper changes in offending or societal concerns.
This paper models decisions to apply to and attend charter schools in Boston using a generalized Roy selection framework linking preferences to the achievement gains generated by charter attendance. The model is estimated with instruments based on randomized admission lotteries and distance to charter schools. Charter schools generate larger gains for disadvantaged students, but demand for charters is stronger among more advantaged students. Similarly, gains are inversely related to unobserved preferences for charters. As a result, counterfactual simulations indicate that charter expansion is likely to be most effective when accompanied by efforts to target students who are unlikely to apply.
This paper models decisions to apply to and attend charter schools in Boston using a generalized Roy selection framework linking preferences to the achievement gains generated by charter attendance. The model is estimated with instruments based on randomized admission lotteries and distance to charter schools. Charter schools generate larger gains for disadvantaged students, but demand for charters is stronger among more advantaged students. Similarly, gains are inversely related to unobserved preferences for charters. As a result, counterfactual simulations indicate that charter expansion is likely to be most effective when accompanied by efforts to target students who are unlikely to apply.
This paper studies how interest groups allocate campaign contributions when congressmen are connected by social ties. We establish conditions for the existence of a unique Nash equilibrium in pure strategies for the contribution game and characterize the associated allocation of the interest groups’ moneys. While the allocations are generally complex functions of the environment (the voting function, the legislators’ preferences, and the social network topology), they are simple, monotonically increasing functions of the respective legislators’ Katz-Bonacich centralities. Using data on the 109th–113th Congresses and on congressmen’s alumni connections, we estimate the model and find evidence supporting its predictions.
This paper studies how interest groups allocate campaign contributions when congressmen are connected by social ties. We establish conditions for the existence of a unique Nash equilibrium in pure strategies for the contribution game and characterize the associated allocation of the interest groups’ moneys. While the allocations are generally complex functions of the environment (the voting function, the legislators’ preferences, and the social network topology), they are simple, monotonically increasing functions of the respective legislators’ Katz-Bonacich centralities. Using data on the 109th–113th Congresses and on congressmen’s alumni connections, we estimate the model and find evidence supporting its predictions.
We examine heterogeneous treatment effects of a universal child care program in Germany by exploiting variation in attendance caused by a reform that led to a large expansion staggered across municipalities. Drawing on novel administrative data from the full population of compulsory school entry examinations, we find that children with lower (observed and unobserved) gains are more likely to select into child care than children with higher gains. Children from disadvantaged backgrounds are less likely to attend child care than children from advantaged backgrounds but have larger treatment effects because of their worse outcome when not enrolled in child care.
We analyze how academic experts and nonexperts forecast the results of 15 piece-rate and behavioral treatments in a real-effort task. The average forecast of experts closely predicts the experimental results, with a strong wisdom-of-crowds effect: the average forecast outperforms 96 percent of individual forecasts. Citations, academic rank, field, and contextual experience do not correlate with accuracy. Experts as a group do better than nonexperts, but not if accuracy is defined as rank-ordering treatments. Measures of effort, confidence, and revealed ability are predictive of forecast accuracy to some extent and allow us to identify “superforecasters” among the nonexperts.
We analyze how academic experts and nonexperts forecast the results of 15 piece-rate and behavioral treatments in a real-effort task. The average forecast of experts closely predicts the experimental results, with a strong wisdom-of-crowds effect: the average forecast outperforms 96 percent of individual forecasts. Citations, academic rank, field, and contextual experience do not correlate with accuracy. Experts as a group do better than nonexperts, but not if accuracy is defined as rank-ordering treatments. Measures of effort, confidence, and revealed ability are predictive of forecast accuracy to some extent and allow us to identify “superforecasters” among the nonexperts.
We examine how a 16-week cut in potential unemployment insurance (UI) duration in Missouri affected search behavior of UI recipients and the aggregate labor market. Using a regression discontinuity design (RDD), we estimate marginal effects of maximum duration on UI and nonemployment spells of 0.45 and 0.25, respectively. We simulate the unemployment rate implied by the RDD estimates assuming no market-level externalities. The implied response closely approximates the decline in the unemployment rate following the benefit cut, suggesting that, even in a period of high unemployment, the labor market absorbed the influx of workers without crowding out other job seekers.
This paper proposes a new methodology for analyzing nonlinear pricing data. We establish identification of the model primitives with a known tariff and characterize the model restrictions on observables. We propose a quantile-based nonparametric estimator that achieves consistency at the parametric rate. We introduce unobserved product heterogeneity with an unknown tariff and show how our identification and estimation results extend. A Monte Carlo study analyzes the robustness of our methodology to menus of two-part tariffs. Analysis of cellular service data assesses the performance of various pricing strategies. We discuss extensions to network effects, multiproduct firms, bundling, differentiated products, and oligopolies.
This paper proposes a new methodology for analyzing nonlinear pricing data. We establish identification of the model primitives with a known tariff and characterize the model restrictions on observables. We propose a quantile-based nonparametric estimator that achieves consistency at the parametric rate. We introduce unobserved product heterogeneity with an unknown tariff and show how our identification and estimation results extend. A Monte Carlo study analyzes the robustness of our methodology to menus of two-part tariffs. Analysis of cellular service data assesses the performance of various pricing strategies. We discuss extensions to network effects, multiproduct firms, bundling, differentiated products, and oligopolies.
This paper estimates a model of the effort decisions of students and teachers in a classroom setting to understand the performance of Mexican high school students on curriculum-based examinations. The model allows for student heterogeneity in initial mathematics preparation and knowledge preference and for teacher heterogeneity in instructional ability and preferences for student knowledge. Survey data include multiple measurements of student and teacher effort, student and teacher preferences, student initial knowledge, and teacher ability. The most important factor accounting for poor performance, the lack of sufficient prior preparation, suggests a mismatch between the curriculum content and entering grade-level mathematics knowledge.
This paper estimates a model of the effort decisions of students and teachers in a classroom setting to understand the performance of Mexican high school students on curriculum-based examinations. The model allows for student heterogeneity in initial mathematics preparation and knowledge preference and for teacher heterogeneity in instructional ability and preferences for student knowledge. Survey data include multiple measurements of student and teacher effort, student and teacher preferences, student initial knowledge, and teacher ability. The most important factor accounting for poor performance, the lack of sufficient prior preparation, suggests a mismatch between the curriculum content and entering grade-level mathematics knowledge.
When people can self-insure via migration, they may have less need for informal risk sharing. At the same time, informal insurance may reduce the need to migrate. To understand the joint determination of migration and risk sharing, I study a dynamic model of risk sharing with limited commitment frictions and endogenous temporary migration. First, I characterize the model. Second, I structurally estimate the model using the new ICRISAT panel from rural India. Third, I introduce a rural employment scheme. The policy reduces migration and decreases risk sharing, lowering the welfare gain of the policy.
We provide evidence that democracy has a positive effect on GDP per capita. Our dynamic panel strategy controls for country fixed effects and the rich dynamics of GDP, which otherwise confound the effect of democracy. To reduce measurement error, we introduce a new indicator of democracy that consolidates previous measures. Our baseline results show that democratizations increase GDP per capita by about 20 percent in the long run. We find similar effects using a propensity score reweighting strategy as well as an instrumental-variables strategy using regional waves of democratization. The effects are similar across different levels of development and appear to be driven by greater investments in capital, schooling, and health.
We explore the impact of allowing for outsourcing service delivery to the private sector within Indonesia’s largest targeted transfer program. In a field experiment across 572 municipalities, we find that allowing for outsourcing the last mile of food delivery reduced operating costs without sacrificing quality. However, the prices citizens paid were lower only where we modified the bidding rules to encourage more bidders. Higher rents are associated with greater entry despite elites’ efforts to block reform. In this context, the option to outsource and sufficient competition generated significant benefits relative to public distribution.
This paper considers equilibrium two-sided search with ex ante heterogeneous agents, vectors of attributes, and idiosyncratic match draws. The analysis applies to a large class of models, from the nontransferable utility case to the collective household model with bargaining, for which transferable utility is a special case. The approach is powerful for it identifies a simple algorithm that, in our numerical application, is found to rapidly converge to equilibrium. Our application explores the impact of equal opportunities for women in the labor market on female match incentives and the timing of marriage.
This paper considers equilibrium two-sided search with ex ante heterogeneous agents, vectors of attributes, and idiosyncratic match draws. The analysis applies to a large class of models, from the nontransferable utility case to the collective household model with bargaining, for which transferable utility is a special case. The approach is powerful for it identifies a simple algorithm that, in our numerical application, is found to rapidly converge to equilibrium. Our application explores the impact of equal opportunities for women in the labor market on female match incentives and the timing of marriage.
We document the economywide extent of misconduct among financial advisers and the associated labor market consequences. Seven percent of advisers have misconduct records, and this share reaches more than 15 percent at some of the largest firms. Roughly one-third of advisers with misconduct are repeat offenders. Approximately half of advisers lose their jobs after misconduct. The labor market partially undoes firm-level discipline by rehiring such advisers. Firms that persistently engage in misconduct coexist with firms that have clean records. We show that this phenomenon may be explained by some firms “specializing” in misconduct and catering to unsophisticated consumers.
We propose a difference-in-differences strategy to identify the existence of interjurisdictional tax competition. Our strategy rests on differences between desired tax levels determined by culture-specific preferences and equilibrium tax levels determined by fiscal externalities and by preferences. While preferences differ systematically between French-speaking and German-speaking Swiss municipalities, local income tax burdens exhibit smooth spatial gradients. To qualify the empirical evidence, we develop a theoretical model of strategic tax setting by local governments that anticipate the effects of taxes on the per capita income and the median “hedonic” income, two inextricable consequences of the sorting of heterogeneous individuals.
We propose a difference-in-differences strategy to identify the existence of interjurisdictional tax competition. Our strategy rests on differences between desired tax levels determined by culture-specific preferences and equilibrium tax levels determined by fiscal externalities and by preferences. While preferences differ systematically between French-speaking and German-speaking Swiss municipalities, local income tax burdens exhibit smooth spatial gradients. To qualify the empirical evidence, we develop a theoretical model of strategic tax setting by local governments that anticipate the effects of taxes on the per capita income and the median “hedonic” income, two inextricable consequences of the sorting of heterogeneous individuals.
Interbank networks amplified the contraction in lending during the Great Depression. Panics induced banks in the hinterland to withdraw interbank deposits from Federal Reserve member banks located in reserve and central reserve cities. These correspondent banks responded by curtailing lending to businesses. Between the peak in the summer of 1929 and the banking holiday in the winter of 1933, interbank amplification reduced aggregate commercial bank lending by an estimated 15 percent.
A key decision facing firms is the extent of control to exert over the different stages in their production processes. We develop and test a property rights model of firm boundary choices along the value chain. We construct firm-level measures of the upstreamness of integrated and nonintegrated inputs by combining information on firms’ production activities in more than 100 countries with input-output tables. Whether a firm integrates upstream or downstream suppliers depends crucially on the elasticity of demand it faces. Moreover, integration is shaped by the relative contractibility of stages along the value chain, as well as by the firm’s productivity.
China’s land reform in 1978–84 unleashed rapid growth in farm output and household income. In new data on reform timing in 914 counties, we find an immediate trend break in the fraction of male children following the reform. Among second births that followed a firstborn girl, sex ratios increased from 1.1 to 1.3 boys per girl in the 4 years following reform. Larger increases are found among families with more education. The land reform estimate is robust to controlling for the county-level rollout of the One Child Policy. Overall, we estimate land reform accounted for about 1 million missing girls.
We explore the first period of sustained decline in child mortality in the United States and provide estimates of the independent and combined effects of clean water and effective sewerage systems on under-5 mortality. Our case is Massachusetts, 1880–1920, when authorities developed a sewerage and water district in the Boston area. We find the two interventions were complementary and together account for approximately one-third of the decline in log child mortality during the 41 years. Our findings are relevant to the developing world and suggest that a piecemeal approach to infrastructure investments is unlikely to significantly improve child health.
This paper examines the importance of buyer-supplier relationships for firm performance. We develop a model in which firms outsource tasks and search for suppliers. Lower search and outsourcing costs lead firms to search more and find better suppliers, which in turn drives down marginal costs. We test the theory by exploiting the opening of a high-speed train line in Japan, which lowered the cost of passenger travel but left shipping costs unchanged. Using an exhaustive data set on firms’ buyer-seller linkages, we find significant improvements in firm performance as well as creation of buyer-seller links, consistent with the model.
We examine the effect of the establishment of the New York Stock Exchange (NYSE) clearinghouse in 1892 on counterparty risk using a novel historical experiment. During this period, the NYSE stocks were dual-listed on the Consolidated Stock Exchange (CSE), which already had a clearinghouse. Using identical securities on the CSE as a control, we find that the introduction of multilateral net settlement through a clearinghouse substantially reduced volatility of NYSE returns caused by settlement risk and increased asset values. Our results indicate that a clearinghouse can improve market stability and value through a reduction in network contagion and counterparty risk.
We examine the effect of the establishment of the New York Stock Exchange (NYSE) clearinghouse in 1892 on counterparty risk using a novel historical experiment. During this period, the NYSE stocks were dual-listed on the Consolidated Stock Exchange (CSE), which already had a clearinghouse. Using identical securities on the CSE as a control, we find that the introduction of multilateral net settlement through a clearinghouse substantially reduced volatility of NYSE returns caused by settlement risk and increased asset values. Our results indicate that a clearinghouse can improve market stability and value through a reduction in network contagion and counterparty risk.
We use the late nineteenth-century establishment of agricultural experiment stations at preexisting land-grant colleges across the United States to estimate the importance of proximity to research for productivity growth. Our analysis reveals that proximity to newly opened permanent stations affected land productivity for about 20 years and then subsequently declined until becoming largely absent today. We conclude that spatial frictions substantially reduced the rate of return to public research spending in the late nineteenth and early twentieth centuries, but such frictions significantly diminished as extension programs, automobiles, and telephones made it easier for discoveries to reach farther farms.
We present a model in which human capital investments occur over the life cycle and across generations, à la Becker and Tomes. The human capital technology features multiple stages of childhood investments, college, and life cycle accumulation. The model can explain a wide range of intergenerational relationships while remaining empirically consistent with cross-sectional inequality. Much of the latter is determined by early investments in children, so that borrowing constraints faced by young parents are important for understanding the persistence of economic status across generations. Education subsidies, especially early on, can significantly reduce the intergenerational persistence of economic status.
We design and implement a large-scale resume correspondence study to address limitations of existing field experiments testing for age discrimination that may bias their results. One limitation that may bias results is giving older and younger applicants similar experience to make them “otherwise comparable.” A second limitation is that greater unobserved differences in human capital investment of older applicants may bias the results against finding age discrimination. On the basis of over 40,000 job applications, we find robust evidence of age discrimination in hiring against older women, especially those near retirement age, but considerably less evidence of age discrimination against men.
We design and implement a large-scale resume correspondence study to address limitations of existing field experiments testing for age discrimination that may bias their results. One limitation that may bias results is giving older and younger applicants similar experience to make them “otherwise comparable.” A second limitation is that greater unobserved differences in human capital investment of older applicants may bias the results against finding age discrimination. On the basis of over 40,000 job applications, we find robust evidence of age discrimination in hiring against older women, especially those near retirement age, but considerably less evidence of age discrimination against men.
The standard new Keynesian model predicts that economies behave differently at the zero lower bound: completely wasteful government spending or forward guidance is very stimulative, and capital destruction or oil supply shocks are expansionary. I provide empirical evidence on this prediction and find it wanting: The Great East Japan Earthquake and oil supply shocks are contractionary at the zero lower bound. Modifications of the model that are consistent with this evidence also overturn other unusual policy predictions, such as large fiscal multipliers. My results suggest that many of the usual rules of economics continue to hold at zero nominal interest rates.
This paper examines whether propaganda broadcast over radio helped to change interethnic attitudes in postgenocide Rwanda. We exploit variation in exposure to the government’s radio propaganda due to the mountainous topography of Rwanda. Results of lab-in-the-field experiments show that individuals exposed to government propaganda have lower salience of ethnicity, have increased interethnic trust, and show more willingness to interact face-to-face with members of another ethnic group. Our results suggest that the observed improvement in interethnic behavior is not cosmetic and reflects a deeper change in interethnic attitudes. The findings provide some of the first quantitative evidence that the salience of ethnic identity can be manipulated by governments.
We nonparametrically estimate spillovers of properties financed by the Low Income Housing Tax Credit (LIHTC) onto neighborhood residents by developing a new difference-in-differences style estimator. LIHTC development revitalizes low-income neighborhoods, increasing house prices 6.5 percent, lowering crime rates, and attracting racially and income diverse populations. LIHTC development in higher-income areas causes house price declines of 2.5 percent and attracts lower-income households. Linking these price effects to a hedonic model of preferences, LIHTC developments in low-income areas cause aggregate welfare benefits of $116 million. Affordable housing development acts like a place-based policy and can revitalize low-income communities.
We nonparametrically estimate spillovers of properties financed by the Low Income Housing Tax Credit (LIHTC) onto neighborhood residents by developing a new difference-in-differences style estimator. LIHTC development revitalizes low-income neighborhoods, increasing house prices 6.5 percent, lowering crime rates, and attracting racially and income diverse populations. LIHTC development in higher-income areas causes house price declines of 2.5 percent and attracts lower-income households. Linking these price effects to a hedonic model of preferences, LIHTC developments in low-income areas cause aggregate welfare benefits of $116 million. Affordable housing development acts like a place-based policy and can revitalize low-income communities.
We introduce a new matching model to mimic two-sided exchange programs such as tuition and worker exchanges, in which export-import balances are required for longevity of programs. These exchanges use decentralized markets, making it difficult to achieve this goal. We introduce the two-sided top trading cycles, the unique mechanism that is balanced-efficient, worker-strategy-proof, acceptable, individually rational, and respecting priority bylaws regarding worker eligibility. Moreover, it encourages exchange, because full participation induces a dominant-strategy equilibrium for firms. We extend it to dynamic settings permitting tolerable yearly imbalances and demonstrate that its regular and tolerable versions perform considerably better than models of current practice.
Depression is the leading cause of illness and disability in adolescence. Many studies show a correlation between religiosity and mental health, yet the question remains whether the relationship is causal. We exploit within-school variation in adolescents’ peers to deal with selection into religiosity. We find robust effects of religiosity on depression that are stronger for the most depressed. These effects are not driven by the school social context; depression spreads among close friends rather than through broader peer groups that affect religiosity. Exploration of mechanisms suggests that religiosity buffers against stressors in ways in which school activities and friendships do not.
This paper explores racial differences in police use of force. On nonlethal uses of force, blacks and Hispanics are more than 50 percent more likely to experience some form of force in interactions with police. Adding controls that account for important context and civilian behavior reduces, but cannot fully explain, these disparities. On the most extreme use of force—officer-involved shootings—we find no racial differences either in the raw data or when contextual factors are taken into account. We argue that the patterns in the data are consistent with a model in which police officers are utility maximizers, a fraction of whom have a preference for discrimination, who incur relatively high expected costs of officer-involved shootings.
Using census microdata on multistate firms and their organizational forms, we estimate the impact of state taxes on business activity. For C corporations, employment and the number of establishments have short-run corporate tax elasticities of −0.4 to −0.5 and do not vary with changes in personal tax rates. Pass-through entity activities show tax elasticities of −0.2 to −0.4 with respect to personal tax rates and are invariant with respect to corporate tax rates. Capital shows similar patterns. Reallocation of productive resources to other states drives around half the effect. The responses are strongest for firms in tradable and footloose industries.
An increase in credit supply driven by looser lending constraints in the mortgage market is the key force behind four empirical features of the housing boom before the Great Recession: the unprecedented rise in home prices, the surge in household debt, the stability of debt relative to house values, and the fall in mortgage rates. These facts are more difficult to reconcile with the popular view that attributes the housing boom only to looser borrowing constraints associated with lower collateral requirements, because they shift the demand for credit.
We study how intelligence and personality affect the outcomes of groups, focusing on repeated interactions that provide the opportunity for profitable cooperation. Our experimental method creates two groups of subjects who have different levels of certain traits, such as higher or lower levels of Intelligence, Conscientiousness, and Agreeableness, but who are very similar otherwise. Intelligence has a large and positive long-run effect on cooperative behavior. The effect is strong when at the equilibrium of the repeated game there is a trade-off between short-run gains and long-run losses. Conscientiousness and Agreeableness have a natural, significant but transitory effect on cooperation rates.
We document a causal response of local retail prices to changes in local house prices, with elasticities of 15–20 percent across housing cycles. These price responses are largest in zip codes with many homeowners and are driven by changes in markups rather than local costs. We argue that markups rise with house prices because greater housing wealth reduces homeowners’ demand elasticity, and firms raise markups in response. Shopping data confirm that house price changes affect the price sensitivity of homeowners, but not that of renters. Our evidence suggests a new source of business cycle markup variation.
This paper investigates how tax changes for different income groups affect aggregate economic activity. I construct a measure of who received (or paid for) tax changes in the postwar period using tax return data from NBER’s TAXSIM. Variation in the income distribution across US states and federal tax changes generate variation in regional tax shocks that I exploit to test for heterogeneous effects. I find that the positive relationship between tax cuts and employment growth is largely driven by tax cuts for lower-income groups and that the effect of tax cuts for the top 10 percent on employment growth is small.
This paper investigates how tax changes for different income groups affect aggregate economic activity. I construct a measure of who received (or paid for) tax changes in the postwar period using tax return data from NBER’s TAXSIM. Variation in the income distribution across US states and federal tax changes generate variation in regional tax shocks that I exploit to test for heterogeneous effects. I find that the positive relationship between tax cuts and employment growth is largely driven by tax cuts for lower-income groups and that the effect of tax cuts for the top 10 percent on employment growth is small.
We develop an asset pricing model with flexible heterogeneity in asset demand across investors, designed to match institutional and household holdings. A portfolio choice model implies characteristics-based demand when returns have a factor structure and expected returns and factor loadings depend on the assets’ own characteristics. We propose an instrumental variables estimator for the characteristics-based demand system to address the endogeneity of demand and asset prices. Using US stock market data, we illustrate how the model could be used to understand the role of institutions in asset market movements, volatility, and predictability.
We show that psychological well-being in adulthood varies with circumstance in early life. Combining a time series of real producer prices of cocoa with a nationally representative household survey in Ghana, we find that a one standard deviation rise in the cocoa price in early life decreases the likelihood of severe mental distress in adulthood by 3 percentage points (half the mean prevalence) for cohorts born in cocoa-producing regions relative to those born in other regions. Impacts on related personality traits are consistent with this result. Maternal nutrition, reinforcing childhood investments, and adult circumstance are likely operative channels of impact.
We provide a framework for empirical analysis of negotiated-price markets. Using mortgage market data and a search and negotiation model, we characterize the welfare impact of search frictions and quantify the role of search costs and brand loyalty for market power. Search frictions reduce consumer surplus by $12/month/consumer, 28 percent of which can be associated with discrimination, 22 percent with inefficient matching, and 50 percent with search costs. Banks with large consumer bases have margins 70 percent higher than those with small consumer bases. The main source of this incumbency advantage is brand loyalty; however, price discrimination based on search frictions accounts for almost a third.
We outline a framework for the empirical analysis of signaling games based on three features: sorting, incentive compatibility, and beliefs. We apply it to document cheap-talk signaling in the use of round-number offers during negotiations. Using millions of online bargaining interactions, we show that items listed at multiples of $100 receive offers that are 8–12 percent lower but are 15–25 percent more likely to sell, demonstrating the trade-off requisite for incentive compatibility. Those same sellers are more likely to accept a similar offer, and buyers are more likely to investigate their listings, consistent with seller sorting and buyer belief updating.
Happiness is reported in ordered intervals (e.g., very, pretty, not too happy). We review and apply standard statistical results to determine when such data permit identification of two groups’ relative average happiness. The necessary conditions for nonparametric identification are strong and unlikely to ever be satisfied. Standard parametric approaches cannot identify this ranking unless the variances are exactly equal. If not, ordered probit findings can be reversed by lognormal transformations. For nine prominent happiness research areas, conditions for nonparametric identification are rejected and standard parametric results are reversed using plausible transformations. Tests for a common reporting function consistently reject.
We study the role of morality in debt repayment, using an experiment with the credit card customers of a large Islamic bank in Indonesia. In our main treatment, clients receive a text message stating that “non-repayment of debts by someone who is able to repay is an injustice.” This moral appeal decreases delinquency by 4.4 percentage points from a baseline of 66 percent and reduces default among customers with the highest ex ante credit risk. Additional treatments help benchmark the effects against direct financial incentives and rule out competing explanations, such as reminder effects, priming religion, and provision of new information.
We provide measures of ethnic and racial segregation in urban consumption. Using Yelp reviews, we estimate how spatial and social frictions influence restaurant visits within New York City. Transit time plays a first-order role in consumption choices, so consumption segregation partly reflects residential segregation. Social frictions also affect restaurant choices: individuals are less likely to visit venues in neighborhoods demographically different from their own. While spatial and social frictions jointly produce significant levels of consumption segregation, we find that restaurant consumption is only about half as segregated as residences. Consumption segregation owes more to social than spatial frictions.
We provide measures of ethnic and racial segregation in urban consumption. Using Yelp reviews, we estimate how spatial and social frictions influence restaurant visits within New York City. Transit time plays a first-order role in consumption choices, so consumption segregation partly reflects residential segregation. Social frictions also affect restaurant choices: individuals are less likely to visit venues in neighborhoods demographically different from their own. While spatial and social frictions jointly produce significant levels of consumption segregation, we find that restaurant consumption is only about half as segregated as residences. Consumption segregation owes more to social than spatial frictions.
While there is strong evidence that more productive plants select into exporting, the literature has struggled to identify export-related efficiency gains within plants. We show that this is due to the common use of revenue-based productivity measures (TFPR): more efficient producers tend to charge lower prices, leading to a downward bias in TFPR. Using census panels of Chilean, Colombian, and Mexican manufacturing plants, we find sizable efficiency gains after export entry based on efficiency measures that are not affected by output prices. Evidence suggests that a complementarity between exporting and investment in technology is an important driver of these gains.
Measurement error is ubiquitous in experimental work. It leads to imperfect statistical controls, attenuated estimated effects of elicited behaviors, and biased correlations between characteristics. We develop statistical techniques for handling experimental measurement error. These techniques are applied to data from the Caltech Cohort Study, which conducts repeated incentivized surveys of the Caltech student body. We replicate three classic experiments, demonstrating that results change substantially when measurement error is accounted for. Collectively, these results show that failing to properly account for measurement error may cause a field-wide bias leading scholars to identify “new” phenomena.
We study the political effects of mass emigration to the United States in the nineteenth century using data from Sweden. To instrument for total emigration over several decades, we exploit severe local frost shocks that sparked an initial wave of emigration, interacted with within-country travel costs. Our estimates show that emigration substantially increased the local demand for political change, as measured by labor movement membership, strike participation, and voting. Emigration also led to de facto political change, increasing welfare expenditures as well as the likelihood of adopting more inclusive political institutions.
During the Great Recession, US regions that experienced large declines in household debt also experienced large drops in consumption, employment, and wages. We develop a search and matching model in which tighter debt constraints raise the cost of investing in new job vacancies and so reduce job-finding rates and employment. On-the-job human capital accumulation is critical to generating sizable drops in employment: it increases the duration of the benefit flows from posting vacancies, thereby amplifying the employment drop from a credit tightening 10-fold relative to the standard model. Our model reproduces the salient cross-regional features of the US Great Recession.
Earnings nonresponse in household surveys is widespread, yet there is limited knowledge of how nonresponse biases earnings measures. We examine the consequences of nonresponse on earnings gaps and inequality using Current Population Survey individual records linked to administrative earnings data. The common assumption that earnings are missing at random is rejected. Nonresponse across the earnings distribution is U-shaped, highest in the left and right tails. Inequality measures differ between household and administrative data due in part to nonresponse. Nonresponse biases earnings differentials by race, gender, and education, particularly in the tails. Flexible copula-based models can account for nonrandom nonresponse.
Earnings nonresponse in household surveys is widespread, yet there is limited knowledge of how nonresponse biases earnings measures. We examine the consequences of nonresponse on earnings gaps and inequality using Current Population Survey individual records linked to administrative earnings data. The common assumption that earnings are missing at random is rejected. Nonresponse across the earnings distribution is U-shaped, highest in the left and right tails. Inequality measures differ between household and administrative data due in part to nonresponse. Nonresponse biases earnings differentials by race, gender, and education, particularly in the tails. Flexible copula-based models can account for nonrandom nonresponse.
We estimate the aggregate productivity gains from reducing barriers to internal labor migration in Indonesia, accounting for worker selection and spatial differences in human capital. We distinguish between movement costs, which mean workers will move only if they expect higher wages, and amenity differences, which mean some locations must pay more to attract workers. We find modest but important aggregate impacts. We estimate a 22 percent increase in labor productivity from removing all barriers. Reducing migration costs to the US level, a high-mobility benchmark, leads to a 7.1 percent productivity boost. These figures hide substantial heterogeneity. The origin population that benefits most sees a 104 percent increase in average earnings from a complete barrier removal, or a 25 percent gain from moving to the US benchmark.
We study the mechanics of cartel enforcement and its interaction with bidding constraints in the context of repeated procurement auctions. Under collusion, bidding constraints weaken cartels by limiting the scope of punishment. This yields a test of collusive behavior exploiting the counterintuitive prediction that introducing minimum prices can lower the winning-bid distribution. The model’s predictions are borne out in Japanese procurement data, where we find evidence that minimum prices weakened collusion. A robust design insight is that setting a minimum price at the bottom of the observed winning-bid distribution necessarily improves over a minimum price of zero.
We study the mechanics of cartel enforcement and its interaction with bidding constraints in the context of repeated procurement auctions. Under collusion, bidding constraints weaken cartels by limiting the scope of punishment. This yields a test of collusive behavior exploiting the counterintuitive prediction that introducing minimum prices can lower the winning-bid distribution. The model’s predictions are borne out in Japanese procurement data, where we find evidence that minimum prices weakened collusion. A robust design insight is that setting a minimum price at the bottom of the observed winning-bid distribution necessarily improves over a minimum price of zero.
We investigate the determinants of students’ university choice in Pakistan, with a focus on monetary returns, nonpecuniary factors enjoyed at school, and financial constraints. To mitigate the identification problem concerning the separation of preferences, expectations, and market constraints, we use rich data on subjective expectations, with direct measures of financial constraints, to estimate a life-cycle model of school choice jointly with school-specific expectations of dropping out. We find that labor market prospects play a small role. Instead, nonpecuniary outcomes, such as the school’s ideology, are the major determinants. Policy simulations suggest that relaxing financial constraints would have large welfare gains.
We investigate the determinants of students’ university choice in Pakistan, with a focus on monetary returns, nonpecuniary factors enjoyed at school, and financial constraints. To mitigate the identification problem concerning the separation of preferences, expectations, and market constraints, we use rich data on subjective expectations, with direct measures of financial constraints, to estimate a life-cycle model of school choice jointly with school-specific expectations of dropping out. We find that labor market prospects play a small role. Instead, nonpecuniary outcomes, such as the school’s ideology, are the major determinants. Policy simulations suggest that relaxing financial constraints would have large welfare gains.
We advocate a different approach to measure the gender gap, summarizing each distribution by suitable evaluative functions and computing the difference between the evaluations. Unlike the conventional approach, ours does not assume rank invariance. We discuss the decision-theoretic framework behind different functions and introduce measures based on entropy functions. We further adopt quantile-copula approaches to account for selection into full-time employment and discuss how to take into account nonmarket values in measuring the gap. The evolution of the gender gap depends on the measure of it and whether nonmarket values are incorporated. We further assess and challenge a variety of assumptions, hypotheses, and findings in the literature.
We advocate a different approach to measure the gender gap, summarizing each distribution by suitable evaluative functions and computing the difference between the evaluations. Unlike the conventional approach, ours does not assume rank invariance. We discuss the decision-theoretic framework behind different functions and introduce measures based on entropy functions. We further adopt quantile-copula approaches to account for selection into full-time employment and discuss how to take into account nonmarket values in measuring the gap. The evolution of the gender gap depends on the measure of it and whether nonmarket values are incorporated. We further assess and challenge a variety of assumptions, hypotheses, and findings in the literature.
We examine the equilibrium effects of college financial aid policies building an overlapping-generations life cycle model with education, labor supply, and saving decisions. Cognitive and noncognitive skills of children depend on parental education and skills and affect education and labor market outcomes. Education is funded by parental transfers that supplement grants, loans, and student labor supply. Crowding out of parental transfers by government programs is sizable and cannot be ignored. The current system of federal aid improves long-run welfare by 6 percent. More generous ability-tested grants would increase welfare and dominate both an expansion of student loans and a labor tax cut.
We examine the equilibrium effects of college financial aid policies building an overlapping-generations life cycle model with education, labor supply, and saving decisions. Cognitive and noncognitive skills of children depend on parental education and skills and affect education and labor market outcomes. Education is funded by parental transfers that supplement grants, loans, and student labor supply. Crowding out of parental transfers by government programs is sizable and cannot be ignored. The current system of federal aid improves long-run welfare by 6 percent. More generous ability-tested grants would increase welfare and dominate both an expansion of student loans and a labor tax cut.
Uncertainty about future economic and climate conditions substantially affects the choice of policies for managing interactions between the climate and the economy. We develop a framework of dynamic stochastic integration of climate and economy, and show that the social cost of carbon is substantially affected by both economic and climate risks and is a stochastic process with significant variation. We examine a wide but plausible range of values for critical parameters with robust results and show that large-scale computing makes it possible to analyze policies in models substantially more complex and realistic than usually used in the literature.
Technology has facilitated new, nontraditional work arrangements, including the ride-sharing company Uber. Uber drivers provide rides anytime they choose. Using data on hourly earnings and driving, we document driver utilization of this real-time flexibility. We propose that the value of flexibility can be measured as deriving from time variation in the drivers’ reservation wage. Measuring time variation in drivers’ reservation wages allows us to estimate the surplus and labor supply implications of Uber relative to alternative, less-flexible work arrangements. Despite other drawbacks to the Uber arrangement, we estimate that Uber drivers earn more than twice the surplus they would in less-flexible arrangements.
We use data from Denmark, Germany, Norway, the United Kingdom, and the United States to document the degree of educational assortative mating, how it evolves over time, and the extent to which it differs between countries. This descriptive analysis motivates and guides a decomposition analysis in which we quantify the contribution of various factors to the distribution of household income. We find that assortative mating accounts for a nonnegligible part of the cross-sectional inequality in household income in each country. However, changes in assortative mating over time barely move the time trends in household income inequality.
We develop frameworks for welfare analysis of Medicaid and apply them to the Oregon Health Insurance Experiment. Across different approaches, we estimate low-income uninsured adults’ willingness to pay for Medicaid between $0.5 and $1.2 per dollar of the resource cost of providing Medicaid; estimates of the expected transfer Medicaid provides to recipients are relatively stable across approaches, but estimates of its additional value from risk protection are more variable. We also estimate that the resource cost of providing Medicaid to an additional recipient is only 40 percent of Medicaid’s total cost; 60 percent of Medicaid spending is a transfer to providers of uncompensated care for the low-income uninsured.
We develop frameworks for welfare analysis of Medicaid and apply them to the Oregon Health Insurance Experiment. Across different approaches, we estimate low-income uninsured adults’ willingness to pay for Medicaid between $0.5 and $1.2 per dollar of the resource cost of providing Medicaid; estimates of the expected transfer Medicaid provides to recipients are relatively stable across approaches, but estimates of its additional value from risk protection are more variable. We also estimate that the resource cost of providing Medicaid to an additional recipient is only 40 percent of Medicaid’s total cost; 60 percent of Medicaid spending is a transfer to providers of uncompensated care for the low-income uninsured.
A positive demand shock for coltan, a mineral whose bulky output cannot be concealed, leads armed actors to create illicit customs and provide protection at coltan mines, where they settle as “stationary bandits.” A similar shock for gold, easy to conceal, leads to stationary bandits in the villages where income from gold is spent, where they introduce illicit mining visas, taxes, and administrations. Having a stationary bandit from a militia or the Congolese army increases welfare. These findings suggest that armed actors may create “essential functions of a state” to better expropriate, which, depending on their goals, can increase welfare.
In online procurement markets, projects are often allocated through a mechanism that allows buyers to take into account a seller’s nonprice characteristics as well as his bid. We design a methodology to recover primitives of the environment in the presence of unobserved seller heterogeneity while accommodating two important features of such markets: buyer-specific choice sets and the high turnover of sellers. We apply our method to data from an online market for programming services, to assess buyers’ welfare gains associated with the globalization enabled by the internet. We find that the internet enables buyers to substantially improve on their outside (local) option; many of the gains arise from access to the international markets.
The absence of a trend in hours worked in the postwar United States is an exception: across countries and historically, hours fall steadily by a little below 0.5% per year. Are steadily falling hours consistent with a stable utility function over consumption and leisure under balanced growth of the macroeconomic aggregates? Yes. We fully characterize the class of such functions and thus generalize the well-known “balanced-growth preferences” that demand constant (as opposed to falling) long-run hours. Key to falling hours is an income effect (of steady productivity growth on hours) that slightly outweighs the substitution effect.
Exploiting admission thresholds to the Bologna day care system, we show using a regression discontinuity (RD) design that one additional day care month at age 0–2 reduces intelligence quotient by 0.5% (4.7% of a standard deviation) at age 8–14 in a relatively affluent population. The magnitude of this negative effect increases with family income. Similar negative impacts are found for personality traits. These findings are consistent with the hypothesis from psychology that children in day care experience fewer one-to-one interactions with adults, with negative effects in families where such interactions are of higher quality. We embed this hypothesis in a model that lends structure to our RD design.
Exploiting admission thresholds to the Bologna day care system, we show using a regression discontinuity (RD) design that one additional day care month at age 0–2 reduces intelligence quotient by 0.5% (4.7% of a standard deviation) at age 8–14 in a relatively affluent population. The magnitude of this negative effect increases with family income. Similar negative impacts are found for personality traits. These findings are consistent with the hypothesis from psychology that children in day care experience fewer one-to-one interactions with adults, with negative effects in families where such interactions are of higher quality. We embed this hypothesis in a model that lends structure to our RD design.
Social insurance is often linked to marriage. Existing evidence suggests small marital responses to financial incentives and stems from settings where benefits are realized in the near future. I analyze how linking survivors insurance to marriage affects the marriage market. Exploiting Sweden’s elimination of survivors insurance, I demonstrate that severing this link (1) affected entry into marriage up to 50 years before expected payout, (2) raised the divorce rate by 10%, and (3) raised the assortativeness of matching. This suggests that marital behavior is a key component of couples’ strategies to plan for financial security in old age.
We study merger policy in a dynamic computational model in which firms can reduce costs through investment or through mergers. Firms invest or propose mergers according to the profitability of these strategies. An antitrust authority can block mergers at some cost. We examine the optimal policy for an antitrust authority that cannot commit to its future policy and approves mergers as they are proposed. We find that the optimal policy can differ substantially from a policy based on static welfare. In general, antitrust policy can greatly affect firms’ investment behavior, and firms’ investment behavior can greatly affect the optimal antitrust policy.
We study merger policy in a dynamic computational model in which firms can reduce costs through investment or through mergers. Firms invest or propose mergers according to the profitability of these strategies. An antitrust authority can block mergers at some cost. We examine the optimal policy for an antitrust authority that cannot commit to its future policy and approves mergers as they are proposed. We find that the optimal policy can differ substantially from a policy based on static welfare. In general, antitrust policy can greatly affect firms’ investment behavior, and firms’ investment behavior can greatly affect the optimal antitrust policy.
The Great Recession saw sharp drops in labor earnings and even larger declines in asset prices. How were the welfare losses from these declines distributed across different age groups? To address this question we construct an overlapping-generations general equilibrium model in which households face large aggregate shocks. A calibrated version of the model replicates observed dynamics for asset prices. Younger households experience larger earnings losses in a model Great Recession, but benefit from being able to buy assets at temporarily depressed prices. As a result, the model predicts that the young experience smaller welfare losses than older cohorts.
Although an auction of drilling rights is often cited as an example of common values, formal evidence has been limited by the problem of auction-level unobserved heterogeneity. We develop an empirical approach for first-price sealed-bid auctions with affiliated values, unobserved heterogeneity, and endogenous bidder entry. We show that important features of the model are nonparametrically identified and apply a semiparametric estimation approach to data from US offshore oil and gas lease auctions. We find that common values, affiliated private information, and unobserved heterogeneity are all present. Failing to account for unobserved heterogeneity obscures the evidence of common values. We examine implications of our estimates for the interaction between affiliation, the winner’s curse, the auction rules, and the number of bidders in determining the aggressiveness of bidding and seller revenue.
People often forget and sometimes fantasize. This paper reports a large-scale experiment on memory errors and their relation to preferential traits including time preference, attitudes toward risk and ambiguity, and psychological characteristics such as anticipatory feelings. We observe systematic incidences of false memory in favor of positive events and positive amnesia in forgetting past negative events. Both positive delusion and positive confabulation significantly relate to present bias, but this is not the case for positive amnesia. In an intraperson, multiple-self model, we demonstrate that positive false memory, rather than selective amnesia, serves to enhance confidence in one’s future self in equilibrium, thereby accounting for our experimental findings.
We study the impact of global food price shocks on local violence across Africa. In food-producing areas, higher prices reduce conflict over the control of territory (“factor conflict”) and increase conflict over the appropriation of surplus (“output conflict”). We argue that this difference arises because higher prices increase the opportunity cost of soldiering for producers while simultaneously inducing consumers to appropriate surplus as real wages fall. In areas without crop agriculture, higher prices increase both forms of conflict. We validate our local-level findings on output conflict using survey data. Our findings help reconcile a growing but ambiguous literature on the economic roots of conflict.
We develop a model of political cycles driven by time-varying risk aversion. Agents choose to work in the public or private sector and to vote Democratic or Republican. In equilibrium, when risk aversion is high, agents elect Democrats—the party promising more redistribution. The model predicts higher average stock market returns under Democratic presidencies, explaining the well-known “presidential puzzle.” The model can also explain why economic growth has been faster under Democratic presidencies. In the data, Democratic voters are more risk averse, and risk aversion declines during Democratic presidencies. Public workers vote Democratic, while entrepreneurs vote Republican, as the model predicts.
Billions of dollars have been spent on pilot programs searching for ways to reduce health care costs. I study one such program, in which hospitals pay doctors bonuses for reducing the total hospital costs of admitted Medicare patients. Doctors respond to the bonuses by becoming more likely to admit patients whose treatment can generate high bonuses and sorting healthier patients into participating hospitals. Conditional on patient health, however, doctors do not reduce costs or change procedure use. These results highlight the ability of doctors to game incentive schemes and the risks of basing nationwide health care reforms on pilot programs.
Firm volatilities comove strongly over time, and their common factor is the dispersion of the economy-wide firm size distribution. In the cross section, smaller firms and firms with a more concentrated customer base display higher volatility. Network effects are essential to explaining the joint evolution of the empirical firm size and firm volatility distributions. We propose and estimate a simple network model of firm volatility in which shocks to customers influence their suppliers. Larger suppliers have more customers, and customer-supplier links depend on customers’ size. The model produces distributions of firm volatility, size, and customer concentration consistent with the data.
This paper exploits variation in the adoption of copyrights within Italy—due to the timing of Napoléon’s military victories—to investigate the causal effects of copyrights on creativity. Baseline regressions compare changes in opera production across Italian states with and without copyrights. This analysis yields three main results. First, the adoption of copyrights led to a significant increase in the number of newly created operas. Second, copyrights raised the quality of new operas, measured both by their immediate success and by their longevity. Third, there were no benefits from copyright extensions beyond the life of the original creator.
Using employer-employee matched and firm production quantity and input data for Portuguese firms, we study the endogenous response of productivity to firm reorganizations as measured by changes in the number of management layers. We show that, as a result of an exogenous demand or productivity shock that makes the firm reorganize and add a management layer, quantity-based productivity increases by about 6%, while revenue-based productivity drops by around 3%. Such a reorganization makes the firm more productive but also increases the quantity produced to an extent that lowers the price charged by the firm and, as a result, its revenue-based productivity as well.
We present and empirically implement an equilibrium labor market search model where risk-averse workers facing medical expenditure shocks are matched with firms making health insurance coverage decisions. We use our estimated model to evaluate the equilibrium impact of many health care reform proposals, including the 2010 Affordable Care Act (ACA). We use the estimates of the early impact of the ACA as a model validation. We find that income-based subsidies for health insurance premiums are crucial for the sustainability of the ACA, while the ACA can still substantially reduce the uninsured rate without the individual or the employer mandate.
Exploiting variation across states and municipalities in the timing and details of midwifery laws introduced during the period 1900–1940 and using data assembled from various primary sources, we find that requiring midwives to be licensed reduced maternal mortality by 7%–8% and may have led to modest reductions in infant mortality. These estimates represent the strongest evidence to date that licensing restrictions can improve the health of consumers and are directly relevant to ongoing policy debates on the merits of licensing midwives.
For a search-theoretic model of the labor market, we seek conditions for the existence of a balanced growth path (BGP), where unemployment, vacancy, and worker’s transitions rates remain constant in the face of improvements in the production and search technologies. A BGP exists iff firm-worker matches are inspection goods and the quality of a match is drawn from a Pareto distribution. Declining search frictions contribute to growth with an intensity determined by the tail coefficient of the Pareto distribution. We develop a strategy to measure the rate of decline of search frictions and their contribution to growth.
This paper provides evidence that prices respond significantly more strongly to increases than to decreases in value-added taxes (VATs). First, using two plausibly exogenous VAT changes, we show that prices respond twice as much to VAT increases as to VAT decreases. Second, we show that this asymmetry results in higher equilibrium profits and markups. Third, we find that firms operating with low profit margins are particularly likely to respond asymmetrically to VAT changes. Fourth, these asymmetric price effects persist several years after VAT changes take place. Fifth, using all VAT changes in the European Union from 1996 to 2015, we find similar levels of asymmetry.
Using data from Duke University undergraduates, we make three main contributions to the literature. First, we show that data on earnings beliefs and probabilities of choosing particular occupations are highly informative of future earnings and occupations. Second, we show how beliefs data can be used to recover ex ante treatment effects and their relationship with individual choices. We find large differences in expected earnings across occupations and provide evidence of sorting on expected gains. Finally, nonpecuniary factors play an important role, with a sizable share of individuals willing to give up substantial amounts of earnings by not choosing their highest-paying occupation.
How much should society be willing to pay for reducing inequality? The standard approach to this normative question relates inequality aversion to risk aversion by treating inequality as an outcome of a lottery. However, in the presence of heterogeneous risk preferences, it is unclear whose preferences should be used for evaluating this lottery. This paper derives a social welfare function as a limit of an iterative procedure, in which each iteration constructs a lottery based on the certainty equivalents from the previous iteration. The limit of this procedure can be interpreted as the equally distributed equivalent of the initial allocation.
We propose a new framework for optimal experimentation, which we term the “A/B testing problem.” Our model departs from the existing literature by allowing for fat tails. Our key insight is that the optimal strategy depends on whether most gains accrue from typical innovations or from rare, unpredictable large successes. If the tails of the unobserved distribution of innovation quality are not too fat, the standard approach of using a few high-powered “big” experiments is optimal. However, if the distribution is very fat tailed, a “lean” strategy of trying more ideas, each with possibly smaller sample sizes, is preferred. Our theoretical results, along with an empirical analysis of Microsoft Bing’s EXP platform, suggest that simple changes to business practices could increase innovation productivity.
We study the theoretical properties and counterfactual predictions of a large class of general equilibrium trade and economic geography models. By combining aggregate factor supply and demand functions with market-clearing conditions, we prove that existence, uniqueness, and—given observed trade flows—the counterfactual predictions of any model within this class depend only on the demand and supply elasticities (“gravity constants”). Using a new “model-implied” instrumental variables approach, we estimate these gravity constants and use these estimates to compute the impact of a trade war between the United States and China.
This study presents evidence on the role of social environment for the formation of prosociality. We show that socioeconomic status (SES) as well as intensity of mother-child interaction and mothers’ prosocial attitudes are related to elementary school children’s prosociality. We also present evidence on a randomly assigned variation of the social environment, providing children with a mentor for 1 year. Our data reveal a significant and persistent increase in prosociality in the treatment relative to the control group. Moreover, enriching the social environment closes the prosociality gap between low- and high-SES children. A mediation analysis suggests that prosociality develops in response to prosocial role models and intense social interactions.
This study presents evidence on the role of social environment for the formation of prosociality. We show that socioeconomic status (SES) as well as intensity of mother-child interaction and mothers’ prosocial attitudes are related to elementary school children’s prosociality. We also present evidence on a randomly assigned variation of the social environment, providing children with a mentor for 1 year. Our data reveal a significant and persistent increase in prosociality in the treatment relative to the control group. Moreover, enriching the social environment closes the prosociality gap between low- and high-SES children. A mediation analysis suggests that prosociality develops in response to prosocial role models and intense social interactions.
Political booms, measured by the rise in governments’ popularity, predict financial crises above and beyond better known early warning indicators, such as credit booms. This predictive power, however, only holds in emerging economies. We argue that governments in developing countries have stronger incentives to “ride” unsound credit booms in order to boost their popularity, rather than implementing corrective policies that could prevent crises but are politically costly. We provide evidence of the relevance of this mechanism, partly by constructing a new cross-country data set on government popularity based on opinion polls.
Political booms, measured by the rise in governments’ popularity, predict financial crises above and beyond better known early warning indicators, such as credit booms. This predictive power, however, only holds in emerging economies. We argue that governments in developing countries have stronger incentives to “ride” unsound credit booms in order to boost their popularity, rather than implementing corrective policies that could prevent crises but are politically costly. We provide evidence of the relevance of this mechanism, partly by constructing a new cross-country data set on government popularity based on opinion polls.
We document an important consequence of bride price, a payment made by the groom to the bride’s family at marriage. Revisiting Indonesia’s school construction program, we find that among ethnic groups without the custom, it had no effect on girls’ schooling. Among ethnic groups with the custom, it had large positive effects. We show (theoretically and empirically) that this is because a daughter’s education, by increasing the amount of money parents receive at marriage, generates an additional incentive for parents to educate their daughters. We replicate these findings in Zambia, a country that had a similar large-scale school construction program.
We model household choice of schools under the Boston mechanism (BM) and develop a new method, applicable to a broad class of mechanisms, to fully solve the choice problem even if it is infeasible via the traditional method. We estimate the joint distribution of household preferences and sophistication types, using administrative data from Barcelona. Counterfactual policy analyses show that a change from BM in Barcelona to the deferred-acceptance mechanism would decrease average welfare by €1,020, while a change to the top-trading-cycles mechanism would increase average welfare by €460.
We model household choice of schools under the Boston mechanism (BM) and develop a new method, applicable to a broad class of mechanisms, to fully solve the choice problem even if it is infeasible via the traditional method. We estimate the joint distribution of household preferences and sophistication types, using administrative data from Barcelona. Counterfactual policy analyses show that a change from BM in Barcelona to the deferred-acceptance mechanism would decrease average welfare by €1,020, while a change to the top-trading-cycles mechanism would increase average welfare by €460.
In this paper, we extend Gary Becker’s empirical analysis of the marriage market to same-sex couples. We build an equilibrium model of the same-sex marriage market that allows for straightforward identification of the gains of marriage. We estimate the model with 2008–12 American Community Survey data on California and find that positive assortative mating is weaker for same-sex couples than for different-sex couples with respect to age and race. Positive assortative mating on education is stronger among female same-sex couples but comparable for male same-sex and different-sex couples. As regards labor market outcomes, our results suggest that specialization within the household mainly applies to different-sex couples.
In this paper, we extend Gary Becker’s empirical analysis of the marriage market to same-sex couples. We build an equilibrium model of the same-sex marriage market that allows for straightforward identification of the gains of marriage. We estimate the model with 2008–12 American Community Survey data on California and find that positive assortative mating is weaker for same-sex couples than for different-sex couples with respect to age and race. Positive assortative mating on education is stronger among female same-sex couples but comparable for male same-sex and different-sex couples. As regards labor market outcomes, our results suggest that specialization within the household mainly applies to different-sex couples.
Women’s reluctance to negotiate is often used to explain the gender wage gap, popularizing the push for women to “lean in” and negotiate more. Examining an environment in which women achieve positive profits when they choose to negotiate, we find that increased negotiations are not helpful. Women know when to ask: they enter negotiations resulting in positive profits and avoid negotiations resulting in negative profits. While the findings are similar for men, we find no evidence that men are more adept than women at knowing when to ask. Thus, our results caution against a greater push for women to negotiate.
We develop a general equilibrium model of asset prices in which benefits of technological innovation are distributed asymmetrically. Financial market participants do not capture all economic gains from innovation even when they own shares in innovating firms. Such gains accrue partly to the innovators, who cannot sell claims on proceeds from their future ideas. We show how the resulting inequality among agents can give rise to a high risk premium on the aggregate stock market, return comovement and average return differences among firms, and the failure of traditional representative agent asset pricing models to account for cross-sectional differences in risk premia.
We develop a general equilibrium model of asset prices in which benefits of technological innovation are distributed asymmetrically. Financial market participants do not capture all economic gains from innovation even when they own shares in innovating firms. Such gains accrue partly to the innovators, who cannot sell claims on proceeds from their future ideas. We show how the resulting inequality among agents can give rise to a high risk premium on the aggregate stock market, return comovement and average return differences among firms, and the failure of traditional representative agent asset pricing models to account for cross-sectional differences in risk premia.
We provide a new estimator for a broad class of equilibrium models of metropolitan housing markets with housing differentiated by quality. Quality is a latent variable that captures all features of a dwelling and its environment. We estimate the model for Chicago and New York, obtaining hedonic housing price functions for each quality level for each metropolitan area, stocks of each quality, and compensating variations required for a household of a given income in Chicago to be equally well off in New York.
We provide a new estimator for a broad class of equilibrium models of metropolitan housing markets with housing differentiated by quality. Quality is a latent variable that captures all features of a dwelling and its environment. We estimate the model for Chicago and New York, obtaining hedonic housing price functions for each quality level for each metropolitan area, stocks of each quality, and compensating variations required for a household of a given income in Chicago to be equally well off in New York.
We develop a dynastic human capital investment framework to study the importance of family borrowing constraints and uninsured labor market risk, as well as the process of intergenerational ability transmission, in determining human capital investments in children at different ages. We calibrate our model to data from the Children of the National Longitudinal Survey of Youth. While the effects of relaxing any borrowing limit at a single stage are modest, eliminating all life-cycle borrowing limits dramatically increases investments, earnings, and intergenerational mobility. The impacts of policy changes at college-going ages are greater when anticipated earlier, and shifting subsidies to earlier ages increases aggregate welfare and human capital.
We develop a dynamic limit pricing model where an incumbent repeatedly signals information relevant to a potential entrant’s expected profitability. The model is tractable, with a unique equilibrium under refinement, and dynamics contribute to large equilibrium price changes. We show that the model can explain why incumbent airlines cut prices dramatically on routes threatened with entry by Southwest, presenting new reduced-form evidence and a calibration that predicts a pattern of price changes across markets similar to the one observed in the data. We use our calibrated model to quantify the welfare effects of asymmetric information and subsidies designed to encourage Southwest’s entry.
We develop a dynamic limit pricing model where an incumbent repeatedly signals information relevant to a potential entrant’s expected profitability. The model is tractable, with a unique equilibrium under refinement, and dynamics contribute to large equilibrium price changes. We show that the model can explain why incumbent airlines cut prices dramatically on routes threatened with entry by Southwest, presenting new reduced-form evidence and a calibration that predicts a pattern of price changes across markets similar to the one observed in the data. We use our calibrated model to quantify the welfare effects of asymmetric information and subsidies designed to encourage Southwest’s entry.
Increasing evidence indicates the importance of management in determining firms' productivity. Yet causal evidence regarding the effectiveness of management practices is scarce, especially for skilled labor in the developed world. In a field experiment measuring commercial airline captains’ productivity, we test four distinct management practices: performance monitoring, performance feedback, target setting, and prosocial incentives. These practices—particularly monitoring and target setting—significantly increase captains' productivity on the targeted fuel-saving dimensions, with positive spillovers on job satisfaction and CO2 emissions. The study reveals an uncharted research opportunity to delve into the black box of firms to examine the determinants of productivity among skilled labor.
Using data on hospitals’ purchases across a large number of important product categories, we find that access to information on purchasing by peer hospitals leads to reductions in the prices hospitals negotiate for supplies. These effects are concentrated among hospitals previously paying relatively high prices for brands purchased in large volumes. Evidence from coronary stents suggests that transparency allows hospitals to resolve asymmetric information problems, but savings are limited in part by the stickiness of contracts in business-to-business settings. Savings are largest for physician preference items, where high-price, high-quantity hospital-brand combinations average 3.9% savings, versus 1.6% for commodities.
Using a random judge design and panel data from Norway, we estimate that imprisonment discourages further criminal behavior, with reoffense probabilities falling by 29 percentage points and criminal charges dropping by 11 over a 5-year period. Ordinary least squares mistakenly reaches the opposite conclusion. The decline is driven by individuals not working prior to incarceration; these individuals increase participation in employment programs and raise their future employment and earnings. Previously employed individuals experience lasting negative employment effects. These findings demonstrate that time spent in prison with a focus on rehabilitation can be preventive for a large segment of the criminal population.
We develop a new method to measure CEO behavior in large samples via a survey that collects high-frequency, high-dimensional diary data and a machine learning algorithm that estimates behavioral types. Applying this method to 1,114 CEOs in six countries reveals two types: “leaders,” who do multifunction, high-level meetings, and “managers,” who do individual meetings with core functions. Firms that hire leaders perform better, and it takes three years for a new CEO to make a difference. Structural estimates indicate that productivity differentials are due to mismatches rather than to leaders being better for all firms.
We provide microfoundations for dynamic skill formation with a model of investment in multiple skills, when jobs place different weights on skills. We show that credit constraints may affect investment even when workers do not exhaust their credit. Firms may invest in their workers’ skills even when there are many similar competitors. Firm and worker incentives can lead to overinvestment. Optimal skill accumulation resembles—but is not—learning by doing. An example shows that shocks to skill productivity benefiting new workers but lowering one skill’s value may adversely affect even relatively young workers, and adjustment may be discontinuous in age.
We use the Becker-DeGroot-Marschak (BDM) mechanism to estimate willingness to pay (WTP) for and heterogeneous impacts of clean water technology through a field experiment in Ghana. Although WTP is low relative to cost, demand is inelastic at low prices. Short-run treatment effects are positive throughout the WTP distribution. After 1 year, use and benefits are both increasing in WTP, with negative effects on low-WTP households. Combining estimated treatment effects with households’ WTP implies valuations of health benefits much smaller than typically used by policy makers. We explore differences between BDM and take-it-or-leave-it valuations and make recommendations for implementing BDM in the field.
We show that genetic endowments linked to educational attainment strongly and robustly predict wealth at retirement. The estimated relationship is not fully explained by flexibly controlling for education and labor income. We therefore investigate a host of additional mechanisms that could account for the gene-wealth gradient, including inheritances, mortality, risk preferences, portfolio decisions, beliefs about the probabilities of macroeconomic events, and planning horizons. We provide evidence that genetic endowments related to human capital accumulation are associated with wealth not only through educational attainment and labor income but also through a facility with complex financial decision-making.
We present results from an experiment that randomized the expansion of electric grid infrastructure in rural Kenya. Electricity distribution is a canonical example of a natural monopoly. Experimental variation in the number of connections, combined with administrative cost data, reveals considerable scale economies, as hypothesized. Randomized price offers indicate that demand for connections falls sharply with price. Among newly connected households, average electricity consumption is very low, implying low consumer surplus. We do not find meaningful medium-run impacts on economic and noneconomic outcomes. We discuss implications for current efforts to increase rural electrification in Kenya and highlight how various factors may affect interpretation.
How global are the gains from innovation? When firms operate plants in multiple countries, technological improvements developed in one location may be shared with foreign sites for efficiency gain. We develop a model that accounts for such transfer and apply it to measure returns to R&D investment for a panel of US multinationals. Our estimates indicate that innovation increases performance at firm locations beyond the innovating site: the median multinational firm realizes abroad 20% of the return to its US R&D investment, revealing a spatial disconnect between the costs and potential gains of policies that encourage multinationals’ US innovation.
We develop a framework to estimate willingness to pay for clean air from defensive investments on differentiated products. Applying this framework to scanner data on air purifier sales in China, we find that a household is willing to pay $1.34 annually to remove 1 μg/m3 of air pollution (PM10) and $32.7 annually to eliminate the pollution induced by the Huai River heating policy. Substantial heterogeneity is explained by income and exposure to information on air pollution. Using these estimates, we evaluate various environmental policies and quantify the value of recent air quality improvements since China declared a war on pollution in 2014.
In settings with uncertainty, tension exists between ex ante and ex post notions of fairness. Subjects in an experiment most commonly select the ex ante fair alternative ex ante and switch to the ex post fair alternative ex post. One potential explanation embraces consequentialism and construes reversals as time inconsistent. Another abandons consequentialism in favor of deontological (rule-based) ethics and thereby avoids the implication that revisions imply inconsistency. We test these explanations by examining contingent planning and the demand for commitment. Our findings suggest that the most common attitude toward fairness involves a time-consistent preference for applying a naive deontological heuristic.
The efficiency of publicly subsidized, privately provisioned social insurance programs depends on the interaction between strategic insurers and the subsidy mechanism. We study this interaction in the context of Medicare’s prescription drug coverage program. We find that the observed mechanism is successful in keeping “raise-the-subsidy” incentives relatively low, acts much like a flat voucher, and obtains a level of welfare close to that for the optimal voucher. Across a range of counterfactuals, we find that more efficient subsidy mechanisms share three features: they retain the marginal elasticity of demand, limit the exercise of market power, and preserve the link between prices and marginal costs.
There are striking differences in inequality and redistribution between the United States and Scandinavia. To study whether there are corresponding differences in social preferences, we conducted a large-scale international social preference experiment where Americans and Norwegians make distributive choices in identical environments. Combining the infrastructure of an international online labor market and that of a leading international data collection agency, we show that Americans and Norwegians differ significantly in fairness views, but not in the importance assigned to efficiency. We also provide causal evidence suggesting that fairness considerations are more fundamental for inequality acceptance than efficiency considerations.
Corrective taxes can solve many market failures, but actual policies frequently deviate from the theoretical ideal because of administrative or political constraints. We present a method to quantify the efficiency costs of constraints on externality-correcting policies or, more generally, the costs of imperfect pricing, using simple regression statistics. Under certain conditions, the R2 and the sum of squared residuals from a regression of true externalities on policy variables measure relative welfare gains from policies. We illustrate via four empirical applications: random mismeasurement of externalities, imperfect electricity pricing, heterogeneity in the longevity of energy-consuming durable goods, and imperfect spatial policy differentiation.
Information aversion—a preference-based fear of news flows—has rich implications for decisions involving information and risk-taking. It can explain key empirical patterns on how households pay attention to savings, namely, that investors observe their portfolios infrequently, particularly when stock prices are low or volatile. Receiving state-dependent alerts following sharp market downturns, such as during the financial crisis of 2008, improves welfare. Information-averse investors display an ostrich behavior: overhearing negative news prompts more inattention. Their fear of frequent news encourages them to hold undiversified portfolios.
We establish currency as an important factor shaping global portfolios. Using a new security-level data set, we demonstrate that investor holdings are biased toward their own currencies to such an extent that countries typically hold most of the foreign-debt securities denominated in their currency. While large firms issue in foreign currency and borrow from foreigners, most firms issue only in local currency and do not directly access foreign capital. These patterns hold broadly across countries except for the United States, as foreign investors hold significant shares of US dollar bonds. The share of dollar-denominated cross-border holdings surged after 2008.
Using a randomized experiment, this study investigates the impact of sustained investment in parenting, from pregnancy until age 5, in the context of extensive welfare provision. Providing the Preparing for Life program, incorporating home visiting, group parenting, and baby massage, to disadvantaged Irish families raised children’s cognitive and socioemotional/behavioral scores by two-thirds and one-quarter of a standard deviation, respectively. There were few differential effects by gender and stronger gains for firstborns and lower-resource households. The program also narrowed the socioeconomic gap in children’s skills. Analyses account for small sample size, differential attrition, multiple testing, contamination, and performance bias.
We study how heterogeneity in performance evaluations across supervisors affects employee and supervisor careers and firm outcomes using data on the performance system of a Scandinavian service sector firm. Supervisors vary widely in how they rate subordinates of similar quality. In our model, this ratings heterogeneity can arise because supervisors can differ in their ability to manage subordinates or in their leniency when rating subordinates. Furthermore, firms might or might not be informed about this heterogeneity. The evidence suggests that supervisor heterogeneity stems, in part, from real differences in managerial ability that firms are partially informed about.
We study the effects of industrial robots on US labor markets. We show theoretically that robots may reduce employment and wages and that their local impacts can be estimated using variation in exposure to robots—defined from industry-level advances in robotics and local industry employment. We estimate robust negative effects of robots on employment and wages across commuting zones. We also show that areas most exposed to robots after 1990 do not exhibit any differential trends before then, and robots’ impact is distinct from other capital and technologies. One more robot per thousand workers reduces the employment-to-population ratio by 0.2 percentage points and wages by 0.42%.
We revisit an old question: does industry labor reallocation affect the business cycle? Our empirical methodology exploits variation in a local labor market’s exposure to industry reallocation on the basis of the area’s initial industry composition and national industry employment trends for identification. Applied to confidential employment data over 1980–2014, we find sharp evidence of reallocation contributing to higher local area unemployment if it occurs during a national recession but little difference in outcomes during an expansion. A multiarea, multisector search-and-matching model with imperfect mobility across industries and downward nominal wage rigidity can reproduce these cross-sectional patterns.
We develop a model of gross capital flows and analyze their role in global financial stability. In our model, consistent with the data, when a country experiences asset fire sales, foreign investments exit (fickleness), while domestic investments abroad return home (retrenchment). When countries have symmetric expected returns and financial development, the benefits of retrenchment dominate the costs of fickleness and gross flows increase fire-sale prices. Fickleness, however, creates a coordination problem since it encourages local policy makers to restrict capital inflows. When countries are asymmetric, capital flows are driven by additional mechanisms—reach for safety and reach for yield—that can destabilize the receiving country.
For many products, platforms enable sellers to transact with buyers. We show that the competitive conditions among sellers shape the market structure in platform industries. If product market competition is tough, sellers avoid competitors by joining different platforms. This allows platforms to sustain high fees and explains why, for example, in some online markets, several homogeneous platforms segment the market. Instead, if product market competition is soft, agglomeration on a single platform emerges, and platforms fight for the dominant position. These insights give rise to novel predictions. For instance, market concentration and fees are negatively correlated in platform industries, which inverts the standard logic of competition.
Almost half of missing women in India are of postreproductive ages. Can intrahousehold gender inequality and asymmetry in poverty explain a portion of these missing women? Using a natural experiment, I link women’s intrahousehold bargaining power to their mortality risk. Using a structural household model, I estimate the age profile of women’s bargaining power and construct women’s relative poverty rates. I find that women’s bargaining power declines with age, with older women’s poverty rates closely matching their mortality rates by age. This suggests that many missing women might be accounted for by measuring poverty at the individual rather than the household level.
This paper quantifies and aggregates the multiple lifetime benefits of an influential high-quality early-childhood program with outcomes measured through midlife. Guided by economic theory, we supplement experimental data with nonexperimental data to forecast the life-cycle benefits and costs of the program. Our point estimate of the internal rate of return is 13.7%, with an associated benefit/cost ratio of 7.3. We account for model estimation and forecasting error and present estimates from extensive sensitivity analyses. This paper is a template for synthesizing experimental and nonexperimental data using economic theory to estimate the long-run life-cycle benefits of social programs.
Do states experience more peace under female leadership? We examine this question in the context of Europe over the fifteenth to twentieth centuries. We use gender of the firstborn and presence of a sister among previous monarchs as instruments for queenly rule. We find that polities led by queens engaged in war more than polities led by kings. While single queens were more likely to be attacked than single kings, married queens were more likely to attack than married kings. These results suggest asymmetries in the division of labor: married queens were more inclined to enlist their spouses in helping them rule, which enabled them ultimately to pursue more aggressive war policies.
I develop a model of agriculture on heterogeneous land to study the relation between trade, productivity, and welfare in Peru, where farmers face high internal and external trade costs. I quantify the model with new data on crop prices, yields, and land allocations. I then measure the effects of changes to trade opportunities. A policy of paving roads raises aggregate productivity (4.9%) and the median farmer’s welfare (2.7%), but increased competition from remote suppliers harms 20% of farmers. An increase in international grain prices spreads unevenly across regions, benefiting farmers but hurting urban consumers close to ports.
The Great Recession was a deep downturn with long-lasting effects on credit, employment, and output. While narratives about its causes abound, the persistence of gross domestic product below precrisis trends remains puzzling. We propose a simple persistence mechanism that can be quantified and combined with existing models. Our key premise is that agents do not know the true distribution of shocks but use data to estimate it nonparametrically. Then, transitory events, especially extreme ones, generate persistent changes in beliefs and macro outcomes. Embedding this mechanism in a neoclassical model, we find that it endogenously generates persistent drops in economic activity after tail events.
Candidate debates have a rich history and remain integral to contemporary campaign strategy. There is, however, little evidence that they affect the behavior of voters or politicians. The scarcity of political information in the developing world offers an attractive testing ground. Using experimental variation in Sierra Leone, we find that public debate screenings build political knowledge that changes the way people vote, which induces a campaign expenditure response by candidates and fosters accountability pressure over the spending of elected officials. Results show how political communication can trigger a chain of events that begins with voters and ultimately influences policy.
In a field experiment, we examine the impact of performance-based incentives for community college instructors. Instructor incentives improve student exam scores, course grades, and credit accumulation while reducing course dropout. Effects are largest among part-time adjunct instructors. During the program, instructor incentives have large positive spillovers, increasing completion rates and grades in students’ courses outside our study. One year after the program, instructor incentives increase transfer rates to 4-year colleges with no impact on 2-year college degrees. We find no evidence of complementarities between instructor incentives and student incentives. Finally, while instructors initially prefer gain-framed contracts over our loss-framed ones, preferences for loss-framed contracts significantly increase after experience with them.
We study the nonparametric identification of gross output production functions under the environment of the commonly employed proxy variable methods. We show that applying these methods to gross output requires additional sources of variation in the demand for flexible inputs (e.g., prices). Using a transformation of the firm’s first-order condition, we develop a new nonparametric identification strategy for gross output that can be employed even when additional sources of variation are not available. Monte Carlo evidence and estimates from Colombian and Chilean plant-level data show that our strategy performs well and is robust to deviations from the baseline setting.
How does the US labor market absorb low-skilled immigration? In the short run, high-immigration locations see their low-skilled labor force increase, native low-skilled wages decrease, and the relative price of rentals increase. Internal relocation dissipates this shock spatially. In the long run, the only lasting consequences are (a) worse labor market conditions for low-skilled natives who entered the labor force in high-immigration years, and (b) lower housing prices in high-immigrant locations, when immigrant workers disproportionately enter the construction sector and lower construction costs. I use a quantitative dynamic spatial equilibrium many-region model to obtain the policy-relevant counterfactuals.
We analyze the empirical content of the Roy model, stripped down to sector-specific unobserved heterogeneity and self-selection on the basis of potential outcomes. We characterize sharp bounds on the joint distribution of potential outcomes and testable implications of the Roy model. We apply these bounds to derive a measure of departure from Roy self-selection, so as to identify prime targets for intervention. Special emphasis is put on the case of binary outcomes. We analyze a Roy model of college major choice in Canada and Germany and take a new look at the underrepresentation of women in science, technology, engineering, and mathematics.
We build a model of the US economy with multiple aggregate shocks that generate fluctuations in equilibrium house prices. Through counterfactual experiments, we study the housing boom-bust around the Great Recession, with three main results. First, the main driver of movements in house prices and rents was a shift in beliefs, not a change in credit conditions. Second, the boom-bust in house prices explains half of the corresponding swings in nondurable expenditures through a wealth effect. Third, a large-scale debt forgiveness program would have done little to temper the collapse of house prices and expenditures but would have dramatically reduced foreclosures and induced a small, but persistent, increase in consumption during the recovery.
We provide microeconomic evidence on ethnic frictions and market efficiency, using dyadic data on managers and borrowers from a large Indian bank. We conjecture that, if exposure to religion-based communal violence intensifies intergroup animosity, riot exposure will lead to lending decisions that are more sensitive to a borrower’s religion. We find that riot-exposed Hindu branch managers lend relatively less to Muslim borrowers and that these loans are less likely to default, consistent with riot exposure exacerbating taste-based discrimination. This bias is persistent across a bank officer’s tenure, suggesting that the economic costs of ethnic conflict are long-lasting, potentially spanning across generations.
We study the impact of lead exposure from birth to adulthood and provide evidence on the mechanisms producing these effects. Following 800,000 children differentially exposed to the phaseout of leaded gasoline in Sweden, we find that even a low exposure affects long-run outcomes, that boys are more affected, and that changes in noncognitive skills explain a sizeable share of the impact on crime and human capital. The effects are greater above exposure thresholds still relevant for the general population, and reductions in exposure equivalent to the magnitude of the recent redefinition of elevated blood lead levels can increase earnings by 4%.
This paper introduces a new long-run data set based on archival data from historical waves of the Survey of Consumer Finances. Studying the joint distribution of household income and wealth, we expose the central importance of portfolio composition and asset prices for wealth dynamics in postwar America. Asset prices shift the wealth distribution because of systematic differences in household portfolios along the wealth distribution. Middle-class portfolios are dominated by housing, while rich households predominantly own business equity. Differential changes in equity and house prices shaped wealth dynamics in postwar America and decoupled the income and wealth distribution over extended periods.
The interaction of worsening fundamentals and strategic complementarities among investors renders identification of self-fulfilling runs challenging. We propose a dynamic model to show how exogenous variation in firms’ liability structures can be exploited to obtain variation in the strength of strategic complementarities. Applying this identification strategy to puttable securities offered by US life insurers, we find that at least 40% of the $18 billion run on life insurers by institutional investors during the 2007–8 crisis was amplified by self-fulfilling expectations. Our findings suggest that other contemporaneous runs in shadow banking by institutional investors may have had a self-fulfilling component.
We study the relationship between firms’ output quality and organizational structure. Using data on the production and transaction chain that makes up Peruvian fish meal manufacturing, we establish three results. First, firms integrate suppliers when the quality premium rises for exogenous reasons. Second, suppliers change their behavior to better maintain input quality when vertically integrated. Third, firms produce a higher share of high-quality output when weather and supplier availability shocks shift them into using integrated suppliers. Overall, our results indicate that quality upgrading is an important motive for integrating suppliers facing a quantity-quality trade-off, as classical theories of the firm predict.
In the United States, hospitals and physicians independently negotiate contracts with insurers. Therefore, a privately insured individual can be treated at an in-network hospital’s emergency department but receive a large unexpected bill from an out-of-network emergency physician working at that facility. Because patients do not choose their emergency physician, emergency physicians can remain out of network and charge high prices without losing patient volume. We illustrate that this strong outside option improves physicians’ bargaining power with insurers. We conclude by analyzing New York’s efforts to address out-of-network billing through binding arbitration between physicians and insurers over out-of-network payments. This intervention reduced out-of-network billing by 12.8 percentage points (88%).
Standard measures of productivity display enormous dispersion across farms in Africa. Crop yields and input intensities appear to vary greatly, seemingly in conflict with a model of efficient allocation across farms. In this paper, we present a theoretical framework for distinguishing between measurement error, unobserved heterogeneity, and potential misallocation. Using rich panel data from farms in Tanzania and Uganda, we estimate our model using a flexible specification in which we allow for several kinds of measurement error and heterogeneity. We find that measurement error and heterogeneity together account for a large fraction of the dispersion in measured productivity.
We study whether gender influences credit attribution for group work using observational data and two experiments. We use data from academic economists to test whether coauthorship matters differently for tenure for men and women. We find that, conditional on quality and other observables, men are tenured similarly regardless of whether they coauthor or solo author. Women, however, are less likely to receive tenure the more they coauthor. We then conduct two experiments that demonstrate that biases in credit attribution in settings without confounds exist. Taken together, our results are best explained by gender and stereotypes influencing credit attribution for group work.
This paper performs a structural analysis of sequential auctions with both synergy and affiliation across auctions. I propose a flexible yet tractable sequential auction model under the private value paradigm and establish its nonparametric identification, demonstrating an intuitive and general method for disentangling synergy from affiliation. After developing an estimation procedure closely tied to the identification steps, I apply it to data on adjacent oil and gas leases that are auctioned sequentially. I assess the role played by affiliation versus synergy in the observed allocation patterns and evaluate the counterfactual policy of bundled auctions.
Using data on liquidity shortfalls generated by the fraud and failure of a cash-in-transit firm, we demonstrate effects on firms’ trade credit usage. We find that firms manage liquidity shortages by increasing the amount of credit drawn from suppliers and decreasing the amount issued to customers. The compounded trade credit adjustments are on average of similar magnitude as corresponding adjustments in cash holdings, suggesting that trade credit positions are economically important sources of reserve liquidity for firms. The underlying mechanism in trade credit adjustments is in part due to shifts in overdue payments.
How much do a manager’s interpersonal skills with subordinates, which we call people management skills, affect employee outcomes? Are managers rewarded for having such skills? Using personnel data from a large high-tech firm, we show that survey-measured people management skills have a strong negative relation to employee turnover. A causal interpretation is reinforced by several research designs, including those exploiting new workers joining the firm and workers switching managers. However, people management skills do not consistently improve most observed nonattrition outcomes. Better people managers themselves receive higher subjective performance ratings, higher promotion rates, and larger salary increases.
This paper shows that liquidity regulation can trigger unintended credit booms in the presence of interbank market power. We consider a price setter and a continuum of price takers who trade reserves after the realization of idiosyncratic liquidity shocks. The price takers are endogenously less liquid and circumvent regulation by engaging in shadow banking, which leads to a reallocation of funding away from the more liquid price setter. This reallocation channel underlies the credit boom. Endogenous responses in bank liquidity ratios also affect the magnitude of the boom. We discuss extensions of the model and illustrate its quantitative performance with an application to China.
We provide an econometric framework for estimating a game of simultaneous entry and pricing decisions while allowing for correlations between unobserved cost and demand shocks. We use our framework to account for selection in the pricing stage. We estimate the model using data from the US airline industry and find that not accounting for endogenous entry leads to biased estimation of demand elasticities. We simulate a merger between American and US Airways and find that product repositioning and postmerger outcomes depend on how we model the characteristics of the merged firm as a function of the premerger firms’ characteristics.
Men who father their first child at a very young age are convicted of significantly fewer crimes in the first years after birth if the child is a son rather than a daughter. This leads to behavioral spillovers that reduce criminal convictions among other young men living in the same neighborhood, with the resulting crime multipliers affecting peers’ crime even after the primary impact on the focal individual has dissipated. Through social multipliers, prevention policies that target potential criminals at an early stage, therefore, lead to larger reductions in the cost of crime than suggested by primary effects alone.
We study the causal effect of incarceration on reoffending using discontinuities in North Carolina’s sentencing guidelines. A regression discontinuity analysis shows that 1 year of incarceration causes a reduction in the likelihood of being reincarcerated within 3, 5, and 8 years from sentencing by 44%, 29%, and 21%, respectively. To parse the potentially heterogeneous dose response relationship underlying these effects, we develop an econometric model of prison sentences and recidivism. We find that incarceration has meaningful reoffending-reducing average effects that diminish in incarceration length. As a result, budget-neutral reductions in sentence length combined with increases in incarceration rates can decrease recidivism.
This paper studies the industry-level and aggregate implications of financial development on international trade. I set up a multi-industry general equilibrium model of international trade with input-output linkages and heterogeneous firms subject to financial frictions. Industries differ in capital intensity, which leads to differences in external finance dependence. The model is parameterized to match key features of firm-level data. Financial development leads to substantial reallocation of international trade shares from labor- to capital-intensive industries, with minor effects at the aggregate level. These findings are consistent with estimates from cross-country industry-level and aggregate data.
We build a multicountry dynamic general equilibrium model to study the economic effects of the 2004 enlargement of the European Union. In our model, trade is costly and households of different skills and nationalities face costly forward-looking migration decisions. We exploit the timing of migration policy changes to identify the changes in migration costs. We find that the changes in migration and trade policy resulted in aggregate welfare gains but with heterogeneous effects across skill groups. We study the interaction between trade and migration policies and highlight the importance of trade for quantifying the welfare and migration effects of labor market integration.
We propose a methodology exploiting time diary data and “leisure Engel curves” to infer quality changes across leisure activities and measure the effects on the marginal return to leisure. We study leisure returns for men aged 21–30, who have shifted leisure toward video gaming and recreational computing and have had larger market work hour declines than older men or women since 2004. We show that recreational computing is distinctly a leisure luxury for younger men. By increasing the value of time, innovations to this leisure technology have lowered young men's work hours by 2%, or much of their work hours decline compared to older men's.
Online contests have become a prominent form of innovation procurement. Contest platforms often display a real-time public leaderboard to provide performance feedback. The impact of information disclosure on players’ decisions is theoretically ambiguous: some players may get discouraged and quit, while others may decide to keep working to remain competitive. We investigate the impact of a leaderboard on contest outcomes using two complementary approaches. First, we estimate a dynamic model using observational data and compare the equilibria with and without a leaderboard. Second, we present experimental evidence from student competitions. We find that a leaderboard on average improves competition outcomes.
Water fluoridation is a common but debated public policy. In this paper, we use Swedish registry data to study the causal effects of fluoride in drinking water. We exploit exogenous variation in natural fluoride stemming from variation in geological characteristics at water sources to identify its effects. First, we reconfirm the long-established positive effect of fluoride on dental health. Second, we estimate a zero effect on cognitive ability in contrast to several recent debated epidemiological studies. Third, fluoride is furthermore found to increase labor income. This effect is foremost driven by individuals from a lower socioeconomic background.
We study the optimal design of student financial aid as a function of parental income. We derive optimal financial aid formulas in a general model. We estimate a model of selection into college for the United States that comprises multidimensional heterogeneity, endogenous parental transfers, dropout, labor supply in college, and uncertain returns. We quantify optimal financial aid in the estimated model and find it is strongly declining in parental income even without distributional concerns. Equity and efficiency go hand in hand.
We estimate the economic surplus created by the Medicare Advantage program under its reformed competitive bidding rules. We use data on the universe of Medicare beneficiaries and develop a model of plan bidding that accounts for both market power and risk selection. We estimate that the Medicare Advantage program generates substantial surplus to participants (of $217 per enrollee-month), but that approximately two-thirds of this surplus is captured by insurers. We use the model to evaluate the impact of possible program changes, including changes that could increase competition and lead to lower profits and higher consumer surplus without raising taxpayer costs.
The use of order-flow information by financial firms has come to the forefront of the regulatory debate. Should a dealer who acquires information by taking client orders be allowed to use or share that information? We explore how information sharing affects dealers, clients, and issuer revenues in US Treasury auctions, in a model calibrated to auction results data, which we use to quantify counterfactuals. Sharing information reduces uncertainty about future value. With less uncertainty, risk-averse bidders bid more. For investors, the welfare effects of information sharing depend on how information is shared and how it affects asymmetry. The model shows that investors can benefit when dealers share information with each other, not when they share more with clients.
This paper argues that incumbent firms may acquire innovative targets solely to discontinue the target’s innovation projects and preempt future competition. We call such acquisitions “killer acquisitions.” We develop a model illustrating this phenomenon. Using pharmaceutical industry data, we show that acquired drug projects are less likely to be developed when they overlap with the acquirer’s existing product portfolio, especially when the acquirer’s market power is large because of weak competition or distant patent expiration. Conservative estimates indicate that 5.3%–7.4% of acquisitions in our sample are killer acquisitions. These acquisitions disproportionately occur just below thresholds for antitrust scrutiny.
We show that family background matters significantly for children’s accumulation of wealth and investor behavior as adults, even when removing the genetic connection between children and the parents raising them. The analysis is made possible by linking Korean-born children who were adopted at infancy by Norwegian parents to a population panel data set with detailed information on wealth and socioeconomic characteristics. The mechanism by which these Korean-Norwegian adoptees were assigned to adoptive families is known and effectively random. This mechanism allows us to estimate the causal effects from an adoptee being raised in one type of family versus another.
We extend the standard intergenerational mobility literature by examining the relationship between adult outcomes of children and the timing of parental income during their childhood years, using data from Norway. We find first that, conditional on permanent household income, the child’s human capital is higher in households where income is balanced between the early childhood and late childhood years than in households with a more imbalanced income profile. Second, compared to that in the early and late periods of childhood, income in the middle period has relatively low productivity.
We report a continuous-time experiment studying the Burdett-Judd model, whose unique Nash equilibrium (NE) features dispersed prices. Adaptive dynamics predict that the NE is stable for one of our parameter sets and unstable for another. The empirical price distribution is close to the NE distribution for the stable parameter set, but for the unstable parameter set it skews toward higher prices in its NE support interval. We offer an empirical definition of price cycles in terms of changes over time in robust measures of central tendency and dispersion, by which the data exhibit persistent cycles in both treatments but larger cycles for the unstable parameters. Results are roughly similar for professional and student sellers and for limited-information treatments.
Large firms play a pivotal role in international trade. We develop a multisector granular model of trade where sectors host a finite number of firms. Both aggregate and granular firm-level forces shape comparative advantage. The model is estimated using French microdata on firm domestic and export sales. We find that granularity accounts for about 20% of the sectoral variation in export intensity and is more pronounced in highly export-intensive sectors. An extension to a dynamic environment with both idiosyncratic and aggregate shocks reveals that firm dynamics plays a central role in shaping comparative advantage reversals observed in the data.
I examine the distributional consequences of technological change in a framework that nests Roy’s (1951) and Becker’s (1973) classical models: workers self-select into two sectors and then match with heterogeneous firms within each sector. In this model, technological change can be decomposed into changes in (i) the degree to which sectors covet the same skill sets and (ii) the extent to which output varies with skill in each sector. By deriving monotone comparative statics results for each of these two types of changes, I am able to provide a comprehensive account of the distributional consequences of technological change.
In economies with a continuum of agents of different types, pecuniary externalities are removed with market exchanges. Agents choose from among various possible prices they want to prevail in the future and buy or sell rights in these market exchanges for future trade. Each agent can choose the exchange it wants without regard to what any other agent is doing. But crucially, the right to trade in each and every exchange is priced. The fee structure has a per-unit price and quantity decomposition: a price, as determined by the exchange chosen, times the quantity of rights acquired.
This paper provides evidence of a novel facet of peer effects by showing that peer personality influences academic achievement. We exploit random assignment of students to university sections and find that students perform better in the presence of persistent peers. The impact of peer persistence is enduring, as students exposed to persistent peers at the beginning of their studies continue to achieve higher grades in subsequent periods. The personality peer effects that we document are distinct from other observable peer characteristics and suggest that peer personality traits affect human capital accumulation.
A central challenge in securing property rights is the subversion of justice. We present a model of a polluter whose discharges harm multiple owners, and we compare property rules, liability rules, and regulation on efficiency grounds. We provide conditions under which property rules are preferred to liability rules, thus verifying the Calabresi-Melamed conjecture. Regulation that enforces partial abatement may be preferred to either of the extreme rules. An empirical analysis of water quality in the United States before and after the Clean Water Act shows that the effects of regulation are consistent with several predictions of the model.
Are identities fungible? How do people come to identify with specific groups? This paper proposes a revealed preference approach, using food consumption to uncover ethnic and religious identity choices in India. We first show that consumption of identity goods responds to forces suggested by social identity research: group status and group salience. Moreover, identity choices respond to the cost of following the group’s prescribed behaviors. We propose and estimate a demand system to quantify the identity changes that followed India’s 1991 reforms. While social identity research has focused on status and salience, our results suggest that economic costs also play an important role.
We study the adoption, diffusion, and impacts of the Universal Product Code (UPC) between 1975 and 1992, during the initial years of the bar code system. We find evidence of network effects in the diffusion process. Matched-sample difference-in-differences estimates show that firm size and trademark registrations increase following UPC adoption by manufacturers. Industry-level import penetration also increases with domestic UPC adoption. Our findings suggest that bar codes, scanning, and related technologies helped stimulate variety-enhancing product innovation and encourage the growth of international retail supply chains.
Use of Internal Revenue Service (IRS) tax records improves researchers’ ability to track income trends, although the focus on taxable market income in this research excludes important income sources. Using IRS data in combination with other data sources, we explore the effect of measuring inequality levels and trends with income, including real accrued capital gains based on Haig-Simons principles. While median market income fell 10% from 1989 to 2016, median economic income increased by 26% using our Haig-Simons-based measure. Top 1% income shares were lower and increased by only about one-third of that estimated using previous approaches over this period.
We conducted a survey of high-ability college students and elicited beliefs about how their choice of major, and of whether to complete their degree, would affect an array of future events: earnings, employment, marriage prospects, potential spousal characteristics, and fertility. We find that students perceive large “returns” to human capital not only in their own future earnings but also in other dimensions (e.g., potential spouse’s earnings and fertility). We find evidence of students sorting into majors on the basis of these perceived returns. Family expectations are particularly important for female students’ major choices. In a follow-up survey conducted 6 years after the initial data collection, we find a close connection between expectations and current realizations.
We study the impact of simplification, deterrence, and tax morale on tax compliance. We ran four natural field experiments varying the communication of the tax administration with the universe of income taxpayers in Belgium throughout the tax process. A consistent picture emerges across experiments: (i) simplifying communication substantially increases compliance, (ii) deterrence messages have an additional positive effect, (iii) invoking tax morale is not effective and often backfires. A discontinuity in enforcement intensity, combined with the experimental variation, allows us to compare simplification with standard enforcement measures. We find that simplification is far more cost-effective, allowing for substantial savings on enforcement costs.
I build an investment-and-marriage model to provide a new explanation for the reversed college gender gap; that is, more women than men are going to college. The explanation is based on differential fecundity and an equilibrium marriage-market effect. The model also sheds light on gender-specific relationships between age at marriage and midlife personal income for American men and women and the evolving relationship between age at marriage and spousal income for American women.
A large literature has shown that asset quality may be signaled by retention or, in a separate literature, screened by liquidity. I present a general framework to analyze both instruments, offering conditions that characterize which instrument will be used in equilibrium. I then expand the private information to include not only asset quality but also seller patience, showing that both retention and liquidity may be used to fully separate both dimensions of private information. The expanded model offers new predictions about how price, quantity, and liquidity covary with each other and with seller private information.
Why are the east sides of formerly industrial cities more deprived? To answer this question, we use individual-level census data and create historical pollution patterns derived from the locations of 5,000 industrial chimneys and an atmospheric model. We show that this observation results from path-dependent neighborhood sorting that began during the Industrial Revolution, as prevailing winds blew pollution eastward. Past pollution explains up to 20% of observed neighborhood segregation in 2011, even though coal pollution stopped in the 1970s. We develop a quantitative model to identify the role of neighborhood effects and relocation rigidities underlying this persistence.
We present a new model of charitable giving where individuals regard out-of-pocket donations and the matches they induce as different. We show that match-price elasticities combine conventional price effects with the strength of warm glow, so that a match-price elasticity alone is insufficient to characterize preferences for giving. Match- and rebate-price elasticities will be different, but together they lead to new tests of underlying giving preferences. We estimate, for the first time, a match-price elasticity in a high-stakes setting together with a rebate elasticity induced by tax policy. The estimates reject extant models of giving but are consistent with the new theory.
Consumers rely on the price changes of goods in their grocery bundles when forming expectations about aggregate inflation. We use micro data that uniquely match individual expectations, detailed information about consumption bundles, and item-level prices. The weights consumers assign to price changes depend on the frequency of purchase, rather than expenditure share, and positive price changes loom larger than negative price changes. Prices of goods offered in the same store but not purchased do not affect inflation expectations, nor do other dimensions. Our results provide empirical guidance for models of expectations formation with heterogeneous consumers.
According to the Lucas-Stokey result, a government can structure its debt maturity to guarantee commitment to optimal fiscal policy by future governments. In this paper, we overturn this conclusion, showing that it does not generally hold in the same model and under the same definition of time consistency as in Lucas-Stokey. Our argument rests on the existence of an overlooked commitment problem that cannot be remedied with debt maturity: a government in the future will not necessarily tax above the peak of the Laffer curve, even if it is ex ante optimal to do so.
This paper provides stark evidence of hysteresis—the failure of an effect to reverse itself as its underlying cause is reversed—in energy demand. We estimate that half of the 23% reduction in residential electricity use caused by a 9-month-long policy that was imposed on millions of Brazilians has persisted for at least 12 years. We examine the implications of our finding by extending the traditional welfare analysis of corrective policies to allow for hysteresis. Our estimate highlights that failing to take hysteresis into account could severely bias the welfare evaluation of policies aimed at reducing (long-run) energy demand.
We conjecture that suppliers offer trade credit to ease competition in downstream markets. We show theoretically that suppliers that have to transfer surplus to high-bargaining-power customers would want to offer an increasing price schedule to preserve sales to other buyers. Suppliers can implement this using trade credit. Empirically, we find that suppliers grant trade credit to high-bargaining-power customers when they fear the cannibalization of sales to other customers. Exploiting a law that lowered the cost of offering trade credit, we show that higher provision of trade credit to high-bargaining-power customers leads to an expansion of the suppliers’ customer base.
Hotter years are associated with lower economic output in developing countries. We show that the effect of temperature on labor is an important part of the explanation. Using microdata from selected firms in India, we estimate reduced worker productivity and increased absenteeism on hot days. Climate control significantly mitigates productivity losses. In a national panel of Indian factories, annual plant output falls by about 2% per degree Celsius. This response appears to be driven by a reduction in the output elasticity of labor. Our estimates are large enough to explain previously observed output losses in cross-country panels.
When choice is stochastic, revealed preference analysis often relies on random utility models. However, it is impossible to infer preferences without assumptions on the distribution of utility noise. We show that this difficulty can be overcome by using response time data. A simple condition on response time distributions ensures that choices reveal preferences without distributional assumptions. Standard models from economics and psychology generate data fulfilling this condition. Sharper results are obtained under symmetric or Fechnerian noise, where response times allow uncovering preferences or predicting choice probabilities out of sample. Application of our tools is simple and generates remarkable prediction accuracy.
We study optimal income taxation when workers’ productivity is stochastic and evolves endogenously because of learning by doing. Learning by doing calls for higher wedges and alters the relation between wedges and tax rates. In a calibrated model, we find that reforming the US tax code brings significant welfare gains and that a simple tax code invariant to past incomes is approximately optimal. We isolate the role of learning by doing by comparing the aforementioned tax code to its counterpart in an economy that is identical to the calibrated one except for the exogeneity of the productivity process. Ignoring learning by doing calls for fundamentally different proposals.
We study how managers mitigate the negative impacts of environmental shocks. Pairing productivity data from a garment firm with granular measures of air pollution, we show that productivity suffers as a result of pollution shocks but that managers respond by reallocating particularly sensitive workers to improve worker-to-task matches, thus mitigating team productivity losses. Responses are smaller for more inattentive managers; these same managers are also least able to mitigate productivity declines. These patterns are confirmed by leveraging variation in opportunities for reallocation and comparing how close managers of differing attentiveness can get to the simulated production frontier by reallocating workers.
In cooperative property rights systems, workers jointly own and manage production, whereas in outside-ownership systems, an owner contracts workers. Despite a rich literature on how the allocation of property rights matters for specialization, efficiency, and equity, little causal evidence exists. During a land reform in El Salvador in 1980, the military government reorganized properties owned by individuals with cumulative landholdings over 500 hectares into cooperatives; properties below this threshold remained as outside-owned properties. Using the discontinuous probability of cooperative formation, I provide evidence on the effects of cooperative property rights relative to outside ownership on specialization, productivity, and worker equity.
We study the interest rates of privately securitized residential mortgages during the credit boom of the early 2000s. They reveal a sharp and persistent drop in the spread between mortgage and Treasury rates starting in the summer of 2003. The emergence of this mortgage rate conundrum immediately followed the collapse of an unprecedented refinancing wave, and it was more pronounced in the regions where that wave had grown faster. These same areas also experienced more originations of the nonconforming mortgages that boosted private label securitization after 2003. Mortgages originated after this shift are the first to show signs of deteriorating quality.
Many small firms lack the finance and marketing skills needed for growth. A standard approach is to train the entrepreneur in these skills. However, rather than requiring entrepreneurs to learn everything, an alternative is to move beyond the boundary of the entrepreneur and link firms to these skills in a marketplace through insourcing workers or outsourcing tasks to professionals. We conducted a randomized experiment in Nigeria to test the relative effectiveness of these different approaches in improving business practices. Insourcing and outsourcing both dominate business training and do at least as well as business consulting at half the cost.
Common resources may be managed with inefficient policies for the sake of equity. We study how rationing the commons shapes the efficiency and equity of resource use in the context of agricultural groundwater use in Rajasthan, India. We find that rationing binds on input use, such that farmers, despite trivial prices for water extraction, use roughly the socially optimal amount of water on average. The rationing regime is still grossly inefficient, because it misallocates water across farmers, lowering productivity. Pigouvian reform would increase agricultural surplus by 12% of household income yet fall well short of a Pareto improvement over rationing.
Despite substantial evidence that resources and outcomes are transmitted across generations, there has been limited inquiry into the extent to which antipoverty programs actually disrupt the cycle of bad outcomes. We leverage the rollout of the United States’s largest early-childhood program, Head Start, to estimate the effect of early-childhood exposure among mothers on their children’s long-term outcomes. We find evidence of intergenerational transmission of effects in the form of increased educational attainment, reduced teen pregnancy, and reduced criminal engagement in the second generation. These effects correspond to an estimated increase in discounted second-generation wages of 6%–11%, depending on specification. Exploration of earlier outcomes suggests an important role for changes in parenting behavior and potential noncognitive channels.
We describe how capital accumulation and the network structure of US production interact to amplify the effects of sectoral trend growth rates in total factor productivity and labor on trend GDP (gross domestic product) growth. We derive expressions that conveniently summarize this long-run amplification effect by way of sectoral multipliers. We estimate that sector-specific factors have historically accounted for approximately three-fourths of long-run changes in GDP growth. Trend GDP growth fell by nearly 3 percentage points over the postwar period, with especially significant contributions from the Construction sector in 1950–80 and the Durable Goods sector in 2000–2018. No sector has contributed any steady significant increase to the trend growth rate of GDP in the past 70 years.
We examine the nature of consumer demand for government-controlled online news outlets in Russia, testing whether such demand reflects a preference for progovernment ideological coverage or other factors unrelated to outlets’ ideological positions. We detect government-sensitive topics and measure outlets’ news-reporting decisions from news article texts, and we estimate a structural model of demand for news, using detailed browsing data that traces individual-level consumption. The average consumer has a distaste for progovernment ideology but a strong, persistent taste for state-owned outlets, primarily driven by third-party referrals and nonsensitive news content. We discuss implications for online media control and media power.
Intermediaries in decentralized markets can affect buyer welfare both directly, by reducing expenses for buyers with high search cost, and indirectly, through a search externality that affects the prices paid by buyers who do not use intermediaries. I investigate the magnitude of these effects in New York City’s trade-waste market, where buyers can search either by themselves or through a waste broker. Combining elements from the empirical search and procurement auction literatures, I construct and estimate a model for a decentralized market. Results from the model show that intermediaries improve welfare and benefit buyers in both the broker and the search markets.
Do elites capture foreign aid? This paper documents that aid disbursements to highly aid-dependent countries coincide with sharp increases in bank deposits in offshore financial centers known for bank secrecy and private wealth management but not in other financial centers. The estimates are not confounded by contemporaneous shocks—such as civil conflicts, natural disasters, and financial crises—and are robust to instrumenting using predetermined aid commitments. The implied leakage rate is around 7.5% at the sample mean and tends to increase with the ratio of aid to GDP. The findings are consistent with aid capture in the most aid-dependent countries.
If bidding in a pure common-value auction is costly and bidders do not know how many others are also bidding, all equilibria are in mixed strategies. Participation is probabilistic, and bid prices are dispersed. The symmetric equilibrium is unique and yields simple analytic expressions. We use them to, for example, show that bid prices exhibit negative skewness. The expressions are further used to estimate the model based on bidding on a Standard & Poor’s 500 security. We find that the number of bidders declined over time, making liquidity supply fragile.
How does banking competition affect credit provision and growth? How does it affect financial stability? In order to identify the causal effects of banking competition, we exploit a discontinuity in bank capital requirements during the nineteenth-century National Banking Era. We show that banks operating in markets with lower entry barriers extend more credit. The resulting credit expansion, in turn, is associated with additional real economic activity. However, banks in markets with lower entry barriers also take more risk and are more likely to default. Thus, we provide causal evidence that banking competition can cause both growth and financial instability.
We investigate the effect of welfare reform on intergenerational welfare participation, using mother-daughter pairs in the Panel Study of Income Dynamics. We find that a mother’s Aid to Families with Dependent Children/Temporary Assistance for Needy Families (AFDC/TANF) participation increased her daughter’s odds of adult participation in that program by roughly 25 percentage points or more, but that welfare reform attenuated this transmission by at least 50%. However, there is no diminution of transmission after welfare reform when we consider the wider safety net or other outcomes. Daughters who grew up with mothers on AFDC/TANF were no better off after reform, with substitution toward other welfare programs over generations.
We provide a parsimonious and unified explanation for randomized selling mechanisms widely used in practice yet commonly perceived as puzzling. Optimality of randomization in the form of conflation and rationing implies that revenue under market-clearing pricing is nonconcave. Randomization is implementable via opaque pricing and underpricing. Relative to market-clearing pricing, randomization increases the equilibrium quantity and quality of goods sold and, consequently, may increase consumer surplus. For fixed quantities, resale increases consumer surplus. However, resale can decrease the equilibrium quantity and quality of goods sold. Thus, resale prohibition, which always benefits the seller, may also increase consumer surplus.
We show that labor market transaction costs explain why the smallest farms are more efficient than slightly larger farms in most low-income countries and that increases in machine capacity with operational scale result in the globally observed rising upper tail of productivity. We find evidence consistent with these mechanisms using Indian data, and we show that if all Indian farms were at the minimum scale required to maximize the return on land, the number of farms would be reduced by 82% and income per farm worker would rise by 68%.
We provide a method to estimate resource shares—the fraction of total household expenditure allocated to each household member—using linear (e.g., ordinary least squares) estimation of Engel curves. The method is a linear reframing of the 2013 nonlinear model of Dunbar, Lewbel, and Pendakur, extended to allow single-parent and other complex households, scale economies in assignable goods, and complementarities between nonassignable goods and supplemented with a linear identification test. We apply the model to data from 12 countries and investigate resource shares, gender gaps, and poverty at the individual level. We reject equal sharing and find large gender gaps in resource shares, and consequently in poverty rates, in some countries.
We provide a unifying empirical framework to study why crime reductions occurred due to a sequence of state-level dropout age reforms enacted between 1980 and 2010 in the United States. Because the reforms changed the shape of crime-age profiles, they generate both a short-term incapacitation effect and a more sustained crime-reducing effect. In contrast to previous research looking at earlier US education reforms, we find that reform-induced crime reduction does not arise primarily from education improvements. Decomposing short- and long-run effects, the observed longer-run effect for the post-1980 education reforms is primarily attributed to dynamic incapacitation.
Economic models are evaluated by testing the correctness of their predictions. We suggest an additional measure, “completeness”: the fraction of the predictable variation in the data that the model captures. We calculate the completeness of prominent models in three problems from experimental economics: assigning certainty equivalents to lotteries, predicting initial play in games, and predicting human generation of random sequences. The completeness measure reveals new insights about these models, including how much room there is for improving their predictions.
Teachers and mentors in creative fields shape their students’ skills and views of the craft and thus the work they produce. How significant and persistent is this influence? Are there consequences for the variety and quality of students’ inventive output? We study these questions in the context of Western music composition over five centuries, during which musical lineages are well documented, the content of composers’ work can be directly compared, and its lasting value can be measured. We find strong evidence of influence, document when it arises and persists, and evaluate its consequences. The results provide insight into where creative ideas come from, why certain ideas get produced as opposed to others, and what the ramifications might be.
The conventional theory about the origin of the state is that the adoption of farming increased land productivity, which led to the production of food surplus. This surplus was a prerequisite for the emergence of tax-levying elites and, eventually, states. We challenge this theory and propose that hierarchy arose as a result of the shift to dependence on appropriable cereal grains. Our empirical investigation, utilizing multiple data sets spanning several millennia, demonstrates a causal effect of the cultivation of cereals on hierarchy, without finding a similar effect for land productivity. We further support our claims with several case studies.
Lack of commitment at the time of auction to repayment of imminently maturing debt can generate a run on debt and immediate default. We show that the same lack of commitment leads to other possible self-fulfilling crises, including issuance of more debt at depressed prices, or a “sudden stop” (forced austerity) in which debt issuance is sharply curtailed. Both outcomes stem from the government's incentive to eliminate uncertainty about imminent payments at the time of auction by altering the level of debt issuance. These outcomes generate a large increase in spread volatility in both a 1-period and a multiperiod quantitative debt model.
We examine gender differences in misconduct punishment in the financial advisory industry. There is a “gender punishment gap”: following an incident of misconduct, female advisers are 20% more likely to lose their jobs and 30% less likely to find new jobs, relative to male advisers. The gender punishment gap is not driven by gender differences in occupation, productivity, nature of misconduct, or recidivism. The gap in hiring and firing dissipates at firms with a greater percentage of female managers and executives. We also explore the differential treatment of ethnic minority men and find similar patterns of “in-group” tolerance.
We provide new theory and evidence on the role of external and internal integration in structural transformation and economic development, using Argentina’s integration into the world economy in the late nineteenth century. Our theoretical model provides microfoundations for a spatial Balassa-Samuelson effect, in which locations closer to world markets have higher population densities, urban population shares, relative prices of nontraded goods, and land prices relative to wages, as well as specializing in traded goods that are transport-cost sensitive. We estimate the model’s parameters, provide evidence in support of this spatial Balassa-Samuelson mechanism, and find substantial effects of both external and internal integration on economic development.
We document evidence of widespread collusion among construction firms in Japan using a novel data set covering most of the construction projects procured by the Japanese national government. Our data set contains information on about 42,000 auctions whose award amount sums to about $40 billion. We identify collusion by focusing on rebids that occur for auctions in which all (initial) bids fail to meet the secret reserve price. We identify more than 1,000 firms whose conduct is inconsistent with competitive behavior. These bidders were awarded about 15,000 projects, or about 37% of the total number of projects in our sample.
We document quasi-experimental evidence against the common assumption in the matching literature that agents have full information on their own preferences. In Germany’s university admissions, the first stages of the Gale-Shapley algorithm are implemented in real time, allowing for multiple offers per student. We demonstrate that nonexploding early offers are accepted more often than later offers, despite not being more desirable. These results, together with survey evidence and a theoretical model, are consistent with students’ costly discovery of preferences. A novel dynamic multioffer mechanism that batches early offers improves matching efficiency by informing students of offer availability before preference discovery.
We study how different forms of communication influence inflation expectations in a randomized controlled trial using nearly 20,000 US individuals. We elicit individuals’ inflation expectations and then provide eight different forms of information regarding inflation. Reading the actual Federal Open Market Committee (FOMC) statement has about the same average effect on expectations as simply being told about the Federal Reserve’s inflation target. Reading news articles about the most recent FOMC meetings results in a forecast revision that is smaller by half. This exogenous variation in inflation expectations has subsequent effects on household spending reported in scanner and survey data.
We study how signaling affects equilibrium outcomes and welfare in an online credit market, using detailed data on loan characteristics and borrower repayment. We build and estimate an equilibrium model in which a borrower may signal her default risk through the reserve interest rate. Comparing markets with and without signaling relative to the benchmark with no asymmetric information, we find that adverse selection destroys as much as 34% of total surplus, up to 78% of which can be restored with signaling. We also estimate backward-bending supply curves for some markets, consistent with the prediction made by Stiglitz and Weiss in 1981.
This paper examines the long-term and spillover effects of management interventions on firm performance. Under the Training Within Industry (TWI) program, the US government provided management training to firms involved in war production between 1940 and 1945. Using a newly collected panel data set on all 11,575 US firms that applied to the program, we find that the TWI training had positive and long-lasting effects on firm performance and the adoption of beneficial managerial practices. Moreover, it generated complementarities among different types of training and had positive spillover effects on the supply chain of trained firms.
The quality of the match between students and schools affects learning, but little is known about the magnitude of these effects or how they respond to changes in market structure. I develop a quantitative equilibrium model of school competition with horizontal competition in match quality. I estimate the model using data from Pakistan, a country with high private enrollment, and (1) quantify the importance of good matches, (2) show that profit-maximizing private schools’ choices of quality advantage wealthier students, increasing inequality and reducing welfare and learning, and (3) provide intuition for when interventions in the market are valuable.
Macroeconomists increasingly use external sources of exogenous variation for causal inference. However, unless such external instruments (proxies) capture the underlying shock without measurement error, existing methods are silent on the importance of that shock for macroeconomic fluctuations. We show that, in a general moving-average model with external instruments, variance decompositions for the instrumented shock are interval-identified, with informative bounds. Various additional restrictions guarantee point identification of both variance and historical decompositions. Unlike structural vector autoregression analysis, our methods do not require invertibility. Applied to US data, they give a tight upper bound on the importance of monetary shocks for inflation dynamics.
This paper considers top income taxation when (i) new ideas drive economic growth, (ii) the reward for successful innovation is a top income, and (iii) innovation cannot be perfectly targeted by a research subsidy—think about the business methods of Walmart, the creation of Uber, or the “idea” of Amazon. These conditions lead to a new force affecting the optimal top tax rate: by slowing the creation of new ideas that drive aggregate GDP, top income taxation reduces everyone’s income, not just income at the top. This force sharply constrains both revenue-maximizing and welfare-maximizing top tax rates.
We develop a theory of collective brand reputation for markets in which product quality is jointly determined by local and global players. In a repeated game of imperfect public monitoring, we model collective branding as an aggregation of quality signals generated in different markets. Such aggregation yields a beneficial informativeness effect for incentivizing the global player. It however also induces harmful free-riding by local, market-specific players. The resulting trade-off yields a theory of optimal brand size and revenue sharing that applies to platform markets, franchising, licensing, umbrella branding, and firms with team production.
Although there are many competing explanations for the Industrial Revolution, there has been no effort to evaluate them econometrically. This paper analyzes how the very different patterns of growth across the counties of England between the 1760s and 1830s can be explained by a wide range of potential variables. We find that industrialization occurred in areas that began with low wages but high mechanical skills, whereas other variables, such as literacy, banks, and proximity to coal, have little explanatory power. Against the view that living standards were stagnant during the Industrial Revolution, we find that real wages rose sharply in the industrializing north and declined in the previously prosperous south.
How should countries cooperate in setting fiscal and trade policies when government expenditures must be financed with distorting taxes? We show that even if countries cannot make explicit transfers to each other, every point on the Pareto frontier is production efficient, so that international trade and capital flows should be effectively free. Trade agreements must be supplemented with fiscal policy agreements. Residence-based income tax systems have advantages over source-based systems. Taxing all household asset income at a country-specific uniform rate and setting the corporate income tax to zero yield efficient outcomes. Value-added taxes should be adjusted at the border.
We study the welfare implications of personalized pricing implemented with machine learning. We use data from a randomized controlled pricing field experiment to construct personalized prices and validate these in the field. We find that unexercised market power increases profit by 55%. Personalization improves expected profits by an additional 19% and by 86% relative to the nonoptimized price. While total consumer surplus declines under personalized pricing, over 60% of consumers benefit from personalization. Under some inequity-averse welfare functions, consumer welfare may even increase. Simulations reveal a nonmonotonic relationship between the granularity of data and consumer surplus under personalization.
I propose a methodology for constructing counterfactuals with respect to changes in policy rules that does not require fully specifying a particular model yet is not subject to Lucas critique. It applies to a class of dynamic stochastic models whose equilibria are well approximated by a linear representation. It rests on the insight that many such models satisfy a principle of counterfactual equivalence: they are observationally equivalent under a benchmark policy and yield an identical counterfactual equilibrium under an alternative one.
We consider a model of oligopolistic competition in a market with search frictions, in which competing firms with products of unknown quality advertise how much information a consumerâs visit will glean. In the unique symmetric equilibrium of this game, the countervailing incentives of attraction and persuasion yield a payoff function for each firm that is linear in the firmâs realized effective value. If the expected quality of the products is sufficiently high (or competition is sufficiently fierce), this corresponds to full information: firms provide the first-best level of information. If not, this corresponds to information dispersion: firms randomize over signals.
No region of the United States fared worse over the postwar period than the Rust Belt. This paper analyzes how much of its decline can be accounted for by the persistent labor market conflict that characterized Rust Belt union-management relations. We develop a multisector, multiregion, dynamic general equilibrium model in which labor market conflict leads to strikes, wage premia, lower investment, and lower productivity growth. These lead to shrinking Rust Belt industries and to workers moving out of the Rust Belt. Labor conflict accounts for half of the decline in the region’s share of manufacturing employment. Foreign competition plays a smaller role, and its effects are concentrated after most of the region’s decline had already occurred.
We study an impatient, risk-neutral government that cannot commit to a particular debt path, financed by competitive lenders. In equilibrium, debt adjusts slowly toward a debt-to-income target, exacerbating booms and busts. Strikingly, gains from trade dissipate when trading is continuous, leaving the government no better off than in financial autarky, owing to a sovereign “debt ratchet effect.” Moreover, citizens who are more patient than their government are strictly harmed. We characterize equilibrium debt dynamics, ergodics, and comparative statics when income follows a geometric Brownian motion and analyze devices that allow the sovereign to recapture gains from trade.
I characterize the dynamics of incentives in an optimal contract with investment delegation, moral hazard, and uncertainty about the agent’s productivity. The principal increases the agent’s incentives after good performance in order to delegate more capital to an agent with higher perceived productivity, thus implementing a convex pay-for-performance scheme. Moreover, the principal commits to reduce the agent’s future incentives in order to mitigate ex ante investment distortions. Methodologically, I provide a duality-based strategy to overcome technical challenges common to continuous-time contracting models with state variables. I also derive a sufficient condition to verify the validity of the first-order approach.
We provide evidence on the importance of coordination frictions in technology adoption, using data from a large provider of electronic wallets during the Indian demonetization. Exploiting geographical variation in exposure to the demonetization, we show that adoption of the wallet increased persistently in response to the large but temporary cash contraction, consistent with the predictions of a technology adoption model with complementarities. Model estimates indicate that adoption would have been 45% lower without complementarities. Our results illustrate how large but temporary interventions can help overcome coordination frictions, though we caution that such interventions may also exacerbate initial differences in adoption.
We formulate a reputational model in which the type of government is time varying and private information. Agents adjust their beliefs about the government’s type (i.e., reputation) using noisy signals about its policies. We consider a debt repayment setting in which reputation influences the market’s perceived probability of default, which affects sovereign spreads. We focus on the 2007–12 Argentine episode of inflation misreport to quantify how markets price reputation. We find that the misreports significantly increased Argentina’s sovereign spreads. We use those estimates to discipline our model and show that reputation can have long-lasting effects on a government’s borrowing costs.
We present the results of a large field experiment on setting reserve prices in auctions for online advertisements, guided by the theory of optimal auction design suitably adapted to the sponsored search setting. Consistent with the theory, revenues increased substantially after the new reserve prices were introduced.
Recent research concludes that the rise in consumption inequality mirrors, or even exceeds, the rise in income inequality. We revisit this finding, constructing improved measures of consumption, focusing on its well-measured components that are reported at a high and stable rate relative to national accounts. While overall income inequality rose over the past 5 decades, the rise in overall consumption inequality was small. The declining quality of income data likely contributes to these differences for the bottom of the distribution. Asset price changes likely account for some of the differences in recent years for the top of the distribution.
We develop a new class of two-stage mechanisms, which fully implement any social choice function under initial rationalizability in complete information environments. We show theoretically that our simultaneous report (SR) mechanisms are robust to small amounts of incomplete information about the state of nature. We also highlight the robustness of the mechanisms to a wide variety of reasoning processes and behavioral assumptions. We show experimentally that an SR mechanism performs well in inducing truth telling in both complete and incomplete information environments and that it can induce efficient investment in a two-sided holdup problem with ex ante investment.
We use a unique combination of register and survey data from Amsterdam to investigate the performance of school assignment mechanisms in practice. We find that deferred acceptance (DA) results in higher mean welfare than the adaptive Boston mechanism. This is due to students making strategic mistakes. The welfare gain of a switch from actual Boston to DA is over 90% of the welfare difference between actual Boston and optimal (proxy) Boston. Disadvantaged and lower-ability students would benefit most from such a switch.
This paper investigates the sources of wage growth over the life cycle, determined by sectoral and firm mobility, unobserved ability, the accumulation of cognitive-abstract or routine-manual skills, and whether workers enroll in vocational training at the start of their career. Our analysis uses longitudinal administrative data over three decades and shows that routine-manual skills drive early wage growth, while cognitive-abstract skills become more important later. Moreover, job amenities are an important determinant of mobility decisions. Vocational training has long-term effects on career outcomes through various channels and generates returns for both the individual and society.
A principal has to take a binary decision. She relies on information privately held by an agent who prefers the same action regardless of his type. The principal cannot incentivize with transfers but can learn the agentâs type at a cost. Additionally, the principal privately observes a signal correlated with the agentâs type. Transparent mechanisms are optimal: the principalâs payoff is the same as if her signal was public. A simple cutoff form is optimal: favorable signals ensure the agentâs preferred action. Signals below this cutoff lead to the nonpreferred action unless the agent appeals. An appeal always triggers type verification.
The economic consequences of large-scale government investments in education depend on general equilibrium effects in both the labor market and the education sector. I develop a general equilibrium model capturing the consequences of massive countrywide schooling initiatives. I provide unbiased estimates of the model’s elasticities, using a regression discontinuity derived from Indian government policy. The earnings returns to a year of education are 13.4%, and the general equilibrium labor market effects substantially depress returns, by 6.6 percentage points. These general equilibrium effects have distributional consequences across cohorts and skill groups, whereby unskilled workers are better off and skilled workers worse off.
Financial crises typically occur because firms and financial institutions are highly exposed to aggregate shocks. We propose a theory to explain these exposures. We study a model where entrepreneurs can issue state-contingent claims to consumers. Even though entrepreneurs can use these instruments to hedge negative shocks, they do not necessarily do so because insuring against these shocks is expensive, as consumers are also harmed by them. This effect is self-reinforcing because riskier balance sheets for entrepreneurs imply higher income volatility for the consumers, making insurance more costly in equilibrium. We show that this feedback is quantitatively important and leads to inefficiently high risk exposure for entrepreneurs.
Employee referral programs (ERPs) are randomly introduced in a grocery chain. On direct effects, larger referral bonuses increase referral quantity but decrease quality, though the increase in referrals from ERPs is modest. However, the overall effect of having an ERP is substantial, reducing attrition by 15% and significantly decreasing labor costs. This occurs, partly, because referrals stay longer than nonreferrals, but, mainly, from indirect effects: nonreferrals stay longer in treated than in control stores. The most supported mechanism for these indirect effects is workers value being involved in hiring. Attrition impacts are larger in higher performing stores and better local labor markets.
Mixture choice data consist of the joint distribution of choices of a group of agents from a collection of menus, comprising the implied stochastic choice function plus any cross-menu correlations. When agents are heterogeneous with respect to both preferences and other aspects of cognition, we show that these two determinants of behavior are identified simultaneously by suitable mixture choice data. We also demonstrate how this finding can be extended to allow for specialized assumptions about cognition, focusing on models of random satisficing thresholds and âquantal Fechnerianâ choice.
We introduce a flexible framework to study probabilistic choice that accommodates heterogeneous types and bounded rationality. We provide a novel progressive structure for the heterogeneous types to capture heterogeneity due to varying levels of a behavioral trait. Given an order of alternatives, our progressive structure sorts the types by the extent to which they align with this order. Unlike the random-utility model, our model uniquely identifies the heterogeneity, allowing policy makers to perform an improved welfare analysis. As a showcase, we provide characterization of a well-studied type of bounded rationality: âless-is-more.â In addition, we provide conditions for unique identification of the underlying order for the less-is-more structure.
Parents make important choices for their children in many areas of life, yet the empirical literature on this topic is scarce. We study parentsâ competitiveness choices for their children by combining two large-scale artifactual field experiments with high-quality longitudinal administrative data. We document three main sets of findings. First, parents choose more competition for their sons than daughters. Second, this gender difference can largely be explained by parentsâ beliefs about their childrenâs competitiveness preferences. Third, parentsâ choices predict childrenâs later-in-life educational outcomes. Taken together, these findings provide novel evidence on the role of parents in shaping childrenâs long-term outcomes.
We consider a mechanism design setting in which agents can acquire costly information on their preferences as well as othersâ. A mechanism is informationally simple if agents have no incentive to learn about othersâ preferences. This property is of interest for two reasons. First, it is a necessary condition for the existence of dominant-strategy equilibria in the extended game. Second, this endogenizes an âindependent-private-valueâ property of the interim information structure. We show that, generically, a mechanism is informationally simple if and only if it satisfies a separability condition that rules out most economically meaningful mechanisms.
In an overlapping-generations economy, the consumption growth of a given cohort member (the “marginal agent”) differs from the aggregate consumption growth. A cohort member is faced with long-run consumption uncertainty even in the absence of aggregate (and within-cohort) consumption risk. This uncertainty allows the model to account for several stylized asset-pricing facts (high market price of risk and volatility, return predictability, low and nonvolatile interest rate) despite deterministic macroeconomic aggregates and inequality measures that are contemporaneously uncorrelated with asset returns. We devise and implement a methodology to measure the marginal agent’s consumption growth and evaluate the model’s quantitative implications.
Names can convey information about race or ethnicity and therefore can be used to discriminate against protected groups; many researchers have demonstrated as much through audit studies. Yet few studies link life outcomes with names using observational data. We use administrative data from over 3 million Black students to ask whether those with more statistically Black names have differential educational outcomes. We find that while test scores, college enrollment, and college completion are negatively correlated with Black names net of background characteristics, this relationship is absent when we compare across siblings within households.
We point-identify and estimate linear social network models without observing any network links. The required data consist of many small networks of individuals, such as classrooms or villages, with individuals who are each observed only once. We apply our estimator to data from Tennesseeâs Project STAR (Student-Teacher Achievement Ratio). Without observing the latent network in each classroom, we identify and estimate peer and contextual effects on studentsâ performance in mathematics. We find that peer effects tend to be larger in bigger classes and that increasing peer effects would significantly improve studentsâ average test scores in some classes.
We construct a model of an exchange economy in which agents trade assets contingent on an observable signal, the probability of which depends on public opinion. The agents in our model are replaced occasionally, and each person updates beliefs in response to observed outcomes. We show that the distribution of the observed signal is described by a quasi-nonergodic process and that people continue to disagree with each other forever. These disagreements generate large wealth inequalities that arise from the multiplicative nature of wealth dynamics, which makes successful bold bets highly profitable.
The Voting Rights Act of 1965 redefined race relations in the United States. Yet evidence on its effect on Black office holding remains scant. Using novel data on Black elected officials between 1962 and 1980, we assess the impact of the Voting Rights Act on the racial makeup of local governments in the Deep South. Exploiting predetermined differential exposure of Southern counties to the mandated federal intervention, we show that the latter fostered local Black office holding, particularly in the powerful county commissions, controlling local public finances. In the presence of election by district, covered counties experienced Black representation gains and faster capital spending growth.
Test score measures of teacher quality may not fully capture teachersâ impact on students. We use test score and nonâtest score measures of student achievement and behavior to estimate multiple dimensions of teacher quality. We find that these two measures of teacher quality are only weakly correlated and that both affect studentsâ high school performance. A teacher removal simulation that uses both measures improves most long-term student outcomes by over 50%, compared to a policy that uses test scores alone. Our results also show that for high school outcomes the effects of teachers in later grades are larger than those in earlier grades and that performance in core elementary school subjects matters more than that in other subjects.
We study partial identification of the preference parameters in the one-to-one matching model with perfectly transferable utilities. We do so without imposing parametric distributional assumptions on the unobserved heterogeneity and with data on one large market. We provide a tractable characterization of the identified set under various classes of nonparametric distributional assumptions on the unobserved heterogeneity. We reexamine some of the relevant questions in the empirical literature on the marriage market, which have been previously studied under the logit assumption. Our results reveal that many findings in the aforementioned literature are primarily driven by such parametric restrictions.
Many economists assume that safer assets are more liquid, and some have practically used âsafeâ and âliquidâ as synonyms. But these terms are not synonyms, and mixing them up can lead to confusion and wrong policy recommendations. We build a multiasset model where an assetâs safety and liquidity are well defined and distinct, and we examine their relationship in general equilibrium. We show that the common belief that âsafety implies liquidityâ is generally justified but also identify conditions under which this relationship can be reversed. We use our model to rationalize, qualitatively and quantitatively, a prominent safety-liquidity reversal observed in the data.
This paper develops a micro-founded general equilibrium model of payments to study the impact of a central bank digital currency (CBDC) on intermediation of private banks. If banks have market power in the deposit market, a CBDC can enhance competition, raising the deposit rate, expanding intermediation, and increasing output. A calibration to the US economy suggests that a CBDC can raise bank lending by 1.57% and output by 0.19%. These crowding-in effects remain robust, albeit with smaller magnitudes, after taking into account endogenous bank entry. We also assess the role of a non-interest-bearing CBDC as the use of cash declines.
This study measures spending power inequality within age cohorts and estimates fiscal progressivity via lifetime net tax rates. We find, first, that inequality in income and especially wealth dramatically overstates inequality in spending power. Second, inequality in current spending power differs from that in lifetime spending power because of credit constraints, in-kind government benefits, and other factors. Third, the US fiscal system is highly progressive once cohorts are old enough to have highly dispersed human wealth. Fourth, householdsâ rankings based on current income can differ substantially from their rankings based on lifetime resources. Fifth, current-year net tax rates substantially understate fiscal progressivity.
We present a mechanism based on managerial incentives through which common ownership affects product market outcomes. Firm-level variation in common ownership causes variation in managerial incentives and productivity across firms, which leads to intraindustry and intrafirm cross-market variation in prices, output, markups, and market shares that is consistent with empirical evidence. The organizational structure of multiproduct firms and the passivity of common owners determine whether higher prices under common ownership result from higher costs or from higher markups. Using panel regressions and a difference-in-differences design, we document that managerial incentives are less performance sensitive in firms with more common ownership.
We document that countries partially default often and with varying intensity, resulting in lengthy episodes and hump-shaped patterns for partial default and debt. Default episodes lead to haircuts for lenders but not to reductions in debt, because the defaulted debt accumulates and borrowing continues. We present a theory of partial default rationalizing these patterns and the heterogeneity of partial default, and partial defaultâs comovements with spreads, debt, and output that are absent in standard sovereign default theory. We include policy counterfactuals in the form of pari passu and no-dilution clauses and debt-relief policies, and their welfare implications.
We show that with indivisible goods, the existence of competitive equilibrium fundamentally depends on agentsâ substitution effects, not their income effects. Our equilibrium existence duality allows us to transport results on the existence of competitive equilibrium from settings with transferable utility to settings with income effects. One consequence is that net substitutabilityâwhich is a strictly weaker condition than gross substitutabilityâis sufficient for the existence of competitive equilibrium. Further applications give new existence results beyond the case of (net) substitutes. Our results have implications for auction design.
This paper demonstrates the long-term intra- and intergenerational benefits of the HighScope Perry Preschool Project, which targeted disadvantaged African American children. We use newly collected data on the original participants through late middle age and on their children into their midtwenties. We document long-lasting improvements in the original participantsâ skills, marriage stability, earnings, criminal behavior, and health. Beneficial program impacts through the child-rearing years translate into better family environments for their children, leading to intergenerational gains. Children of the original participants have higher levels of education and employment, lower levels of criminal activity, and better health than children of the controls.
Karl Marxâs high academic stature outside of economics diverges sharply from his peripheral influence within the discipline, particularly after nineteenth-century developments rendered the labor theory of value obsolete. We hypothesize that the 1917 Russian Revolution is responsible for elevating Marx into the academic mainstream. Using the synthetic control method, we construct a counterfactual for Marxâs citation patterns in Google Ngram data. This allows us to predict how often Marx would have been cited if the Russian Revolution had not happened. We find a significant treatment effect, meaning that Marxâs academic stature today owes a substantial debt to political happenstance.
We investigate whether a market served by a multiproduct monopolistic seller can be segmented in a way that benefits all consumers and the seller. The seller can offer a different product menu in each market segment, combining second- and third-degree price discrimination. We show that markets for which profit maximization leads to inefficiency can, generically, be segmented into two market segments in a way that increases the surplus of all consumers weakly and of some consumers and the seller strictly. Our constructive proof is based on deriving implications of binding incentive compatibility constraints when profit maximization implies inefficiency.
Most social preference theories are based on observations of nonvoluntary interactions. Nonselfish behavior may take fundamentally different forms in voluntary interactions, such as market transactions. We investigate the âPrinciple of Mutual Benefitââan injunctive norm requiring individuals who enter interactions voluntarily to conform to common expectations about behavior within them. This norm induces patterns of behavior inconsistent with existing social preference theories and allows extrinsic incentives to crowd in trustworthiness. We embed this norm in a model consistent with evidence about promise keeping, gift exchange, and âavoiding the ask.â We present new experimental evidence that people adhere to it.
This paper studies the optimal determination of deposit insurance when bank runs are possible. We show that the welfare impact of changes in the level of deposit insurance coverage can be generally expressed in terms of a small number of sufficient statistics, which include the level of losses in specific scenarios and the probability of bank failure. We characterize the wedges that determine the optimal ex ante regulation, which map to asset- and liability-side regulation. We demonstrate how to employ our framework in an application to the most recent change in coverage in the United States, which took place in 2008.
We consider a dynamic monetary economy where agents gradually learn about the holding cost of a new asset and coordinate to adopt it as money or abandon it. We provide closed-form solutions for state-contingent asset prices and agents’ adoption decision. The transactional benefits of using money are endogenous and can convexify or concavify the payoff structure. Thus, the arrival of new information can raise or reduce the asset’s price, which is in sharp contrast to standard insights in experimentation models. Full disclosure of the asset type and an increase in the learning speed improve information but have different welfare implications.
We study optimal Pareto-improving factor taxation when agents are heterogeneous in their labor productivity and wealth and markets are complete. Pareto-improving policies require a gradual reform: labor taxes should be cut, and capital taxes should remain high for a long time before reaching the limit. This policy redistributes wealth in favor of workers, promotes growth, and causes early deficits and government debt in the long run. We address several technical issues, such as sufficiency of Lagrangian solutions in a Ramsey problem, their relation to welfare functions, and solution algorithms. We also provide a proof that long-run capital taxes are zero.
Using a general equilibrium heterogeneous agent model featuring health production, we quantify the contribution of health price in explaining cross-country differences in health expenditures and health status. Considering other country-specific explanatory factors, US health prices are estimated to be 33% higher than those of European countries. This price differential explains more than 60% of the difference in health expenditures and more than half of the difference in health status between Europe and the United States. Despite its large impact at the aggregate level, these price differences increase the lifetime cost of living of Americans by 2 percentage points.
As Romer and Weitzman emphasized in the 1990s, new ideas are often combinations of existing ideas, an insight absent from recent models. In Kortum's research around the same time, ideas are draws from a probability distribution, and Pareto distributions play a crucial role. Why are combinations missing, and do we really need such strong distributional assumptions to get exponential growth? This paper demonstrates that combinatorially growing draws from standard thin-tailed distributions lead to exponential growth; Pareto is not required. More generally, it presents a theorem linking the max extreme value to the number of draws and the shape of the upper tail for probability distributions.
This paper examines a commonly used measure of persuasion whose precise interpretation has been obscure in the literature. By using the potential outcome framework, we define the causal persuasion rate by a proper conditional probability of taking the action of interest with a persuasive message conditional on not taking the action without the message. We then formally study identification under empirically relevant data scenarios and show that the commonly adopted measure generally does not estimate—but often overstates—the causal rate of persuasion. We discuss several new parameters of interest and provide practical methods for causal inference.
We attempt to understand potential common forces behind rising market concentration and a slowdown in business dynamism in the US economy, through a micro-founded general equilibrium model of endogenous firm dynamics. The model captures the strategic behavior between competing firms, its effect on their innovation decisions, and the resulting “best-versus-the-rest” dynamics. We consider multiple potential mechanisms that can drive the observed changes and use the calibrated model to assess their relative importance, with particular attention to the implied transitional dynamics. Our results highlight the dominant role of a decline in the intensity of knowledge diffusion from frontier firms to laggard ones. We present new evidence that corroborates a declining knowledge diffusion in the economy.
We estimate productivity gains of 13.5% from workplace soft skills training among Indian garment workers. Productivity gains are greater when trainees work on joint operations alongside other coworkers, consistent with gains being driven by improved teamwork and collaboration. Furthermore, untreated coworkers on the treated production lines also show increased productivity. These improvements in the teamwork substitute for managerial attention. Despite productivity gains and higher promotion probabilities among treated workers, there are no effects on wages or retention, consistent with frictions in this labor market. Consequently, the net return to the firm was large: 256% 8 months after program completion.
We propose a model with local spatial markets and heterogeneous agents to understand and evaluate the geographic expansion of bank branches after banking deregulation in Thailand. The model features heterogeneity in financial frictions across regions, with the costs of accessing credit and deposits depending on the distance from the nearest branch. Disciplined by micro estimates of the effects of branch openings, the model reproduces salient regional and aggregate patterns concerning occupational choice, financial access, and inequality. We apply the model to study two counterfactual financial sector policies in distant markets, one subsidizing branches and the other subsidizing household deposits.
We measure the contribution of firm-embedded productivity to cross-country income differences. By firm-embedded productivity we refer to firm-specific components of productivity, such as blueprints, management practices, and other intangible capital. Using micro-level data for multinational enterprises (MNEs), we compare market shares of the same MNE in different countries and document that they are systematically larger in less developed countries. This indicates that MNEs face less competition and that firm-embedded productivity is scarce in these countries. We implement a measure of firm-embedded productivity based on this observation. Differences in firm-embedded productivity account for one-third of the cross-country variance in output per worker in our sample.
What is the optimal fiscal policy response to a recession when the government is subject to sovereign risk? We study this question in a model of endogenous sovereign default with nominal rigidities. Increasing spending in a recession reduces unemployment, but it exposes the government to a debt crisis. We quantitatively analyze this trade-off between stimulus and austerity and find that expanding government spending may be undesirable, even in the presence of sizable Keynesian stabilization gains and inequality concerns. Consistent with these findings, we show that sovereign risk is a key driver of the fiscal procyclicality observed worldwide.
We study agency frictions in the US Congress. We examine the long-standing hypothesis that political elites engage in conflict because they fail to internalize the associated costs. We compare the voting behavior of legislators with draft age sons versus draft age daughters during the conscription-era wars of the twentieth century. We estimate that having a draft age son reduces proconscription voting by 7–11 percentage points. Support for conscription recovers when a legislator’s son ages out of eligibility. We establish that agency problems contribute to political conflict and that politicians are influenced by private incentives orthogonal to political concerns or ideological preferences.
We examine the contribution of trade to the rise of modern agriculture, taking into account interactions between trade, input requirements, and technology adoption. We develop and estimate a new multicountry general equilibrium model that incorporates producers’ choices of which crops to produce and with which technologies at the level of grid cells covering the earth’s surface. We find that trade cost reductions in agricultural inputs and the international transmission of productivity growth in the agricultural input sector since the 1980s induced large shifts from traditional, labor-intensive technologies to modern, input-intensive ones, with important global and distributional implications for productivity and welfare.
We evaluate progress in the War on Poverty as President Lyndon B. Johnson defined it, which established a 20% baseline poverty rate and adopted an absolute standard. While the official poverty rate fell from 19.5% in 1963 to 10.5% in 2019, our absolute full-income poverty measure—which uses a fuller income measure and updates thresholds only for inflation—fell from 19.5% to 1.6%. However, we also show that relative poverty reductions have been modest. Additionally, government dependence increased over this time, with the share of working-age adults receiving under half their income from market sources more than doubling.
We estimate a life-cycle model of consumption, human capital investment, and labor supply. The interaction between human capital and labor supply toward the end of the life cycle is most novel. The estimates replicate the main features of the data, in particular the large increase in wages and small increase in labor supply at the beginning of the life cycle and the small decrease in wages but large decrease in labor supply toward the end. We show that incorporating human capital is critical when analyzing changes to Social Security.
In the United States, households obtain health insurance through distinct market segments. To explore the economics of this segmentation, we consider the effects of pooling coverage provided through small employers and through individual marketplaces. We model households’ demand for insurance and health care along with insurers’ price setting to predict equilibrium choices and premiums. Applying our model to data from Oregon, we find that pooling can mitigate adverse selection in the individual market and benefit small group households without raising taxpayer costs. Our estimates provide insight into the effects of new regulations that allow employers to shift coverage to individual marketplaces.
This paper extends a canonical model of intergenerational human capital investment to a geographic context to study the role of migration in influencing income mobility in the United States. The main result is that migration is considerably influential in shaping the high rates of economic mobility observed among children from low-wage areas, with human capital investment behavioral responses being important to consider. Equalizing school quality across locations does more to reduce interstate inequality in income mobility than equalizing skill prices, and policies that attempt to decrease human capital flight from low-wage areas via cash transfers are unlikely to be cost-effective.
We document strong skill matching in Turkish firms’ production networks. Additionally, in the data, export demand shocks from rich countries increase firms’ skill intensity and their trade with skill-intensive domestic partners. We explain these patterns using a quantitative model with heterogeneous firms, quality choices, and endogenous networks. A counterfactual economy-wide export demand shock of 5% leads both exporters and nonexporters to upgrade quality, raising the average wage by 1.2%. This effect is nine times the effect in a scenario without interconnected quality choices. We use the model to study the conditions for the success of export promotion policies.
This paper estimates differences in human capital as country-of-origin-specific labor productivity terms in firm production functions, making it immune to wage discrimination concerns. After accounting for education and experience, estimated human capital varies by a factor of around three between the 90th and the 10th percentile. When I investigate which country-of-origin characteristics most closely correlate with human capital, cultural values are the only robust predictor. This relationship persists among children of migrants. Consistent with a plausible cultural mechanism, individuals whose origin places a high value on autonomy hold a comparative advantage in positions characterized by a low degree of routinization.
This paper estimates the effect of financial sponsorship of clinical trials on reported drug efficacy, leveraging the insight that the exact same pairs of drugs are often compared in different trials conducted by parties with different financial interests. I assemble new psychiatric trial data to estimate that a drug appears substantially more effective when the trial is sponsored by that drug’s manufacturer, compared with the same drug tested against the same combination of drugs but without sponsorship. This difference is not explained by observable characteristics, but publication bias is important. Preregistration may be effective in overcoming this bias.
Forecasts of professional forecasters are anomalous: they are biased, and forecast errors are autocorrelated and predictable by forecast revisions. We propose that these anomalies arise because professional forecasters do not know the model that generates the data. We show that Bayesian agents learning about hard-to-learn features of the world can generate all the prominent aggregate anomalies emphasized in the literature. We show this for professional forecasts of nominal interest rates and Congressional Budget Office forecasts of gross domestic product growth. Our learning model for interest rates can explain observed deviations from the expectations hypothesis of the term structure without relying on time variation in risk premia.
This paper studies how competition affects firms’ expectations in a new dynamic general equilibrium model with rational inattention and oligopolistic competition where firms acquire information about their competitors’ beliefs. In the model, firms with fewer competitors are less attentive to aggregate variables—a novel prediction supported by survey evidence. A calibrated version of the model matches the relationship between firms’ numbers of competitors and their uncertainty about aggregate inflation as a nontargeted moment. A quantitative exercise reveals that firms’ strategic inattention to aggregates significantly amplifies monetary nonneutrality and shifts output response disproportionately toward less competitive oligopolies by distorting relative prices.
How should successive generations insure each other when the young can default on previously promised transfers to the old? This paper studies intergenerational insurance that maximizes the expected discounted utility of all generations subject to participation constraints for each generation. If complete insurance is unattainable, the optimal intergenerational insurance is history dependent even when the environment is stationary. The risk from a generational shock is spread into the future with periodic “resetting.” If we interpret intergenerational insurance in terms of debt, the fiscal reaction function is nonlinear and the risk premium on debt is lower than the risk premium with complete insurance.
We examine aggregate economic gains in the United States as the railroad network expanded in the nineteenth century. Using data from the Census of Manufactures, we estimate relative increases in county aggregate productivity from relative increases in county market access. In general equilibrium, we find that the railroads substantially increased national aggregate productivity. By accounting for input distortions, we estimate much larger aggregate economic gains from the railroads than previous estimates. Our estimates highlight how broadly-used infrastructure or technologies can have much larger economic impacts when there are inefficiencies in the economy.
The price of a safe asset reflects not only the expected discounted future cash flows but also future service flows, since retrading allows partial insurance of idiosyncratic risk in an incomplete markets setting. This lowers the issuers’ interest burden. As idiosyncratic risk rises during recessions, so does the value of the service flows bestowing the safe asset with a negative β. The resulting exorbitant privilege resolves government debt valuation puzzles and allows the government to run a permanent (primary) deficit without ever paying back its debt, but the government faces a debt Laffer curve.
We study entry restrictions in a private monopoly: the Latin notary system. Under this widespread system, the state grants notaries exclusive rights to certify important economic transactions, including real estate. To uncover the current policy goals behind the geographic entry restrictions, we develop an empirical entry model that incorporates a spatial demand model and a multioutput production model. We find that the entry restrictions serve primarily producer interests and give only a small weight to consumer surplus. We show how reform would generate considerable welfare improvements and imply a substantial redistribution toward consumers without threatening geographic coverage.
How do elite universities balance diversity and academics during admissions? We develop a theory-based empirical framework to identify and quantify this potential trade-off, using postentry outcomes. We apply this to matched admission and exam-performance data from Cambridge. Comparing first- versus second-round admits from different demographic groups yields bounds on the trade-off magnitude, which (a) hold irrespective of whether we observe all applicant characteristics and (b) require no information on rejected applicants. We find robust evidence of trade-off between gender balance and future performance in math-intensive subjects but not for state/private school students or for gender in competitive nonmathematical disciplines.
Cadasters are public records of land ownership that facilitate clear assignment of property rights and land demarcation, thereby reducing transaction costs for economic agents and strengthening the state’s capacity to tax. Macro-level research on the evolution of formal land registration has largely been lacking. Using a novel dataset on the emergence and development of state-administered cadasters in 159 countries over the past millennium, we analyze empirically the association between the development of cadastral institutions and long-run economic growth. Our findings suggest a substantive positive effect of the introduction of cadasters on modern per capita income levels.
Central banks can operate with negative equity, and many have done so in history without undermining trust in fiat money. However, there are limits. How negative can central bank equity be before fiat money loses credibility? We address this question using a global game approach motivated by the fall of the Bank of Amsterdam (1609–1820). We solve for the unique break point where negative equity and asset illiquidity render fiat money worthless. We draw lessons on the role of fiscal support and central bank capital in sustaining trust in fiat money.
We investigate how skills developed when children are 3–5 years old drive schooling outcomes in middle childhood and adolescence. We find that skills map onto three distinct factors—cognitive skills, executive functions, and economic preferences. Importantly, each of the three factors predict later schooling outcomes. While early executive function skills and cognitive scores are linked to future behavioral patterns and other key student outcomes, economic preferences have an independent effect: children who are impatient in early childhood have more disciplinary referrals. Finally, random assignment to preschool impacts grades and disciplinary referrals through changes to cognitive skills and executive functions.
We generalize the traditional, static Keynesian cross by deriving an intertemporal Keynesian cross for the dynamic output response to government spending and taxes in microfounded general equilibrium models. Intertemporal marginal propensities to consume (iMPCs) are sufficient statistics for this response, with fiscal multipliers depending only on the interaction between iMPCs and public deficits. We provide empirical estimates of iMPCs and argue that they are inconsistent with representative agent or two-agent models but can be matched by certain heterogeneous agent models. Models that match empirical iMPCs imply larger and more persistent output responses to deficit-financed fiscal policy, with cumulative spending multipliers above 1.
Throughout the twentieth century, the relationship between women’s human capital and men’s income was nonmonotonic: while college-educated women married richer spouses than high school–educated women, graduate-educated women married poorer spouses than college-educated women. This can be rationalized by a bidimensional matching framework where women’s human capital is negatively correlated with another valuable trait: fertility, or reproductive capital. Such a model predicts nonmonotonicity in income matching with a sufficiently high income distribution of men. A simulation of the model using US Census fertility and income data shows that it can also predict the recent transition to more assortative matching as desired family sizes have fallen.
We show how real and financial frictions amplify, prolong, and propagate the negative impact of uncertainty shocks. We use a novel instrumentation strategy to address endogeneity in estimating the impact of uncertainty by exploiting differential firm exposure to exchange rate, policy, and energy price volatility. We show that financially constrained firms cut investment more than unconstrained firms following an uncertainty shock. We then build a general equilibrium heterogeneous firms model with real and financial frictions, finding that financial frictions (i) amplify uncertainty shocks by doubling their impact on output; (ii) increase persistence by doubling the duration of the drop; and (iii) propagate uncertainty shocks by spreading their impact onto financial variables.
We provide the first empirical analysis of the relationship between algorithmic pricing (AP) and competition by studying the impact of adoption in Germany’s retail gasoline market, where software became widely available in 2017. Because adoption dates are unknown, we identify adopting stations by testing for structural breaks in AP markers, finding most breaks to be around the time of widespread AP introduction. Because station adoption is endogenous, we instrument using headquarter adoption. Adoption increases margins but only for nonmonopoly stations. In duopoly and triopoly markets, margins increase only if all stations adopt, suggesting that AP has a significant effect on competition.
We modify the 1983 Diamond and Dybvig model so that banks offer liquidity services to depositors, raise equity funding, make risky loans, and invest in safe, liquid assets. Banks monitor borrowers to ensure that they repay loans and they are susceptible to depositor runs. We model the run decision by solving a novel global game. Relative to a social planner, banks opt for a more deposit-intensive capital structure, their assets may be more or less lending intensive, and the level of lending may be higher or lower. Correcting these three distortions requires a package of three regulations.
We develop and estimate a model of student study time choices on a social network. The model is designed to exploit unique data in the Berea Panel Study. Study time data allow us to quantify an intuitive mechanism for academic social interactions: own study time may depend on friend study time in a heterogeneous manner. Social network data allow us to embed study time and resulting academic achievement in an estimable equilibrium framework. We develop a specification test that exploits the equilibrium nature of social interactions and use it to show that novel study propensity measures mitigate econometric endogeneity concerns.
To decide the number, size, and location of its plants, a firm balances the benefit of delivering goods from multiple plants with the cost of setting up and managing these plants and the potential for cannibalization among them. Modeling the decisions of heterogeneous firms in an economy with a vast number of distinct locations involves a large combinatorial problem. Using insights from discrete geometry, we study a tractable limit case of this problem in which these forces operate at a local level. Our analysis delivers predictions on sorting across space. Compared with less productive firms, productive firms place more plants in dense, high-rent locations and fewer plants in markets with low density and low rents. We present evidence consistent with these and several other predictions, using US establishment-level data.
We study the effects of monetary policy–induced changes in Tobin’s q on corporate investment and capital structure. We develop a theory of the mechanism, provide empirical evidence, evaluate the ability of the quantitative theory to match the evidence, and quantify the relevance for monetary transmission to aggregate investment.
We study a mentoring program that aims to improve the labor market prospects of disadvantaged adolescents. Our randomized controlled trial investigates its effectiveness on three outcomes highly predictive of later labor market success: math grades, patience/social skills, and labor market orientation. For low-SES (socioeconomic status) adolescents, the mentoring increases a combined index of the outcomes by over half a standard deviation after 1 year, with significant increases in each outcome. Effects on grades and labor market orientation, but not on patience/social skills, persist 3 years after program start. By that time, the mentoring also improves early realizations of school-to-work transitions for low-SES adolescents. The mentoring is not effective for higher-SES adolescents.
We propose a supply-side channel for the transmission of monetary policy. We show that when high-markup firms have lower pass-throughs than low-markup firms, then positive demand shocks, such as monetary expansions, alleviate cross-sectional misallocation by reallocating resources to high-markup firms. Consequently, positive “demand shocks” are accompanied by endogenous positive “supply shocks” that raise productivity and lower inflation. We derive a tractable, four-equation model where monetary shocks generate hump-shaped productivity responses. In our calibration, the supply-side effect amplifies the total impact of monetary shocks on output by about 70%. We provide empirical evidence validating our model’s predictions using identified monetary shocks.
We present results from a large-scale experimental evaluation of a national parenting program in Chile. The program is low cost: it lasts only 6–8 weeks, and it is administered to groups of eight to 12 parents. It is implemented by the national health system, taking advantage of its existing physical infrastructure and human resources. We find that 3 years after the interventions ends, children whose parents are offered the opportunity to participate in this program increase their vocabulary and socioemotional development scores by 0.1 standard deviations, mirrored by similar improvements in caregiver’s parenting behaviors and beliefs.
Will stock exchanges innovate to address latency arbitrage and the arms race for speed? This paper models how exchanges compete in the modern electronic era and how this shapes incentives for market-design innovation. In the status quo, exchange trading fees are competitive, but exchanges earn economic rents from selling speed. These rents create a wedge between private and social incentives to innovate and support the persistence of an inefficient market design in equilibrium of a market-design adoption game. We discuss implications for policy and insights for the literatures on market design, innovation, and platforms.
We construct an index of long-term expected earnings growth for S&P 500 firms and show that it has remarkable power to jointly predict future errors in expectations and stock returns, in both the aggregate market and the cross section. The evidence supports a mechanism whereby good news causes investors to become too optimistic about long-term earnings growth. This leads to inflated stock prices and, as beliefs are systematically disappointed, subsequent low returns in the aggregate market. Overreaction of long-term expectations helps resolve major asset-pricing puzzles without time-series or cross-sectional variation in required returns.
In economies with fixed exchange rates, the adjustment to government-spending shocks is asymmetric. Expansionary shocks are absorbed by the real exchange rate, contractionary shocks by output. This result emerges in a small open-economy model with downward nominal wage rigidity and is supported by new empirical evidence based on panel data from different exchange-rate regimes. The exchange-rate regime, economic slack, inflation, and how spending is financed all matter for the fiscal transmission mechanism in the way predicted by the model. Estimates that fail to distinguish between the effects of positive and negative shocks are subject to a “depreciation bias.”
Most household production studies ignore unobserved inputs. Without additional assumptions, however, estimated impacts of the observed inputs cannot provide informative estimates of marginal products because of contaminating variations in unobserved inputs. Not even the signs of marginal impacts can be ascertained. One can establish the direction of these biases and significantly reduce them by including detailed information about nonproductive (pure consumption) goods in the analysis. Estimates from prior demand studies can also help determine the direction of the bias. We describe the stringent assumptions one must invoke in the absence of such additional information to be able to relate estimated effects to the true marginal products.
This paper studies the social value of closing price differentials in financial markets. We show that arbitrage gaps exactly correspond to the marginal social value of executing an arbitrage trade. Moreover, arbitrage gaps and price impact measures are sufficient to compute the total social value from closing an arbitrage gap, which may emerge for different reasons, including nonpecuniary benefits of holding particular assets. Theoretically, we show that, for a given arbitrage gap, the total social value of arbitrage is higher in more liquid markets. We compute the welfare gains from closing arbitrage gaps for covered interest parity violations.
Job and wage mobility can arise from firms and workers learning about workers’ ability and from workers acquiring human capital with experience. To date, the relative importance of these two mechanisms is debated. Using administrative data from one firm, I estimate a structural model that integrates them. I find the direct effect of beliefs about ability on wages, which existing work has focused on, to be small. However, by improving the sorting of workers to the firm’s jobs, learning about ability is indirectly a crucial determinant of wage growth and dispersion.
We develop and estimate a model of supply and demand for childcare. On the demand side, households make consumption, labor supply, and childcare decisions. On the supply side, centers make entry, price, and quality decisions. In addition, both paid and informal caregivers are available. Child development is a function of the time spent with parents and nonparental care providers. We estimate the model using data from the Early Childhood Longitudinal Study, Birth Cohort, and perform policy experiments. Vouchers that can be used only in high-quality centers or by working mothers are particularly effective, since they deliver child development gains while increasing mothers’ labor supply.
Concerns about income inequality emphasize the importance of accurate income measures. Estimates of top income shares based only on individual tax returns are biased by tax-base changes, social changes, and missing income sources. This paper addresses these shortcomings and presents new estimates of the distribution of national income since 1960. Our analysis of pretax income shows that top income shares are lower and have increased less since 1980 than other studies using tax data. In addition, increasing government transfers and tax progressivity have resulted in rising real incomes for all income groups and little change in aftertax top income shares.
Globally, preschool enrollment has surged, but its quality is often poor. We evaluate strategies to improve quality of public preschools in Colombia. The first, designed by the government and rolled out nationwide, provided extra funding, mainly earmarked for hiring teaching assistants. The second also offered low-cost training for existing teachers. The first intervention had no effect on child development, while the second improved children’s cognitive development, especially for more disadvantaged children. This pattern can be explained by the interventions affecting teachers' behavior differently. The first led teachers to reduce their classroom time, including learning activities, while additional training offset the adverse effect on learning activities and improved teaching quality.
We study the welfare and human capital impacts of colleges’ (non)participation in Chile’s centralized higher-education platform, leveraging administrative data and two policy changes: the introduction of a large scholarship program and the inclusion of additional institutions, which raised the number of on-platform slots by approximately 40%. We first show that the expansion of the platform raised on-time graduation rates. We then develop and estimate a model of college applications, offers, wait lists, matriculation, and graduation. When the platform expands, welfare increases, and welfare, enrollment, and graduation rates are less sensitive to off-platform frictions. Gains are larger for students from lower-socioeconomic-status backgrounds.
Wealth inequality has prompted calls for higher taxes on capital income and wealth but also concerns that rich households would respond by concealing their assets offshore. We use a general equilibrium model to study how taxing capital more heavily would affect offshore tax evasion and how this would affect the broader economy. Without evasion, tax revenue could be increased dramatically, inequality could be reduced, and widespread welfare gains could be achieved. After accounting for evasion, however, tax revenue would rise marginally or even fall, inequality would increase, and widespread welfare losses would result.
Studying a dynamic model of intergenerational transmission, we show that past events affect contemporaneous trends in intergenerational mobility. Structural changes may generate long-lasting mobility trends that can be nonmonotonic, and declining mobility may reflect past gains rather than a recent deterioration of equality of opportunity. We provide two applications. We first show that changes in the parent generation have partially offset the effect of rising skill premia on income mobility in the United States. We then show that a Swedish school reform reduced the transmission of inequalities in the directly affected generation but increased their persistence in the next.
The return on government debt is lower than that of assets with similar payoffs. We study optimal debt management and taxation when the government cannot directly redistribute toward the agents in need of liquidity but otherwise has access to a complete set of linear tax instruments. Optimal government debt provision calls for gradually closing the wedge between the returns as much as possible, but tax policy may work as a countervailing force: as long as financial frictions bind, it can be optimal to tax capital even if this magnifies the discrepancy in returns.
Despite the prevalence of nonroutine analytical team tasks in modern economies, little is understood regarding how incentives influence performance in these tasks. In a series of field experiments involving more than 5,000 participants, we investigate how incentives alter behavior in teams working on such a task. We document a positive effect of bonus incentives on performance, even among teams with strong intrinsic motivation. Bonuses also transform team organization by enhancing the demand for leadership. Exogenously increasing teams’ demand for leadership results in performance improvements comparable to those seen with bonus incentives, rendering it as a likely mediator of incentive effects.
As millions of soldiers deployed to Iraq or Afghanistan between 2001 and 2021, Veteran Affairs Disability Compensation payments quadrupled and the veteran suicide rate rose rapidly. We estimate the causal contribution of combat deployments to declining veteran well-being. Deployments increase injuries, combat deaths, and disability compensation, but we find limited effects on suicide, deaths of despair, financial health, incarceration, or education. Our estimates suggest that deployment cannot explain either the recent rise in disability payments, which is more likely driven by policy changes, or the surge in noncombat deaths, which is better explained by shifts in observable characteristics of soldiers.
Nearly 1 billion people still lack electricity access. Developing countries are investing billions of dollars in “last-mile” electrification, although evidence on its economic impacts is mixed. We estimate the development effects of rural electrification in the context of India’s national electrification program, RGGVY (Rajiv Gandhi Grameen Vidyutikaran Yojana), which reached over 400,000 villages. Using regression-discontinuity and difference-in-differences designs, we estimate that RGGVY meaningfully expanded electricity access. However, the program generated limited economic impacts after 3–5 years. Scaling our intent-to-treat estimates using instrumental variables, we find that “full electrification” reduces welfare in small villages but has a 33% internal rate of return in large villages.
Monetary exchange is called essential when better outcomes become incentive compatible when money is introduced. We study essentiality theoretically and experimentally using finite-horizon monetary models that are naturally suited to the lab. Following mechanism design, we also study the effects of strategy recommendations both when they are incentive compatible and when they are not. Results show that output and welfare are significantly enhanced by fiat currency if monetary equilibrium exists but not otherwise. Also, recommendations help if incentive compatible but not otherwise. Sometimes money gets used when it should not, and we investigate why, using surveys and measures of social preferences.
We study how author connections influence paper outcomes at the Journal of Human Resources. Authors who attended the same PhD program, worked with, affiliate with the same National Bureau of Economic Research program(s), or are closely linked via coauthorship networks as the handling editor are more likely to avoid a desk rejection. Reviewer recommendations are similarly influenced by PhD and employment matches. Matching on signals of ability—such as top five publishing, attending a high-ranked PhD program, or working in a high-ranked department—also impact peer review decisions. We find some evidence that published papers with greater connectivity subsequently receive fewer citations.
This article studies the effect of team gender composition and leadership on women’s influence in two field experiments. Study 1 finds that male-majority teams accord disproportionately less influence to women and are less likely to choose women to represent the team externally. We replicate this finding in a new context, where we also vary the gender of an assigned team leader. We find that a female leader substantially increases women’s influence, even in male-majority teams. With a model of discriminatory voting, we show that either increasing women's share or assigning a female leader decreases the penalty women face by more than 50%.
We study the role of preferred habitat in understanding the economic effects of the Federal Reserve’s quantitative easing (QE). Using high-frequency identification and exploiting the structure of the primary market for US Treasuries, we isolate demand shocks that are transmitted solely through preferred habitat channels but otherwise mimic QE shocks. We document large localized yield curve effects when financial markets are disrupted. Our calibrated model, which embeds preferred habitat in a New Keynesian framework, can largely account for the observed financial effects of QE. QE is modestly stimulative for output and inflation, but alternative policy designs can generate stronger effects.
The appropriateness of many high-cost loan regulations depends on whether demand is driven by financial conditions (“misfortunes”) or imperfect decisions (“mistakes”). Bank records from Iceland show that borrowers have especially low liquidity just before getting a loan. Borrowers exhibit lower decision-making ability (DMA) in linked-choice experiments: 45% of loan dollars go to the bottom 20% of the DMA distribution. Standard determinants of demand do not explain this relationship, which is also mirrored by the relationship between DMA and an unambiguous mistake. Both misfortune and mistake thus appear to drive demand.
This paper examines whether informal care by family members influences the demand for long-term care insurance. Motivated by evidence that the availability of informal caregivers correlates with lower insurance demand and that informal care substitutes for formal care, I estimate a dynamic model of long-term care decisions between an elderly parent and her adult child. The availability of informal care lowers demand for insurance by 7 percentage points and suppresses Medicaid spending. A policy that provides equivalent cash benefits for informal care for such families can generate meaningful increases in insurance demand and family welfare and decreases in Medicaid spending.
We examine how informational frictions impact schooling and work outcomes by estimating a dynamic structural model where individuals face uncertainty about their academic ability and productivity, which determine their schooling utility and wages. We account for different college types, majors, occupational search frictions, and work hours. Individuals learn from grades and wages, which may affect their choices. Removing informational frictions would increase graduation by 4.4 percentage points and by an additional 2 points without search frictions. Providing students with full information about their abilities would increase the college and white-collar wage premia while reducing the graduation gap by family income.
We empirically investigate how the performance of small and medium-sized enterprises (SMEs) changes when gaining access to market information. To do so, we evaluate the impact of an information program diffused by a bank among its SME customers. Adopting firms gained access to reports with rich information about their own clientele and that of nearby establishments. While we find that adoption is associated with a 4.5% revenue increase, our instrumental variable results indicate that adoption increases revenue by 9%. The main mechanism driving our result is that the new information prompted adopting establishments to target gender-age customer groups underserved before adoption.
We estimate long-run trends in intergenerational relative mobility for representative samples of the US-born population. Harmonizing all surveys that include father’s occupation and own family income, we develop a mobility measure that allows for the inclusion of nonwhite individuals and women for the 1910s–1970s birth cohorts. We show that mobility increases between the 1910s and 1940s cohorts and that the decline of Black-white income gaps explains about half of this rise. We also find that excluding Black Americans, particularly women, considerably overstates the level of mobility for twentieth-century birth cohorts while simultaneously understating its increase between the 1910s and 1940s.
We combine classic occupational choice (Roy model) and frictionless matching (following Sattinger) to explain earnings by occupation and firm in a way that is consistent with double assignment. In our model, within-firm inequality is globally nonzero whenever there is asymmetry in the revenue function or the occupational skill distribution across occupations. Occupational earnings overlap each other, and, unlike in the Roy model, the distributions of potential earnings are endogenous. In line with recent empirical findings on earning decomposition, skill-biased technical change increases within-firm inequality mostly among high-wage firms and not among low-wage firms.
We fully solve a sorting problem with heterogeneous firms and multiple heterogeneous workers whose skills are imperfect substitutes. We show that optimal sorting, which we call mixed and countermonotonic, is comprised of two regions. In the first region, mediocre firms sort with mediocre workers and coworkers such that the output losses are equal across all these teams (mixing). In the second region, a high-skill worker sorts with low-skill coworkers and a high-productivity firm (countermonotonicity). We characterize the equilibrium wages and firm values. Quantitatively, our model can generate the dispersion of earnings within and across US firms.
This paper provides novel insights into the science of scaling by examining an educational mentoring program in Mexico. The empirical analysis encompasses two independent field experiments and seizes a unique opportunity to learn from the government’s implementation of the same intervention. While the program originally implemented at scale demonstrates limited effectiveness, the introduction of a new modality with enhanced mentor training significantly improves children’s outcomes. Mentor-parent interactions are found to stimulate parental engagement at the community-school level. Our findings support the hypothesis that parents can play an important role in facilitating the scalability of educational programs.
Working-memory (WM) capacity is a key component of a wide range of cognitive and noncognitive skills—such as fluid IQ, math, reading, and inhibitory control—but can WM training improve these skills? Here, we examine the causal impact of WM training embedded in regular school teaching, using a randomized educational intervention with 6–7-year-old children. We find substantial gains in WM capacity and document positive spillover effects on geometry, fluid IQ, and inhibitory control. Three years later, treated children are 16 percentage points more likely to enter an advanced secondary school track.
Popular New Keynesian macroeconomic models predict that cuts in various types of distortionary taxes are contractionary when monetary policy is constrained at the zero lower bound (ZLB). We turn to a long span of history in the United Kingdom to test this hypothesis. Using a new long-run dataset of narrative-identified tax changes from 1918 to 2020, we show that tax cuts are expansionary in both low-interest-rate environments and more normal times. We do not find evidence of a deflationary spiral at the ZLB. Tax cuts may therefore still  be a useful tool to stimulate economic activity when monetary policy is constrained.
We study the introduction of a noninvasive prenatal screening—cell-free DNA (cfDNA) screening—which is used to target a more costly invasive test that elevates miscarriage risk. Using Swedish administrative data, we document that coverage of cfDNA substantially increases cfDNA screening and reduces invasive testing. We develop and estimate a stylized model of prenatal choices and find that narrow targeting of cfDNA coverage can improve outcomes and reduce costs, while broader coverage also improves outcomes but with increased costs. These findings point to the potential gains from well-designed targeting of screening but at the same time highlight the importance of the targeting design.
We study China’s export growth to the United States from 1950 to 2008, using a structural model to disentangle the effects of past tariff changes from the effects of changes in expectations of future tariffs. We find that the effects of China’s 1980 Normal Trade Relations (NTR) grant lasted past its 2001 accession to the World Trade Organization (WTO), and the likelihood of losing NTR status decreased significantly during 1986–92 but changed little thereafter. US manufacturing employment trends support our findings: industries more exposed to the 1980 reform have shed workers steadily since then without acceleration around China’s WTO accession.
We estimate a model of savings for retired couples and singles who face longevity and medical expense risks and in which couples can leave bequests both when the first spouse dies and when the last spouse dies. We show that saving motives vary by marital status, permanent income, and age. We find that most households save more for medical expenses than for bequests but that richer households and couples, who hold most of the wealth, save more for bequests. As a result, bequest motives are a key determinant of aggregate retirement wealth.
The scientific community assigns credit or “priority” to individuals who publish an important discovery first. We examine the impact of losing a priority race (colloquially known as getting “scooped”) on publication and career outcomes. To do so, we analyze data from structural biology where the nature of the scientific process together with the Protein Data Bank enables us to identify priority races and their outcomes. We find that scooped teams are less likely to publish in top journals and receive 21 percent fewer citations. We further study the implications of priority racing on research strategy, academic inequality, and scientist beliefs.
In this paper, we study the process of children’s skill formation using a dynamic latent factor model to identify key features of the skill production function. We develop and estimate a joint dynamic process for latent investment and skill development, incorporating both static and dynamic complementarities between parental investments and children’s skills in the technology of skill formation. Our analysis of US data reveals that early childhood investments (age 5–6) are highly effective for cognitive skill development, with greater marginal productivity for children with lower existing skills. This suggests that targeting interventions at disadvantaged young children is most beneficial.
Decentralized trading motivates financial innovation, making synthetic products like derivatives nonredundant, even when all traders trade all assets. This nonredundancy arises because derivatives affect cross-security inference (information) and, in markets with large traders, equilibrium price impact (liquidity). The efficient securities differ from the underlying assets. While the market index/mutual funds are efficient in decentralized markets with competitive investors, heterogeneous portfolios that balance index tracking with liquidity transformation become efficient in markets with large traders. Efficient securities facilitate the trading of all fundamental risks but generally forgo hedging all contingencies to minimize the price impact costs associated with risk sharing and diversification.
We develop a model of financial crises with both a financial amplification mechanism, via frictional intermediation, and a role for sentiment, via time-varying beliefs about an illiquidity state. The model accounts for the entire crisis cycle, matching data on the frothy precrisis behavior of asset markets and credit; the sharp transition to a crisis where asset values fall, disintermediation occurs, and output falls; and the slow postcrisis recovery in output. Both the intermediation and the belief mechanism are essential to match the crisis cycle. However, modeling the belief variation via either a Bayesian or a diagnostic model can match the broad patterns.
We conduct experiments on an online platform to investigate the causal effect of gender discrimination on labor supply decisions. Controlling for the piece-rate wage, we find that workers who face explicit negative gender-discriminatory wage inequality supply substantially less labor compared with workers who face gender-neutral wage inequality. We also examine the effect of positive discrimination, differences between men and women, and the impact of implicit rather than explicit discrimination. We identify decreased work morale as the underlying mechanism. In addition, we provide survey evidence showing that discrimination in the field reduces work morale and labor supply, corroborating our experimental results.
Why does the stock market rise and fall? From 1989 to 2017, the real per capita value of corporate equity increased at a 7.2% annual rate. We estimate that 40% of this increase was attributable to a reallocation of rewards to shareholders in a decelerating economy, primarily at the expense of labor compensation. Economic growth accounted for just 25% of the increase, followed by a lower risk price (21%) and lower interest rates (14%). The period 1952–88 experienced only one-third as much growth in market equity, but economic growth accounted for more than 100% of it.
We analyze the contribution of legal status incentives on the marriage choices of natives and migrants. Access to legal status reduces the probability of immigrants intermarrying with natives by 40% and increases the hazard rate of separation for intermarriages by 20%. We develop and estimate a multidimensional equilibrium model of marriage, fertility, and separation, where individuals match on observed and unobserved characteristics. Allowing for trade-offs between cultural distance, legal status, and other socioeconomic spousal characteristics, we quantify the role of legal status and the strength of cultural preferences and evaluate the welfare consequences of granting legal status to immigrants.
We develop a model of competition in prices and infrastructure among mobile network operators. Although consolidation increases market power, it can lead to more efficient data transmission due to economies of scale, which we derive from physical principles. After estimating our model with French consumer and infrastructure data, equilibrium simulations reveal that while prices decrease with the number of firms, so do download speeds. Our framework also allows us to quantify the impact of spectrum allocation. The marginal social value of spectrum exceeds firms’ willingness to pay in our model as well as observed prices in spectrum auctions.
Misconduct—market actions that are unethical and indicative of fraud—is a significant yet poorly understood issue that underlies many economic transactions. We design a field experiment to study the impact of two-sided antimisconduct information programs, which we deploy on the local markets for mobile money (“human ATMs”) in Ghana. The programs lead to a large reduction in misconduct (−21⁢ percentage points=−72%) and, as a result, broader improvements in overall market activity, consumer welfare, and firm revenue. We show the treatment effect is due to a combination of more accurate consumer beliefs about misconduct and increased vendor reputation concerns.
We propose a political economy mechanism that explains the presence of fiscal regimes punctuated by crisis periods. Our model focuses on the interaction between successive deficit-biased governments subject to independently and identically distributed fiscal shocks. We show that the economy transitions between a fiscally responsible regime and a fiscally irresponsible regime, with transitions occurring during crises when fiscal needs are large. Under fiscal responsibility, governments limit their spending to avoid transitioning to fiscal irresponsibility. Under fiscal irresponsibility, governments spend excessively and precipitate crises that lead to the reinstatement of fiscal responsibility. Regime transitions can occur only if governments’ deficit bias is large enough.
We study the effectiveness of pay-and-chase lawsuits and up-front regulations for combating health-care fraud. Between 2003 and 2017, Medicare spent $7.7 billion on 37.5 million regularly scheduled ambulance rides for patients traveling to and from dialysis facilities even though many did not satisfy Medicare’s criteria for receiving reimbursements. Using an identification strategy based on the staggered timing of regulations and lawsuits across the United States, we find that adding a prior authorization requirement for ambulance reimbursements reduced spending much more than pursuing criminal and civil litigation did on their own. We find no evidence that prior authorization affected patients’ health.
US firms in service industries increasingly operate in more local markets. Employment, sales, and spending on fixed costs have increased rapidly in these industries. These changes have favored top firms, leading to increasing national concentration. Top firms in service industries have grown by expanding into new local markets, predominantly small and mid-sized US cities. Market concentration at the local level has decreased in all US cities, particularly in cities that were initially small. These facts are consistent with the availability of new fixed-cost-intensive technologies that yield lower marginal costs in service sectors. The entry of top service firms into new local markets has led to substantial unmeasured productivity growth, particularly in small markets.
This paper argues that standard dynamic stochastic general equilibrium models grossly overestimate the impact of forward guidance on the macroeconomy, a phenomenon we call the “forward guidance puzzle.” Using data from a panel of Blue Chip survey expectations, we show that accommodative forward guidance had effects on output and inflation expectations that were positive and nontrivial, but still 28 and 8 times smaller, respectively, than implied by standard models. We show that incorporating a perpetual youth structure into the benchmark provides one possible resolution to the puzzle.
This paper develops an open-economy heterogeneous-agent New Keynesian model in which households differ in their income, wealth, and real and financial integration with international markets. We use the model to reassess classic questions in international macroeconomics from a distributional perspective. Our analysis yields two main takeaways. First, heterogeneity in households’ international integration plays a central role in driving the unequal consumption responses to external shocks, more so than income and wealth. Second, the conduct of monetary policy in open economies faces a stabilization-inequality trade-off, with fixed exchange rate regimes leading to amplified but more equal consumption responses to external shocks.
Coupons have been a mainstay of marketing for decades all over the world, but their short- and long-run effects on sales are still not understood fully. We develop a model of consumer demand to empirically study whether firms can indeed use coupons as a means to price discriminate by attracting new consumers without losing (cannibalizing) revenue from existing ones, and whether these new consumers return to the firm after the price promotion. In addition, we ask what types of businesses are most likely to benefit from such promotions. Following alcohol revenue for restaurants using e-coupons, we find that offering a coupon increases demand during the promotion, and to a lesser degree after the promotion, suggesting that coupons can be used to price discriminate, while an advertising effect is less obvious. While coupons increase profits on average, the effect on each firm’s profits depends on the firm’s characteristics.
This paper uses a large-scale field experiment in India to study attitudinal, behavioral, and cognitive constraints that can stymie the link between financial education and financial outcomes. The study complements financial education with (i) financial incentives on a financial literacy test to affect participant motivation, (ii) financial goal setting to provide a psychological nudge, and (iii) personalized financial counseling to enhance the intensity of treatment. The analysis finds no impact of financial incentives on learning but significant effects of both goal setting and counseling on real financial outcomes. These results identify important complements to financial education that can bridge the gap between financial knowledge and behavior change.
We experimentally test how effort responds to wages—randomly assigned to accrue to individuals or to a charity—in the presence of expectations-based reference points or targets. When individuals earn money for themselves, higher wages lead to higher effort with relatively muted targeting behavior. When individuals earn money for a charity, higher wages instead lead to lower effort with substantial targeting behavior. A reference-dependent theoretical framework suggests an explanation for this differential impact: when individuals place less value on earnings, such as when accruing earnings for a charity instead of themselves, more targeting behavior and a more sluggish response to incentives should result. Results from an additional experiment add support to this explanation. When individuals select into earning money for a charity and thus likely place a higher value on those earnings, targeting behavior is muted and no longer generates a negative effort response to higher wages.
We find that student debt is negatively related to the propensity to start a firm, particularly larger and more successful ventures. An exogenous change due to the Higher Education Amendments of 1998, which made student debt completely nondischargeable through personal bankruptcy, reduced the likelihood of entrepreneurship by student loan borrowers that were already in four-year college at the time of this regulation. Moreover, an exogenous shock to the level of student debt due to the Higher Education Amendments of 1992 negatively impacts entrepreneurship rates for students already in four-year college at the time of this regulation. Entrepreneurs with more student debt are more likely to fall behind on their student debt payments, and this relation is mitigated when their ventures are successful. Our evidence indicates that student debt inhibits entrepreneurship by exacerbating the effect of negative business outcomes on the individual.
Classical queueing theory has typically focused on customers, and server availability has been taken for granted. However, data accessibility and the emergence of complex service systems, for example, call centers, revealed the need to stochastically model the complex behavior of servers. In this work, we propose a new model that accommodates such behavior; we call it Erlang-S, where “S” stands for servers. Our model assumes a pool of present servers, some of whom are available to serve customers from the queue while others are not, and the process of becoming available or unavailable is modeled explicitly. Our focus here is on applying the model to real systems, specifically call centers. Estimating the parameters of the new model from call-center data is challenging because reality is observed discretely in time as opposed to its continuous evolution. We therefore use an expectation-maximization algorithm that computes the expected number of relevant quantities given the discrete-time data. Erlang-S differs from the Erlang-A model, which has been commonly used for modeling call centers: the latter model assumes that all agents who are present are, in fact, available for service. When comparing predictions of the two models against call-center data, we find that Erlang-A generally overestimates queue length and consequently also the fraction of abandonment, and Erlang-S predicts reality more closely and usefully. Our conclusion is that it is important to model explicitly server dynamics to obtain accurate and valuable models of complex service systems.
We investigate the credibility of nonbinding preplay statements about cooperative behavior, using data from a high-stakes TV game show in which contestants play a variant on the classic Prisoner’s Dilemma. We depart from the conventional binary approach of classifying statements as promises or not, and propose a more fine-grained two-by-two typology inspired by the idea that lying aversion leads defectors to prefer statements that are malleable to ex-post interpretation as truths. Our empirical analysis shows that statements that carry an element of conditionality or implicitness are associated with a lower likelihood of cooperation, and confirms that malleability is a good criterion for judging the credibility of cheap talk.
In a paper published in Management Science in 2015, Stewart, Reimers, and Harris (SRH) demonstrated that shapes of utility and probability weighting functions could be manipulated by adjusting the distributions of outcomes and probabilities on offer as predicted by the theory of decision by sampling. So marked were these effects that, at face value, they profoundly challenge standard interpretations of preference theoretic models in which such functions are supposed to reflect stable properties of individual risk preferences. Motivated by this challenge, we report an extensive replication exercise based on a series of experiments conducted as a quasi-adversarial collaboration across different labs and involving researchers from both economics and psychology. We replicate the SRH effect across multiple experiments involving changes in many design features; importantly, however, we find that the effect is also present in designs modified so that decision by sampling predicts no effect. Although those results depend on model-based inferences, an alternative analysis using a model-free comparison approach finds no evidence of patterns akin to the SRH effect. On the basis of simulation exercises, we demonstrate that the SRH effect may be a consequence of misspecification biases arising in parameter recovery exercises that fit imperfectly specified choice models to experimental data. Overall, our analysis casts the SRH effect in an entirely new light.
People vary in what they view as a fair distribution of earnings in organizations and, more generally, society. Where do these different views originate? We study the question of whether the experience of failure or success in a winner-take-most competition shapes people’s perspectives about distributive justice. In a laboratory experiment, subjects generated a high or low income either through a lottery or through a performance-based tournament. A subset of subjects could then redistribute the income of another subset of subjects. We find that the tournament losers redistribute significantly more than all of the other distributors when the inequality is generated by the tournament, whereas the lottery losers redistribute significantly more than all of the other distributors when the inequality is generated by the lottery. The effect still holds when controlling for potential self-selection into different outcomes of the tournament. We replicate the results in a second experiment and show that the underlying psychological mechanisms include an in-group bias and a self-serving bias in responsibility attribution. These findings have implications for the design of compensation schemes in organizations and for public policies in general.
The reputation information provided by market feedback systems tends to be compressed in the sense that reliable and unreliable sellers have similar feedback scores. The experiment presented here features a market in which what a buyer receives is a noisy signal of what was actually sent. We focus on the influence the noise has on endogenously given feedback. The attributional uncertainty creates room for leniency in feedback giving. We find that buyer leniency reduces the informativeness of the feedback system and, in combination with uncertainty, diminishes seller trustworthiness. With a noisy signal, buyers pay about the same prices but get significantly less.
We quantify the pervasiveness of informed trading activity in target companies’ equity options before the announcements of 1,859 U.S. takeovers between 1996 and 2012. About 25% of all takeovers have positive abnormal volumes, which are greater for short-dated, out-of-the-money calls, consistent with bullish directional trading before the announcement. Over half of this abnormal activity is unlikely due to speculation, news and rumors, trading by corporate insiders, leakage in the stock market, deal predictability, or beneficial ownership filings by activist investors. We also examine the characteristics of option trades litigated by the Securities and Exchange Commission (SEC) for alleged illegal insider trading. Although the characteristics of such trades closely resemble the patterns of abnormal option volume in the U.S. takeover sample, we find that the SEC litigates only about 8% of all deals in it.
When entering into a negotiation, individuals have the choice to enact a variety of communication styles. We test the differential impact of being “warm and friendly” versus “tough and firm” in a distributive negotiation when first offers are held constant and concession patterns are tracked. We train a natural language processing algorithm to precisely quantify the difference between how people enact warm and friendly versus tough and firm communication styles. We find that the two styles differ primarily in length and their expressions of politeness (Study 1). Negotiators with a tough and firm communication style achieved better economic outcomes than negotiators with a warm and friendly communication style in both a field experiment (Study 2) and a laboratory experiment (Study 3). This was driven by the fact that offers delivered in tough and firm language elicited more favorable counteroffers. We further find that the counterparts of warm and friendly versus tough and firm negotiators did not report different levels of satisfaction or enjoyment of their interactions (Study 3). Finally, we document that individuals’ lay beliefs are in direct opposition to our findings: participants believe that authors of warmly worded negotiation offers will be better liked and will achieve better economic outcomes (Study 4).
The editors of Management Science acknowledge all of our 2018 reviewers and guest associate editors, who generously provided expert counsel and guidance on a voluntary basis. We are grateful for their contributions; without them the journal could not function. Below, we list those reviewers who contributed four or more reviews in 2018.
Rank-order relative-performance evaluation, in which pay, promotion, symbolic awards, and educational achievement depend on the rank of individuals in the distribution of performance, is ubiquitous. Whenever organizations use rank-order relative-performance evaluation, people receive feedback about their rank. Using a real-effort experiment, we aim to discover whether people respond to the specific rank that they achieve. In particular, we leverage random variation in the allocation of rank among subjects who exerted the same effort to obtain a causal estimate of the rank response function that describes how effort provision responds to the content of rank-order feedback. We find that the rank response function is U-shaped. Subjects exhibit “first-place loving” and “last-place loathing”: that is, subjects work hardest after being ranked first or last. We discuss implications of our findings for the optimal design of performance feedback policies, workplace organizational structures, and incentives schemes.
This paper documents the increasing importance of software for successful innovation in manufacturing sectors well beyond the traditional definition of electronics and information technology. Using panel data for 229 publicly listed firms from 18 countries across four manufacturing industries over the period 1981–2005, we find significant variation across firms in the software intensity of their innovative activity. Firms that exhibit a higher level of software intensity generate more patents per R&D dollar, and their investment in R&D is more highly valued by equity markets.
We show that a model featuring an average commodity factor, a carry factor, and a momentum factor is capable of describing the cross-sectional variation of commodity returns. More parsimonious one- and two-factor models that feature only the average and/or carry factors are rejected. To provide an economic interpretation, we show that innovations in global equity volatility can price portfolios formed on carry, while innovations in a commodity-based measure of speculative activity can price portfolios formed on momentum. Finally, we characterize the relation between the factors and the investment opportunity set.
Many jobs are connected to a prosocial mission—namely, to a social purpose beyond profit maximization. I use three laboratory experiments to investigate if employers can use the mission to economize on monetary incentives. In my first experiment, I exogenously vary whether the agents’ effort generates a donation to a charity of their choice (matched mission), generates a donation to a charity chosen by another subject (random mission), or generates no donation (no mission). I find that the mission, whether matched or random, increases effort compared to the no-mission condition. Consistent with the theory, nonmotivated principals exploit the agents’ motivation by offering lower piece rates, whereas very motivated principals pay higher piece rates to boost the donation. I find no difference in the effort and piece rate between the matched- and random-mission conditions. In my second experiment, I use a selected pool of motivated subjects but still observe no difference between these two treatments. In my third experiment, I explore whether the effect of mission-matching may arise through gift exchange: principals decide between choosing the mission or delegating the choice to the agent. I do not find evidence that agents who are delegated the mission choice reciprocate with higher effort. These findings suggest that while a prosocial mission allows for economizing on monetary incentives, there are no further gains from increasing the quality of the mission-matching.
We present a lab-field experiment designed to systematically assess the external validity of social preferences elicited in a variety of experimental games. We do this by comparing behavior in the different games with several behaviors elicited in the field and with self-reported behaviors exhibited in the past, using the same sample of participants. Our results show that the experimental social preference games do a poor job explaining both social behaviors in the field and social behaviors from the past. We also include a systematic review and meta-analysis of previous literature on the external validity of social preference games.
Despite its central role in the theory of incentives, empirical evidence of a trade-off between risk and incentives remains scarce. We reexamine this trade-off in a workplace lab environment and find that, in line with theory, principals increase fixed pay while lowering performance pay when the relationship between effort and output is noisier. Unexpectedly, agents produce substantially more in the noisy environment than in the baseline despite weaker incentives. In addition, principals’ earnings are significantly higher in the noisy environment. We show that these findings can be accounted for when agents maximize a non-CARA utility function or when they exhibit loss aversion.
We study the impact of multidimensional bargaining and the location of inventory risk on the performance of a two-stage supply chain. We conduct a controlled human subjects experiment where a retailer and supplier either interact through ultimatum offers or dynamically bargain over contract terms, including a wholesale price and, potentially, an order quantity. We also manipulate whether the risk associated with unsold inventory lies with the retailer or the supplier or is endogenously determined in the bargaining process. One key insight is that supply chain efficiency is significantly higher when the order quantity is included in the negotiation and that, contrary to the normative theory, this leads to a Pareto improvement whereby both the supplier and retailer earn higher profits. A second important result, also counter to the normative theory, is that the party incurring the cost of unsold inventory always earns a lower profit than its counterpart, regardless of the bargaining environment or inventory risk location. To explain these data, we posit that retailers and suppliers are affected by an anchoring bias and demonstrate that it can explain many of our results.
We study the saving behavior of infinitely long-lived agents who face income uncertainty and deterministic interest rates. Using monotone recursive preferences, we prove that risk aversion unambiguously increases savings. The result accounts for possibly binding borrowing constraints and holds for very general specification of income uncertainty, which can follow any kind of stochastically monotone process.
This paper introduces the formal study of process flexibility to the novel domain of sports analytics. In baseball, positional flexibility is the analogous concept to process flexibility from manufacturing. We study the flexibility of players (plants) on a baseball team who produce innings-played at different positions (products). We develop models and metrics to evaluate expected and worst-case performance under injury risk (capacity uncertainty) with continuous player-position capabilities. Using Major League Baseball data, we quantify the impact of flexibility on team and individual performance and explore the player chains that arise when injuries occur. We discover that top teams can attribute at least one to two wins per season to flexibility alone, generally as a result of long subchains in the infield or outfield. The least robust teams to worst-case injury, those whose performance is driven by one or two star players, are over four times as fragile as the most robust teams. We evaluate several aspects of individual flexibility, such as how much value individual players bring to their team in terms of average and worst-case performance. Finally, we demonstrate the generalizability of our framework for player evaluation by quantifying the value of potential free agent additions and uncovering the true “MVP” of a team.
Most models of ambiguity aversion satisfy the Anscombe–Aumann monotonicity axiom. Monotonicity implies a weak form of separability of preferences across events that occur with unknown probability. We construct a test of weak separability by modifying the Allais paradox, adapting it to the Anscombe–Aumann framework. Three experimental studies are conducted. Study 1 finds frequent, systematic violations of weak separability in the lab. These findings replicate in study 2, where we employ a subject pool of online workers and use a natural rather than an artificial source of uncertainty. Investigating a potential explanation of the violations, study 3 suggests that the certainty effect plays a major role.
Many studies show that time preference data from experiments and surveys are related to field behavior. Time preference measures in these studies typically depend simultaneously on utility curvature, the level of impatience, and the change in the level of impatience. Thus, these studies do not allow one to establish which of these three components drive(s) the field behavior of interest. Of these components, the change in the level of impatience is theoretically thought to be the main driver of time inconsistencies and self-control problems. To test this theoretical presumption, one has to measure the change in the level of impatience independently from utilities and levels of impatience. This paper introduces a measure of the degree of decreasing impatience, the DI-index. It measures the change of impatience independently from the level of impatience and independently from utility. It can also be used to test various discounting models. An experiment finds no correlation between the degree of decreasing impatience and self-reported self-control problems in daily life, suggesting that changing impatience is not the sole driver of self-control problems.
We introduce the fatigue disutility model. Set in continuous time, the model formalizes the notion that fatigue accumulates with effort, decays with rest, and produces an increase in marginal instant disutility. The model is meant to be prescriptive, although it rationalizes several anomalies observed in time preference. Under very general conditions, the most efficient temporal profile of effort exhibits a high-low-high pattern. We consider a variant whereby marginal productivity decreases with fatigue, and we examine the optimal management of fatigue and productivity under various scenarios. We also reexamine the beneficial role of breaks in reducing fatigue. We bring the model to the data and provide a calibration that favorably predicts the speed profiles observed in swimming competitions.
We investigate behavioral reactions toward exogenous changes of implicit norm-relevant information in a natural field setting where customers are free to choose if and how much to pay for a service. Customers’ voluntary payments are significantly affected by subtle information cues: cues that signal a high rather than a low payment norm increase payments by some 27%. Consistent with the conjecture that this effect is in large part driven by customers’ uncertainty about the actual norm, responses are mitigated when explicit norm-relevant information is provided. Additional treatments suggest that the reactions to the cues are not driven by mere saliency but by the information deduced from the cues in the presence of uncertainty.
We study dynamic unstructured bargaining with deadlines and one-sided private information about the amount available to share (the “pie size”). Using mechanism design theory, we show that given the players’ incentives, the equilibrium incidence of bargaining failures (“strikes”) should increase with the pie size, and we derive a condition under which strikes are efficient. In our setting, no equilibrium satisfies both equality and efficiency in all pie sizes. We derive two equilibria that resolve the trade-off between equality and efficiency by favoring either equality or efficiency. Using a novel experimental paradigm, we confirm that strike incidence is decreasing in the pie size. Subjects reach equal splits in small pie games (in which strikes are efficient), while most payoffs are close to either the efficient or the equal equilibrium prediction, when the pie is large. We employ a machine learning approach to show that bargaining process features recorded early in the game improve out-of-sample prediction of disagreements at the deadline. The process feature predictions are as accurate as predictions from pie sizes only, and adding process and pie data together improves predictions even more.
Using the wisdom of crowds—combining many individual judgments to obtain an aggregate estimate—can be an effective technique for improving judgment accuracy. In practice, however, accuracy is limited by the presence of correlated judgment errors, which often emerge because information is shared. To address this problem, we propose an elicitation procedure in which respondents are asked to provide both their own best judgment and an estimate of the average judgment that will be given by all other respondents. We develop an aggregation method, called pivoting, which separates individual judgments into shared and private information and then recombines these results in the optimal manner. In several studies, we investigate the method and examine the accuracy of the aggregate estimates. Overall, the empirical data suggest that the pivoting method provides an effective judgment aggregation procedure that can significantly outperform the simple crowd average.
We introduce a new type of utility that we call “process utility,” which pertains to individuals’ preference about how they want to obtain an outcome. We posit that decision makers derive utility not only from the outcome itself, but also from the process through which that outcome is obtained. We focus on two normatively equivalent processes for obtaining an outcome: action and inaction. We argue that inducing differences in how outcomes are obtained can lead to significant preference reversals. We examine process utility in binary choice where one outcome is predominantly preferred over the other. We find that when the frequently selected (“advantaged”) alternative is framed as an inaction, its choice share decreases, but that when the infrequently selected (“disadvantaged”) alternative is framed as an inaction, its choice share increases. Finally, we discuss potential moderators of our effects.
This paper seeks to understand the relational factors that may affect the decisions of both third-party raters and service providers in a setting where service providers compete with one another. We employ laboratory economics experiments to examine how removing anonymity and allowing for repeated interactions between the rater and the service provider impact both the ratings assigned by the rater and the quality levels expended by the service provider. Our methodology enables us to observe the true quality level chosen by a service provider, which allows us to accurately detect any bias in the assessment of the third-party rater. The experimental results show that the decisions of both the rater and the service provider are very sensitive to the relational factors that govern their interaction. When the rater and the service provider know each other’s identities, we observe a high proportion of overrating even though raters earn less monetary rewards for doing so, and the propensity to overrate is even stronger with repeated interactions. Furthermore, the service provider chooses low quality levels. We develop and estimate a model that captures the rater’s psychological trade-off between remaining objective and helping the service provider compete in the marketplace, and the evolution of the service provider’s beliefs about the rater’s preferences.
To what extent does expertise depend on context? We observe professionals perform a task that is logically isomorphic to—but contextually distinct from—a familiar task in which they are skilled. We find that performance plummets when contextual cues disappear, suggesting that the expertise we observe on the familiar task is more heuristic than conceptual and does not travel far.
The pari passu principle of awarding claimants proportionally to their pre-insolvency claims is the most prominent principle in the law of insolvency. We report from a lab experiment designed to study whether people find this principle a fair solution to the bankruptcy problem. The experimental design generates situations where participants work and accumulate claims in firms, some of which subsequently go bankrupt. Third-party arbitrators are randomly assigned to determine how the liquidation value of the bankrupt firms should be distributed between claimants. Our main finding is that there is a striking support for the pari passu principle. We estimate a random utility model that allows for the arbitrators to differ in what they consider a fair solution to the bankruptcy problem and find that about 85% of the participants endorse the proportional rule. We also find that a nonnegligible fraction of the arbitrators follow the constrained equal losses rule, while there is almost no support in our experiment for the constrained equal awards rule or other fairness rules suggested in the normative literature.
Organizations often implement changes that can signal their values. However, the most objectively efficient changes do not necessarily serve as the best signals. Across seven experiments, we investigate how different rates of transition influence people’s perceptions of how committed organizations are to the values underlying changes or improvements. We find that slower, less efficient transitions signal greater commitment compared with faster, more efficient transitions that reach otherwise identical endpoints (Experiment 1). Using mediation and moderation strategies, we demonstrate that this discontinuity occurs because people assume slower transitions require relatively more effort to enact (Experiments 2 and 3). Moreover, these commitment inferences persist beyond the point at which changes end (Experiment 4), when further improvement along the same dimension is no longer possible (Experiment 5), and regardless of whether the organization decided to transition either quickly or slowly (Experiment 6). This effect reverses, however, when people can directly compare slower and faster transitions that ultimately reach identical endpoints (Experiment 7). Taken together, these findings suggest that people often infer greater commitment from slower transitions that unfold over time, even when those transitions are objectively inferior to faster alternatives.
Both theory and empirical evidence suggest that managers’ career concerns can serve as an important source of implicit economic incentives. We examine how incentives for political promotion are related to compensation policy and firm performance in Chinese state-owned enterprises. We find that the likelihood that the CEO receives a political promotion is positively related to firm performance. We also find that CEOs with a higher likelihood of political promotion have lower pay levels and lower pay–performance sensitivity. Overall, the evidence suggests that competition in the political job market helps mitigate weak monetary incentives for CEOs in China.
The gender difference in competitiveness has been cited as an important factor driving the gender gap in labor market outcomes. Using a field experiment with more than 35,000 university students, I explore the impact of compensation scheme on willingness to apply for a job. I find that competitive compensation schemes that depend on relative performance disproportionately deter women from applying. I do not find the same deterrence effect under a compensation scheme in which students face uncertain payoffs independent of performance. I also test the impact of describing the job as helping a charity, and this increases the willingness to apply but does not affect the gender gap. My findings are important for managers, who need to understand the impact of different compensation schemes on the share of women recruited for a job posting.
We study strategic communication between a customer and an advisor who is privately informed about the most suitable choice for the customer but whose preferences are misaligned with the customer’s preferences. The advisor sends a message to the customer who, in turn, can secure herself from bad advice by acquiring costly information on her own. In our experiments, we find that making the customer’s information acquisition less costly leads to less prosocial behavior of the advisor. This can be explained by a model of shared guilt, which predicts a shift in causal attribution of guilt from the advisor to the customer if the latter could have avoided her ex post disappointment. We conclude that providing better access to information through, for example, consumer protection regulation or digital information aggregation and dissemination, may have unintended negative consequences on peoples’ willingness to take responsibility for each other.
It is well known that goals serve as reference points, and their influence on pleasure can be understood with prospect theory’s value function. We examine how people feel about their progress on two goals (i.e., academics and fitness). What happens when they achieve one goal but fail to reach another? In four studies, we test the assumptions needed to explain hedonic reactions to progress along two goals. Loss aversion and diminishing sensitivity hold on each variable separately. However, we find violations of additivity in the integration of the emotions about outcomes. A success in one goal and a failure in another feel worse than the sum of the pleasure and pain associated with the gain and loss, respectively.
Healthy eating goals influence many consumer choices, such that evaluating the healthiness of food portions is important. Given that both the type and quantity of food jointly contribute to weight and overall health, evaluations of a food portion’s healthiness ought to consider both type and quantity. However, existing literature tends to examine food type and food quantity separately. Across seven studies, we show that consumers treat type as a primary dimension and quantity as a secondary dimension, such that a change in type (versus quantity) has a greater impact on perceived healthiness or health goal impact, even when holding objective impact constant in terms of calories. We also examine whether one reason this effect occurs is because most consumers consider type (a categorical attribute) before quantity (a continuous attribute). We conclude by discussing extensions of these ideas to other perceptual assessments involving both type and quantity (e.g., price perceptions).
This research examines how an individual’s place in the status hierarchy affects their willingness to expend effort on group tasks, why this occurs, and a contingency governing this relationship. Among firefighter teams (Study 1), MBA student workgroups (Study 2), and undergraduates in the laboratory (Study 3), we find that the relationship between status and effort, through performance expectations, is contingent on the perceived visibility of one’s efforts (i.e., task visibility). When task visibility is high, greater status leads to higher performance expectations. When task visibility is low or absent, this relationship was not present. Overall, our findings help paint a more complete picture of the relationship between status, performance expectations, and effort in workgroups while also furthering our understanding of the psychological experience of status.
Prior studies conclude that an unintended consequence of firms complying with the Sarbanes–Oxley Act is lower levels of risk-taking activities, including investment. We first show that prior studies cannot isolate the effects of SOX from other contemporaneous events. We then use the implementation requirements of SOX404 to construct a natural experiment that isolates the effects of SOX404 for a sample of small firms. We do not find a reduction in investment and other risk-taking activities for firms that had to comply with SOX404, relative to other firms. Because small firms are expected to be the most adversely affected by the regulation, our results cast doubt on the notion that SOX404 had a negative impact on larger firms.
We shed light on a money-for-privacy trade-off in the market for smartphone applications (“apps”). Developers offer their apps at lower prices in return for greater access to personal information, and consumers choose between low prices and more privacy. We provide evidence for this pattern using data from 300,000 apps obtained from the Google Play Store (formerly Android Market) in 2012 and 2014. Our findings show that the market’s supply and demand sides both consider an app’s ability to collect private information, measured by the apps’s use of privacy-sensitive permissions: (1) cheaper apps use more privacy-sensitive permissions; (2) given price and functionality, demand is lower for apps with sensitive permissions; and (3) the strength of this relationship depends on contextual factors, such as the targeted user group, the app’s previous success, and its category. Our results are robust and consistent across several robustness checks, including the use of panel data, a difference-in-differences analysis, “twin” pairs of apps, and various measures of privacy-sensitivity and app demand.
This paper studies the effect of providing feedback to college students on their position in the grade distribution by using a natural field experiment. This information was updated every six months during a three-year period. We find that greater grades transparency decreases educational performance, as measured by the number of examinations passed and grade point average (GPA). However, self-reported satisfaction, as measured by surveys conducted after feedback is provided but before students take their examinations, increases. We provide a theoretical framework to understand these results, focusing on the role of prior beliefs and using out-of-trial surveys to test the model. In the absence of treatment, a majority of students underestimate their position in the grade distribution, suggesting that the updated information is “good news” for many students. Moreover, the negative effect on performance is driven by those students who underestimate their position in the absence of feedback. Students who overestimate initially their position, if anything, respond positively. The performance effects are short lived—by the time students graduate, they have similar accumulated GPA and graduation rates.
We outline computational techniques for predicting perceptions of risk. Our approach uses the structure of word distribution in natural language data to uncover rich representations for a very large set of naturalistic risk sources. With the application of standard machine learning techniques, we are able to accurately map these representations onto participant risk ratings. Unlike existing methods in risk perception research, our approach does not require any specialized participant data and is capable of generalizing its learned mappings to make quantitative predictions for novel (out-of-sample) risks. Our approach is also able to quantify the strength of association between risk sources and a very large set of words and concepts and, thus, can be used to identify the cognitive and affective factors with the strongest relationship with risk perception and behavior.
A little-understood phenomenon of customer reward programs is the prevalent use of finite reward expiration terms. We develop a theoretical framework to investigate the economic rationale behind this phenomenon and the trade-off between short and long expiration terms. In our model, a monopolistic firm sets the expiration term, along with the price and reward size, and interacts with consumers over an infinite horizon. Consumers are heterogeneous in shopping probabilities and product valuations and forward-looking in making purchase decisions. We find that a customer reward program with a finite expiration term can increase firm profits when (i) the valuation difference within the consumer population is intermediate and (ii) the shopping probabilities and valuations are negatively correlated among consumers. Several model extensions confirm the robustness of these results. Finally, we conduct an empirical investigation on the reward program practice of the top 100 U.S. retailers, which provides directional support for several key theoretical predictions.
Can an organization avoid blame for an unpopular action when an adviser advises it to do it? We present experimental evidence suggesting this is the case—advice to be selfish substantially decreases punishment of being selfish. Further, this result is true despite advisers’ misaligned incentives, known to all: Through a relational contract incentive, advisers are motivated to tell the decision makers what they want to hear. Through incentivized elicitations, we find suggestive evidence that advice moves punishment by affecting beliefs of how necessary the selfish action was. In follow-up treatments, however, we show advice does not decrease punishment solely through a beliefs channel. Advice not only changes beliefs about what happened, but also the perceived morality of it. Finally, in treatments in which advisers are available, the data suggest selfish decision makers act more selfishly.
Agents’ decisions to exert effort depend on the incentives and the potential costs involved. So far, most of the attention has been on the incentive side. However, our laboratory experiments underline that both the incentive and the cost side can be used separately to shape work performance. In our experiment, subjects work on a real-effort slider task. Between treatments, we vary the incentive scheme used for compensating workers. Additionally, by varying the available outside options, we explore the role of implicit costs of effort in determining workers’ performance. We observe that incentive contracts and implicit costs interact in a nontrivial manner. In general, performance decreases as implicit costs increase. Yet the magnitude of the reaction differs across incentive schemes and across the offered outside options, which, in turn, alters estimated output elasticities. In addition, comparisons between incentive schemes crucially depend on the implicit costs.
The disclosure of compensation peer groups is argued to provide shareholders with valuable information that can be used to scrutinize chief executive officer (CEO) compensation. However, research suggests that there are substantial incentives for executives and directors to bias the compensation peer group upward such that the CEO can extract additional rent. We leverage the idea that reciprocated peer nominations are unlikely to be biased to construct counterfactual peer groups that allow us to measure the bias of disclosed peer groups. Analyses of 11 years of comprehensive data on compensation peer groups demonstrate that the average firm uses an upwardly biased peer group. The size of the bias increases when incentives and opportunities to do so are more pronounced. Specifically, results show that bias is larger when financial targets are not met and when exercising discretion in the selection of peer firms is justifiable. More importantly, upward bias in compensation peer groups is highly predictive of an increase in CEO compensation, suggesting that there is a strong incentive for CEOs to strategically select peers. Finally, although average peer group bias has gone down in recent years, the predictive effect of bias on pay has gone up. These findings call into question the practical impact of recent efforts to introduce greater transparency into the process for determining executive compensation.
Behavior differs between transparent and nontransparent presentations of decisions, but “transparent presentation” has not been precisely defined. We formally define “transparent frames” for risk and time, establish their uniqueness, provide algorithms for constructing them, and compare them with “standard” presentation formats. A logic emerges for predicting systematic shifts in choice under risk and over time, and how violations of rational choice theory will depend on frames. An experiment verifies most of those predictions in choice under risk. We extend results to choice under uncertainty and also predict frame dependence of ambiguity aversion, a result supported by recent experimental evidence.
Although reference dependence plays a central role in explaining behavior, little is known about the way that reference points are selected. This paper identifies empirically which reference point people use in decision under risk. We assume a comprehensive reference-dependent model that nests the main reference-dependent theories, including prospect theory, and that allows for isolating the reference point rule from other behavioral parameters. Our experiment involved high stakes with payoffs up to a week’s salary. We used an optimal design to select the choices in the experiment and Bayesian hierarchical modeling for estimation. The most common reference points were the status quo and a security level (the maximum of the minimal outcomes of the prospects in a choice). We found little support for the use of expectations-based reference points.
This paper examines the relation between air pollution and individual investors’ trading behavior and performance. Using unique data on stock trades by 87,504 individuals from 34 cities in China, we find a negative relation between air pollution and trade performance. This result is obtained after controlling for investor-year fixed effects and date fixed effects, as well as local weather conditions. More strikingly, abnormal trade performance decreases monotonically with the levels indicating the severity of air pollution. Furthermore, we find evidence suggesting that air pollution makes investors more susceptible to the disposition effect and attention-driven buying behavior. Overall, the results highlight a hitherto-unexplored cost that ambient air pollution imposes on stock market investors.
This research addresses the fundamental question of whether providing a safe workplace improves or hinders organizational survival, because there are conflicting predictions on the relationship between worker safety and organizational performance. The results, based on a unique longitudinal database covering more than 100,000 organizations across 25 years in the U.S. state of Oregon, indicate that, in general, organizations that provide a safe workplace have significantly lower odds and length of survival. Additionally, the organizations that would, in general, have better survival odds benefit most from not providing a safe workplace. This suggests that relying on the market does not engender workplace safety.
Entrepreneurial teams assign equity positions in their start-ups using a term sheet that details equity splits and the conditions for being granted those splits. The design of equity split agreements has attracted considerable attention in the entrepreneurial community, with no convergence on a single preferred contract form. This paper experimentally examines the effectiveness of different contractual arrangements, focusing in particular on the effects of contract form and contracting timing on founder effort and on the value of the venture. Our results suggest that performance improves with the incentive strength of the contract, but they question the conventional logic that this effect is causal. Instead, we suggest a novel causal sequence. Rather than the contract form being the primitive and the behavior the derived consequence, our results suggest the reverse. The differences in contract performance are driven primarily by the sorting of high contributors into nonequal contracts and of low contributors into equal contracts; that is, equal contracts are bad for team performance not because of their incentive strength but because of the founder types that adopt them. Taken together, these results suggest that both investors and founders should pay as much (or more) attention to personality type as they do to contract form.
Compensation systems have rapidly been shifting away from a fixed wage contractual payment basis. Many companies today are creating incentive compensation contracts to reward hard-working employees for jobs done well. Profit sharing (“sharing compensation contract”) and target with bonus (“target compensation contract”) are two common performance-based compensation contracts prevalent in business. We theoretically and behaviorally study the sharing and target compensation contracts in an operational context where a firm sets the parameters of the compensation contracts and a store manager, after observing the compensation contract offered to him, chooses his effort level (unobservable by the firm) and makes ordering decisions for the store. Our experimental data suggest systematic deviations from the theoretical benchmark and reveal behavioral promise and pitfalls under the two compensation contracts. In particular, the store manager is more willing to exert high effort under the target contract all else being equal. However, the store manager is also more likely to punish the firm for perceived “unfair” offers by submitting an extremely low order quantity. We find that bounded rationality plays an important role in driving a higher effort rate under the target contract than the sharing contract. We introduce a new formulation of the fairness concerns, which is referred to as by-state fairness, where individuals, rather than considering whether the expected profits received are fair, consider the fairness in the potential realized outcomes. This new formulation explains why managers are more likely to order very little to punish the firm under the target contract. In addition, we conduct validation experiments to verify our behavioral explanation.
What can be done to combat political misinformation? One prominent intervention involves attaching warnings to headlines of news stories that have been disputed by third-party fact-checkers. Here we demonstrate a hitherto unappreciated potential consequence of such a warning: an implied truth effect, whereby false headlines that fail to get tagged are considered validated and thus are seen as more accurate. With a formal model, we demonstrate that Bayesian belief updating can lead to such an implied truth effect. In Study 1 (n = 5,271 MTurkers), we find that although warnings do lead to a modest reduction in perceived accuracy of false headlines relative to a control condition (particularly for politically concordant headlines), we also observed the hypothesized implied truth effect: the presence of warnings caused untagged headlines to be seen as more accurate than in the control. In Study 2 (n = 1,568 MTurkers), we find the same effects in the context of decisions about which headlines to consider sharing on social media. We also find that attaching verifications to some true headlines—which removes the ambiguity about whether untagged headlines have not been checked or have been verified—eliminates, and in fact slightly reverses, the implied truth effect. Together these results contest theories of motivated reasoning while identifying a potential challenge for the policy of using warning tags to fight misinformation—a challenge that is particularly concerning given that it is much easier to produce misinformation than it is to debunk it.
We study how three matching institutions, differing in how relationships are dissolved, affect cooperation in a repeated prisoner’s dilemma and how cooperation rates are affected by the presence of a reputation mechanism. Although cooperation is theoretically sustainable under all institutions, we show experimentally that cooperation rates are lowest under random matching, highest under fixed matching, and intermediate in a flexible matching institution, where subjects have the option to dissolve relationships. Our results also suggest important interactions between the matching institution and reputation mechanism. Under both the random matching and flexible matching institutions, both subjective (based on subjects’ ratings) and objective (based on subjects’ actions) reputation mechanisms lead to substantial increases in cooperative behavior. However, under fixed matching, only the subjective reputation mechanism leads to higher cooperation. We argue that these differences are due to different reputation mechanisms being more forgiving of early deviations from cooperation under certain matching institutions, which gives subjects the ability to learn the value of cooperation rather than getting stuck with a bad reputation and, consequently, uncooperative relationships.
We use a laboratory experiment to study the effects of disclosing the number of active participants in contests with endogenous entry. At the first stage, potential participants decide whether to enter competition, and at the second stage, entrants choose their investments. In a 2×2 design, we manipulate the size of the outside option, ω, and whether the number of entrants is disclosed between the stages. Theory predicts more entry for lower ω and the levels of entry and aggregate investment to be independent of disclosure in all cases. We find empirical entry frequencies decreasing with ω. For aggregate investment, we find no effect of disclosure when ω is low but a strong positive effect of disclosure when ω is high. The difference is driven by substantial overinvestment in contests with a small, publicly known number of players contrasted by more restrained investment in contests in which the number of players is uncertain and may be small. The behavior under disclosure is explained by a combination of joy of winning and entry regret.
Providing patients with timely care from the appropriate unit involves both correct clinical evaluation of patient needs and making admission decisions to effectively manage a unit with limited capacity in the face of stochastic patient arrivals and lengths of stay. We study human decision behavior in the latter operations management task. Using behavioral models and controlled experiments in which physicians and MTurk workers manage a simulated hospital unit, we identify cognitive and environmental factors that drive systematic admission decision bias. We report on two main findings. First, seemingly innocuous “occupancy information hurdles” (e.g., having to type a password to view current occupancy) can cause a chain of events that leads physicians to maintain systematically lower unit utilization. Specifically, these hurdles cause physicians to make most admission decisions without checking the current unit occupancy. Then—between the times that they do check—physicians underestimate the number of available beds when occupancy increases from admissions are more salient than occupancy decreases from discharges. Second, decision-related random error or “noise” leads to higher- or lower-than-optimal utilization of hospital units in predictable patterns, depending on the system parameters. We provide evidence that these patterns are due to some settings providing more opportunity for physicians to mistakenly admit patients and other settings that provide more opportunity to mistakenly reject patients. These findings help identify when and why clinicians are likely to make inefficient decisions because of human cognitive limitations and suggest mitigation strategies to help hospital units improve their capacity management.
Although significant research has examined how technology can intensify racial and other outgroup biases, limited work has investigated the role information systems can play in abating them. Racial biases are particularly worrisome in healthcare, where underrepresented minorities suffer disparities in access to care, quality of care, and clinical outcomes. In this paper, we examine the role clinical decision support systems (CDSS) play in attenuating systematic biases among black patients, relative to white patients, in rates of amputation and revascularization stemming from diabetes mellitus. Using a panel of inpatient data and a difference-in-difference approach, results suggest that CDSS adoption significantly shrinks disparities in amputation rates across white and black patients—with no evidence that this change is simply delaying eventual amputations. Results suggest that this effect is driven by changes in treatment care protocols that match patients to appropriate specialists, rather than altering within physician decision making. These findings highlight the role information systems and digitized patient care can play in promoting unbiased decision making by structuring and standardizing care procedures.
Data-driven decision-making (DDD) is rapidly transforming modern operations. The availability of big data, advances in data analytics tools, and rapid gains in processing power enable firms to make decisions based on data rather than intuition. Yet, most firms still allow managers to override decisions from DDD tools, as managers might possess private information not present in the DDD tool. We report on a field-experiment conducted by an automobile replacement parts retailer that examines the profit implications of providing discretionary power to merchants. We find that merchants’ overrides of the DDD tool reduce profitability by 5.77%. However, our analysis over product life cycle (PLC) reveals that merchants increase (decrease) profitability for growth- (mature- & decline-) stage products.
Prospect Theory’s value function suggests that investors would be risk averse in the gain domain and risk seeking in the loss domain—that is, the reflection effect. However, most of the experimental evidence relies on choice tasks in the gain domain between prospects marked in dollar amounts and considering non-mixed lotteries. There is not much work that examines environments with properties typical in investment decisions where the task is fund allocation involving mixed lotteries with outcomes being rate of return. The recent negative deposit rates in Europe demonstrate the importance of this question and, in particular, understanding investment decisions in the loss domain. This paper fills this gap by using a series of laboratory experiments mimicking these properties of investment decisions with a range of investment amounts and with the money to invest either being earned and literally on the table or not. Yet, no matter the settings, we find no evidence for the reflection effect in investment, and behavior is most consistent with maximizing expected return. This holds regardless of the language used (abstract or not), whether we use a two- or a three-state lottery, whether the task is continuous rather than discrete, or the risky portfolio is a mixed lottery.
Copy trading allows traders in social networks to receive information on the success of other agents in financial markets and to directly copy their trades. Internet platforms like eToro, ZuluTrade, and Tradeo have attracted millions of users in recent years. The present paper studies the implications of copy trading for the risk taking of investors. Implementing a novel experimental financial asset market, we show that providing information on the success of others leads to a significant increase in risk taking of subjects. This increase in risk taking is even larger when subjects are provided with the option to directly copy others. We conclude that copy trading leads to excessive risk taking.
Collusion is widely condemned for its negative effects on consumer welfare and market efficiency. In this paper, I show that collusion may also in some cases facilitate the creation of unexpected new sources of value. I bring this possibility into focus through the lens of a historical episode from the 19th century, when colluding railroads in the U.S. South converted 13,000 miles of railroad track to standard gauge over the course of two days in 1886, integrating the South into the national transportation network. Route-level freight traffic data reveal that the gauge change caused a large shift in market share from steamships to railroads, but did not affect total shipments or prices on these routes. Guided by these results, I develop a model of compatibility choice in a collusive market and argue that collusion may have enabled the gauge change to take place as it did, while also tempering the effects on prices and total shipments.
The decomposition of dynamic risks a company faces into components associated with various sources of risk, such as financial risks, aggregate economic risks, or industry-specific risk drivers, is of significant relevance in view of risk management and product design, particularly in (life) insurance. Nevertheless, although several decomposition approaches have been proposed, no systematic analysis is available. This paper closes this gap in literature by introducing properties for meaningful risk decompositions and demonstrating that proposed approaches violate at least one of these properties. As an alternative, we propose a novel martingale representation theorem (MRT) decomposition that relies on martingale representation and show that it satisfies all of the properties. We discuss its calculation and present detailed examples illustrating its applicability.
In this article, we examine whether consumers may “accidentally” endanger a product they own when a new version of the product is introduced. We propose that owners endanger their product when they want to upgrade to a new version but have difficulty justifying the upgrade and that owners find justification more difficult when a new version offers an improved design but does not offer a significant technological improvement. Owners endanger their product hoping that it will be fortuitously damaged. Product damage provides owners with a good reason to upgrade. Focusing on iPhone as a case study, field data and experiments provide evidence for product endangering, and they support the role of justification in three ways. First, as hypothesized, endangering occurs when the new product offers an improved design but does not offer a significant technological improvement. Second, owners are less likely to endanger a product that is under warranty; therefore, damage to it will not enable upgrading. Third, owners are more likely to endanger their product when their justification concerns are heightened.
We integrate the results of a social network survey and a forecast information sharing experiment to examine the roles of trust and trustworthiness in impacting high-ranking executives’ decisions in supply chain interactions. The members of our executive sample have, on average, 17 years of work experience. A significant portion of them holds positions at the C-level in world-leading organizations that span a wide range of industries. By examining the roles of trust and trustworthiness in the decision making of high-ranking executives, we find strong external validation for as well as demonstrate how these nonpecuniary, behavioral factors impact the outcomes of business interactions. We employ a multimethod research design that allows us to investigate the extent to which the executives’ trust beliefs toward a relevant network of exchange partners (which we define as their “network trust”) impact their trust behaviors when engaging in business interactions with members of this network. We determine the conditions pertaining to the executives’ professional experiences that strengthen or weaken the impact of network trust on the executives’ trust behaviors in supply chain interactions. For example, executives with more diverse professional experiences rely more on network trust to shape their trust behaviors. Conversely, executives with prior positive trust experiences rely less on network trust in their trusting behaviors. We quantify that improved trust and trustworthiness can yield up to 41%, 6%, and 5% gain in the expected profit of the supplier, the retailer, and the supply chain. Our results offer tangible implications for how organizations can better leverage executives’ knowledge about how much to rely on network trust in business interactions to achieve better outcomes.
Extant theories of intertemporal choice entangle two aspects of time preference: impatience and time inconsistency. Impatient people focus on present consumption without worrying too much about the future; they may spend freely and avoid exercise. An outsider might question their choices, but impatient people do not experience conflict over those choices. By contrast, people who are time-inconsistent intend to save and exercise, but they fail to do so when temptation is proximate. Such individuals are conflicted; their preferences today differ from their preferences tomorrow. I characterize the interaction between impatience and time inconsistency in three leading models of temporal discounting that go beyond the exponential model, which does not predict time inconsistency at any level of impatience. The quasi-hyperbolic model predicts that time inconsistency increases with patience, whereas the hyperbolic model makes the opposite prediction. The constant-sensitivity model predicts that time inconsistency peaks at a moderate level of impatience. The results of an experiment using real monetary consequences with delays of up to one year align most closely with the prediction of the constant-sensitivity model.
This paper analyzes a two-person, two-stage model of sequential exploration where both information and payoff externalities exist and tests the derived hypotheses in the laboratory. We theoretically show that, even when agents are self-interested and perfectly rational, the information externality induces an encouragement effect: a positive effect of first player exploration on the optimality of the second player exploring as well. When agents have other-regarding preferences and imperfectly optimize, the encouragement effect is strongest. The explorative nature of the game raises the expected surplus compared with a payoff equivalent public goods game. We empirically confirm our main theoretical predictions using a novel experimental paradigm. Our findings are relevant for motivating and managing groups and teams innovating not only for private but also and especially so, for public goods.
Promoting contribution of content is a key challenge for platforms that support the collective creation or transfer of knowledge. We use a field experiment on a massive open online course to study the role of forum size (number of people in a forum) in the contribution of content per person. We find that larger forums elicit more contributions per person. The number of questions and other help-seeking threads posted per person was unchanged by forum size, but replies and other more conversational posts increased sharply. Most of the positive effect of size was in a subset of socially responsive subjects. The implication of social responsiveness driving our results is that the unequal distribution of contribution in online platforms is unlikely to be easily changed: if more contributions are elicited from infrequent contributors, the greatest contributors would contribute even more because there would be more to respond to.
The editors of Management Science acknowledge all our 2019 reviewers and guest associate editors, who generously provided expert counsel and guidance on a voluntary basis. We are grateful for their contributions; without them the journal could not function. Below, we list those reviewers who contributed four or more reviews in 2019.
Many online platforms rely on users to voluntarily provide content. What motivates users to contribute content for free, however, is not well understood. In this paper, we use a revealed-preference approach to show that career concerns play an important role in user contributions to Stack Overflow, the largest online question-and-answer community. We investigate how activities that can enhance a user’s reputation vary before and after the user finds a new job. We contrast this reputation-generating activity with activities that do not improve a user’s reputation. After finding a new job, users contribute 23.7% less in reputation-generating activity; by contrast, they reduce their non–reputation-generating activity by only 7.4%. These findings suggest that users contribute to Stack Overflow in part because they perceive such contributions as a way to improve future employment prospects. We provide direct evidence against alternative explanations such as integer constraints, skills mismatch, and dynamic selection effects.
Gender quotas are frequently proposed to address persistent gender imbalances in managerial roles. However, it is unclear how quotas for female managers affect organizations and whether quotas improve or damage relationships between managers and their subordinates. We conduct a representative survey to study opinions on quotas for female managers and, based upon the survey, design a novel set of experiments to investigate how quotas influence wage setting and effort provision. Our findings reveal that both opinions about gender quotas and workplace behavior crucially depend on the workplace environment. In our survey, we observe that approval for gender quotas is low if women are not disadvantaged in the manager-selection process, regardless of whether there are gender differences in performance. Complementing this evidence, we observe in our experiments that quotas lead to lower effort levels and lower wages in such environments. By contrast, in environments in which women are disadvantaged in the selection process, we observe a higher approval of quotas as well as higher effort levels and higher wages. These findings are consistent with the concept of meritocracy and suggest that it is important to evaluate the perception of gender disadvantages in the workplace environment before implementing quotas.
We demonstrate that lottery markets can exhibit the “hot-hand” phenomenon, in which past winning numbers tend to have a greater share of the betting proportion in future draws even though past and future events are independent. This is surprising as previous works have instead documented the presence of an opposite effect, the “gambler’s fallacy” in the U.S. lottery market. The current literature also suggests that the gambler’s fallacy prevails when random numbers are generated by mechanical devices, such as in lottery games. We use two sets of naturally occurring data to show that both the gambler’s fallacy and the hot-hand fallacy can exist in different types of lottery games. We then run online experimental studies that mimic lottery games with one, two, or three winning numbers. Our experimental results show that the number of winning prizes impacts behavior. In particular, whereas a single-prize game leads to a strong presence of the gambler’s fallacy, we observe a significant increase in hot-hand behavior in multiple-prize games with two or three winning numbers.
We investigate how firms use information technology (IT) implementation to mitigate an anomaly in capital markets: investors underreacting to new public information. The theory of information uncertainty (IU) suggests that the anomaly is amplified with IU; that is, with ambiguity in information about firm value. We theorize that a firm’s IT in general—and enterprise systems (ES) in particular—can mitigate IU, thus reducing the IU-induced underreaction anomaly. Based on a difference-in-differences analysis of a sample of 572 ES implementations, our main finding is that ES implementation does reduce IU-induced underreaction anomaly. This is achieved through a reduction in the firm’s fundamentals volatility and an improvement in information quality. We also find that firms with greater IT capability are better positioned to realize the anomaly-reducing benefits of ES implementation and that ES’s anomaly-reducing effect is most pronounced when high levels of both functional and operational ES modules are implemented. We obtain remarkably consistent results when using alternate empirical design, samples, and measures of news. Such IT impacts are economically highly consequential because they improve capital market efficiency.
This paper investigates the relationship between waiting time and subsequent purchase decisions. The prior literature assumes that purchase decisions are independent from the waiting time. By contrast, we find that when people spend a longer time waiting in a line, they tend to consume more. We identify mental accounting for sunk costs as the underlying mechanism that drives this behavior; a larger purchase allows customers to offset the long wait suffered. Finally, we explore the effect of managerial practices commonly employed by firms to improve customers’ waiting experience. We find that although these practices indeed result in improved customer experience, they can actually result in lower consumption at the individual level.
Despite their idiosyncrasies, motor and cognitive learning and endurance sports training have in common that they involve repeated practice. While considerable research has been devoted to the effect of practice on performance, little is known about optimal practice strategies. In this paper, we model the practice process for both skill acquisition and retention, and optimize its profile to maximize performance on a predefined date. For skill acquisition, we find that the optimal process involves multiple phases of practice increase and decrease, yielding U-shaped effort consistent with the principle of distributing practice, and that the transitions between phases are smoother for skills that are easily forgotten (e.g., cognitive skills) than for those that are easily retained (e.g., continuous motor skills). In particular for the latter, an extended period of rest should precede an ultimate high-intensity stress. For skill retention, the optimal practice strategy consists of cycles of either constant effort (for skills that are easily forgotten) or pulsed effort (for skills that are easily retained) consistent with the principle of alternating stress and rest. Our parametric model thus indicates when commonly used high-performance practice strategies are indeed optimal.
We propose a new measure for housing sentiment and show that it accurately tracks expectations of future house price growth rates. We construct the housing sentiment index using partial least squares on household survey responses to questions about buying conditions for houses. We find that housing sentiment explains a large share of the time variation in house prices during both boom and bust cycles, and it strongly outperforms several macroeconomic variables typically used to forecast house prices.
Ideas are connected. New ideas are often seen as creative combinations of previous ideas. I study these connections in the context of motion pictures. A network of 4,445 movies is constructed to indicate which movies are similar. I first examine the properties of the network using descriptive and regression analysis; then I develop a model of network formation for counterfactual analysis. It is found that most movies imitate and evolve around a “core” of the more successful movies. In addition, imitation is both conventional and atypical: a new movie usually follows a stream of similar movies yet simultaneously combines atypical elements from movies outside this stream. This atypicality, if well balanced, has a positive effect on the individual movie’s box office. However, I find that, in the long run, atypical combination may lead to a worse collective box-office performance because of the way it changes the market structure.
Just as employers face uncertainty when hiring workers, workers also face uncertainty when accepting employment, and bad employers may opportunistically depart from expectations, norms, and laws. However, prior research in economics and information sciences has focused sharply on the employer’s problem of identifying good workers rather than vice versa. This issue is especially pronounced in markets for gig work, including online labor markets, in which platforms are developing strategies to help workers identify good employers. We build a theoretical model for the value of such reputation systems and test its predictions on Amazon Mechanical Turk, on which employers may decline to pay workers while keeping their work product and workers protect themselves using third-party reputation systems, such as Turkopticon. We find that (1) in an experiment on worker arrival, a good reputation allows employers to operate more quickly and on a larger scale without loss to quality; (2) in an experimental audit of employers, working for good-reputation employers pays 40% higher effective wages because of faster completion times and lower likelihoods of rejection; and (3) exploiting reputation system crashes, the reputation system is particularly important to small, good-reputation employers, which rely on the reputation system to compete for workers against more established employers. This is the first clean field evidence of the effects of employer reputation in any labor market and is suggestive of the special role that reputation-diffusing technologies can play in promoting gig work, in which conventional labor and contract laws are weak.
Retailers colocate with rivals to take advantage of economies of agglomeration even though colocation implies greater competition. Using data on all new car transactions registered in Ohio from 2007 to 2014, we estimate a structural model of consumer search for spatially differentiated products that explicitly captures the agglomeration and competition effects of retail colocation. Search frictions generate an average of $333 per car in dealer markups. Agglomeration implies that dealer closures could harm incumbent colocated dealers, even though the incumbent dealers would face less competition. Our results inform the recent policy debate surrounding the massive downsizing of car retail networks and highlight the role of contagion in brick-and-mortar retailing.
How do emerging market corporates fare during periods of currency depreciation? We find that nonfinancial firms that exploit favorable global financing conditions to issue U.S. dollar bonds and build cash balances are also those whose share price is most vulnerable to local currency depreciation. In particular, firms’ vulnerability to currency depreciation derives less from the foreign currency debt as such, and more from the cash balances that are built up by using foreign currency debt. Overall, our results point to a financial motive for dollar bond issuance by emerging market firms in carry trade–like transactions that leave them vulnerable in an environment of dollar strength.
In uncertain environments, project reviews provide an opportunity to make “continue or abandon” decisions and thereby maximize a project’s expected payoff. We experimentally investigate continue/abandon decisions in a multistage project under two conditions: when the project is reviewed at every stage and when review opportunities are limited. Our results confirm findings in the literature that project abandonment tends to be delayed; yet, we also observe premature termination. Decisions are highly path dependent; in particular, subjects are more likely to abandon after observing reduced project value, and abandonment rate is higher near the middle—rather than near the beginning or end—of a project. Interestingly, when reviews are limited, subjects are less likely to continue a project that should be abandoned. At the same time, subjects are more inclined to review again after receiving negative (rather than positive) news. Our data are explained well by a model that incorporates three behavioral concepts—gains or losses from comparing the project value with an internal adaptive reference point, sunk cost bias, and status quo bias. Our work suggests that more frequent reviews need not lead to better project performance, and it also identifies contexts in which outside intervention is most valuable in project decision making.
Time-series data—measurements of a quantity over time—can be presented as stocks (the quantity at each point in time) or flows (the change in quantity from one point in time to the next). In a series of six experiments, we find that the choice of presenting data as stocks or flows can have a consequential impact on judgments. The same data can lead to positive or negative assessments when presented as stocks versus flows and can engender optimistic or pessimistic forecasts for the future. For example, when employment data from 2007 to 2013 are shown as flows (jobs created or lost), President Obama’s impact on the economy during his first year in office is viewed positively, whereas when the same data are shown as stocks (total jobs), his impact is viewed negatively. The results highlight a challenge that accompanies the growing reliance on data and analytics for decision making within organizations: seemingly benign choices—such as that between two informationally equivalent data presentations—can substantively impact how data are interpreted and used, even though the underlying information is the same.
We propose a new method to disentangle individual from team productivity, CoScore. CoScore uses the varying membership and levels of success of all teams to simultaneously infer an individual’s productivity and her credit for each of her teams’ successes. Crucially, the productivities of all individuals are determined endogenously via the solution of a fixed point problem. We show that CoScore is well defined, and we provide axiomatic foundations for the inferred credit allocation. We illustrate CoScore in scientific research and sports.
We investigate the joint impact of managers at different hierarchical levels on firm performance in Major League Baseball. We separately quantify the contribution of upper and middle managers and the impact of their match quality—the degree to which managers cooperate effectively across layers to impact firm success. We establish that match quality is a statistically significant and economically meaningful driver of firm performance. Higher-quality managers tend to be matched together across levels and achieve higher match quality during their joint employment. Match quality does not improve over the length of a joint employment spell, but lower match quality is found in pairs with more divergent educational attainment and prior strategic approaches. Hence, match quality is partly innate, and manager pairings may have difficulty improving their cooperation through learning. When we control for match quality, we find significantly lower estimates of heterogeneity in manager ability compared with commonly used estimators of managerial impact. Still, both middle and upper managers retain a meaningful impact on firm performance.
The behavioral literature has demonstrated that the format of supply chain contracts matters even when theoretically it should not and that contracts that in theory coordinate channels fail to do so in laboratory experiments. The existing body of experimental evidence uses an ultimatum bargaining protocol to test analytical models, but there is no reason to think that bargaining in supply chains is in the form of ultimatum offers. We investigate the effect of bargaining on contract performance by extending the bargaining protocol to allow the manufacturer to make concessions. We test coordinating contract with bargaining in the laboratory by comparing wholesale price and the two-part tariff contracts using two different bargaining protocols. We then develop and estimate a statistical model of behavior with bargaining and find that this model organizes our data well. Our main finding is that the contracts that we study are more efficient when participants are allowed to make concessions. The additional channel efficiency is owing to more efficient offers made by manufacturers. The higher channel efficiency primarily benefits the retailer—the weaker party. Our main contribution is the observation that, when testing analytical models of contracts in the laboratory, the way that the bargaining process is implemented, such as the ability to make concessions, has a critical effect on conclusions.
This paper studies how the ease of repossessing collateral in bankruptcy affects corporate leasing policy. Using plausibly exogenous variation of the ability to repossess assets generated by state antirecharacterization laws, I find that the antirecharacterization laws, which make collateral repossession easier for secured lending, reduces corporate leasing. Consistent with the argument that only financially constrained firms value additional debt capacity because of the increased ability to repossess assets, I find that the effect concentrates in financially constrained firms. I also find that the effect is much stronger for firms with less specific assets. In addition, I find that the laws also affect leverage, cash holding, and corporate investment.
This paper studies the dynamic propagation mechanisms of systemic risk shocks within and across macrosystems of governments and financial institutions. We propose a novel approach to identify relevant systemic shocks and to classify them into sovereign or banking categories. We find that sovereign shocks have a significant and persistent impact on the probability of a collective banking default. We also explore channels through which these shocks propagate and identify how sovereign fiscal fragility and banking exposure are relevant mechanisms of shock transmission.
We model an expert review system where two producers competing for market share each are evaluated by two raters. Employing economics experiments, the paper examines how the rater’s incentive to provide objective feedback can be distorted in the presence of social ties and different penalty structures for assigning unobjective ratings. The results reject the self-interested model. We find that raters assign more biased ratings to help the producer they know compete, and this distortion is exacerbated when the reputation cost for rating unobjectively is lowered. Counterintuitively, when both of the raters know the same producer, the likelihood of biased ratings drops significantly. To explain the empirical regularities, we develop a behavioral economics model and show that the rater’s utility function should account not only for social preferences toward the producer, but also the rater’s psychological aversion toward favoring a producer more than the other rater. Our findings demonstrate that it is critical for policymakers to be cognizant of the nonpecuniary factors that can influence behavior in expert review systems.
Because many key career events, such as examinations and interviews, involve competition and stress, gender differences in response to these factors could help to explain the labor market gender gap. In a laboratory experiment, we manipulate psychosocial stress using the Trier Social Stress Test and confirm that this is effective by measuring salivary cortisol level and heart rate. Subjects perform in a real-effort task under both tournament and piece-rate incentives, and we elicit willingness to compete. We find that women under heightened stress perform worse than women in the control group when compensated with tournament incentives, whereas there is no treatment difference under piece-rate incentives. For men, stress does not affect output under competition or under piece rate. The gender gap in willingness to compete is not affected by stress, but stress decreases competitiveness overall, which is related to performance for women. Our results could explain gender differences in performance under competition, with implications for hiring practices and incentive structures in firms.
Increasing a current payoff’s ambiguity from a precise value (e.g., $150) to a range (e.g., $140–$160) generally reduces the payoff’s appeal, as does delaying the payoff from, for example, now to one year from now. However, we report five studies in which adding small ranges to future payoffs increases future payoff appeal, an emergent property designated the future ambiguity effect. This effect generalizes across various choice sets, payoff levels, and delays, and it prevails even when a future smaller ambiguous payoff is preferred more than a future larger precise payoff. Two underlying processes are proposed and supported: (1) the payoff ambiguity’s explicit risk of receiving a smaller payoff distracts people from the future’s larger implicit risk of receiving nothing, and (2) payoff ambiguity restores some of the excitement lost to the future’s psychological distance. Nonetheless, the future ambiguity effect is not universal, given that larger ranges can reduce and even eliminate it (boundary condition).
Risk is an integral part of many economic decisions and is vitally important in finance. Despite extensive research on decision making under risk, little is known about how risks are actually perceived by financial professionals, the key players in global financial markets. In a large-scale survey experiment with 2,213 finance professionals and 4,559 laypeople in nine countries representing ~50% of the world’s population and more than 60% of the world’s gross domestic product, we expose participants to return distributions with equal expected return, and we systematically vary the distributions’ next three higher moments. Of these, skewness is the only moment that systematically affects financial professionals’ perception of financial risk. Strikingly, variance does not influence risk perception, even though return volatility is the most common risk measure in finance in both academia and the industry. When testing other, compound risk measures, the probability to experience losses is the strongest predictor of what is perceived as being risky. Analyzing professionals’ propensity to invest, skewness and loss probability also have strong predictive power, while volatility and kurtosis have some additional effect. Our results are very similar for laypeople, and they are robust across and within countries with different cultural backgrounds, as well as for different job fields of professionals.
New Internet-based “sharing-economy” markets enable consumer-owners to rent out their durable goods to nonowners. We model such markets and explore their equilibria both in the short run, in which ownership decisions are fixed, and in the long run, in which ownership decisions can be changed. We find that sharing-economy markets always expand consumption and increase surplus, but may increase or decrease ownership. Regardless, ownership is decoupled from individual preferences in the long run, as the rental rates and the purchase prices of goods become equal. If there are costs of bringing unused capacity to the market, they are partially passed through, creating a bias toward ownership. To test our theoretical work empirically, we conduct a survey of consumers, finding broad support for our modeling assumptions. The survey also allows us to offer a partial decomposition of the bring-to-market costs, based on attributes that make a good more or less amenable to being shared.
We study the role of vertical differentiation in the adoption of LEED (Leadership in Energy & Environmental Design), a multitier environmental building certification system. Our identification strategy relies on the timing of adoption and shows that builders seek to differentiate from each other by choosing a different certification level from previously certified buildings. A common concern in this framework is that mean-reverting behavior could be mistaken for differentiation. We develop a new method for establishing the importance of strategic interactions based on simulating from a model with independent choice and unobserved heterogeneity, and showing that such a model cannot generate the level of interaction that we observe. Finally, we estimate a model that incorporates both differentiation incentives and correlated market-level unobservables and use our estimates from this model to simulate the impact of reducing the number of LEED tiers from four to two. The simulations indicate that environmental investments depend on the location of the threshold between tiers.
Developing marketing campaigns for a new product or a new target population is challenging because of the scarcity of relevant historical data. Building on dynamic Bayesian learning, a sequential optimization assists in creating new data points within a finite number of learning phases. This procedure identifies effective advertisement design elements as well as customer segments that maximize the expected outcome of the final marketing campaign. In this paper, the marketing campaign performance is modeled by a multiplicative advertising exposure model with Poisson arrivals. The intensity of the Poisson process is a function of the marketing campaign features. A forward-looking measurement policy is formulated to maximize the expected improvement in the value of information in each learning phase. A computationally efficient approach is proposed that consists of solving a sequence of mixed-integer linear optimization problems. The performance of the optimal learning policy over a set of benchmark policies is evaluated using examples inspired from the property and casualty insurance industry. Further extensions of the model are discussed.
A field experiment involving 94,571 orders from 24,637 customers of an app-based laundry pick-up, cleaning, and delivery service examined the effects of various randomly assigned tip recommendations on consumers’ tip amounts, satisfaction ratings, frequency of return, and bill size. We find that tip recommendations affect tip amounts, but not customer satisfaction, patronage frequency, or bill size, which implies that neither the processes underlying the tip-recommendation effects on tipping nor consumer tipping itself affect these other consumer outcomes. From a practical perspective, these results and conclusions inform efforts to increase or decrease tipping. Recommending larger tip amounts, at least within the $2–$10 or 5%–25% ranges studied here, appears to be a safe means of increasing the amounts customers leave. More generally, altering customers’ tipping behavior will not itself adversely affect those customers’ subsequent satisfaction, repatronage, or spending, as long as the means used to alter tipping do not directly affect these other outcomes.
We study how monetary policy affects the funding composition of the banking sector. When monetary tightening reduces the supply of retail deposits, banks attempt to substitute wholesale funding for deposit outflows to smooth their lending. Because of financial frictions, banks have varying degrees of access to wholesale funding. Therefore, large banks, or those with greater reliance on wholesale funding, increase their wholesale funding more. Consequently, monetary tightening increases both the reliance on and the concentration of wholesale funding within the banking sector. Our findings also suggest that liquidity requirements could bolster monetary policy transmission through the bank lending channel.
We examine how regulatory burdens affect the investment and innovation of newly public firms. To do so, we exploit the Jumpstart Our Business Startups (JOBS) Act, which eliminates certain disclosure, auditing, and governance requirements for a subset of newly public firms. Firms treated with these reduced burdens invest more and more efficiently after going public relative to untreated firms. These findings are concentrated in innovative investments and are nonexistent in dual-class firms. Overall, our findings suggest that the burdens to being public exacerbate agency frictions, which lead managers to take on fewer risky projects.
We consider a single product dynamic pricing with demand learning. The candidate prices belong to a wide range of a price interval; the modeling of the demand functions is nonparametric in nature, imposing only smoothness regularity conditions. One important aspect of our model is the possibility of the expected reward function to be nonconcave and indeed multimodal, which leads to many conceptual and technical challenges. Our proposed algorithm is inspired by both the Upper-Confidence-Bound algorithm for multiarmed bandit and the Optimism-in-the-Face-of-Uncertainty principle arising from linear contextual bandits. The multiarmed bandit formulation arises from local-bin approximation of an unknown continuous demand function, and the linear contextual bandit formulation is then applied to obtain more accurate local polynomial approximators within each bin. Through rigorous regret analysis, we demonstrate that our proposed algorithm achieves optimal worst-case regret over a wide range of smooth function classes. More specifically, for k-times smooth functions and T selling periods, the regret of our proposed algorithm is O˜(T(K+1)/(2K+1)), which is shown to be optimal via the development of information theoretical lower bounds. We also show that in special cases, such as strongly concave or infinitely smooth reward functions, our algorithm achieves an O(T) regret, matching optimal regret established in previous works. Finally, we present computational results that verify the effectiveness of our method in numerical simulations.
We offer a new network perspective on one of the central topics in operations management—the bullwhip effect (BWE). The topic has both practical and scholarly implications. We start with an observation: the variability of orders placed to suppliers is larger than the variability of sales to customers for most firms, yet the aggregate demand variability felt by suppliers upstream does not amplify commensurably. We hypothesize that changes to the supplier’s customer base can smooth out its aggregate demand. We test the hypothesis with a data set that tracks the evolution of supply relationships over time. We show that the effect of customer base management extends beyond the statistical benefits of aggregation. In particular, both the formation and the dissolution of customer-supplier relationships are associated with the smoothing of the aggregate demand experienced by suppliers. This provides fresh insight into how firms may leverage their customer-supplier relationships to mitigate the impact of the BWE.
The competition for donations between charities is tough. Yet, little is known about how giving behavior is affected by competition between charities. Do people have a need to satisfy their demand for giving by contributing to a particular charity? Or can the demand for doing good be satisfied by giving to any organization? In a donation dictator game, I vary competition between charities by (i) altering the set of similar real charities to which subjects can donate and (ii) changing the relative price of giving to a randomly selected charity in the choice set by introducing a matching grant. I find weak substitution between charities when giving to more than one charity is possible, as the donated amounts to individual charities decrease with the size of the choice set. At the same time, aggregate giving to all charities increases when charities are in competition. Intensified competition through an increase in the charitable giving market seems to attract new giving and increases overall public good provision. Price competition, however, does not attract new donations when market size is constant and charities compete for donations. These findings carry important insights for managers of nonprofit organizations and provide information on how to improve existing fundraising strategies.
We contribute to the growing literature on the effectiveness of corporate boards by examining the effect of two insights that have been largely unexplored in prior studies that use public data. First, since boards’ responsibilities are wide-ranging, more holistic performance measures may better capture the full range of their duties than specific public actions and outcomes (e.g., disclosure of risk management processes, financial restatements, acquisition returns, CEO turnover). And second, because corporate boards share many characteristics of other types of teams, their effectiveness is likely to be influenced by their internal operations. To examine the performance effects of these insights, we use data from 577 directors of U.S. public firms that responded to a survey we conducted in 2015–2016 and qualitative data from interviews of 75 directors. Our study establishes a strong relation between director perceptions of board performance effectiveness and internal board operations. Further, by highlighting the critical role of internal operations, identifying areas of relative strength and weakness in boards’ effectiveness in various activities, and probing director perceptions of their primary responsibilities, we are able to offer concrete suggestions for future research on board effectiveness.
Competition plays an ambiguous role in nursing home markets where public and private payers coexist. Using U.S. nursing home data with a wide range of market structures, we find a U-shaped relationship between competition and service quality when nursing homes serve a mix of public and private segments, and a monotonically increasing relationship when nursing homes mostly serve the public, price-regulated, segment. The outcomes can be explained by the interplay of two opposing effects of competition: the reputation-building effect, whereby competing firms choose high quality to build a good reputation, and the rent-extraction effect, whereby competition hinders investment for quality improvements by lowering price premia. These observations are consistent with a repeated game model that incorporates public and private-payer segments.
This paper assembles a toolkit for the assessment of model risk when model uncertainty sets are defined in terms of an F-divergence ball around a reference model. We propose a new family of F-divergences that are easy to implement and flexible enough to imply convincing uncertainty sets for broad classes of reference models. We use our theoretical results to construct concrete examples of divergences that allow for significant amounts of uncertainty about lognormal or heavy-tailed Weibull reference models without implying that the worst case is necessarily infinitely bad. We implement our tools in an open-source software package and apply them to three risk management problems from operations management, insurance, and finance.
This research studies a resource pool-choice dilemma, in which a group of resource seekers independently choose between a larger pool containing more resources and a smaller pool containing fewer resources, knowing that the resources in each pool will be divided equally among its choosers, so that the more (fewer) people choose a certain pool, the fewer (more) resources each of them will get. This setting corresponds to many real-world situations, ranging from students choosing majors as a function of job opportunities to entrepreneurs choosing markets as a function of customer bases. Ten studies reveal a systematic undershooting bias: fewer people choose the larger pool relative to both the normative equilibrium benchmark and chance (random choice), thus advantaging those who choose the larger pool and disadvantaging those who choose the smaller pool. We present evidence showing that the undershooting bias is driven by bounded rationality in strategic thinking and discuss the relationship between our paradigm and other coordination games.
We examine a sample of dual-class firms to isolate the magnitude and duration of the demand-driven price effect from stock repurchases. In this novel setting, the non-repurchased class serves as a near-perfect counterfactual to the repurchased class and controls for private information about firm value contained in the repurchases. The average repurchase in our sample, 0.30% of outstanding shares within a month, increases the stock price by 40 to 70 basis points relative to the non-repurchased class of stock. The effect dissipates completely over the subsequent month unless extended by continued repurchases. This small, short-lived price effect leaves little scope for CEOs to benefit from value-destroying repurchases motivated by self-interest.
There is substantial variation in fixed-price call provision terms—call price premium and call protection. I investigate determinants of call price, call protection, and estimated call option value. Consistent with agency theory and asymmetric information models, I find that lower credit quality and opaque issuers choose higher call premiums, longer call protection, and overall less valuable call options. Higher-quality issuers, particularly financial institutions that struggle when interest rates are low, do the opposite.
We propose and validate a comprehensive measure of power for the top management teams (TMTs) of publicly listed Chinese firms. We show that our measure is positively associated with the four power dimensions developed by prior research for U.S. firms as well as three Asia-relevant power dimensions, including political capital, seniority, and gender. We find that our TMT power measure is a valid proxy for TMT power for both state-controlled firms and non-state-controlled firms. We also compare our TMT power measure with one alternative TMT power proxy based on executive compensation and find no evidence that the alternative proxy is better than our measure in capturing TMT’s true power. Further, we provide evidence that the divergence between our power proxy and the power proxy based on executive compensation reflects nonmarket institutional forces in China and has important implications for corporate outcomes.
Large institutional investors own an increasing share of the equity markets in the United States. The implications of this development for financial markets are still unclear. The paper presents novel empirical evidence that ownership by large institutions predicts higher volatility and greater noise in stock prices as well as greater fragility in times of crisis. When studying the channel, we find that large institutional investors exhibit traits of granularity (i.e., subunits within a firm display correlated behavior), which reduces diversification of idiosyncratic shocks. Thus, large institutions trade larger volumes and induce greater price impact.
Information products provide agents with additional information that can be used to update actions. In many situations, access to such products can be quite limited. For instance, in epidemics, there tends to be a limited supply of medical testing kits, or tests. These tests are information products because their output of a positive or a negative answer informs individuals and authorities on the underlying state and the appropriate course of action. In this paper, using an analytical model, we show how the accuracy of a test in detecting the underlying state affects the demand for the information product differentially across heterogeneous agents. Correspondingly, the test accuracy can serve as a rationing device to ensure that the limited supply of information products is appropriately allocated to the heterogeneous agents. When test availability is low and the social planner is unable to allocate tests in a targeted manner to the agents, we find that moderately good tests can outperform perfect tests in terms of social outcome.
Classical approaches to experimental design assume that intervening on one unit does not affect other units. There are many important settings, however, where this noninterference assumption does not hold, as when running experiments on supply-side incentives on a ride-sharing platform or subsidies in an energy marketplace. In this paper, we introduce a new approach to experimental design in large-scale stochastic systems with considerable cross-unit interference, under an assumption that the interference is structured enough that it can be captured via mean-field modeling. Our approach enables us to accurately estimate the effect of small changes to system parameters by combining unobtrusive randomization with lightweight modeling, all while remaining in equilibrium. We can then use these estimates to optimize the system by gradient descent. Concretely, we focus on the problem of a platform that seeks to optimize supply-side payments p in a centralized marketplace where different suppliers interact via their effects on the overall supply-demand equilibrium, and we show that our approach enables the platform to optimize p in large systems using vanishingly small perturbations.
Electricity end-users have been increasingly generating their own electricity via rooftop solar panels. We study the impact of such distributed renewable energy (DRE) on utility profits and social welfare under net metering, which is a widespread policy in the United States. Utilities have been lobbying against net-metered distributed solar based on the common belief that it harms utility profits. We find that when wholesale market dynamics are considered, net-metered DRE may be a positive for utilities. That is, net-metered DRE strictly improves the expected utility profit when the utility’s self-supply is below a threshold and the wholesale electricity price is sufficiently responsive to wholesale demand fluctuations. Our paper distinctively considers both downstream and upstream impacts of net-metered DRE on utilities and analyzes the tradeoff between these impacts. Net-metered DRE can increase utilities’ expenses because of their required buyback from generating customers, and reduces their retail sales revenues. In addition, it can either reduce utilities’ wholesale procurement costs or affect their wholesale market revenues. Our results suggest that utilities might benefit from emerging business strategies that motivate their customers to install solar panels. Our numerical study uses data on the distributed solar in California and the wholesale electricity market operated by the California Independent System Operator, and demonstrates that our findings hold under realistic parameters.
A person’s success often depends on whether others believe what they say. Growing evidence suggests that people are less likely to believe statements made by women rather than men. We consider whether assertive cheap talk, an important and widely used tool for increasing credibility, is a mechanism for this gender gap. If women face negative returns to assertive cheap talk, then they have less access to an effective tool for increasing their credibility. We provide evidence using a laboratory experiment and an online replication, both with real stakes, in an advice-following setting. We study whether assertive cheap talk affects advice following, whether subjects discriminate based on advisor gender, and whether there are differential returns to assertive cheap talk by gender. Subjects were randomly assigned to an unseen male or female team leader who were otherwise identical and to different types of prescripted, increasingly assertive written communication from the leader. Assertive language significantly increased advice following, but we find no evidence for gender discrimination. We also find that assertive language had positive returns for both male and female leaders, despite subjects perceiving this language as more masculine. However, female subjects were still less likely to choose the self-promotional language. Thus, even in the absence of discrimination, this choice would reduce adherence to advice provided by women, generating a gender gap. Greater use of assertive language could be an effective strategy for women to increase their influence and credibility in the labor market.
The Lucas tree model [Lucas RE Jr (1978) Asset prices in an exchange economy. Econometrica 46(6):1429–1445.] lies at the heart of modern macrofinance. At its core, it provides an analysis of the equilibrium price of a long-lived asset in an exchange economy where consumption is the objective and the sole purpose of the asset is to smooth consumption through time. Experimental tests of the model use a particular instantiation of the Lucas model. Here we adopt a different instantiation to the first two, extending their analyses from a two-period oscillating world to a three-period cyclical world; this is partly to test the robustness of their results. We also go one step further and compare this solution (to a consumption-smoothing problem), in which consumption claims are traded via the long-lived asset, with the alternative solution provided by a market, in which agents can directly trade (short-lived) consumption claims between periods. We find that the latter exchange economy is more efficient in encouraging consumption smoothing than the economy with the long-lived asset. We find evidence of uncompetitive trading in both markets.
Business degrees are popular and lead to high earnings. Female business graduates, however, earn less than their male counterparts. These gender differences can be traced back to university, where women shy away from majors like finance that lead to high earnings. In this paper, we investigate how the gender composition of peers in business school affects women’s and men’s major choices and labor market outcomes. We find that women who are randomly assigned to teaching sections with more female peers become less likely to choose male-dominated majors like finance and more likely to choose female-dominated majors like marketing. After graduation, these women end up in jobs where their earnings grow more slowly. Men, on the other hand, become more likely to choose male-dominated majors and less likely to choose female-dominated majors when they had more female peers in business school. However, men’s labor market outcomes are not significantly affected. Taken together, our results show that studying with more female peers in business school increases gender segregation in educational choice and affects labor market outcomes.
We present experiments exploring why high ability workers join teams with less able coworkers when there are no short-term financial benefits. We distinguish between two explanations: prosocial preferences and expected long-term financial gains from teaching future teammates. Participants perform a real-effort task and decide whether to work independently or join a two-person team. Treatments vary the payment scheme (piece rate or revenue sharing), whether teammates can communicate, and the role of teaching. High ability workers are more willing to join teams in the absence of revenue sharing and less willing to join teams when they cannot communicate. When communication is possible, the choice of high ability workers to join teams is driven by expected future financial gains from teaching rather than some variety of prosocial preferences. This result has important implications for the role of adverse selection in determining the productivity of teams.
This study provides a comprehensive model of an agent’s behavior in response to multiple sales management instruments, including compensation, recruiting/termination, and training. The model takes into account many of the key elements that constitute a realistic sales force setting: allocation of effort, forward-looking behavior, present bias, training effectiveness, and employee selection and attrition. By understanding how these elements jointly affect agents’ behavior, the study provides guidance on the optimal design of sales management policies. A field validation, by comparing counterfactual and actual outcomes under a new policy, attests to the accuracy of the model. The results demonstrate a tradeoff between adjusting fixed and variable pay; how sales training serves as an alternative to compensation; a potential drawback of hiring high-performing, experienced salespeople; and how utilizing a leave package leads to sales force restructuring. In addition, the study offers a key methodological contribution by providing formal identification conditions for hyperbolic time preference. The key to identification is that under a multiperiod nonlinear incentive system, an agent’s proximity to a goal affects only future payoffs in nonpecuniary benefit periods, providing exclusion restrictions on the current payoff.
Growing literature points to the effectiveness of leveraging social interactions and nudges to spur adoption of prosocial behaviors. This study investigates a large-scale behavioral intervention designed to actively leverage social learning and peer interactions to encourage adoption of residential solar photovoltaic systems. Municipalities choose a solar installer offering group pricing and undertake an informational campaign driven by volunteer ambassadors. We find a causal treatment effect of 37 installations per municipality from the campaigns and no evidence of harvesting or persistence. The intervention also lowers installation prices. Randomized controlled trials based on the intervention show that selection into the program is important, whereas group pricing is not. Our results suggest that the program provided economies of scale and lowered consumer acquisition costs, leading to low-cost emission reductions.
Media dissemination plays an important role in facilitating price discovery. Political pressure that restricts media dissemination can hinder this function and affect investors’ perceptions. This paper studies the magnitude of newspaper censorship in China and its economic consequences using a setting of tunneling scandals. We find significant evidence of censorship of tunneling-related negative news at the national and local levels. We further show that news that survives censorship reduces information asymmetry and improves pricing efficiency. Censorship blocks informative tunneling news and delays incorporation of tunneling reporting into prices.
Using transaction-level credit-card spending from a large U.S. financial institution, we show that disaggregated sales provide accurate and persistent signals of customer demand relevant to a firm’s stock pricing. After controlling for earnings and sales surprises, one interquintile increase in the adjusted customer spending during a firm’s fiscal quarter leads to a 1.5 percentage point increase in the 60-day post–earnings announcement cumulative abnormal return. The predictability concentrates in consumer-oriented firms, especially those relying more on indirect sales distribution channels. We also find a stronger return response to spending from high-FICO-score, high-liquidity, and loyal customers. The transmission speed of disaggregated sales information is slower than that of the earnings information, and small firms or firms far from their end customers exhibit a more delayed price response. Finally, the return implications of adjusted customer spending extend to firms along the production chain.
This paper studies whether euphemisms obfuscate the content of earnings conference calls and cause investors to underreact. I argue that managers’ use of euphemisms can alleviate the impact of bad news and delay the market reaction to adverse information. Using a dictionary of corporate euphemisms, I find that their use by managers—but not by analysts—is negatively associated with both immediate and future abnormal returns, and their frequency moderates the negative market reaction to bad earnings news. Finally, stock underreaction is more pronounced on busy earnings announcement dates, when investor attention is distracted.
I study the role of accounting and financial reporting in entrepreneurial finance by examining whether financial statement disclosure increases capital raised through equity crowdfunding. On average, I find a positive association between financial reporting and capital raised, suggesting that accounting reduces information asymmetry with potential investors. Additionally, the importance of financial reporting in equity crowdfunding varies predictably in the cross-section. Specifically, financial reporting is associated with greater capital raised when the firm has longer historical operations, during periods of higher macroeconomic uncertainty, and when complemented by detailed shareholder agreements. Finally, using a mediation analysis, I find evidence that financial reporting is indirectly associated with better ex post performance by increasing the likelihood of raising capital. These results provide insight into the role of financial reporting in entrepreneurial finance and inform the ongoing debate over regulation and disclosure in the equity crowdfunding market.
We use a novel panel with detailed transaction records of more than one million de-identified individuals to study the effect of a large-scale Chinese government-issued digital coupon program on consumer spending. Exploiting a difference-in-differences approach, we find that the digital coupon is highly effective in stimulating consumption. An effective government subsidy of RMB 1 can drive excess spending of RMB 3.4 to RMB 5.8, and the effect persists across multiple coupon issuance waves. In explaining the results, we find that a behavioral model with mental accounting and loss aversion can match the empirical evidence from the field. Our analysis, by illustrating the importance of embedding behavioral factors into the design and implementation of public policy, informs the current debate about cost-effective policy tools to recover the economy.
In an influential study, Bender et al. [Bender S, Bloom N, Card D, Van Reenen J, Wolter S (2018) Management practices, workforce selection, and productivity. J. Labor Econom. 36(S1):S371–S409] document consistent relationships between management practices, productivity, and workforce composition using administrative data from German firms matched to ratings of their practices from the World Management Survey. We replicate and extend their analysis using comparable data from Brazil. The main conclusions from their study are supported in ours, strengthening the view that more structured practices affect organizational performance through workforce selection across different institutional settings. However, we find that more structured management practices are linked to greater wage inequality in Brazil, relative to greater wage compression in Germany, suggesting that some of the consequences of adopting structured practices are tied to the local context.
I examine how patent enforcement affects corporate research and development (R&D), exploiting the legal changes induced by the Supreme Court decision eBay v. MercExchange. This ruling increased courts’ flexibility in remedying patent cases and effectively lowered the potential costs of patent litigation for defendants. For identification, I compare innovative activity across firms differentially exposed to patent litigation before the ruling. Across several measures, I find that the decision led to a general increase in innovation. This result confirms that the changes in enforcement induced by the ruling reduced some of the distortions caused by patent litigation. Exploring the channels, I show that patent litigation negatively affects investment because it lowers the returns from R&D and exacerbates its financing constraints.
We develop a model of many-to-one matching markets in which agents with multiunit demand aim to maximize a cardinal linear objective subject to multidimensional knapsack constraints. The choice functions of agents with multiunit demand are therefore not substitutable. As a result, pairwise stable matchings may not exist and even when they do, may be highly inefficient. We provide an algorithm that finds a group-stable matching that approximately satisfies all the multidimensional knapsack constraints. The novel ingredient in our algorithm is a combination of matching with contracts and Scarf’s Lemma. We show that the degree of the constraint violation under our algorithm is proportional to the sparsity of the constraint matrix. The algorithm, therefore, provides practical constraint violation bounds for applications in contexts, such as refugee resettlement, day care allocation, and college admissions with diversity requirements. Simulations using refugee resettlement data show that our approach produces outcomes that are not only more stable, but also more efficient than the outcomes of the Deferred Acceptance algorithm. Moreover, simulations suggest that in practice, constraint violations under our algorithm would be even smaller than the theoretical bounds.
We study how institutional investor attention to a firm affects the timeliness of analysts’ forecasts for that firm. We measure abnormal institutional attention (AIA) using Bloomberg news search activity for the firm on earnings announcement days. We find that analysts issue more timely forecasts when AIA is high on the earnings announcement day. Analyst responsiveness to AIA is stronger when analysts have more resources and experience and weaker when the AIA of other covered firms is high. Analysts who respond more to AIA are more likely to be named all-star analysts and less likely to be demoted to a smaller brokerage. We address endogeneity concerns using a measure of expected AIA that is unaffected by concurrent information. Our findings suggest that responsiveness to institutional attention influences the production of analyst research and analysts’ career outcomes.
Motivated by recent initiatives to increase transparency in procurement, we study the effects of disclosing information about previous purchases in a setting where an organization delegates its purchasing decisions to its employees. When employees can use their own discretion, which may be influenced by personal preferences, to select a supplier, the incentives of the employees and the organization may be misaligned. Disclosing information about previous purchasing decisions made by other employees can reduce or exacerbate this misalignment, as peer effects may come into play. To understand the effects of transparency, we introduce a theoretical model that compares employees’ actions in two settings: one where employees cannot observe each other’s choices and one where they can observe the decision previously made by a peer before making their own. Two behavioral assumptions are central to our model: that employees are heterogeneous in their reciprocity toward their employer, and that they experience peer effects in the form of income inequality aversion toward their peer. As a result, our model predicts the existence of negative spillovers as a reciprocal employee is more likely to choose the expensive supplier (which gives the employee a personal reward) when the employee observes that a peer did so. A laboratory experiment confirms the existence of negative spillovers and the main behavioral mechanisms described in our model. A surprising result not predicted by our theory is that employees whose decisions are observed by their peers are less likely to choose the expensive supplier than the employees in the no-transparency case. We show that observed employees’ preferences for compliance with the social norm of appropriate purchasing behavior explain our data well.
This paper experimentally examines a conflict of interest (COI) situation in which a third-party reviewer provides a product assessment for a firm but also potentially benefits economically from the assessed firm’s rival. We present a behavioral economics model to examine how reviewer competition and reciprocal relationships between firms and reviewers affect decision outcomes, followed by an experiment to investigate the model predictions. The experimental results are consistent with the behavioral model predictions. In particular, we empirically document a COI problem where the third-party reviewer’s report is biased, and consequently, the assessed firm underinvests in product quality. We find that this adverse result is driven by reciprocity between the third-party reviewer and the assessed firm’s rival. When we introduce an additional reviewer such that there is competition among the third-party reviewers, reporting biases are alleviated, and firms raise product quality levels. Interestingly, however, when informal agreements exist between the third-party reviewer and the assessed firm’s rival, reviewer competition exacerbates biases even more compared with the case without competition, further undermining the assessed firm’s incentive to invest in product quality.
A four-year series of subjective probability forecasting tournaments sponsored by the U.S. intelligence community revealed a host of replicable drivers of predictive accuracy, including experimental interventions such as training in probabilistic reasoning, anti‐groupthink teaming, and tracking of talent. Drawing on these data, we propose a Bayesian BIN model (Bias, Information, Noise) for disentangling the underlying processes that enable forecasters and forecasting methods to improve—either by tamping down bias and noise in judgment or by ramping up the efficient extraction of valid information from the environment. The BIN model reveals that noise reduction plays a surprisingly consistent role across all three methods of enhancing performance. We see the BIN method as useful in focusing managerial interventions on what works when and why in a wide range of domains. An R-package called BINtools implements our method and is available on the first author’s personal website.
Consider a canonical problem in choice under uncertainty: choosing from a convex feasible set consisting of all (Anscombe–Aumann) mixtures of two acts f and g, {αf+(1−α)g:α∈[0,1]}. We propose a preference condition, monotonicity in optimal mixtures, which says that surely improving the act f (in the sense of weak dominance) makes the optimal weight(s) on f weakly higher. We use a stylized model of a sales agent reacting to incentives to illustrate the tight connection between monotonicity in optimal mixtures and a monotone comparative static of interest in applications. We then explore more generally the relation between this condition and preferences exhibiting ambiguity-sensitive behavior as in the classic Ellsberg paradoxes. We find that monotonicity in optimal mixtures and ambiguity aversion (even only local to an event) are incompatible for a large and popular class of ambiguity-sensitive preferences (the c-linearly biseparable class. This implies, for example, that maxmin expected utility preferences are consistent with monotonicity in optimal mixtures if and only if they are subjective expected utility preferences. This incompatibility is not between monotonicity in optimal mixtures and ambiguity aversion per se. For example, we show that smooth ambiguity preferences can satisfy both properties as long as they are not too ambiguity averse. Our most general result, applying to an extremely broad universe of preferences, shows a sense in which monotonicity in optimal mixtures places upper bounds on the intensity of ambiguity-averse behavior.
Destigmatization is an understudied social process in which the negative outcomes for a previously stigmatized group improve. We theorize that during a period of destigmatization, the effects of stigma persist more strongly for people stigmatized by association than for those directly stigmatized. We propose that this occurs because, during periods of destigmatization, conscious prejudice has diminished but nonconscious prejudice remains, so people correct for their explicit biases toward individuals with the stigmatizing trait but are unaware of their ongoing implicit prejudice toward those stigmatized by association. Our evidence comes from archival data on individual employment in film during the cold war years in Hollywood. It shows that as the stigma of being on an anticommunist blacklist weakened, the employment penalty for being a coworker of a blacklisted artist was greater than the penalty for actually having been on the blacklist itself. A supplemental experiment, designed to address the limitations of archival data, shows the same imbalanced employment penalties in another stigma currently undergoing destigmatization (that of physical disability). Paradoxically, as stigmas recede, harmful effects persist more for associates of stigmatized individuals than for the stigmatized themselves.
What are the long-term consequences of compensation changes? Using data from an inbound sales call center, we study employee responses to a compensation change that ultimately reduced take-home pay by 7% for the average affected worker. The change caused a significant increase in the turnover rate of the firm’s most productive employees, but the response was relatively muted for less productive workers. On-the-job performance changes were minimal among workers who remained at the firm. We quantify the cost of losing highly productive employees and find that their heightened sensitivity to changes in compensation limits managers’ ability to adjust incentives. Our results speak to a driver of compensation rigidity and the difficulty managers face when setting compensation.
The shortest-remaining-processing-time (SRPT) scheduling policy has been extensively studied, for more than 50 years, in single-server queues with infinitely patient jobs. Yet, much less is known about its performance in multiserver queues. In this paper, we present the first theoretical analysis of SRPT in multiserver queues with abandonment. In particular, we consider the M/GI/s+GI queue and demonstrate that, in the many-sever overloaded regime, performance in the SRPT queue is equivalent, asymptotically in steady state, to a preemptive two-class priority queue where customers with short service times (below a threshold) are served without wait, and customers with long service times (above a threshold) eventually abandon without service. We prove that the SRPT discipline maximizes, asymptotically, the system throughput, among all scheduling disciplines. We also compare the performance of the SRPT policy to blind policies and study the effects of the patience-time and service-time distributions.
A stochastic bound is a portfolio that stochastically dominates all alternatives in a reference portfolio set instead of a single alternative portfolio. An approximate bound is a portfolio that comes as close as possible to this ideal. To identify and analyze exact or approximate bounds, feasible approaches to numerical optimization and statistical inference are developed based on linear programming and subsampling. The use of reference sets and stochastic bounds is shown to improve investment performance in representative applications to enhanced benchmarking using equity industry rotation and equity index options combinations.
Both theory and evidence are mixed regarding the impact on prices of trading on “dark” venues partially exempt from National Market System requirements. Theory predicts that price discovery improves as dark venues siphon noisy uninformed trades, but increased adverse selection reduces liquidity. Empirical studies, which focus on intraday inefficiency, also find contradictory results. We extend that literature to investigate the impact of dark trading on a long-standing inefficiency based on under-reaction to quarterly earnings. We study a randomized controlled trial created by the “trade-at” rule of the Securities and Exchange Commission’s Tick Size Pilot Program that exogenously shocks dark trading. We supplement that with ordinary least squares and two-stage least squares regressions on a more representative Compustat/Center for Research in Security Prices sample. All our results suggest that under-reaction increases with dark trading, consistent with reduced liquidity limiting arbitrage. We contribute to the literature on dark trading and inefficient processing of accounting disclosures, highlighting the role of advances in trading technology.
We show that, in the presence of a risk-free asset, the return distribution of every portfolio is determined by its mean and variance if and only if asset returns follow a specific skew-elliptical distribution. Thus, contrary to common belief among academics and practitioners, skewed returns do not allow a rejection of mean-variance analysis. Our work differs from Chamberlain's [Chamberlain G (1983) A characterization of the distributions that imply mean-variance utility functions. J. Econom. Theory 29(1):185–201.] by focusing on the returns of portfolios, where the weights over the risk-free asset and the risky assets sum to unity. Furthermore, it extends Meyer's [Meyer J, Rasche RH (1992) Sufficient conditions for expected utility to imply mean-standard deviation rankings: Empirical evidence concerning the location and scale condition. Econom. J. (London) 102(410):91–106.] by introducing elliptical noise into their generalized location-scale framework. To emphasize the relevance of our skew-elliptical model, we additionally provide empirical evidence that it cannot be rejected for the returns of typical portfolios of common stocks or popular alternative investments.
The idiosyncratic volatility (IVOL) anomaly exhibits strong calendar effects. The negative relation between IVOL and the next-month return obtains mainly in the third week of the month. The IVOL-return relation is generally negative on Mondays and positive on Fridays. However, the positive impact is absent on the third Friday because of selling pressure from stocks delivered at option expiration. This imbalance between the negative and positive returns during the third week of the month has a large impact on the IVOL-return relation. Removing the third Friday and subsequent Monday return reduces the monthly IVOL effect by at least 40%.
We show that the difference between the natural rate of interest and the current level of monetary policy stance, which we label Convergence Gap (CG), contains information that is valuable for bond predictability. Adding CG in forecasting regressions of bond excess returns significantly raises the R2, and restores countercyclical variation in bond risk premia that is otherwise missed by forward rates. Consistent with the argument that CG captures the effect of real imbalances on the path of rates, our factor has predictive ability for real bond excess returns. The importance of the gap remains robust out-of-sample and in countries other than the United States. Furthermore, its inclusion brings significant economic gains in the context of dynamic conditional asset allocation.
This study investigates how headquarters’ involvement affects the efficiency of transfer price negotiations. Although prior research explores autonomous transfer price negotiations, evidence suggests that headquarters can become involved in these negotiations, particularly after they fail. Although the likely intention of headquarters’ involvement is to overcome inefficiencies arising from decentralized managers’ inability to agree on a transfer price, we suggest that such involvement can reduce agreement frequency and the efficiency of transfer pricing in coordinating transfers between divisions. Reduced agreement may occur because involvement can reduce managers’ perceived responsibility for the negotiation outcome and because they may expect headquarters’ decision to be more favorable for them than a negotiated price. Headquarters’ involvement can also reduce the coordination efficiency of transfer pricing because of information asymmetries and headquarters’ decision biases in interpreting negotiation failure and using available information. In an experiment, we manipulate whether headquarters’ involvement is absent or present. We also manipulate whether headquarters suggests a nonbinding price (weak involvement) or whether it imposes a price on divisions (strong involvement). Consistent with our predictions, we find that headquarters’ involvement reduces the frequency of negotiation agreement and the coordination efficiency of transfer pricing. Efficiency is reduced more when involvement is strong rather than weak. We contribute to research by studying managers’ negotiation behavior in the realistic setting of potential headquarters’ involvement and by providing evidence on headquarters’ biased perceptions of negotiation impasse and the unintended consequences of its involvement.
The editors of Management Science acknowledge all our 2020 reviewers and guest associate editors, who generously provided expert counsel and guidance on a voluntary basis. We are grateful for their contributions; without them the journal could not function. Below, we list those reviewers who contributed four or more reviews in 2020.
We identify analysts’ information acquisition patterns by linking EDGAR (Electronic Data Gathering, Analysis, and Retrieval) server activity to analysts’ brokerage houses. Analysts rely on EDGAR in 24% of their estimate updates with an average of eight filings viewed. We document that analysts’ attention to public information is driven by the demand for information and the analysts’ incentives and career concerns. We find that information acquisition via EDGAR is associated with a significant reduction in analysts’ forecasting error relative to their peers. This relationship is likewise present when we focus on the intensity of analyst research. Attention to public information further enables analysts to provide forecasts for more time periods and more financial metrics. Informed recommendation updates are associated with substantial and persistent abnormal returns, even when the analyst accesses historical filings. Analysts’ use of EDGAR is associated with longer and more informative analysis within recommendation reports.
Organizations often require agents’ private information to achieve critical goals such as efficiency or revenue maximization, but frequently it is not in the agents’ best interest to reveal this information. Strategy-proof mechanisms give agents incentives to truthfully report their private information. In the context of matching markets, they eliminate agents’ incentives to misrepresent their preferences. We present direct field evidence of preference misrepresentation under the strategy-proof deferred acceptance in a high-stakes matching environment. We show that applicants to graduate programs in psychology in Israel often report that they prefer to avoid receiving funding, even though the mechanism preserves privacy and funding comes with no strings attached and constitutes a positive signal of ability. Surveys indicate that other kinds of preference misrepresentation are also prevalent. Preference misrepresentation in the field is associated with weaker applicants. Our findings have important implications for practitioners designing matching procedures and for researchers who study them.
Precise, compared with round, asking prices lead to counteroffers and final agreements that are closer to the asking price. Consequently, popular advice for sellers is to set precise asking prices. We propose that the advice is useful, but only in a buyer’s market, in which buyers counter below the asking price. In a seller’s market, in which buyers counter above the asking price, sellers who wish to receive high counteroffers and sell for high prices should set round asking prices. A preregistered study (n = 1,809) shows that, compared with round asking prices, precise prices lead to higher counteroffers in a buyer’s market but to lower counteroffers in a seller’s market. The effect is driven by buyers’ use of a finer-grained pricing scale when countering precise asking prices. An analysis of transactions (n = 8,278) from Amsterdam’s 2017 real estate market, in which 70% of the properties were sold above the asking price, corroborates the experimental findings. Results show that increasing the roundness of the asking price by one decimal, for instance, from precise to the thousands to precise to the tens of thousands, was associated with an increase of 0.6% in the selling price, equivalent to €2,099 on average.
Aggregate implied volatility spread (IVS), defined as the cross-sectional average difference in the implied volatilities of at-the-money call and put equity options, is significantly and positively related to future stock market returns at daily, weekly, and monthly to semiannual horizons. This return predictive power is incremental to existing return predictors, and it is significant both in sample and out of sample. Furthermore, IVS can forecast macroeconomic news up to one year ahead. The return predictability concentrates around macro news announcement. Common informed trading in equity options offers an integrated explanation for the ability of IVS to predict both future stock market returns and real economic activity.
This paper documents the effects of last-place aversion in queues and its implications for customer experiences and behaviors, as well as for operating performance. An observational analysis of customers queuing at a grocery store, and four online studies in which participants waited in virtual queues, revealed that waiting in last place diminishes wait satisfaction while increasing the probabilities of switching and abandoning queues, with detrimental implications for queuing systems. The research suggests that last-place aversion can lead to maladaptive customer behaviors—switching behaviors that increase wait times and abandoning when the benefits of waiting are most pronounced. The results indicate that this behavior is partially explained by the inability to make a downward social comparison; namely, when no one is behind a queuing individual, that person is less certain that continuing to wait is worthwhile. Furthermore, this paper provides evidence that queue transparency is an effective service design lever that managers can use to reduce the deleterious effects of last-place aversion in queues. When people cannot see that they are in last place, the behavioral effects of last-place aversion are nullified; and when they can see that they are not in last place, the tendency to renege is greatly diminished. Finally, a system-level experiment, in which pairs of queues were created and analyzed, reveals that when the effects of last-place aversion are addressed, overall abandonment decreases, such that with equivalent arrival and service rates, total service provision can be increased.
This paper investigates the impact of customer compatibility—the degree of fit between customers’ needs and the capabilities of the operations serving them—on customer experiences and firm performance. We use variance decomposition analysis to quantify the relative importance of customer, employee, process, location, and market-level effects on customer satisfaction. In our models, which explain roughly a quarter of the aggregate variance, differences among customers account for 96%–97% of the explainable portion. Further analysis of interaction-level data from banking and quick-service restaurants reveals that customers report relatively consistent satisfaction across transactions with particular firms but that some customers are habitually more satisfied than others. A second set of empirical studies provides evidence that these customer-level differences are explained in part by customer compatibility. Customers whose needs, proxied by differences in demographics and product choices, diverge more starkly from those of their bank’s average customers report significantly lower levels of satisfaction. Consistently, banks that serve customer bases with more dispersed needs receive lower satisfaction scores than banks serving customer bases with less dispersed needs. Finally, a longitudinal analysis of the deposit and loan growth of all federally insured banks in the United States from 2006 to 2017 reveals that customer compatibility affects a firm’s financial performance. Branches with more divergent customers grow more slowly than branches with less divergent customers. Institutions serving customer bases with more dispersed needs have branches that exhibit slower growth than those of institutions serving customer bases with less dispersed needs.
This paper develops a new algorithm for increasing the revenue in a dynamic product assortment problem. Then, it identifies the challenges faced by managers in practice and discusses the conditions under which workers follow the algorithm. To do so, I conducted a field experiment with a beverage vending machine business. The experiment shows that, on average, workers are reluctant to follow the algorithmic advice; however, the workers are more willing to conform once their forecasts are integrated into the algorithm. Analyses using nonexperimental variations highlight the importance of taking worker and context heterogeneity into account to maximize the benefit from adopting a new algorithm. Higher worker’s regret, sales volatility, and fewer delegations increase the conformity, while they mitigate the effects of integration. Workers avoid high-traffic vending machines and focus on machines with high sales volatility when adopting the algorithm. The effects on the sales are largely similar to the effects on product assortments. The results emphasize the gap between nominal and actual performance of an algorithm and several practical issues to be resolved.
We show that a firm’s ability to access the public bond market for the first time is greatly improved when habitual dual holders (HDHs)—financial conglomerates that tend to simultaneously hold both equity and bonds of their portfolio firms—are among its shareholders. HDHs are more likely to buy bonds in a bond initial public offering (IPO) and to take larger bond positions than bond investors with no equity in the firm. Greater equity ownership by HDHs is associated with a higher fraction of the issue ending up in the hands of pre-IPO shareholders, lower offering yield spreads, and more covenants overall but fewer covenants that restrict payout to shareholders.
We show that technology spillovers shift the composition of corporate research and development by promoting innovation based on the exploitation of existing knowledge while disincentivizing innovation that explores new areas and breaks new ground. Accordingly, firms facing large technology spillovers attain fewer superstar inventors among their human capital, who are important drivers of breakthrough technology advancement. These findings complement the existing studies documenting the positive effect of technology spillovers in increasing firms’ overall innovation outputs; they highlight potential downsides of technology spillovers in reducing firm investment in technology breakthrough and valuable human capital.
Using a rational expectations equilibrium framework, I evaluate the effects of a short-sale prohibition in an economy with asymmetrically informed investors who are identical except for their information sets. Relative to an economy in which short selling is permitted, the financial market is less informationally efficient under a short-sale ban even when the ban is not binding. This alters the risk-sharing environment and leads to an increase in information acquisition. Additionally, a short-sale prohibition increases market depth. Imposing a cost on short selling instead of a strict prohibition yields similar results. Novel empirical implications are identified.
This study investigates the comprehensive and multidimensional effects of quota (goal) frequency on sales force performance. The study provides a theory of salespeople’s behavior—aggregate effort and the product-type focus—in response to the temporal length of a sales quota cycle. The theory includes many realistic elements, such as salespeople’s multidimensional effort, heterogeneity in ability, product focus, and forward-looking behavior. We test the theory through a field experiment, varying the sales compensation structure of a major retail chain in Sweden. Consistent with the developed theory, shifting to a temporally frequent quota structure leads to an increase in sales performance for low-performing salespeople by preventing them from giving up in later periods within a quota-evaluation cycle, but to a decrease in sales performance for high-performing salespeople. With quotas set over short time horizons, the high-performing salespeople focus mainly on low-ticket products, resulting in a decrease in both sales volume and the sale of high-ticket products, thus reducing the firm’s profits.
Even when human point forecasts are less accurate than data-based algorithm predictions, they can still help boost performance by being used as algorithm inputs. Assuming one uses human judgment indirectly in this manner, we propose changing the elicitation question from the traditional direct forecast (DF) to what we call the private information adjustment (PIA): how much the human thinks the algorithm should adjust its forecast to account for information the human has that is unused by the algorithm. Using stylized models with and without random error, we theoretically prove that human random error makes eliciting the PIA lead to more accurate predictions than eliciting the DF. However, this DF-PIA gap does not exist for perfectly consistent forecasters. The DF-PIA gap is increasing in the random error that people make while incorporating public information (data that the algorithm uses) but is decreasing in the random error that people make while incorporating private information (data that only the human can use). In controlled experiments with students and Amazon Mechanical Turk workers, we find support for these hypotheses.
The ongoing shortage of pharmaceutical drugs critically threatens public health. With increasing industry consolidation, operational disruptions at a firm can lead to a nationwide shortage of life-saving drugs. In 2012, the U.S. Food and Drug Administration mandated all manufacturers to report any manufacturing interruption that can potentially cause shortages. The goal of the mandate was to mitigate drug shortages by enhancing operational transparency in the pharmaceutical industry. Subsequently, other countries such as Canada have also begun mandating reporting of interruptions to alleviate drug shortages. We leverage the policy changes in the United States and Canada to understand the impact of mandated reporting induced operational transparency on alleviating the extent of drug shortages. Using the data on time-to-recovery for individual drug-shortage incident and annual-days-of-shortage for each drug, we find that the new policy alleviates drug shortages, but its effectiveness is contingent upon the prevailing level of competition in the product category. Although the intervention is not as impactful under a monopoly, the mandate is most effective under a duopoly, and its impact wanes as competition intensifies. In the absence of the mandate-induced transparency, competition does not necessarily alleviate shortages, but with the regulation, competition can relieve drug shortages. Our results potentially offer healthcare providers and policymakers the impetus to alleviate drug shortages by mandating interruption reporting and improving operational transparency.
Although prior research in traditional equity financing shows that male founders are preferred, emerging evidence in low-stakes crowdfunding (e.g., rewards-based crowdfunding) indicates that female entrepreneurs may have an advantage, particularly with female investors. We seek to examine whether investors in high-stakes equity crowdfunding, which includes elements from both traditional equity financing and low-stakes crowdfunding, respond differently to male and female founders. Specifically, we examine whether founder gender preferences, if they exist, vary based on the gender and the experience of the investor. Through a randomized field experiment, we find that inexperienced female investors are significantly more interested (138%) in ventures with female founders than those with male founders; however, we do not observe founder gender preferences among experienced female investors. For male investors, we do not observe differences in interest based on founder gender or investor experience. Thus, we confirm that the gender gaps observed in traditional equity financing are ameliorated in the equity crowdfunding context. Furthermore, we identify a boundary condition to the preference for female founders reported in earlier work involving low-stakes crowdfunding. In high-stakes crowdfunding, investor experience serves as a contingency that reduces female investors’ preference for female founders, potentially because of the weakening effects of activism homophily and the lower reliance on heuristics as investor experience increases.
We examine the revenue–utility assortment optimization problem with the goal of finding an assortment that maximizes a linear combination of the expected revenue of the firm and the expected utility of the customer. This criterion captures the trade-off between the firm-centric objective of maximizing the expected revenue and the customer-centric objective of maximizing the expected utility. The customers choose according to the multinomial logit model, and there is a constraint on the offered assortments characterized by a totally unimodular matrix. We show that we can solve the revenue–utility assortment optimization problem by finding the assortment that maximizes only the expected revenue after adjusting the revenue of each product by the same constant. Finding the appropriate revenue adjustment requires solving a nonconvex optimization problem. We give a parametric linear program to generate a collection of candidate assortments that is guaranteed to include an optimal solution to the revenue–utility assortment optimization problem. This collection of candidate assortments also allows us to construct an efficient frontier that shows the optimal expected revenue–utility pairs as we vary the weights in the objective function. Moreover, we develop an approximation scheme that limits the number of candidate assortments while ensuring a prespecified solution quality. Finally, we discuss practical assortment optimization problems that involve totally unimodular constraints. In our computational experiments, we demonstrate that we can obtain significant improvements in the expected utility without incurring a significant loss in the expected revenue.
This paper illustrates how supply chain (SC) analytics could provide strategic and operational insights to evaluate the risk-based allocation of regulatory resources in food SCs, for management of food safety and adulteration risks. This paper leverages data on 89,970 tests of aquatic products extracted from a self-constructed data set of 2.6 million food safety tests conducted by the China Food and Drug Administration (CFDA) organizations. The integrated and structured data set is used to conduct innovative analysis that identifies the sources of adulteration risks in China’s food SCs and contrasts them with the current test resource allocations of the CFDA. The analysis highlights multiple strategic insights. Particularly, it suggests potential gaps in the current CFDA testing allocation by SC location, which is heavily focused on retail and supermarkets. Instead, the analysis indicates that high-risk parts of the SC, such as wholesale and wet markets, are undersampled. Additionally, the paper highlights the impact that SC analytics could have on policy-level operational decision making to regulate food SCs and manage food safety. The hope is that the paper will stimulate the interest of academics with expertise in these areas to conduct more work in this important application domain.
The expansive learning curve literature in operations management has established how various facets of prior experience improve average performance. In this paper, we explore how increased cumulative experience affects performance variability or consistency. We use a two-stage estimation method of a heteroskedastic learning curve model to examine the relationship between experience and performance variability among paramedics at the London Ambulance Service. We find that, for paramedics with lower experience, an increase in experience of 500 jobs reduces the variance of task completion time by 8.7%, in addition to improving average completion times by 2.7%. Similar to prior results on the average learning curve, we find a diminishing impact of additional experience on the variance learning curve. We provide an evidence base for how to model the learning benefits of cumulative experience on performance in service systems. Our findings imply that the benefits of learning are substantially underestimated if the consistency effect is ignored. Specifically, our estimates indicate that queue lengths (or wait times) might be overestimated by as much as 4% by ignoring the impact of the variance learning curve in service systems. Furthermore, our results suggest that previously established drivers of productivity should be revisited to examine how they affect consistency, in addition to average performance.
We investigate whether and to what extent shareholder litigation shapes corporate innovation by examining the staggered adoption of universal demand laws in 23 states from 1989 to 2005. These laws impose obstacles against shareholders filing derivative lawsuits, thereby significantly reducing managers’ litigation risk. Using a difference-in-differences design and a matched sample, we find that, following the passage of the laws, firms invested more in research and development, produced more patents in new technological classes and more patents based on new knowledge, generated more patents with significant impacts, and achieved higher patent value. Our findings suggest that the external pressure imposed by shareholder litigation discourages managers from engaging in explorative innovation activities.
This paper examines whether investor learning about profitability (i.e., the mean of earnings distribution) leads to persistence in disclosure decisions. A repeated single-period model shows that persistent investor beliefs about profitability lead to persistent disclosure decisions. Using earnings forecast data, I structurally estimate the model and perform several counterfactual analyses. I find that, when investors are assumed to know profitability, the persistence of management forecast decisions significantly declines by 17%–27%. About 24% of firms would have disclosed differently, resulting in 3.9% net change in the amount of information (i.e., posterior variance) provided to the capital market. Collectively, the results indicate the importance of learning profitability in understanding disclosure decisions and the capital market consequences of disclosures.
Using a newly assembled 50-country firm-level database spanning 19 years, we document a bright side for employees of business group–affiliated firms: less pronounced fluctuations in employment than unaffiliated firms in response to macroeconomic shocks. The results are robust to a variety of tests designed to mitigate endogeneity concerns, including propensity score matching and comparisons of successful and failed group integrations, and are present in both booms and recessions. Our results are most consistent with group internal labor markets rather than several alternative explanations (internal capital markets, a lower overall sensitivity to shocks in group firms, or agency problems).
Although there is ample evidence of discrimination against women in the workplace, it can be difficult to understand what factors contribute to discriminatory behavior. We use an experiment to both document discrimination and unpack its sources. First, we show that, on average, employers prefer to hire male over female workers for male-typed tasks, even when the two workers have identical résumés. Second, and most critically, we use a control condition to identify that this discrimination is not specific to gender. Employers are simply less willing to hire a worker from a group that performs worse on average, even when this group is, instead, defined by a nonstereotypical characteristic. In this way, beliefs about average group differences are the key driver of discrimination against women in our setting. We also document some evidence for in-group preferences that contribute to the gender discrimination observed. Finally, our design allows us to understand and quantify the extent to which image concerns mitigate discriminatory behavior.
This paper studies whether board connectedness affects corporate innovation. We find that well-connected boards have a positive effect on innovation activities and quality. The effect is stronger when firms have higher demand for advising or face more severe agency problems. Firms with greater needs for external finance benefit more from board connections with bankers. We show that the positive relation is causal and robust based on a battery of empirical tests including exogenous variation in board connectedness resulting from death and retirement of directors and from a regulatory shock under new exchange listing rules. Evidence indicates that types and relatedness of connections as well as director characteristics contribute to cross-sectional heterogeneity of the positive effect.
We propose a discrete-time affine pricing model that simultaneously allows for (i) the presence of systemic entities by departing from the no-jump condition on the factors’ conditional distribution, (ii) contagion effects, and (iii) the pricing of credit events. Our affine framework delivers explicit pricing formulas for default-sensitive securities such as bonds and credit default swaps (CDSs). We estimate a euro-area multicountry version of the model and address economic questions related to the pricing of sovereign credit risk. We find that both frailty (common factors) and contagion phenomena are important to account for the joint dynamics of credit spreads. Our results also provide evidence of credit-event pricing, which is at the source of substantial credit risk premiums, even for short maturities. Finally, we extract measures of depreciation-at-default from CDSs denominated in different currencies.
We study the choice of a principal to either delegate a decision to a group of careerist experts or to consult them individually and keep the decision-making power. Our model predicts a trade-off between information acquisition and information aggregation. On the one hand, the expected benefit from being informed is larger in case the experts are consulted individually. Hence, the experts either acquire the same or a larger amount of information, depending on the cost of information, than in case of delegation. On the other hand, any acquired information is better aggregated in the case of delegation, in which experts can deliberate secretly. To test the model’s key predictions, we run an experiment. The results from the laboratory confirm the predicted trade-off despite some deviations from theory on the individual level.
Many operational settings share the following three features: (i) a centralized planning system allocates tasks to workers or service providers, (ii) the providers generate value by completing the tasks, and (iii) the completion of tasks influences the providers’ welfare. In such cases, the planning system’s allocations often entail trade-offs between the service providers’ welfare and the total value that is generated (or that accrues to the system itself), and concern arises that allocations that are good under one metric may perform poorly under the other. We propose a broad framework for quantifying the magnitude of value losses when allocations are restricted to satisfy certain desirable guarantees to the service providers. We consider a general class of guarantees that includes many considerations of practical interest arising (e.g., in the design of sustainable two-sided markets) in workforce welfare and compensation, or in sourcing and payments in supply chains, among other application domains. We derive tight bounds on the relative value loss and show that this loss is limited for any restriction included in our general class. Our analysis shows that when many providers are present, the largest losses are driven by fairness considerations, whereas when few providers are present, they are driven by the heterogeneity in the providers’ effectiveness to generate value; when providers are perfectly homogenous, the losses never exceed 50%. We study additional loss drivers and find that less variability in the value of jobs and a more balanced supply-demand ratio may lead to larger losses. Lastly, we demonstrate numerically using both real-world and synthetic data that the loss can be small in several cases of practical interest.
We develop a new measure of innovation using the text of analyst reports of S&P 500 firms. Our text-based measure gives a useful description of innovation by firms with and without patenting and R&D (research and development). For nonpatenting firms, the measure identifies innovative firms that adopt novel technologies and innovative business practices (e.g., Walmart’s cross-geography logistics). For patenting firms, the text-based measure strongly correlates with valuable patents, which likely capture true innovation. The text-based measure robustly forecasts greater firm performance and growth opportunities for up to four years, and these value implications hold just as strongly for innovative nonpatenting firms.
Motivated by applications in shared vehicle systems, we study dynamic pricing of resources that relocate over a network of locations. Customers with private willingness to pay sequentially request to relocate a resource from one location to another, and a revenue-maximizing service provider sets a price for each request. This problem can be formulated as an infinite-horizon stochastic dynamic program, but it is difficult to solve, as optimal pricing policies may depend on the locations of all resources in the network. We first focus on networks with a hub-and-spoke structure, and we develop a dynamic pricing policy and a performance bound based on a Lagrangian relaxation. This relaxation decomposes the problem over spokes and is thus far easier to solve than the original problem. We analyze the performance of the Lagrangian-based policy and focus on a supply-constrained large network regime in which the number of spokes (n) and the number of resources grow at the same rate. We show that the Lagrangian policy loses no more than O(ln n/n) in performance compared with an optimal policy, thus implying asymptotic optimality as n grows large. We also show that no static policy is asymptotically optimal in the large network regime. Finally, we extend the Lagrangian relaxation to provide upper bounds and policies to general networks with multiple interconnected hubs and spoke-to-spoke connections and to incorporate relocation times. We also examine the performance of the Lagrangian policy and the Lagrangian relaxation bound on some numerical examples, including examples based on data from RideAustin.
We study how delivery data can be applied to improve the on-time performance of last-mile delivery services. Motivated by the delivery operations and data of a food delivery service provider, we discuss a framework that integrates travel-time predictors with order-assignment optimization. Such integration enables us to capture the driver’s routing behavior in practice as the driver’s decision-making process is often unobservable or intricate to model. Focusing on the order-assignment problem as an example, we discuss the classes of tractable predictors and prediction models that are highly compatible with the existing stochastic and robust optimization tools. We further provide reformulations of the integrated models, which can be efficiently solved with the proposed branch-and-price algorithm. Moreover, we propose two simple heuristics for the multiperiod order-assignment problem, and they are built upon single-period solutions. Using the delivery data, our numerical experiments on a real-world application not only demonstrate the superior performance of our proposed order-assignment models with travel-time predictors, but also highlight the importance of learning behavioral aspects from operational data. We find that a large sample size does not necessarily compensate for the misspecification of the driver’s routing behavior.
Service providers often share delay information, in the form of delay announcements, with their customers. In practice, simple delay announcements, such as average waiting times or a weighted average of previously delayed customers, are often used. Our goal in this paper is to gain insight into when such announcements perform well. Specifically, we compare the accuracies of two announcements: (i) a static announcement that does not exploit real-time information about the state of the system and (ii) a dynamic announcement, specifically the last-to-enter-service (LES) announcement, which equals the delay of the last customer to have entered service at the time of the announcement. We propose a novel correlation-based approach that is theoretically appealing because it allows for a comparison of the accuracies of announcements across different queueing models, including multiclass models with a priority service discipline. It is also practically useful because estimating correlations is much easier than fitting an entire queueing model. Using a combination of queueing-theoretic analysis, real-life data analysis, and simulation, we analyze the performance of static and dynamic announcements and derive an appropriate weighted average of the two which we demonstrate has a superior performance using both simulation and data from a call center.
We consider a system with an evolving state that can be stopped at any time by a decision maker (DM), yielding a state-dependent reward. The DM does not observe the state except for a limited number of monitoring times, which he must choose, in conjunction with a suitable stopping policy, to maximize his reward. Dealing with these types of stopping problems, which arise in a variety of applications from healthcare to finance, often requires excessive amounts of data for calibration purposes and prohibitive computational resources. To overcome these challenges, we propose a robust optimization approach, whereby adaptive uncertainty sets capture the information acquired through monitoring. We consider two versions of the problem—static and dynamic—depending on how the monitoring times are chosen. We show that, under certain conditions, the same worst-case reward is achievable under either static or dynamic monitoring. This allows recovering the optimal dynamic monitoring policy by resolving static versions of the problem. We discuss cases when the static problem becomes tractable and highlight conditions when monitoring at equidistant times is optimal. Lastly, we showcase our framework in the context of a healthcare problem (monitoring heart-transplant patients for cardiac allograft vasculopathy), where we design optimal monitoring policies that substantially improve over the status quo recommendations.
Teams, juries, electorates, and committees must often select from various alternative courses of action what they judge to be the best option. The phenomenon that the central tendency of many independent estimates is often quite accurate—“the wisdom of the crowd”—suggests that group decisions based on plurality voting can be surprisingly wise. Recent experimental studies demonstrate that the wisdom of the crowd is further enhanced if individuals have the opportunity to revise their votes in response to the independent votes of others. We argue that this positive effect of social information turns negative if group members do not first contribute an independent vote but instead cast their votes sequentially such that early mistakes can cascade across strings of decision makers. Results from a laboratory experiment confirm that when subjects sequentially state which of two answers they deem correct, majorities are more often wrong when subjects can see how often the two answers have been chosen by previous subjects than when they cannot. As predicted by our theoretical model, this happens even though subjects’ use of social information improves the accuracy of their individual votes. A second experiment conducted over the internet involving larger groups indicates that although early mistakes on easy tasks are eventually corrected in long enough choice sequences, for difficult tasks wrong majorities perpetuate themselves, showing no tendency to self-correct.
Although a business’s reputation can affect its pricing, prices can also affect its reputation. To explore the effect of prices on reputation, we investigate daily data on menu prices and online ratings from a large rating and ordering platform. We find that a price increase of 1% leads to a decrease of 3%–5% in the average rating. Consistent with this, the overall distribution of ratings for cheaper restaurants is similar to that of more expensive restaurants. Finally, these effects do not seem to be driven by consumer retaliation against price changes but by changes in absolute price levels.
As conveners that bring various stakeholders into the same physical space, firms can powerfully influence the course of pandemics such as coronavirus disease 2019. Even when operating under government orders and health guidelines, firms have considerable discretion to keep their establishments open or closed during a pandemic. We examine the role of social learning in the exercise of this discretion at the establishment level. In particular, we evaluate how the closure decisions of chain establishments, which are associated with national brands, affect those of proximate, same-industry community establishments, which are independently owned or managed. We conduct these analyses using cell phone location tracking data on daily visits to 230,403 U.S.-based community establishments that are colocated with chain establishments affiliated with 319 national brands. We disentangle the effects of social learning from confounding factors by using an instrumental variables strategy that relies on local variation in community establishments’ exposure to closure decisions made by brands at the national level. Our results suggest that closing decisions of community establishments are affected by the decisions made by chain establishments; a community establishment is 3.5% more likely to be open on a given day if the proportion of nearby open chain establishments increases by one standard deviation.
The previous literature documents that female-owned businesses are less profitable than male-owned businesses, including microenterprises that make up the majority of firms in developing countries. In this paper, we uncover an overlooked gendered constraint for these businesses: childcare. We collect field data through unannounced visits to a sample of microentrepreneurs in select areas of Uganda, combining surveys of business owners and real customers, as well as purchases by confederate buyers (i.e., mystery shoppers). We document that childcare duties in businesses are highly gendered: 37% of female owners bring small children to work, compared with 0% of men. Childcare duties are correlated with a “baby-profit gap,” as businesses where children are present earn 48% lower profits than even other female-owned businesses where a child is not present. Using our rich data, we analyze potential reasons why childcare obligations may affect profits. We find that prices, product quality, and other explanations are not robustly correlated with the presence of a baby. However, we find that women with children in the store are more likely to run out of stock than both men and women who do not have children in the store. Although we caution that our analysis is not causal, we consistently find that childcare duties are associated with profitability and may relate to the wider gender gap in business performance.
We present evidence that the desire to gain human capital is an important motive for corporate acquisitions. Our tests exploit the staggered recognition of the Inevitable Disclosure Doctrine (IDD) by U.S. state courts, which prevents employees with trade secret knowledge from working for other firms. We find a significant increase in the likelihood of being acquired for firms headquartered in states that recognize such a doctrine relative to firms headquartered in states that do not. Our result is stronger for firms with greater human capital and for firms whose employees have better ex ante employment mobility. We show that the IDD is positively associated with the retention of target firms’ key technicians, employees, and top executives after an acquisition. We also show that the IDD is positively associated with synergy creation, acquirers’ announcement returns, and acquirers’ long-run stock and operating performance. Overall, our result indicates that corporate acquisitions can be used as a means for firms to overcome labor market frictions and gain access to valuable human capital.
Intertemporal discount rates vary widely across contexts and individuals. We propose that a sizable fraction of this variation results from differences in how visual attention is allocated to different features of the decision, such as earlier versus future rewards, and that fluctuations in attentional patterns alter choices. We first tested this hypothesis in an experiment in which participants chose between receiving smaller-sooner versus larger-later monetary rewards while their attention was recorded with eye tracking. We found that cross-participant variation in the allocation of attention explained between 40% and 53% of the individual differences in discounting and that cross-trial variation explained 16% of the participants’ propensity to choose the delayed option. To test causality, multiple additional experiments exogenously manipulated the allocation of visual attention and found that shifting attention to attributes that are relatively more attractive in a larger-later option increased patient decision making and altered purchasing behavior. Together, these results are consistent with the existence of a causal impact of visual attention on intertemporal choice and suggest that manipulating attention can have a sizeable impact for important managerial and public policy choice domains.
Despite subjects being informed about tax rules before making saving decisions, we find—using laboratory experiments—that deferred taxation results in after-tax pensions that are approximately 25% lower compared with an economically equivalent immediate pension-tax system. This indicates substantial tax misperceptions. For subjects with low tax knowledge, tax misperceptions remain stable, even if they have gained experience. Tax misperceptions nearly disappear for all subjects only if we provide recurrent numerical informational pension-tax nudges and if subjects have gained experience. We demonstrate that replacing the tax-deductibility of retirement savings with government matching contributions increases after-tax pensions above the level under immediate taxation without the need to provide informational tax nudges.
When organizations want their employees to adopt behaviors that advance prosocial and instrumental aims, which motive should they express? A groundswell of recent work suggests that highlighting prosocial actions inspires and motivates employees. Building on this work, we embed a field experiment in the context of an organizational change initiative (Study 1). A large university sought to change the behavior of administrative employees who purchase office supplies, encouraging them to place orders of at least $50, referred to as “bundling.” We exploit the fact that the organization could justify the same behavior in contrasting ways. We randomly assign employees to view either a prosocial (“limiting pollution”), instrumental (“limiting costs”), or mixed motive (“limiting pollution and limiting costs”) for caring about bundling each time they access the organization’s procurement system. We then evaluate changes in employees’ behavior by comparing a six-month baseline to a six-month experimental period, covering 10,169 purchases in 556 offices. Contrary to expectations from related research, the instrumental motive was most effective for changing behavior, leading to significantly more bundling than the prosocial motive. Two follow-up vignette experiments probe theoretical mechanisms. They indicate that an instrumental motive seems more genuine (i.e., reflecting the organization’s true motive) than a prosocial motive (Study 2) and that seeming genuine increases individuals’ intention to bundle (Study 3). This research reveals that prosocial justifications can be less effective than instrumental ones and suggests that perceptions of genuineness may shape the effectiveness of behavioral change efforts in organizations.
We investigate the effects of write-downs on market prices and volumes under fair value accounting. We also examine the prominent role that illiquidity plays in exacerbating the direct and spillover effects of exit valuation on equity and credit default swap (CDS) markets. Using hand-collected data on write-down announcements made during and after the 2007–2009 financial crisis, we find that firms that wrote down assets in accordance with fair value rules experience significant abnormal negative stock returns and spikes in the CDS premiums written on their obligations; similar firms without write-downs exhibit sympathetic and significant negative abnormal returns and positive premiums. We find that both the direct effect of the write-downs and the indirect spillover effects resulting from crisis-related illiquidity in the markets for financial assets (affecting the magnitude of write-downs) and in the securities markets (affecting the reaction to the write-downs) during the financial crisis go beyond normal direct and information transfer effects and may have contributed to the adverse consequences of the crisis.
The existing literature finds that information not captured by traditional term structure factors helps predict excess bond returns. When estimating no-arbitrage affine term structure models, aligning in-sample and out-of-sample objective functions results in term structure factors that capture information that remains hidden from existing approaches. Specifically, the estimates of the third term structure factor radically differ and are related to the fourth principal component, which helps forecast bond returns. The new objective function leads to substantial improvements in forecasting performance. It also results in higher model term premiums and lower expected future short rates.
Theories of organizations are sympathetic to long-standing ideas from network science that organizational networks should be regarded as multiscale and capable of displaying emergent properties. However, the historical difficulty of collecting individual-level network data for many (N ≫ 1) organizations, each of which comprises many (n ≫ 1) individuals, has hobbled efforts to develop specific, theoretically motivated hypotheses connecting micro- (i.e., individual-level) network structure with macro-organizational properties. In this paper we seek to stimulate such efforts with an exploratory analysis of a unique data set of aggregated, anonymized email data from an enterprise email system that includes 1.8 billion messages sent by 1.4 million users from 65 publicly traded U.S. firms spanning a wide range of sizes and 7 industrial sectors. We uncover wide heterogeneity among firms with respect to all measured network characteristics, and we find robust network and organizational variation as a result of size. Interestingly, we find no clear associations between organizational network structure and firm age, industry, or performance; however, we do find that centralization increases with geographical dispersion—a result that is not explained by network size. Although preliminary, these results raise new questions for organizational theory as well as new issues for collecting, processing, and interpreting digital network data.
As a new general-purpose technology, robots have the potential to radically transform employment and organizations. In contrast to prior studies that predict dramatic employment declines, we find that investments in robotics are associated with increases in total firm employment but decreases in the total number of managers. Similarly, we find that robots are associated with an increase in the span of control for supervisors remaining within the organization. We also provide evidence that robot adoption is not motivated by the desire to reduce labor costs but is instead related to improving product and service quality. Our findings are consistent with the notion that robots reduce variance in production processes, diminishing the need for managers to monitor worker activities to ensure production quality. As additional evidence, we also find that robot investments predict improved performance measurement and increased adoption of incentive pay based on individual employee performance. With respect to changes in skill composition within the organization, robots predict decreases in employment for middle-skilled workers but increases in employment for low- and high-skilled workers. We also find that robots predict not only changes in employment but also corresponding adaptations in organizational structure. Robot investments are associated with both centralization and decentralization of decision-making authority depending on the task, but decision rights in either case are reassigned away from the managerial level of the hierarchy. Overall, our results suggest that robots have distinct and profound effects on employment and organizations that require fundamental changes in firm practices and organizational design.
We provide evidence of delayed attention and inaction in response to COVID-19 in countries that did not experience SARS in 2003. Using cross-country data, we find that individuals in countries that had SARS infections in 2003 searched more intensively for COVID-19-related information on Google in late January 2020, the time of the first known outbreak in Wuhan, China. Early attention to the novel virus, as measured by Google searches, is associated with deeper stock market drops in countries with SARS experience. In contrast, people in countries without SARS experience started to pay more attention much later, in March. Moreover, governments in these countries responded significantly more slowly in implementing social distancing policies to combat domestic COVID-19 outbreaks than governments in countries with SARS experience. Moreover, such early responses of individuals and governments in countries with SARS experience are prevalent within continent, even in non-Asian countries. Furthermore, people in countries with SARS experience are more compliant with social distancing rules. These timely attention and proactive responses of individuals and governments are more pronounced in countries that reported deaths caused by SARS, which left deeper imprints. Our findings suggest that the imprint of similar viruses’ experience is a fundamental mechanism underlying timely responses to COVID-19.
This paper proposes an original approach for backtesting systemic risk measures. This backtesting approach makes it possible to assess the systemic risk measure forecasts used to identify the financial institutions that contribute the most to the overall risk in the financial system. Our procedure is based on simple tests similar to those generally used to backtest the standard market risk measures such as value-at-risk or expected shortfall. We introduce a concept of violation associated with the marginal expected shortfall (MES), and we define unconditional coverage and independence tests for these violations. We can generalize these tests to any MES-based systemic risk measures such as the systemic expected shortfall (SES), the systemic risk measure (SRISK), or the delta conditional value-at-risk (ΔCoVaR). We study their asymptotic properties in the presence of estimation risk and investigate their finite sample performance via Monte Carlo simulations. An empirical application to a panel of U.S. financial institutions is conducted to assess the validity of MES, SRISK, and ΔCoVaR forecasts issued from a bivariate GARCH model with a dynamic conditional correlation structure. Our results show that this model provides valid forecasts for MES and SRISK when considering a medium-term horizon. Finally, we propose an early warning system indicator for future systemic crises deduced from these backtests. Our indicator quantifies how much is the measurement error issued by a systemic risk forecast at a given point in time which can serve for the early detection of global market reversals.
Existing literature suggests that hospital occupancy matters for quality of care, as measured by various patient outcomes. However, estimating the causal effect of increased hospital busyness on in-hospital mortality remains an elusive task due to statistical power challenges and the difficulty in separating shocks to occupancy from changes in patient composition. Using data from a large public hospital system in Mexico, we estimate the impact of congestion on in-hospital mortality by exploiting the shock in hospitalizations induced by the 2009 H1N1 pandemic, instrumenting hospital admissions due to acute respiratory infections (ARIs) with measures of ARI cases at nearby healthcare facilities as a proxy for the size of the local outbreak. Our instrumental-variables estimates show that a 1% increase in ARI admissions in 2009 led to a 0.25% increase in non-ARI in-hospital mortality. We show that these effects are nonlinear in the size of the local outbreak, consistent with the existence of tipping points. We further show that effects are concentrated at hospitals with limited infrastructure, suggesting that supply-side policies that improve patient assignment across hospitals and strategically increase hospital capacity could mitigate some of the negative impacts. We discuss managerial implications, suggesting that up to 25%–30% of our estimated deaths at small and non-intensive-care-unit hospitals could have been averted by reallocating patients to reduce congestion.
A platform might have the potential to bring enormous value to its users. However, without a well-orchestrated launch strategy that coordinates a sufficient number of users onto the platform, this potential will not be realized. The theoretical literature predicts that one approach to coordinating platform take-off is to influence the market’s subjective focal expectations of the future installed base of users. This paper reports on a field experiment investigating the causal role of subjective expectations in the launch of a new platform venture, in which invitations to join a newly launched platform were sent to 16,349 individuals. The invitations included randomized statements regarding the size of the future expected installed base (along with disclosures of the current installed base). I find that simple, subjective, uncommitted, and relatively costless statements broadcasted by the platform with the goal of influencing market expectations were indeed able to influence platform takeoff and overcome an initial chicken-and-egg problem. These broadcasted subjective statements regarding future installed base had a larger influence on adoption rates than did disclosures of the true current installed base during early adoption. However, these subjective statements of expected future installed base ceased to have any effect once the true current installed base grew large. I discuss implications for the promotion, marketing, and evangelism of new platform ventures.
Many real-world analytics problems involve two significant challenges: prediction and optimization. Because of the typically complex nature of each challenge, the standard paradigm is predict-then-optimize. By and large, machine learning tools are intended to minimize prediction error and do not account for how the predictions will be used in the downstream optimization problem. In contrast, we propose a new and very general framework, called Smart “Predict, then Optimize” (SPO), which directly leverages the optimization problem structure—that is, its objective and constraints—for designing better prediction models. A key component of our framework is the SPO loss function, which measures the decision error induced by a prediction. Training a prediction model with respect to the SPO loss is computationally challenging, and, thus, we derive, using duality theory, a convex surrogate loss function, which we call the SPO+ loss. Most importantly, we prove that the SPO+ loss is statistically consistent with respect to the SPO loss under mild conditions. Our SPO+ loss function can tractably handle any polyhedral, convex, or even mixed-integer optimization problem with a linear objective. Numerical experiments on shortest-path and portfolio-optimization problems show that the SPO framework can lead to significant improvement under the predict-then-optimize paradigm, in particular, when the prediction model being trained is misspecified. We find that linear models trained using SPO+ loss tend to dominate random-forest algorithms, even when the ground truth is highly nonlinear.
In the West, where posted prices are the norm, it is uncommon to observe consumers receive discounts below the posted price. Nevertheless, we find that when stores are asked, a discount is granted approximately 40% of the time, with a median discount percentage of 10%. Discounts are more likely to be offered by small-scale firms, for higher-priced products, and for nonsale items. More generally, differences in price delegation behavior across firm types serve as an indicator that monitoring costs and employee skills are important drivers of bargaining behavior.
Cloud computing providers must constantly hold many idle compute instances available (e.g., for maintenance or for users with long-term contracts). A natural idea, which should intuitively increase the provider’s profit, is to sell these idle instances on a secondary market, for example, via a preemptible spot market. However, this ignores possible “market cannibalization” effects that may occur in equilibrium as well as the additional costs the provider experiences due to preemptions. To study the viability of offering a spot market, we model the provider’s profit optimization problem by combining queuing theory and game theory to analyze the equilibria of the resulting queuing system. Our main result is an easy-to-check condition under which a provider can simultaneously achieve a profit increase and create a Pareto improvement for the users by offering a spot market (using idle resources) alongside a fixed-price market. Finally, we illustrate our results numerically to demonstrate the effects that the provider’s costs and her strategy have on her profit.
We exploit the 2008 Oregon ban on noncompete agreements (NCAs) for hourly-paid workers to provide the first evidence on the impact of NCAs on low-wage workers. We find that banning NCAs for hourly workers increased hourly wages by 2%–3% on average. Since only a subset of workers sign NCAs, scaling this estimate by the prevalence of NCA use in the hourly-paid population suggests that the effect on employees actually bound by NCAs may be as great as 14%–21%, though the true effect is likely lower due to labor market spillovers onto those not bound by NCAs. Whereas the positive wage effects are found across the age, education, and wage distributions, they are stronger for female workers and in occupations where NCAs are more common. The Oregon low-wage NCA ban also improved average occupational status in Oregon, raised job-to-job mobility, and increased the proportion of salaried workers without affecting hours worked.
This paper develops a tractable methodology for designing an optimal priority system for assigning agents to heterogeneous items while accounting for agents’ choice behavior. The space of mechanisms being optimized includes deferred acceptance and top trading cycles as special cases. In contrast to previous literature, I treat the inputs to these mechanisms, namely the priority distribution of agents and quotas of items, as parameters to be optimized. The methodology is based on analyzing large market models of one-sided matching using techniques from revenue management and solving a certain assortment planning problem whose objective is social welfare. I apply the methodology to school choice and show that restricting choices may be beneficial to student welfare. Moreover, I compute optimized choice sets and priorities for elementary school choice in Boston.
There exists significant hype regarding how much machine learning and incorporating social media data can improve forecast accuracy in commercial applications. To assess if the hype is warranted, we use data from the film industry in simulation experiments that contrast econometric approaches with tools from the predictive analytics literature. Further, we propose new strategies that combine elements from each literature in a bid to capture richer patterns of heterogeneity in the underlying relationship governing revenue. Our results demonstrate the importance of social media data and value from hybrid strategies that combine econometrics and machine learning when conducting forecasts with new big data sources. Specifically, although both least squares support vector regression and recursive partitioning strategies greatly outperform dimension reduction strategies and traditional econometrics approaches in forecast accuracy, there are further significant gains from using hybrid approaches. Further, Monte Carlo experiments demonstrate that these benefits arise from the significant heterogeneity in how social media measures and other film characteristics influence box office outcomes.
We conducted a field experiment in a Dutch retail chain of 122 stores to study the interaction between team incentives, team social cohesion, and team performance. Theory predicts that the effect of team incentives on team performance increases with the team’s social cohesion because social cohesion reduces free-riding behavior. In addition, team incentives may lead to more coworker support or to higher peer pressure and thereby, can affect the team’s social cohesion. We introduced short-term team incentives in a randomly selected subset of stores and measured for all stores, both before and after the intervention, the team’s sales performance and the team’s social cohesion as well as coworker support and peer pressure. The average treatment effect of the team incentive on sales is 1.5 percentage points, which does not differ significantly from zero. In line with theory, the estimated treatment effect increases with social cohesion as measured before the intervention. Social cohesion itself is not affected by the team incentives.
Firms often register trademarks as they launch new products or services. We find that the number of new trademark registrations positively predicts firm profitability, stock returns, and underreaction by analysts in their earnings forecasts. Using the Federal Trademark Dilution Act (FTDA) as an exogenous shock to trademark protection, we find that greater trademark protection strengthens the predictability of new trademark registrations. Together, our evidence suggests that investors undervalue new trademark registrations.
There is often considerable anxiety and conflicting advice concerning the benefits of presenting/being evaluated first. We thus investigate how expert evaluators vary in their evaluations of entrepreneurial proposals based upon the order in which they are evaluated. Our research setting is a premiere innovation fund competition in Beijing, China, where the prize money at stake is economically meaningful, and evaluators are quasi-randomly assigned to evaluate written grant proposals without the possibility of peer influence. This enables us to credibly recover a causal position effect. We also theorize and test how heterogeneity in evaluators’ prior (context-specific) judging experience moderates position effects. Overall, we find that a proposal evaluated first requires total assets in the top 10th percentile to merely equal the evaluation of a proposal in the bottom 10th percentile that is not evaluated first. Firm and evaluator fixed-effects models yield consistent findings. We consider evaluation design elements that may mollify these position effects in the discussion section.
This paper examines the relative advantages of single-product and multiproduct firms following changes in customer switching costs. Whereas a single-product firm can closely tailor offerings to customers’ needs, a multiproduct firm can create value for customers in the form of flexibility, allowing them to change between product varieties as preferences evolve without needing to switch providers. We argue that this value-creation mechanism is more effective when customers face high switching costs and explore this prediction in the mobile telecommunications sector, using an exogenous policy change (mobile number portability) that suddenly decreases customer switching costs. Our results reveal that when customer switching costs fall, multiproduct firms see lower growth than single-product firms, and entry with a multiproduct offering becomes less frequent than before. The study highlights how customer switching costs can enable or inhibit choices of firm scope.
Prior research suggests portfolio entrepreneurs—businesspeople who run more than one firm simultaneously—launch more successful ventures than their single-business counterparts. However, their ventures are less likely to survive. In an attempt to reconcile this paradox, this paper presents a framework in which portfolio entrepreneurs’ main advantage is not a superior ability to select the best business opportunities ex ante, but rather the ability to redeploy human and capital resources across businesses ex post, which reduces the sunkenness of their investments in new projects. This redeployment option facilitates their exit from new businesses that fail initial market tests. Thus, portfolio entrepreneurs’ heterogeneous termination decisions explain a greater portion of new firm performance differential than ex ante opportunity selection. We test these ideas using a longitudinal data set of more than 5,700 entrepreneurs and find consistent evidence. Portfolio companies do not show systematically higher performance at the time of entry; a performance difference emerges only over time, as the selection effect and resource redeployment occur.
Cheap-talk communication between parties with conflicting interests is common in many business and economic settings. Two distinct behavioral economics theories, the trust-embedded model and the level-k model, have emerged to explain how cheap talk works between human decision makers. The trust-embedded model considers that decision makers are motivated by nonpecuniary motives to be trusting and trustworthy. In contrast, the level-k model considers that decision makers are purely self-interested but limited in their ability to think strategically. Although both theories have been successful in explaining cheap-talk behaviors in separate contexts, they point to contrasting drivers for human behaviors. In this paper, we provide the first direct comparison of both theories within the same context. We show that, in a cheap-talk setting that well represents many practical situations, the two models make characteristically distinct and empirically distinguishable predictions. We leverage past experiment data from this setting to determine what aspects of cheap-talk behavior each model captures well and which model (or combination of models) has better explanatory power and predictive performance. We find that the trust-embedded model emerges as the dominant explanation. Our results, thus, highlight the importance of investing in systems and processes to foster trusting and trustworthy relationships in order to facilitate more effective cheap-talk interactions.
This paper studies price bargaining when both parties have left-digit bias when processing numbers. The empirical analysis focuses on the auto finance market in the United States, using a large data set of 35 million auto loans. Incorporating left-digit bias in bargaining is motivated by several intriguing observations. The scheduled monthly payments of auto loans bunch at both $9- and $0-ending digits, especially over $100 marks. In addition, $9-ending loans carry a higher interest rate, and $0-ending loans have a lower interest rate. We develop a Nash bargaining model that allows for left-digit bias from both consumers and finance managers of auto dealers. Results suggest that both parties are subject to this basic human bias: the perceived difference between $9- and the next $0-ending payments is larger than $1, especially between $99- and $00-ending payments. The proposed model can explain the phenomena of payments bunching and differential interest rates for loans with different ending digits. We use counterfactuals to show a nuanced impact of left-digit bias, which can both increase and decrease the payments. Overall, bias from both sides leads to a $33 increase in average payment per loan compared with a benchmark case with no bias.
The growing market for retail structured investment products and empirical evidence for excessive pricing of such products raise the hypothesis that private investors show increased risk appetite in structured investment contexts. A two-stage framed field experiment building on cumulative prospect theory is designed to test this hypothesis. Subjects’ expectations regarding the future performance of an underlying index are elicited first. A bisection algorithm is then applied to derive the certainty equivalents of 20 simple individually tailored deposits. The results support the increased risk appetite hypothesis, revealing that subjects reach for substantial gains and underweight tail loss events when evaluating the deposits. Similar results emerge in a follow-up experiment where the uncertain deposits are replaced by risky versions. While previous studies propose that misperception of complex terms and optimism contribute to the mispricing of structured instruments, the current experiments show that nonstandard risk appetite manifests in the valuation of simple well-defined products, controlling for expectations.
Modern forecasting algorithms use the wisdom of crowds to produce forecasts better than those of the best identifiable expert. However, these algorithms may be inaccurate when crowds are systematically biased or when expertise varies substantially across forecasters. Recent work has shown that meta-predictions—a forecast of the average forecasts of others—can be used to correct for biases even when no external information, such as forecasters’ past performance, is available. We explore whether meta-predictions can also be used to improve forecasts by identifying and leveraging the expertise of forecasters. We develop a confidence-based version of the Surprisingly Popular algorithm proposed by Prelec, Seung, and McCoy. As with the original algorithm, our new algorithm is robust to bias. However, unlike the original algorithm, our version is predicted to always weight forecasters with more informative private signals more than forecasters with less informative ones. In a series of experiments, we find that the modified algorithm does a better job in weighting informed forecasters than the original algorithm and show that individuals who are correct more often on similar decision problems contribute more to the final decision than other forecasters. Empirically, the modified algorithm outperforms the original algorithm for a set of 500 decision problems.
We study how the menu of contracts presented to a decision maker—including contracts she may be precluded from choosing—affects her choice of remunerative but risky actions relative to lower paying, less risky alternatives. We do this through a series of laboratory experiments modeled after the loan repayment options offered to U.S. student borrowers, analyzing borrowers’ task (career) choices in settings that vary the menu of available and unavailable loan repayment plans and knowledge of unavailable options. In these experiments, we observe behavior that is inconsistent with predictions from standard economic models in which agents can easily make complex decisions and each alternative in a choice set is evaluated independently of other potential options. Instead, we provide evidence that expanding the menu of choices or making an agent aware of choices that she has been denied can affect how a contract is valued. Our empirical findings are most consistent with behavioral models that allow for anticipated regret over a choice that turns out to be suboptimal ex post or preferences for simplicity and gratitude for being unburdened from having to make a choice.
This paper investigates multiperiod decisions under multiple beliefs. We explore the dynamic consistency of both complete and incomplete orderings. We focus on a dominance concept that supports decision-making under multiple characterizations of uncertainty by ruling out strategies that are dominated across a set of beliefs. We uncover a distinction between two types of dynamic inconsistency, which we label fallacious and fallible inconsistency. Fallacious inconsistency occurs when an a priori optimal strategy is suboptimal in the second period, thus requiring the decision-maker to depart from the original strategy. Fallible inconsistency occurs when an a priori suboptimal second-period action ceases being suboptimal from the perspective of the second-period preferences. We introduce corresponding definitions of dynamic consistency and show that the two types of consistency are equivalent for complete orderings, but differ for incomplete orderings. Subjective expected utility is dynamically consistent and non-expected-utility decision rules, such as minmax, are not. We show that the dominance relation over beliefs falls between these two: it is immune to the more severe fallacious inconsistency, but not to the less problematic fallible inconsistency. We illustrate the method and concepts using a numerical example addressing a focal, real-world problem of risk and ambiguity regarding climate change.
How do we combine others’ probability forecasts? Prior research has shown that when advisors provide numeric probability forecasts, people typically average them (i.e., they move closer to the average advisor’s forecast). However, what if the advisors say that an event is “likely” or “probable?” In eight studies (n = 7,334), we find that people are more likely to act as if they “count” verbal probabilities (i.e., they move closer to certainty than any individual advisor’s forecast) than they are to “count” numeric probabilities. For example, when the advisors both say an event is “likely,” participants will say that it is “very likely.” This effect occurs for both probabilities above and below 50%, for hypothetical scenarios and real events, and when presenting the others’ forecasts simultaneously or sequentially. We also show that this combination strategy carries over to subsequent consumer decisions that rely on advisors’ likelihood judgments. We discuss and rule out several candidate mechanisms for our effect.
We use the initial public offering (IPO) setting to provide evidence that the combination of valuation uncertainty and short-sales constraints generates significant equity market mispricing. The IPOs that we predict to be most susceptible to overpricing in the immediate aftermarket have first-day returns of +47% and lockup expiration returns of −9%. Our detailed analysis of securities lending market data confirms that these IPOs experience severe short-sales constraints that peak around the lockup expiration. Our paper both explains the anomalous pricing of IPOs and highlights the importance of valuation uncertainty and short-sales constraints in explaining equity mispricing.
We propose an optimal currency hedging strategy for global equity investors using currency value, carry, and momentum to proxy for expected currency returns. A benchmark risk constraint ensures the overlay closely mimics a fully hedged portfolio. We compare this with naïve and alternative hedges in a demanding out-of-sample test, with transaction and rebalancing costs and margin requirements. Other hedging methods generally reduce risk but at a cost. Some tend to short currencies with high returns and all incur substantial costs with frictions, mostly margin requirements and equity rebalancing costs. The proposed strategy uses predictable returns to reduce this cost. It produces a statistically significant 17% gain in Sharpe ratio and an annualized Jensen-α of 0.93% versus a fully hedged benchmark. Notably, most of the implementation costs of the strategy would be incurred by the benchmark anyway. This reduces its marginal cost and highlights a specific synergy of integrating hedging with speculation.
Using the details of vesting terms, we document that stock options granted in high-investor-sentiment periods tend to have shorter vesting periods and durations and are more likely to vest completely or have a significantly larger fraction vested within one year of the grant date, relative to low-sentiment periods. We further find that the sentiment effect on vesting terms is more pronounced when firms are largely held by investors with short investment horizons (e.g., transient institutions). Moreover, short vesting terms in high-sentiment periods are positively associated with future mergers-and-acquisitions activity and capital expenditures. Overall, our findings are consistent with theoretical predictions that, in a speculative market, shareholders incentivize managers with short-term-oriented compensation contracts to induce managers to pursue actions maintaining overvaluation.
We develop an analytical framework to study experimental design in two-sided marketplaces. Many of these experiments exhibit interference, where an intervention applied to one market participant influences the behavior of another participant. This interference leads to biased estimates of the treatment effect of the intervention. We develop a stochastic market model and associated mean field limit to capture dynamics in such experiments and use our model to investigate how the performance of different designs and estimators is affected by marketplace interference effects. Platforms typically use two common experimental designs: demand-side “customer” randomization (CR) and supply-side “listing” randomization (LR), along with their associated estimators. We show that good experimental design depends on market balance; in highly demand-constrained markets, CR is unbiased, whereas LR is biased; conversely, in highly supply-constrained markets, LR is unbiased, whereas CR is biased. We also introduce and study a novel experimental design based on two-sided randomization (TSR) where both customers and listings are randomized to treatment and control. We show that appropriate choices of TSR designs can be unbiased in both extremes of market balance while yielding relatively low bias in intermediate regimes of market balance.
Customer behavior is often assumed to follow weak rationality, which implies that adding a product to an assortment will not increase the choice probability of another product in that assortment. However, an increasing amount of research has revealed that customers are not necessarily rational when making decisions. In this paper, we propose a new nonparametric choice model that relaxes this assumption and can model a wider range of customer behavior, such as decoy effects between products. In this model, each customer type is associated with a binary decision tree, which represents a decision process for making a purchase based on checking for the existence of specific products in the assortment. Together with a probability distribution over customer types, we show that the resulting model—a decision forest—is able to represent any customer choice model, including models that are inconsistent with weak rationality. We theoretically characterize the depth of the forest needed to fit a data set of historical assortments and prove that with high probability, a forest whose depth scales logarithmically in the number of assortments is sufficient to fit most data sets. We also propose two practical algorithms—one based on column generation and one based on random sampling—for estimating such models from data. Using synthetic data and real transaction data exhibiting nonrational behavior, we show that the model outperforms both rational and nonrational benchmark models in out-of-sample predictive ability.
We consider a seller’s dynamic pricing problem with demand learning and reference effects. We first study the case in which customers are loss-averse: they have a reference price that can vary over time, and the demand reduction when the selling price exceeds the reference price dominates the demand increase when the selling price falls behind the reference price by the same amount. Thus, the expected demand as a function of price has a time-varying “kink” and is not differentiable everywhere. The seller neither knows the underlying demand function nor observes the time-varying reference prices. In this setting, we design and analyze a policy that (i) changes the selling price very slowly to control the evolution of the reference price and (ii) gradually accumulates sales data to balance the trade-off between learning and earning. We prove that, under a variety of reference-price updating mechanisms, our policy is asymptotically optimal; that is, its T-period revenue loss relative to a clairvoyant who knows the demand function and the reference-price updating mechanism grows at the smallest possible rate in T. We also extend our analysis to the case of a fixed reference price and show how reference effects increase the complexity of dynamic pricing with demand learning in this case. Moreover, we study the case in which customers are gain-seeking and design asymptotically optimal policies for this case. Finally, we design and analyze an asymptotically optimal statistical test for detecting whether customers are loss-averse or gain-seeking.
We classify institutions into socially responsible investors (SRI) and not socially responsible investors using the value weighted corporate social responsibility (CSR) scores of their portfolio holdings. We find that firms that exhibit increases in SRI ownership tend to increase future CSR scores. Our analysis of stock price responses to the revelation of SRI ownership changes indicates that the revelation of higher SRI ownership is associated with negative stock returns. These effects are particularly strong when we focus on SRI-activists, who tend to target firms with low CSR scores and lobby to increase them over time. These observations are consistent with the hypothesis that anticipated increases in CSR activities reduce firm values.
We consider a social learning model where agents learn about an underlying state of the world from individual observations as well as from exchanging information with each other. A principal (e.g., a firm or a government) interferes with the learning process in order to manipulate the beliefs of the agents. By utilizing the same forces that give rise to the “wisdom of the crowd” phenomenon, the principal can get the agents to take an action that is not necessarily optimal for them but is in the principal’s best interest. We characterize the social norms and network structures that are susceptible to this kind of manipulation and derive conditions under which a social network is impervious and cannot be manipulated. In the process, we develop a new centrality measure and describe how our model offers insights into designing networks that are resistant to manipulation.
Well-functioning markets for technology (MFT) allow inventors to sell their inventions to others that may derive more value from them. We argue that the growing use of science in inventions enhances MFT. Science-based inventions have higher gains from trade and lower transaction costs. This relationship is amplified in equilibrium because science-based inventions are also likely to feature smaller inventors with a greater propensity to trade. Using large-scale data, we show that patents citing science are more likely to be traded, especially for novel patents and for smaller inventors. We conclude that the growing use of science in invention is beneficial by encouraging the expansion of MFT and supporting a division of innovative labor.
The growth of sharing economy marketplaces like Airbnb has generated discussions on their socioeconomic impact and lack of regulation. As a result, most major cities in the United States have started to collect an “occupancy tax” for Airbnb bookings. In this study, we investigate the heterogeneous treatment effects of the occupancy tax policy on Airbnb listings, using a combination of a generalized causal forest methodology and a difference-in-differences framework. While we find that the introduction of the tax significantly reduces both listing revenues and sales, more importantly, these effects are disproportionately more pronounced for residential hosts with single shared-space (nontarget) listings versus commercial hosts with multiple properties or entire-space (target) listings. We further show that this unintended consequence is caused by customers’ discriminatory tax aversion against nontarget listings. We then leverage these empirical results by prescribing how hosts should optimally set prices in response to the occupancy tax and identify the discriminatory tax rates that would equalize the tax’s effect across nontarget and target listings.
We examine the relationship between brand capital and stock price crash risk. Crash risk, defined as the negative skewness in the distribution of returns for individual stocks, captures asymmetry in risk, and has important implications for investment choices and risk management. Using a sample of 39,685 publicly listed U.S. firm-year observations covering 1975 to 2018, we show that brand capital is significantly and negatively related to crash risk. We also use an advanced machine learning approach and confirm that brand capital is a strong predictor of future stock price crashes. Our cross-sectional analyses show that this negative relationship is more evident for subsamples with transitory poor earnings performance or persistent good earnings performance, greater corporate tax avoidance, and weak corporate governance structures. The results survive numerous robustness tests, including the use of alternative measures of brand capital, crash risk, and several endogeneity tests. In sum, our findings are consistent with agency theory, suggesting that high levels of brand capital expose firms to investor and customer scrutiny, which reduces managerial opportunistic behavior that may include the accumulation and concealment of negative information.
This paper examines whether the massive Chinese anticorruption campaign ensnares corrupt firms, contains a political component, and reduces corporate corruption. Consistent with the campaign’s stated objectives, investigated executives are more likely to come from Chinese firms with characteristics commonly associated with measures of poor governance, self-dealing, and inefficiencies. However, affiliations with prominent investigated political leaders increase investigation likelihood, while university affiliations with current central leadership decrease investigation likelihood, possibly indicating political partiality. Except for reported entertainment expenditures and chief executive officer pay, there has been little evidence of a substantial overall decrease in measures of potential corporate corruption.
We examine whether venture capital (VC) investors learn information contained in public market stock prices. VCs are less likely to stage finance startups and syndicate with other VCs when stock prices are more informative. An instrumental variable approach suggests that the relation is likely causal. The startup’s initial public offering (IPO) prospect is the plausible information contained in stock prices learned by VCs. The effect of VC learning on staging and syndication is more pronounced when collecting information is more costly and the information learned is more reliable. Evidence from a survey of VC investors confirms that they actively learn information from the public market. VCs’ learning from the public market significantly affects their investments across startup firms. Our paper sheds new light on the real effects of financial markets and suggests that the informational role of security prices is much broader than what we have thought.
Although firms’ announcement of data breaches can lead to reputational or operational damages, extant research suggests that stock markets are relatively unresponsive to such announcements. We investigate whether markets’ unresponsiveness can be explained by firms strategically timing the announcement to coincide with busy days in the media, thereby reducing attention and, ultimately, attenuating market reactions. We leverage novel data on data breach announcements in the United States between 2008 and 2018 and create a measure of busyness in the trade press—news pressure—based on the Wall Street Journal. To investigate, we conduct two complementary studies. In Study 1, we employ an instrumental variable approach to assess whether announcements coincide with days of predictably high news pressure. We find that this is the case. On days with a one-standard-deviation-higher predictable news pressure, 4.44% more data breaches are announced (or approximately 19.024 data records). Strategic timing is more prevalent for breaches that are severe, that have firm-internal causes, and that leak healthcare data or credentials. In Study 2, we utilize a stock market event study to assess market reactions conditional on news pressure on the announcement day. We find that data breach announcements are associated with negative market reactions, yet these are attenuated by higher news pressure on the announcement day. If news pressure is on its empirical mean (respectively, one standard deviation above), we estimate a median decline in market capitalization of $347 (respectively, $85) million. We conclude that firms’ strategic timing might explain inconsistent findings in prior work.
Bitcoin falls dramatically short of the scale provided by banks for payments. Currently, its ledger grows by the addition of blocks of ∼2,000 transactions every 10 minutes. Intuitively, one would expect that increasing the block capacity would solve this scaling problem. However, we show that increasing the block capacity would be futile. We analyze strategic interactions of miners, who are heterogeneous in their power over block addition, and users, who are heterogeneous in the value of their transactions, using a game-theoretic model. We show that a capacity increase can facilitate large miners to tacitly collude—artificially reversing back the capacity via strategically adding partially filled blocks in order to extract economic rents. This strategic partial filling crowds out low-value payments. Collusion is sustained if the smallest colluding miner has a share of block addition power above a lower bound. We provide empirical evidence of such strategic partial filling of blocks by large miners of Bitcoin. We show that a protocol design intervention can breach the lower bound and eliminate collusion. However, this also makes the system less secure. On the one hand, collusion crowds out low-value payments; on the other hand, if collusion is suppressed, security threatens high-value payments. As a result, it is untenable to include a range of payments with vastly different outside options, willingness to bear security risk, and delay onto a single chain. Thus, we show economic limits to the scalability of Bitcoin. Under these economic limits, collusive rent extraction acts as an effective mechanism to invest in platform security and build responsiveness to demand shocks. These traits are otherwise hard to attain in a disintermediated setting owing to the high cost of consensus.
Research has found strong links between past credit booms and adverse outcomes for macroeconomic aggregates like output and investment. However, are price impacts also seen more widely in broad asset classes such as equity and fixed-income markets? We document such a robust and significant connection using a large sample of historical data for many advanced countries since 1870. Credit boom periods with a high “leverage factor” tend to be predictably followed by unusually low returns to risky equities, in absolute terms and relative to a safe fixed-income portfolio. Fixed income is a safe haven at these times and has slightly higher than normal returns. We show these properties hold in-sample and out-of-sample. Return predictability because of the leverage factor is distinct from that because of momentum (lagged return) and value (cashflow relative to price). Trading strategies built on the leverage factor accrue meaningful excess profits out-of-sample.
We consider joint learning and optimization problems under a general Cascade Click model. Under this model, customers examine the products in a decreasing order of display, from the top to (potentially) the bottom of the list. At each step, customers can decide to either purchase the current product, forego the current product and continue examining the next product, or simply terminate the search without purchasing any product. We first consider the core pricing problem, where the display position (ranking) of each product is fixed and the only decision that the firm needs to make is pricing. We then consider an extension to the problem of joint ranking and pricing in the presence of filtering options, which the customers can use to filter out some undesirable products. For both problems, we develop Upper Confidence Bound (UCB)-based joint learning and optimization algorithms with theoretical performance guarantees. The key challenge here is in constructing a UCB algorithm that exploits the structure of the Cascade Click model while at the same time taking into account all of the historical click and purchase information. Our numerical results yield three key insights. First, naively applying a standard black box UCB algorithm without adapting it to the Cascade structure is very inefficient and results in a huge loss in total revenues during a finite horizon. Second, applying a learning algorithm by assuming a mis-specified model that ignores the Cascade behavior may result in a highly suboptimal solution. Third, jointly optimizing ranking and pricing can significantly improve performance. Thus, although in practice these decisions are sometimes made separately due to organizational structure, our results suggest that a significant benefit can be realized when the two decisions are more closely coordinated.
Over the past two decades, behavioral research in privacy has made considerable progress transitioning from acontextual studies to using contextualization as a powerful sensitizing device for illuminating the boundary conditions of privacy theories. Significant challenges and opportunities wait, however, on elevating and converging individually contextualized studies to a context-contingent theory that explicates the mechanisms through which contexts influence consumers’ privacy concerns and their behavioral reactions. This paper identifies the important barriers occasioned by this lack of context theorizing on the generalizability of privacy research findings and argues for accelerating the transition from the contextualization of individual research studies to an integrative understanding of context effects on privacy concerns. It also takes a first step toward this goal by providing a conceptual framework and the associated methodological instantiation for assessing how context-oriented nuances influence privacy concerns. Empirical evidence demonstrates the value of the framework as a diagnostic device guiding the selection of contextual contingencies in future research, so as to advance the pace of convergence toward context-contingent theories in information privacy.
We study in this paper a revenue-management problem with add-on discounts. The problem is motivated by the practice in the video game industry by which a retailer offers discounts on selected supportive products (e.g., video games) to customers who have also purchased the core products (e.g., video game consoles). We formulate this problem as an optimization problem to determine the prices of different products and the selection of products for add-on discounts. In the base model, we focus on an independent demand structure. To overcome the computational challenge of this optimization problem, we propose an efficient fully polynomial-time approximation scheme (FPTAS) algorithm that solves the problem approximately to any desired accuracy. Moreover, we consider the problem in the setting in which the retailer has no prior knowledge of the demand functions of different products. To solve this joint learning and optimization problem, we propose an upper confidence bound–based learning algorithm that uses the FPTAS optimization algorithm as a subroutine. We show that our learning algorithm can converge to the optimal algorithm that has access to the true demand functions, and the convergence rate is tight up to a certain logarithmic term. We further show that these results for the independent demand model can be extended to multinomial logit choice models. In addition, we conduct numerical experiments with the real-world transaction data we collect from a popular video gaming brand’s online store on Tmall.com. The experiment results illustrate our learning algorithm’s robust performance and fast convergence in various scenarios. We also compare our algorithm with the optimal policy that does not use any add-on discount. The comparison results show the advantages of using the add-on discount strategy in practice.
Appointment schedules, in essence, balance supply and demand and are often employed in settings where resources are scarce and thus a high utilization is realized (e.g., healthcare). Whereas most of the existing literature focuses on the single-server case, a framework is developed to study appointment scheduling in multiserver settings. Relying on phase-type approximations, general service-time distributions are modeled, which are fed into a recursive approach allowing evaluation and optimization of an objective function that balances expected waiting times and idle times. Studying optimized schedules for multiple servers reveals that the start and end of a session can deviate greatly from the dome-shaped pattern as established for the single-server case. Furthermore, a comparison of various multiserver setups shows that significant performance gains can be achieved when servers are pooled. This allows an explicit quantification of the cost of continuity of care. In addition, session overtime as well as early finish of servers can be incorporated in the approach; the benefits of the additional flexibility that a multiserver setting provides are summarized. For the stationary plateau of the dome, to which the optimal interarrival times converge, steady-state appointment schedules are obtained by exploiting the embedded Markov chain; these schedules are shown and argued to converge quickly to optimal solutions obtained in a heavy-traffic regime. In this regime, algebraic solutions are derived, which provide interesting managerial guidelines when the pooling of servers is considered in appointment scheduling.
During a heat wave on a summer afternoon, a utility firm may face unusually high demand and procurement cost for electricity. Under such conditions, a demand-response event occurs, and the firm asks residential customers to reduce their demand. Such a demand-response program not only reduces the firm’s procurement cost, but it can also be environmentally beneficial by reducing generation from emissions-intensive power plants. In a demand-response program, a utility firm pays a rebate to customers for each unit of their demand reduction—the difference between a customer’s demand and consumption. However, the demand reduction cannot be directly measured because the firm cannot observe the customer’s demand, but only its consumption. Accordingly, a utility firm estimates the demand reduction by subtracting the consumption from a baseline, which is typically set as a customer’s average historical demand. In this paper, we first investigate how the existence of a baseline influences a customer’s demand reduction decision and when it leads to under- or overestimation of the actual demand reduction. We then analyze how a utility firm should adjust the baseline from the customer’s average demand. We find that it should inflate (deflate) the baseline if the cost difference between event and non-event periods is large (small), even though this may lead to greater overestimation (underestimation) of the customer’s demand reduction. Interestingly, we show that inflation of the baseline, which one would expect to make reducing demand more attractive for a customer, can actually lead to a smaller demand reduction, resulting in higher emissions.
One of the central challenges in online advertising is attribution, namely, assessing the contribution of individual advertiser actions such as emails, display ads, and search ads to eventual conversion. Several heuristics are used for attribution in practice; however, most do not have any formal justification. The main contribution in this work is to propose an axiomatic framework for attribution in online advertising. We show that the most common heuristics can be cast under the framework and illustrate how these may fail. We propose a novel attribution metric, which we refer to as counterfactual adjusted Shapley value (CASV), which inherits the desirable properties of the traditional Shapley value while overcoming its shortcomings in the online advertising context. We also propose a Markovian model for the user journey through the conversion funnel, in which ad actions may have disparate impacts at different stages. We use the Markovian model to compare our metric with commonly used metrics. Furthermore, under the Markovian model, we establish that the CASV metric coincides with an adjusted “unique-uniform” attribution scheme. This scheme is efficiently implementable and can be interpreted as a correction to the commonly used uniform attribution scheme. We supplement our theoretical developments with numerical experiments using a real-world large-scale data set.
We consider price optimization under the finite-mixture logit model. This model assumes that customers belong to one of a number of customer segments, where each customer segment chooses according to a multinomial logit model with segment-specific parameters. We reformulate the corresponding price optimization problem and develop a novel characterization. Leveraging this new characterization, we construct an algorithm that obtains prices at which the revenue is guaranteed to be at least (1−ϵ) times the maximum attainable revenue for any prespecified ϵ>0. Existing global optimization methods require exponential time in the number of products to obtain such a result, which practically means that the prices of only a handful of products can be optimized. The running time of our algorithm, however, is exponential in the number of customer segments and only polynomial in the number of products. This is of great practical value, because in applications, the number of products can be very large, whereas it has been found in various contexts that a low number of segments is sufficient to capture customer heterogeneity appropriately. The results of our numerical study show that (i) ignoring customer segmentation can be detrimental for the obtained revenue, (ii) heuristics for optimization can get stuck in local optima, and (iii) our algorithm runs fast on a broad range of problem instances.
In e-commerce warehouses, online retailers increase their efficiency by using a mixed-shelves (or scattered storage) concept, where unit loads are purposefully broken down into single items, which are individually stored in multiple locations. Irrespective of the stock keeping units a customer jointly orders, this storage strategy increases the likelihood that somewhere in the warehouse the items of the requested stock keeping units will be in close vicinity, which may significantly reduce an order picker’s unproductive walking time. This paper optimizes picker routing through such mixed-shelves warehouses. Specifically, we introduce a generic exact algorithmic framework that covers a multitude of picking policies, independently of the underlying picking zone layout, and is suitable for real-time applications. This framework embeds a bidirectional layered graph algorithm that provides the best known performance for the simple picking problem with a single depot and no further attributes. We compare three different real-world e-commerce warehouse settings that differ slightly in their application of scattered storage and in their picking policies. Based on these, we derive additional layouts and settings that yield further managerial insights. Our results reveal that the right combination of drop-off points, dynamic batching, the utilization of picking carts, and the picking zone layout can greatly improve the picking performance. In particular, some combinations of policies yield efficiency increases of more than 30% compared with standard policies currently used in practice.
This paper explores how loss-framed incentives affect behavior in a multitasking environment in which participants have more than one way of recovering (expected) losses. In a real-effort laboratory experiment, we offer participants task incentives that are framed as either a reward (gain) or penalty (loss). We study their responses along three dimensions: performance in the incentivized task, theft, and voluntary provision of help. We find that framing incentives as a penalty rather than as a reward does not significantly improve task performance, but it increases theft and leads to a small and insignificant reduction in the share of participants willing to help the experimenter. Secondary analyses based on our theoretical framework help us pin down the mechanism at play and suggest that loss aversion drives participants’ response. Our findings have important implications for incentive design in practice.
With the rapid growth of e-commerce, agency selling is currently gaining popularity among online retailers (e-tailers). Prior research implicitly abstracts away cross-brand pass-through under traditional wholesale selling (i.e., how the retail price of another brand adjusts to changes in a given brand’s wholesale price) and suggests that a shift to agency selling benefits e-tailers but harms suppliers. As an important counterweight to this result, we discover that an e-tailer’s choice regarding selling format is critically moderated by retail pass-through behavior. On the one hand, agency selling can improve channel efficiency compared with wholesale selling. On the other hand, the relative intensity of supplier competition between these two selling formats is ambiguous. We show that the existing result applies only for a nonnegative cross-brand pass-through rate (e.g., under linear demands); otherwise (e.g., under multiplicative or exponential demands), the opposite may hold. Interestingly, we find that the conflict over the preference of selling format may not arise, and that all channel members could be better off with wholesale selling. Compared with the case of Bertrand competition, the e-tailer is even more likely to adopt wholesale selling under Cournot competition. Finally, under agency selling with an endogenous commission fee, we advise caution regarding the seemingly innocuous normalization of suppliers’ marginal costs. Surprisingly, suppliers may benefit from higher marginal costs. Overall, our findings not only shed light on the theory of agency selling but also provide a plausible explanation for the observation that wholesale selling continues to prevail in online markets.
This paper estimates the effects of time-varying consumer preference bias on trade flows and welfare. We use a unique data set from the BBC World Service Poll, which surveys (annually during 2005–2017 with some gaps) the populations of a wide array of countries on their views of whether an evaluated country is having a mainly positive or negative influence in the world. We identify the effects on consumer preference parameters due to shifts in these country image perceptions and quantify their general equilibrium effects on bilateral exports and welfare (each time for an evaluated exporting country, holding the exporting country’s own preference parameters constant). We consider five important shifts in country image: the George W. Bush effect, the Donald Trump effect, the Senkaku Islands Dispute effect, the Brexit effect, and the Good-Boy Canadian effect. We find that such changes in bilateral country image perceptions have quantitatively important trade and welfare effects. The negative impact of Donald Trump’s “America First” campaign rhetoric on the U.S.’s country image might have cost the United States 4%–5% of its total exports and welfare gains from trade. In contrast, the consistent improvement of Canada’s country image between 2010 and 2017 has amounted to more than 8% of its total welfare gains from trade.
We consider a subscription platform that offers services to variety-seeking consumers who incorporate transportation costs in their decision of how many and which vendor services to consume. ClassPass in fitness and MoviePass in entertainment are examples of such platforms. We find that for the platform to be successful, it should enter markets where consumers’ added benefit from patronizing more than one vendor is relatively high, thus strengthening the position of the platform in negotiations with the vendors. As well, managers should consider entering markets where competition between the vendors is relatively weak and in particular, where vendors benefit from local monopoly positions because of high transportation costs incurred by consumers. When entering such markets, offering the subscription contract is likely to attract new customers who are not active when the platform does not exist. Moreover, appropriate crafting of the agreement with the vendors in this case allows the parties to fully extract the surplus derived by platform customers. Last, the platform’s managers should be cognizant of the need to identify tools that facilitate alleviated price competition with vendors. Negotiating over an appropriate transfer fee per customer to pay the vendor or imposing restrictions on the level of service that their customers can use may be such tools. Offering customers lower-quality services when using the vendor in comparison with the quality they could obtain by buying directly from him may not be a successful tool to alleviate price competition.
Using a proprietary data set containing more than 10 million transactions over 14 months from hundreds of grocery stores, we examine consumer payment choices at point of sale (POS) between cash and mobile, where the use of other methods (including cards) is minimal. We find that cash is the dominant method of payment. Nonetheless, the share of mobile payments has increased at the expense of cash payments over time. Importantly, we exploit price incentives for consumers using mobile payment to examine the price substitution between cash and mobile payments. Our results show that consumers are more likely to use mobile payment when they receive price incentives for doing so, and such an effect persists for a few days, even after the price incentive expires. Nonetheless, the price incentives are unlikely financed by additional transactions paid via mobile but subsidized by mobile payment providers. Interestingly, we find several factors that enhance and supplement the steering effect of price incentives. First, a larger monetary reward seems to induce a stronger impact of price incentive on mobile payment. Second, the steering effect of price incentive is stronger for stores that serve consumers who have frequently been using mobile payment and for price-sensitive consumers. Third, the additional mobile payments come from transactions that would not have occurred with price incentive and those that switch from cash transactions.
We examine the effect of introducing an incentive plan based on social performance in a sample of 186 social mission–oriented firms in Korea. We find that the social performance of social enterprises (SEs) significantly improves over time after adoption of an incentive plan based on social performance, and that the incentive effect increases with managers’ perceived measurability of social performance. Moreover, we document that social bonuses do not harm SEs’ financial performance and that they have a positive spillover effect on financial performance in SEs that have a higher level of task complementarity between social and financial goals. Our results also show that when the main beneficiary of social bonuses is expected to be a firm’s employees, the incentive effect of social bonuses decreases (increases) with a firm’s focus on social controls (formal controls). In contrast, when the main beneficiary is expected to be a firm’s social mission, the incentive effect increases with a firm’s reliance on social controls.
Regression regularization techniques show that deviations of accounting fundamentals from their preceding moving averages forecast drifts in equity market prices. Deviations-based predictability survives a comprehensive set of prominent anomalies. The profitability applies strongly to the long leg and survives value weighting and excluding microcaps. We provide evidence that the predictability arises because investors anchor to recent means of fundamentals. A factor based on our fundamentals-based index yields economically significant intercepts after controlling for a comprehensive set of other factors, including those based on profit margins and earnings drift.
We show that executive ownership is a significant driver of the demand for credit following credit expansion policies. Our focus on credit demand is in contrast to most studies that have focused on credit supply factors such as bank capital. Our identification exploits the large and unexpected Chinese credit expansion in 2008. This setting offers a unique advantage as in 2008 the Chinese government had almost complete control over the banking sector and it directed the banks to increase credit supply. Thus, in this setting, demand, rather than supply, largely drives the observed changes in firms’ borrowing. We provide extensive robustness tests to validate our results.
This paper documents the bimodality of momentum stocks: both high- and low-momentum stocks have nontrivial probabilities for both high and low returns. The bimodality makes the momentum strategy fundamentally risky and can cause a large loss. To alleviate the bimodality and improve return predictability, this paper develops a novel cross-sectional prediction model via machine learning. By reclassifying stocks based on their predicted financial performance, the model significantly outperforms off-the-shelf machine learning models. Tested on the U.S. market, a value-weighted long-short portfolio earns a monthly alpha of 2.4% (t-statistic = 6.63) when regressed against the Fama–French five factors plus the momentum and short-term reversal factors.
Since May 2015 several U.S. Bank Holding Companies (BHCs) have been newly classified as small banks by regulators, thus benefiting from a friendlier regulatory capital environment. Using a difference-in-differences setting, we show that less regulation on small BHCs boosts small business lending of the affiliated commercial banks. We employ various tests to demonstrate that these findings are attributable to a capital channel where increases in lending are driven by the preferential capital treatment granted to the small BHC. The regulatory capital relief also has some positive effects for the local economy. Overall, the effects of the regulatory capital relief for small BHCs are consistent with its desired policy objectives.
This paper proposes a new reduced-form model for the pricing of VIX derivatives that includes an independent stochastic jump intensity factor and cojumps in the level and variance of VIX, while allowing the mean of VIX variance to be time varying. I fit the model to daily prices of futures and European options from April 2007 through December 2017. The empirical results indicate that the model significantly outperforms all other nested models and improves on benchmark by 21.6% in sample and 31.2% out of sample. The model more accurately portrays the tail behavior of VIX risk-neutral distribution for both short and long maturities, as it better captures the time-varying skew found to be largely independent of the level of the VIX smile.
We use a series of experiments to understand whether and how people’s beliefs about their own abilities are biased relative to the Bayesian benchmark and how these beliefs then affect behavior. We find that subjects systematically and substantially overweight positive feedback relative to negative (asymmetry) and also update too little overall (conservatism). These biases are substantially less pronounced in an ego-free control experiment. Updating does retain enough of the structure of Bayes’ rule to let us model it coherently in an optimizing framework, in which, interestingly, asymmetry and conservatism emerge as complementary biases. We also find that exogenous changes in beliefs affect subjects’ decisions to enter into a competition and do so similarly for more and less biased subjects, suggesting that people cannot “undo” their biases when the time comes to decide.
We estimate the causal effects of responsible scheduling practices on store financial performance at the U.S. retailer Gap, Inc. The randomized field experiment evaluated a multicomponent intervention designed to improve dimensions of work schedules—consistency, predictability, adequacy, and employee control—shown to foster employee well-being. The experiment was conducted in 28 stores in the San Francisco and Chicago metropolitan areas for nine months between November 2015 and August 2016. Intent-to-treat (ITT) analyses indicate that implementing responsible scheduling practices increased store productivity by 5.1%, a result of increasing sales (by 3.3%) and decreasing labor (by 1.8%). Drawing on qualitative interviews with managers and quantitative analyses of employee shift-level data, we offer evidence that the intervention improved financial performance through improved store execution. Our experiment provides evidence that responsible scheduling practices that take worker well-being into account can enhance store productivity by motivating additional employee effort and reducing barriers to employees adhering to the scheduled labor plan.
This study identifies information accessibility as a determinant of corporate innovation. Using the sudden termination of Google’s search services in China, we find a persistently large negative effect on the intensity and quality of innovation among firms relying on foreign knowledge. The results are stronger for firms in industries dominated by foreign technology, in regions with local web filters, and for firms with fewer alternative sources of foreign information. We also find that the affected firms cite fewer foreign patents and their innovation efficiency declines after Google’s exit. Overall, the results are consistent with the view that access to information is an important driver of technological progress.
We consider a rental service with a fixed number of rental units distributed across multiple locations. The units are accessed by customers without prior reservation and on an on-demand basis. Customers can decide on how long to keep a unit and where to return it. Because of the randomness in demand and in returns, there is a need to periodically reposition inventory away from some locations and into others. In deciding on how much inventory to reposition and where, the system manager balances potential lost sales with repositioning costs. Although the problem is increasingly common in applications involving on-demand rental services, not much is known about the nature of the optimal policy for systems with a general network structure or about effective approaches to solving the problem. In this paper, first, we show that the optimal policy in each period can be described in terms of a well-specified region over the state space. Within this region, it is optimal not to reposition any inventory, whereas, outside the region, it is optimal to reposition but only such that the system moves to a new state that is on the boundary of the no-repositioning region. We also provide a simple check for when a state is in the no-repositioning region. Second, we leverage the features of the optimal policy, along with properties of the optimal cost function, to propose a provably convergent approximate dynamic programming algorithm to tackle problems with a large number of dimensions.
In this paper, we model a firm that can reduce its carbon footprint in the presence of a segment of eco-conscious consumers, who consider the product’s carbon footprint when making purchasing decisions. The firm can reduce its controllable emissions at increased fixed and variable costs. The firm can also buy carbon offsets, at the price set by a nongovernmental organization (NGO), for both its controllable and uncontrollable emissions in the supply chain. We find that the firm should not use these two emission reduction methods as simple substitutes. In particular, as the offset price decreases, the firm may spend more efforts reducing its controllable emissions. Also, a firm’s decision to buy carbon offsets depends on the correlation between consumers’ preferences for the product function and for its environmental attributes, and this has implications for NGOs selling offsets. Specifically, although NGOs should price offsets as low as possible in most cases, we find some instances where a premium pricing strategy may be more effective in promoting lower-carbon footprint products, especially when eco-conscious consumers have a significantly higher valuation for the product than those who do not care about the environment, on average.
Although innovation sharing between a buyer and a supplier—a common practice in the automotive industry—can increase the efficiency and total profit of a supply chain, suppliers are often reluctant to do so. Sharing innovations would leave the supplier in a vulnerable position if the buyer were to exploit the information (e.g., by resharing the supplier’s innovation with competing suppliers). Anecdotal evidence from automotive suppliers tells us that the nature of a supplier-buyer relationship for the most part depends on who (e.g., a short-run-focused procurement manager or a long-term-focused engineer) manages the relationship. In this paper, we examine how the allocation of decision rights to short-run- and long-run-focused employees affects collaboration between the firms. To accomplish this, we model a relationship between a supplier and a buyer where the buyer is a dual decision maker, consisting of long-run- and/or short-run-focused employees. We characterize the equilibrium of this model and show that the frequency of collaborative outcomes is lowest when the procurement manager has full control and highest when the engineer has full control or in a setup where employees can unilaterally enforce collaboration. A laboratory experiment confirms that collaborations occur more frequently when a manager with a long-term focus is in charge of or actively involved in decision making. Depending on how joint control is structured, joint control can help or hurt collaboration: Collaboration is highest when employees can unilaterally enforce it, whereas the random joint-control case results in collaboration that is as low as in the procurement manager control case.
We provide a new framework to identify demand elasticities in markets where managers rely on algorithmic recommendations for price setting and apply it to a data set containing bookings for a sample of midsized hotels in Europe. Using nonbinding algorithmic price recommendations and observed delay in price adjustments by decision makers, we demonstrate that a control-function approach, combined with state-of-the-art model-selection techniques, can be used to isolate exogenous price variation and identify demand elasticities across hotel room types and over time. We confirm these elasticity estimates with a difference-in-differences approach that leverages the same delays in price adjustments by decision makers. However, the difference-in-differences estimates are more noisy and only yield consistent estimates if data are pooled across hotels. We then apply our control-function approach to two classic questions in the dynamic pricing literature: the evolution of price elasticity of demand over and the effects of a transitory price change on future demand due to the presence of strategic buyers. Finally, we discuss how our empirical framework can be applied directly to other decision-making situations in which recommendation systems are used.
What should a distressed buyer’s sourcing strategy be? We find that this depends on the dynamics in a potential in-court bankruptcy. To establish causality, we use a novel sourcing data set in combination with a unique quasi-natural experimental setting provided by a regulatory shock that significantly strengthened the protection granted to suppliers when a distressed buyer files for bankruptcy: the Supplier Protection Act. We find that, following this regulatory change, the number of suppliers for buyers near financial distress (those most affected by the act, the treated group) increased by nearly 35% relative to financially sound firms (the control group). We also find that this shift allowed distressed buyers to obtain more trade credit, expand inventory holdings, and increase performance, leading to an overall increase in firm value of 7.2%. In turn, these effects led to a sizable reduction in the probability of the affected buyers defaulting and filing for bankruptcy. Our results have important implications for corporate executives: right-sizing the supply base can be critical for buyers near financial distress, and implementing policies to engage and protect suppliers can be the way out of distress.
The traditional queueing literature assumes that service time is largely independent of social influences. However, queues are social systems; and social considerations are therefore likely to impact customers’ service time decision to the extent they have control. Through a series of experiments, we show that when others are waiting in line, customers tend to accelerate their own service time, and in doing so, sacrifice their own consumption utility. This behavior is driven by concern for others. Notably, the effect is diminished when they themselves have waited, as it is perceived as fair to let others wait if one also had to wait. We further show that obscuring the visibility between customers in service and those waiting in line diminishes the negative effect of others queueing on one’s own service time.
Vertical equity or fairness is an important aspect in many settings, yet has received relatively little attention in the literature. Recent developments underline the practical relevance (e.g., COVID-19 vaccination policies). It plays an important role in the performance evaluation of many (nongovernmental) organizations. For example, donors might require a family-planning organization to allocate a minimum fraction of the total utility (client volume) to a particular player (the “high-impact” subgroup of the population, e.g., young and poor clients). However, the price (decrease in client volume) of such requirements is not well-understood. Consequently, this price is not accounted for in decision making. We provide an analytical upper bound on the price (i.e., loss of overall utility) of vertical equity considerations in resource allocation. We assume that these concerns are expressed via outcome constraints, specifying a minimum percentage of the total utility for each player. Our set-up considers a decision maker maximizing total utility over a general convex set, subject to outcome constraints. The set-up is general and applicable to many practical problems. Our results depend only on high-level parameters and are therefore well-suited for strategic decision making. We conclude with two applications. First, we apply our results to practical instances in health delivery. We confirm that outcome constraints can entail a substantial price and analyze the factors driving this price close to the worst-case bound. Second, we analyze how our results can help bound the impact of prioritization in vaccine allocation.
Newborn screening (NBS) is a state-level initiative that detects life-threatening genetic disorders for which early treatment can substantially improve health outcomes. Cystic fibrosis (CF) is among the most prevalent disorders in NBS. CF can be caused by a large number of mutation variants to the CFTR gene. Most states use a multitest CF screening process that includes a genetic test (DNA). However, due to cost concerns, DNA is used only on a small subset of newborns (based on a low-cost biomarker test with low classification accuracy), and only for a small subset of CF-causing variants. To overcome the cost barriers of expanded genetic testing, we explore a novel approach, of multipanel pooled DNA testing. This approach leads not only to a novel optimization problem (variant selection for screening, variant partition into multipanels, and pool size determination for each panel), but also to novel CF NBS processes. We establish key structural properties of optimal multipanel pooled DNA designs; develop a methodology that generates a family of optimal designs at different costs; and characterize the conditions under which a 1-panel versus a multipanel design is optimal. This methodology can assist decision-makers to design a screening process, considering the cost versus accuracy trade-off. Our case study, based on published CF NBS data from the state of New York, indicates that the multipanel and pooling aspects of genetic testing work synergistically, and the proposed NBS processes have the potential to substantially improve both the efficiency and accuracy of current practices.
This paper examines the impact of Airbnb on the local rental housing market. Airbnb provides landlords an alternative opportunity to rent to short-term tourists, potentially leading some landlords to switch from long-term rentals and thereby, affecting rental housing supply and affordability. Despite recent government regulations to address this concern, it remains unclear how many and what types of properties are switching. Combining Airbnb and American Housing Survey data, we estimate a structural model of property owners’ decisions and conduct counterfactual analyses to evaluate various regulations. We find that Airbnb mildly cannibalizes the long-term rental supply. Cities where Airbnb is more popular experience a larger rental supply reduction, but they do not necessarily have a larger percentage of switchers. Affordable units are the major sources of both the negative and positive impacts of Airbnb. They cause a larger rental supply reduction, which harms local renters; they also create a larger market expansion effect, which benefits local hosts who own affordable units and may be less economically advantaged. Policy makers need to strike a balance between local renters’ affordable housing concerns and local hosts’ income source needs. We also find that imposing a linear tax is more desirable than limiting the number of days a property can be listed. We propose a new convex tax that imposes a higher tax on expensive units and show that it can outperform existing policies in terms of reducing cannibalization and alleviating social inequality. Finally, Airbnb and rent control can exacerbate each other’s negative impacts.
Native advertising is not fully transparent to consumers because it bears similarity to editorial content. Increasing the opaqueness of native ads can raise publishers’ click-through rate, but can also negatively affect consumers’ quality perception of the publishers’ editorial content and lead to lower profitability. In this paper, we develop a game-theoretical model of native ads to investigate the economic implications of regulation. Our model considers two types of publishers, who differ in the quality of their editorial content. We show that publishers have incentives to self-regulate native ads through lower opaqueness in order to signal their high quality to the market. We find that stricter regulation can make native ads more opaque, on average, because it can eliminate the incentives of high-quality publishers to distinguish themselves from low-quality publishers. Consequently, strengthening regulation can yield lower consumer surplus and social welfare.
We investigate the welfare of intermediaries in oligopolistic markets where intermediaries offer additional services. We exploit the unique circumstance that in the empirical setting studied, outdoor advertising, consumers can purchase from manufacturers or intermediaries. Intermediaries provide additional services to the consumers and charge a margin for them. Intermediaries provide the following additional services: search services (information about products), purchase-aggregation services (access to quantity discounts), and consulting services. We specify an equilibrium model and structurally estimate it using market-level data. The demand includes consumers with costly search and channel-specific preferences. The supply includes two distribution channels. One features bargaining about wholesale prices between manufacturers and intermediaries and downstream price competition. The other is vertically integrated. We show how Google search data can be used to identify the search-cost parameters. We use the estimated model to simulate counterfactual scenarios where intermediaries do not offer additional services. We find that the three services considered provide value to consumers, with search playing a prominent role. Our analysis helps explain why intermediaries are ubiquitous in modern economies despite the double marginalization.
This paper quantifies the effects of online review platforms on restaurant revenue and consumer welfare. Using a novel data set containing revenues and information from major online review platforms in Texas, I show that online review platforms help consumers learn about restaurant quality more quickly. The effects on learning show up in restaurant revenues. Specifically, doubling the review activity increases the revenue of a high-quality independent restaurant by 5%–19% and decreases that of a low-quality restaurant by a similar amount. These effects vary widely across restaurants’ locations. Restaurants around highway exits are affected twice as much as those in nonhighway areas, implying that reviews are more useful to travelers and tourists than locals. The effects also decline as restaurants age, consistent with the diminishing value of information in learning. In contrast, chain restaurants are affected to a much lesser degree than independent restaurants. Building on this evidence, I develop a structural demand model with aggregate social learning. Counterfactual analyses indicate that online review platforms raise consumer welfare much more for tourists than for locals. By encouraging consumers to eat out more often at high-quality independent restaurants, online review platforms increased the total industry revenue by 3.0% over the period from 2011–2015.
We study dynamic contests between two players whose performance is determined jointly by effort and luck. The players observe each other’s positions in real time. There is a fixed deadline, and the player with a higher performance at the deadline wins the contest. We fully characterize the Markov perfect equilibrium for heterogeneous players. Effort is high when the players are tied but collapses quickly when one of them assumes a lead, due to a dynamic momentum effect. Therefore, total expected effort does not necessarily increase in the prize or in the players’ abilities. We discuss implications for contest design and propose splitting the contest to cool off competition and introducing optimal head-starts for heterogeneous players as possible solutions.
Nonlinear perception of risk is integrated into models of decision under ambiguity, thereby providing a theoretical basis for behavioral analyses that involve both risk and ambiguity. The main model replaces the risk front of maxmin expected utility by rank-dependent utility, and it is derived from simple, observable axioms that are not restricted to expected utility under risk. The model highlights the interaction between risk attitude and ambiguity attitude, and it is compatible with the paradoxical choices hypothesized by Machina. Following the same idea, nonlinear perception of risk can also be integrated into variational and multiplier preferences. When applied to comparative ambiguity attitudes, the idea enables more comparisons by allowing for both heterogeneous taste and perception of risk.
This paper studies how the presence of peers and different peer assignment rules—self-selection versus random assignment—affect individual performance. Using a framed field experiment, we find that the presence of a randomly assigned peer improves performance by 28% of a standard deviation (SD), whereas self-selecting peers induces an additional 15%–18% SD improvement in performance. Our results document peer effects in multiple characteristics and show that self-selection changes these characteristics. However, a decomposition reveals that variations in the peer composition contribute only little to the performance differences across peer assignment rules. Rather, we find that self-selection has a direct effect on performance.
We investigate company reactions to the threat of reputational losses. To do so, we leverage the introduction of a naming-and-shaming policy for tax debt enforcement in Slovenia in 2012. The policy was announced four months before its implementation, which allows us to separate responses to the threat of shaming from the responses to actual shaming. Our extensive administrative tax data cover taxes owed and paid for the universe of taxpayers in Slovenia. Based on a quasi-experimental research design, we document that corporations significantly reduce their tax debt in response to the threat of shaming, particularly in industries in which reputational concerns are likely to be important. Self-employed individuals also reduce their tax debt but to a lesser extent. The publication of the first naming-and-shaming list further reduced tax debt among shamed taxpayers. However, the effect of actual shaming is marginal compared with that of the threat of shaming and reduces quickly. Previously compliant taxpayers remained compliant throughout.
In the two weeks after the U.S. Congress passed a package of anti-sex trafficking bills on March 21, 2018, two of the largest online commercial sex advertising platforms ceased operation. On March 23, Craigslist voluntarily removed their personals section, which had been dominated by advertisements for commercial sex. And on April 6, the Department of Justice seized Backpage.com, the largest online platform for commercial sex advertisements. Our research examines the impact of these shutdowns on a variety of important outcome variables, notably prostitution arrests and violence against women—variables that the prior literature has shown were impacted by the introduction of commercial sex advertising platforms. We employ a generalized difference-in-differences model by exploiting cross-city variation in the preshutdown usage of the two shuttered sites. We find no causal effect of the shutdowns on any of the outcome variables we measure. Further analysis suggests that these null results are likely due to the fluidity of online markets. Our data show that the majority of advertisers and users of Backpage and Craigslist’s personals quickly moved to other (often off-shore) commercial sex advertising portals. Our results highlight the challenges that governments face in reducing online sex trafficking, as the market for commercial sex advertising appears agile enough to quickly disperse to offshore sites after a few popular domestic sites are shut down. Our results have general implications for the governance of other illegal activities online.
Many digital platforms have accrued enormous power and scale, leveraging cross-side network effects between the sides they connect (e.g., producers and consumers or creators and viewers). Platforms motivate a diverse spectrum of producers, large and small, to participate by sharing platform revenue with them, predominantly under a linear revenue-sharing scheme with the same commission rate regardless of producer power or size. Under pressure from society, lawsuits, and antitrust investigations, major platforms have announced revenue sharing designs that favor smaller businesses. We develop a model of platform economics and show that a small-business oriented (SBO) differential revenue sharing design can increase total welfare and outputs on the platform. Although smaller producers almost always benefit from the shift in revenue sharing design, spillover effects can also make large producers better off under some conditions. More interestingly, we show that platforms are the most likely winner under a differential revenue sharing scheme. Hence, an intervention that ostensibly offers concessions and generous treatment to producers might well be self-serving for platforms and good for the entire ecosystem.
How does task expertise affect the allocation of attention? Our theory argues that when attention is scarce, expertise and attention are complements: A manager optimally focuses her attention on tasks in which she has relatively more expertise; she “manages with style.” In contrast, when attention is abundant, attention and expertise become substitutes: A manager shifts her attention toward tasks in which she has less expertise; she “manages against her style.” Using microlevel data on managers from two unrelated companies and employing various measures of time stress and managerial attention, we find converging and supporting evidence. A manager’s attention capacity determines whether she manages with style or against it. Whereas current behavioral approaches view managing with style as prevalent and biased, our theory and findings suggest, instead, that it is contingent and optimal.
Insurance companies and pension funds have liabilities far into the future and typically well beyond the longest maturity bonds trading in fixed-income markets. Such long-lived liabilities still need to be discounted, and yield curve extrapolations based on the information in observed yields can be used. We use dynamic Nelson-Siegel (DNS) yield curve models to extrapolate risk-free yield curves for Switzerland and several countries. We find slight biases in extrapolated long bond yields of just a few basis points. In addition, the DNS model allows the generation of useful financial risk metrics, such as ranges of possible yield outcomes over projection horizons commonly used for stress-testing purposes. Therefore, we recommend using DNS models as a simple tool for generating extrapolated yields for long-term interest rate risk management.
Investment consultants market their services by claiming their fund manager recommendations add significant value. Using nonpublic data sourced from investment consultants and the UK regulator, we find no such evidence, but identify several practices that explain their exaggerated claims: comparisons to benchmarks instead of peers, inclusion of simulated and backfilled returns, use of investment horizons that allow losers to be forgotten, and unexplained exclusions of products from the analysis. Consultants do not fully disclose their methodology to investors, who therefore cannot verify or reliably compare their performance.
Using a large sample of unlisted industrial firms in China, we find that a decrease in local governments’ land transfer revenues leads to lower tax avoidance by firms within their jurisdiction. Our cross-sectional variation tests suggest that the tax-avoidance-reduction effect is stronger in cities with higher land finance dependence and government intervention, as well as where the political leaders have stronger promotion incentives. However, the effect is moderated for politically connected firms. Further analysis reveals that intensified tax enforcement is the mechanism through which land transfer revenue losses result in decreased tax avoidance. Our study offers novel evidence on a previously underexplored determinant of corporate tax avoidance through the lens of land finance.
Patent thickets, a phenomenon of fragmented ownership of overlapping patent rights, hamper firms’ commercialization of patents and thus deliver asset pricing implications. We show that firms with deeper patent thickets are involved in more patent litigations, launch fewer new products, and become less profitable in the future. These firms are also associated with lower subsequent stock returns, which can be explained by a conditional Capital Asset Pricing Model (CAPM) based on a general equilibrium model that features heterogeneous market betas conditional on time-varying aggregate productivity. This explanation is supported by further evidence from factor regressions and stochastic discount factor tests.
The problems of nonconcave utility maximization appear in many areas of finance and economics, such as in behavioral economics, incentive schemes, aspiration utility, and goal-reaching problems. Existing literature solves these problems using the concavification principle. We provide a framework for solving nonconcave utility maximization problems, where the concavification principle may not hold, and the utility functions can be discontinuous. We find that adding portfolio bounds can offer distinct economic insights and implications consistent with existing empirical findings. Theoretically, by introducing a new definition of viscosity solution, we show that a monotone, stable, and consistent finite difference scheme converges to the value functions of the nonconcave utility maximization problems.
The relationship between profitability and leverage is controversial in the capital structure literature. We revisit this relation in light of a novel quasi-natural experiment that increases market power for a subset of firms. We find that treated firms increase their profitability throughout the treatment period. However, they only transiently reduce financial leverage, gradually reverting to their preshock level. Firms respond differently according to size with large firms gradually adjusting their leverage toward a new target and small firms reducing it. The patterns are broadly consistent with dynamic trade-off models with both fixed and variable adjustment costs.
We introduce a new framework that facilitates term structure modeling with both positive interest rates and flexible time series dynamics but that is also tractable, meaning amenable to quick and robust estimation. Using both simulations and U.S. historical data, we compare our approach with benchmark Gaussian and stochastic volatility models as well as a shadow rate model that enforces positive interest rates. Our approach, which remains arbitrarily close to arbitrage free, offers a more accurate characterization of bond Sharpe ratios because of a better fit of the volatility dynamics and a more efficient estimation of the return dynamics. Further, the shadow rate and stochastic volatility models exhibit important restrictions that are largely absent in our approach.
How does cognitive diversity in a group affect its performance? Prior research suggests that group cognitive diversity poses a performance tradeoff: Diverse groups excel at creativity and innovation, but struggle to take coordinated action. Building on the insight that group cognition is not static, but is instead dynamically and interactively produced, we introduce the construct of discursive diversity, a manifestation of group cognitive diversity, which reflects the degree to which the meanings conveyed by group members in a given set of interactions diverge from one another. We propose that high-performing teams are ones that have a collective capacity to modulate shared cognition to match changing task requirements: They exhibit higher discursive diversity when engaged in ideational tasks and lower discursive diversity when performing coordination tasks. We further argue that teams exhibiting congruent modulation—that is, those with low group-level variance in members’ within-person semantic shifts to changing task requirements—are more likely to experience success than teams characterized by incongruent modulation. Using the tools of computational linguistics to derive a measure of discursive diversity and drawing on a novel longitudinal data set of intragroup electronic communications and performance outcomes for 117 remote software development teams on an online platform (www.gigster.com), we find support for our theory. Our findings suggest that the performance tradeoff of group cognitive diversity is not inescapable: Groups can navigate it by aligning their levels of discursive diversity to match their task requirements and by having members stay aligned with one another as they make these adjustments.
We investigate whether sophisticated investors obtain information about Securities and Exchange Commission (SEC) comment letters before the public release date. Specifically, we examine mutual fund trading behavior around dates firms receive a comment letter. We find significant abnormal net selling by mutual funds immediately after a firm receives a comment letter. Additional tests find that abnormal net selling is greater when firms receive a second-round letter, where information leakage is more likely (e.g., firms with high board member connectedness and higher dedicated institutional ownership) and when comment letters address more critical issues (e.g., the need to restate prior results or related party transactions). We also find that funds with high abnormal net selling in the private phase avoid significant future share price declines. In sum, we find consistent evidence that mutual funds appear to trade on information obtained during the private phase of the SEC comment letter process.
We examine the relation between public concern about immigration and customer complaints against minority financial advisors in the United States. We find that minority advisors are more likely to receive complaints in periods of high public concern about immigration than in other periods, relative to their white colleagues from the same firm, at the same office location, and at the same point in time. This result holds for both complaints with merit and dismissed complaints and is more pronounced in counties where residents likely hold stronger anti-immigration views. We also find that minority advisors are more likely to face regulatory actions or leave their firms after customer allegations in periods of high public concern about immigration than in other periods. Overall, our study provides descriptive evidence of a positive relation between public concern about immigration and customer dissatisfaction with minority advisors.
The mandated increase in segment disaggregation under SFAS 131 could have harmed shareholders by revealing proprietary information or benefited them by reducing agency problems. Using a sample of firms that lobbied against SFAS 131 on the grounds of competitive harm, I examine whether concerns about proprietary costs, a much-cited reason for nondisclosure, motivate firms to lobby against reporting mandates to protect firms’ competitive position or are used as an excuse to disguise managers’ self-interest. Consistent with the proprietary cost hypothesis, I find that these lobbying firms experienced a decrease in operating performance upon adoption of SFAS 131. I find similar results for nonlobbying firms whose industry associations voiced concern of competitive harm, suggesting that associations are motivated by member concerns to lobby in accounting standard setting. The effect is more pronounced for firms that were forced to increase the number of reportable segments to a greater extent. Moreover, the reduced operating performance arises from lower sales growth and smaller profit margins. These findings shed light on lobbying motives and suggest that concerns about the competitive harm of reporting mandates were warranted.
Although corporate insiders face substantial restrictions on stock sales, securing tax deductions through charitable donations of stock is viewed as an attractive alternative. Recent press coverage and growing empirical evidence confirm that insider donations occur frequently and often precede stock price drops. Securities regulators have also taken note, with a recent push for new rules to require rapid disclosure as with insider trades. This paper develops a model of informed stock trading when disposal of stock by insiders takes the form of tax-favored charitable donations rather than direct trading. We demonstrate that charitable gifts by insiders can reflect nonpublic information about firm value and that they do so in a manner that promotes greater market efficiency. Relative to informed trading, insider donations yield greater market liquidity, more efficient equity prices, and superior investor protection. The results suggest that although insider donations deserve scrutiny, they are not equivalent to insider trades. The results also provide a general framework to examine implications of insider donations for tax policy governing philanthropic behavior.
Mature internet advertising platforms offer high-level campaign management tools to help advertisers run their campaigns, often abstracting away the intricacies of how each ad is placed and focusing on aggregate metrics of interest to advertisers. On such platforms, advertisers often participate in auctions through a proxy bidder, so the standard incentive analyses that are common in the literature do not apply directly. In this paper, we take the perspective of a budget management system that surfaces aggregated incentives—instead of individual auctions—and compare first and second price auctions. We show that theory offers surprising endorsement for using a first price auction to sell individual impressions. In particular, first price auctions guarantee uniqueness of the steady-state equilibrium of the budget management system, monotonicity, and other desirable properties, as well as efficient computation through the solution to the well-studied Eisenberg–Gale convex program. Contrary to what one can expect from first price auctions, we show that incentives issues are not a barrier that undermines the system. Using realistic instances generated from data collected at real-world auction platforms, we show that bidders have small regret with respect to their optimal ex post strategy, and they do not have a big incentive to misreport when they can influence equilibria directly by giving inputs strategically. Finally, budget-constrained bidders, who have significant prevalence in real-world platforms, tend to have smaller regrets. Our computations indicate that bidder budgets, pacing multipliers, and regrets all have a positive association in statistical terms.
Price discrimination strategies, which offer different prices to customers based on differences in their valuations, have become common practice. Although it allows sellers to increase their profits, it also raises several concerns in terms of fairness (e.g., by charging higher prices (or denying access) to protected minorities in case they have higher (or lower) valuations than the general population). This topic has received extensive attention from media, industry, and regulatory agencies. In this paper, we consider the problem of setting prices for different groups under fairness constraints. We first propose four definitions: fairness in price, demand, consumer surplus, and no-purchase valuation. We prove that satisfying more than one of these fairness constraints is impossible even under simple settings. We then analyze the pricing strategy of a profit-maximizing seller and the impact of imposing fairness on the seller’s profit, consumer surplus, and social welfare. Under a linear demand model, we find that imposing a small amount of price fairness increases social welfare, whereas too much price fairness may result in a lower welfare relative to imposing no fairness. On the other hand, imposing fairness in demand or consumer surplus always decreases social welfare. Finally, no-purchase valuation fairness always increases social welfare. We observe similar patterns under several extensions and for other common demand models numerically. Our results and insights provide a first step in understanding the impact of imposing fairness in the context of discriminatory pricing.
We examine the impact of providing access to mobile savings accounts and improving financial management skills on the performance of microenterprises in Mozambique. The effects are highly heterogeneous: Combining both types of support is associated with a large increase in both short- and long-term firm profits and in financial security for female microentrepreneurs. This allowed female-headed microenterprises, particularly those with a higher level of profits at baseline, to close the gender profit gap in performance and skills relative to their male counterparts. The main drivers of improved business performance are improved financial management practices (bookkeeping), an increase in accessible savings, and reduced transfers to friends and relatives. Providing access to mobile money as a tool to save and manage finances also increases long-term profits of female microentrepreneurs, particularly for those with higher profits at baseline. However, neither treatment has any impact on male-led enterprises. Uncovering this heterogeneity in impact across different types of microenterprises can help improve the targeting of these interventions in the future.
This paper investigates the impact of pre-existing offline data on online learning in the context of dynamic pricing. We study a single-product dynamic pricing problem over a selling horizon of T periods. The demand in each period is determined by the price of the product according to a linear demand model with unknown parameters. We assume that before the start of the selling horizon, the seller already has some pre-existing offline data. The offline data set contains n samples, each of which is an input-output pair consisting of a historical price and an associated demand observation. The seller wants to use both the pre-existing offline data and the sequentially revealed online data to minimize the regret of the online learning process. We characterize the joint effect of the size, location, and dispersion of the offline data on the optimal regret of the online learning process. Specifically, the size, location, and dispersion of the offline data are measured by the number of historical samples, the distance between the average historical price and the optimal price, and the standard deviation of the historical prices, respectively. For both single-historical-price setting and multiple-historical-price setting, we design a learning algorithm based on the “Optimism in the Face of Uncertainty” principle, which strikes a balance between exploration and exploitation and achieves the optimal regret up to a logarithmic factor. Our results reveal surprising transformations of the optimal regret rate with respect to the size of the offline data, which we refer to as phase transitions. In addition, our results demonstrate that the location and dispersion of the offline data also have an intrinsic effect on the optimal regret, and we quantify this effect via the inverse-square law.
As cities debate how to regulate Airbnb and other home-sharing services, we study the impacts of home sharing on local residential real estate markets. By accommodating transient travelers with short-term rental properties, home-sharing platforms have evolved as a major alternative channel that attracts the growing supply of residential properties. However, on the demand side of local residential markets, home-sharing platforms are not a viable option for residents. To demonstrate this dynamic between home sharing and local residential markets, we leverage a unique quasi-experiment on Airbnb—a platform policy that caps the number of properties a host can manage in a city—and find that the policy reduced rents (in the long-term rental markets) and home values (in the for-sale housing markets) by about 3% and did not affect the price-to-rent ratio. Consistent with the conjecture, we find that the policy impacts can be attributed to increased supply in local residential markets because of the policy. Quantitatively, our estimates suggest that, if the density of affected Airbnb properties is 1% higher in a market, the policy may further decrease rents and home values by about 0.03%–0.06%, which is similar across each policy-affected city. Our empirical findings add to the debate about the impacts of home sharing on local residential markets with a novel data set and a unique identification strategy. Practically speaking, our research is a timely response to the debate on regulating home sharing and has implications for various stakeholders of the residential real estate markets.
A growing number of people today are participating in the gig economy, working as independent contractors on short-term projects. We study the effects of competition on gig workers’ effort and creativity on a Chinese novel-writing platform. Authors produce and sell their works chapter by chapter under a revenue-sharing or pay-by-the-word contract with the platform. Exploiting a regulation that induced a massive entry of novels in the romance genre but not other genres, we find that, on average, intensified competition led authors to produce content more quickly, whereas its effect on book novelty was weak. However, revenue-sharing books responded to competition substantially more than pay-by-the-word books, particularly regarding novelty. Moreover, the effect of competition on novelty is considerably stronger for books at earlier stages of the product life cycle. Finally, the platform increased the promotion of contracted books, which disproportionately favored pay-by-the-word books. We discuss the implications of these results for creative workers, platform firms, and policy makers in the gig economy.
Recent field experiments demonstrate that advice, mentorship, and feedback from randomly assigned peers improve entrepreneurial performance. These results raise a natural question: what is preventing entrepreneurs and managers from forming these peer connections themselves? We argue that entrepreneurs may be under-networked because they lack the necessary social skills—the ability to communicate effectively and interact collaboratively with new acquaintances—that allow them to match efficiently with knowledgeable peers. We use a field experiment in the context of a business training program in Togo to test if a short social skills training module increases the number and complementarity of peers that participants choose to learn from. We find that social skills training led entrepreneurs to match with 50% more peers and that more of those matches were based on complementary managerial skill. Finally, the training also increased entrepreneurs’ monthly profits by approximately 20%. Further analyses point to improvements in networking and advice as the drivers of performance improvements. Our findings suggest that social skills help entrepreneurs build relationships that create value for both themselves and their peers.
We compile a comprehensive data set of initial coin offerings (ICOs) from 19 data sources including 11 ICO aggregators. We alleviate severe limitations of available ICO data by performing the first systematic analysis of ICO data quality. We use our data set to study determinants of ICO funding success as well as post-ICO operating performance and provide evidence on some novel determinants of initial and longer-term ICO success. Finally, we show that post-ICO operating performance is positively associated with contemporaneous token returns and is generally negatively associated with token return volatility, suggesting that post-ICO operating performance has financial ramifications.
Prediction methods are often employed to estimate parameters of optimization models. Although the goal in an end-to-end framework is to achieve good performance on the subsequent optimization model, a formal understanding of the ways in which prediction methods can affect optimization performance is notably lacking. This paper identifies conditions on prediction methods that can guarantee good optimization performance. We provide two types of results: asymptotic guarantees under a well-known Fisher consistency criterion and nonasymptotic performance bounds under a more stringent criterion. We use these results to analyze optimization performance for several existing prediction methods and show that in certain settings, methods tailored to the optimization problem can fail to guarantee good performance. Conversely, optimization-agnostic methods can sometimes, surprisingly, have good guarantees. In a computational study on portfolio optimization, fractional knapsack, and multiclass classification problems, we compare the optimization performance of several prediction methods. We demonstrate that lack of Fisher consistency of the prediction method can indeed have a detrimental effect on performance.
We consider a two-sided streaming service platform that generates revenues by charging users a subscription fee for unlimited access to the content and compensates content providers (artists) through a revenue-sharing allocation rule. Platform users are heterogeneous in both their overall consumption and the distribution of their consumption over different artists. We study two primary revenue allocation rules used by market-leading music streaming platforms—pro-rata and user-centric. With pro-rata, artists are paid proportionally to their share of the overall streaming volume, whereas with user-centric, each user’s subscription fee is divided proportionally among artists based on the consumption of that user. We characterize when these two allocation rules can sustain a set of artists on the platform and compare them from both the platform’s and the artists’ perspectives. In particular, we show that, despite the cross-subsidization between low- and high-streaming-volume users, the pro-rata rule can be preferred by both the platform and the artists. Furthermore, the platform’s problem of selecting an optimal portfolio of artists is NP-complete. However, by establishing connections to the knapsack problem, we develop a polynomial time approximation scheme (PTAS) for the optimal platform’s profit. In addition to determining the platform’s optimal revenue allocation rule in the class of pro-rata and user-centric rules, we consider the optimal revenue allocation rule in the class of arbitrary rules. Building on duality theory, we develop a polynomial time algorithm that outputs a set of artists so that the platform’s profit is within a single artist’s revenue from the optimal profit.
Medicare does not pay for a skilled nursing facility (SNF) unless a fee-for-service patient has stayed in the hospital for at least three days. This Medicare reimbursement rule, or the “three-day rule,” provides full coverage for the first 20 days and partial coverage for days 21–100 for skilled nursing care provided at any Centers for Medicare and Medicaid Services-approved SNF. In this paper, we study how this Medicare reimbursement rule affects patient routing to SNFs and whether an SNF discharge reduces patients’ 30-day hospital readmission rates. Data analysis shows that Medicare patients are more likely to be discharged to an SNF rather than home after the three-day cutoff, and SNF discharges increase hospital readmission rates for Medicare day 3 patients. This perverse effect is driven by infection-related readmissions and is more likely to occur when local SNFs have lower occupancy rates and higher deficiency citations than the median SNF of the same state-year. Back-of-the-envelope calculation suggests that the three-day rule may have generated an extra Medicare cost of $71 million to $345 million per year due to the overuse of SNFs and the subsequent rise in hospital readmissions. Replacing the three-day rule with a machine-learning algorithm mimicking private insurers would help.
Organizations can learn from prior successes and failures to improve organizational performance. Few learning-curve studies have investigated this phenomenon at the individual level. A notable exception found that surgeons learn from their own success and others’ failure. Success in surgery is common and individually independent from other surgeries. We study learning from success and failure in a context where success is rare and competitive: Formula One (F1) racing. Only one driver will win a race, preventing the other competitors from winning. Even severe failures causing drivers to abandon the race are common. We investigate two types of abandonments: car failures and driver failures. Our data set covers F1 from the start of F1 in 1950 through 2017, yielding 21,487 driver-race observations. We find that win probability follows an inverted U-shaped function of racing experience. We also find that drivers learn from their own success, teammates’ success, as well as own car failures. However, drivers do not learn from their own driver failures. A teammate’s win increases the probability of winning the next race by 1.8%. An own car failure increases the probability of winning the next race by 1.9%. We use two characteristics of success, frequency and competitiveness, to define a spectrum of organizational settings. Placement of our F1 findings and the surgery findings on this spectrum reveals when managers can expect benefits from their own versus others’ success and failure.
Firms often engage in price promotion wars to gain market share from their competitors. However, poor customer satisfaction as a result of limited service capacity may significantly impact such a pricing strategy. In this paper, we consider a two-firm price competition model in which customers’ purchase decisions are affected by their anticipation of a poor service encounter. Our equilibrium analysis reveals that firms would be less aggressive in engaging in price cutting when customers care more about service quality and when service capacity is relatively low. Interestingly, when service capacity is close (but not exact) to covering one half of the total market demand, firms would adopt a mixed strategy with randomized pricing, driven by unilateral motives to either capture more market share (by lowering prices) or increase profit margin (by raising prices). We further show that having a superior service capacity presents a competitive advantage for a firm and such advantage can be preemptive. In an extended two-period model that allows for customer switching after a poor service encounter, we find that when service capacity is relatively low, firms may offer deeper price discounts in the first period if customers are forward looking than if they are myopic. Our numerical study confirms that the main qualitative insights obtained in our base model continue to hold when the customer switching behavior is considered.
When multiple retailers hold inventory to satisfy random demand, retailer inventory-sharing strategies can potentially reduce the supply-demand mismatch and increase overall supply chain performance. In this paper, we experimentally investigate alternative inventory-sharing strategies in a two-tier supply chain with an upstream manufacturer and two downstream retailers. In one setting, retailers act as if they are centralized and use a single quantity to fulfill joint demand. In the other, retailers are decentralized and face separate demands, but they can transfer inventory after demands are realized. In this latter decentralized scenario, we also consider whether the manufacturer or retailers have decision authority over the inventory transfer price. One key result is that when the retailers are decentralized and the manufacturer sets the transfer price, both retailers and the manufacturer earn higher profits than in the centralized retailer strategy, which runs counter to theory. We also find that when retailers are decentralized and set their own transfer price, the most equitable distribution of profits is achieved. In an effort to account for these results, we find that a model of fairness captures decisions well. Overall, by investigating how different inventory-sharing strategies affect the distribution of profits in a two-tier supply chain, our results provide guidance to firms considering how, if at all, they should enter such arrangements.
This paper explores how firms that lack expertise in machine learning (ML) can leverage the so-called AI Flywheel effect. This effect designates a virtuous cycle by which as an ML product is adopted and new user data are fed back to the algorithm, the product improves, enabling further adoptions. However, managing this feedback loop is difficult, especially when the algorithm is contracted out. Indeed, the additional data that the AI Flywheel effect generates may change the provider’s incentives to improve the algorithm over time. We formalize this problem in a simple two-period moral hazard framework that captures the main dynamics among ML, data acquisition, pricing, and contracting. We find that the firm’s decisions crucially depend on how the amount of data on which the machine is trained interacts with the provider’s effort. If this effort has a more (less) significant impact on accuracy for larger volumes of data, the firm underprices (overprices) the product. Interestingly, these distortions sometimes improve social welfare, which accounts for the customer surplus and profits of both the firm and provider. Further, the interaction between incentive issues and the positive externalities of the AI Flywheel effect has important implications for the firm’s data collection strategy. In particular, the firm can boost its profit by increasing the product’s capacity to acquire usage data only up to a certain level. If the product collects too much data per user, the firm’s profit may actually decrease (i.e., more data are not necessarily better).
The U.S. K–12 public education system has been notoriously hard to improve. Some argue new education technologies (EdTech) can help transform schools for the better. Yet, as large-scale policy reforms have had only limited success, it seems unlikely that small changes from EdTech could have any measurable impact. In this paper, we study DonorsChoose, a nonprofit that operates a teacher crowdfunding platform. We ask whether DonorsChoose improves educational outcomes, specifically at low-income schools. Combining DonorsChoose data with data on student test scores in Pennsylvania from 2012–2013 to 2017–2018, we find that an increase in the number of DonorsChoose projects funded at a school leads to higher student performance, after controlling for selection biases. For a school with zero funded projects, one funded project—of about $400 in value—translates to between two to nine more students scoring basic and above in all subjects in high school and science and language arts in primary and middle school. We find this effect is driven mostly by low-income schools, indicating funded projects help close the gap in educational outcomes between students at low- versus high-income schools. Based on a textual analysis of 20,000 statements from all funded teachers describing how project resources are used, we find two channels of improvement most effective in the lowest income schools. We demonstrate that, although DonorsChoose projects are small, they improve outcomes and reduce inequality because they come directly from frontline workers—teachers—who know most intimately the obstacles their students face and how to help.
In this paper, we investigate the demand response of a firm’s existing customers to retail store entry and which aspects of the response are demand-expanding and which cannibalize online sales. The empirical goal of the paper is to separately identify the effects of customer-to-store distance on purchase frequency, channel choice, and expenditure per purchase, using transaction-level data from a multichannel apparel brand. Our identification strategy exploits within-customer variation in distance resulting from store entry during a period of rapid retail expansion. We establish retail distance effects using descriptive regressions before developing a unified structural model that affords rich counterfactual analyses and further controls for product category preferences. We find material effects of decreasing retail store distance on purchase frequency and retail channel choice but not expenditures per purchase. Our structural model ascribes mechanisms to these effects in the form of increased brand consideration, higher retail utility from nonmonetary factors (e.g., reduced driving times), and infungibility of monetary transportation costs with budgets for apparel. Our estimates imply that a 10% reduction in retail store distance increases retail channel expenditures by 1.9% and decreases online channel expenditures by 1.2%, resulting in a 0.4% increase in total expenditures. Through counterfactual experiments, we demonstrate that retail expansion can ultimately limit the ability of the firm to price discriminate across channels because reducing transportation costs weakens the firm’s ability to enforce channel-based segmentation schemes.
We investigate how historical price information (e.g., accessed through price trackers) influences consumers’ purchase decisions and thus affects a firm’s dynamic pricing strategy. We first show that when consumers with heterogeneous tastes are not informed about historical prices, the monopolist charges a high regular price for most of the time and periodically holds low-price sales. Then we consider the case in which a small fraction of consumers (such as price tracker users) become informed of historical prices. At the new equilibrium, the monopolist lowers the regular price and advances sales, implying shorter price cycles, more frequent sales, and a positive spillover effect of price tracker users’ informational advantage on the rest of uninformed consumers. We conclude with a discussion of the impact of price trackers on firms and other relevant managerial implications of the model.
We examine how freemium platforms can design social referral programs to encourage growth and engagement without sacrificing revenue. On the one hand, social referral programs generate new referrals from users who would not have paid for the premium features. On the other hand, they also attract new referrals from users who would have paid but prefer to invite others, resulting in more referrals but fewer paying users. We use data from a large-scale randomized field experiment in an online dating platform to assess the effects of adding referrals programs to freemium platforms and changing the referral requirements on users’ behavior, namely, on their decisions to invite, pay, and engage with the platform. We find that introducing referral programs in freemium platforms can significantly contribute to increasing the number of referrals at the expense of revenue. Platforms can avoid the loss in revenue by reserving some premium features exclusively for paying users. We also find that increasing referral requirements in social referral programs can work as a double-edged sword. Increasing the referral threshold results in more referrals and higher total revenue. Yet these benefits appear to come at a cost. Users become less engaged, decreasing the value of the platform for all users. We explore two mechanisms that help to explain the differences in users’ social engagement. Finally, and contrary to prior findings, we find that the quality of the referrals is not affected by the referral requirements. We discuss the theoretical and practical implications of our research.
Existing research on word-of-mouth considers various descriptive statistics of rating distributions, such as the mean, variance, skewness, kurtosis, and even entropy and the Herfindahl-Hirschman index. But real-world consumer decisions are often derived from visual assessment of displayed rating distributions in the form of histograms. In this study, we argue that such distribution charts may inadvertently lead to a consumer-choice bias that we call the histogram distortion bias (HDB). We propose that salient features of distributions in visual decision making may mislead consumers and result in inferior decision making. In an illustrative model, we derive a measure of the HDB. We show that with the HDB, consumers may make choices that violate well-accepted decision rules. In a series of experiments, subjects are observed to prefer products with a higher HDB despite a lower average rating. They could also violate widely accepted modeling assumptions, such as branch independence and first-order stochastic dominance.
Global shocks bring unanticipated changes in the business environment of foreign multinational enterprises (MNEs) and rival domestic firms. We examine whether there is a difference between how MNEs and domestic firms react in heterogeneous local or subnational markets to a global demand shock. Leveraging the 2009–2010 H1N1 influenza pandemic as a source of exogenous variation in global demand for influenza vaccines, we investigate the role of subnational heterogeneity in economic resources, industry infrastructure, and political alignment within an emerging economy on the behavior of incumbent MNEs and rival domestic firms. We find that following the pandemic, MNE market share in the influenza vaccine market relative to the noninfluenza vaccine markets declines more in regions with lower government health spending per capita and also, in regions unaligned with the federal government. Additional analyses suggest that these changes in market share are not caused by a reduction in MNE revenues. Rather, they are caused by domestic firms that were already present in noninfluenza vaccine markets diversifying by entering the highly related influenza vaccine market. Finally, a granular examination of the differential responses reveals that such responses are not related to preshock differences in regional coverage of MNEs and domestic firms. This study contributes to the extant literature by suggesting that the direct costs or opportunity costs of new market and region entry are relatively greater for MNEs than for domestic firms, particularly in regions that have inadequate health infrastructure and are politically not aligned.
Innovation is important for firm performance and broader economic growth. However, breakthrough innovations necessarily require greater risk taking than more incremental approaches. To understand how managers respond to uncertainty when making research and development decisions, we conducted experiments with master’s degree students in a program focused on the intersection of business and technology. Study participants were asked to choose whether to fund hypothetical research projects using a process that mirrors real-world research and development funding decisions. The experiments provided financial rewards that disproportionately encouraged the choice of higher-risk projects. Despite these incentives, most participants chose lower-risk projects at the expense of projects more likely to generate a large payoff. Heterogeneity analysis and additional experimental treatments show that individual risk preferences predict greater tolerance of high-risk projects and suggest that more appropriate decision making can be learned. Thus, for firms seeking to fund breakthrough research and development, appropriate screening and training of employees may play important roles in increasing the likelihood of success.
We use a unique feature of California’s property tax system to empirically identify the causal effect of selling homeowners’ past property tax payments on their choice of listing price. Although past property taxes are sunk costs, we find that they have a significant positive effect on the sellers’ choice of listing price, which is inconsistent with rational models of decision making. This effect is stronger when sellers expect to sell at a loss relative to their purchase price and for properties whose value is harder to assess. The effect of property taxes on listing price is mostly transmitted to the selling price, which is consistent with the idea that buyers use listing prices as anchors to assess property values. Overall, our results suggest that sunk costs affect prices in the housing market.
We examine the consequences of a regulatory intervention aimed at generalizing tenure voting in French public companies. The 2014 Florange Act departs from the ‘one share one vote’ principle by automatically granting double-voting rights (DVR) to shares held for at least two years. However, firms can opt out through an annual meeting vote. We document three main findings. First, firms that adopt DVR by default experience a decrease in long-term foreign institutional ownership offset by an increase in insider/family ownership. Second, those firms significantly underperform in terms of stock returns after Florange relative to those that reject DVR. Third, their environmental and social performance deteriorates. Collectively, our evidence casts doubt on the merit of regulation-induced tenure voting as a desirable corporate governance mechanism.
Researchers have often attributed discrete messages such as ratings to a difference in preferences between sender and receiver. By extending a standard model of information transmission, we show that discreteness can also arise when preferences are identical but misinterpretation is possible. Whereas discrete messages are less precise, they are easier to interpret. We provide predictions for the distribution of ratings. If we believe that an observed distribution results from cooperative behavior, the model provides a method for inferring the objectives of the sender and receiver. Ratings inflation and deflation arise as emergent properties of an optimal distribution.
I study whether industry employment of active regulators weakens oversight. To examine this question, I exploit that the Financial Reporting Enforcement Panel (FREP), the German capital-market regulator responsible for enforcing public firms’ compliance with accounting standards, allows its senior regulators to serve on boards of public firms during their FREP tenure. I find that firms are less likely to face enforcement actions after they appoint active regulators to their board. After such an appointment, firms are more likely to receive a qualified audit opinion, more likely to have an above-normal risk of accounting manipulation, as measured by an F-score greater than one, and exhibit higher income-increasing abnormal accruals. These findings suggest that directorships of active regulators can result in conflicts of interest that weaken oversight.
Modern communication technologies enable efficient exchange of information but often sacrifice direct human interaction inherent in more traditional forms of communication. This raises the question of whether the lack of personal interaction induces individuals to exploit informational asymmetries. We conducted two experiments with a total of 848 subjects to examine how human versus machine interaction influences cheating for financial gain. We find that individuals cheat about three times more when they interact with a machine rather than a person, regardless of whether the machine is equipped with human features. When interacting with a human, individuals are particularly reluctant to report unlikely and therefore, suspicious outcomes, which is consistent with social image concerns. The second experiment shows that dishonest individuals prefer to interact with a machine when facing an opportunity to cheat. Our results suggest that human presence is key to mitigating dishonest behavior and that self-selection into communication channels can be used to screen for dishonest people.
Conventional optimization algorithms that prescribe order packing instructions (which items to pack in which sequence in which box) focus on box volume utilization yet tend to overlook human behavioral deviations. We observe that packing workers at the warehouses of the Alibaba Group deviate from algorithmic prescriptions for 5.8% of packages, and these deviations increase packing time and reduce operational efficiency. We posit two mechanisms and demonstrate that they result in two types of deviations: (1) information deviations stem from workers having more information and in turn better solutions than the algorithm; and (2) complexity deviations result from workers’ aversion, inability, or discretion to precisely implement algorithmic prescriptions. We propose a new “human-centric bin packing algorithm” that anticipates and incorporates human deviations to reduce deviations and improve performance. It predicts when workers are more likely to switch to larger boxes using machine learning techniques and then proactively adjusts the algorithmic prescriptions of those “targeted packages.” We conducted a large-scale randomized field experiment with the Alibaba Group. Orders were randomly assigned to either the new algorithm (treatment group) or Alibaba’s original algorithm (control group). Our field experiment results show that our new algorithm lowers the rate of switching to larger boxes from 29.5% to 23.8% for targeted packages and reduces the average packing time of targeted packages by 4.5%. This idea of incorporating human deviations to improve optimization algorithms could also be generalized to other processes in logistics and operations.
Advertising is often criticized for presenting only partial or selective information about products. This criticism is particularly pronounced for health products, where large asymmetries in information may exist between consumers and firms. This paper explores how government restrictions designed to prevent selective advertising affect the types of information to which consumers are exposed. We exploit a natural experiment in the form of a U.S. Food and Drug Administration (FDA) crackdown that prevented pharmaceutical companies from using selectively chosen information in their Internet search ads. Because companies could not adequately document side effects within the advertising space allowed, they removed their ads. Our results suggest that, after the ads were removed, consumers were more likely to seek information from websites based on user-generated content or websites that focused on medical treatments not regulated by the FDA, such as Canadian pharmacies and sites promoting herbal remedies.
This paper investigates empirically the effect of market power on dynamic pricing in the presence of inventories. Our setting is the auto retail industry; we analyze how automotive dealerships adjust prices to inventory levels under varying degrees of market power. We first establish that inventory fluctuations create scarcity rents for cars that are in short supply. We then show that dealers’ ability to adjust prices in response to inventory depends on their market power, that is, the quantity of substitute inventory in their selling area. Specifically, we show that the slope of the price–inventory relationship (higher inventory lowers prices) is significantly steeper when dealers find themselves in a situation of high rather than low market power. A dealership with high market power moving from a situation of inventory shortage to a median inventory level lowers transaction prices by about 0.57% ceteris paribus, corresponding to 32.5% of dealers’ average per-vehicle profit margin or $145.6 on the average car. Conversely, when competition is more intense, moving from inventory shortage to a median inventory level lowers transaction prices by about 0.35% ceteris paribus, corresponding to 20.2% of dealers’ average per-vehicle profit margin or $90.9. To our knowledge, we are the first to empirically show that market power affects firms’ ability to dynamically price.
A well-known principle in economics is that firms differentiate their product offerings in order to relax competition. However, in this paper we show that information frictions can invalidate this principle. We build a duopolistic competition model of second-degree price discrimination with information frictions in which (i) an equilibrium always exists with overlapping product qualities, whereas (ii) an equilibrium with nonoverlapping product qualities exists only if both information frictions and the cost of providing high quality are sufficiently small. As a consequence, reasons other than an attempt to soften competition should explain why firms in some cases carry nonoverlapping product lines.
Hospital and healthcare administrators name high prescription drug costs as one of their largest problems. A significant body of research demonstrates that meals and honoraria from pharmaceutical firms to physicians leads to higher prescribing of expensive, brand name drugs, despite little difference in efficacy. Some administrators and scholars have advocated for mandatory disclosure of these payments in order to reduce this conflict of interest, but many practitioners believe disclosure has little effect on prescribing, and the empirical evidence is mixed. This paper uses a quasi-experiment of a 2009 payment disclosure policy in Massachusetts to estimate the causal impact of public disclosure on prescribing. The comprehensive data set includes all retail prescriptions for 262 drugs in nine drug classes written by 5,730 physicians in five states over 48 months. We show a significant postdisclosure reduction in brand name drug prescriptions by Massachusetts physicians, relative to control physicians in other states. These effects are driven by heavy prescribers of brand name drugs in the prepolicy period, particularly for drugs with large prepolicy sales forces. Effects are also detected before the first data were released, implying that the effects are not because patients or administrators responded to the disclosed payments. Instead, some physicians may have changed their payments and prescriptions behavior to avoid appearing biased. Taken in tandem with the many studies showing that pharmaceutical industry payments influence prescribing, this study suggests a strong role for mandatory public disclosure in reducing conflicts of interest in medicine and costly prescribing of brand name drugs.
We study the bundle size pricing (BSP) problem in which a monopolist sells bundles of products to customers and the price of each bundle depends only on the size (number of items) of the bundle. Although this pricing mechanism is attractive in practice, finding optimal bundle prices is difficult because it involves characterizing distributions of the maximum partial sums of order statistics. In this paper, we propose to solve the BSP problem under a discrete choice model using only the first and second moments of customer valuations. Correlations between valuations of bundles are captured by the covariance matrix. We show that the BSP problem under this model is convex and can be efficiently solved using off-the-shelf solvers. Our approach is flexible in optimizing prices for any given bundle size. Numerical results show that it performs very well compared with state-of-the-art heuristics. This provides a unified and efficient approach to solve the BSP problem under various distributions and dimensions.
This paper studies the persistent effects of short-term peer exposure on long-run performance in a college setting. I exploit the random assignment of undergraduates to peer groups during a mandatory orientation week and track the students’ performance over four years (until graduation). Assignment to orientation week groups with high levels of peer ability is associated with lower performance during the first year at college and a higher probability of early dropout. These adverse effects are driven entirely by the exposure of low-ability students to high-ability peers. Beyond the first year, exposure to higher peer ability during the orientation week negatively affects selection into the college’s most popular major (business administration) and final grade point average. Taken together, the findings suggest that the composition of short-term peer groups matters for individual choices and long-run performance outcomes.
This paper studies how firms restructure their relational contracts in the face of permanent shocks to the value of their relationships. In the context of the U.S. airline industry, we argue that major carriers enter self-enforcing agreements with their outsourced regional partners because a key aspect of airline operations—the exchange of landing slots under adverse weather—is formally noncontractible. We show empirically that major and regional airlines did not terminate their relational contracts after the 2008 crisis but rather, restructured the scope of such contracts in a way that restored their credibility. In particular, we show that a major airline was less likely to continue outsourcing a route to a regional partner after the 2008 crisis the lower the present discounted value of their preexisting relationship and hence, the larger the negative effect of the crisis on the relational contract’s “self-enforcing range.”
Social movements have the potential to effect change in strategic decision making. In this paper, we examine whether the #MeToo movement, spurred by the Harvey Weinstein scandal, leads to changes in the likelihood of Hollywood producers working with female writers on new movie projects. Because #MeToo affected the entire industry, we use variation in whether producers had past collaborations with Weinstein to investigate whether and how #MeToo may spur change. We find that producers previously associated with Weinstein are, on average, about 35% more likely to work with female writers after the scandal than they were before, relative to nonassociated producers, and the size of this effect increases with the intensity of the association. Female producers are the main drivers of our results, perhaps because they are more likely than male producers to resonate with the movement’s cause and face relatively low costs of enacting change. Changes made by other groups, such as production teams with the most intense association with Weinstein and less experienced all-male teams, may be better explained by motivations to mitigate risk. We also find that producers do not sacrifice writer experience by hiring more female writers and that both experienced and novice female writers have benefited from the increased demand. Our study shows that social movements that seek to address gender inequality can, indeed, lead to meaningful change. It also provides perspective for thinking about whether, and to what extent, changes may occur in broader settings.
The most commonly cited issues with mobile apps are low user engagement and retention levels. In this paper, we use a randomized control trial to test the efficacy of crowdsourcing on enhancing user engagement and retention in the context of mobile gaming apps. We examine two specific crowdsourcing features: the ability to submit content and the ability to access crowdsourced content. We find that the content submission significantly increases engagement and retention by reducing users’ hazard of ending a session by approximately 11% relative to the baseline and reducing the hazard of abandoning the game app by 14%. In contrast, giving users the ability to access crowdsourced content has no significant effect on engagement but has a positive effect on retention by reducing the hazard of abandoning the game app by 13%. Surprisingly, we find that the interaction effect of these two crowdsourced features is negative on user engagement. Individually, the submission feature manifests itself via empowering users to control their product use experience, whereas the access feature’s positive effect on retention is mediated by diversity and novelty of content. However, the two effects are not complementary. It turns out when these two features are given together, the empowerment enabled by one’s own submission is crowded out by others’ submissions, and this dominates the diversity benefit. Crowdsourcing features have heterogeneous impact on different user segments, with heavy users and users of longer tenure being more affected by the crowdsourcing features.
We compare non-GAAP earnings per share (EPS) in firms’ annual earnings announcements and proxy statements using hand-collected data from U.S. Securities and Exchange Commission filings. We find that proxies for capital market incentives (contracting incentives) are more highly associated with firms’ disclosure of non-GAAP EPS in annual earnings announcements (proxy statements). However, we find systematic differences in the properties of firms’ non-GAAP earnings and exclusions depending on whether they disclose non-GAAP EPS in both the earnings announcement and the proxy statement. When firms disclose non-GAAP EPS in both documents, we find that non-GAAP EPS is more useful for assessing firm value. Specifically, these firms are more likely to: (1) exclude nonrecurring items, (2) exclude less persistent earnings components, and (3) provide less aggressive non-GAAP EPS. Our results suggest that non-GAAP EPS is higher in quality for investors when disclosed in both the annual earnings announcement and the proxy statement. We provide some of the first large-sample evidence consistent with the use of non-GAAP EPS metrics in both financial reporting and compensation contracting.
This study examines the effects of jurisdictions’ corporate taxes and other policies on firms’ headquarters (HQ) location decisions. Using changes in state corporate income tax rates across time and states as the setting, we find that a one-percentage-point increase in the HQ state corporate income tax rate increases the likelihood of firms relocating their HQ out of the state by 16.8%, and an equivalent decrease in the HQ state rate decreases the likelihood of HQ relocations by 9.1%. Exploiting the unique tax policy features within the state apportionment system lends strong support to the interpretation that taxation drives this effect. Our analyses also demonstrate that state income tax features affect the destination of the HQ move. We contribute to the literature on corporate decision making by showing how state income taxation affects a real corporate decision that has significant economic consequences for the company and the state.
Prior literature demonstrates that increased trading activity of a firm’s stock is associated with abnormal future stock returns (the high-volume return premium) and interprets this phenomenon as evidence that increased visibility generates reductions in cost of capital. Motivated by this interpretation, we investigate whether increased trading activity entails changes in real corporate actions. We document a positive relation between abnormal trading volume, future investment expenditures, and financing cash flows. This positive relation is not subsumed by the arrival of investment-related news or other corporate disclosures or by subsequent earnings information and is concentrated among firms with high financial constraints and firms with lower levels of investor recognition.
This paper investigates the association of corporate reporting and executive network centrality, which measures an executive’s relative position in a massive network consisting of outside corporate leaders. I find that high-centrality chief executive officers (CEOs) and chief financial officers (CFOs) are generally more likely to engage in financial misreporting than low-centrality CEOs and CFOs. I also find that the influence of CFO network centrality is greater than that of CEOs in financial misreporting. Further analyses show that the monitoring effect of internal governance mechanisms on high-centrality executives is very limited and that the discipline of the managerial labor market is weaker for high-centrality CFOs as well. My results hold for a subsample subject to exogenous shocks to CFO connectedness and are robust to a series of alternative specifications including using CFO fixed effects. Taken together, my findings suggest that corporate reporting can be influenced by executives’ social network position, with high-centrality CFOs using their social power to make adverse corporate reporting decisions to gain personal benefits.
To capture the dynamics of idiosyncratic volatility of stock returns over different horizons and investigate the relationship between idiosyncratic volatility and expected stock returns, this paper develops and estimates a parsimonious model of idiosyncratic volatility consisting of a short-run and a long-run component. The conditional short-run and long-run components are found to be positively and negatively related to expected stock returns, respectively. The positive relation between the short-run component and stock returns may be caused by investors requiring compensation for bearing idiosyncratic volatility risk when facing trading frictions and hold underdiversified portfolios. The negative relationship between the long-run component and stock returns may reflect the fact that stocks with high long-run idiosyncratic volatility are less exposed to systematic risk factors and, hence, earn lower returns. Moreover, the low-risk exposure of stocks characterized by high idiosyncratic volatility lends support to real-option-based mechanisms to explain this negative relation. In particular, the systematic risk of a firm with abundant growth options crucially depends upon the risk exposure of these options. The value of growth options could rise significantly because of convexity when the increase in idiosyncratic volatility occurs over long horizons. And growth options’ systematic risk could fall because the relative magnitude of their value in relation to systematic risk factors decreases.
The editors of Management Science acknowledge all our 2021 reviewers and guest associate editors who generously provided expert counsel and guidance on a voluntary basis. We are grateful for their contributions; without them, the journal could not function. Here, we list those reviewers who contributed four or more reviews in 2021.
Optimal stopping is the problem of deciding when to stop a stochastic system to obtain the greatest reward, arising in numerous application areas such as finance, healthcare, and marketing. State-of-the-art methods for high-dimensional optimal stopping involve approximating the value function or the continuation value and then using that approximation within a greedy policy. Although such policies can perform very well, they are generally not guaranteed to be interpretable; that is, a decision maker may not be able to easily see the link between the current system state and the policy’s action. In this paper, we propose a new approach to optimal stopping wherein the policy is represented as a binary tree, in the spirit of naturally interpretable tree models commonly used in machine learning. We show that the class of tree policies is rich enough to approximate the optimal policy. We formulate the problem of learning such policies from observed trajectories of the stochastic system as a sample average approximation (SAA) problem. We prove that the SAA problem converges under mild conditions as the sample size increases but that, computationally, even immediate simplifications of the SAA problem are theoretically intractable. We thus propose a tractable heuristic for approximately solving the SAA problem by greedily constructing the tree from the top down. We demonstrate the value of our approach by applying it to the canonical problem of option pricing, using both synthetic instances and instances using real Standard & Poor’s 500 Index data. Our method obtains policies that (1) outperform state-of-the-art noninterpretable methods, based on simulation regression and martingale duality, and (2) possess a remarkably simple and intuitive structure.
Many real-world optimization problems have input parameters estimated from data whose inherent imprecision can lead to fragile solutions that may impede desired objectives and/or render constraints infeasible. We propose a joint estimation and robustness optimization (JERO) framework to mitigate estimation uncertainty in optimization problems by seamlessly incorporating both the parameter estimation procedure and the optimization problem. Toward that end, we construct an uncertainty set that incorporates all of the data, and the size of the uncertainty set is based on how well the parameters are estimated from that data when using a particular estimation procedure: regressions, the least absolute shrinkage and selection operator, and maximum likelihood estimation (among others). The JERO model maximizes the uncertainty set’s size and so obtains solutions that—unlike those derived from models dedicated strictly to robust optimization—are immune to parameter perturbations that would violate constraints or lead to objective function values exceeding their desired levels. We describe several applications and provide explicit formulations of the JERO framework for a variety of estimation procedures. To solve the JERO models with exponential cones, we develop a second-order conic approximation that limits errors beyond an operating range; with this approach, we can use state-of-the-art second-order conic programming solvers to solve even large-scale convex optimization problems.
We introduce data-driven decision-making algorithms that achieve state-of-the-art dynamic regret bounds for a collection of nonstationary stochastic bandit settings. These settings capture applications such as advertisement allocation, dynamic pricing, and traffic network routing in changing environments. We show how the difficulty posed by the (unknown a priori and possibly adversarial) nonstationarity can be overcome by an unconventional marriage between stochastic and adversarial bandit learning algorithms. Beginning with the linear bandit setting, we design and analyze a sliding window-upper confidence bound algorithm that achieves the optimal dynamic regret bound when the underlying variation budget is known. This budget quantifies the total amount of temporal variation of the latent environments. Boosted by the novel bandit-over-bandit framework that adapts to the latent changes, our algorithm can further enjoy nearly optimal dynamic regret bounds in a (surprisingly) parameter-free manner. We extend our results to other related bandit problems, namely the multiarmed bandit, generalized linear bandit, and combinatorial semibandit settings, which model a variety of operations research applications. In addition to the classical exploration-exploitation trade-off, our algorithms leverage the power of the “forgetting principle” in the learning processes, which is vital in changing environments. Extensive numerical experiments with synthetic datasets and a dataset of an online auto-loan company during the severe acute respiratory syndrome (SARS) epidemic period demonstrate that our proposed algorithms achieve superior performance compared with existing algorithms.
When trying to maximize the adoption of a behavior in a population connected by a social network, it is common to strategize about where in the network to seed the behavior, often with an element of randomness. Selecting seeds uniformly at random is a basic but compelling strategy in that it distributes seeds broadly throughout the network. A more sophisticated stochastic strategy, one-hop targeting, is to select random network neighbors of random individuals; this exploits a version of the friendship paradox, whereby the friend of a random individual is expected to have more friends than a random individual, with the hope that seeding a behavior at more connected individuals leads to more adoption. Many seeding strategies have been proposed, but empirical evaluations have demanded large field experiments designed specifically for this purpose and have yielded relatively imprecise comparisons of strategies. Here we show how stochastic seeding strategies can be evaluated more efficiently in such experiments, how they can be evaluated “off-policy” using existing data arising from experiments designed for other purposes, and how to design more efficient experiments. In particular, we consider contrasts between stochastic seeding strategies and analyze nonparametric estimators adapted from policy evaluation and importance sampling. We use simulations on real networks to show that the proposed estimators and designs can substantially increase precision while yielding valid inference. We then apply our proposed estimators to two field experiments, one that assigned households to an intensive marketing intervention and one that assigned students to an antibullying intervention.
Personalized marketing in retail requires a model to predict how different marketing actions affect product choices by individual customers. Large retailers often handle millions of transactions daily, involving thousands of products in hundreds of categories. Product choice models thus need to scale to large product assortments and customer bases, without extensive product attribute information. To address these challenges, we propose a custom deep neural network model. The model incorporates bottleneck layers to encode cross-product relationships, calibrates time-series filters to capture purchase dynamics for products with different interpurchase times, and relies on weight sharing between the products to improve convergence and scale to large assortments. The model applies to loyalty card transaction data without predefined categories or product attributes to predict customer-specific purchase probabilities in response to marketing actions. In a simulation, the proposed product choice model predicts purchase decisions better than baseline methods by adjusting the predicted probabilities for the effects of recent purchases and price discounts. The improved predictions lead to substantially higher revenue gains in a simulated coupon personalization problem. We verify predictive performance using transaction data from a large retailer with experimental variation in price discounts.
We study the problem of learning shared structure across a sequence of dynamic pricing experiments for related products. We consider a practical formulation in which the unknown demand parameters for each product come from an unknown distribution (prior) that is shared across products. We then propose a meta dynamic pricing algorithm that learns this prior online while solving a sequence of Thompson sampling pricing experiments (each with horizon T) for N different products. Our algorithm addresses two challenges: (i) balancing the need to learn the prior (meta-exploration) with the need to leverage the estimated prior to achieve good performance (meta-exploitation) and (ii) accounting for uncertainty in the estimated prior by appropriately “widening” the estimated prior as a function of its estimation error. We introduce a novel prior alignment technique to analyze the regret of Thompson sampling with a misspecified prior, which may be of independent interest. Unlike prior-independent approaches, our algorithm’s meta regret grows sublinearly in N, demonstrating that the price of an unknown prior in Thompson sampling can be negligible in experiment-rich environments (large N). Numerical experiments on synthetic and real auto loan data demonstrate that our algorithm significantly speeds up learning compared with prior-independent algorithms.
Clinical pathways outline standardized processes in the delivery of care for a specific disease. Patient journeys through the healthcare system, however, can deviate substantially from these pathways. Given the positive benefits of clinical pathways, it is important to measure the concordance of patient pathways so that variations in health system performance or bottlenecks in the delivery of care can be detected, monitored, and acted upon. This paper proposes the first data-driven inverse optimization approach to measuring pathway concordance in any problem context. Our specific application considers clinical pathway concordance for stage III colon cancer. We develop a novel concordance metric and demonstrate using real patient data from Ontario, Canada that it has a statistically significant association with survival. Our methodological approach considers a patient’s journey as a walk in a directed graph, where the costs on the arcs are derived by solving an inverse shortest path problem. The inverse optimization model uses two sources of information to find the arc costs: reference pathways developed by a provincial cancer agency (primary) and data from real-world patient-related activity from patients with both positive and negative clinical outcomes (secondary). Thus, our inverse optimization framework extends existing models by including data points of both varying “primacy” and “alignment.” Data primacy is addressed through a two-stage approach to imputing the cost vector, whereas data alignment is addressed by a hybrid objective function that aims to minimize and maximize suboptimality error for different subsets of input data.
The Bass Model (BM) has an excellent track record in the realm of new product sales forecasting. However, its use for optimal dynamic pricing or advertising is relatively limited because the Generalized Bass Model (GBM), which extends the BM to handle marketing variables, uses only percentage changes in marketing variables, rather than their actual values. This restricts the GBM’s prescriptive use, for example, to derive the optimal price path for a new product, conditional on an assumed launch price, but not the launch price itself. In this paper, we employ a utility-based extension of the BM, which can yield normative prescriptions regarding both the introductory price and the price path after launch, for the new product. We offer two versions of this utility-based diffusion model, namely, the Bass-Gumbel Diffusion Model (BGDM) and the Bass-Logit Diffusion Model (BLDM), the latter of which has been previously used. We show that both the BGDM and BLDM handily outperform the GBM in forecasting new product sales using empirical data from four product categories. We discuss how to estimate the BGDM and BLDM in the absence of past sales data. We compare the optimal pricing policy of the BLDM with the GBM and derive optimal pricing policies that are implied by the BLDM under various ranges of model parameters. We illustrate a dynamic pricing approach that allows managers to derive optimal marketing policies in a computationally convenient manner and extend this approach to a competitive, multiproduct case.
We consider a retailer that sells a perishable product, making joint pricing and inventory ordering decisions over a finite time horizon of T periods with lost sales. Exploring a real-life data set from a leading supermarket chain, we identify several distinctive challenges faced by such a retailer that have not been jointly studied in the literature: the retailer does not have perfect information on (1) the demand-price relationship, (2) the demand noise distribution, (3) the inventory perishability rate, and (4) how the demand-price relationship changes over time. Furthermore, the demand noise distribution is nonparametric for some products but parametric for others. To tackle these challenges, we design two types of data-driven pricing and ordering (DDPO) policies for the cases of nonparametric and parametric noise distributions. Measuring performance by regret, that is, the profit loss caused by not knowing (1)–(4), we prove that the T-period regret of our DDPO policies are in the order of T2/3(log ⁡T)1/2 and T1/2log ⁡T in the cases of nonparametric and parametric noise distributions, respectively. These are the best achievable growth rates of regret in these settings (up to logarithmic terms). Implementing our policies in the context of the aforementioned real-life data set, we show that our approach significantly outperforms the historical decisions made by the supermarket chain. Moreover, we characterize parameter regimes that quantify the relative significance of the changing environment and product perishability. Finally, we extend our model to allow for age-dependent perishability and demand censoring and modify our policies to address these issues.
The increasing impact of algorithmic decisions on people’s lives compels us to scrutinize their fairness and, in particular, the disparate impacts that ostensibly color-blind algorithms can have on different groups. Examples include credit decisioning, hiring, advertising, criminal justice, personalized medicine, and targeted policy making, where in some cases legislative or regulatory frameworks for fairness exist and define specific protected classes. In this paper we study a fundamental challenge to assessing disparate impacts in practice: protected class membership is often not observed in the data. This is particularly a problem in lending and healthcare. We consider the use of an auxiliary data set, such as the U.S. census, to construct models that predict the protected class from proxy variables, such as surname and geolocation. We show that even with such data, a variety of common disparity measures are generally unidentifiable, providing a new perspective on the documented biases of popular proxy-based methods. We provide exact characterizations of the tightest possible set of all possible true disparities that are consistent with the data (and possibly additional assumptions). We further provide optimization-based algorithms for computing and visualizing these sets and statistical tools to assess sampling uncertainty. Together, these enable reliable and robust assessments of disparities—an important tool when disparity assessment can have far-reaching policy implications. We demonstrate this in two case studies with real data: mortgage lending and personalized medicine dosing.
The success of a new drug is assessed within a clinical trial using a primary endpoint, which is typically the true outcome of interest—for example, overall survival. However, regulators sometimes approve drugs using a surrogate outcome—an intermediate indicator that is faster or easier to measure than the true outcome of interest—for example, progression-free survival—as the primary endpoint when there is demonstrable medical need. Although using a surrogate outcome (instead of the true outcome) as the primary endpoint can substantially speed up clinical trials and lower costs, it can also result in poor drug-approval decisions because the surrogate is not a perfect predictor of the true outcome. In this paper, we propose combining data from both surrogate and true outcomes to improve decision making within a late-phase clinical trial. In contrast to broadly used clinical trial designs that rely on a single primary endpoint, we propose a Bayesian adaptive clinical trial design that simultaneously leverages both observed outcomes to inform trial decisions. We perform comparative statics on the relative benefit of our approach, illustrating the types of diseases and surrogates for which our proposed design is particularly advantageous. Finally, we illustrate our proposed design on metastatic breast cancer. We use a large-scale clinical trial database to construct a Bayesian prior and simulate our design on a subset of clinical trials. We estimate that our design would yield a 16% decrease in trial costs relative to existing clinical trial designs, while maintaining the same Type I/II error rates.
Although medical research has addressed the clinical management of chronic opioid users, little is known about how operational interventions shortly after opioid initiation can impact a patient’s likelihood of long-term opioid use. Using a nationwide U.S. database of medical and pharmaceutical claims, we investigate the care delivery process at the most common entry point to opioid use: the primary care setting. For patients who return to primary care for a follow-up appointment within 30 days of opioid initiation, we ask who should revisit and potentially revise the opioid-based treatment plan: the initial prescriber (provider concordance) or an alternate clinician (provider discordance)? First, using a fully controlled logistic model, we find that provider discordance reduces the likelihood of long-term opioid use 12 months after opioid initiation by 31% (95% Confidence Interval: [18%, 43%]). Both the instrumental variable analysis technique and propensity-score matching (utilizing the minimum-bias estimator approach) account for omitted variable bias and indicate that this is a conservative estimate of the true causal effect. Second, looking at patient activities immediately after the follow-up appointment, we find that this long-term reduction is at least partially explained by an immediate reduction in opioids prescribed after the follow-up appointment. Third, the data suggest that the benefit associated with provider discordance remains significant regardless of whether the patient’s initial prescriber was their regular primary care provider or another clinician. Overall, our analysis indicates that systematic, operational changes in the early stages of managing new opioid patients may offer a promising, and hitherto overlooked, opportunity to curb the opioid epidemic.
Voluntary shelter-in-place directives and lockdowns are the main nonpharmaceutical interventions that governments around the globe have used to contain the Covid-19 pandemic. In this paper, we study the impact of such interventions in the capital of a developing country, Santiago, Chile, that exhibits large socioeconomic inequality. A distinctive feature of our study is that we use granular geolocated mobile phone data to construct mobility measures that capture (1) shelter-in-place behavior and (2) trips within the city to destinations with potentially different risk profiles. Using panel data linear regression models, we first show that the impact of social distancing measures and lockdowns on mobility is highly heterogeneous and dependent on socioeconomic levels. More specifically, our estimates indicate that, although zones of high socioeconomic levels can exhibit reductions in mobility of around 50%–90% depending on the specific mobility metric used, these reductions are only 20%–50% for lower income communities. The large reductions in higher income communities are significantly driven by voluntary shelter-in-place behavior. Second, also using panel data methods, we show that our mobility measures are important predictors of infections: roughly, a 10% increase in mobility correlates with a 5% increase in the rate of infection. Our results suggest that mobility is an important factor explaining differences in infection rates between high- and low-incomes areas within the city. Further, they confirm the challenges of reducing mobility in lower income communities, where people generate their income from their daily work. To be effective, shelter-in-place restrictions in municipalities of low socioeconomic levels may need to be complemented by other supporting measures that enable their inhabitants to increase compliance.
The online trading platform Alibaba provides financial technology (FinTech) credit for millions of micro, small, and medium-sized enterprises (MSMEs). Using a novel data set of daily sales and an internal credit score threshold that governs the allocation of credit, we apply a fuzzy regression discontinuity design (RDD) to explore the causal effect of credit access on firm volatility. We find that credit access significantly reduces firm sales volatility and that the effect is stronger for firms with fewer alternative sources of financing. We further look at firm exit probability and find that firms with access to FinTech credit are less likely to go bankrupt or exit the business in the future. Additional channel tests reveal that firms with FinTech credit invest more in advertising and product/sector diversification, particularly during business downturns, which serves as effective mechanisms through which credit access reduces firm volatility. Overall, our findings contribute to a better understanding of the role of FinTech credit in MSMEs.
This study examines the relation between financial reporting quality (FRQ) and eponymy, that is, naming a firm after the founder. We hypothesize that compared with noneponymous firms, eponymous firms have higher FRQ because of reputation concerns. Using a sample of 2,271 large Italian private firms, we document that eponymy is positively associated with accrual-based FRQ measures, a Benford’s law–based FRQ measure, and a tax-related misstatement–based FRQ measure. Consistent with the reputation concern rationale, we find that the positive association between eponymy and FRQ is attributable to eponymous firms that have rarer names or receive more press coverage. Furthermore, the positive association between FRQ and eponymy is similar whether the top executives/board members belong to the founding family’s first or later generations. We also find that eponymous firms are more conditionally conservative. Collectively, the results suggest that reputation concerns act as a disciplining mechanism for FRQ in private firms.
This paper examines the consequences of the paycheck protection program (PPP) for bank risk-taking and whether the shift to the current expected credit loss (CECL) model moderates this effect. We find that the extent of a bank’s PPP participation is associated with relatively greater changes in risk-taking outside of the PPP. We also show that this effect is concentrated in banks that have not early adopted the CECL model and banks with timelier pre-PPP loan loss provisions, suggesting that timelier loan loss recognition constrains risk-taking incentives. Overall, our findings provide insight into the indirect consequences of government stimulus programs administered through banks and the role of accounting in constraining bank risk-taking.
Automated investment managers, or robo-advisors, have emerged as an alternative to traditional financial advisors. The viability of robo-advisors crucially depends on their ability to offer personalized financial advice. We introduce a novel framework in which a robo-advisor interacts with a client to solve an adaptive mean-variance portfolio optimization problem. The risk-return tradeoff adapts to the client’s risk profile, which depends on idiosyncratic characteristics, market returns, and economic conditions. We show that the optimal investment strategy includes both myopic and intertemporal hedging terms that reflect the dynamic risk profile of the client. We characterize the optimal portfolio personalization via a tradeoff faced by the robo-advisor between receiving information from the client in a timely manner and mitigating behavioral biases in the communicated risk profile. We argue that the optimal portfolio’s Sharpe ratio and return distribution improve if the robo-advisor counters the client’s tendency to reduce market exposure during economic contractions when the market risk-return tradeoff is more favorable.
This paper estimates the heterogeneity in peer effects among research scientists in terms of network position. I propose a new measure, brokerage degree, that determines the extent to which a scientist depends on a coauthor to provide him unique access to other scientists further away. I apply this measure to the coauthorship network of medical scientists. I show that network position is crucial for productivity by facilitating access to nonredundant knowledge. Identification results from variation in brokerage degree among coauthors linked to a star scientist who dies. A one standard deviation increase in the brokerage degree of a deceased star is associated with a 10% decrease in annual publications of his coauthor. By applying brokerage degree to topics, I provide evidence that access to knowledge flows embodied in scientists further away can account for a large proportion of the identified heterogeneity effect.
Service systems are typically limited resource environments where scarce capacity is reserved for the most urgent customers. However, there has been a growing interest in the use of proactive service when a less urgent customer may become urgent while waiting. On one hand, providing service for customers when they are less urgent could mean that fewer resources are needed to fulfill their service requirement. On the other hand, using limited capacity for customers who may never need the service in the future takes the capacity away from other more urgent customers who need it now. To understand this tension, we propose a multiserver queueing model with two customer classes: moderate and urgent. We allow customers to transition classes while waiting. In this setting, we characterize how moderate and urgent customers should be prioritized for service when proactive service for moderate customers is an option. We identify an index, the modifiedcμ/θ-index, which plays an important role in determining the optimal scheduling policy. This index lends itself to an intuitive interpretation of how to balance holding costs, service times, abandonments, and transitions between customer classes.
Research and practical development of data-anonymization techniques have proliferated in recent years. Yet, limited attention has been paid to examine the potentially disparate impact of privacy protection on underprivileged subpopulations. This study is one of the first attempts to examine the extent to which data anonymization could mask the gross statistical disparities between subpopulations in the data. We first describe two common mechanisms of data anonymization and two prevalent types of statistical evidence for disparity. Then, we develop conceptual foundation and mathematical formalism demonstrating that the two data-anonymization mechanisms have distinctive impacts on the identifiability of disparity, which also varies based on its statistical operationalization. After validating our findings with empirical evidence, we discuss the business and policy implications, highlighting the need for firms and policy makers to balance between the protection of privacy and the recognition/rectification of disparate impact.
Economic incentives are a promising approach for improving health behavior but have been limited by their short-lived benefits. In this manuscript, we examine whether coupling economic incentives with motivational tools provided by health wearables can address this limitation and drive longer-term changes in health behavior. We focus on “gain-loss” incentive schemes that offer both an economic reward for goal attainment and a penalty for failure to meet a goal. In an experiment conducted on individuals wearing Fitbit wearables, we find that gain-loss incentives can drive increases in physical activity but are limited by the element of choice. Specifically, we find modest and short-lived increases in physical activity for those provided the choice of gain-loss incentives. The subpar benefits for this group seem to emerge because those who benefit most from these schemes do not opt into them when they are voluntary. In contrast, we find significant and persistent increases in physical activity for those assigned (oftentimes against their preference) to the same gain-loss incentives. These individuals recorded ∼2,000 additional steps daily during the incentive period, and benefits persisted for six months after incentives ended. Critically, the persistent gains to this group were driven by individuals who also utilized the wearable’s goal-setting tool. Our results suggest that a novel approach toward motivating sustained changes in health behavior couples aggressive incentive schemes that jolt individuals out of their comfort zone in the short term with motivational tools built into health wearables that help individuals sustain healthy behavior after economic incentives end.
We study an original equipment manufacturer (OEM) purchasing two inputs for assembly from two suppliers with private cost information. The OEM can contract with the two suppliers either simultaneously or sequentially. We consider both cases in which the OEM has relatively equal bargaining power (the dynamic bargaining institution) or substantial bargaining power (the mechanism design institution). For the dynamic bargaining institution, we show that in sequential bargaining, the supply chain profit is higher, the OEM earns a lower profit, the first supplier earns a higher profit, and the second supplier may earn a higher or lower profit, than compared with simultaneous bargaining. For the mechanism design institution, we show that all players’ profits are the same in simultaneous and sequential contracting. We also benchmark against a case where the OEM procures both inputs from a single integrated supplier (a dyadic supply chain). We then test these predictions in a human-subjects experiment, which supports many of the normative predictions qualitatively with some deviations: an OEM with relatively equal bargaining power weakly prefers to contract with suppliers simultaneously, whereas an OEM with substantial bargaining power prefers to contract with suppliers sequentially. In addition, the OEM’s profit and supply chain efficiency are higher in the dyadic supply chain than the assembly system.
We use a proprietary data set from a national department store chain and evaluate the competitive impact of the launch of a buy-online-and-pick-up-in-store service by a major competitor. The transaction-level data set includes nearly 50 million transactions (purchase and return) across both online and brick-and-mortar channels. Although the strategy of buying online and picking up in a store is primarily designed to attract online shoppers into stores, our findings show that after the competitor’s launch, both online and store sales at the focal department store chain are negatively affected. Our results indicate a differential competitive threat that is predicated on the value proposition that the buy-online-and-pick-up-in-store service poses for customers in each channel. Online shoppers are drawn to the competitor through an additional level of shopping assurance, along with the free and fast delivery that the buy-online-and-pick-up-in-store service provides to customers. For store shoppers, the service facilitates research-online, buy-offline behavior, as well as product availability information that eliminates wasted trips to the store. Distance to market affects the intensity of impact. For the online channel, the estimated loss in sales averages 4.7% across the demographic market areas that are served and ranges between 0.4% and 18.5%. For stores, the average estimated loss in sales is 1.8% and ranges between 0.1% and 3.7%.
We analyze congested network-based markets and their impact on competition, equilibrium charges and efficiency. Several strategies are explored including price caps, mergers and investments in new technologies. We find that congested networks served by collaborating (serial) and competing (parallel) firms may lead to excessive prices. Additionally, oligopolists may only serve captive demand, leading to inefficiently low flows. Perhaps surprisingly, permitting a firm with market power to horizontally integrate with a competitor may improve efficiency. We also show that price caps in congested networks are ineffective due to their failure to signal the existence of scarce resources. Instead, partial vertical integration may prove beneficial by creating incentives to expand capacity through technology adoption, provided the price cap regime is dropped. The model is subsequently illustrated with a case study of air traffic control provision in Western Europe, in which it is shown that substantial changes in the regulation are required in order to create a more cost efficient sector with increased capacity.
It is well known that manufacturing operations can affect the environment, but hardly any research explores whether the natural environment shapes manufacturing operations. Specifically, we investigate whether water scarcity, which results from environmental conditions, influences manufacturing firms to lower their toxic releases to the environment. We created a data set that spans 2000–2016 and includes details on the toxic emissions of 3,092 manufacturing facilities in Texas. Additionally, our data set includes measures of the water scarcity experienced by these facilities. Our econometric analysis shows that manufacturing facilities reduce their toxic releases into the environment when they have experienced drought conditions in the previous year. We examine facilities that release toxics to water as well as facilities with no toxic releases to water. We find that the reduction in total releases (to all media) is driven mainly by those facilities that release toxic chemicals to water. Further investigation at a more granular level indicates that water scarcity compels manufacturing facilities to lower their toxic releases into media other than water (i.e., land or air). The impact of water scarcity on toxic releases to water is more nuanced. A full-sample analysis fails to link water scarcity to lower toxic releases to water, but a further breakdown shows that manufacturing facilities in counties with a higher incidence of drought do lower their toxic releases to water. We also find that facilities that release toxics to water undertake more technical and input modifications to their manufacturing processes when they face water scarcity.
In this paper, we examine the impact of racially charged events on the demand for antiracist classroom resources in U.S. public schools. We use book requests made by teachers on DonorsChoose, the largest crowdfunding platform for public school teachers, as a measure of intent to address race-related topics in the classroom. We use the precise timing of high-profile police brutality and other racially charged events in the United States (2010–2020) to identify their effect on antiracism requests relative to a control group. We find a significant increase in antiracism requests following the killing of George Floyd in 2020 and a null effect for all other events in the decade. We also find an increase in requests for books featuring Latinx, Asian, Muslim, and Jewish cultures, suggesting that a focus on equality for one group can spill over and yield culturally aware dialogues for other groups as well. Event studies suggest that local protests played a role in motivating some of the teachers to post these requests. In just four months following George Floyd’s death, $3.4 million worth of books featuring authors and characters from marginalized communities were successfully funded, reaching more than half a million students. Text analysis of impact notes posted by teachers suggests that hundreds of thousands of young students are being engaged in discussions about positive affirmation and cross-cultural acceptance.
Much research on advice taking examines how people revise point estimates given input from others. This work has established that people often egocentrically discount advice. If they were to place more weight on advice, their point estimates would be more accurate. Yet the focus on point estimates and accuracy has resulted in a narrow conception of what it means to heed advice. We distinguish between revisions of point estimates and revisions of attendant probability distributions. Point estimates represent a single best guess; distributions represent the probabilities that people assign to all possible answers. A more complete picture of advice taking is provided by considering revisions of distributions, which reflect changes in both confidence and best guesses. We capture this using a new measure of advice utilization: the influence of advice. We observe that, when input from a high-quality advisor largely agrees with a person’s initial opinion, it engenders little change in one’s point estimate and, hence, little change in accuracy yet significantly increases confidence. This pattern suggests more advice taking than generally suspected. However, it is not necessarily beneficial. Because people are typically overconfident to begin with, receiving advice that agrees with their initial opinion can exacerbate overconfidence. In several experiments, we manipulate advisor quality and measure the extent to which advice agrees with a person’s initial opinion. The results allow us to pinpoint circumstances in which heeding advice is beneficial, improving accuracy or reducing overconfidence, as well as circumstances in which it is harmful, hurting accuracy or exacerbating overconfidence.
The standard assumption in social learning environments is that agents learn from others through choice outcomes. We argue that in many settings, agents can also infer information from others’ response times (RT), which can increase efficiency. To investigate this, we conduct a standard information cascade experiment and find that RTs do contain information that is not revealed by choice outcomes alone. When RTs are observable, subjects extract this private information and are more likely to break from incorrect cascades. Our results suggest that in environments where RTs are publicly available, the information structure may be richer than previously thought.
We experimentally investigate, in an unstructured bargaining environment with commonly known money payoffs, the attraction effect and compromise effect (AE and CE) in bargaining, namely, a tendency for bargainers to agree to an intermediate option (CE) or to an option that dominates another option (AE). We conjecture that the relevance of the AE and CE in bargaining is constrained by how focal the feasible agreements’ payoffs are. We indeed observe that there are significant AEs and CEs, but these effects are mediated by the efficiency and equality properties of the feasible agreements. Due to the allure of equality, the effects are harder to observe when an equal earnings contract is available. Decoys are more effective in shifting agreements from a very unequal contract to a less unequal one rather than the reverse.
When soliciting novel product ideas from the “crowd,” companies may opt to show a prototype in order to steer the generation of ideas in the desired direction. On the one hand, the more features the prototype incorporates, the larger the potential for activating relevant knowledge in memory that may serve as a basis for generating novel ideas. On the other hand, it increases the risk of fixation on the incorporated features, which may inhibit the generation of novel ideas. Based on the “dual pathway to creativity” theory, which identifies the depth and breadth of exploration of one’s knowledge base as cognitive pathways to the generation of novel ideas, we argue that the number (and type) of features included in the prototype in combination with the design goal, that is, generating ideas for functional versus aesthetic product improvements, determines whether the positive effects outweigh the negative effects. With a functional design goal, we find that exposure to a prototype with more features leads to more novel ideas as a result of a more thorough exploration of one’s knowledge base. However, with an aesthetic design goal, exposure to a prototype with more features leads to less novel ideas because of a narrower exploration. The latter effect is driven by people’s tendency to consider the whole or gestalt of the prototype when generating aesthetic ideas. This negative effect can, thus, be mitigated by stimulating people to employ a nonholistic, piecemeal thinking style.
An important challenge for many firms is to identify the life transitions of its customers, such as job searching, expecting a child, or purchasing a home. Inferring such transitions, which are generally unobserved to the firm, can offer the firms opportunities to be more relevant to their customers. In this paper, we demonstrate how a social network platform can leverage its longitudinal user data to identify which of its users are likely to be job seekers. Identifying job seekers is at the heart of the business model of professional social network platforms. Our proposed approach builds on the hidden Markov model (HMM) framework to recover the latent state of job search from noisy signals obtained from social network activity data. Specifically, we use the latent states of the HMM to fuse cross-sectional survey responses to a job-seeking status question with longitudinal user activity data, resulting in a partially HMM. Thus, in some time periods, and for some users, we observe a direct measure of the true job-seeking status. We demonstrate that the proposed model can predict not only which users are likely to be job seeking at any point in time but also what activities on the platform are associated with job search and how long the users have been job seeking. Furthermore, we find that targeting job seekers based on our proposed approach can lead to a 29% increase in profits of a targeting campaign relative to the approach that was used by the social network platform.
We propose target date funds modified to exploit stock return predictability driven by the variance risk premium. The portfolio rule of these tactical target date funds (TTDFs) is extremely simplified relative to the optimal one, making it easy to implement and to communicate to investors. We show that saving for retirement in TTDFs generates economically large welfare gains, even after we introduce turnover restrictions and transaction costs, and after taking into account parameter uncertainty. This predictability also appears to be uncorrelated with individual household risk, suggesting that households are in a prime position to exploit it.
We develop a model of competition between banks and a marketplace lender to motivate empirical tests using local market data on U.S. banks and the largest marketplace lending platform. Employing mergers of large, multimarket banks as an exogenous credit supply shock, we find that marketplace lending absorbs unmet demand for consumer credit following a decline in the availability of bank credit. Merger-induced bank branch closings lead to an increase in marketplace loan requests and loan acceptance rates, particularly for debt consolidation loans to lower-risk consumers. We also find that marketplace lending mitigates credit distress in local economies affected by mergers.
This study examines the role of differences in firms’ propensity to meet earnings expectations in explaining why firms with high analyst forecast dispersion experience relatively low future stock returns. We first demonstrate that the negative relation between dispersion and returns is concentrated around earnings announcements. Next, we show that this relation disappears when we control for ex ante measures of firms’ propensity to meet earnings expectations and that the component of dispersion explained by these measures drives the return predictability of dispersion. We further demonstrate that firms with low analyst dispersion are substantially more likely to achieve positive earnings surprises and provide new evidence consistent with both expectations management and strategic forecast pessimism explaining this result. Overall, we conclude that investor mispricing of firms’ participation in the earnings-expectations game provides a viable explanation for the dispersion anomaly.
Data on population movements can be helpful in designing targeted policy responses to curb epidemic spread. However, it is not clear how to exactly leverage such data and how valuable they might be for the control of epidemics. To explore these questions, we study a spatial epidemic model that explicitly accounts for population movements and propose an optimization framework for obtaining targeted policies that restrict economic activity in different neighborhoods of a city at different levels. We focus on COVID-19 and calibrate our model using the mobile phone data that capture individuals’ movements within New York City (NYC). We use these data to illustrate that targeting can allow for substantially higher employment levels than uniform (city-wide) policies when applied to reduce infections across a region of focus. In our NYC example (which focuses on the control of the disease in April 2020), our main model illustrates that appropriate targeting achieves a reduction in infections in all neighborhoods while resuming 23.1%–42.4% of the baseline nonteleworkable employment level. By contrast, uniform restriction policies that achieve the same policy goal permit 3.92–6.25 times less nonteleworkable employment. Our optimization framework demonstrates the potential of targeting to limit the economic costs of unemployment while curbing the spread of an epidemic.
We study the impact of using informational messaging aimed at encouraging women to seek a career in technology and the resulting trade-offs for organizations pursuing recruitment strategies of this kind. Our treatment, implemented through two field experiments among potential applicants to a five-month software-coding program targeted at low-income women in Peru and Mexico, counterbalances the strong male stereotype associated with a career in tech. Although our informational messages substantially increase application rates, including candidates at the top of the cognitive skill distribution, they introduce negative selection on cognitive skills, implying a higher cost of screening. Moreover, we observe selection on the noncognitive dimensions addressed with the treatment (e.g., stronger gender stereotypes and traditional norms). This points to the barriers that preclude more women from applying to tech positions, as well as the trade-offs for organizations of adopting such a strategy.
Ride-hailing marketplaces like Uber and Lyft use dynamic pricing, often called surge, to balance the supply of available drivers with the demand for rides. We study driver-side payment mechanisms for such marketplaces, presenting the theoretical foundation that has informed the design of Uber’s new additive driver surge mechanism. We present a dynamic stochastic model to capture the impact of surge pricing on driver earnings and their strategies to maximize such earnings. In this setting, some time periods (surge) are more valuable than others (nonsurge), and therefore trips of different time lengths vary in the induced driver opportunity cost. First, we show that multiplicative surge, historically the standard on ride-hailing platforms, is not incentive compatible in a dynamic setting. We then propose a structured, incentive-compatible pricing mechanism. This closed-form mechanism has a simple form and is well approximated by Uber’s new additive surge mechanism. Finally, through both numerical analysis and real data from a ride-hailing marketplace, we show that additive surge is more incentive compatible in practice than is multiplicative surge.
We present evidence that unnecessarily complex disclosure can result from strategic incentives to shroud information. In our laboratory experiment, senders are required to report their private information truthfully but can choose how complex to make their reports. We find that senders use complex disclosure more than half the time. This obfuscation is profitable because receivers make systematic mistakes in assessing complex reports. Regression and structural analysis suggest that these mistakes could be driven by receivers who are naive about the strategic use of complexity or overconfident about their ability to process complex information.
By providing quick and easy access to credit, online lending platforms may help borrowers overcome financial setbacks and/or refinance high-interest debt, thereby decreasing bankruptcy filings. On the other hand, these platforms may cause borrowers to overextend themselves financially, leading to a “debt trap” and increasing bankruptcy filings. To investigate the impact of online lending on bankruptcy filings, we leverage variation in when state regulators granted approval for a major online lending platform—Lending Club—to issue peer-to-peer loans. Using a difference-in-differences approach, we find that state approval of Lending Club led to an increase in bankruptcy filings. A complementary instrumental variables analysis using loan-level data yields similar results. We find suggestive evidence that the ease of receiving a Lending Club loan causes some borrowers to overextend themselves financially, leading to bankruptcy. Our results suggest that recent initiatives from online lending platforms to control how borrowers use loans, such as Lending Club’s “balance transfer loans” that send loan funds directly to creditors, can help these platforms provide safe and affordable credit. Our study adds to the literature that examines how online platforms influence society and the economy; it contributes to the literature that examines how financial products, services, and regulations influence bankruptcy filings; and it has policy implications for online lending design and regulation.
The general data protection regulation (GDPR) represents a dramatic shift in global privacy regulation. We focus on GDPR’s enhanced consumer consent requirements that aim to provide transparent and active elicitation of data allowances. We evaluate the effect of enhanced consent on consumer opt-in behavior and on firm behavior and outcomes after consent is solicited. Utilizing an experiment at a large telecommunications provider with operations in Europe, we find that opt-in for different data types and uses increased once GDPR-compliant consent was elicited. However, consumers did not uniformly increase data allowances and continued to generally restrict permissions for more sensitive or tangential uses of their personal information. We also find that sales, the efficacy of marketing communications, and contractual lock-in increased after consumers provided new data allowances. Additional analysis suggests that these gains to the firm emerged because new data allowances enabled them to increase their use of targeted marketing for households that were amenable to these marketing efforts. These results have significant implications for firms and policymakers and suggest that enhanced consent provided via GDPR may be effective for increasing consumer privacy protection while also allowing firms reliant on consumers’ personal information to improve outcomes.
We provide direct evidence of how dealers’ funding liquidity affects their liquidity provision in securities markets. Worse funding liquidity (higher repo haircuts and rates) leads to larger bid-ask spreads and transaction costs in corporate bonds. We also find that dealers’ relationships with money funds are important determinants of their repo haircuts and rates. Using dealers’ exposure to the 2016 Securities and Exchange Commission (SEC) money fund reform as an instrument, we show that funding liquidity indeed has a causal effect on market liquidity. Finally, dealers with lower funding liquidity tend to have smaller market shares and execute more trades on an agency basis.
Innovation is a contract-intensive economic activity in a world of incomplete contracts. We show that trust mitigates incomplete contracting and enhances innovation by acting as an informal contracting mechanism. Trust plays an especially important role when formal laws and regulations are lacking, and it promotes innovation by encouraging collaboration and fostering tolerance for failure. Further analyses show that trust also facilitates cross-border technological spillover and innovation collaboration. Overall, our evidence highlights innovation as a key conduit through which trust affects economic growth.
We study tactical models for the design of same-day delivery (SDD) systems. Same-day fulfillment in e-commerce has seen substantial growth in recent years, and the underlying management of such services is complex. Although the literature includes operational models to study SDD, they tend to be detailed, complex, and computationally difficult to solve, and thus may not provide any insight into tactical SDD design variables and their impact on the average performance of the system. We propose a simplified vehicle-dispatching model that captures the “average” behavior of an SDD system from a single stocking location by utilizing continuous approximation techniques. We analyze the structure of optimal vehicle-dispatching policies given our model for two important instance families—the single-vehicle case and the case in which the delivery fleet is large—and develop techniques to find these policies that require only simple computations. We also leverage these results to analyze the case of a finite fleet, proposing a heuristic policy with a worst-case approximation guarantee. We then demonstrate with several example problem settings how this model and these policies can help answer various tactical design questions, including how to select a fleet size, determine an order cutoff time, and combine SDD and overnight order delivery operations. We validate model predictions empirically against a detailed operational model in a computational case study using geographic and Census data for the northeastern metro Atlanta region, and we demonstrate that our model predicts the average number of orders served and dispatch time to within 1%.
We find firms’ work-related injury rates are negatively associated with the level of analyst coverage. This result is also robust at the establishment level at which we find local analysts have a more profound impact than distant analysts. Cross-sectionally, our results are exacerbated in firms with weak internal governance mechanisms and in industries with low union representation. Finally, management is more likely to discuss safety issues during earnings conference calls in the presence of more analysts. Overall, our results suggest analysts play an effective external monitoring role and have a subtle yet important impact on employee welfare.
We theorize peer awards’ effects on the volume and novelty of creative user-generated content (UGC) produced at online platform communities. We then test our hypotheses via a randomized field experiment on Reddit, wherein we randomly and anonymously assigned Reddit’s Gold Award to 905 users’ posts over a two-month period. We find that peer awards induced recipients to make longer, more frequent posts and that these effects were particularly pronounced among newer community members. Further, we show that recipients were causally influenced to engage in greater (lesser) exploitation (exploration) behavior, producing content that exhibited significantly greater textual similarity to their own past (awarded) content. However, because the effects were most pronounced among new community members, who also produce content that, in general, is systematically more novel than that of established members to begin with, this process yields a desirable outcome: larger volumes of generally novel UGC for the community.
Newspapers are increasingly reliant on subscription revenue as advertising spend shifts to online platforms. Many newspapers have implemented paywalls in an attempt to boost subscription revenue. We study whether and how paywalls can help newspapers boost subscription revenue by retaining existing subscribers. Most major newspapers offer free access to paywalled content to subscribers to the print edition, which may help the newspaper retain subscribers by making their subscriptions more valuable. We leverage variation in whether and when existing subscribers activated access to the paywall of a top 30 North American newspaper. Our identification strategy accounts for self-selection in subscribers’ decisions to activate paywall access. We find that a subscriber’s activation of digital access decreases the risk of her canceling her subscription by about 31% and increases her subscription revenue by 7%–12%. In other words, digital activation improves subscriber retention and the associated subscription revenue. This suggests a crosschannel spillover in which the online product (the paywalled website) increases customers’ valuation for the offline product (the printed newspaper). Our results have implications not only for the newspaper industry but also for firms in other industries that offer subscribers to one product free or subsidized access to a complementary product.
We examine how the introduction of monetary incentives by a knowledge-sharing platform affects the nonrewarded knowledge activity on the platform. Our setting is a question-and-answer platform that provides monetary incentives for holding live talks. Using a combination of coarsened exact matching and difference-in-differences estimation techniques, we find that the launch of the paid feature creates a positive spillover effect on the hosts’ free contributions, specifically, 9.4%–40.8% more answers in the short run when compared with nonhosts. The paid feature did not result in any significant change in the quality of answers. We suggest reputation building is one plausible mechanism underlying the spillover. Additional analyses reveal the spillover effect is negative for short-lived hosts in the long run, indicating possible crowding out of free contributions. The positive spillover effect for long-lived hosts lasts longer but is also reduced over time. Our findings suggest that introducing monetary incentives can be a viable business model for knowledge platforms to stimulate user contributions in both the paid and related unpaid activities. Yet platform owners should be cautious about the potential negative spillover after users stop contributing to the paid activity and develop effective strategies to maintain users’ long-term interests in the paid program.
Private and public organizations are interested in finding effective ways to reduce crime and promote ethical behavior without investing heavy resources into monitoring and compliance. In this paper, we experimentally study how revealing different information about a fine distribution affects deterrence of an undesirable behavior. We use a novel incentive-compatible elicitation method to observe subjects lying (the undesirable behavior) and quantify the extent to which this behavior responds to information structures. We find that punishment schemes that communicate only partial information (the minimum fine in particular) are more effective than full information schemes at deterring lying. We explore the mechanism driving this result and link it to subjects’ beliefs about their own versus the average expected fine in treatments with partial information.
Many applied economic settings involve trade-offs between in-group members and strangers. To better understand decision making in these contexts, this paper measures and investigates the economic relevance of heterogeneity in moral universalism: the extent to which people exhibit the same level of altruism and trust toward strangers as toward in-group members. We first introduce a new experimentally validated, survey-based measure of moral universalism that is simple and easily scalable. We then deploy this tool in a large, representative sample of the U.S. population to study heterogeneity and economic relevance. We find that universalism is a relatively stable trait at the individual level. In exploratory analyses, heterogeneity in universalism is significantly related to observables: Older people, men, the rich, the rural, and the religious exhibit less universalist preferences and beliefs. Linking variation in universalism to self-reports of economic and social behaviors, we document the following correlations. Universalists donate less money locally, but more globally, and are less likely to exhibit home bias in equity and educational investments. In terms of social networks, universalists have fewer friends, spend less time with them, and feel more lonely. These results provide a blueprint for measuring moral universalism in applied settings and suggest that variation in universalism is relevant for understanding a myriad of economic behaviors.
A wide body of empirical research has revealed the descriptive shortcomings of expected value and expected utility models of risky decision making. In response, numerous models have been advanced to predict and explain people’s choices between gambles. Although some of these models have had a great impact in the behavioral, social, and management sciences, there is little consensus about which model offers the best account of choice behavior. In this paper, we conduct a large-scale comparison of 58 prominent models of risky choice, using 19 existing behavioral data sets involving more than 800 participants. This allows us to comprehensively evaluate models in terms of individual-level predictive performance across a range of different choice settings. We also identify the psychological mechanisms that lead to superior predictive performance and the properties of choice stimuli that favor certain types of models over others. Moreover, drawing on research on the wisdom of crowds, we argue that each of the existing models can be seen as an expert that provides unique forecasts in choice predictions. Consistent with this claim, we find that crowds of risky choice models perform better than individual models and thus provide a performance bound for assessing the historical accumulation of knowledge in our field. Our results suggest that each model captures unique aspects of the decision process and that existing risky choice models offer complementary rather than competing accounts of behavior. We discuss the implications of our results on theories of risky decision making and the quantitative modeling of choice behavior.
Every year, nearly 5,000 patients die while waiting for kidney transplants, and yet an estimated 3,500 procured kidneys are discarded. Such a polarized coexistence of dire scarcity and massive wastefulness has been mainly driven by insufficient pooling of cadaveric kidneys across geographic regions. Although numerous policy initiatives are aimed at broadening organ pooling, they rarely account for a key friction—efficient airline transportation, ideally direct flights, is necessary for long-distance sharing, because of the time-sensitive nature of kidney transplantation. Conceivably, transplant centers may be reluctant to accept kidney offers from far-off locations without direct flights. In this paper, we estimate the effect of the introduction of new airline routes on broader kidney sharing. By merging the U.S. airline transportation and kidney transplantation data sets, we create a unique sample tracking (1) the evolution of airline routes connecting all the U.S. airports and (2) kidney transplants between donors and recipients connected by these airports. We estimate the introduction of a new airline route increases the number of shared kidneys by 7.3%. We also find a net increase in the total number of kidney transplants and a decrease in the organ discard rate with the introduction of new routes. Notably, the posttransplant survival rate remains largely unchanged, although average travel distance increases after the introduction of new airline routes. Our results are robust to alternative empirical specifications and have important implications for improving access to the U.S. organ transplantation system.
Background. Influenza imposes heavy societal costs through healthcare expenditures, missed days of work, and numerous hospitalizations each year. Considering these costs, the healthcare and behavioral science literature offers suggestions on increasing demand for flu vaccinations. Yet, the adult flu vaccination rate fluctuated between 37% and 46% between 2010 and 2019. Aim. Although a demand-side approach represents one viable strategy, an operations management approach would also highlight the need to consider a supply-side approach. In this paper, we investigate how to improve clinic vaccination rates by altering provider behavior. Methodology. We implement and study a flu vaccine intervention among 145 clinics from nine different states. This intervention randomly assigned these clinics to a control group or one of two separate treatment arms that received either relative performance feedback or financial incentives. Results. We find clinics that received relative performance feedback outperformed all others: Our intervention led to a 12% increase in flu shots for this group of clinics. Moreover, we also find clinics in this group exhibit rank response behavior, specifically last-place aversion; in particular, clinics near last place outperform the corresponding control clinics by 23% points. Conclusion. Overall, we find that clinic-level performance feedback can effectively drive operational improvement. Even a small increase in the U.S. adult flu vaccination rate might confer hundreds of millions of dollars in societal benefits and prevents thousands of hospitalizations. We discuss the implications of our work for healthcare operations theory, healthcare providers, and healthcare administrators.
The cross-sectional variation in corporate profitability has occupied research across fields as diverse as strategic management, industrial organization, finance, and accounting. Prior work suggests that corporate idiosyncrasies are important determinants of profitability, but it disagrees on the quantitative importance of particular effects. This paper shows that corporate specificities become irrelevant in the long run because profitability is ergodic conditional on survival, leading to a uniform, time-invariant regularity in profitability that applies across firms. Conditional on survival, we cannot reject the hypothesis that corporations are on average equally profitable and also experience equally volatile fluctuations in their profitability, irrespective of their individual characteristics. Because the same is not true for shorter-lived firms, even for more than 20 years after entry, we can reconcile our findings with an extensive literature that studies profitability in heterogeneous samples of surviving and shorter-lived firms. Our findings provide a new benchmark for long-term performance in competitive environments and offer a novel perspective by highlighting a robust commonality instead of specificities.
We examine the teams that emerge when a primary care physician (PCP) refers patients to specialists. When PCPs concentrate their specialist referrals—for instance, by sending their cardiology patients to fewer distinct cardiologists—repeat interactions between PCPs and specialists are encouraged. Repeated interactions provide more opportunities and incentives to develop productive team relationships. Using data from the Massachusetts All Payer Claims Database, we construct a new measure of PCP team referral concentration and document that it varies widely across PCPs, even among PCPs in the same organization. Chronically ill patients treated by PCPs with a one standard deviation higher team referral concentration have 4% lower healthcare utilization on average, with no discernible reduction in quality. We corroborate this finding using a national sample of Medicare claims and show that it holds under various identification strategies that account for observed and unobserved patient and physician characteristics. The results suggest that repeated PCP-specialist interactions improve team performance.
Product reliability is a key concern for manufacturers. We examine worker turnover as a significant but underrecognized determinant of product reliability. Our study collects and integrates (1) data reporting factory worker staffing and turnover from within a major consumer electronics producer’s supply chain and (2) traceable data reporting the component quality and field failures—that is, replacements and repairs—of nearly 50 million consumer mobile devices over four years of customer usage. Devices are individually traced back to the factory conditions and staffing, down to the assembly line–week, under which they were produced. Despite the manufacturer’s extensive quality control efforts, including stringent testing, each percentage point increase in the weekly rate of workers quitting from an assembly line (its weekly worker turnover) is found to increase field failures by 0.74%–0.79%. In the high-turnover weeks following paydays, eventual field failures are strikingly 10.2% more common than for devices produced during the lowest turnover weeks immediately before paydays. In other weeks, the assembly lines experiencing higher turnover produce an estimated 2%–3% more field failures on average. The associated costs amount to hundreds of millions of U.S. dollars. We demonstrate that staffing and retaining a stable factory workforce critically underlies product reliability and showcase the value of traceability coupled with connected workplace and product data in supply chain operations.
We study the effects of village credit information sharing on individual microloan repayment, using a randomized experiment with loan applicants from 40 villages in rural China. In our main treatment, customers received a message on the loan application form that “overdue payment (40 days after each installment due date) will be considered for public disclosure among the village by showing debtors’ names on a blackboard outside the village office of the microlending institution.” On average, this social appeal reduces the share of delinquents and the individual delinquency rate by 18.6% and 5.6% from baseline rates of 79.5% and 15.2%, respectively. The effects appear more pronounced among male and older borrowers. Additional treatments help to benchmark the effect against lender credit information sharing and separate the effects on adverse selection and moral hazard. Mechanism analysis shows that the publicly disclosed “blacklist” of delinquents affects borrowers’ repayment behaviors, partially through borrowers’ fear of losing informal risk insurance from the village society and predominately through public shaming penalties. Overall, these results support that, in traditional societies, social appeals can provide not only pecuniary, but also psychological incentives to improve loan repayment. Psychological incentives, to some extent, have stronger effects.
This paper studies whether greater competition can mitigate agency problems within banks. We measure the intensity of the agency conflict within a bank by the volume of loans that the bank lends to its insiders (e.g., executives). We first check that these loans are a form of private benefit. By exploiting interstate branching deregulation, we then show that banks react to greater competition by reducing insider lending, especially when the entry of new competitors may more strongly affect bank profitability. Results are robust to using various identification approaches and alternative indicators of agency conflict. We conclude that competitive pressure reduces managerial self-dealing.
We exploit the staggered passage of state-level fair-employment laws in the post-World War II period to examine how stronger worker protection against racial discrimination affects firm profitability and financing decisions. We find that firms experience a decline in operating profitability after the passage of anti-discrimination laws. We also document that the adoption of these laws leads to a reduction in debt ratios, which suggests that firms are able to partially offset the negative effects on operating profitability by adjusting their capital structure. Consistent with theoretical predictions, these effects of anti-discrimination laws are more pronounced for firms in states and cities with a greater proportion of African Americans, firms with high labor intensity, firms in states experiencing high African American migration, and firms in concentrated industries. Some of our evidence suggests that anti-discrimination laws lead to a reduction in statistical discrimination or monopsony power rather than taste-based discrimination. Taken together, our results are supportive of theoretical models of discrimination and show that racial discrimination laws significantly affect firm operating performance and financial policies.
Does a bank’s dependence on different external funding sources shape its voluntary disclosure of information? We evaluate whether economic shocks that increase the supply of bank deposits alter the cost–benefit calculations of bank managers concerning voluntary information disclosure. We measure information disclosure using 10-K filings, 8-K filings, and earnings guidance. As for the funding shock, we use unanticipated technological innovations that triggered shale development and booms in bank deposits. Further analyses suggest that greater exposure to shale development reduced information disclosure by relaxing the incentives for managers to disclose information to attract funds from external capital markets.
We examine how online customer reviews for one generation of a product affect sales of another generation in the same product series. The main intriguing result is that previous generation valence has a positive impact on current generation sales; however, current generation valence has a negative impact on previous generation sales. The positive impact of previous generation valence becomes even stronger (1) as the uncertainty (standard deviation) in reviews for the current generation increases and (2) when the current generation valence is high. In contrast, it becomes weaker (1) as the uncertainty in reviews for the previous generation increases and (2) when the current generation has been on the market for a longer period of time. Other results are discussed. Our data consist of intergenerational pairs of point-and-shoot cameras on the largest online seller of such devices, Amazon.com. We estimate the current and previous generation models jointly, allowing for errors to be clustered at the daily and product levels. In addition, we address endogeneity concerns over the online word of mouth measures by using instrumental variables.
Although extant literature investigates the role of sell-side equity analysts in capital markets, most studies do not consider that sell-side equity analysts often work in hierarchical teams. Lead analysts manage a team of associate and junior analysts who participate in the team’s tasks. Building on the delegation theory in the management literature, we hypothesize and find a division of labor between lead and associate analysts, where lead analysts are more likely to delegate tasks (1) that are less significant, (2) that are simpler, (3) when the workload of the lead analyst increases, and (4) when the associate analyst is more competent. Our results further suggest that associate analysts play a significant role in forecasting. By contrast, lead analysts are the main contributors to the qualitative aspects of analyst reports and are more likely to participate in earnings conference calls. Overall, our study documents the significant role of associate analysts in forecasting and the division of labor between lead and associate analysts.
I study the importance of alpha decay for the measurement of realized and conditional expected returns in asset pricing studies. Alpha decay refers to the reduction in abnormal expected returns (relative to an asset pricing model) in response to an anomaly becoming widely known among market participants. As decreases in alpha are associated (ceteris paribus) with positive realized returns, the econometrician may misinterpret these repricing returns as evidence that the anomaly will persist in the future. Because alpha decay is generally a nonstationary phenomenon, asset pricing tests that impose stationarity may lead to biased inference. I illustrate the importance of alpha decay using the most commonly studied anomalies in the asset pricing literature and find that the measured alpha differs from the true alpha by about 1.4% per year. I provide a simple formula to correct for this bias and show how to incorporate alpha decay tests into the standard asset pricing toolkit.
We formulate a dynamic no-arbitrage asset pricing model for equities and corporate bonds, featuring time variation in both risk aversion and economic uncertainty. The joint dynamics among cash flows, macroeconomic fundamentals, and risk aversion accommodate both heteroskedasticity and non-Gaussianity. The model delivers measures of risk aversion and uncertainty at the daily frequency. We verify that equity variance risk premiums are very informative about risk aversion, whereas credit spreads and corporate bond volatility are highly correlated with economic uncertainty. Our model-implied risk premiums outperform standard instruments for predicting asset excess returns. Risk aversion is substantially correlated with consumer confidence measures and in early 2020 reacted more strongly to new COVID cases than did an uncertainty proxy.
Choice-based demand estimation is a fundamental task in retail operations and revenue management, providing necessary input data for inventory control, assortment, and price-optimization models. The task is particularly difficult in operational contexts where product availability varies over time and customers may substitute into the available options. In addition to the classical multinomial logit (MNL) model and extensions (e.g., nested logit, mixed logit, and latent-class MNL), new demand models have been proposed (e.g., the Markov chain model), and others have been recently revisited (e.g., the rank list-based and exponomial models). At the same time, new computational approaches were developed to ease the estimation function (e.g., column-generation and expectation-maximization (EM) algorithms). In this paper, we conduct a systematic, empirical study of different choice-based demand models and estimation algorithms, including both maximum-likelihood and least-squares criteria. Through an exhaustive set of numerical experiments on synthetic, semisynthetic, and real data, we provide comparative statistics of the predictive power and derived revenue performance of an ample collection of choice models and characterize operational environments suitable for different model/estimation implementations. We also provide a survey of all the discrete choice models evaluated and share all our estimation codes and data sets as part of the online appendix.
We examine the ability of existing and new factor models to explain the comovements of G10 currency changes, measured using “currency baskets.” A clustering technique reveals a clear two-block structure in currency comovements, with the first block containing mostly the dollar currencies and the other the European currencies. A factor model incorporating this “clustering” factor and two additional factors, a commodity currency factor and a “world” factor based on trading volumes, fits currency basket correlations much better than extant factors, such as value and carry, do. In particular, it explains on average about 60% of currency variation and generates a root mean squared error relative to sample correlations of only 0.11. The model also fits comovements in emerging market currencies well. Economically, the correlations between currency baskets underlying the factor structure are inversely related to the physical distances between countries.
This paper examines whether tax uncertainty can alter investment decisions, focusing primarily on the timing of large capital investments. Empirically, we exploit the staggered implementation of Schedule UTP, a discrete policy change expected to increase tax uncertainty, finding that, on average, firms responded by delaying large capital investments. This effect is stronger among firms at which the policy treatment is particularly germane, that is, for firms with more material UTBs or with low-to-moderate quality public accounting information. We also test the underlying mechanism, finding that managers buffer against higher tax uncertainty with cheaper sources of financing (cash) and that the investment effect is concentrated among financially constrained firms. The results show that Schedule UTP also reduces the sensitivity of investment to growth opportunities (investment-Q sensitivity) in line with a higher hurdle rate for firms facing higher tax uncertainty.
We examine the impact of ambiguity, or Knightian uncertainty, on the capital structure decision, using a static tradeoff theory model in which agents are both ambiguity and risk averse. The model confirms the well-known result that greater risk—the uncertainty over outcomes—leads firms to decrease leverage. Conversely, the model indicates that greater ambiguity—the uncertainty over the probabilities associated with the outcomes—leads firms to increase leverage. Using a theoretically based measure of ambiguity, our empirical analysis presents evidence consistent with these notions, showing that ambiguity has an important and distinct impact on capital structure.
We highlight the complexities in estimating the valuation effects of board gender quotas by critically revisiting studies of Norway’s pioneering board gender-quota law. We use the short-run event study of Ahern and Dittmar [Ahern KR, Dittmar A (2012) The changing of the boards: The impact on firm valuation of mandated female board representation. Quart. J. Econom. 127(1):137–197] to illustrate (1) the difficulties in attributing quota-related news to specific dates, (2) the need to account for contemporaneous cross-correlation of stock returns when judging the statistical significance of event-related abnormal stock returns, and (3) the fundamental difficulty of separating quota-induced valuation effects from the influences of firm characteristics and macroeconomic events such as the financial crisis. We provide new evidence suggesting that the valuation effect of Norway’s quota law was statistically insignificant. Overall, our evidence suggests that, at the time of the Norwegian quota, the supply of qualified female director candidates was high enough to avoid the negative consequences of the quota highlighted previously in the literature.
Incorporating side observations in decision making can reduce uncertainty and boost performance, but it also requires that we tackle a potentially complex predictive relationship. Although one may use off-the-shelf machine learning methods to separately learn a predictive model and plug it in, a variety of recent methods instead integrate estimation and optimization by fitting the model to directly optimize downstream decision performance. Surprisingly, in the case of contextual linear optimization, we show that the naïve plug-in approach actually achieves regret convergence rates that are significantly faster than methods that directly optimize downstream decision performance. We show this by leveraging the fact that specific problem instances do not have arbitrarily bad near-dual-degeneracy. Although there are other pros and cons to consider as we discuss and illustrate numerically, our results highlight a nuanced landscape for the enterprise to integrate estimation and optimization. Our results are overall positive for practice: predictive models are easy and fast to train using existing tools; simple to interpret; and, as we show, lead to decisions that perform very well.
This paper studies financial statement consistency — the purported means to comparability — from an information perspective. We model consistency as firms’ required propensity to apply common accounting methods to individual transactions and show that consistency creates information spillover through correlated measurements (“spillover channel”) while potentially reducing the informativeness of one’s own report (“standalone channel”). The model generates two central predictions. First, optimal consistency decreases with a transaction’s fundamental correlation as high correlation diminishes information gains via the spillover channel. Second, optimal consistency decreases with a transaction’s fundamental volatility as high volatility exacerbates information losses via the standalone channel. Empirical evidence supports both predictions. Overall, this paper contributes a framework for studying comparability and draws useful policy implications.
This study investigates the impact of investor sentiment on excess equity return forecasting. A high (low) investor sentiment may weaken the connection between fundamental economic (behavioral-based nonfundamental) predictors and market returns. We find that although fundamental variables can be strong predictors when sentiment is low, they tend to lose their predictive power when investor sentiment is high. Nonfundamental predictors perform well during high-sentiment periods while their predictive ability deteriorates when investor sentiment is low. These paradigm shifts in equity return forecasting provide a key to understanding and resolving the lack of predictive power for both fundamental and nonfundamental variables debated in recent studies.
We examine whether firms’ political hedging activities are effective at mitigating political risk. Focusing on the risk induced by partisan politics, we measure political hedging as the degree to which firms’ political connections are balanced across Republican and Democratic candidates. We find that greater political hedging is associated with reduced stock return volatility, particularly during periods of higher policy uncertainty. Similarly, greater political hedging is associated with reduced crash risk, investment volatility, and earnings volatility. Moreover, the reduction in earnings volatility appears to relate to both a firm’s taxes and its operating activities, as we find that greater political hedging is associated with reduced cash effective tax rate volatility and pretax income volatility. We further find investors are better able to anticipate future earnings for firms that engage in political hedging, suggesting that political hedging helps improve firms’ information environments. Lastly, we perform an event study using President Obama’s Clean Power Plan. We find that on the days this policy proposal was debated in Congress, energy and utility firms experienced heightened intraday return volatility (relative to other firms and nonevent days). However, this heightened volatility is mitigated for energy and utility firms that are more politically hedged. Overall, we conclude that political hedging is an effective risk management tool that helps mitigate firm risk.
In this paper, we study a regretful seller’s problem of selling a fixed number of goods over a finite and known time horizon. The seller engages in counterfactual thinking to compare her selected price with other forgone alternatives. If a forgone alternative (ex post) generates a better outcome than the selected one, then the seller experiences regret. We characterize the pricing decision of a regretful seller and find that, although regret leads the seller to set a price that is lower than that set by an unbiased seller, the regretful seller employs decision policies whose structure is similar to those of the unbiased seller: the price decreases with the remaining inventory and increases with the time-to-go. Interestingly, we find that the seller who has a greater number of goods does not necessarily receive greater revenue.
I study the effects of language commonality (i.e., sharing a native language) on information production in financial markets. Using a hand-collected data set on the prevalent dialects for 2,091 cities (counties) in China, I identify the effects of language commonality separately from those of shared hometown and geographic proximity. In in-sample tests, language commonality between analysts and CEOs increases the return of trading on analysts’ recommendations by 5.5%. The results mainly stem from less intelligible dialects. Broadly speaking, language commonality can alleviate communication frictions when nonnative languages are used in professional settings.
We study the value of price discrimination in large social networks. Recent trends in industry suggest that, increasingly, firms are using information about social network to offer personalized prices to individuals based upon their positions in the social network. In the presence of positive network externalities, firms aim to increase their profits by offering discounts to influential individuals that can stimulate consumption by other individuals at a higher price. However, the lack of transparency in discriminative pricing may reduce consumer satisfaction and create mistrust. Recent research focuses on the computation of optimal prices in deterministic networks under positive externalities. We want to answer the question of how valuable such discriminative pricing is. We find, surprisingly, that the value of such pricing policies (increase in profits resulting from price discrimination) in very large random networks are often not significant. Particularly, for Erdös–Renyi random networks, we provide the exact rates at which this value decays in the size of the networks for different ranges of network densities. Our results show that there is a nonnegligible value of price discrimination for a small class of moderate-sized Erdös–Renyi random networks. We also present a framework to obtain bounds on the value of price discrimination for random networks with general degree distributions and apply the framework to obtain bounds on the value of price discrimination in power-law networks. Our numerical experiments demonstrate our results and suggest that our results are robust to changes in the model of network externalities.
The evaluation and selection of novel projects lies at the heart of scientific and technological innovation, and yet there are persistent concerns about bias, such as conservatism. This paper investigates the role that the format of evaluation, specifically information sharing among expert evaluators, plays in generating conservative decisions. We executed two field experiments in two separate grant-funding opportunities at a leading research university, mobilizing 369 evaluators from seven universities to evaluate 97 projects, resulting in 761 proposal-evaluation pairs and more than $250,000 in awards. We exogenously varied the relative valence (positive and negative) of others’ scores and measured how exposures to higher and lower scores affect the focal evaluator’s propensity to change their initial score. We found causal evidence of a negativity bias, where evaluators lower their scores by more points after seeing scores more critical than their own rather than raise them after seeing more favorable scores. Qualitative coding of the evaluators’ justifications for score changes reveals that exposures to lower scores were associated with greater attention to uncovering weaknesses, whereas exposures to neutral or higher scores were associated with increased emphasis on nonevaluation criteria, such as confidence in one’s judgment. The greater power of negative information suggests that information sharing among expert evaluators can lead to more conservative allocation decisions that favor protecting against failure rather than maximizing success.
This paper shows that debt undermines relational incentives and harms worker morale. We build a dynamic model of a manager who uses limited financial resources to simultaneously repay a creditor and motivate a worker. If the manager can divert or misuse revenue, then debt makes the manager less willing to follow through on promised rewards, leading to low worker effort. In profit-maximizing equilibria, the firm prioritizes repaying its debts, leading to gradual increases in effort and wages. These dynamics can persist even after debts have been fully repaid. Consistent with this analysis, we document that a firm’s financial leverage is negatively related to measures of employee morale, wages, and productivity.
A large experimental literature is devoted to studying discrimination. An important question for policymakers and firms is what drives the discrimination uncovered by those experiments. However, motivations are hard to determine when decision makers pay selective attention to information because their learning is private. We overcome this challenge by deriving conditions on average outcomes that reveal decision makers are prejudiced no matter what they learn about individuals in each demographic group before making their decisions. This provides a test of prejudice that is general, simple, and robust and that can potentially be used to identify prejudice in a wide range of important settings, such as hiring, consumer lending, and housing access. We demonstrate our test of prejudice using two influential labor market experiments.
Nonprofits regularly use conditional “thank you” gifts to entice prospective donors to give, yet experimental evidence suggests that their effects are mixed in practice. This paper uses multiple laboratory experiments to test when and why thank you gifts vary in effectiveness. First, we demonstrate that although gifts often increase donations to charities that donors did not rate highly, many of the same gifts had no effects or negative effects for charities that prospective donors already liked. We replicate these findings in a second experiment that uses a different range of charity and gift options as well as different measures of participant perceptions of a charity. We also find that making gifts optional, as is common in fundraising campaigns, does not eliminate these negative gift effects. In additional experiments, we directly test for donor motives using self-report and priming experiments. We find that thank you gifts increase (decrease) the weight that donors place on self-interested (prosocial) motives, leading to changes in donation patterns. Altogether, our results suggest that practitioners may find gifts more useful when appealing to donors not already familiar with or favorably inclined to their charity, such as during donor acquisition campaigns. They may be less useful when appealing to recent donors or others who already favor the charity, in part because the gift may activate mindsets or norms that emphasize self-interested motives instead of more prosocial, other-regarding motives.
How does deleveraging affect the market liquidity of high-embedded-leverage securities issued by financial institutions and the funding constraints of these institutions? We use the forced deleveraging of structured mutual funds during the 2015 Chinese stock market crash to study the effects of deleveraging. Our regression-discontinuity analysis shows that deleveraging significantly reduces the market liquidity of the deleveraging funds’ equity units. Moreover, our difference-in-differences analysis shows that deleveraging results in large decreases in subsequent fund flows, stock and cash holdings, and performance, with the impact channeled through the deterioration of the market liquidity of the fund’s equity units.
This paper broadens the focus of empirical research on salesforce management to include multitasking settings with multidimensional incentives, where salespeople have private information about customers. This allows us to ask novel substantive questions around multidimensional incentive design and job design while managing the costs and benefits of private information. To this end, the paper introduces the first structural model of a multitasking salesforce in response to multidimensional incentives. The model also accommodates (i) dynamic intertemporal tradeoffs in effort choice across the tasks and (ii) salesperson’s private information about customers. We apply our model in a rich empirical setting in microfinance and illustrate how to address various identification and estimation challenges. We extend two-step estimation methods used for unidimensional compensation plans by embedding a flexible machine learning (random forest) model in the first-stage multitasking policy function estimation within an iterative procedure that accounts for salesperson heterogeneity and private information. Estimates reveal two latent segments of salespeople—a hunter segment that is more efficient in loan acquisition and a farmer segment that is more efficient in loan collection. Counterfactuals reveal heterogeneous effects: hunters’ private information hurts the firm as they engage in adverse selection; farmers’ private information helps the firm as they use it to better collect loans. The payoff complementarity induced by multiplicative incentive aggregation softens adverse specialization by hunters relative to additive aggregation but hurts performance among farmers. Overall, task specialization in job design for hunters (acquisition) and farmers (collection) hurts the firm as adverse selection harm overwhelms efficiency gain.
In this paper, we investigate the impact of ownership structure on corporate advertising expenditures. Using mutual fund mergers as an exogenous shock to ownership structure, we find that competing firms owned by the same institutional blockholders experience a significant reduction in advertising expenditure. The reduction in advertising expenditure is more likely to occur in the presence of higher coordination benefits or lower coordination costs. Specifically, this effect is more pronounced for firms in more competitive industries, in higher advertising-intensity industries, with greater common ownership, with more concentrated institutional ownership, and with headquarters located in the same state. Overall, our empirical evidence indicates that ownership by common institutional investors significantly affects corporate advertising strategy.
We study taxi markets in Singapore to understand market entry in the field. Although market-entry games in the laboratory consistently produce equilibrium outcomes, we show that a lack of market knowledge hinders the markets from consistently reaching equilibrium in the field. In Singapore, a small, 720-square-kilometre island city that can be divided into 29 taxi markets, full equilibrium is elusive: 68% of the market-entry decisions made by the 2,728 taxi drivers in our data could be improved. Using three months of earnings and detailed movement data from these taxi drivers, we find an average 20% gap in marginal wage rates across markets. We use dynamic programming to derive the optimal solution for more than 3 million search decisions and find that only 32% of the searches ended in an optimal market. Finally, we find that market knowledge developed in a given month explains an additional 3% variation of the earning losses in the 2.6 million decisions for the subsequent two months, an improvement in model fit of 74%, whereas strategic thinking and minimization risk have no impact on earning loss.
We study decision behavior in the selection, forecasting, and production for a new product. In a stylized behavioral model and five experiments, we generate new insight into when and why this combination of tasks can lead to overconfidence (specifically, overestimating the demand). We theorize that cognitive limitations lead to noisy interpretations of signal information, which itself is noisy. Because people are statistically naive, they directly use their noisy interpretation of the signal information as their forecast, thereby underaccounting for the uncertainty that underlies it. This process leads to unbiased forecast errors when considering products in isolation, but leads to positively biased forecasts for the products people choose to launch due to a selection effect. We show that this selection-driven overconfidence can be sufficiently problematic that, under certain conditions, choosing the product randomly can actually yield higher profits than when individuals themselves choose the product to launch. We provide mechanism evidence by manipulating the interpretation noise through information complexity—showing that even when the information is equivalent from a Bayesian perspective, more complicated information leads to more noise, which, in turn, leads to more overconfidence in the chosen products. Finally, we leverage this insight to show that getting a second independent forecast for a chosen product can significantly mitigate the overconfidence problem, even when both individuals have the same information.
Firms’ use of special purpose acquisition companies (SPACs) to go public has increased dramatically, leading to market and regulatory debate about their use of projections. Examining SPAC mergers from 2004 through 2021, we find that 80% of firms provide projections for four years ahead on average, with approximately one-quarter of recent projections extending more than five years. For the sample of SPAC mergers with observable postmerger revenue, we find that only 35% of firms meet or beat their projections. This proportion declines for forecasts that are longer horizon, and nonserial SPAC sponsors miss forecasts by greater percentages. When we compare SPAC projected revenue growth with benchmark samples of firms completing an initial public offering (IPO) and matched firms, the SPAC projections are approximately three times larger on average than benchmark firms’ actual revenue growth, with even greater differences for long-term projections. After the merger, firms reduce their use of projections, providing them at statistically similar rates as benchmark firms. Overall, the evidence supports concerns that the SPAC merger includes highly optimistic projections.
We consider an online assortment optimization problem where we have n substitutable products with fixed reusable capacities c1,…,cn. In each period t, a user with some preferences (potentially adversarially chosen) who offers a subset of products, St, from the set of available products arrives at the seller’s platform. The user selects product j∈St with probability given by the preference model and uses it for a random number of periods, t˜j, that is distributed i.i.d. according to some distribution that depends only on j generating a revenue rj(t˜j) for the seller. The goal of the seller is to find a policy that maximizes the expected cumulative revenue over a finite horizon T. Our main contribution is to show that a simple myopic policy (where we offer the myopically optimal assortment from the available products to each user) provides a good approximation for the problem. In particular, we show that the myopic policy is 1/2-competitive, that is, the expected cumulative revenue of the myopic policy is at least half the expected revenue of the optimal policy with full information about the sequence of user preference models and the distribution of random usage times of all the products. In contrast, the myopic policy does not require any information about future arrivals or the distribution of random usage times. The analysis is based on a coupling argument that allows us to bound the expected revenue of the optimal algorithm in terms of the expected revenue of the myopic policy. We also consider the setting where usage time distributions can depend on the type of each user and show that in this more general case there is no online algorithm with a nontrivial competitive ratio guarantee. Finally, we perform numerical experiments to compare the robustness and performance of myopic policy with other natural policies.
Ignorance enables individuals to act immorally. This is well known in policy circles, in which there is keen interest in lowering moral ignorance. In this paper, we study how the demand for moral ignorance responds to monetary incentives and how the demand curve for ignorance reacts to social norm messages. We propose a simple behavioral model in which individuals suffer moral costs when behaving selfishly in the face of moral information. In several experiments, we find that moral ignorance decreases by more than 30 percentage points with small monetary incentives, but we find no significant change with social norm messages, and we document strong persistence of ignorance across moral contexts. Our findings indicate that rather simple messaging interventions may have limited effects on ignorance. In contrast, changes in incentives could be highly effective.
Many online platforms offer time-locked sales campaigns, whereby products are sold at fixed prices for prespecified lengths of time. Platforms often display some information about previous customers’ purchase decisions during campaigns. Using a dynamic Bayesian persuasion framework, we study how a revenue-maximizing platform should optimize its information policy for such a setting. We reformulate the platform’s problem equivalently by reducing the dimensionality of its message space and proprietary history. Specifically, three messages suffice: a neutral recommendation that induces a customer to make her purchase decision according to her private signal about the product and a positive (respectively (resp.), negative) recommendation that induces her to purchase (resp., not purchase) by ignoring her signal. The platform’s proprietary history can be represented by the net purchase position, a single-dimensional summary statistic that computes the cumulative difference between purchases and nonpurchases made by customers having received the neutral recommendation. Subsequently, we establish structural properties of the optimal policy and uncover the platform’s fundamental trade-off: long-term information (and revenue) generation versus short-term revenue extraction. Further, we propose and optimize over a class of heuristic policies. The optimal heuristic policy provides only neutral recommendations up to a cutoff customer and provides only positive or negative recommendations afterward, with the recommendation being positive if and only if the net purchase position after the cutoff customer exceeds a threshold. This policy is easy to implement and numerically shown to perform well. Finally, we demonstrate the generality of our methodology and the robustness of our findings by relaxing some informational assumptions.
Integrating inventory and assortment planning decisions is a challenging task that requires comparing the value of demand expansion through broader choice for consumers with the value of higher in-stock availability. We develop a stockout-based substitution model for trading off these values in a setting with inventory replenishment, a feature missing in the literature. Using the closed form solution for the single-product case, we develop an accurate approximation for the multiproduct case. This approximated formulation allows us to optimize inventory decisions by solving a fractional integer program with a fixed point equation constraint. When products have equal margins, we solve the integer program exactly by bisection over a one-dimensional parameter. In contrast, when products have different margins, we propose a fractional relaxation that we can also solve by bisection and that results in near-optimal solutions. Overall, our approach provides solutions within 0.1% of the optimal policy and finds the optimal solution in 80% of the random instances we generate.
We analyze the parallel lottery that is used to allocate hunting permits in the state of Alaska. Each participant is given tickets to distribute among lotteries for different types of items. Participants who win multiple items receive their favorite, and new winners are drawn from the lotteries with unclaimed items. When supply is scarce, equilibrium outcomes of parallel lotteries approximate a competitive equilibrium from equal incomes (CEEI), which is Pareto efficient. When supply is moderate, parallel lotteries exhibit two sources of inefficiency. First, some agents may benefit from trading probability shares. Second, outcomes may be “wasteful”: agents may receive nothing even if acceptable items remain unallocated. We bound both sources of inefficiency and show that each is eliminated by giving applicants a suitable number of tickets k: trades are never beneficial when k = 1, and waste is eliminated as k→∞. In addition, we show that the wastefulness of the k-ticket parallel lottery has some benefits: agents with strong preferences may prefer parallel lottery outcomes to those of any nonwasteful envy-free mechanism. These agents prefer small values of k, while agents with weak preferences prefer large values of k. Together, these results suggest that the k-ticket parallel lottery performs well under most circumstances and may be suitable for other settings where items are rationed.
We consider a sales effort management problem under an all-or-nothing constraint. The seller will receive no bonus/revenue if the sales volume fails to reach a predetermined target at the end of the sales horizon. Throughout the sales horizon, the sales process can be moderated by the seller through costly effort. We show that the optimal sales rate is nonmonotonic with respect to the remaining time or the outstanding sales volume required to reach the target. Generally, it has a watershed structure, such that for any needed sales volume, there exists a cutoff point on the remaining time above which the optimal sales rate decreases in the remaining time and below which it increases in the remaining time. We then study easy-to-compute heuristics that can be implemented efficiently. We start with a static heuristic derived from the deterministic analog of the stochastic problem. With an all-or-nothing constraint, we show that the performance of the static heuristic hinges on how the profit-maximizing rate fares against the target rate, which is defined as the sales target divided by the length of the sales horizon. When the profit-maximizing rate is higher than the target rate, the static heuristic adopting the optimal deterministic rate is asymptotically optimal with negligible loss. On the other hand, when the profit-maximizing rate is lower than the target rate, the performance loss of any asymptotically optimal static heuristic is of an order greater than the square root of the scale parameter. To address the poor performance of the static heuristic in the latter case, we propose a modified resolving heuristic and show that it is asymptotically optimal and achieves a logarithmic performance loss.
In the past two decades, many nursing homes converted their ownership status from nonprofit to for-profit (NP-to-FP). These conversions have drawn public scrutiny and triggered a debate about the implications of ownership conversions on nursing home performance. Exploring a nationwide panel data set of U.S. nursing homes from 2006 to 2017, we observe that nursing homes with higher financial distress are associated with higher likelihood of NP-to-FP conversions. The postconversion operating margins increased significantly. Converted nursing homes improved their financial performance by reducing operating costs while keeping net resident revenues unchanged. Both cutting registered nurse staffing and cutting overhead staffing contributed to reductions in operating costs; however, only the former cost-reduction measure had a negative impact on quality. On average, the postconversion quality of care declined. The effects of NP-to-FP conversions on nursing homes were moderated by preconversion financial distress: High-distress nursing homes aggressively cut registered nurse staffing and experienced severe quality decline, whereas low-distress ones kept registered nurse staffing unchanged and largely avoided quality decline. These findings lead to both policy and managerial insights. To nursing home regulators, we recommend increased oversight on NP-to-FP conversions of nursing homes with high preconversion financial distress. To managers of nursing homes undergoing NP-to-FP conversions, our findings suggest that although cost reduction is an effective strategy to improve financial performance, they need to avoid the pitfall of cutting registered nurse staffing and instead focus on streamlining overhead operations in order to increase operating efficiency without compromising quality.
We analyze the problem of a buyer who purchases a long-term project from one of several suppliers. A changing state of the world influences the costs of the suppliers. We distinguish between complete contracts conditioning on all future realizations of the state of the world and incomplete contracts renegotiated whenever the state of the world changes. We provide conditions such that incomplete contracting does not pose a problem. If the changing state of the world is publicly observable and the buyer cannot switch between suppliers during the lifetime of the project, the buyer achieves the same surplus irrespective of whether contracts are complete or incomplete. An English auction followed by renegotiation whenever the state of the world changes is optimal. To identify conditions when buyers should consider drafting complete contracts, we extend the analysis by considering private information about the changing state of the world and supplier switching. In both cases, incomplete contracting poses a problem. In a survey of procurement consultants, we confirm that publicly observable states of the world via price indexes play an important role in procurement. Moreover, the consultants confirm that supplier switching is infrequent in procurement practice. Thus, incomplete contracting is less of a problem in a considerable share of procurement projects. However, complete contracts are useful and could be used more often.
This paper reports two experiments in which attitudes toward temporal risk resolution is elicited from choices between two-outcome lotteries that pay out at some future fixed date and can be resolved either now or later. We show that matching probabilities provides a simple method to measure attitudes toward temporal resolution—via the utility scale—under the recursive expected utility of Kreps and Porteus. We also analyze our data using a general recursive model that can reveal attitudes toward temporal risk resolution through the utility scale and/or the probability weighting scale. In terms of goodness of fit, as well as of prediction accuracy, our results point to a better performance of the probability weighting approach. More specifically, we show that individuals become less sensitive and more pessimistic with respect to winning probabilities when lotteries are resolved later rather than now.
Communication is one of the most effective devices in promoting team cooperation. However, asymmetric communication sometimes breeds collusion and hurts team efficiency. Here, we present experimental evidence showing that excluding one member from team communication hurts team cooperation; the communicating partners collude in profit allocation against the excluded member, and the latter reacts by exerting less effort. Allowing the partners to reach out to the excluded member partially restores cooperation and fairness in profit allocation, but it does not stop the partners from talking behind that member’s back even when they could have talked publicly. The partners sometimes game the system by tricking the excluded member into contributing but then grabbing all profits for themselves.
Probability weighting is a major concept for accommodating systematic departures from expected utility theory. We examine the relation between probability weighting and cognitive ability with two experiments: one recruiting subjects with a large variation in cognitive ability and the other using the within-subject manipulation of time constraints in lottery choices and cognitive tests. We find a significant association between likelihood insensitivity—the cognitive component of probability weighting—and cognitive limitation such that subjects with a lower cognitive score or more interrupted cognition due to time pressure respond less discriminately to intermediate probabilities and more over-sensitively to extreme probabilities. Our findings shed light on the sources of anomalous choices against expected utility theory.
There is an ongoing debate regarding the degree to which a forecaster’s ability to draw correct inferences from market signals is real or illusory. This paper attempts to shed light on the debate by examining how personal characteristics do or do not affect forecaster success. Specifically, we investigate the role of fluid intelligence, manipulativeness, and theory of mind on forecast accuracy in experimental asset markets. We find that intelligence improves forecaster performance when market mispricing is low, manipulativeness improves forecaster performance when mispricing is high, and the degree to which theory of mind skills matter depends on both the level of mispricing and how information is displayed. All three of these results are consistent with hypotheses derived from the previous literature. Additionally, we observe that male forecasters outperform female forecasters after controlling for intelligence, manipulativeness, and theory of mind skills as well as risk aversion. Interestingly, we do not find any evidence that forecaster performance improves with experience across markets or within markets.
In social trading, less experienced investors (followers) are allowed to copy the trades of experts (traders) in real time after paying a fee. Such a copy-trading mechanism often runs into a transparency-revenue tension. On the one hand, social trading platforms need to release traders’ trades as transparently as possible to allow followers to evaluate traders accurately. On the other hand, complete transparency may undercut the platform’s revenue because followers can free ride. That is, followers can manually copy the trades of a trader to avoid paying the following fees. This study addresses this critical tension by optimizing the level of transparency through delaying the release of trading information pertaining to the trades executed by traders. We capture the economic impact of the delay using the notions of profit-gap and delayed-profit. We propose a mechanism that elucidates the economic effects of the profit-gap and delayed-profit on followers and, consequently, the amount of money following a trader: protection effect and evaluation effect. Empirical investigations find support for these two effects. We then develop a stochastic control formulation that optimizes platform revenue, where the control is the optimal delay customized at the trader level and calculated as a function of the current amount of money following a trader and the number of views on the trader’s profile page. The optimized revenue can be incorporated into an algorithm to provide a systematic way to infuse the platform’s goals into the ranking of the traders. A counterfactual study is conducted to demonstrate the performance of the optimal delay policy (versus a constant-delay policy) using data from a leading social trading platform operating in the foreign exchange market.
Digital extortion has emerged as a significant threat to organizations that rely on information technologies for their operations. Using human subject experimentation, we study the effectiveness of message appeals in encouraging defenders to adopt two mitigation strategies, investment in security and refusal to pay ransoms, to digital extortion threats. We explore two types of appeals, benefit and normative, for this purpose. We find that the decisions of the defenders (representing any organization that can be a potential victim) deviate from the predictions of game theory. However, given the strategic interactions between the defenders and the attacker as well as noisy decision-making behaviors, it is challenging to untangle the influence of the appeals on the defenders. We develop a structural model based on the quantal response equilibrium framework to measure how message appeals change the defenders’ utilities of investment and payment refusal. Although the interventions may be successful in increasing the utilities of investment and/or payment refusal, their impacts on investment rate and payment rate are mitigated by the attacker reducing ransoms. Thus, it is challenging for an intervention to significantly boost a community’s investment rate or to suppress the ransom payment rate. We characterize how security outcomes of a community (including expected ransom, attack rate, investment rate, and payment rate) vary with the defenders’ utilities of investment and pay refusal.
Coordinated action within and beween organizations is easier when individuals share communication codes—mappings between stimuli and labels. Because codes are specific to the groups within which they arise as conventions, collaboration across organizational units that have developed their own distinctive codes is often difficult. However, not all code differences are equal in their implications for communication difficulty and the capacity of individuals starting out with different codes to develop a shared code. Using computational models, we develop a theory about the nature of differences in initial communication codes and how they impact convergence on a common code. Our results show that the difficulty of code convergence lies not as much in learning new codes as in unlearning existing ones. The most severe challenges to communication stem from “code clashes” where codes contain different mappings between the same labels and stimuli. Furthermore, clashes that arise when agents have developed their individual codes in different task environments but draw on a common set of labels are likely to be the hardest to recover from, reflecting the perils of being “separated by a common language.”
We theorize that status awards will have a disciplining effect on evaluators, changing how they evaluate. Specifically, status awards will lead evaluators to place less weight on unreliable indicators of candidate quality, such as gender. We test this theory using data from restaurant evaluations on Yelp, focusing on the relationship between an evaluator’s restaurant rating and their reporting of being served by a man or a woman in their review text. We use Yelp’s evaluator status award (“Elite”) to analyze whether observed gender bias in the star ratings given to restaurants decreases after an evaluator receives this status award. We find that evaluators rate restaurants more similarly after receiving the award, regardless of whether they report being served by a man or a woman. Status awards in our context close the gender gap in restaurant ratings by 56.5% (a 0.07 stars improvement out of an initial rating gap of −0.13 stars). This reduction in gender bias is mostly due to a decrease in the number of extremely low (1 star) ratings in reviews that reference female servers. Research on status and evaluations has mostly focused on how evaluators react to increases in candidate status. We demonstrate the importance of evaluator status as a mechanism for decreasing observed gender differences in evaluations.
In this paper, we study the impact of labor unions on product quality failures. We use a product recall as our measure of quality failure because it is an objective metric that is applicable to a broad cross-section of industries. Our analysis employs a union panel setting and close union elections in a regression discontinuity design framework to overcome identification issues. In the panel regressions, we find that firms that are unionized and those that have higher unionization rates experience a greater frequency of quality failures. The results obtain even at a more granular establishment level in a subsample in which we can identify the manufacturing establishment associated with the recalled product. When comparing firms in close elections, we find that firms with close union wins are followed by significantly worse product quality outcomes than those with close union losses. These results are amplified in non–right-to-work states, where unions have a relatively greater influence on the workforce. We find that unionization increases firms’ costs and operating leverage and, consequently, crowds out investments that potentially impact quality. We also find some suggestive evidence that unions may compromise quality by hurting employee morale and by resisting technological upgrades in the firm. Overall, our results suggest that unions have an adverse impact on product recalls, and thus, product quality is an important dimension along which unions impact businesses.
We introduce risk-averse bidders in a security-bid auction to analyze how the security design affects bidders’ equilibrium behavior and, as a result, the revenue and efficiency of the auction. We show that steeper securities provide more insurance because they allow bidders to smooth payoffs across realizations. Such insurance levels the playing field for more-risk-averse bidders, inducing them to bid more aggressively. As a consequence, the auction’s allocative efficiency weakly increases when the seller switches from a flatter to a steeper security. Furthermore, we prove that when bidders are homogeneously and sufficiently risk averse, the only security that guarantees Pareto efficiency is the steepest, that is, a call option. We also determine the relationship between the security design and the auction format. In particular, we show that for convex and superconvex families of securities, the first-price auction yields higher expected revenues, provided a technical condition, whereas for subconvex families, the second price yields higher expected revenues, provided that bidders are moderately risk averse. Finally, we show that steeper securities also attract higher entry from an ex ante perspective, when entry is costly, and discuss the effects that the presence of risk aversion has on informal auctions.
Accurate cost information is critical to effective decision making within organizations. Cost computations often rely on subjective judgments by employees regarding the amount of time that different tasks consume. In an experimental setting, we examine the accuracy of two common approaches to eliciting subjective time estimates vital for accurate cost information. Specifically, we compare estimation error when employees estimate (i) the total time for all iterations of a task (the pool approach) versus (ii) the average time for one iteration of a task (the unit approach). These two approaches have received interest by both practitioners and researchers and are at the heart of the difference between conventional activity-based costing (ABC) and time-driven ABC. While mathematically equivalent, we hypothesize and find that the two approaches evoke different cognitive processes that lead to differences in estimation error. Relative to the unit approach, the pool approach produces larger error in the allocation of time among different tasks, but only when the number of iterations per task varies across tasks. Further, the pool approach results in overestimation of productive time, whereas the unit approach leads to underestimation of productive time. Our findings are robust to different response modes of the pool approach (estimates in absolute time units and in percentages). This study is relevant for designers and users of cost and performance-measurement systems in that allocation errors lead to cost cross-subsidization and poor resource-allocation decisions, while overall errors undermine capacity utilization decisions.
We compare the ability of dictionary-based and machine-learning methods to capture disclosure sentiment at 10-K filing and conference-call dates. Like Loughran and McDonald [Loughran T, McDonald B (2011) When is a liability not a liability? Textual analysis, dictionaries, and 10-Ks. J. Finance 66(1):35–65.], we use returns to assess sentiment. We find that measures based on machine learning offer a significant improvement in explanatory power over dictionary-based measures. Specifically, machine-learning measures explain returns at 10-K filing dates, whereas measures based on the Loughran and McDonald dictionary only explain returns at 10-K filing dates during the time period of their study. Moreover, at conference-call dates, machine-learning methods offer an improvement over the Loughran and McDonald dictionary method of a greater magnitude than the improvement of the Loughran and McDonald dictionary over the Harvard Psychosociological Dictionary. We further find that the random-forest-regression-tree method better captures disclosure sentiment than alternative algorithms, simplifying the application of the machine-learning approach. Overall, our results suggest that machine-learning methods offer an easily implementable, more powerful, and reliable measure of disclosure sentiment than dictionary-based methods.
The purpose of our study is to further understand managerial incentives that affect the volatility of reported earnings. Prior research suggests that the volatility of fourth-quarter earnings may be affected by the integral approach to accounting (i.e., “settling up” of accrual estimation errors in the first three quarters of the fiscal year) or earnings management to meet certain reporting objectives (e.g., analyst forecasts). We suggest that another factor affecting fourth-quarter earnings is managers’ intentional smoothing of fiscal-year earnings. For each firm, we create pseudo-year earnings using four consecutive quarters other than the four quarters of the reported fiscal year. We then compare the earnings volatility of pseudo years to the earnings volatility of the firm’s own reported fiscal year. We find evidence consistent with fourth-quarter accruals reflecting managerial incentives to smooth fiscal-year earnings. This conclusion is validated by several cross-sectional tests, the pattern in quarterly cash flows and accruals, and several robustness tests. Overall, we contribute to the literature exploring alternative explanations for the differential volatility of fiscal-year and fourth-quarter earnings.
Voluntary environmental certification programs have been a popular tool used by governments, industry groups, and nonprofit organizations alike. A central question in the design of such programs is who should pay for them. In a context where firms respond strategically to a certification, the answer to this question is a priori ambiguous and, ultimately, empirical. This paper provides important insights on this question using ENERGY STAR, a voluntary certification program for energy-efficient products, as a case study. I show that firms are highly strategic with respect to this certification and extract consumer surplus associated with certified products via three mechanisms. They offer products that bunch at the certification requirement, differentiate certified products in the energy and nonenergy dimensions, and charge a price premium on certified products. I use these findings to motivate a structural econometric model with firms’ strategic behaviors with respect to product line and pricing decisions and to investigate the incidence of a certification licensing fee to fund the certification program.
From business to politics and academia, the economic effects of gender quotas are under scrutiny. We provide new causal evidence based on the introduction of mandatory gender quotas for boards of directors of Italian listed companies. Exploiting staggered board elections, we find that quotas are associated with a new selection of board members, characterized by higher education and lower age, and no significant costs on firm performance or the stock market.
Employee turnover is a significant cost for businesses and a key human capital metric, but firms do not disclose this measure. We examine whether turnover is informative about future firm performance using a large panel of turnover data extracted from employees’ online profiles. We find that turnover is negatively associated with future financial performance (one-quarter ahead return on assets and sales growth). The negative association between turnover and future performance is stronger for small firms, for young firms, for firms with low labor intensity, when the local labor market is tight, and when the firm is trying to replace departing employees. The negative association disappears when turnover is very low, suggesting that a certain amount of turnover can be beneficial. Consistent with the concern that turnover increases operational uncertainty, we find a positive association between turnover and the uncertainty of future financial performance. Finally, we find a significant association between turnover and future stock returns, suggesting that investors do not fully incorporate turnover information. Our findings answer the call from the Securities and Exchange Commission to determine the importance of turnover disclosure.
We develop a data-driven decision model to improve process quality in manufacturing. A challenge for traditional methods in quality management is to handle high-dimensional and nonlinear manufacturing data. We address this challenge by adapting explainable artificial intelligence to the context of quality management. Specifically, we propose the use of nonlinear modeling with Shapley additive explanations to infer how a set of production parameters and the process quality of a manufacturing system are related. Thereby, we contribute a measure of process importance based on which manufacturers can prioritize processes for quality improvement. Grounded in quality management theory, our decision model selects improvement actions that target the sources of quality variation. The decision model is validated in a real-world application at a leading manufacturer of high-power semiconductors. Seeking to improve production yield, we apply our decision model to select improvement actions for a transistor chip product. We then conduct a field experiment to confirm the effectiveness of the improvement actions. Compared with the average yield in our sample, the experiment returns a reduction in yield loss of 21.7%. Furthermore, we report on results from a postexperimental rollout of the decision model, which also resulted in significant yield improvements. We demonstrate the operational value of explainable artificial intelligence by showing that critical drivers of process quality can go undiscovered by the use of traditional methods.
The growing adoption of virtual queues in the service and retail industries has been greatly accelerated in recent times. In collaboration with a major ride-sharing platform, we study how the wait time information (WTI), both its initial magnitude and its subsequent progress over time, impacts customers’ abandonment behavior in virtual queues. The study was conducted through a randomized field experiment that included 1,425,745 rides: one-third of the rides received a neutral WTI, one-third received an optimistic WTI shorter than the neutral WTI (hence less frequent updates), and one-third received a pessimistic WTI (hence more frequent updates). The underlying wait time did not vary across the three groups. We find that both the magnitude of the initial WTI and the update frequency of the WTI have a significant impact on customer abandonment. Specifically, when adjusting the initial WTI by one minute, it did not impact customer abandonment. This is because the magnitude effect of the initial WTI is cancelled out by the opposite update-frequency effect. However, when adjusting the WTI by more than one minute, the magnitude effect dominates: when comparing the pessimistic WTI of four minutes with the neutral initial WTI of two minutes, five minutes with three minutes, and eight minutes with five minutes, customers’ likelihood to abandon increases by 6.2%, 14.1%, and 19.6%, respectively. Similar but opposite effects are found when comparing the optimistic WTI with the neutral WTI. We discuss how firms can use our findings and insights to design and operate better virtual queues.
We study a new parts-procurement planning problem that is motivated by a global auto manufacturer (GAM) that practices mass customization. Because of the astronomically large number of producible configurations, forecasting their demand is impossible. Instead, firms forecast demand for options that constitute a vehicle. Requirements for many parts (up to 60%) are based on the combinations of options in a fully configured vehicle. The options’ forecast, however, does not map into a unique configuration-level forecast. As a result, the options’ forecast translates into ranges for many parts’ requirements. The combined ranges of a set of parts are not always equal to the sum of the component ranges; they may be less. Determining parts ranges is a large-scale NP-hard problem. Large ranges and inaccurate calculation of these ranges can result in excess inventories, shortages in inventories, and suboptimal flexibility levels. We model and analyze the problem of allocating parts to suppliers and accurately computing the ranges to minimize procurement costs arising because of ranges. The range costs are assumed to be convex increasing. We perform extensive numerical analysis using a large set of randomly generated instances as well as eight industrial instances received from GAM to establish the quality of our approximation framework. Our proposed approach significantly reduces the error in range estimates relative to current industry practice. In addition, the proposed approach for allocations of parts to suppliers reduces joint-parts ranges by an average of 29.87% relative to that of current practice.
Practitioners and academics alike have argued that a firm’s interest in its short-term capital market valuation (short-termism) is harmful to the firm’s long-term profit. Their argument is intuitive—when a firm exhibits short-termism, its decision making will cater to the short term at the expense of the long term. Some practitioners claim that the adverse effects of increased short-termism become particularly acute in competitive markets. However, there is little academic research that examines the compound effect of short-termism and competition on a firm’s operational choices and long-term profit. In this paper, we provide a rigorous analytical model to examine how short-termism and competition can interact to induce a firm to distort its capacity investment and affect its long-term profit. We model a firm that has private information about its market demand, which can be either high or low and is captured by the firm’s type. Signaling this private information can influence both the investor’s valuation and the competitor’s entry decision. We find that operational distortion can emerge not only when short-termism is large, but also when it is small. In fact, when short-termism is sufficiently small, both firm types will distort their operational decision by underinvesting in a pooling outcome. We show, however, that the impact of short-termism on a firm’s long-term profit is not monotonically negative, and a certain level of short-termism can be beneficial to a firm’s long-term profit. The positive impact of incremental short-termism is robust to alternative modeling assumptions, including the form of competition and the investor’s risk profile.
Problems concerning dynamic learning and decision making are difficult to solve analytically. We study an infinite-horizon discrete-time model with a constant unknown state that may take two possible values. As a special partially observable Markov decision process (POMDP), this model unifies several types of learning-and-doing problems such as sequential hypothesis testing, dynamic pricing with demand learning, and multiarmed bandits. We adopt a relatively new solution framework from the POMDP literature based on the backward construction of the efficient frontier(s) of continuation-value vectors. This framework accommodates different optimality criteria simultaneously. In the infinite-horizon setting, with the aid of a set of signal quality indices, the extreme points on the efficient frontier can be linked through a set of difference equations and solved analytically. The solution carries structural properties analogous to those obtained under continuous-time models, and it provides a useful tool for making new discoveries through discrete-time models.
This study provides the first large-sample archival evidence on the impact of three commonly used accounting performance goals (thresholds, targets, and maximums) in CEO compensation contracts on corporate risk taking. Using proxy statement disclosure on performance goals for CEOs of U.S. public companies, we find that lower thresholds and higher maximums are associated with greater corporate risk taking, and these results are more pronounced when CEOs have greater incentives to achieve accounting performance goals or have lower innate risk aversion. In addition, we find that target difficulty is not significantly associated with corporate risk taking after controlling for thresholds and maximums. Finally, we find that CEO compensation contracts are more likely to have lower thresholds and higher maximums when risk taking is more value-enhancing or when R&D investment is more profitable, consistent with boards setting performance goals to induce an appropriate amount of corporate risk taking. Our study contributes to the accounting literature on target setting and corporate risk taking by identifying accounting performance goals as a tool in executive compensation contract design to influence risk taking.
Many innovative products are designed to satisfy the demand of specific target consumers; thus, the innovators will inevitably compete with each other in the product market. We investigate how a profit-maximizing principal should properly allocate her limited resources to support the innovations of multiple potentially competing innovators. We find that, as the available resources increase, the optimal diversification of investment may first increase and then decrease. This interesting nonmonotone pattern is driven by a trade-off between the risk of innovation failure and rent dissipation because of competition. Using this framework, we also analyze a nonprofit principal seeking to maximize the total number of successful innovations, the probability of at least one innovator succeeding, consumer surplus, and total social welfare. A nonprofit principal tends to invest more diversely compared with a for-profit counterpart.
Could introducing a tiny interest rate on positive balances of checking accounts affect investment decisions? We suggest, counterintuitively, that it might decrease allocations to checking accounts and increase riskless investments with higher returns. This violation of monotonicity is a potential outcome of a novel behavioral phenomenon that we formalize and investigate experimentally. It posits that even a small interest rate highlights or turns on the safe gains dimension, bumping up its decision weight while shrouding other considerations, such as liquidity. Consequently, choices may shift from the most liquid option, the checking account, to safe investments with superior returns. Our exploration of this phenomenon covers three different choice environments: investment decisions, social preferences, and choice under uncertainty.
This paper studies how globalization affects the corporate tax policies of U.S. manufacturing firms. Using U.S.-granting China Permanent Normal Trade Relations as a quasi-natural experiment, we find a significant increase in tax reduction activities for firms facing higher exposure to Chinese imports. The effect is more pronounced for firms with higher managerial slack. We also find that the effect is stronger for firms in less diversified products market and faster changing industries. We also show that U.S. firms facing higher Chinese import competition are more likely to engage in other tax-motivated activities: acquisition of subsidiaries in low-tax regions and suspected transfer pricing. Furthermore, we explore the 2017 tax cut and the recent U.S.-China trade dispute and find that firms engage less in tax reduction activities after the 2017 tax cut and after the tariff increase for Chinese imports.
Using a network approach that circumvents well-known challenges in estimating peer effects, we show that interactions with a firm’s geographic neighbors play a significant causal role in corporate investment behavior and a modest role in financial policies and firm performance. Moreover, these geography network effects are almost entirely driven by propagation effects through product market and supply chain networks. We corroborate our findings in a quasi-experimental framework that allows for spillovers in treatment effects. Our findings help rationalize industrial clusters (e.g., Silicon Valley), as they illustrate that agglomeration economies are substantial and operate predominantly within industry boundaries.
Diversification is a fundamental concept in economics and finance. This paper argues that decision makers have an intrinsic preference for diversification that is responsive to cost and that this willingness to pay for diversification is driven by risk aversion and loss aversion. In an experiment replicating a portfolio choice problem, the value of diversification is estimated to be at 5% of the initial endowment of approximately $100. Moreover, risk-averse and loss-averse individuals are willing to pay more for diversification. These findings point to the idea that diversification is a fundamental preference and may help explain portfolio choice anomalies such as irrational diversification, the diversification bias, and overdiversification.
We examine how childcare inequalities in the home affect the work productivity of female talent, using unique data on the family structures of hedge fund managers and the exogenous shock from school closures during the early COVID-19 pandemic response. We find that female managers’ ability to generate abnormal returns is curbed by 9% on average in the shock-month of school closures, providing a direct measure of the cost of unpaid care work. This effect is driven by mothers and especially mothers with young children. With increasing calls for more female representation in all layers of the economy and the efforts exerted toward that goal, there is reason for concern that these efforts might not factor in as the pandemic has uncovered how women in general and mothers in particular bear both the burden of unpaid care work and the subsequent cost to their paid work.
Using proxy statement data describing the terms of compensation contracts, we examine how overlapping membership between compensation and audit committees influences the use of earnings metrics in compensation. Although research predicts that such overlap could either increase or decrease the reliance on earnings, we find that firms with overlapping directors rely less on earnings-based performance measures in incentive contracts without altering the overall level of performance-contingent cash bonuses. In addition, we provide evidence that firms substitute earnings measures with measures less subject to earnings management. Our findings are robust to potential alternative explanations, extend to an implicit relation between earnings and compensation for a larger sample, and are not driven by the tendency toward an overlapping committee structure more broadly.
I study the information asymmetry effects of Statement of Financial Accounting Standards Number 161 (SFAS 161), which requires changes to the content and format of derivative and hedging footnote disclosures. Using a difference-in-differences design, I investigate whether these mandatory disclosure changes affected bid-ask spreads. To capture the extent to which firms were likely impacted by SFAS 161, I employ two complementary measures: (1) actual changes in firms’ derivative and hedging disclosures, and (2) pre-SFAS 161 levels of firms’ derivative and hedging activities. Both measures provide consistent evidence that bid-ask spreads decreased more for firms whose disclosures were more likely affected by SFAS 161. I also find that increased qualitative information and more disaggregated quantitative data (i.e., disclosure content) matter more than disclosure grouping and tabular display (i.e., disclosure format) for the observed decrease in bid-ask spreads. Overall, my findings suggest that the disclosure changes required by SFAS 161 reduced information asymmetry among investors regarding the firm value effects of derivative and hedging activities. These results may prove useful to regulators and standard setters as they consider disclosure requirements in other contexts.
This paper introduces the index τ=lnβ/lnδ as a measure of time inconsistency and vulnerability to self-control problems in the quasi-hyperbolic, beta-delta (β,δ) discounting model. We provide a preference foundation for τ and, consequently, a revealed preference definition of failed self-control. The τ index is independent of utility and has an intuitive interpretation as the maximum number of future selves who can disagree with the current self with respect to uniform deviations from an intertemporal plan. The index is also computable for continuous discount functions after an appropriate mapping of functions onto the (β,δ) family. The τ index thus provides a common yardstick for comparing temporal inconsistency across different functional forms.
We investigate the effects of group identity on hiring decisions with adverse selection problems. We run a laboratory experiment in which employers cannot observe a worker’s ability or verify the veracity of the ability the worker claims to have. We evaluate whether sharing an identity results in employers discriminating in favor of ingroup workers and whether it helps workers and employers overcome the adverse selection problem. We induce identities using the minimal group paradigm and study two settings: one in which workers cannot change their identity and one in which they can. Although sharing a common identity does not make the worker’s claims more honest, employers strongly discriminate in favor of ingroup workers when identities are fixed. Discrimination cannot be explained by employers’ beliefs and, hence, seems to be taste-based. When possible, few workers change their identity. However, the mere possibility of changing identities erodes the employers’ trust toward ingroup workers and eliminates discrimination.
Leadership theories in sociology and psychology argue that effective leaders influence follower behavior not only through the design of incentives and institutions, but also through personal abilities to persuade and motivate. Although charismatic leadership has received considerable attention in the management literature, existing research has not yet established causal evidence for an effect of leader charisma on follower performance in incentivized and economically relevant situations. We report evidence from field and laboratory experiments that investigate whether a leader’s charisma—in the form of a stylistically different motivational speech—can induce individuals to undertake personally costly but socially beneficial actions. In the field experiment, we find that workers who are given a charismatic speech increase their output by about 17% relative to workers who listen to a standard speech. This effect is statistically significant and comparable in size to the positive effect of high-powered financial incentives. We then investigate the effect of charisma in a series of laboratory experiments in which subjects are exposed to motivational speeches before playing a repeated public goods game. Our results reveal that a higher number of charismatic elements in the speech can increase public good contributions by up to 19%. However, we also find that the effectiveness of charisma varies and appears to depend on the social context in which the speech is delivered.
Recent scholarship argues that experimentation should be the organizing principle for entrepreneurial strategy. Experimentation leads to organizational learning, which drives improvements in firm performance. We investigate this proposition by exploiting the time-varying adoption of A/B testing technology, which has drastically reduced the cost of testing business ideas. Our results provide the first evidence on how digital experimentation affects a large sample of high-technology start-ups using data that tracks their growth, technology use, and products. We find that, although relatively few firms adopt A/B testing, among those that do, performance improves by 30%–100% after a year of use. We then argue that this substantial effect and relatively low adoption rate arises because start-ups do not only test one-off incremental changes, but also use A/B testing as part of a broader strategy of experimentation. Qualitative insights and additional quantitative analyses show that experimentation improves organizational learning, which helps start-ups develop more new products, identify and scale promising ideas, and fail faster when they receive negative signals. These findings inform the literatures on entrepreneurial strategy, organizational learning, and data-driven decision making.
Management scientists recognize that decision making depends on the information people have but lack a unified behavioral theory of the demand for (and avoidance of) information. Drawing on an existing theoretical framework in which utility depends on beliefs and the attention paid to them, we develop and test a theory of the demand for information encompassing instrumental considerations, curiosity, and desire to direct attention to beliefs one feels good about. We decompose an individual’s demand for information into the desire to refine beliefs, holding attention constant, and the desire to focus attention on anticipated beliefs, holding these beliefs constant. Because the utility of resolving uncertainty (i.e., refining beliefs) depends on the attention paid to it and more important or salient questions capture more attention, demand for information depends on the importance and salience of the question(s) it addresses. In addition, because getting new information focuses attention on one’s beliefs and people want to savor good news and ignore bad news, the desire to obtain or avoid information depends on the valence (i.e., goodness or badness) of anticipated beliefs. Five experiments (n = 2,361) test and find support for these hypotheses, looking at neutrally valenced as well as ego-relevant information. People are indeed more inclined to acquire information (a) when it feels more important, even if it cannot aid decision making (Experiments 1A and 2A); (b) when a question is more salient, manipulated through time lag (Experiments 1B and 2B); and (c) when anticipated beliefs have higher valence (Experiment 2C).
Using a panel of credit default swap (CDS) spreads and supply chain links, we observe that both favorable and unfavorable credit shocks propagate through supply chains in the CDS market. Particularly, the three-day cumulative abnormal CDS spread change (CASC) is 63 basis points for firms whose customers experienced a CDS up-jump event (an adverse credit shock). The value is 74 basis points if their suppliers experienced a CDS up-jump event. The corresponding three-day CASC values are –36 and –38 basis points, respectively, for firms whose customers and suppliers, respectively, experienced an extreme CDS down-jump event (a favorable credit shock). These effects are approximately twice as large for adverse credit shocks originating from natural disasters. Credit shock propagation is absent in inactive supply chains and is amplified if supply chain partners are followed by the same analysts. Industry competition and financial linkages between supply chain partners, such as trade credit and large sales exposure, amplify the shock propagation along supply chains. Strong shock propagation persists through second and third supply chain tiers for adverse shocks but attenuates for favorable shocks.
How do innovative firms react when existing products experience negative shocks? We explore this question with detailed project-level data from drug development firms. Using the Food and Drug Administration public health advisories as idiosyncratic negative shocks to approved drugs, we examine how drug makers react through investment decisions. Following these shocks, affected firms increase research and development (R&D) expenditures, driven by a higher likelihood of acquiring external innovations rather than developing novel projects internally. Such acquisition activities are concentrated in firms with weak research pipelines. We also find that competing developers move resources away from the affected therapeutic areas. Our results show how investments in specialized commercialization capital create path dependencies and alter the direction of R&D investments.
Nonprofit crowdsourcing platforms such as food recovery organizations rely on volunteers to perform time-sensitive tasks. Thus, their success crucially depends on efficient volunteer utilization and engagement. To encourage volunteers to complete a task, platforms use nudging mechanisms to notify a subset of volunteers with the hope that at least one of them responds positively. However, because excessive notifications may reduce volunteer engagement, the platform faces a tradeoff between notifying more volunteers for the current task and saving them for future ones. Motivated by these applications, we introduce the online volunteer notification problem, a generalization of online stochastic bipartite matching where tasks arrive following a known time-varying distribution over task types. Upon arrival of a task, the platform notifies a subset of volunteers with the objective of minimizing the number of missed tasks. To capture each volunteer’s adverse reaction to excessive notifications, we assume that a notification triggers a random period of inactivity, during which she will ignore all notifications. However, if a volunteer is active and notified, she will perform the task with a given pair-specific match probability that captures her preference for the task. We develop an online randomized policy that achieves a constant-factor guarantee close to the upper bound we establish for the performance of any online policy. Our policy and hardness results are parameterized by the minimum discrete hazard rate of the interactivity time distribution. The design of our policy relies on sparsifying an ex ante feasible solution by solving a sequence of dynamic programs. Furthermore, in collaboration with Food Rescue U.S., a volunteer-based food recovery platform, we demonstrate the effectiveness of our policy by testing it on the platform’s data from various locations across the United States.
We study the classic multiperiod joint pricing and inventory control problem in a data-driven setting. In this problem, a retailer makes periodic decisions on the prices and inventory levels of a product that she wishes to sell. The retailer’s objective is to maximize the expected profit over a finite horizon by matching the inventory level with a random demand, which depends on the price in each period. In reality, the demand functions or random noise distributions are usually difficult to know exactly, whereas past demand data are relatively easy to collect. We propose a data-driven approximation algorithm that uses precollected demand data to solve the joint pricing and inventory control problem. We assume that the retailer does not know the noise distributions or the true demand functions; instead, we assume either she has access to demand hypothesis sets and the true demand functions can be represented by nonnegative combinations of candidate functions in the demand hypothesis sets, or the true demand function is generalized linear. We prove the algorithm’s sample complexity bound: the number of data samples needed in each period to guarantee a near-optimal profit is O(T6ϵ−2log T), where T is the number of periods, and ϵ is the absolute difference between the expected profit of the data-driven policy and the expected optimal profit. In a numerical study, we demonstrate the construction of demand hypothesis sets from data and show that the proposed data-driven algorithm solves the dynamic problem effectively and significantly improves the optimality gaps over the baseline algorithms.
We study the effect of Medicaid expansion on wait time in the emergency department (ED), using a difference-in-differences approach, where the treatment group includes the states that expanded Medicaid at the beginning of 2014 and the control group includes the states that did not expand Medicaid before 2016. We first focus on the average treatment effect and find that Medicaid expansion increases ED wait time by 10.4% (or 3.5 minutes). We then develop a first-difference causal forest (FDCF) approach for heterogeneous treatment-effect analysis by incorporating the first-difference approach into the causal forest approach. Our comprehensive simulation studies show that the FDCF approach has smaller mean-squared errors than direct applications of the causal forest approach. Finally, we apply the FDCF approach to our empirical example and find that the effect of Medicaid expansion varies widely across different hospitals. Our results are useful to policymakers deciding whether to expand Medicaid and to hospital managers seeking to understand the effect of Medicaid expansion on their hospitals. Our results are also useful to researchers applying causal machine learning methods for heterogeneous treatment-effect analysis.
Florida, an important state in presidential elections in the United States, has received considerable media coverage in recent years for long lines to vote. Do some segments of the population receive a disproportionate share of the resources to serve the voting process, which could encourage some or dissuade others from voting? We conduct the first empirical panel data study to examine whether minority and Democrat voters in Florida experience lower poll worker staffing, which could lengthen the time to vote. We do not find evidence of a disparity directly due to race. Instead, we observe a political party effect—all else equal, a 1% increase in the percentage of voters registered as Democrat in a county increases the number of registered voters per poll worker by 3.5%. This effect appears to be meaningful—using a voting queue simulation, a 5% increase in voters registered as Democrat in a county could increase the average wait time to vote from 40 minutes (the approximate average wait time to vote in Florida in 2012 and the highest average wait time across all states in that election per the Cooperative Congressional Election Study) to about 115 minutes.
We study the joint effects of motivation and workload on human servers’ service time. Using operational and survey data from a call center with a pooled queue structure and limited financial incentives, we examine how individual differences between servers’ trait intrinsic motivation (IM) and extrinsic motivation (EM) impact their average offline, online, and total service times in response to changing workloads. We find significant differences in the patterns of workload and service time relationships across different stages of the service request between servers possessing different combinations of trait motivation. For example, servers with a combination of high IM and low EM were approximately 15% (161%) faster in processing the offline portion of service requests than their peers with the opposite combination (low and high) when workload levels were low (high), respectively. In contrast, servers with high IM-low EM were approximately 35% (5%) slower in processing the online portion of service requests than their low IM-high EM counterparts when workload levels were low (high), respectively. Our findings suggest important nuances in how servers with different trait motivation types respond to changing workload across different stages of the service request. The behavioral pattern shown by high IM-low EM servers is consistent with the preferences of productivity-seeking call center managers who favor speedup and slowdown at certain stages of the service request, conditional to workload. These findings underscore the importance of accounting for trait-based individual differences for a more complete understanding of the complex relationship between workload and service time.
Markets are increasingly used as information aggregation mechanisms to predict future events. If policymakers and managers use markets to guide policy and managerial decisions, interested parties may attempt to manipulate the market in order to influence decisions. We study experimentally the willingness of managers to base decisions on market information under the shadow of manipulation. We find that when there are manipulators in the market, managers under-utilize the information revealed in prices. Furthermore, mere suspicion of manipulation erodes trust in the market, leading to the implementation of suboptimal policies—even without actual manipulation.
Social preferences facilitate the internalization of health externalities, for example, by reducing mobility during a pandemic. We test this hypothesis using mobility data from 258 cities worldwide alongside experimentally validated measures of social preferences. Controlling for time-varying heterogeneity that could arise at the level at which mitigation policies are implemented, we find that they matter less in regions that are more altruistic, patient, or exhibit less negative reciprocity. In those regions, mobility falls ahead of lockdowns, and remains low after the lifting thereof. Our results elucidate the importance, independent of the cultural context, of social preferences in fostering cooperative behavior.
We investigate what fraction of all significant results in website A/B testing is actually null effects (i.e., the false discovery rate (FDR)). Our data consist of 4,964 effects from 2,766 experiments conducted on a commercial A/B testing platform. Using three different methods, we find that the FDR ranges between 28% and 37% for tests conducted at 10% significance and between 18% and 25% for tests at 5% significance (two sided). These high FDRs stem mostly from the high fraction of true null effects, about 70%, rather than from low power. Using our estimates, we also assess the potential of various A/B test designs to reduce the FDR. The two main implications are that decision makers should expect one in five interventions achieving significance at 5% confidence to be ineffective when deployed in the field and that analysts should consider using two-stage designs with multiple variations rather than basic A/B tests.
Reward-based crowdfunding has enabled entrepreneurs to interact with consumers even before product launches. However, this market persistently suffers from a high failure rate; that is, entrepreneurs fail to launch and deliver their products as promised. We investigate the extent to which this high failure rate is because of information distortion—entrepreneurs have uncertainty about consumers’ evaluation of the new products. We model the product launch decisions of different types of entrepreneurs who raise funds through preselling on reward-based crowdfunding platforms and subsequently decide whether to continue with the product launch. To do so, we collect structured and unstructured data from Kickstarter’s digital video game category and classify attributes using supervised learning methods. We develop and estimate an integrated model of crowdfunding demand and entrepreneurs’ product launch decisions. We find that the information entrepreneurs gather from crowdfunding sales has sizable impacts on the product launch decisions of entrepreneurs with low managerial capital or new to the crowdfunding platform. Our counterfactual simulations suggest that platform policy regulating overfunded projects can reduce the product launch failure rate by about 13%.
We investigate an editorial review program for which a review platform supplements user reviews with editorial ones written by professional writers. Specifically, we examine whether and how editorial reviews influence subsequent user reviews (reviews written by noneditor reviewers). A quasiexperiment conducted on a leading review platform in Asia, based on several econometric and natural language processing techniques, yields empirical evidence of an overall positive effect of editorial reviews on subsequent user reviews from the platform’s perspective. First, more reviews are provided for restaurants that receive editorial reviews. In addition, these reviews discuss substantive topics while also including a discussion on other topics, leading to a net increase in content length and variety. They also are more neutral in sentiment and are associated with lower rating valences. Further analysis of the mechanism reveals that the subsequent user reviews of the restaurants that receive editorial reviews become more similar to the editorial reviews in regard to topics, sentiment/rating, length, and readability, indicating a herding effect in how to write a review as the main driver of the change in the subsequent reviews. We further empirically isolate this herding effect among long-time reviewers. The findings suggest that review platforms could use an editorial review program not only to boost the quantitative aspect of user reviews but also, to manage the qualitative aspect as well.
Digitization has given creators direct access to consumers as well as a plethora of new data for suppliers of new products to draw on. We study how this affects market efficiency in the context of book publishing. Using data on about 50,000 license deals over more than 10 years, we identify the effects of digitization from quasi-experimental variation across book types. Consistent with digitization generating additional information for predicting product appeal, we show that the size of license payments more accurately reflects a product’s ex post success, and more so for publishers that invest more in data analytics. These effects cannot be fully explained by changes in bargaining power or in demand. We estimate that efficiency gains are worth between 10% and 18% of publishers’ total investments in book deals. Thus, digitization can have large impacts on the allocation of resources across products of varying qualities in markets in which product appeal has traditionally been difficult to predict ex ante.
What happens in the aftermath of the introduction of a new status ranking? In this study, we exploit the unique empirical opportunity generated by the release of the first edition of the Michelin Guide for Washington, DC, in the fall of 2016. We build on prior work on rankings as insecurity-inducing devices by suggesting that newly awarded high-status actors modify their self-presentation attributes to fit with what they believe audiences expect from the elite. Our results show that, depending on their standing prior to Michelin’s entry, restaurants acted upon different attributes of their self-presentation. Restaurants with high prior standing emphasized attributes that channeled authenticity and exclusivity, which may imply that their Michelin designation triggered operational changes. Actors with low prior standing, on the other hand, acted on descriptive attributes that did not necessarily imply operational changes and could be easily manipulated to signal their belonging among the elite. We contribute to research on status and conformity by disentangling the sources and types of conformity behaviors that newly awarded high-status actors deploy.
We study how access to high-skill labor affects the outcomes of start-up firms. We obtain exogenous variation in firms’ ability to access skilled labor by using win rates in H-1B visa lotteries. Relative to other firms that also applied for H-1B visas, firms with higher lottery win rates are more likely to receive additional venture capital funding and to have a successful exit via an IPO or acquisition. H-1B visa lottery winners also subsequently receive more patents and patent citations. Overall, our results suggest that access to high-skill labor is a critical determinant of success for start-up firms.
We study how innovative firms manage their innovation portfolios after filing for Chapter 11 reorganization using three decades of data. We find that they sell off core (i.e., technologically critical and valuable), rather than peripheral, patents in bankruptcy. The selling pattern is driven almost entirely by firms with greater use of secured debt, and the mechanism is secured creditors exercising their control rights on collateralized patents. Creditor-driven patent sales in bankruptcy have implications for technology diffusion—the sold patents diffuse more slowly under new ownership and are more likely to be purchased by patent trolls.
This paper develops a framework for designing collateral requirements in a centrally cleared market. Clearing members post collateral—initial margins and default funds—to increase their pledgeable income, thereby committing to risk management. The two types of collateral, however, are not perfect substitutes. By achieving loss mutualization, default funds are economically more efficient than initial margins in aligning members’ incentives for risk management ex ante. The optimal mix of collateral resources balances the efficiency in providing incentives with their relative opportunity costs. Our model predicts increased use of initial margins under stringent capital requirements and of default funds under distressed market scenarios.
We propose a method to extract the risk-neutral distribution of firm-specific stock returns using both options and credit default swaps (CDS). Options and CDS provide information about the central part and the left tail of the distribution, respectively. Taken together, but not in isolation, options and CDS span the intermediate part of the distribution, which is driven by exposure to the risk of large, but not extreme, returns. Through a series of asset-pricing tests, we show that this intermediate-return risk carries a premium, particularly at times of heightened market stress.
This paper examines whether information extracted via text-based statistical methods applied to employee reviews left on the website Glassdoor.com can be used to develop indicators of corporate misconduct risk. We argue that inside information on the incidence of misconduct as well as the control environments and broader organizational cultures that contribute to its occurrence are likely to be widespread among employees and to be reflected in the text of these reviews. Our results show that information extracted from such text can be used to develop measures with useful properties for measuring misconduct risk. Specifically, the measures we develop clearly discriminate between high- and low-misconduct-risk firms and improve out-of-sample predictions of realized misconduct risk above and beyond other readily observable characteristics, such as Glassdoor firm ratings, firm size, performance, industry risk, violation history, and press coverage. We provide further evidence on the efficacy of our text-based measures of misconduct risk by showing that they are associated with future employee whistleblower complaints even after controlling for these same observable characteristics.
We examine the financial reporting quality of special purpose acquisition corporations (SPACs) following a successful merger. We compare a sample of SPACs with completed mergers from 2006 to 2020 to initial public offering (IPO) firms in the same industry covering the same period. Compared with similar IPO firms, SPACs are more likely to restate their financial statements and have internal control weaknesses. We also find that SPACs are more likely to file untimely financial statements, amend previously issued filings, and have comment letters that go more rounds with the Securities and Exchange Commission. This lower reporting quality also results in less informative earnings to investors. Our evidence corroborates concerns from the media, accounting firms, and regulators that SPACs exhibit low financial reporting quality in comparison with IPOs.
We analyze a large-scale survey of small business owners, managers, and employees in the United States to understand the effects of the COVID-19 pandemic on those businesses. We explore two waves of the survey that were fielded on Facebook in April 2020 and December 2020. We document five facts about the impact of the pandemic on small businesses. (1) Larger firms, older firms, and male-owned firms were more likely to remain open during the early stages of the pandemic with many of these heterogeneities persisting through the end of 2020. (2) At businesses that remained open, concerns about demand shocks outweighed concerns about supply shocks though the relative importance of supply shocks grew over time. (3) In response to the pandemic, almost a quarter of the firms reduced their prices with price reductions concentrated among businesses facing financial constraints and demand shocks; almost no firms raised prices. (4) Only a quarter of small businesses had access to formal sources of financing at the start of the pandemic, and access to formal financing affected how firms responded to the pandemic. (5) Increased household responsibilities affected the ability of managers and employees to focus on their work, whereas increased business responsibilities impacted their ability to take care of their household members. This effect persisted through December 2020 and was particularly strong for women and parents of school-aged children. We discuss how these facts inform our understanding of the economic effects of the COVID-19 pandemic and how they can help design policy responses to similar shocks.
Despite the substantial economic impact of the restaurant industry, large-scale empirical research on restaurant survival has been sparse. We investigate whether consumer-posted photos can serve as a leading indicator of restaurant survival above and beyond reviews, firm characteristics, competitive landscape, and macroconditions. We employ machine learning techniques to extract features from 755,758 photos and 1,121,069 reviews posted on Yelp between 2004 and 2015 for 17,719 U.S. restaurants. We also collect data on restaurant characteristics (e.g., cuisine type, price level) and competitive landscape as well as entry and exit (if applicable) time from each restaurant’s Yelp/Facebook page, own website, or Google search engine. Using a predictive XGBoost algorithm, we find that consumer-posted photos are strong predictors of restaurant survival. Interestingly, the informativeness of photos (e.g., the proportion of food photos) relates more to restaurant survival than do photographic attributes (e.g., composition, brightness). Additionally, photos carry more predictive power for independent, young or mid-aged, and medium-priced restaurants. Assuming that restaurant owners possess no knowledge about future photos and reviews, photos can predict restaurant survival for up to three years, whereas reviews are only predictive for one year. We further employ causal forests to facilitate the interpretation of our predictive results. Among photo content variables, the proportion of food photos has the largest positive association with restaurant survival, followed by proportions of outside and interior photos. Among others, the proportion of photos with helpful votes also positively relates to restaurant survival.
We propose a new data-driven approach for addressing multistage stochastic linear optimization problems with unknown distributions. The approach consists of solving a robust optimization problem that is constructed from sample paths of the underlying stochastic process. We provide asymptotic bounds on the gap between the optimal costs of the robust optimization problem and the underlying stochastic problem as more sample paths are obtained, and we characterize cases in which this gap is equal to zero. To the best of our knowledge, this is the first sample path approach for multistage stochastic linear optimization that offers asymptotic optimality guarantees when uncertainty is arbitrarily correlated across time. Finally, we develop approximation algorithms for the proposed approach by extending techniques from the robust optimization literature and demonstrate their practical value through numerical experiments on stylized data-driven inventory management problems.
Regulators frequently relax accounting rules during a financial crisis as a means of regulatory forbearance. The new accounting options provide banks with an opportunity for an accrual-based increase in their regulatory capital. The use of such an accounting option helps reduce the costs of government interventions such as bailouts and avoid the dilution of existing shareholders’ ownership rights. We examine the introduction of the reclassification option for financial assets during the 2008 financial crisis and study the position of accrual-based options in the pecking order of banks’ recapitalization measures. The findings suggest that the accrual-based increase in regulatory capital is temporary and does not provide permanent relief. Consistent with the long-term costs of accrual-based measures, investors perceive the accounting choice as a negative signal. If banks do not complement their use of the accounting option by other corrective actions that result in a real capital increase and a liquidity injection, they continue to suffer from low capitalization and financial difficulties in the following years. Ultimately, government interventions in accounting regulation are unlikely to offer a sustainable solution to capital shortfalls in the banking sector if they are not supported by the concurrent enforcement of real corrective actions.
We introduce a novel approach to measure the founding strategic differentiation of startups and its relationship to follow-on performance. We use natural language processing and historical websites to estimate the similarity between the founding website of an individual startup, the historical website of public firms at the startup’s founding year, and the founding website of other startups founded in the same year. We propose that distance in the value proposition stated in these websites represents differentiation in the market. Startup differentiation is estimated as the average text-based distance from the five closest incumbents (public firms). We implement this approach using a large sample of startups from Crunchbase. Our measure predicts a meaningful increase in early-stage financing and equity outcomes, unconditionally and controlling for cohort and industry fixed effects. The positive benefits of equity outcomes only evidence themselves after year 6 of age, suggesting more differentiated firms may take longer to prove themselves. Using out-of-sample tests, we also demonstrate that our measure is economically important, predicting 30% of the total variation in the receipt of early-stage financing and 20% of variation in equity outcomes. Public datasets of our differentiation score and scraped website data are provided, together with open-source code to replicate our approach in other settings.
Uncertainty shocks are also risk premium shocks. With countercyclical risk aversion (RA), a positive shock to uncertainty increases risk and elevates RA as consumption growth falls. The combination of high RA and high uncertainty produces significant equity risk premia in bad times, which in turn, exacerbate the decline of macroeconomic aggregates and equity prices. Moreover, in the cross-section of equity returns, investors demand a risk premium for stocks that perform poorly in times of high uncertainty and elevated risk aversion. In a model with endogenously time-varying RA, uncertainty shocks lead to large falls in investment and equity prices that closely match state-dependent data responses.
This paper studies the prevalence of potential anticompetitive effects of vertical mergers using a novel data set on U.S. and international buyer-seller relationships and across a large range of industries. We find that relationships are more likely to break when suppliers vertically integrate with one of the buyers’ competitors than when they vertically integrate with an unrelated firm. This relationship holds for both domestic and cross-border mergers and for domestic and international relationships. It also holds when instrumenting mergers using exogenous downward pressure on the supplier’s stock prices, suggesting that reverse causality is unlikely to explain the result. In contrast, the relationship vanishes when using rumored or announced but not completed integration events. Firms experience a substantial drop in sales when one of their suppliers integrates with one of their competitors. This sales drop is mitigated if the firm has alternative suppliers in place. These findings are consistent with anticompetitive effects of vertical mergers, such as vertical foreclosure, rising input costs for rivals, or self-foreclosure.
The growing influence of internet platforms acting as content aggregators is one of the most important challenges facing the media industry. We develop a simple model to understand the impact of third-party content bundling by a social platform that has a monopoly on showing user-generated content to consumers. In our model, consumers can access news either directly through a newspaper’s website or indirectly through a platform, which also offers social content. We show that content bundling, when unilaterally implemented by the platform, tends to harm publishers and to increase the dispersion of quality across outlets, with initially high-quality outlets investing more and low-quality ones investing less. With many heterogenous newspapers, the result is robust even if each newspaper can prevent the platform from using its content. When content bundling follows an agreement between the platform and publisher, its effects are reversed, as publishers’ profits go up while quality dispersion goes down. In a setup with heterogeneous consumers, we also show that the platform’s ability to personalize the mix of content it shows to users induces publishers to invest more in the quality of their content.
We study how daily labor supply responds to unanticipated earnings shocks among Singapore’s taxi drivers using a novel identification strategy that uses idiosyncratic variation in booking cancellations and passenger no-shows (CNS) that drivers repeatedly receive. Our results provide new and more compelling evidence in support of the income-targeting model of labor supply. Not only are the average responses on the extensive margin consistent with the income-targeting model, but the responses on the intensive margin and the heterogeneous responses at different income levels and across driver characteristics are as well. We find that drivers work longer and earn more per hour following CNS, and the effects are robust after controlling for rich fixed effects, market supply and demand conditions, and drivers’ sunk cost of time. The CNS effects on ending a shift exhibit a U-shaped pattern, are strongest when cumulative income is close to the average shift income, and become insignificant when the income level is too low or too high. The effects are most pronounced in the first hour of CNS and fade away quickly afterward. Drivers achieve higher productivity by reducing break time, taking more jobs, driving faster, driving to places with more earning opportunities, and having more time with passengers on board. Drivers choose the response strategies that are complementary to their abilities and circumstances such as schedule flexibility and potential for productivity improvement: those with flexible working schedules tend to prolong their shifts, whereas those with flexible earnings rates tend to increase their subsequent productivity. Our novel identification strategy strengthens the empirical literature on daily labor supply, and our findings of heterogeneity effects offer new insights on income-targeting behaviors.
Uncertainty may exist about the desirability of trade in bilateral bargaining. For instance, buyers may not know their value perfectly and sellers may not be fully aware of their cost structure. We endogenize the expected surplus of trade by considering information gathering before price negotiation between a seller and a buyer. We show that prebargaining information acquisition can reverse standard findings in canonical bargaining models, regarding how the bargaining primitives may influence the equilibrium expected payoffs and the negotiated price. In particular, a higher bargaining power can result in a lower expected payoff, because the other party’s reduced incentive to acquire information would reduce the total pie to be split between the parties. In the same vein, the seller’s expected payoff can decrease as its material cost becomes lower or its outside option improves, and the buyer can be hurt by a higher value from the transaction or from its outside option. Similarly, the seller/buyer may become worse off by having more information if that induces the counter party to acquire less information. In addition, the expected negotiated price may decrease with the seller’s relative bargaining power, its material/opportunity cost, or the buyer’s incremental value. We also examine the robustness of the basic results under joint information acquisition or noncredible communication. Moreover, we show that a shopping intermediary may prefer to decrease the seller’s bargaining power or increase the buyer’s cost of gathering information. We discuss how our findings can shed light on practice and empirical research.
We study the effects of positive and negative advertising in presidential elections. We develop a model to disentangle these effects on voter turnout and candidate choice. The central empirical challenges are highly correlated and endogenous advertising quantities that are measured with error. To address these challenges, we construct a large set of potential instruments, including interactions with incumbency that we demonstrate provide the critical identifying variation, and apply machine-learning causal inference methods. Using data from the 2000 and 2004 U.S. presidential elections, we find that positive and negative ads play fundamentally different roles. Negative ads are more effective at driving relative candidate shares, whereas positive ads stimulate turnout. These results indicate that a candidate geographically targeting tone trades off local relative share gains and local increases in turnout for localities with a strong base. Counterfactual simulations, where the candidates adjust the quantity of positive and negative advertising while budgets remain fixed, indicate that ad tone alone can impact the outcome of close elections. Our analysis also provides potential explanations as to why past studies have produced mixed findings on both ad-tone and turnout effects.
Hospitalists are medical doctors that specialize in the care of hospitalized patients, a role that until recently belonged to primary care physicians. We develop an operational model of hospitalist-patient interactions with rounding and responding service modes, optimizing hospitalist caseload and case-mix to achieve the maximal reduction in patient length of stay (LOS). We show that hospitalists are effective at reducing LOS for patients with complex conditions, corroborating intuitive reasoning. However, the optimal hospitalist case-mix also includes “simple” patients with few interventions and short LOS, as they can effectively reduce discharge delays. This actionable insight is particularly salient for small community hospitals with simple, short-stay patients, where hospitalists may be undervalued due to the prevailing belief that they are primarily effective for complex patients. We conduct a comparative case study of a small community hospital and a large academic hospital, drawing a stark contrast between the two in terms of ideal caseload and patient coverage. Despite the fact that the academic hospital treats higher complexity patients, hospitalists at the community hospital should actually have a lower caseload than hospitalists at the academic hospital due to shorter stays in the community hospital. We find that both hospitals are understaffed but for different reasons: the academic hospital needs to staff more hospitalists to reduce the current caseload of its hospitalists, whereas the community hospital needs to staff more hospitalists to expand its hospitalist coverage to more patients. We estimate that these hospitals can save on average $1.5 million annually by implementing the optimal staffing policies.
We develop a game-theoretic model to study the incentive for competing manufacturers to share supplier audit information. Based on the audit information, each manufacturer decides whether to source from a common supplier who has uncertain responsibility violation risk or to switch to a backup supplier who has no responsibility violation risk but charges a higher price. When supplier responsibility violation occurs, some consumers boycott the manufacturers involved. Audit information allows a manufacturer to reduce the uncertainty about the risk of the common supplier. We show that audit information sharing may make the manufacturers’ sourcing strategies more or less differentiated. As a result, the information-sharing decision is not monotone in the model parameters. We fully characterize the manufacturers’ equilibrium audit information-sharing and sourcing decisions and establish conditions under which audit information sharing induces the manufacturers to adopt more or less responsible sourcing strategies. We also show that a manufacturer could be better off when the cost premium of sourcing from the backup supplier or the risk of the common supplier becomes higher or the audit information becomes less accurate. We consider several extensions of the base model and demonstrate that the main insights remain mostly valid.
Recent years have seen considerable debate about the practicability of a global quantity/price commitment to control carbon emissions and tackle environmental issues. In this paper, we study the impact of the cap-and-trade policy (quantity commitment) and the carbon tax policy (price commitment) on a firm’s technology investment and production decisions. The main feature captured in our model is that there exist correlated uncertainties between the sales market (demand uncertainty) and the permit trading market (permit price volatility) under the cap-and-trade policy. The correlation relationship stands on the following intuition. The demands for final products affect firms’ production output, which generates the needs of emission permits and influences the permit price. We show that under the cap-and-trade policy, with the uncertainty of the future emission price, the firm could flexibly adjust its production quantity to enhance its profit, resulting in low incentives to invest in clean technology. However, as the (positive) correlation between the sales market and the permit trading market increases, the production flexibility is constrained so that the firm has to increase its technology investment to hedge against the future risk of a high emission price. Making a comparison between the cap-and-trade and carbon tax policies, we find that when the correlation coefficient is moderate, the carbon tax policy generates a multiwin situation (i.e., more technology investment, higher expected profit and consumer surplus, and fewer carbon emissions). Case studies are provided to illustrate the implications and model variants are examined to check the robustness of the main results. Overall, our analysis sheds light on recent debate over carbon pricing and identifies the important role of correlated uncertainties in carbon policy design.
The COVID-19 pandemic has killed millions and gravely disrupted the world’s economy. A safe and effective vaccine was developed remarkably swiftly, but as of yet, uptake of the vaccine has been slow. This paper explores one potential explanation of delayed adoption of the vaccine, which is data privacy concerns. We explore two contrasting regulations that vary across U.S. states that have the potential to affect the perceived privacy risk associated with receiving a COVID-19 vaccine. The first regulation—an “identification requirement”—increases privacy concerns by requiring individuals to verify residency with government approved documentation. The second regulation—“anonymity protection”—reduces privacy concerns by allowing individuals to remove personally identifying information from state-operated immunization registry systems. We investigate the effects of these privacy-reducing and privacy-protecting regulations on U.S. state-level COVID-19 vaccination rates. Using a panel data set, we find that identification requirements decrease vaccine demand but that this negative effect is offset when individuals are able to remove information from an immunization registry. Our results remain consistent when controlling for CDC-defined barriers to vaccination, levels of misinformation, vaccine incentives, and states’ phased distribution of vaccine supply. These findings yield significant theoretical and practical contributions for privacy policy and public health.
This paper examines the effect of the expiry of recording copyright on the supply of music—in the form of rereleases, availability on streaming platforms, and concert performances—by artists popular in the United Kingdom in the 1960s. We find that recording copyright expiry has different effects on a song’s availability in different distribution channels. The lapsing of copyright leads to a large increase in the number of rereleases in physical formats, holding constant artist, age, and year fixed effects. However, when a song’s original recording copyright expires, it becomes less likely to be performed in concert. Moreover, copyright status is not associated with differences in availability on the digital streaming platform Spotify. These results show that copyright expiry has nuanced effects on availability and can lead to different and even opposite effects on availability of a product across different distribution channels. They also show that within the context of digital distribution, the impact of copyright on availability differs based on the business model of a platform.
A major challenge in obtaining evaluations of products or services on e-commerce platforms is eliciting informative responses in the absence of verifiability. This paper proposes the square root agreement rule (SRA): a simple reward mechanism that incentivizes truthful responses to objective evaluations on such platforms. In this mechanism, an agent gets a reward for an evaluation only if the answer matches that of a peer agent, where this reward is inversely proportional to a popularity index of the answer. This index is defined to be the square root of the empirical frequency at which any two agents performing the same evaluation agree on the particular answer across evaluations of similar entities operating on the platform. Rarely agreed-on answers thus earn a higher reward than answers for which agreements are relatively more common. We show that in the many tasks regime, the truthful equilibrium under SRA is strictly payoff-dominant across large classes of natural equilibria that could arise in these settings, thus increasing the likelihood of its adoption. Although there exist other mechanisms achieving such guarantees, they either impose additional assumptions on the response distribution that are not generally satisfied for objective evaluations or they incentivize truthful behavior only if each agent performs a prohibitively large number of evaluations and commits to using the same strategy for each evaluation. SRA is the first known incentive mechanism satisfying such guarantees without imposing any such requirements. Moreover, our empirical findings demonstrate the robustness of the incentive properties of SRA in the presence of mild subjectivity or observational biases in the responses. These properties make SRA uniquely attractive for administering reward-based incentive schemes (e.g., rebates, discounts, reputation scores, etc.) on online platforms.
A common pattern of control in firms is for management to retain a broad set of rights, whereas the remaining stakeholders’ contracts provide them with targeted veto rights over specific classes of decisions. We explain this pattern of control sharing as an efficient organizational response that balances the need to encourage management to account for stakeholders’ interests against the need to prevent self-interested stakeholders from blocking valuable proposals. Enforceable obligations of good faith and fair dealing play an essential role in facilitating undivided management control of many decisions. With these legal protections (but not without them), shared control is more likely when the parties are more symmetrically informed and hence, better able to bargain to efficient decisions.
Firm-induced migration typically entails firms relocating workers to fill value-creating positions at destination locations. But such relocated workers are often exposed to external employment opportunities at their destinations, possibly triggering turnover. We conceptualize the firm-induced migration path, consisting of the relocated workers’ place of origin and destination, as relevant in determining worker performance and turnover postrelocation. Using a unique data set from a large Indian technology firm that hires talent from both large cities and smaller towns, we document robust econometric patterns by exploiting the firm’s randomized assignment of workers to production centers across the country. These production centers are located in the largest technology cluster in India (Bangalore), smaller technology clusters, and noncluster locations. We find that the firm-induced migration path shapes both worker performance and turnover. Compared with workers from large cities, workers from smaller towns achieve higher performance when relocated to Bangalore than to other production centers, but are also more likely to join competing firms. Fine-grained data on employment and human-capital-augmentation opportunities at workers’ destination locations, and on socioeconomic conditions in workers’ places of origin, help us rule in an abductive explanation: across firm-induced migration paths, differences in external labor-market opportunities between workers’ places of origin and their destinations, as well as intrafirm skill-development opportunities at the destination, are related to heterogeneous human-capital outcomes.
We study the value of divergence in values and preferences in organizations by combining three stages of a decision process—ex ante information acquisition, interim project choice, and ex post project execution—into a tractable model. A key insight is that our unified model provides predictions different from models without the execution decision stage. We consider an organization that consists of a decision maker who selects a project and an implementer who acquires costly information before project choice and executes the selected project. They have intrinsic and possibly divergent preferences over projects. We show that, although the implementer’s dual role generates a disadvantage of designing conflicts in terms of the implementation motivation, it simultaneously boosts the implementer’s motivation for information acquisition to influence the decision maker’s project choice more under divergent preferences. Our results provide managerial insights that designing conflicts is beneficial only in environments where additional information is sufficiently precise and must be accompanied by a manager who is balanced and incorporating feedback.
Morals constrain self-serving behavior. Yet, self-regulation failures in the face of monetary temptation are common at the workplace. To limit such failures, organizations can design environments that limit the temptation to behave self-servingly, nudging workers to uphold their morals. In a series of experiments where participants may be tempted to take excessive pay after exerting effort, we study whether a simple intervention—asking individuals to state the wage they believe should be paid ex ante, before facing the temptation to take excessive compensation—prevents self-serving behavior. In contrast to lay beliefs and the predictions from prior work, we find that such an intervention is not effective, leading to self-serving behavior. However, a more realistic elicitation procedure of the appropriate wage mitigates this effect. These findings contribute to work on the malleability of moral behavior showing that simple interventions thought to effectively mitigate self-serving behavior can prompt individuals to stretch their moral boundaries. They also stress the importance of properly testing interventions that might seem intuitive.
Dynamic structures in intertemporal choices offer multiple channels through which reference dependence can occur. We examine intertemporal reference dependence when using choice lists to elicit time preference over outcome sequences. Reference point effects can arise endogenously within an outcome sequence and exogenously from the experimental environment of the choice list. We show that estimated discount factors in the choice list are biased by both kinds of reference points and propose a model to jointly account for both. Our experimental design with outcome sequences also enables us to jointly estimate the discount factor and utility curvature. We further discuss the implications for recent developments in the measurement of intertemporal preference.
Several corporations have committed to procuring a percentage of their electricity demand from renewable sources by a future date. Long-term financial contracts with renewable generators based on a fixed strike price, known as virtual power purchase agreements (VPPAs), are popular to meet such a target. We formulate rolling power purchases using a portfolio of VPPAs as a Markov decision process, accounting for uncertainty in generator availability and in the prices of electricity, renewable energy certificates, and VPPAs. Obtaining an optimal procurement policy is intractable. We consider forecast-based reoptimization heuristics consistent with practice that limit the sourcing of different VPPA types and the timing of new agreements. We extend these heuristics and introduce an information-relaxation based reoptimization heuristic, both of which allow for full sourcing and timing flexibilities. The latter heuristic also accounts for future uncertainties when making a decision. We assess the value of decision flexibility in rolling power purchases to meet a renewable target by numerically comparing the aforementioned policies and variants thereof on realistic instances involving a novel strike price stochastic process calibrated to data. Policies with full timing flexibility and no sourcing flexibility reduce procurement costs significantly compared with one with neither type of flexibility. Introducing sourcing flexibility in the former policies results in further significant cost reduction, thus providing support for using VPPA portfolios that are both dynamic and heterogeneous. Computing near-optimal portfolios of this nature entails using our information-relaxation based reoptimization heuristic because portfolios constructed via forecast-based reoptimization exhibit higher suboptimality.
Berger and Pope (2011) show that being slightly behind increases the likelihood of winning in professional (National Basketball Association; NBA) and collegiate (National Collegiate Athletic Association; NCAA) basketball. We extend their analysis to large samples of Australian football, American football, and rugby matches, but find no evidence of such an effect for these three sports. When we revisit the phenomenon for basketball, we only find supportive evidence for NBA matches from the period analyzed in Berger and Pope (2011). There is no significant effect for NBA matches from outside this sample period, for NCAA matches, or for matches from the Women’s National Basketball Association. High-powered meta-analyses across the different sports and competitions do not reject the null hypothesis of no effect of being slightly behind on winning. The confidence intervals suggest that the true effect, if existent at all, is likely relatively small.
We explore the relationship between organizational religious affiliation and wrongdoing using a unique data set on inspections in 16,101 nursing homes over five years. We find that violations of standards of care are more severe in religiously affiliated homes. We track this difference to a reduction in the likelihood that organizational members file complaints rather than poorer behaving caretakers or differential treatment by enforcement agents. Fewer complaints increase the time that religiously affiliated homes operate without monitoring, which allows violations to escalate before they are detected. Our findings highlight an understudied process in the literature on organizational wrongdoing: Although much attention has been devoted to how inspector bias can lead to incorrect conclusions about the true rates of wrongdoing across organizations, religious affiliation can lead to similarly incorrect conclusions—but through an internal organizational process.
Using a unique setting of an online peer-to-peer lender, I show that banks expand credit access for consumers who obtain FinTech loans. Consistent with FinTech relieving information frictions, this effect is stronger for more credit-constrained consumers. Many borrowers, especially higher-quality ones, use peer-to-peer loans to repay expensive revolving debt. Yet, debt financing and credit score changes cannot fully explain higher bank credit. The increase in bank credit access is stronger when information sets between banks and peer-to-peer lenders diverge more. These results highlight information spillovers as a novel mechanism through which FinTech lending can relieve financial constraints for consumers.
This article examines the cross-country asset pricing implications of disaster risk concerns. We construct a new disaster risk index, relying on six news-implied rare disaster proxies of Manela and Moreira (2017), and show that this index is a powerful predictor for stock returns and other asset returns in international markets both in and out of sample. By further disentangling a global common component from our rare disaster index, we find evidence supporting theories that emphasize globally shared disaster risk as the important driving force of asset price fluctuations. Moreover, we conduct a return decomposition analysis and find that the global disaster risk drives stock returns primarily through the discount rate channel.
Although many central banks in the 21st century have become more transparent, Chinese monetary policy communications have been relatively opaque, suggesting that financial market participants must commit significant resources to predicting the central bank’s actions. We conduct a novel systematic textual analysis of the discussion in the quarterly reports of China fund managers, from which we infer their near-term expectations for monetary policy. We construct an aggregate index of manager expectations and show that, as a forecast of Chinese monetary policy, it compares favorably with both market- and model-based alternative projections. We also show that fund managers act on these expectations and correctly anticipating shifts in Chinese monetary policy improves fund performance. Our results imply that manager skill is an important determinant of fund returns, providing the first evidence from China on a question for which studies of asset management in other countries have reached conflicting conclusions. Finally, we find that expectations are more accurate for funds that commit more analytical resources, have higher management fees, or have stronger managerial educational background.
A primary concern in mergers and acquisitions is the risk the deal may be cancelled before it is completed. We document that “interim risk” varies asymmetrically with the aggregate market return. Deals tend to be renegotiated when the market rises, but cancelled when the market crashes. These effects are conditional on the method of payment and the contracting stage of the deal, consistent with a mechanism of ex post renegotiation. Variation in interim risk over time alters the method of payment in mergers and the firms that are targeted and acquired.
Recent studies have proposed a large set of powerful anomaly-based factors in the stock market. This study examines the role of investor inattention in the corresponding anomalies underlying these factors and other underreaction-related anomalies. Using media coverage as a proxy for investor attention, we show that the anomalies underlying many recently proposed prominent factors are much more pronounced among firms with low media coverage in portfolio-formation periods. In addition, we find many other prominent anomalies that previous literature has attributed to underreaction also tend to perform much better among firms with low media coverage. The average Fama-French five-factor alpha spread of these anomalies is about 0.97% per month among firms with low news coverage and only 0.24% per month among firms with high news coverage. Moreover, most of the alpha spread comes from the short leg of the anomalies and from the firms that are more difficult to arbitrage. Overall, our evidence indicates that investor inattention at least partially drives many of the recently proposed factors.
Using annual survey-based investor relations (IR) data for a panel of European companies, we document that the supply and effectiveness of IR varies with country- and firm-level demand. Relative to their industry peers, firms from insider-oriented countries have larger IR staff, which predicts better IR rankings. Better IR is associated with greater visibility, information assimilation, and valuation, with visibility and assimilation being significantly greater for firms from insider-oriented countries. Within such countries, firms with greater outsider orientation have higher capital market benefits. Furthermore, using Markets in Financial Instruments Directive II as a shock to analyst coverage, we find an incrementally larger association between IR and visibility in insider-oriented countries after 2017. Overall, the evidence suggests that the supply of IR in insider-oriented markets has reached a high level, acting as a viable mechanism to improve firms’ information environment. However, within those countries, IR demand still varies significantly, with outsider-oriented firms showing greater IR effectiveness.
This study uses an information-asymmetry framework to examine the effect of initiation of credit default swaps (CDS) trading on firm dividend payout policy. We find evidence that CDS initiation is associated with increasing dividends, which is consistent with firms distributing excess free cash flow to mitigate exacerbated manager-equityholder agency conflicts resulting from reduced monitoring by banks following CDS initiation. Additional findings support this explanation by showing that the dividend increases are concentrated among borrowing firms with higher agency cost before CDS initiation, among firms whose lead arranger banks have a relatively less strong reputation in the loan-syndication market, and among firms whose loans are subject to less intense monitoring features—that is, less restrictive loan covenants—following CDS initiation. Additional analyses also suggest that inferences are robust to controlling for the potential effects of CDS initiation on capital structure.