Abstract
					Using mobile wallet and card transaction data from a leading Singapore bank, this paper studies the effect of a mobile wallet payment technology introduction in 2017 on business growth. We find that mobile wallet usage doubled after the new technology introduction, and the improved payment efficiency generated a significant spillover effect. Small merchants experienced a monthly increase in debit and credit card sales amount (count) of 3.5 percent (3.4 percent) compared to large merchants. The payment technology promoted sales growth primarily for new businesses by facilitating customer acquisition.
Abstract
					In this article, we provide a descriptive account of how people from different generations vary in their use of financial management technology, their access credit markets, and how they finance consumption and incur financial costs and penalties. We use a detailed panel of transaction-level data from Iceland on individual spending, incomes, balances, and credit limits from a personal financial management software. We find that technology adoption is faster for millennials, but use of consumer credit and financial penalties are higher for older generations. While the "coholding puzzle" exists for all people, it appears to be more severe for baby boomers.
Abstract
					How does FinTech credit mitigate local credit supply frictions in China's segmented credit market? In our simple theoretical models, we show that FinTech credit (i) expands the extensive margin of credit to borrowers of lower credit scores and (ii) provides relatively more credit to borrowers with lower credit scores. We confirm both predictions based on comprehensive data from one of China's largest FinTech credit providers.
Abstract
					In many prediction problems researchers have found that combinations of prediction methods ("ensembles") perform better than individual methods. In this paper we apply these ideas to synthetic control type problems in panel data. Here a number of conceptually quite different methods have been developed. We compare the predictive accuracy of three methods with an ensemble method and find that the latter dominates. These results show that ensemble methods are a practical and effective method for the type of data configurations typically encountered in empirical work in economics, and that these methods deserve more attention.
Abstract
					We revisit the panel data analysis of Acemoglu et al. (forthcoming) on the relationship between democracy and economic growth using state-of-the-art econometric methods. We argue that panel data settings are high-dimensional, resulting in estimators to be biased to a degree that invalidates statistical inference. We remove these biases by using simple analytical and sample-splitting methods, and thereby restore valid statistical inference. We find that debiased fixed effects and Arellano-Bond estimators produce higher estimates of the long-run effect of democracy on growth, providing even stronger support for the key hypothesis of Acemoglu et al.
Abstract
					The paper's introduction offers a high-level review of Bitcoin's features, especially its governance by protocol. The paper proceeds to summarize Bitcoin's analysis as a payment system. It pays particular attention to a comparison between Bitcoin and a firm-run payment system.
Abstract
					We ask which markets drive bitcoin prices and how price discovery happens across different exchanges. Does the greater exuberance for cryptocurrencies outside the United States affect prices only on local markets or does it impact price formation on global cryptocurrency markets? We document significant heterogeneity in which price formation happens across exchanges and time. When markets are more integrated, shocks to prices on all exchanges contribute to price discovery. However, when markets become segmented, those exchanges that have large arbitrage spreads relative to the US price, i.e. where investors are more exuberant become much less important for price discovery.
Abstract
					Female genital cutting (FGC) affects more than 200 million women globally. Education is often depicted as an effective instrument for abandoning the practice, but causal evidence is scant. This paper uses the introduction of the Universal Primary Education program in Nigeria as a natural experiment to identify the causal effect of mothers’ education on the probability that their daughters are cut. Household survey data indicate no statistically significant impact of the reform on the probability that daughters undergo FGC, which may be explained by an insignificant effect of the reform on maternal support for the practice.
Abstract
					This paper examines the impact of the Athena Scientific Women's Academic Network (SWAN) Charter on the wages and employment trajectories of female faculty.
 The Athena SWAN Charter is a gender equality initiative that formally recognizes good practice towards the representation and career progression of women in 
science, technology, engineering, mathematics, and medicine (STEMM) through an accreditation process. We find that the gender wage gap closes after Athena 
SWAN accreditation. However, female faculty at the non-professorial level are not more likely to be promoted to professor after accreditation, or to move to an 
Athena SWAN accredited university. Taken together these results suggest that the higher wage growth experienced by female non-professorial faculty after Athena 
SWAN accreditation is likely to come from pay rises within a particular rank.
Abstract
					We study how childhood exposure to a nontraditional family (a working married mother, a married mother that is the primary breadwinner, or a non-married mother) affects gender role attitudes in young adulthood. Boys and girls develop more liberal gender attitudes when they spend more time with a non-married mother. In intact families, boys' gender attitudes, more than girls', appear positively influenced by the role model of a working mother, especially if she is also the primary breadwinner. However, the effect of childhood exposure to a mother with greater economic power on boys' gender attitudes is smaller in more gender conservative families.
Abstract
					This paper provides evidence on child penalties in female and male earnings in different countries. The estimates are based on event studies around the birth of the first child, using the specification proposed by Kleven et al. (2018). The analysis reveals some striking similarities in the qualitative effects of children across countries, but also sharp differences in the magnitude of the effects. We discuss the potential role of family policies (parental leave and childcare provision) and gender norms in explaining the observed differences.
Abstract
					We report on an experiment with poor rural households in Ethiopia, which aimed to boost aspirations for a better future through exposure to documentaries 
featuring local male and female role models. We explore effects on parents' educational aspirations and investment in children's education. At baseline, educational 
aspirations are high but biased against girls. At a six-month follow-up, the intervention increased parents' aspirations for their children's education and increased 
enrollment, time spent in school, and schooling expenditures. There was no catching up of girls relative to boys. Results are consistent with broader local social 
norms that value education but disfavor women.
Abstract
					We study attitudes towards domestic violence in a sample of young women and men exposed to the edutainment TV series MTV Shuga 3, which features a sub-plot on this theme, and in a sample that was not. We measure viewers' memory of the characters and identification with them. Eight months after the show, male viewers of Shuga report improved attitudes and are 21 percent less likely to justify violence than men in the control group. Attitudes improve among women and men who remember the characters associated with the violence plot, though not among those who identify with the characters.
Abstract
					India's female employment rate is one of the lowest in the world. One approach to expanding female employment is to make young women's family members more supportive of them working. We report on the effects of two interventions aimed at increasing family members' supportiveness in rural India. The first entails showing them video testimonials by working women and their family members. The second prompts a conversation between working women and their families about the benefits and challenges they face when a woman in the household works. We find no evidence that the interventions changed employment or attitudes.
Abstract
					This paper uses state police stop data in Texas to assess patrol activity. We find that both the types of stops and allocation of resources over space change in darkness relative to daylight, and that the changes in stop type and manpower allocation are correlated within police officers. We also find that the counties receiving more police resources in darkness have a higher share of minority residents. Veil of Darkness (VOD) tests of racial discrimination in traffic stops require that the distribution of motorists be independent of darkness, which is unlikely to be the case without detailed geographic controls.
Abstract
					We rely on a policy experiment in the New York City Police Department (NYPD) to address the well-known problems of omitted variable bias and infra-marginality in traditional outcomes tests of racial bias in police stops. The NYPD designated specific areas as impact zones and deployed extra officers to these areas and encouraged them to conduct more intensive stop, question, and frisk activity. We find that the NYPD are more likely to frisk black and Hispanic suspects after an area becomes an impact zone compared to other areas of the city.
Abstract
					The United States is embroiled in an important debate about police use of force tactics. I find that black civilians are disproportionately likely to be involved in a use of force incident during an arrest, examining data from Dallas, Texas. However, this race disparity stems from differences in the initial likelihood of arrest. Further, I fail to find evidence of taste-based racial bias in use of force conditional on arrest, leveraging variation across officer and civilian race. The results suggest that reforms that narrowly focus on force-related protocols may be unlikely to reduce racial disparities in use of force.
Abstract
					Many police jurisdictions have recently expanded their Taser arsenals with a goal of reducing officer-involved shootings. We analyze substitution between Tasers and firearms by means of an event study made possible by a policy change at the Chicago Police Department. Before March 2010, only sergeants and field training officers had access to Tasers; after that date, they were made available to patrol officers. We find that the change in Taser policy led to a large increase in Taser use, but not to a decrease in the use of firearms.
Abstract
					The 1965 Voting Rights Act (VRA) is considered by many to be the most effective civil rights law ever passed. In 2013, the Supreme Court struck down important provisions from the VRA in Shelby County v. Holder. This paper first discusses how the potential weakening of minority political power brought about by Shelby County may have made the government less responsive to minorities' policy demands. Then we proceed to show that the lack of minority power is already producing economic inequality that is reflected in public-sector wages and in private-sector occupations with a high number of public workers.
Abstract
					This paper's goal is to determine whether the degree of labor market tightness affects the frequency of discrimination charges. State-level panel data on enforcement and litigation actions from the US Equal Employment Opportunity Commission, along with disaggregated labor market statistics, allow us to assess the effects of labor market conditions on discrimination based on race or ethnicity, and how these effects vary across states and over time. Our findings have implications for how macroeconomic policies might be used to promote equal opportunity in the labor market.
Abstract
					We use a choice experiment to examine public support for minimum wages. We first elicit respondents' moral assessment of two labor market systems: one with a minimum wage and one without. Then, we present four pairs of hypothetical employment outcomes and ask respondents to "vote." Our estimates suggest that the average respondent requires a 4.65 percentage point reduction in unemployment before they would support a system without a minimum wage. We also find that equity matters; respondents are 11.1 percentage points less likely to support a minimum wage if it disproportionately affects minorities and females.
Abstract
					We estimate the increasing health care needs of American inmates by combining data on inmate demographics and national health trends. Decades of harsh punishment combined with demographic shifts have led to a "greying" prison population that is a source of concern for policymakers. Our estimates reveal that inmate health care needs are significant and growing beyond what is predicted by their age profile. While the fraction of inmates aged 40 or more increased by 49 percent between 1996 and 2004, the prevalence of medical conditions such as diabetes, hypertension, asthma, and cancer among inmates grew between 177 and 268 percent.
Abstract
					As the drug epidemic continues to cripple communities and disrupt our country, identifying and understanding state and federal policies which have helped alleviate the burden of substance use disorders (SUDs) is imperative. In 2010, the passage of the Patient Protection and Affordable Care Act (ACA) expanded health coverage and services offered to millions of Americans. Prior to the ACA, treatment for substance use disorders was not included in all medical coverage. We examine the brief literature on ACA Medicaid Expansion and SUDs and complement this literature by including the effects on measures of supply and efficacy of SUD treatment.
Abstract
					We study how drug violence in Mexico and internal immigration enforcement in the United States affect the selectivity of Mexican immigrants. We find that violence is associated with an increase in English proficiency among immigrants. Furthermore, the deterrence effect of interior enforcement varies: it is associated with increases in the probability of observing undocumented immigrants with prior migration experience, who are English proficient and have higher unobservable abilities. Those factors are associated with a higher probability of finding a job, and higher productivity and earnings in the US labor market.
Abstract
					Exposure to parental incarceration is particularly prevalent in the United States, where about 7 percent of children have lived with a parent who was incarcerated. In this paper, I use nationally representative US data and apply partial identification methods to bound the likely effects of parental incarceration on education and labor market outcomes. Findings suggest that parental incarceration leads to substantially higher rates of high school dropout. Results provide some support for negative effects on likelihood of college degree attainment and employment in young adulthood. This work has important implications for criminal justice policy and social policies toward children.
Abstract
					Although teen pregnancy has been on the decline in the United States, it remains among the highest within developed countries. Hispanics, who are more likely to be undocumented immigrants, lead this trend, yet the role of legal status has yet to be considered. To investigate this question, we examine teenage fertility responses to the Deferred Action for Childhood Arrivals (DACA) program, which provides temporary legal status to undocumented youth. We find that DACA reduced the likelihood of having a teenage birth by 1.6 percentage points and eliminated roughly half of the gap in teenage childbearing between documented and undocumented women.
Abstract
					Community college completion rates are extremely low, especially among low-income students. One potential explanation is that low-income students have limited capacity to overcome financial shocks, such as large medical, legal, or car repair bills. Some programs offer "emergency financial assistance" (EFA) to prevent these events from curtailing educational progress. We test the efficacy of EFA within the context of a broader randomized controlled trial at a community college in Texas. We find no evidence that access to EFA alone leads to improved outcomes. We speculate that EFA will only be effective if it is paired with additional case management services.
Abstract
					We estimate attainment effects of financial aid at a large community college. Using variation from a field experiment that altered how the college presented loans and a discontinuity in the Pell Grant formula, we separately identify the effects of grant aid and loans on short-run attainment. Although increases in Pell Grant aid cause students to reduce their borrowing, our experiment allows us to partial out the effect of any borrowing response on attainment. Both grants and loans significantly increase credits completed and grades.
Abstract
					Several recent studies have investigated the impact of college advising on whether students enter and succeed in postsecondary education. These papers generally find positive impacts from advising, yet few explore the extent of heterogeneity in impacts between program counselors. We take advantage of quasi-random counselor assignment to explore variation and correlates of college counselor effectiveness using rich administrative data on adviser-advisee interactions from a multisite randomized control trial of a college advising program. Large overall effects on college enrollment from the advising intervention are consistent across counselors; there is little relationship between counselor characteristics or behaviors and student outcomes.
Abstract
					The Right to Education (RTE) Act passed in 2009 guarantees access to free primary education to all children ages 6-14 in India. This paper investigates whether national trends in educational outcomes change around the time of this law using household surveys and administrative data. We document four trends: (1) school-going increases after the passage of RTE, (2) test scores decline dramatically after 2010, (3) school infrastructure appears to improve both before and after RTE, and (4) the number of students who have to repeat a grade falls precipitously after RTE is enacted, in line with official provisions of the law.
Abstract
					In this paper I ask whether peer effects generate changes in education investments in the areas where deported criminals are located in Central America using administrative data in El Salvador. I exploit the increase in criminal deportations from the United States in 1996 to analyze how individuals who grew up in municipalities affected by gangs in 1996 have fewer years of schooling when they are young adults. I find that individuals who were exposed during childhood to gang leaders have less schooling than those who were older than 16 in 1996 when the law was passed.
Abstract
					We analyze the effects of increased access to education in one generation on human capital outcomes in the next generation. Using longitudinal data, we exploit the geographical and cohort variations in exposure to a massive primary school construction program in the 1970s in Indonesia. We show that the school building project increases primary school completion rates among both men and women. We find that children whose mothers were exposed to the school building project score higher on the national primary school examination, suggesting the importance of maternal education in the intergenerational transmission of human capital.
Abstract
					A great advantage of our rigorous doctoral training is that as PhD economists we speak a common language that allows for efficient vetting and quick dissemination of ideas and insights. But what good is sophisticated grammar and a powerful vocabulary if the contents of our narratives are lacking? Our top three criteria for admissions to PhD programs are prior coursework in math, the quantitative GRE score, and prior coursework in economics. To attract top talent and prevent becoming a stagnant discipline that loses the influence we have in society and academia, students' creativity, originality, and drive should receive more weight.
Abstract
					This study examines male and female course persistence and choice of economics degree via a combination of student, instructor, and structural characteristics. We find that students of both genders who declare economics as their major are more likely to take additional economics courses than their non-major peers. Additionally, students' economics grades are a significant determinant of course persistence and degree selection, but men and women respond somewhat differently to their absolute and relative grades. Finally, men's economics degree selection is significantly correlated with their math abilities, while women's economics degree selection is correlated with both their math and verbal aptitudes.
Abstract
					This study investigates whether gender differences in SET vary over the course of a semester, particularly in response to feedback from the instructor. We survey principles of economics courses at multiple institutions three times during the semester to analyze whether the evaluations of male and female instructors change throughout the term, specifically after the first exam is returned. Results indicate a negative effect on evaluations for female instructors relative to male instructors associated with returning grades. This work shows the importance of understanding the dynamics of changes in evaluations within a course over the semester.
Abstract
					This study analyzes GPA data from the transcripts of college grades using the Baccalaureate and Beyond survey data from the National Center for Education Statistics at the US Department of Education. It reports GPAs overall and for 12 undergraduate majors including economics. The regression analysis investigates the likely effects of prior ability or achievement, demographics, and institutional variables on both the overall GPA and GPAs in selected academic subjects, including economics. Gender differences are explored for the marginal effects of taking a course in a subject and differences in the percentages of "A" grades earned when a course is taken.
Abstract
					This paper quantifies the impact of environmental policy on income inequality. We focus on the Clean Air act and the National Ambient Air Quality standards for fine particulate matter and ozone. Using a matched difference-in-differences estimator, we find evidence that both standards increased inequality in market income and a measure of income that deducts per-capita air pollution damage from adjusted gross income. While pollution standards can reduce pollution levels and thus result in significant environmental benefits in aggregate, our findings suggest that these standards appear to distort the distribution of economic resources in complex, and at times unfortunate, ways.
Abstract
					In the United States, ambient air quality is regulated through National Ambient Air Quality standards (NAAQS). Enforcement of these standards is delegated to state and sub-state regulators who are also tasked with designing their own monitoring networks for ambient pollution. Past work has found evidence consistent with strategic behavior: local regulators strategically avoid pollution hotspots when siting monitors. This paper assesses whether income and race have historically played a role in monitor siting decisions.
Abstract
					We use state-of-the-art, satellite-based PM 2.5 data products to assess the extent to which the Environmental Protection Agency's existing, monitor-based measurements over- or underestimate true exposure to PM 2.5 pollution. Treating satellite-based estimates as truth implies a substantial number of "policy errors"—overregulating areas that are in compliance with the air quality standards and under-regulating other areas that appear to be in violation. We investigate the health implications of these apparent errors. We also highlight the importance of accounting for prediction error in satellite-based estimates. Once prediction errors are accounted for, conclusions with regards to "policy errors" become substantially more uncertain.
Abstract
					This paper develops a simplified methodology to distribute total national income across income groups that reproduces closely the sophisticated methodology of Piketty, Saez, and Zucman (2018). It starts from top income share series based on fiscal income of Piketty and Saez (2003) and makes two basic assumptions on how national income components not included in fiscal income are distributed: (1) nontaxable labor income and capital income from pension funds are distributed like taxable labor income; (2) other nontaxable capital income is distributed like taxable capital income. This methodology could be applied to countries with less data.
Abstract
					Developing a national account-based measure of the distribution of income from the commonly used census-based concept of money income has been the subject of earlier research. We use publicly available survey and administrative data to construct a distribution of personal income after enhancing the top income distribution in the Current Population Survey (2007 and 2012). We show that inequality measures are fairly sensitive to the definition of income contemporaneously and across time. This work helps bridge the gap between micro data and macro statistics and informs about results from other studies, such as Piketty et al. (2018).
Abstract
					Many studies have used tax data to measure the U.S. income distribution, but their results vary widely. For example, in 2014 the top 1 percent share of income is 21.5 percent in Piketty and Saez (2003 and updates), 16.7 percent in the Congressional Budget Office (2018), and 13.1 percent in our analysis. What accounts for such large differences? We provide a step-by-step analysis of how methodological differences affect the results and address issues raised in Piketty, Saez, and Zucman (2018, 2019). Important differences include accounting for declining marriage rates, including social insurance and employer benefits, accounting for tax reforms, and including income missing from tax returns.
Abstract
					We study the evolution of superstar firms in the US economy over the past 60 years. Contrary to common wisdom, superstar firms have not become larger or more productive but have become more profitable. The contribution of star firms to aggregate US productivity growth has fallen over time, from about 72 basis points per year before 2000 down to about 43 afterwards.
Abstract
					We compute the "applications elasticity" as a proxy for firm-level labor supply elasticity by regressing the applications to a given job on the posted wage. The average applications elasticity in our data is 0.42. We then relate our elasticity estimates to concentration in labor markets defined by six-digit SOC occupations and commuting zone. We show a robust negative relationship between the two. Applications elasticity is near zero for all but the most densely populated labor markets, suggesting that 80 percent of the workforce works in labor markets where employers exercise significant monopsony power.
Abstract
					We extend the model in Azar and Vives (2018) to allow for investment and show that higher effective market concentration (augmented by common ownership) leads to lower equilibrium wages, real interest rates, lower output, lower labor share, and lower capital share as well (under a mild condition). We calibrate a multisector sector model of the US economy and find that the rise in common ownership may account for the broad evolution of labor and capital shares in the period 1985-2015 while measured increases in concentration cannot (under plausible values for elasticity parameters).
Abstract
					This paper evaluates the impact of the Affordable Care Act Medicaid expansions four years after implementation using data from the 2010-2017 National Health Interview Survey. We find that low-income adults in states that implemented the Medicaid expansions experienced increases in insurance and Medicaid coverage and improvements in access to health care across several measures.
Abstract
					This paper investigates how elite capture affects the welfare gains from targeted government transfer programs in Indonesia, using both a high-stakes field experiment that varied the extent of elite influence and nonexperimental data on a variety of existing government programs. While the relatives of those holding formal leadership positions are more likely to receive benefits in some programs, we argue that the welfare consequences of elite capture appear small: eliminating elite capture entirely would improve the welfare gains from these programs by less than one percent.
Abstract
					This paper presents a summary of recent evidence on long-term treatment effects from job search assistance and training services on labor market outcomes. The evidence is based on merging program data from three randomized controlled trials (RCTs) to administrative tax data. The RCTs are for the following programs: the Nevada Reemployment Eligibility Assessment program, Workforce Investment Act Adult and Dislocated Worker programs, and the Job Corps program.
Abstract
					Although technology-driven economic growth generates gains in consumption and employment opportunities, it may also negatively impact other dimensions of well-being, such as emotional well-being or sense of stability. We study 204 aspects of self-reported well-being among 1,576 US MTurk survey respondents, aggregated into seven themes: evaluative well-being, emotional well-being, positive perceptions of technology or economic growth, autonomy and flexibility, work environment, feelings of calmness and stability, and feelings of belonging and connection. Demographic associations with aspects of well-being vary somewhat across the themes. We highlight the value of a multidimensional approach when comparing well-being across different groups in the United States.
Abstract
					Gig work mediated through online platforms has received much recent attention. We find only one sector—the transportation services sector—in which there is unambiguous evidence of substantial and rapidly growing gig activity. A challenge for tracking and understanding the rise in gig activity is that core household surveys are missing the recent overall rise in self-employment that is apparent in administrative and private sector transactions data. We show that this limitation of available household survey data is evident even in the transportation services sector, where the growth in self-employment activity since 2013 has been exponential.
Abstract
					Measuring the gig economy has been challenging. Drawing on anonymized administrative banking data, we measure supply-side participation in the online platform economy between 2013 and 2018. We find 2.3 million account holders who received payments from 128 transportation, non-transport work, selling, and leasing platforms. Participation grew rapidly, particularly in the transportation sector. Average monthly revenues declined among drivers and increased among lessors even within metro areas. At least a third—and likely more—of the decline in transportation revenues is driven by decreases in hours worked. These findings raise important policy questions and motivate promising directions for future work.
Abstract
					The gig economy is widely regarded to be a source of secondary or temporary income, but little is known about economic activity outside of the gig economy. Using data from a large, online personal finance application, I document the evolution of non-gig income and household balance sheets surrounding the participation decision for gig economy jobs. This simple analysis reveals striking pretrends in income and assets. In addition to providing insight into the reasons why households enter the gig economy, these findings have potentially important implications for the external validity of previous studies focusing on gig economy activity only.
Abstract
					As the workforce ages, how will the work lives of older people evolve? One way to ease into retirement is to move to the gig economy where workers choose hours and intensity of work that fit their needs and capabilities. However, older workers are often reaping the benefits of the latter end of an implicit contract while gig economy workers are paid their marginal product. We show that age/earnings profiles in the traditional labor market are different than for Uber drivers. While the move to the gig economy generates flexibility, older workers are paid less than their younger coworkers.
Abstract
					Using a 1994 law change, we exploit quasi-experimental variation in the assignment of rent control in San Francisco to study which types of landlords bear the burden of decreased rental payments versus substitute away from supplying rent-controlled housing. We find rent control leads to a long-run decrease in the supply of rental housing. This effect is more pronounced among properties managed by corporate landlords versus individual landlords. Raising revenue for rental subsidies through rent control appears to be regressive, since corporations can evade the tax burden of rent control more easily, likely due to their superior access to capital.
Abstract
					Using detailed location-specific criminal incident-level data, we find that sudden rent decontrol in Cambridge, Massachusetts in 1995 caused overall crime to fall by 16 percent—approximately 1,200 crimes annually. We estimate that this annual direct benefit to Cambridge residents was roughly $10 million (in 2008 dollars), accounting for 10 percent of the growth in the Cambridge residential property values attributable to decontrol.
Abstract
					Second generation rent control seeks to prevent negative quantity effects by exempting newly built units. The artificially lowered rent in the controlled segment makes renting attractive for households that would otherwise not have rented in the market, replacing households with higher willingness to pay for housing. These households bid up prices in the free market segment, giving rise to an opposite-sign spillover from the controlled to the free market (Mense, Michelsen, and Kholodilin 2017). This paper documents a positive effect of "second generation" rent control on the value of vacant, buildable land.
Abstract
					In many global cities the rental housing market is partially regulated. We document that the Paris housing market is dual: a flexible rent sector coexists with a large controlled rent sector. The two sectors have very different rent gradients towards the center of the agglomeration. We develop a model explicitly accounting for these features which allows to investigate general equilibrium effects of rent controls at the city level. In this framework the coexistence of a controlled and flexible rent sector increases the spatial misallocation of households. This mismatch can generally be alleviated by an improvement in urban transport infrastructures.
Abstract
					Building on insights from the differential privacy literature, we develop a simple noise-infusion method to reduce privacy loss when disclosing statistics such as OLS regression estimates based on small samples. Although our method does not offer a formal privacy guarantee, it outperforms widely used methods of disclosure limitation such as count-based cell suppression both in terms of privacy loss and statistical bias. We illustrate how the method can be implemented by discussing how it was used to release estimates of social mobility by census tract in the Opportunity Atlas. We provide a step-by-step guide and code to implement our approach.
Abstract
					In low-rate environments, policy strategies that involve holding rates "lower for longer" (L4L) may mitigate the effects of the effective lower bound (ELB). However, these strategies work in part by managing the public's expectations, which is not always realistic. Using the Fed's large-scale macroeconometric model, we study the effectiveness of L4L policies when financial market participants are forward-looking but other agents are not. We find that the resulting limited ability to manage expectations reduces but does not eliminate the advantages of L4L policies. The best policies provide adequate stimulus at the ELB while avoiding sizable overshoots of inflation and output.
Abstract
					We reconsider several monetary and fiscal policies that have been proposed as tools of stabilization policy when conventional interest-rate policy is constrained by the zero lower bound on interest rates, assuming that households and firms are capable of explicit forward planning over only a limited horizon. The predicted effects of all of the policies are somewhat different than under rational expectations, but credible announcements about future policy can still influence behavior, and there is, if anything, an even stronger case for pursuing systematic policies outside crisis periods in order to shape expectations during a crisis.
Abstract
					Key macro indicators such as output, productivity, and inflation are based on a complex system across multiple statistical agencies using different samples and levels of aggregation. The Census Bureau collects nominal sales, the Bureau of Labor Statistics collects prices, and the Bureau of Economic Analysis constructs nominal and real GDP using these data and other sources. The price and quantity data are integrated at a high level of aggregation. This paper explores alternative methods for reengineering key national output and price indices using item-level data. Such reengineering offers the promise of greatly improved key economic indicators along many dimensions.
Abstract
					We use tailored surveys and benchmarking in the flat-weave rug industry to better understand the shortcomings of standard productivity measures. Quantity-based productivity (TFPQ) performs poorly because of variation in product specifications across firms. Controlling for specifications aligns TFPQ with lab benchmarks. We also collect quality metrics to construct quality productivity (the ability to produce quality given inputs) and find substantial dispersion across firms. This motivates interest in multidimensional productivity, or capability. As quality productivity is negatively correlated with TFPQ, revenue-based productivity (TFPR) may perform better at capturing capabilities in settings where better firms make products with more demanding specifications that have greater input requirements.
Abstract
					One of the most successful empirical relationships in international trade is the gravity equation. A key decision for researchers in estimating this relationship is the level of aggregation, since the gravity equation is log linear, whereas aggregation involves summing the level rather than the log of trade. In this paper, we derive a Jensen's inequality correction term for nested constant elasticity of substitution preferences, such that a log-linear gravity equation holds exactly for each nest. We provide evidence that sectoral composition is quantitatively relevant for the aggregate effect of distance on international trade, particularly for more disaggregated definitions of sectors.
Abstract
					This paper presents new estimates of gross worker flows for Canada for the sample period 1978 to 2016. We use administrative data from the Canadian Record of Employment in combination with the Canadian Labor Force Survey to estimate employer-to-employer flows in addition to flows between labor market states. We highlight three main results: Roughly two-thirds of all job separations are employer-to-employer flows. Employer-to-Employer flows are highly procyclical. The combination of these two results means that total job separations are procyclical. If employer-to-employer flows improve match quality, our results imply that recessions have a sullying effect on the labor market.
Abstract
					We investigate the origins of cyclical and trend movements in the labor force participation rate (LFPR) using a three-state flow decomposition. The procyclicality of LFPR can be traced to cyclical flows between employment and unemployment. By contrast, labor force entry and exit explain virtually all of the trend movements. Among men, rising labor force exit rates account for two-thirds of the trend decline in male LFPR since the 1990s. For women, trend increases in female LFPR during the 1990s were dominated by declining exit rates, while the trend decline since the Great Recession can be traced to declining entry rates.
Abstract
					Tightening labor markets in the United States and other advanced economies suggest inflation should be on the rise, yet it remains subdued. Is the Phillips curve broken? We bring together surveys of household or firm expectations for 18 countries to estimate an expectations-augmented Phillips curve. We find strong evidence of a Phillips curve relationship: the Phillips curve is alive and well. The fact that inflation remains well below inflation expectations, both in the United States and abroad, suggests that there remains significant slack in labor markets.
Abstract
					This paper briefly reviews the measurement of the magnitude of profit shifting by multinational firms. Highlighting differences between estimates using microeconomic and macroeconomic approaches, it sketches a conceptual framework that can help explain these divergent estimates. In particular, these approaches arguably differ in their conceptualization of the boundary between tax avoidance and behavioral responses to taxes. The paper also discusses the future of profit shifting, drawing on a data set that codes anti-avoidance measures undertaken by OECD countries over the period of 2000-2014. Governments have significantly strengthened these rules over this period, despite collective action problems that potentially inhibit their implementation.
Abstract
					Why do some firms adopt certain tax havens, and how sensitive is the demand for tax havens? We address these questions by studying how the repeal of section 936 tax credits affected firms with affiliates in Puerto Rico. We first describe the characteristics of US multinationals that were exposed to section 936. We then show that the market value of exposed firms decreased after losing access to section 936, implying that firms could not perfectly substitute to other tax havens. Finally, we find that firms exposed to section 936 did not respond by expanding their network of tax havens.
Abstract
					This paper reviews common challenges of taxing multinational firms, using Chile as a case study. We briefly describe key international tax avoidance methods: profit shifting to low-tax jurisdictions through transfer pricing and debt shifting. We discuss the prevalent policy to tax multinationals—the arm's length principle—and alternative proposals using apportionment formulas. Novel data from Chile show that multinationals make up a large share of GDP but report lower profit and effective tax rates than local firms. In 2011, Chile implemented a reform following OECD guidelines to enforce the arm's length principle. We discuss potential effects on tax collection and welfare.
Abstract
					When the names of banks that borrow from an emergency lending facility are inadvertently leaked, the facility may become stigmatized. We examine how the quality of the borrowing pool of banks changed when stigma was unexpectedly introduced at a once confidential lending facility during the Great Depression. This facility experienced a compositional shift in the quality of its borrowing pool, where only weaker banks that maintained smaller liquidity buffers used the facility, while an alternative confidential facility attracted stronger banks. Our results shed light on how the design of lending facilities may attract certain types of banks.
Abstract
					Does health insurance affect fertility decisions? Fertility may increase if insurance lowers the costs of having a child. Fertility may decrease if children are more likely to survive into adulthood (quality-quantity tradeoff). We study a largely permanent United Mine Workers of America (UMWA) insurance program. A large group of women of childbearing age gained pregnancy coverage for the first time. The insurance also covered children. We use a trend break specification with county-level variation in insurance. We find new evidence of the quality-quantity tradeoff. Fertility rates declined by about one percent per year in counties with average levels of insurance.
Abstract
					In many settings, traditional medicine is a popular, accessible, and affordable alternative to modern medicine. Understanding the determinants of the use of traditional medicine is important because it is widespread and because of the growing evidence of mistrust in modern medicine. We examine the historical and present day correlates of knowledge and use of traditional medicine in Central Africa. We find that type of colonial contact matters for present day traditional medicine use and that belief in witchcraft predicts more use of traditional medicine. We suggest that traditional healers may play an important role in rebuilding trust in modern medicine.
Abstract
					International currencies play important roles as foreign exchange reserves but are also most frequently used to denominate corporate and government bonds, bank loans, and import and export invoices. These currencies offer unrivaled liquidity, constituting large shares of the volume on global foreign exchange markets, and are commonly chosen as the anchors targeted by countries with pegged or managed exchange rate regimes. We provide evidence suggesting a recent rise in the use of the dollar, and fall of the use of the euro, with similar patterns manifesting across all these aspects of international currency use.
Abstract
					We show empirically that the variation across country pairs in exchange rate pass-through and trade elasticity is meaningfully explained by the dollar's dominance as invoicing currency. We use a hierarchical Bayesian approach to directly and flexibly model pass-through heterogeneity conditional on the invoicing currency share. We estimate that the importer's country-level dollar invoicing share explains 15 percent of the overall variance across trading pairs in dollar exchange rate pass-through into bilateral prices.
Abstract
					Do differences in border price adjustment by currency of invoicing carry over to allocations? We document the cross-industry variation in the response of Swiss export prices and export values by currency of invoicing of border prices in the aftermath of the large and abrupt Swiss franc (CHF) appreciation in January 2015. Industries with higher CHF-invoicing shares (and a larger increase in foreign-currency denominated prices) experienced substantially weaker export growth in the two-year period after January 2015.
Abstract
					Cognitive abilities help explain the large cross-sectional variation in inflation expectations at the household level. But which type of cognitive abilities are important? We find that not only quantitative abilities but also logical and verbal abilities are important to explain the accuracy and plausibility of households' inflation expectations. We discuss the channels through which different forms of cognition might shape households' abilities to forecast future macroeconomic variables. We also draw implications for the effectiveness of policies that aim to manage households' expectations.
Abstract
					Growing evidence in macrofinance suggests long-lasting effects of personally experienced outcomes on beliefs. To understand the underlying mechanism we turn to the neurological foundations of memory formation. We propose that emotional tagging plays a crucial role in assigning weights in the belief formation process. We use exposure to communism as well as variation in its emotional tagging to predict long-run beliefs. We show that living under communism has long-term effects on beliefs about its benefits. In addition, positive and negative emotional tags strongly affect the (pro- or anti-communist) direction of beliefs, providing anchors to memory that seem hard to reverse.
Abstract
					Loewenstein and Simonsohn (2006) found that movers across US cities anchor their rental choices to rents in the city of origin, but subsequently converge to comparable local households. We explain this finding using the authors' (2019) model of memory and attention. Rents in the destination city cue recall of "normal" rents in the city of origin, making the former surprisingly high or low, causing movers to under- or overspend, respectively. Over time, experience with new city rents allows the memory database to adapt, and the effect fades away. The model yields two new predictions, for which we find supportive evidence.
Abstract
					Patents and other intellectual property (IP) have grown in relative importance in investments and market capitalizations of public firms (e.g., Corrado and Hulten 2010). This paper illustrates the construction of IP-intensive stock price indexes, focusing on a network analysis tool (Martin 2001, Winer et al. 2003, Luse and Martin 2014) that helps pinpoint firms that are most likely to generate value from their intangible assets. The analysis finds that (a) stock price indexes constructed using the tool yield above-average returns and (b) stock prices of US companies in two tech-driven sectors outperform non-US firms despite lower average patent portfolio valuations.
Abstract
					The last 40 years have seen huge innovations in computing and in the availability of data. Data derived from millions of administrative records or by using (as we do) new methods of data generation such as text mining are now common. New data often requires new methods, which in turn can inspire new data collection. If history is any guide, some methods will stick and others will prove to be a flash in the pan. However, the larger trends toward demanding greater credibility and transparency from researchers in applied economics and a 'collage' approach to assembling evidence will likely continue.
Abstract
					This study provides a first assessment of awareness of, attitudes toward, perceived norms regarding, and adoption of open science practices within a broadly representative sample of active economics researchers. We observe a steep increase in adoption over the last decade, with an accelerating trend: as of 2017, 93 percent of economists had used at least one such practice—including posting data, sharing study materials, and study pre-registration—rising from 33 percent a decade earlier. We document extensive variation in adoption across economics subfields. Notably, most economists appear to underestimate the trend toward research transparency in the discipline.
Abstract
					We propose a specification check for p-hacking. More specifically, we advocate the reporting of t-curves and mu-curves—the t-statistics and estimated effect sizes derived from regressions using every possible combination of control variables from the researcher's set—and introduce a standardized and accessible implementation. Our specification check allows researchers, referees, and editors to visually inspect variation in effect sizes, significativity, and sensitivity to the inclusion of control variables. We provide a Stata command that implements the specification check. Given the growing interest in estimating causal effects, the potential applicability of this specification check to empirical studies is large.
Abstract
					Scholars assert that pre-analysis plans (PAPs) generate boring, lab-report style papers and thus hamper publication. We test this claim by comparing the publication rates of experimental NBER working papers with and without PAPs. We find that articles with PAPs are slightly less likely to be published. However, conditional on being published, PAP-generated papers are significantly more likely to land in top-five journals. Also, PAP-based journal articles generate more citations. Our findings suggest that the alleged trade-off between career concerns and the scientific credibility that comes from registering and adhering to a PAP is less stark than is sometimes alleged.
Abstract
					Forecasts of experimental results can clarify the interpretation of research results, mitigate publication bias, and improve experimental designs. We collect forecasts of the results of three Registered Reports preliminarily accepted to the Journal of Development Economics, randomly varying four features: (1) small versus large reference values, (2) whether predictions are in raw units or standard deviations, (3) text-entry versus slider responses, and (4) small versus large slider bounds. Forecasts are generally robust to elicitation features, though wider slider bounds are associated with higher forecasts throughout the forecast distribution. We make preliminary recommendations on how many forecasts should be gathered.
Abstract
					How do ethical arguments affect AI adoption in business? We randomly expose business decision-makers to arguments used in AI fairness activism. Arguments emphasizing the inescapability of algorithmic bias lead managers to abandon AI for manual review by humans and report greater expectations about lawsuits and negative PR. These effects persist even when AI lowers gender and racial disparities and when engineering investments to address AI fairness are feasible. Emphasis on status quo comparisons yields opposite effects. We also measure the effects of "scientific veneer" in AI ethics arguments. Scientific veneer changes managerial behavior but does not asymmetrically benefit favorable (versus critical) AI activism.
Abstract
					Policymakers often express concern about the impact of carbon taxes on employment or GDP. Using a new dataset on carbon tax rates, we estimate the macroeconomic impacts of these taxes on GDP and employment growth rates for various specifications and samples. Our point estimates suggest a zero to modest positive impact on GDP and total employment growth rates. More importantly, we find no robust evidence of a negative effect of the tax on employment or GDP growth. For the European experience at least, we find no support for the view that carbon taxes are job or growth killers.
Abstract
					This paper explores the fiscal consequences of climate change. The analysis considers climate change impacts on (i) the cost of existing government services (e.g., disaster assistance) and (ii) the need for publicly provided anticipatory adaptation (e.g., sea walls). These channels are integrated into the COMET, a dynamic general equilibrium climate-economy model with distortionary taxation and government expenditures. The main result is that accounting for fiscal impacts may increase the welfare benefits of efficient climate policy by up to 30 percent. Business-as-usual climate change may necessitate increases in income tax rates and elevate the marginal cost of raising public funds.
Abstract
					While a firm knows the carbon price with certainty under a tax, it must form an expectation about future allowance prices to identify its cost-effective abatement investment under a cap-and-trade program. We illustrate graphically how errors in forming this expectation increase the costs of irreversible pollution abatement investment under cap-and-trade relative to a tax. We describe empirical "cost-effectiveness anomalies" in allowance markets that may be attributed to cap-and-trade's inherent uncertainty. We model investment under simulated US carbon tax and cap-and-trade policies and find that allowance price uncertainty can increase resource costs 20 percent for a given quantity of emission abatement.
Abstract
					Credit markets typically freeze in recessions: access to credit declines, and the cost of credit increases. A conventional policy response is to rely on monetary tools to saturate financial markets with liquidity. Given limited space for monetary policy in the current economic conditions, we study how fiscal stimulus can influence local credit markets. Using rich geographical variation in US federal government contracts, we document that, in a local economy, interest rates on consumer loans decrease in response to an expansionary government spending shock.
Abstract
					In a world where monetary policy cannot assume responsibility for stabilization policy, there is a strong need for fiscal policy to address stabilization issues. In this context, we argue for "semi-automatic stabilizers," aimed at reducing unemployment slumps rather than output recessions. We show that the hole left by the limits on monetary policy implies a large role for fiscal policy in general and for semi-automatic stabilizers in particular. Finally, we argue that the design of stabilizers, whether they focus on mechanisms that rely primarily on income or on intertemporal substitution effects, depends crucially on the general design of discretionary policy.
Abstract
					Countercyclical fiscal policy generally focuses on national economic downturns. But US states experience significantly different patterns of unemployment, and demand shocks appear to drive much of that variation. State budget rules limit the ability of states to mount their own countercyclical policies. Federal taxes and spending programs have countercyclical effects within states, but the magnitude of those effects depends on policies that were designed based on other considerations (just as the extent of national automatic stabilizers is the result of policies based on other considerations). Enacting countercyclical fiscal policy calibrated to state unemployment rates would reduce the cost of recessions.
Abstract
					Debt-to-GDP ratios across developed economies are at historically high levels, and government borrowing rates remain persistently low. Blanchard (2019) provides evidence that the fiscal costs and welfare costs are low of increased government debt in low interest rate environments. This paper attempts to replicate Blanchard's main results and tests their robustness to key assumptions about risk in the model. This study finds that Blanchard's stated approach results in no long-run average welfare gains from increased government debt and that those welfare losses are exacerbated if some strong risk-reducing assumptions are relaxed to more realistic values.
Abstract
					The rise of freelance work in the online platform economy (OPE) has received considerable media and policy attention in recent years, but freelance work is by no means a new phenomenon. In this paper, we draw on IRS tax records to identify instances when workers begin doing online platform work versus other freelance/independent contractor "gig" work for firms. We find gig work occurs around major reductions in outside income and document usage over the lifecycle. Our results provide suggestive evidence on motivations for entering into each type of work.
Abstract
					Ensuring tax compliance is an enduring problem for governments in all countries. In this paper, we examine the role of information reporting in increasing tax compliance. We first discuss the practice of information reporting in the US, including a recent IRS initiative that implemented information reporting for income received through debit and credit cards via the new Form 1099-K. We then review the literature on the compliance effects of information reporting. Finally, we report some new evidence that indicates that Form 1099-K information reporting had significant—but heterogeneous—impacts on compliance rates of different types of business reporting.
Abstract
					The banking sector is sometimes characterized by dysfunctional culture, but little is known about what values bankers hold. We gather data on employee values in a large multinational bank and measure alignment within the bank and with broader society. We find that bankers at the bottom of the hierarchy hold values that are mirrors of their societies, but the top-ranked bankers hold values that are most distinct from their countries. These distinctive values are those with the greatest impact on performance and potential for promotion, suggesting a possible trade-off between coherence within the organization and dissonance with society.
Abstract
					This paper explores the relationship between individual identity and organizational attachment. Using individual data from employees at a large employer in the services sector, we show that making individual values salient (through a value affirmation) on average reduces organizational attachment. However, this effect is heterogenous across individuals: those initially attached to the organization increase their attachment, while those who started off less identified with the organization reduce their attachment. Overall, the results illustrate the importance of heterogeneity and how individual identity/values and organizational attachment can conflict.
Abstract
					Women continue to be underrepresented in academic ranks in the economics profession. The Committee on the Status of Women in the Economics Profession of the American Economic Association established the CeMENT mentoring workshop to support women in research careers. The program was designed as a randomized controlled trial. This study evaluates differences between the treatment and control groups in career outcomes. Results indicate that relative to women in the control group, treated women are more likely to stay in academia and more likely to have received tenure in an institution ranked in the top 30 or 50 in economics in the world.
Abstract
					We contribute to the literature on diversity in the economics profession, which has mostly focused on academia, by providing a first look at the employment and earnings of federal government economists by gender and race. Combining micro-level data on federal workers with information on their earnings in federal and private sector jobs, we examine the share of federal government economists by race and gender, earnings differences by race and gender, and whether earning gaps differ during their federal government tenure.
Abstract
					Salary history bans forbid employers from asking job candidates to disclose their salaries. However, applicants can still volunteer this information. Our theoretical model predicts that the effect of these laws varies by how workers comply. Our survey of Americans in the labor force finds candidates fall into three compliance types: 25 percent always disclose their salary whether asked or not, 17 percent never disclose, and 58 percent comply with the ban. Importantly, compliance type varies by demographics (e.g. always-disclosers are more male, compliers are more female), and workers are more likely to disclose as others do the same, which suggests unraveling.
Abstract
					This paper quantifies the impact of the Vietnam War on fertility rates in the late 1960s and early 1970s. For draft-eligible men wishing to avoid military service, the hardship deferment (III-A) for paternity created a powerful incentive to father a child. We provide a time series analysis suggesting that the risk of being drafted and the availability of the paternity deferments significantly increased US fertility rates, especially among childless women likely to be partnered with draft-eligible men. Our results suggest caution in attributing the decline in fertility after 1970 solely to the legalization of abortion.
Abstract
					What do historical changes in legal access to reproductive health care technology tell us about the long-run effects of such changes? We investigate this question using data from the Health and Retirement Study and an identification strategy leveraging variation in exposure to legal changes in access across cohorts born in the same states. We find positive effects on educational attainment that align with prior work but are not statistically significant. We also find positive effects on working in a Social Security-covered job in women's 20s and 30s but no evidence of positive effects on women's earnings in their 50s.
Abstract
					This paper reexamines the association between local economic conditions and fertility using a new dataset of county-level birthrates and per capita income in the United States spanning the period 1937–2016. Using a panel data model, we estimate that growth in local income is positively associated with birthrates over our entire sample period and that the strength of that association peaked during the 1960–1990 period and has declined in recent decades. We additionally estimate dynamic responses to local income shocks, finding that birthrates remain elevated for up to four years after a shock.
Abstract
					Organizations miss out if their smartest members do not bring their ideas to the table. Gallus and Heikensten (2019) establish that gender differences play an important role for female participation in STEM fields (science, technology, engineering, and math). Moreover, they show that these differences can be eliminated by providing suitable forms of social recognition via awards. This article focuses on self-stereotyping and explores its role as a mechanism behind the effect of recognition on the gender gap in the tendency to speak up.
Abstract
					Why are women underrepresented in the fields of science, technology, and innovation? Using a sample of Gates and NIH grant applications submitted by a common pool of US-based academic researchers, we implement a range of text analysis methods associated with gendered language. We find that despite significant institutional differences, there are consistent gender differences in scientific communication. By contrast, we find starkly differing impacts of these text characteristics on funding outcomes across our institutional settings. Our findings suggest that institutional reform is likely to be a viable strategy for increasing gender inclusion in science and technology.
Abstract
					We study whether increasing the share of female inventors leads to more biomedical inventions that focus on the needs of women. After accounting for detailed disease-technology, disease-year, and technology-year fixed effects, we find that a 10 percentage point increase in the share of female inventors in a research area yields 1.2 percentage points more female-focused patents. Notably, this effect only holds for female-led invention teams. Areas with a greater share of female inventors in supporting roles do not produce more female-focused inventions. For gender to impact the direction of invention, it appears that women must occupy positions of power.
Abstract
					This paper studies the spread of antibiotic resistance and its determinants, relying on unique data at state, year, bacteria, and drug level, covering all US states. I relate antibiotic resistance to the use of antibiotics in human prescription and animal production in a triple difference-in-difference design to control for confounders. Despite that animal production absorbs most of the antibiotic production, the results show that the main determinant of resistance is in fact human prescriptions, emphasizing the role of policies targeting hospitals and ambulatory care. Resistance is particularly sensitive to antibiotic use for newer drugs.
Abstract
					Postmortems on the recent Ebola outbreak in West Africa suggest that effective community engagement helped slow transmission by encouraging people to come forward and be tested. We evaluate the impact of Community Care Centers: a new crisis response model designed to allay fears about western medical care and, thus, encourage early reporting, isolation, and treatment. We employ new panel data on reported Ebola cases and a difference-in-difference design and find that Community Care Centers dramatically increased reporting, potentially reducing the spread of Ebola. Our results highlight how community-based efforts to increase confidence in health systems can be critical for crisis management.
Abstract
					Ten years ago, donors committed $1.5 billion to a pilot Advance Market Commitment (AMC) to help purchase pneumococcal vaccine for low-income countries. The AMC aimed to encourage the development of such vaccines, ensure distribution to children in low-income countries, and pilot the AMC mechanism for possible future use. Three vaccines have been developed and more than 150 million children immunized, saving an estimated 700,000 lives. This paper reviews the economic logic behind AMCs, the experience with the pilot, and key issues for future AMCs.
Abstract
					This paper measures the costs and types of administrative inputs in health care. We use data on labor and nonlabor inputs by industry and categorize them as administrative or not. We find that nonlabor inputs are a critical part of administrative spending, over and above labor inputs. Trends in nonlabor administrative input spending have differed dramatically from that of labor input spending for hospitals over the last 20 years. Hospitals have substituted away from office workers and toward externally purchased inputs. The share of managers and technical workers in administration has grown. The technology of health care administration is changing.
Abstract
					One of the most challenging environments in health care is the emergency department (ED) A key decision-maker in that context is triage nurses, who assess patient illness severity and influence wait times for medical attention. We gather novel data on the triage process across 108 EDs, including wait times, triage nurse identities and assessments, and detailed patient information and outcomes. Using quasi-random assignment to ED, we find a striking rate of "inversions," where patients who are sicker based on either ex ante information or ex post outcomes are scored as sicker and wait longer than their healthier counterparts.
Abstract
					Using data on more than 250,000 emergency department (ED) visits, we study the time-of-day effect on physician decision-making and patient outcomes. After controlling for patient characteristics, physician fixed effects, and work hours, we find that cases treated at night have significantly lower probability of inpatient admission and involve fewer medical tests. These cases are also more likely to revisit the ED, which supports the decline in physician performance. While we cannot completely rule out the possibility of limited hospital arrangements, our findings are most consistent with the detrimental effect of disrupted circadian rhythms during night shifts.
Abstract
					We test for the importance of nudges in improving student performance in introductory economics courses at UNC-Chapel Hill. We use a randomized controlled trial to test the effectiveness of nudges in encouraging use of academic supports and (jointly) the use of these supports on academic performance. With our aggregated sample the average treatment effects take the correct sign but are uniformly statistically insignificant. This near-zero average effect masks large and significant effects of nudges among subgroups of individuals: females, first years, and individuals of color. Our results identify subgroup-activity pairings for which nudges work at the margin to encourage participation.
Abstract
					Using administrative and survey data, we diagnose the learning environment in an introductory economics course. Relative to men from overrepresented groups, women and underrepresented minority students finish the course reporting significantly lower measures of relevance, belonging, and growth mindsets, factors related to college success. For example, they are less likely to agree that their professor used relatable examples, more likely to report feeling different than the typical economics major, and less likely to report believing they could learn the material. We also describe a new, low-cost initiative expanding the role of undergraduate teaching assistants to promote a more inclusive environment.
Abstract
					University of Toronto undergraduates can choose between conventional and literacy-targeted (LT) principles of economics courses. We compare demographics and performance in subsequent courses for 13,000 students over 11 years and find that LT courses attract a greater percentage of female and domestic students; conditional on meeting grade thresholds, LT students do just as well in intermediate theory and statistics courses as conventional principles students; women do as well or better than men in intermediate theory and statistics courses. With appropriately chosen thresholds, departments offering LT courses can preserve subsequent disciplinary rigor and address underrepresentation of women and minorities.
Abstract
					Substantial evidence suggests active learning pedagogies are superior to lecturing, but little evidence exists on the prevalence of such methods. Watts and Schaur (2011) find, based on self-reported data, the median instructor lectures 83 percent of the time. We analyze audio recordings of 535 total classes from 30 different instructors to show instructors greatly underestimate how often they use passive learning pedagogies such as lecturing. Survey results show instructors estimate they lecture approximately 78.5 percent of class time; our data reveals the true average is 89 percent. This gap between perception and reality is statistically significant.
Abstract
					This research establishes the influence of linguistic traits on human behavior. Exploiting variations in the languages spoken by children of migrants with identical ancestral countries of origin, the analysis indicates that the presence of periphrastic future tense and its association with long-term orientation has a significant positive impact on educational attainment, whereas the presence of sex-based grammatical gender, and its association with gender bias, has a significant adverse impact on female educational attainment.
Abstract
					We study the cost of being too patient on happiness. We find that the relationship between patience and various measures of subjective well-being is hump-shaped: there exists an optimal amount of patience that maximizes happiness. Beyond this optimal level, higher levels of patience have a negative impact on well-being.
Abstract
					This paper shows that contemporary population-level heterogeneity in risk aversion, time preference, altruism, positive reciprocity, negative reciprocity, and trust partly traces back to the structure of the migration patterns of our very early ancestors. To document this pattern, we link differences in preferences between populations to the length of time elapsed since the ancestors of the respective groups broke apart from each other, as proxied by genetic and linguistic distance measures. Preference differences are significantly increasing in ancestral distance in both cross-country regressions and within-country analyses across groups of migrants.
Abstract
					Willingness to migrate is a necessary but not sufficient condition for migration from an origin to destination country. For the United States and other countries with an excess supply of immigrants, the slot-rationing rule is a key determinant of immigrant composition not captured by supply-based models. A stylized rationing-based model better explains the attainment of immigrants in both the United States and Sweden with the model's two variables explaining over 50 percent of the variation in origin country education attainment and earnings.
Abstract
					We document that, in the early twentieth century, children of immigrants who were given more-foreign first names completed fewer years of schooling, earned less, and married less assimilated spouses. However, we find few differences in the adult outcomes of brothers with more/less foreign-sounding first names. This pattern suggests that the negative association between ethnic names and adult outcomes in this era does not stem from discrimination on the basis of first names but instead reflects household differences associated with cultural assimilation. We cannot rule out discrimination on the basis of other ethnic cues.
Abstract
					The race between education and technology provides a canonical framework that does a remarkable job of explaining US wage structure changes across the twentieth century. The framework involves secular increases in the demand for more-educated workers from skill-biased technological change, combined with variations in the supply of skills from changes in educational access. We expand the analysis backward and forward. The framework helps explain rising skill differentials in the nineteenth and twenty-first centuries but needs to be augmented to illuminate the recent convexification of education returns and implied slowdown in the growth of the relative demand for college workers.
Abstract
					We conduct an empirical simulation exercise that gauges the plausible impact of increased rates of college attainment on a variety of measures of income inequality and economic insecurity. Using two different methodological approaches⁠—a distributional approach and a causal parameter approach⁠—we find that increased rates of BA and AA attainment would meaningfully increase economic security for lower income individuals and shrink gaps between the 90th percentile and lower percentiles. Increases in college attainment would not significantly reduce inequality at the very top of the distribution, as measured by the 99/90 earnings ratio.
Abstract
					We extend the canonical model of skill-biased technical change by modeling the allocation of tasks to factors and allowing for automation and the creation of new tasks. In our model, factor prices depend on the set of tasks they perform. Automation can reduce real wages and generate sizable changes in inequality associated with small productivity gains. New tasks can increase or reduce inequality depending on whether they are performed by skilled or unskilled workers. Industry-level data suggest that automation significantly contributed to the rising skill premium, while new tasks reduced inequality in the past but have contributed to inequality recently.
Abstract
					In this paper, we use detailed job vacancy data to estimate changes in skill demand in the years since the Great Recession. The share of job vacancies requiring a bachelor's degree increased by more than 60 percent between 2007 and 2019, with faster growth in professional occupations and high-wage cities. Since the labor market was becoming tighter over this period, cyclical "upskilling" is unlikely to explain our findings.
Abstract
					We study the firm-level implications of robot adoption in France. Of 55,390 firms in our sample, 598 adopted robots between 2010 and 2015, but these firms accounted for 20 percent of manufacturing employment. Adopters experienced significant declines in labor shares, the share of production workers in employment, and increases in value added and productivity. They expand their overall employment as well. However, this expansion comes at the expense of competitors, leading to an overall negative association between adoption and employment. Robot adoption has a large impact on the labor share because adopters are larger and grow faster than their competitors.
Abstract
					Studying firm-level adjustments is important for understanding the economic effects of workplace automation. So far, emerging firm-level evidence is focused on robotics and the manufacturing sector. In this paper, we document that the adoption of automation technologies extends beyond manufacturing firms. We identify firm-level automation events and show that automating firms experience faster employment and revenue growth than do nonautomating firms. However, around automation events themselves, employment growth slows markedly. Notably, we find that these effects are similar for manufacturing and nonmanufacturing firms, suggesting that an increasing diffusion of automation technology has important consequences for firms and their workers.
Abstract
					This paper measures aggregate changes in job characteristics in the United States from 2005 to 2015 and decomposes those changes into components representing shifts within occupations and changes in occupational employment shares. Per our title, within-occupation changes dominate, raising doubts about the ability of projections based on expected changes in the occupational composition of employment to capture the likely future of work. Indeed, our data show only weak relationships between automatability, repetitiveness, and other job attributes and changes in occupational employment. The results suggest that analysts give greater attention to within-occupation impacts of technology in assessing the future of work.
Abstract
					This paper documents a puzzle. Despite the numerous popular press discussions of artificial intelligence (AI) in health care, there has been relatively little adoption. Using data from Burning Glass Technologies on millions of online job postings, we find that AI adoption in health care remains substantially lower than in most other industries and that under 3 percent of the hospitals in our data posted any jobs requiring AI skills from 2015–2018. The low adoption rates mean any statistical analysis is limited. Nevertheless, the adoption we do observe shows that larger hospitals, larger counties, and integrated salary model hospitals are more likely to adopt.
Abstract
					This study provides new evidence on the impact of parental wealth on college degree attainment. Using geocoded data from the Panel Study of Income Dynamics (1968–2017) linked to local housing price data from the Federal Housing Finance Agency, the empirical strategy analyzes parental housing wealth changes induced by local housing booms of the late 1990s–early 2000s and the subsequent housing bust of the 2007–2009 period. 2SLS/IV estimates show parental wealth significantly increases the likelihood of earning a four-year college degree. Moreover, the combined effects of parental income and wealth are significantly greater than the effects of income alone.
Abstract
					This paper investigates the past decade's increase in wealth inequality along racial and ethnic lines. Using a new measure of wealth stratification based on data from the Survey of Consumer Finances, we find that stratification increased significantly for blacks from 2007 to 2016; Hispanics exhibited a similar but less pronounced trend. Our regression analysis shows that relative to whites, blacks and Hispanics tend to invest more in houses and less in stocks, controlling for observable demographic factors. Consequently, these groups did not benefit as much as whites from the decade's spectacular increase in stock prices.
Abstract
					For many applications in public finance, it is difficult to find a source of exogeneous variation in local taxes. In this paper we use an event study design to show that the school finance reforms are one potential source of exogenous variation in taxes. This new instrument enlarges the tool kit for applied economists and other social scientists studying public finance and education.
Abstract
					We investigate the local deterrence effect of immigration raids on Hispanic Head Start enrollment. Using a nationwide panel of raids from 2006 to 2008, a time of intensified immigration enforcement across communities in the US, we find robust evidence that raids decreased Hispanic Head Start enrollment by around 10 percent. We disentangle this impact and find evidence that this decrease is driven by a deterrence effect rather than a mobility effect, which suggests that families are staying in their communities but not enrolling their children in Head Start.
Abstract
					This research investigates the relationship between Employee Stock Ownership Plans (ESOPs) and criminal participation as measured by arrests, conviction, and incarceration among formerly incarcerated individuals. Using the 1997 National Longitudinal Survey of Youth, I find that formerly incarcerated individuals with ESOP employment are significantly less likely to be arrested, convicted, and incarcerated. This effect likely operates through improvement in labor market outcomes: formerly incarcerated ESOP employees earn approximately 25 percent more in annual income and work roughly 8.8 percent more hours per week than formerly incarcerated workers who are employed but not working for an ESOP firm.
Abstract
					Does interior enforcement selectively deter Mexican migration? Our study shows that more aggressive enforcement increases the likelihood of having immigrants with US work experience and with jobs secured in the United States before their migration. We also look at whether having employment may be associated with lower crime incidence and shorter detention periods among immigrants. We find that employment decreases the likelihood of observing immigrants committing serious crimes and on the length of immigrant detention. By attracting quality workers, enforcement might decrease crime incidence, along with the length and costs of detention of removable immigrants in the United States.
Abstract
					An increasingly diverse population in the United States has given rise to a growing body of literature that analyzes the causes and consequences of descriptive representation. Using individual-level representative data on registration and voting for the entire United States over the 2008–2018 decade, we find that diversity in the candidate pool promotes the registration and voting of eligible-to-vote individuals, particularly those belonging to the youngest generations of voters, those located in swing states, and growing minorities, as in the case of Hispanic voters. Given the changing electorate, increasing candidate diversity might prove crucial in promoting political and electoral engagement.
Abstract
					Using confidential-use, individual-level Internal Revenue Service and US Census data, we follow the earnings of Hispanics and Asians between the ages of 18–45 with panel data that spans the years 2005–2014. These two groups represent the largest immigration flows in recent years. We examine the impact that labor market entrants and new immigrant arrivals within each group have on group earnings inequality. We show that labor market entrants and immigrants increase inequality for both groups.
Abstract
					This study provides evidence of racial and gender disparities among police officers by examining a key metric of internal recognition: departmental award nominations. Using a novel dataset on Chicago police officers, we find that black (female) officers are significantly less likely to be nominated compared to their white (male) colleagues, even after controlling for cohort, age, experience, and key policing activity metrics such as arrests, uses of force, and complaints. Further, the discrepancy is likely not a result of statistical discrimination on the part of nominators, as the minority nominations gap grows among higher award percentiles.
Abstract
					We estimate the causal impact of criminal activity nuisance ordinances on tenant evictions and eviction filings. These ordinances penalize property owners when certain types of illegal activity occur on or near their property, reported primarily through 911 calls. We exploit the staggered implementation of laws by municipalities and estimate the treatment effect on eviction outcomes using a difference-in-difference framework. The results show that criminal activity nuisance ordinances increase eviction filing rates by about 16 percent of the sample mean and court ordered evictions by 14 percent of the sample mean.
Abstract
					We merge data on spatial variation in the presence of convicts across eighteenth and nineteenth century Australia with results from the country's 2017 poll on same-sex marriage and with household survey data. These combined data allow us to identify the lasting impact of convict colonization on social norms about marriage. We find that in areas with higher historical convict concentrations, more Australians recently voted in favor of same-sex marriage and hold liberal views about marriage more generally. Our results highlight how founder populations can have lasting effects on locally held social norms.
Abstract
					We present a New Keynesian model with endogenous risk. The conditional output gap volatility depends on the price of risk, giving rise to a vulnerability channel of monetary policy. Lower interest rates not only shift consumption intertemporally but also shift conditional output risk. The model fits estimates of the conditional output gap distribution 1 to 12 quarters ahead and suggests an intertemporal risk return trade-off for policymakers. Via the impact on risk taking, easy monetary policy lowers short-term downside risks to growth but increases medium-term risks. The framework can be used to jointly consider macroprudential and monetary policy.
Abstract
					We show that the creation of private safe assets by shadow banks can decrease traditional banks' supply of safe assets. The 2014–2016 money fund reform created a large demand shock for safe assets, to which Federal Home Loan Banks (FHLBs) responded, expanding their balance sheets and increasing their issuance of short-term debt. To reduce the resulting interest rate risk, FHLBs shortened the repricing of their loans to banks. Focusing on small banks for which the reform was exogenous, we use a novel instrumental variable strategy to show that shadow banks create safe assets at the expense of banks' deposits.
Abstract
					We document how primary dealers use and re-use collateral in the United States. Using confidential supervisory data, we map how collateral flows through individual dealers, identifying whether the collateral is encumbered or rehypothecated. From these data we estimate the degree of collateral re-use at the dealer level. We find a high degree of US Treasury re-use, for which we posit three possible drivers: (1) intermediation of cash, (2) intermediation of collateral, and (3) "stripping" and distribution of their safe asset benefits. This work contributes to research aimed at understanding how collateral circulation improves market functioning but may lead to fragility.
Abstract
					The sale and repurchase (repo) market played a central role in the recent financial crisis. From the second quarter of 2007 to the first quarter of 2009, net repo financing provided to US banks and broker-dealers fell by about $900 billion—more than half of its pre-crisis total. Significant details of this "run on repo" remain shrouded because many of the providers of repo finance are lightly regulated or unregulated cash pools. Our analysis highlights the danger of relying exclusively on data from regulated institutions, which would miss the most important parts of the run.
Abstract
					Policymakers would like to predict and mitigate the risks associated with the post-global financial crisis rise in corporate leverage in emerging markets. However, long-standing advanced-economy bankruptcy models fail to capture the idiosyncrasies that impact the solvency of emerging market firms. We study how a machine learning technique for variable selection, LASSO, can improve corporate distress risk models in emerging markets. Exploring the trade-off between model fit and predictive power, we find that larger models forecast distress with more accuracy during periods of economic stress (when global factors gain relevance), while more parsimonious specifications outperform during normal times.
Abstract
					We empirically evaluate the importance of two sources of public information affecting pricing of global corporate bonds: bond ratings provided by rating agencies and sovereign yields of the issuer's country. We find that both in the cross section of firms and over time more variation in corporate bond yields is explained by sovereign yields than by corporate bond ratings. When sovereign yields are high, their importance in pricing corporate bonds declines. In these states, for advanced economies' borrowers, the importance of corporate ratings increases. There is a small upward trend in the importance of corporate ratings over time.
Abstract
					With a novel database, we examine the evolution of capital flows since the collapse of the Bretton Woods system in the early 1970s. We decompose capital flows into global, regional, and idiosyncratic factors. In contrast to previous findings, which mostly use data from the 2000s, we find that booms and busts in capital flows are mainly explained by regional factors and not the global factor. We link leverage in the financial center to regional capital flows and the cost of borrowing in international capital markets to examine the drivers of capital flow bonanzas and busts.
Abstract
					This paper analyzes the real effects on firms of sovereign debt inflow shocks in emerging countries. We follow Broner et al. (2019) and exploit six episodes of country inclusions into two major local currency sovereign debt indexes. We complement their evidence by analyzing real variables and find that government-related and financial firms experience larger growth in income, employment, and dividends, relative to tradable firms, in the three years following sovereign debt inflow shocks. Our findings suggest that capital inflows to sovereign debt markets can hamper exports and benefit financial and service-based firms, thus reshaping the domestic economy.
Abstract
					This paper tests if prudential and macroprudential regulations have meaningfully reduced the incidence of capital flow "waves," that is, of sudden stops and surges of 
capital flows from abroad. The results support other work documenting changes since 2008 in how global factors affect capital flows but provide mixed evidence on how 
regulations have affected the incidence of sharp capital flow movements. Regulations that strengthen banks (such as higher capital-asset ratios) meaningfully reduce the 
incidence of surges, but tighter macroprudential regulations appear to have done little to reduce the incidence of capital flow waves—and are even correlated with an 
increased risk of sudden stops. This may reflect their limited use to date, or how they interact with different types of capital flows. Macroprudential regulations may have 
reduced the volume and volatility of bank flows but shifted financial intermediation outside the regulated sector and thereby increased the volatility of debt and equity 
flows. These reforms could still provide important benefits, however, in terms of building the resilience of banks and thereby mitigating the negative effects of capital 
flow waves on the broader economy. Even if the waters are not much calmer, the waves should do less damage.
Abstract
					Did the effect of US monetary policy on the global financial cycle change after the crisis? We analyze the international transmission of the Fed's policy shocks since 2009. We find similar effects for the policies that act mostly on the short end of the US yield curve. But there is evidence of potent information effects active at the long end. Lower ten-year Treasury yields are associated with weaker global financial activity and flight to safety. The information content of the VIX may have changed substantially since the crisis.
Abstract
					The interest in how financial conditions affect real economic activity has grown since the great financial crisis (GFC), not least because some of the mechanisms at play in the financial sector may have changed. We shed light on this issue by examining the empirical relationship between global Purchasing Managers' Indices, world trade, and indicators of global financial conditions, with a special focus on the broad dollar index. We show that the influence of the dollar on real economic activity and global trade seems to have increased since the GFC, while that of the VIX has decreased.
Abstract
					Foreign governments went from owning a tenth of publicly available US Treasury notes and bonds in 1985 to over half in 2008. Recently, foreign governments have reduced their positions. I find foreign official purchases have depressed medium-term yields, despite conventional wisdom pointing toward the long end of the yield curve. To examine effects over the entire yield curve, I embed a structural vector autoregression of macroeconomic variables into an affine term structure model. With segments of the yield curve increasingly determined by international financial markets, it may be more difficult for the Federal Reserve to implement its interest rate policy.
Abstract
					Using another year of data including significant escalations in the trade war, we find that the costs of the US tariffs continue to be almost entirely borne by US firms and consumers. We show that the response of import values to the tariffs increases in absolute magnitude over time, consistent with the idea that it takes time for firms to reorganize supply chains. We find heterogeneity in the responses of some sectors, such as steel, where tariffs have caused foreign exporters to drop their prices substantially, enabling them to export relatively more than in sectors where tariff pass-through was complete.
Abstract
					We examine how the looming threat of tariff hikes under a trade agreement renegotiation impacts firm entry into a trading partner's market by exploiting uncertainty over the future UK-EU trade relationship brought about by the June 2016 Brexit referendum. Using the universe of UK export transactions at the firm and product level, we find that uncertainty over future market access to the EU deterred entry modestly in the months immediately after the Brexit vote, but the deterrent effect increased over time.
Abstract
					We examine if Brexit uncertainty has trade externalities beyond Europe. Using detailed data on export values and participation, tariffs, and Brexit probabilities prior to the referendum, we estimate ongoing negative trade-uncertainty elasticities between the United Kingdom and its non-European partner countries in preferential trade agreements that will require renegotiation post-Brexit. We use them to isolate the impact of the referendum on export values and net entry; we find effects similar to those identified by Graziano et al. (2018) for the UK and EU.
Abstract
					We argue that within-industry investor diversification is directly related to common ownership incentives (profit loads on rival firms by the manager of a firm) in product markets. Because of their respective investment strategies, passive investors are naturally more diversified than active investors. If more money flows from active toward passive investors, then common ownership incentives increase. The opposite occurs if active investors receive more money flows. This pattern is shown in two example US industries for the period 2004–2012.
Abstract
					Brand-name pharmaceutical companies often file lawsuits against generic drug manufacturers that challenge the monopoly status of patent-protected drugs. Institutional horizontal shareholdings, measured by the generic shareholders' ownership in the brand-name company relative to their ownership in the generic manufacturer, are significantly positively associated with the likelihood that the two parties enter into a settlement agreement in which the brand pays the generic manufacturer to stay out of the market.
Abstract
					I explore recent behavior in the market for superpremium ice cream. I first document that the flavors offered in supermarkets by Ben & Jerry's and Haagen-Dazs became increasingly differentiated from 2006–2013. Using an estimated model of demand, I show that this differentiation increased profits for both firms. Also, unilateral deviation from the set of products offered in 2013 would have increased variable profits for the deviating firm. These facts, when coupled with anecdotal evidence, suggest that these firms tacitly coordinated their choice of flavors. A companion piece, Sullivan (2019), formalizes this result and quantifies the implications for outcomes and welfare.
Abstract
					A current debate in antitrusts analyzes whether to allow horizontal agreements that counteract large imbalances of power in vertical negotiations. We leverage detailed data to empirically assess the consequences for patients of a recent case in which a group of physicians in Chile formed a trade association to improve their bargaining position with insurers. As a result of this agreement, out-of-pocket costs increased by 160 percent. Overall, we find large decreases in consumer surplus.
Abstract
					This paper examines the effects of promotions to increase participation in digital banking and improve financial inclusion. M-Shwari, Kenya's most popular digital banking platform, ran a promotion called Stawisha Na M-Shwari from mid-April 2016 to early June 2016. The promotion incentivized individuals to save and to repay loans. We find large and persistent effects of the promotion on loan-taking behavior. While savings ramp up during the promotional period, we do not see sustained increases in savings after the end of the promotion.
Abstract
					Mobile money can reduce the cost of sending remittances as compared with traditional money transfer systems. Despite remittances being a crucial part of the West African economy, mobile money is failing to take off. We use supply and demand data for money transfer services to better understand low mobile money adoption in Niger. Using a modified Becker-DeGroot-Marschak mechanism to elicit willingness to pay, we find that households are willing to pay the cost of sending a transfer via mobile money, with substantial regional variation. This regional variation is correlated with agent density, which suggests that agent infrastructure might be a barrier.
Abstract
					Who uses mobile money, and what do people do with it? This paper describes mobile money adoption patterns following the experimental introduction of mobile money for the first time in rural areas of Southern Mozambique. We use administrative and household survey data to characterize adopters as well as their mobile money usage patterns over three years. Adopters of mobile money (and early adopters in particular) are more educated than nonadopters, and they are also more likely to already hold a bank account. Positive self-selection of adopters should be considered when introducing mobile money as a tool for rapid financial inclusion.
Abstract
					We present results from a randomized control trial on access to mobile money with 480 entrepreneurs in Malawi. Treated individuals received account opening assistance and basic training on mobile money and were encouraged to save. Withdrawal fees were waived. Seventy-three percent of treatment respondents made at least 1 deposit, and 53 percent made at least 5. Treatment respondents reallocated labor from business to agriculture, and we find some evidence for an increase in expenditures. Evidence suggests that treatment effects were driven in large part by respondents using the accounts for savings.
Abstract
					Women empowerment programs may reduce intimate partner violence (IPV) by improving autonomy, increasing bargaining power, and reducing socioeconomic stress. Yet, this might not happen if partners increase violence to either control the woman's resources or assert their dominance. Data from South Kivu, DRC, are consistent with the view that IPV may be related to both control and socioeconomic stress: IPV is higher when women are the main household earner, more educated, and younger than their husband and when households experienced more socioeconomic shocks. Based on these findings, the effect of empowerment programs on IPV in this setting are theoretically ambiguous.
Abstract
					A randomized trial was conducted in rural Uganda in which 112 villages were exposed to video dramatizations about violence against women (VAW) or placebo topics. The treatment videos encouraged viewers to report VAW. Eight months later, surveys showed increased willingness to report in treatment villages as well as lower reported rates of VAW. The present survey experiment suggests a possible causal mechanism: the videos made allegations more credible so that those who come forward with reports are more confident that they will be believed.
Abstract
					We investigate differences in spousal reports of intimate partner violence (IPV) against women and men using a sample of 800 couples in rural Kenya. We find that up to one-third of couples disagree but that disagreement varies by violence type and victim's gender. We study the role of gender attitudes in explaining this heterogeneity. We find that couples with more gender-unequal attitudes are more likely to agree on violence against women and less likely to agree on violence against men. This suggests that gender norms govern reporting by the victim. Thus, discrepancies may result even if perpetrators report accurately.
Abstract
					This paper argues that the social nature of humans, absent from the standard economic model, is crucial for understanding our large modern social states and why concerns about inequality are so pervasive. A social solution arises when a situation is resolved at the group level (rather than the individual level) through cooperation and fair distribution of the resulting surplus. In human societies, childcare and education for the young, retirement benefits for the old, health care for the sick, and income support for those in need are resolved at the social level and through the social state in advanced economies. Social situations are pervasive even outside government and play a significant role in the distribution of pretax market incomes.
Abstract
					Using a unique dataset, this paper examines the extent to which streets named after prominent Confederate generals are related to Black-White labor market differentials. Examining individual-level data shows that Blacks who reside in areas that have a relatively higher number of Confederate streets are less likely to be employed, are more likely to be employed in low-status occupations, and have lower wages compared to Whites. I find no evidence that individual characteristics, local characteristics, or geographic sorting explain these results.
Abstract
					While the role of World War II veterans in the civil rights movement has been well documented, debate about the causal effect of military service remains. Combining detailed information on World War II enlistments and Civil Rights Commission data on voter registration, we present the first causal estimates of the role of Black veterans in high-risk political participation in the US South. Each Black enlistee increased Black voter registration by more than two additional Black registrants after the Voting Rights Act of 1965. We find similar effects on the presence of Black rights groups and, in response, White nationalist organizations.
Abstract
					Correspondence experiments probe for discrimination by manipulating employer perceptions of applicant characteristics. We consider the gains from dynamically adapting the number and quality of fictitious applications each employer receives to their prior callback decisions. Calibrating employer behavior to experimental data from Nunley et al. (2015), we find that it is possible to cut the number of applications required to detect a fixed number of discriminators roughly in half relative to a benchmark design with a fixed number of applications per job. These gains are achieved primarily from abandoning jobs with very low callback probabilities and those that call back Black applicants.
Abstract
					Algorithmic decision-making can lead to discrimination against legally protected groups, but measuring such discrimination is often hampered by a fundamental selection challenge. We develop new quasi-experimental tools to overcome this challenge and measure algorithmic discrimination in pretrial bail decisions. We show that the selection challenge reduces to the challenge of measuring four moments, which can be estimated by extrapolating quasi-experimental variation across as-good-as-randomly assigned decision-makers. Estimates from New York City show that both a sophisticated machine learning algorithm and a simpler regression model discriminate against Black defendants even though defendant race and ethnicity are not included in the training data.
Abstract
					Invited seminar talks are a primary way that economists get feedback on their work, disseminate their research, and build their professional networks. In this paper, we present descriptive evidence on who gave invited seminar talks in economics. We use a balanced panel of 66 departments between August 2014 and December 2019, focusing on the gender and underrepresented minority (URM) status of the speakers. We find that 76 percent of the talks in our sample were given by non-URM men, 23 percent by non-URM women, and less than 1 percent each by URM men and URM women. These averages mask substantial heterogeneity across departments.
Abstract
					This paper investigates how women's works are perceived among their peers. I construct a dataset using bibliographic data from articles published in top journals in economics and granular information on the articles that cite them. I find that female-authored papers in top economic journals are (i) more likely to be cited outside economics, (ii) less likely to be cited by top-tier journals, and (iii) less likely to be cited by men. I conclude with a discussion on those results and their implications for females in economics.
Abstract
					There are widespread gender inequities within the economics discipline. In this paper, we collect and analyze new longitudinal salary and personnel data from top economics departments at public institutions. A panel spanning 2005 to 2018 allows us to follow individuals and facilitates the examination of gender gaps in career progression, salary growth, and mobility. Using these data, we document the growth of salary gender gaps with the length of time in the profession, emerging roughly 10 years after the start of one's career. Some of these gaps are attributable to women moving through academic ranks more slowly than men.
Abstract
					This paper investigates the impact of gender differences in field of specialization on gender disparities in job placement among recent economics PhD candidates. Women are underrepresented as assistant professors, especially at top-50 institutions, and overrepresented in nonresearch positions. Our decomposition results show that our variables account for 28 percent to 67 percent of the gender gap in placement outcomes. Fields of specialization account for the larger share (75 percent to 132 percent) of the explained differences for positions outside of top-50 institutions. For top-50 institutions, the ranking of the PhD institutions accounts for two-thirds of the explained placement differences.
Abstract
					Previous research has shown that women in the treatment group of the CeMENT randomized controlled trial increased their publications and the likelihood that they were tenured in top-50 economics departments. This paper examines one potential mechanism, namely that CeMENT expanded the collaboration networks of the participants. Our analysis finds that women who received the mentoring treatment had 3 additional pre-tenure coauthors, 1.6 more pre-tenure publications, and 43 additional citations to those publications. After controlling for additional coauthors, the CeMENT program increased publications and top-tier publications. These results suggest that the information conveyed at the workshop facilitated participants' career success.
Abstract
					We examine the process underlying field specialization among beginning economists. Our multivariate logit framework accommodates single- and dual-field specializations with correlated choices. Including field-specific relative salaries and expected probabilities of academic employment is a novel aspect of this research. After conditioning on personal, economic, and institutional variables, we find that women graduate students are less likely to specialize in labor/health, macro/finance, industrial organization, public economics, and development/growth/international fields and are more likely to specialize in agricultural/resource/environmental fields. The Duncan dissimilarity index suggests that 14 percent of either sex would have to change specialization in order to achieve complete parity.
Abstract
					We conducted a randomized control trial with nearly 1,000 students to test whether using a text-message-based tool that provides small commitments with social accountability helps students procrastinate less and maintain engagement with course material, yielding improved academic performance. All students received identical content via text message, but the treatment group engaged with an online platform encouraging commitments and featuring a social feed with rankings. The analysis reveals that microcommitments with social accountability improved academic performance relative to students who received simple nudges. The increase is equivalent to 3 percentage points on an exam, driven by online and hybrid classes.
Abstract
					Math skills are critical for success in economics courses. However, instructors often lack information about the level and extent of their students' underpreparedness in mathematics. In this paper, we describe the development of two new assessments of math skills relevant for introductory and intermediate economics courses. The assessments may be used early in the semester to evaluate students and identify those with weak math skills. With data from introductory and intermediate microeconomics courses, we employ two different methodologies, a simple threshold analysis and a more sophisticated LASSO logit approach, to illustrate how our assessments identify students at risk of underperforming.
Abstract
					We use a regression discontinuity design to estimate the causal effect of letter grades in introductory courses on the probability of choosing an economics major at Wellesley College, a highly selective women's college. We find that women just above letter-grade cutoffs are 18 percentage points more likely to major in economics than women just below, a 50 percent increase. The effects are larger among financial aid recipients. Grade sensitivity among women is not explained by the presence of male students or instructors; it is more plausibly explained by lower precollege preferences for the major and gender-specific responses to noisy signals like grades.
Abstract
					This paper studies one college's policy requiring minimum grades in core courses for completion of the economics major. The policy reduced majors by approximately 6 percent. Grades of C- and D (requiring students to retake the course) dropped substantially, while grades of C (the minimum acceptable grade) did not change, and grades from C+ to B rose. Difference-in-difference analysis suggests that the policy caused the grade shift. Because C grades did not change and grades as high as B increased, I conclude that the policy caused increased effort by students who were below and somewhat above the performance standard.
Abstract
					Women persist in the field of economics at significantly lower rates than men. We show that the gender of an academic advisor is an important determinant of female undergraduates' persistence in economics. We use data from a four-year college where first-year economics majors are randomly assigned to advisors who are also faculty members in the economics department. Advisors help students choose courses and monitor their academic progress. We find that having a female advisor rather than a male advisor reduces female students' first-year dropout rates and increases their likelihood of graduating with an economics degree.
Abstract
					We examine the determinants of membership into the National Bureau of Economic Research (NBER) using data from all tenured and tenure-track economists at R1 universities in the United States. We construct an annual panel of employment, research productivity, NBER membership, and connectedness to NBER members. Using survival analysis, we show that conditional on controls, the hazard of becoming an NBER member is lower for men. Membership is highly dependent on top-five publications rather than total publications or citations, particularly so for women. Networks play a crucial role in determining NBER membership—especially having same-sex colleagues and advisors who are NBER members.
Abstract
					We assess whether light-touch interventions can increase the proportion of women who study economics. Over 2,000 students were randomly assigned to receive a message with basic information about the economics major, the basic message combined with an emphasis on the rewarding careers or financial returns associated with the major, or no message. The basic message increased the proportion of male students majoring in economics by 2 percentage points, equivalent to the control mean. We find no significant effects for female students. Extrapolating to the full sample, the basic message would nearly double the male/female ratio among economics majors.
Abstract
					In a field experiment designed to encourage undergraduate women and underrepresented minority students to study economics, we send personalized letters to students completing introductory economics classes inviting them to an informational meeting. A random sample of high-achieving students receives letters that also praise their performance and encourage them to persist in economics. Receiving this "nudge" increases the probability of informational meeting attendance and increases the number of women entering the economics and accounting major and of men entering the economics major. There is a substantial increase in the number of treated Hispanic students, particularly women, who choose economics and accounting.
Abstract
					We analyze an intervention that provided information from diverse voices about breadth, opportunities, and grade distributions in economics. In 2020, the year of a global pandemic, randomized control trials delivered videos/infographics and letters to students in Michigan State University's introductory classes. We find suggestive evidence, due to large standard errors, that the video treatment differentially increases the intentions of female and underrepresented minority (URM) students to take additional courses and major in economics. The video treatment increased the probability of URM students' self-reported chances of taking another economics course by 6 percentage points, 11 percent above the baseline, relative to the control group.
Abstract
					This study uses data from Academic Analytics to examine gender differences in promotion to associate professor in economics. We found that women in economics were 15 percent less likely to be promoted to associate professor after controlling for cumulative publications, citations, grants, and grant dollars. In contrast, we found no significant gender differences in promotion in other fields including biomedical science, physical science, political science, mathematics and statistics, and engineering. We separated the sample by the research intensity of institutions and found suggestive evidence that these results were being driven by less research-intensive institutions.
Abstract
					The 1960s witnessed landmark legislation that aimed to increase women's wages, including the Equal Pay Act of 1963, Title VII of the Civil Rights Act, and the 1966 amendments to the Fair Labor Standards Act. Although the gender gap in pay changed little at the mean/median during the decade, our distributional analysis shows that women's wages converged sharply on men's below but diverged above the median. However, the bulk of women's relative pay gains are not explained by changes in observed attributes. Our findings suggest an important role for legislation in narrowing the gender gap in the 1960s.
Abstract
					We focus on the timing of labor supplied during the day and its interaction with home care responsibilities. Using the American Time Use Survey, we measure the incidence of household care activities between 8 AM and 5 PM (the prime time of the day). Women experience more work interruptions during that time. These work interruptions imply wages that are about 9 percent lower. This result is consistent with occupations offering more flexibility but also a lower wage. We offer suggestive evidence that missing work due to household demands has a larger penalty in occupations with more coordinated work schedules.
Abstract
					Gender differences in professional networks have been shown to contribute to men and women's disparate labor market outcomes. This gap could be due to differences in network access, differences in network usage, or both. Using novel administrative data from a student-alumni professional networking website, we study gender differences in student network usage, holding network access fixed. Focusing on messages sent by students to alumni, we document that male and female students network similarly, in terms of both the number of messages sent and the specific questions asked. Furthermore, there are only small gender differences in question tone.
Abstract
					The rapid spread of the COVID-19 pandemic and subsequent countermeasures disrupted economic activity around the world. We investigate the effects of COVID-19 disruptions on the gender gap in academia. We administer a global survey of academics to collect nuanced data on the respondents' circumstances, such as the number and ages of children and time use. All academics report substantial increases in childcare and housework burdens, but women experienced significantly larger increases than men. Female academics with children report a disproportionate reduction in research time, both relative to childless men and women and to male academics with children.
Abstract
					This paper investigates whether an electoral defeat has different effects on the subsequent political involvement of male and female candidates for state office. Using US state legislative election returns from 1972 to 2010 and a regression discontinuity design, I find that there is no gender difference in the effects of an electoral defeat on the propensity to run again for state legislature. I discuss possible explanations for why the gender gap in persistence documented among novice local politicians disappears among state politicians, focusing on the role of prior office-holding experience.
Abstract
					We test whether the observed difference in the propensity to negotiate between men and women can be explained by gender differences in information about other people's negotiating experiences and outcomes and by confidence in one's abilities and in talking to strangers. Using survey data from Wisconsin public school teachers, we show that up to 54 and 17 percent of the gender gap in the likelihood of negotiating pay can be explained by differences in information and confidence between men and women.
Abstract
					Previous research has shown that norms around the role of women in society could help explain the gender gap in mathematics and that these norms could be transmitted within the family. Using data from the Florida Department of Education combined with birth certificates, we uncover important heterogeneity in the transmission of gender biases within the family. We find that gender role norms can explain the lower performance of girls in mathematics only in relatively affluent White families, whereas they do not apparently matter for the performance of Black girls.
Abstract
					Academic women in economics have different experiences and outcomes than men and women in other social science fields do, including bias within their performance evaluation instruments, student teaching evaluations (STEs). Despite research citing biases in STEs, no study summarized the magnitude of these biases. A systematic review and meta-analysis addresses this by combining data from all prior research on the subject. Our meta-analysis examines gender bias in STEs, finding significant gender differences in economics favoring men but no evidence for gender differences in the remaining social sciences. Implications are discussed, and recommendations are made.
Abstract
					To measure whether principals exhibit gender bias when assessing teacher effectiveness, we compare principals' subjective evaluations against teachers' self-evaluations and objective effectiveness in Ghanaian primary schools. Female and male teachers rate themselves equivalently. Principals are 11 percentage points less likely to rate a female teacher as "more effective," but female teachers are objectively more effective based on student learning. Principals assess the least effective male teacher as more effective than the objectively most effective female teacher. We corroborate results with a survey experiment showing similar gender bias. This bias against female teachers has implications for promotion and student learning.
Abstract
					We present new evidence on three measures of civil rights enforcement—litigation, judge dismissal, and plaintiff win rates—across US district courts from 1979 to 2016. Across courts, higher shares of Republican judges are associated with higher dismissal rates regardless of court composition in terms of gender and race. Further, we find that states with higher litigation rates also exhibit higher racial wage gaps, whereas states with higher judge dismissal (plaintiff win) rates experience higher (lower) racial wage gaps. Our results highlight the importance of legal institutions on the persistence of racial inequality.
Abstract
					A growing body of research documents the importance of wealth and the racial wealth gap in perpetuating inequality across generations. We examine the impact of wealth on child income. Our two-stage least squares regressions reveal that grandparental wealth has an important effect on the younger generation's stock, which in turn affects the younger generation's household income. We further explore the relationship between income and wealth by decomposing the child's income by race. We find that the intergroup disparity in income is mainly attributable to differences in family background. These findings indicate that wealth is an important source of income inequality.
Abstract
					We investigate whether inequality in wealth distribution is broadly associated with adverse socioeconomic outcomes across countries. There are few studies that investigate these relationships, likely due to data limitations. On the other hand, a substantial body of work suggests that income inequality correlates with undesirable outcomes. This paper evaluates the relationship between measures of wealth inequality and a number of outcomes across countries in a unified estimation framework that circumvents publication bias. While we fail to find support for a broad negative association, we do find a negative correlation between wealth inequality and institutional quality.
Abstract
					We evaluate the distributional impacts of active labor market programming for indigenous peoples in Canada. Using administrative data and an empirical strategy that compares participants in high-intensity programs—skills interventions, job-creation partnerships, or wage subsidies—to those in low-intensity programs, such as employment assistance or job counseling, reveals large returns to high-intensity programming for above-median earnings. Returns are largest for women at the mean, suggesting that high-intensity programming may reduce gender gaps in earnings among participants, who represent 10 percent of all indigenous people in Canada. Larger returns at the top of the distribution indicate that overall inequality among participants could increase.
Abstract
					We examine the impact of the Indian Gaming Regulatory Act on the income rank of American Indian (AI) reservation residents. We assemble a panel dataset at the individual level for tax filers residing on AI reservations in 1989. We examine the effect of casino operations and cash distribution payments (from casino revenues) on the income-rank evolution over time. Casino operations provide an unambiguous increase in family income rank for those residing on reservations with an operating casino relative to those on reservations without a casino. The presence of an operating casino increases relative income rank by half a percentage point.
Abstract
					In collaboration with an American Indian nation, we conducted a survey that is the first of its kind in Indian Country. The survey explored tribal members' financial experiences in the months before the first bank opened on their reservation. In this article, we connect respondents' reported ex ante trust in banks to their support for the new bank. Descriptively, respondents are highly supportive of the new bank whatever their ex ante trust in banks, but the relationship is nonlinear. Native ownership seems to be particularly silent to those in the middle or low end of the trust distribution.
Abstract
					The UN Declaration on the Rights of Indigenous People promotes self-governance as a matter of justice rather than economics. How will self-governance affect the incomes of indigenous people? To gain insight, we compare long-run income growth on American Indian reservations with and without federal oversight through the 1934 Indian Reorganization Act. Reservations with more autonomy had 12–15 percent higher income per capita in 2016, even conditional on 1930s income. However, these more autonomous reservations also experienced wider income variance with more downside risk. The findings are consistent with theory emphasizing the development trade-offs between local and centralized governance.
Abstract
					We examine the effect of community-designed electoral codes on Canadian First Nation communities. Adopting a custom code for local elections allows for changes such as increasing term duration, creating appeal and supervisory bodies, and incorporating traditional governance elements. To reduce biases due to selective opt-in, we exploit the timing of the electoral reform and a rich set of controls. We find that bands using the custom systems pay lower remunerations to their chiefs, spend more on education and training and less on band development, and have better wastewater services but show no sizable differences in income, population, or employment.
Abstract
					What are the consequences of the adoption of traditional governance institutions among indigenous groups for local government affairs? We study the 1995 Usos y Costumbres traditional governance reform in the state of Oaxaca, which legitimized these structures in a subset of its municipalities. We show that the degree of ethnolinguistic polarization between residents of outlying communities and residents of municipal capitals is an important barrier to the former's political representation in local elections. In terms of public goods provision, villages of ethnic minorities are less likely to gain electric service but more likely to gain sewerage services and public schooling.
Abstract
					Harmonized commercial laws are considered an essential ingredient to commerce and trade and have been called the backbone of American commerce. Key components of these laws are those governing secured transactions. In recent years, Native American tribal governments have moved to adopt commercial codes to increase economic development on their reservations, but many have modified these codes to address challenges to tribal sovereignty and culture. This paper compares reservations that adopted modified secured transaction acts to reservations that adopted uniform laws. We demonstrate that reservations can potentially experience substantial economic gains from either form of adoption.
Abstract
					The trajectory of new business applications and transitions to employer businesses differs markedly during the Great Recession and the COVID-19 recession. Both applications and transitions to employer start-ups decreased slowly but persistently in the post-Lehman crisis period of the Great Recession. In contrast, during the COVID-19 recession, new applications initially declined but have since sharply rebounded, resulting in a surge in applications during 2020. Projected transitions to employer businesses also rise, but this is dampened by a change in the composition of applications in 2020 toward applications that are more likely to be nonemployers.
Abstract
					In this paper, we show that the pandemic recession has led to frequent cuts in nominal wages. Within three months in 2020, as many wage cuts had occurred as occurred throughout the Great Recession. Unlike employment declines, wage cuts were concentrated at the top of the wage distribution. However, these cuts have been relatively short lived, particularly among high earners. Finally, wage cuts have been concentrated in firms that have seen large employment declines. Wage cuts appear not to be a substitute for cutting employment, at least when the shock to labor demand is this large.
Abstract
					We examine the text content of US patent applications, identifying those that advance technologies in support of video conferencing, telecommuting, remote interactivity, and working from home (collectively, WFH). The share of new patent applications that advance WFH technologies more than doubles from January to September of 2020, greatly surpassing its previous peak and following an upward trajectory since the onset of the pandemic. This evidence suggests that (re)directed technical change in reaction to COVID-19 will raise the quality and efficiency of remote work, thereby reinforcing a shift to working from home even after the pandemic ends.
Abstract
					Using data from 14 government sources, we develop comprehensive estimates of US economic activity by sector, legal form of organization, and firm size to characterize how four government direct-lending programs—the Paycheck Protection Program, Main Street Lending Program, Corporate Credit Facilities, and Municipal Liquidity Facility—relate to these classes of economic activity in the United States. The classes targeted by these programs are vast—accounting for 97 percent of total US employment—though entity-specific financial criteria limit coverage within specific programs. These programs notionally cover a far larger universe than what was targeted by analogous Great Recession-era lending policies.
Abstract
					The outbreak of the COVID-19 virus has led many states to take the drastic measures of social distancing. Using US executive order, occupation, and survey data, we measure the fall in labor supply due to these measures. Starting from a model of production networks, we analyze the sectoral effects of these labor shocks for the United States. We find that nonlinearities in the production network account for around half of the drop in GDP associated to the implementation of social distancing measures. The model also generates realistic dispersion in sectoral output change.
Abstract
					This paper assesses the prospects of a 2021 "time bomb" in small- and medium-sized enterprise (SME) failures triggered by the generous support policies enacted during the 2020 COVID-19 crisis. Policies implemented in 2020 do not on their own create a 2021 time bomb for SMEs. Rather, business failures and policy costs remain modest. By contrast, credit contraction poses significant risk. Such a contraction would disproportionately impact firms that could survive COVID-19 in 2020 without any fiscal support. Even in that scenario, most business failures would arise not from excessively generous 2020 policies but rather from the contraction of credit to the corporate sector.
Abstract
					Drawing on data from the firm-level Survey of Business Uncertainty, we present three pieces of evidence that COVID-19 is a persistent reallocation shock. First, rates of excess job and sales reallocation over 24-month periods (looking back 12 months and ahead 12 months) have risen sharply since the pandemic struck, especially for sales. Second, as of December 2020, firm-level forecasts of sales revenue growth over the next year imply a continuation of recent changes, not a reversal. Third, COVID-19 shifted relative employment growth trends in favor of industries with a high capacity for employees to work from home.
Abstract
					Early in the COVID-19 pandemic, much of the US economy was closed to limit the virus's spread, and several emergency interventions were implemented. Our analysis of older (45–75) respondents fielded in April–May of 2020 indicates that about 1 in 5 respondents was financially fragile and would have difficulty facing a midsize emergency expense. Some subgroups were at particular risk of facing financial difficulties, especially younger respondents, those with larger families, Hispanics, and those with low income. Moreover, the more financially literate were better able to handle such shocks, indicating that knowledge can provide some additional protection during a pandemic.
Abstract
					We experimentally study individuals' perceptions about and advice to others regarding retirement savings and annuitization during the pandemic. Many people recommend that others save more for retirement, but those most affected by the pandemic tell others to save and annuitize less. We investigate two possible channels for this result and show that the pandemic does not substantially alter optimism regarding survival probabilities. Hence, we conclude that economic factors are driving our results. Consequently, some financial ramifications of the COVID-19 outbreak are yet to be revealed, as the pandemic is having longer-term effects on people's willingness to save and annuitize.
Abstract
					We examine how the outbreak of the COVID-19 virus in the Hubei province of China impacted pro-social behavior and attitudes toward risk and uncertainty. The study repeatedly applies a panel of financially incentivized individual and strategic decision tasks via the WeChat social media platform to a population of preregistered Wuhan University students. We find that the initial outbreak coupled with the lock-down of Wuhan City led to an uptick in altruism, trust, and ambiguity aversion and a downtick in risk aversion. Over the remaining samples, we observed that all measurements return to baseline levels except for risk aversion.
Abstract
					We use daily transaction data in 214 cities to study the impact of COVID-19 on consumption after China's outbreak in late January 2020. Based on difference-in-difference estimation, daily offline consumption—via bank card and mobile Quick Response code transactions—fell by 32 percent, or 18.57 million renminbi (RMB) per city, during the 12-week period. The effect is prevalent across cities and is more pronounced in the dining-and-entertainment and travel categories. We infer that China's offline consumption decreased by over 1.22 trillion RMB, or 1.2 percent of China's 2019 GDP, in the 3-month postoutbreak period.
Abstract
					We provide an overview of Census Bureau activities to enhance the consistency, timeliness, and relevance of our data products in response to the COVID-19 pandemic. We highlight new data products designed to provide timely and granular information on the pandemic's impact: the Small Business Pulse Survey, weekly Business Formation Statistics, the Household Pulse Survey, and Community Resilience Estimates. We describe pandemic-related content introduced to existing surveys such as the Annual Business Survey and the Current Population Survey. We discuss adaptations to ensure the continuity and consistency of existing data products such as principal economic indicators and the American Community Survey.
Abstract
					Pandemic-driven economic changes are measurable in days and weeks rather than months and years, underscoring a need for more timely economic data to inform the public. We summarize newly available estimates of spending using card transaction data that are available on the Bureau of Economic Analysis website and analyze correlations between card data and official series. We find that card data perform well in measuring large changes in the economy around the pandemic, although the correlations are much lower during a period of stability prior to the pandemic. This pattern is likely attributable to a shift in the signal-to-noise ratio over these periods.
Abstract
					This paper describes a weekly economic index (WEI) developed to track the rapid economic developments associated with the onset of and policy response to the novel coronavirus in the United States. The WEI, with its ten component series, tracks the overall economy. Comparing the contributions of the WEI's components in the 2008 and 2020 recessions reveals differences in how the two events played out at a high frequency. During the 2020 collapse and recovery, it provides a benchmark to interpret similarities and differences of novel indicators with shorter samples and/or nonstationary coverage, such as mobility indexes or credit card spending.
Abstract
					Vaccinating the world's population quickly in a pandemic has enormous health and economic benefits. We analyze the problem faced by governments in determining the scale and structure of procurement for vaccines. We analyze alternative approaches to procurement, arguing that buyers should directly fund manufacturing capacity and shoulder most of the risk of failure while maintaining some direct incentives for speed. We analyzed the optimal portfolio of vaccine investments for countries with different characteristics as well as the implications for international cooperation. Our analysis, considered in light of the experience of 2020, suggests lessons for future pandemics.
Abstract
					Investment in intangible capital such as R&D has increased dramatically since the 1990s. However, productivity growth remains sluggish in recent years. One potential reason is that a significant share of the increase in intangible investment is geared toward consumer products such as pharmaceutical drugs with limited spillovers to productivity. We document that a significant share of R&D spending in the United States is done by pharmaceutical firms and geared to developing drugs for older patients. Increased life expectancy and quality of life for the elderly increases welfare but may not be reflected in estimates of total factor productivity.
Abstract
					Recent policy attention has focused on proposals to reduce prices for drugs that have received public funding. From an implementation perspective, such policies rely on public disclosure of government support for research. In this paper, we highlight two conceptual problems with past attempts to measure these public disclosures and construct a new dataset that corrects for these problems. Our corrected measures suggest that underreporting of public research support is less of an issue than previously thought.
Abstract
					From early in the COVID-19 pandemic, economists have stressed the importance of individuals endogenously changing their behavior to reduce their risk of infection. This paper quantifies time variation in the endogenous behavioral response of economic activity to the prevalence of the virus using an estimated behavioral SIR model with time-varying parameters. We find significant variation in both the relationship between economic activity and viral prevalence and the relationship between transmissibility and economic activity. This variation reflects adaptation to the pandemic and has implications both for specification of behavioral SIR models and for the next stage of the pandemic.
Abstract
					A simple model of COVID-19 that incorporates feedback from disease prevalence to disease transmission through an endogenous response of human behavior does a remarkable job fitting the main features of the data on the growth rates of daily deaths observed across a large number of countries and states in the United States in 2020. This finding, however, suggests a new empirical puzzle: very large wedges that shift disease transmission rates holding disease prevalence fixed are required both across regions and within a region over time for the model to match the data on deaths from COVID-19 as an equilibrium outcome exactly.
Abstract
					We study the behavior of implied dividend volatility, constructed from the prices of options on index-level dividends, during the COVID-19 pandemic. We use these data to construct a lower bound on expected excess returns on dividend claims and find that the bound moves significantly over time. However, most of the variation in dividend futures prices reflects changes in growth expectations rather than expected excess returns, making them valuable assets to uncover growth expectations. We conclude that the short-term economic outlook is uncertain and not expected to recover in the near term.
Abstract
					Using monthly data on costly natural disasters affecting the United States over the last 40 years, we estimate 2 time series models and use them to generate predictions about the impact of COVID-19. We find that while our models yield reasonable estimates of the impact on industrial production and the number of scheduled flight departures, they underestimate the unprecedented changes in the labor market.
Abstract
					"Placebo tests" are normally used to support evidence of pollution impacts on health outcomes. In this study, we argue that one should be cautious to proceed with falsification tests. We examine how a large metropolitan area in Brazil copes with increased health-care demand due to high air pollution under hospital capacity constraints. Using wind as an instrument, we find that the pollution exposure increases pediatric hospitalization for respiratory diseases while the number of planned procedures decreases in public hospitals. On average, for every four additional pollution-related admissions, one elective care procedure is displaced. Urgent procedures are not displaced.
Abstract
					Reductions in ambient pollution have been suggested as a "silver lining" to the COVID-19 pandemic. We analyze China's pollution monitor data and account for the large annual improvements in air quality following the Lunar New Year, which essentially coincided with lock-downs. With the exception of nitrogen dioxide, China's air quality improvements in 2020 are smaller than we should expect near the pandemic's epicenter, Hubei province. We see smaller improvements in sulfur dioxide than expected, while ozone concentrations roughly doubled in Hubei. Similar patterns are found for the six provinces neighboring Hubei. We conclude that COVID-19 had ambiguous impacts on China's air quality.
Abstract
					Under the Paris Agreement, India has pledged that 40 percent of its electricity generating capacity will come from non-fossil-fuel sources by the year 2030; however, this pledge does not limit total coal-fired generating capacity. As of 2019, planned increases in coal-fired capacity totaled 95 gigawatts—46 percent of installed coal-fired capacity in 2018. In this paper, we estimate the carbon dioxide benefits and health co-benefits of not building these plants. We also estimate the mortality impacts of the 2018 stock of coal-fired power plants and use it to calculate the tax on electricity generation from coal that would internalize these damages.
Abstract
					China emits twice as much CO2 as the United States. Launched in seven regions in 2013–2014, China's pilot carbon-trading programs cover roughly 7 percent of China's CO2 emissions. These market-based policies offer the best existing evidence as to whether the national carbon-trading program starting in 2021 will curb emissions. Here, we analyze changes in air quality using visibility measures from weather stations. We find the pilot programs improved local air quality, and this was likely a co-benefit of reduced carbon emissions. However, these improvements were modest, and there is some evidence of pollution leakage to the nonpilot regions.
Abstract
					This paper characterizes the importance of ownership networks of firms that are subject to a prominent energy regulation in China: the Top 1000 Enterprises Energy-Saving Program. We use data on the activities of regulated and unregulated firms that are part of the same conglomerate to study the overall importance of conglomerates as well as their geographic concentration. Accounting for business networks of regulated firms significantly increases the fraction of output that is affected by the regulation. We also document that most related firms of Top 1000 firms are located in the same province.
Abstract
					Governments taxing carbon emissions within their jurisdiction can impose a commensurate tax on emissions embodied in imports in order to mitigate emissions leakage. California offers a rare opportunity to investigate how such a border carbon adjustment (BCA) is working in practice. Experience to date highlights important tensions between greenhouse gas accounting accuracy, market efficiency, and concerns about trade protectionism. We simulate electricity market outcomes under BCA designs that differ in terms of how the carbon intensity of imports is assessed. Simulations suggest significant potential for leakage via resource shuffling. Realized emissions outcomes indicate that this potential has not been fully realized.
Abstract
					Martin and Zhang (2020) show that the increase in manufacturing output in China's special economic zones significantly increased air pollution. In this complementary paper, we document that widespread migration into these industrial clusters between 2000 and 2010 did little to change overall population exposure to pollution. We show using satellite air pollution data that there is much heterogeneity across zones and that most population growth occurred in relatively cleaner zones, supporting recent literature that documents local willingness to make location decisions based on environmental quality (Chen et al. 2019, Khanna et al. 2020).
Abstract
					Do US air pollution offset markets disproportionately relocate pollution to or from low-income or minority communities? Concerns about an equal distribution of environmental quality across communities—environmental justice—have growing policy influence. We relate prices and quantities of offset transactions to the demographics of the communities surrounding polluting plants. We find little association of offset prices or offset-induced movements in pollution with the share of a community that is Black or Hispanic or with mean household income. This analysis of 12 prominent offset markets suggests that they do not substantially increase or decrease the equity of environmental outcomes.
Abstract
					This paper examines the link between electoral incentives and environmental degradation by exploiting a satellite dataset on 107,000 forest fires and 879 asynchronous district elections in Indonesia. Fires represent a cheap but illegal means of converting forested land to other uses, but they risk burning out of control and creating substantial negative environmental externalities. We find a significant electoral cycle in forest fires. Ignitions and area burned decline during election years but steeply increase in the year after. The results suggest that politicians may suppress this activity at times when it might particularly dent their electoral chances.
Abstract
					In Delhi, one of the world's most polluted cities, there is relatively little information on indoor air pollution and how it varies by socioeconomic status (SES). Using indoor air quality monitors (IAQMs), we find that winter levels of household air pollution exceed World Health Organization standards by more than 20 times in both high- and low-SES households. We then evaluate a field experiment that randomly assigned monthlong IAQM user trials across medium- and high-SES households but suffered from significant survey non-response. Among respondents, IAQMs did not affect take-up of subsidized air purifier rentals or other defensive behavior.
Abstract
					We estimate consumer response to the first large-scale real-time electricity pricing (RTP) program. In 2015, RTP became the default tariff for residential customers in Spain, exposing them to prices that vary hourly based on day-ahead wholesale prices. Using expected national wind production as an instrument for price, we estimate household-level demand elasticities for RTP households and non-RTP (placebo) households. Estimates show no difference in behavior across RTP and non-RTP households. Reasons for nonresponse may include low potential gains or high nonmonetary costs of information acquisition and behavioral change. We discuss implications for optimal dynamic electricity pricing.
Abstract
					We provide the first at-scale estimate of electric vehicle (EV) home charging. Previous estimates are based on conflicting surveys or are extrapolated from a small, unrepresentative sample of households with dedicated EV meters. We combine billions of hourly electricity meter measurements with address-level EV registration records from California households, including 64,000 EV owners. The average EV increases overall household load by 2.9 kilowatt-hours per day, well under half the amount assumed by state regulators. Results imply that EVs travel less than expected on electric power, raising questions about transportation electrification for climate policy.
Abstract
					Many environmental regulations are designed to clean up the dirtiest firms. However, if pollution intensity is negatively correlated with market share, this approach may not be the most cost-effective way to reduce pollution. This paper illustrates the theoretical conditions under which it is more cost effective to incentivize pollution intensity improvements among relatively cleaner firms. I provide a decision rule for regulators designing pollution reduction policy, and I show that the California wholesale electricity sector exhibits investment behavior consistent with the trade-off implied by this rule.
Abstract
					We use causal forests to evaluate the heterogeneous treatment effects (TEs) of repeated behavioral nudges toward household energy conservation. The average response to treatment is a monthly electricity reduction of 9 kilowatt-hours (kWh), but the full distribution of responses ranges from -40 to +10 kWh. Households learn to reduce more over time, conditional on having responded in year one. Pre-treatment consumption and home value are the most commonly used predictors in the forest. The results suggest the ability to use machine learning techniques for improved targeting and tailoring of treatment.
Abstract
					This study examines the impact of performance pay on teacher selection. I exploit a shift toward performance pay in Wisconsin induced by the enactment of Act 10, which gave school districts autonomy to redesign their compensation schemes. Following the law, half of Wisconsin school districts eliminated salary schedules and started negotiating pay with individual teachers based on performance. Comparing the quantity of teaching degrees in Wisconsin institutions before and after Act 10, and relative to those in similar states, I find that Act 10 led to a 20 percent increase in teaching degrees. This effect was entirely driven by selective universities.
Abstract
					We provide descriptive evidence on the level and within-state distribution of school capital expenditures over the past two decades. We relate these to the fiscal institutions governing capital funding across states. Within-state differences in capital expenditures between the highest- and lowest-income school districts fell considerably following the Great Recession. Spending declined in the highest-income districts, while state support for low-income districts remained stable. Suggestive evidence points to the importance of constraints on districts' ability to raise local funding and the structure of state support in explaining these differences and trends over time.
Abstract
					A recent literature provides new evidence that school resources are important for student outcomes. This paper examines whether school accountability systems that incentivize performance (such as No Child Left Behind) raise the efficiency with which additional resources get spent. We leverage the timing of school finance reforms to compare funding impacts on student test scores between states that had accountability in place at the time of the reform and states that did not. The results show that finance-reform-induced increases in student performance are driven by those states where the reform was accompanied by the presence of test-based accountability.
Abstract
					We study the effects of the Common Application (CA) platform, which allows students to submit a single application to multiple institutions, on student choice. Using individual-level data from freshman surveys over the period 1982–2014, we develop two proxies for student choice, one based upon the number of applications submitted and another based upon students attending non-first-choice institutions. Using these proxies, we first document sharp increases in student choice over time. Linking these outcomes to the timing of CA membership, we provide evidence of a link between CA entry and increased student choice.
Abstract
					Young workers' early years in the labor market are a key and formative time. Using data from 31 countries, this article documents the selection of labor market entrants into large firms, which existing literature associates with propitious environments for young workers. The young and inexperienced are underrepresented at large firms compared to experienced and older workers. Entrants who do get their first job at large firms are positively selected in terms of education and cognitive skills. The patterns of large-firm selection (i.e., importance of education vs. skills) somewhat differ between Europe, East and Southeast Asia, and North America.
Abstract
					Do workers' first jobs affect their careers? Do such first-job effects (FJEs) vary across worker types? If so, can policy improve upon a "free" labor market by altering initial worker-employer matches? We study these questions using Norway's pre–2013 system of assigning doctors to their first job—residencies—through a random serial dictatorship. This generated individual-level variation in workers' choice sets over employers, which we use as instrumental variables to estimate FJEs. We then decompose workers' preferences over first employers into FJEs-on-earnings and employer "amenity value" components, showing how matches and worker welfare changed in the post–2013 decentralized labor market.
Abstract
					We test whether employment growth in a male worker's initial industry influences earnings growth using the 1979 National Longitudinal Survey of Youth. We follow workers for 20 years after reporting their first industry, finding that lower employment growth in their initial industry implies substantially lower earnings growth. Notably, after controlling for observable skills, controls for family background and region have no impact on estimates. Effects appear larger for initial occupations that involve more routine or manual tasks as well as for occupations that involve less abstract tasks, but these differences are not statistically significant.
Abstract
					We examine the interaction between Social Security Disability Insurance (SSDI) access and economic shocks during the Great Recession by exploiting exogenous variation in SSDI appeals processing time—a measure of hassle or access—between neighboring zip codes assigned to different hearing offices. During the Great Recession, longer processing times led to lower SSDI enrollment in places that experienced more severe labor market downturns. In the full sample, processing time has no clear effect on the pace of employment recovery. However, among severely shocked places with high baseline SSDI enrollment, those with longer processing times saw faster recovery in employment rates.
Abstract
					Wage insurance provides income support to displaced workers who find reemployment at a lower wage. We study the effects of the wage insurance provisions of the US Trade Adjustment Assistance (TAA) program using administrative data from the state of Virginia. The program includes an age-based eligibility cutoff, allowing us to compare earnings and employment trajectories for workers whose ages at the time of displacement make them eligible or ineligible for the program. Our findings suggest that wage insurance eligibility increases short-run employment probabilities and that wage insurance and TAA training may yield similar long-run effects on employment and earnings.
Abstract
					The Supplemental Nutrition Assistance Program (SNAP), the only universal US means-tested safety net program, has a low benefit-reduction rate. Thus, many SNAP recipients are working. We apply recent methods to study whether there is evidence of moral hazard among SNAP recipients. We see if individuals respond to incentives in SNAP eligibility by bunching near kink points in the budget set. While this responsiveness has been shown for various taxes and tax credits, little work has examined responsiveness of safety net program participants to kinks in their eligibility formulae. We use novel administrative data on eligibility determination and find little evidence of responsiveness around these kinks.
Abstract
					President Jackson vetoed the bill to recharter the Second Bank of the United States on July 10, 1832. I describe events leading to the veto and through the bank's dissolution in 1836 using private 
correspondence and official government documents. These sources reveal a political process through which charges against the bank took hold, accomplices and backup plans were lined up, and 
the bank was ultimately destroyed with the assistance of chartered banks in New York City. Although the aggressive means by which the bank was dismantled led to a system-wide financial failure 
and recession in the short term, the long-run outcome was likely a wider diffusion of banking services and a more efficient allocation of capital. The Federal Reserve benefited from applying a more 
rigorous regulatory structure onto the grid that the populists, free bankers, and National Banking System established.
Abstract
					Although corporate default crises are often quite severe, previous work has found little impact on real macroeconomic variables. This article investigates the relationship between railroad defaults and the balance sheets of local banks following the Panic of 1873. Receivers appointed to run railroads in default lacked the legal tools necessary to fully maintain railroad operations. The results indicate that railroad bond defaults negatively impacted the lending activity of local banks. Affected banks experienced declines in loans and deposits along with increases in excess reserves. These findings point to a disruption of the transportation network attributable to the railroad bond default crisis.
Abstract
					Using a new dataset of all NYC trust company stocks, we study the impact of the Panic of 1907 and the ensuing cash infusion by JP Morgan and the Treasury. Using synthetic controls, we find that three "troubled" trusts performed far worse than the other trusts, whose valuations rebounded within a year. Moreover, trust companies connected to "money trust" banks maintained higher valuation than independents and rebounded much faster. The desire to prevent panic from spreading from infected trusts to financial institutions in his purview could explain Morgan's rapid intervention to stem the contagion.
Abstract
					We use Bureau of Economic Analysis, census, and Current Population Survey data to study trends in income inequality across US states and counties from 1960–2019. Both states and counties have diverged in terms of per capita pretax incomes since the late 1990s, with transfers serving to dampen this divergence. County incomes have been diverging since the late 1970s. These trends in mean income mask opposing patterns among top- and bottom-income quantiles. Top incomes have diverged markedly across states since the late 1970s. In contrast, bottom-income quantiles and poverty rates have converged across areas in recent decades.
Abstract
					We study the desirability of industrial policies that generate sectoral hubs using a quantitative spatial model with cognitive nonroutine and other occupations. The productivity of each occupation in an industry depends on sector-specific production externalities, which we estimate using a model-implied instrumental variable approach. We find that the optimal policy gives rise to national hubs in coastal cities in tradable services, like professional services, and smaller regional hubs in less tradable services, like health and education. The optimal policy prescribes developing manufacturing in smaller towns. We decompose the implied changes in local costs and the available varieties in each sector.
Abstract
					When policymakers invest in urban infrastructure, there are concerns that poor residents living near the infrastructure will be displaced. This paper investigates mechanisms that may lead to such infrastructure-induced gentrification using a general equilibrium urban commuting model. Our goal is to elucidate the channels through which infrastructure-induced gentrification occurs and understand how policy choices mitigate or accentuate gentrification.
Abstract
					In markets with complicated products such as insurance, why do firms offer many products even when consumers appear to receive little benefit? We show that when consumers face information acquisition costs, firms may have an incentive to introduce many undifferentiated products. This allows firms to gain market share and increase markups. We document initial evidence consistent with the model using data from Medicare prescription drug insurance. Insurers that offer more duplicate or similar plans have higher-cost plans. These results suggest a role for policymakers to restrict product proliferation in markets with complicated products.
Abstract
					There is growing interest in market design using default rules and other "choice architecture" principles to steer consumers toward desirable outcomes. Using data from Massachusetts's health insurance exchange, we study an "automatic retention" policy intended to prevent coverage interruptions among low-income enrollees. Rather than disenroll people who lapse in paying premiums, the policy automatically switches them to an available free plan until they actively cancel or lose eligibility. We find that automatic retention has a sizable impact, switching 14 percent of consumers annually and differentially retaining healthy, low-cost individuals. The results illustrate the power of defaults to shape insurance coverage outcomes.
Abstract
					A planner aims to target individuals who exceed a threshold in a characteristic, such as wealth or ability. The individuals can rank their friends according to the characteristic. We study a strategy-proof mechanism for the planner to use the rankings for targeting. We discuss how the mechanism works in practice when the rankings may contain errors.
Abstract
					To solicit information from a social network in urban Monrovia, Liberia, we ask community members to assess their neighbors' poverty and assist in targeting a cash transfer. We find little evidence that local leaders, randomly selected neighbors, or neighbors nominated by fellow community members can accurately assess whether others in their community are among the poorest. Yet, all three groups target transfers to the poor modestly better than would be attributable to chance but worse than proxy-means-test-based targeting. We conclude that community advice provides some information for targeting but there are significant information frictions in networks in Monrovia.
Abstract
					Successful innovation is essential for the survival and growth of organizations, but how best to incentivize innovation is poorly understood. We compare how two common incentive schemes affect innovative performance in a field experiment run in partnership with a large life sciences company. We find that a winner-takes-all compensation scheme generates significantly more novel innovation relative to a compensation scheme that offers the same total compensation but shares it across the ten best innovations. Moreover, the winner-takes-all scheme does not reduce innovative output on average and, among teams of innovators, generates more output than the less risky prize structure.
Abstract
					We complement the literature on common ownership by presenting two new observations from entrepreneurial start-ups. First, given the increase in common ownership of start-ups by venture capital investors, inclusion of high-value start-ups in standard common ownership measures may actually increase aggregate measures of common ownership. Second, we suggest that even if public-firm common ownership leads to collusive inefficiency and higher prices in the short term, it may also create opportunities for entry of innovative high-growth start-ups. Consistent with this, we document that entrepreneurial activity and common ownership of start-ups tends to be higher in industries with higher common ownership among public firms.
Abstract
					We document new stylized facts on the occupational mix of businesses in the United States and how their internal organization evolves over their life cycles. Our main empirical finding is that younger businesses have fewer hierarchical layers and lower span of control than comparable older businesses do. Our results suggest that businesses become simultaneously more hierarchical and increase their managerial span of control over their life cycles. We show that this pattern is not entirely driven by selection or differences in size and is pervasive across cohorts and sectors.
Abstract
					We examine how firms adjust their labor demand to immigration policy changes resulting from intensified interior immigration enforcement. Using the temporal and geographic variation in the adoption of such policies as a source of identification, we find that firms boost their demand for low-skilled foreign-born labor under the H-2B visa program as enforcement intensifies. Furthermore, firms' increased demand for guest workers is inversely related to natives' employment in occupations where most H-2B workers are hired; however, it does not seem to alter natives' wages or work hours, nor does it seem to redistribute native labor away from those occupations.
Abstract
					Many medical professionals left Puerto Rico due to the financial crisis. Puerto Rico passed Act 14 in April 2017 to mitigate the exodus of physicians, reducing the flat tax on medical services to 4 percent. The same year, Puerto Rico was devastated by a Category 4 hurricane, leaving the island without power for several months. A difference-in-difference model is used to estimate the net effects of the hurricane and Act 14 on the number of health-care providers. The number of health-care providers decreased by 6.5 percent, family physicians by 17.5 percent, and specialists by 8 percent.
Abstract
					Native Americans have 3.5 times the COVID-19 infection rate and 1.5 times the death rate of non-Hispanic Whites. We demonstrate that social distancing policies may have unanticipated effects on behaviors. We estimate the effect of nonpharmaceutical interventions (NPIs) on the types of grocery stores visited by individuals residing on and off of American Indian reservations during the pandemic. We find that there is a larger reduction in the distance traveled to grocery stores for on-reservation households than for off-reservation households. We also find an increase in the relative share of trips to convenience stores for reservation residents.
Abstract
					Using high-frequency data for sovereign long-term bond yields and five-year credit default swap spreads, we estimate a regression model to identify a nonlinear link between cross-section deviation of market yield and extreme movements in African markets and other regions. Results indicate that African sovereign bonds have been subject to herding. International investors tend to lump African sovereign bonds into one asset class, pricing risk based on regional market performance instead of individual countries' performance. Moreover, we find evidence of herding spillovers from other regions. Africa is the most vulnerable of developing regions to shifts in market sentiment.
Abstract
					We propose a proximal bootstrap that can consistently estimate the limiting distribution of √n consistent estimators with nonstandard asymptotic distributions in a computationally efficient manner by formulating the proximal bootstrap estimator as the solution to a convex optimization problem, which can have a closed-form solution for certain designs. This paper considers the application to finite-dimensional regularized estimators, such as the Lasso, ℓ1-norm regularized quantile regression, ℓ1-norm support vector regression, and trace regression via nuclear norm regularization.
Abstract
					This paper illustrates two algorithms designed in Forneron and Ng (2020): the resampled Newton-Raphson (rNR) and resampled quasi-Newton (rQN) algorithms, which speed up estimation and bootstrap inference for structural models. An empirical application to BLP shows that computation time decreases from nearly five hours with the standard bootstrap to just over one hour with rNR and to only 15 minutes using rQN. A first Monte Carlo exercise illustrates the accuracy of the method for estimation and inference in a probit IV regression. A second exercise additionally illustrates statistical efficiency gains relative to standard estimation for simulation-based estimation using a dynamic panel regression example.
Abstract
					Black agricultural land ownership was at a peak just after the turn of the twentieth century; however, there was a nearly 90 percent decline in ownership from 1910 to 1997. In this paper, we use US Census of Agriculture data to estimate that the present, compounded value of the Black land loss from 1920 to 1997 is roughly $326 billion.
Abstract
					Recent estimates indicate approximately 8.4 million US households are unbanked with an additional 24.2 million US households classified as underbanked. We focus on intersectionality, specifically the intersection of race and gender, to better understand the probability of being unbanked and underbanked in the US. Additionally, we look at drivers of this financial exclusion. We find Black women are significantly more likely than Black men or any other group to be unbanked or to be underbanked. Further, we find limited wealth is more frequently cited by Black women as the main reason why they do not engage with the banking system.
Abstract
					I study the relationship among child-to-parent transfers, parents' social security eligibility, and child wealth building. Using data from the Panel Study of Income Dynamics and a regression discontinuity approach, I find that the wealth of adult children increases discontinuously at the parents' Social Security eligibility age for Black, female, and low-income groups. Additionally, the probability that a parent receives monetary transfers decreases discontinuously at the Social Security age for these groups. The effects were not statistically significant for counterpart groups. These findings suggest that by reducing the reliance of parents on their adult children, Social Security may contribute to wealth building among economically disadvantaged households.
Abstract
					Countries that implement wealth taxes make many practical compromises regarding relative treatment and approach to valuation of different categories of assets in order to ease assessment and liquidity difficulties with this form of taxation. Relying on Norwegian variation in tax and base rules, we illustrate the resulting complexity and evaluate the effect of taxation on saving and portfolio composition. Our results highlight the sensitivity of the strength of response to the base definition.
Abstract
					We use Danish register data to examine intergenerational rank-rank correlations in net wealth and gross housing wealth by child age and parental income. Our results indicate that gross housing wealth correlations are more stable by child age than are net wealth correlations, which we argue is due to a downward bias in net wealth correlations from transitory debt. Intergenerational housing wealth correlations also are larger for lower-income families, while net wealth correlations do not vary much across the income distribution. Finally, we show that intergenerational net wealth and gross housing wealth correlations move in opposite directions across the income distribution.
Abstract
					We examine the effects of the sudden withdrawal of expanded pandemic unemployment benefits in June 2021 using anonymized bank transaction data for 16,253 individuals receiving unemployment insurance (UI) in April 2021. Comparing the difference-in-differences between states withdrawing and retaining expanded UI, we find that UI receipt falls 36.3 p.p., while employment rises by only 6.8 p.p. by early September. Average cumulative UI benefits fall by $2,529, while average cumulative earnings increase by only $292. Heterogeneity by unemployment duration implies that these effects are primarily driven by extensive margin expiration of benefits rather than by intensive margin reductions in the benefit level.
Abstract
					We investigate the uneven pattern of access to unemployment insurance (UI) by age, gender, race, and ethnicity across the United States. We present results from a descriptive analysis using publicly available data reported by states over time on rates of UI recipiency and characteristics of UI beneficiaries. Recipiency measures the proportion of all unemployed who are receiving UI benefits. We find suggestive evidence that UI recipiency shares are lower than unemployment shares for females, youth, and Blacks. We offer program reforms that could be adopted by all states and required by the federal government to improve UI recipiency rates.
Abstract
					In the United States, unemployment insurance (UI) is financed by taxes levied on employers. We develop a model to decompose UI taxes into a firing tax component levied on firms that lay off workers, and a uniform payroll tax component levied on all firms regardless of their layoffs. We develop a novel methodology to measure the two components and document a number of facts about the uniform payroll tax component: it is large, accounting for just under half of UI taxes; it rises significantly after recessions; and it is more cyclical in states with poorly funded UI systems.
Abstract
					This paper provides new descriptive evidence about which soft skills employers value in young, entry-level workers. We ran employer surveys as part of an experiment to generate letters of recommendation for New York City's Summer Youth Employment Program participants. Supervisors rated over 9,200 of their summer employees on overall quality and 10 separate soft skills. Better ratings correspond to better outside employment and earnings. We find that communication skills and dependability most impress employers. Young women's advantage in soft skills explains their entire advantage in overall ratings, as well as 14 percent of their advantage in outside earnings.
Abstract
					Although subsidized summer jobs programs have been shown to improve youth outcomes, little is known about the effects of private sector employment experiences. We study a unique program that brokers employer-paid summer internships for youth across a variety of industries and occupations. Using administrative data, we employ fixed effects and matching models to estimate the impact of these internships on academic outcomes. We find that private sector job experience significantly increases attendance, reduces course failures, and raises proficiency on statewide exams. Participants are more likely to take the SAT and enroll in college with a shift from two-year to four-year institutions.
Abstract
					Oregon recently launched an automatic-enrollment retirement savings program for private sector workers lacking access to other workplace retirement plans. We analyze participation choices, account balances, and inflow/outflow data using administrative records between August 2018 and April 2020. Within the small to mid-sized firms served by OregonSaves, estimated average after-tax earnings are low ($2,365 per month) and turnover rates are high (38.2 percent per year). Younger employees and employees in larger firms are less likely to opt out, but participation rates fall over time. Overall, we conclude that OregonSaves has meaningfully increased employee savings by reducing search costs.
Abstract
					Economic crises are often accompanied by waves of antiminority behavior. We build on the framework developed in Bursztyn et al. (2022) to propose that crises, in addition to shifting people's attitudes toward minorities, can provide intolerant people with a plausible rationale for expressing their preexisting prejudice. The availability of such a rationale thus increases antiminority behavior by reducing the associated social sanctions. In an experiment examining how economic crises affect social inference about the motives underlying xenophobic behavior, we find that crises lead respondents to ascribe antiminority behavior to economic concerns rather than to innate xenophobia.
Abstract
					There is a widespread belief that Republicans and Democrats are worlds apart with respect to their preferences for redistribution. However, is that partisan divide real? In this paper, we discuss evidence from the General Social Survey and a tailored survey. We also discuss a revealed-preference measure constructed with administrative data. We conclude that the partisan divide is more nuanced than previously thought.
Abstract
					We test for a "Ferguson Effect" by studying how police effort responds to different incidents of police violence. We do so using two settings in Minneapolis: (1) George Floyd's murder, and (2) police-involved shootings. We find that following George Floyd's death, arrests and police-initiated calls decreased by 62 and 69 percent, respectively. By comparison, arrests and police-initiated calls decreased by 3 and 1.5 percent following police-involved shootings. We conclude that incidents of police violence generate "de-policing," and the effect is much larger following highly publicized incidents.
Abstract
					I study the viability of Twitter-based measures for measuring public attitudes about the police. I find that Twitter-based measures track Gallup's measure of public attitudes toward the police starting around 2014, when the Twitter user base stabilized, but not before 2014. Increases in Black Lives Matter protests are also associated with increases in negative sentiment measures from Twitter. The findings suggest that Twitter-based measures can be used to acquire granular evaluations of police performance, but they are more useful in analyzing panel data of multiple agencies over time rather than in tracking a single geographical area over time.
Abstract
					In the mid-nineteenth century, the urban milk supply in the United States was regularly skimmed or diluted with water, reducing its nutritional value. At the urging of public health experts, cities across the country hired milk inspectors, who were tasked with collecting and analyzing milk samples with the goal of preventing adulteration and skimming. Using city-level data for the period 1880−1910, we explore the effects of milk inspections on infant mortality and mortality among children under the age of five. Event study estimates are small and statistically insignificant, providing little evidence of post-treatment reductions in either infant or child mortality.
Abstract
					US cities invested heavily in water and sewer infrastructure throughout the late nineteenth and early twentieth centuries. These investments improved public health and quality of life by helping US cities control typhoid fever and other waterborne diseases. We show that segregated cities invested in water infrastructure earlier but were slower to reach universal access and slower to eliminate typhoid fever. We develop a theoretical model that illustrates how segregation, by facilitating the exclusion of Black households from water and sewer systems, explains these seemingly paradoxical findings.
Abstract
					As the United States economy grew in the 1920s, both wealth and income inequality rose as well. California land values were especially volatile as a variety of shocks buffeted the state. This paper summarizes how these local booms affected housing inequality by linking archival data on city property values to the full count 1930 census. I first characterize the relationship between the type of shock and city property values during the 1920s. Then I relate these real estate market swings to the occupational and housing distribution within and across cities in 1930.
Abstract
					Recent work shows a puzzle in the early twentieth century United States: as intergenerational mobility decreased, assortative mating increased. We argue that these two facts are causally related by using a shock to intergenerational mobility caused by falling immigration with the Quota Acts of 1921 and 1924, which essentially closed the borders to European immigration. We find that lower immigration caused lower intergenerational mobility, causing assortative mating to increase. We also look at the choice of nativity of spouse, finding that socioeconomic status gradients increase for every outcome as immigration decreases.
Abstract
					In 1919, there were 6 cars for every 100 people in the United States; in 1929, there were 19. The diffusion of the car transformed daily life and had large economic effects. Data on car registrations at the state level help us to understand the correlates of car diffusion. We also consider some of the ways in which car diffusion likely impacted the economy.
Abstract
					Using data on the value of Federal Housing Administration (FHA) mortgage insurance between 1935 and 1939, I estimate the effect of the agency's program on racial disparities in home ownership and home values. The distance between an FHA office and counties within its jurisdiction is used as an instrument. I find that insurance activity had a negligible effect on the racial gap in home ownership and a sizable effect on the gap in home values. Results suggest that while African American households continued to acquire homes, they may have chosen lower-priced properties, as they lacked the same access to credit as White buyers.
Abstract
					This paper studies the rise of sundown towns—places where Blacks and other minorities were excluded after dark—outside the South after 1890. We provide a new dataset on the timing of sundown town establishment using full count census records. Using a shift-share instrumental variables approach, we show that the presence of Southern Whites is causally related to the appearance of sundown towns, with lynchings and the establishment of KKK chapters as plausible mechanisms for racial exclusion.
Abstract
					The recent economic history of global integration has been characterized by a dismantling of capital controls and increased foreign direct investment (FDI). This paper explores the role of impediments to international capital mobility, foreign direct investment, and technology diffusion in shaping Latin American economic growth. First, the paper summarizes and quantifies the effects of the Bretton Woods international financial system in Latin America. Then, I study the consequences of capital controls—and their dismantling—on FDI and trade-induced technological advancements and their role in shaping local development, especially in the 1990s after the implementation of several trade liberalization policies.
Abstract
					The COVID-19 pandemic created unexpected and prolonged disruptions to childcare access. Using survey evidence on time use by academic researchers before and after the pandemic, we analyze the extent to which greater access to either school-based or partner-provided childcare mitigated the severe disruptions to research observed among parents during COVID-19. We find that access to public schools offsets the research time loss to a greater extent among mothers of young children relative to fathers, narrowing the emerging post-pandemic gender gap. Having a stay-at-home partner reduced the disruptions to research time equally for both genders.
Abstract
					In many high-income economies, the COVID-19 recession has resulted in unprecedented declines in women's employment. We examine how the forces that underlie this observation play out in developing countries. A force affecting high- and low-income countries alike is increased childcare needs during school closures. In Nigeria, mothers of school-age children experience the largest declines in employment during the pandemic, just as in high-income countries. A key difference is the role of the sectoral distribution of employment: whereas in high-income economies, reduced employment in contact-intensive services had a large impact on women, this sector plays a minor role in low-income countries.
Abstract
					We document the smaller average employment size and lower financial access of Black-owned businesses compared to White-owned businesses. Controlling for other characteristics, we find that observed differences in finance account for 60 percent of the 11.3 percent racial gap in number of employees; differences in returns account for 103 percent. The results imply that if both the levels and returns on finance were equalized across races, then Black-owned firms would be 18.4 percent larger than their actual size. Equalizing financial factors alone would reverse the firm size gap so that Black-owned firms would be larger than White-owned firms by 7.1 percent.
Abstract
					We analyze how Paycheck Protection Program (PPP) funds were disbursed to minority communities in the $278 billion rebooted program in January 2021. Using administrative microdata covering all PPP loans, we find strong positive relationships between PPP loan flows to both employer and nonemployer businesses and the minority share of the population. In contrast, the relationships were negative in the 2020 first round and less positive in the 2020 second round. For employer businesses, the positive relationship was also stronger for first-draw loans than for second-draw loans. The PPP reboot appears to have been disbursed to minority communities as intended.
Abstract
					We use a structural framework to interpret trends related to Black entrepreneurship, and infer how race-specific barriers faced by Black entrepreneurs have changed since the Great Recession. While all barriers declined consistently before the Recession, we find only the cost of starting a firm has declined since, relative to the cost faced by non-Black entrepreneurs. Since the Recession, Black entrepreneurs have experienced sharply increasing costs of employing labor and capital, and declining demand relative to other entrepreneurs. As a result, convergence in entrepreneurship rates has stalled.
Abstract
					We assess the role of fintech firms in loans made through the Paycheck Protection Program (PPP), a US government policy response to the COVID-19 pandemic that provided loans to small businesses. We argue that fintech firms' reliance on technology rather than relationship-banking approaches used by traditional banks helps to address discrimination in lending, at least in part. Using newly released data on the PPP program, we find support for our arguments: while Black-owned businesses received loans that were approximately 50 percent lower than observationally similar White-owned businesses, the effect narrows considerably when fintechs are allowed to provide loans.
Abstract
					Using hand-collected race information about small business owners that concealed their race in Paycheck Protection Program applications, we find evidence that not disclosing race information in loan applications pays off significantly. Our results show that Black-owned businesses that concealed their race obtained 52 percent more in funding than self-reported Black-owned businesses. Interestingly, White-owned businesses that also concealed their race information obtained approximately 10 percent more in funding relative to self-reported White-owned businesses. However, the effect is not statistically significant. Our findings are consistent with a prisoner's dilemma theoretical framework in which all participants are better off by not self-reporting race.
Abstract
					Using a large dataset of around 500,000 students from about 1,900 schools, this paper shows the effect of two school closures and 1.5 years of the COVID-19 pandemic on standardized learning growth for mathematics, reading, and spelling in Dutch primary education. We find that the school closures have a negative effect on standardized learning growth, amounting to an annual average of 5.5 weeks of learning loss. When analyzing differential effects by socioeconomic status, parental education, household income, household structure, household size, and migration status, we find that the negative effect is larger for the more vulnerable students.
Abstract
					We investigate the impact of the 2020 COVID-19 rental eviction moratoria on household well-being. Analysis of new panel data indicates that eviction moratoria reduced evictions and resulted in redirection of scarce household financial resources to immediate consumption needs, notably including food and grocery spending. We also find that eviction moratoria reduced household food insecurity and mental stress, with larger effects evidenced among African American households. Findings suggest broad salutary effects of eviction moratoria during a period of widespread virus and economic distress.
Abstract
					Employing a difference-in-differences framework, we examine the effect of COVID-19 on various performance metrics of minority-owned banks relative to peer banks. We find little evidence of worsening performance of minority-owned banks, except for Asian-owned banks. In some instances, minority banks show improved performance. We find a decline in nonperforming single-family residential loans for Hispanic-owned banks. Moreover, minority banks have disbursed more Paycheck Protection Program (PPP) loans than their matched non-minority counterparts. Their resilient performance indicates that minority banks are well positioned to aid in the ongoing economic recovery.
Abstract
					During a crisis, does ethnic composition influence policy efficiency? How do the effects of ethnic divisions differ from those of ethnic diversity? Using the lens of the COVID-19 pandemic, we show that ethnic divisions, rather than diversity, significantly reduce the efficacy of crisis response. United States counties with higher levels of ethnic divisions fared worse after lockdowns in COVID-19 cases and deaths. Diversity had little effect, except in highly segregated areas. Results are not driven by differences in politics, public goods, socioeconomics, or levels of high-risk populations.
Abstract
					We study the effects of race, network centrality, and policies that tolerate some level of virus spread (laissez-faire) on COVID-19 deaths in nursing homes in the United States. Our analysis uses unique data on nursing home networks and calibration-based estimates of states' preferences for health relative to short-term economic gains. Our findings suggest that laissez-faire policies increase deaths. Nursing homes with a larger share of Black residents experience more deaths, but they are less vulnerable to laissez-faire policies, especially when not central in social networks. Our findings highlight significant interactions between COVID-19 policies, race, and network structure among US seniors.
Abstract
					Consumption is a well-being measure that is determined by a combination of resources (e.g., income, in-kind benefits, assets, debt, time) available to households, their circumstances, and their preferences. In this study, we derive consumption poverty statistics using a consumption measure that includes the flow of services from owner-occupied housing and vehicles and in-kind transfers. The base data are from the US Consumer Expenditure Survey Interview from 2015 through 2020. The consumption poverty rate (using an absolute threshold anchored to the 2015 relative consumption poverty rate) declines from 16.8 percent in 2015 to 11.5 percent in 2020.
Abstract
					The COVID-19 recession caused regressive market income changes in the United States, with large losses more frequent than during the Great Recession and more concentrated at the bottom of the distribution. Progressive taxes and transfers, especially from expanded unemployment insurance benefits and stimulus checks, dramatically offset these declines. We use administrative tax data to show that public policies made large annual tax-unit level income declines in 2020 less common than during the Great Recession, as well as 2019, an expansionary year. These policies stabilized incomes over the entire distribution, but this effect was strongest among those starting with low incomes.
Abstract
					This paper develops an overlapping generations model that isolates the impact of the US racial wealth gap in 1962 on the long-run dynamics of wealth. The model predicts that one component of the initial gap, firm ownership, coupled with the intergenerational transfer of that ownership results in a permanent wealth gap independent of other dimensions of inequality. This implies that even if all discrimination against Black Americans had ceased upon the end of Jim Crow, the wealth gap would have persisted without a reparations policy addressing the fact that the initial firm ownership gap arose in the first place.
Abstract
					Mexico has one of the highest self-employment rates in the OECD. I study the relationship between business ownership and migration from Mexico to the United States using longitudinal data from the Mexican Migration Project (MMP). I find that the self-employed have a substantially lower probability of moving north, either legally or illegally. Although running a business could allow a person to finance a costly trip to the US, it also raises the opportunity costs of leaving and the nonpecuniary benefits of staying at home. The findings highlight the role of self-employment in a developing country in the likelihood of emigration.
Abstract
					Using NIPA and IPEDS data from 2000 to 2017, this research employs a panel event-study VAR to determine the recursive impact of federal education policy on college enrollment and state spending on education. Specifically, this project focuses on race and gender to analyze the Elementary and Secondary Education Act, and Common Core State Standards as random shocks to federal spending. Do federal policy or state standards help educational disparities? Findings indicate decentralized policies or standards must be centrally aligned to be effective in the US. Improvements must be made for all demographic groups.
Abstract
					Non-wage benefits are an important component of employment arrangements, but are not available to or used by all workers. Do differences in firm, worker, or match-specific characteristics drive benefit take-up? We provide new evidence on heterogeneity in use of non-wage benefits, focusing on disability accommodations. Using administrative data in Oregon, we document significant dispersion in accommodation rates across worker and firm characteristics. We decompose the variance in accommodation use, finding that firm characteristics explain substantially more than worker or injury characteristics (29 percent vs. 4 percent). This finding highlights the firm's role in use of non-wage benefits like disability accommodations.
Abstract
					Using data from the US Customs and Border Protection and novel data on border fencing, we examine how the construction of border fencing under the Secure Fence Act influenced crossing decisions and the likelihood of migrant deaths. Apprehension data suggest that fence construction induced migrants to cross in unfenced sectors. Meanwhile, the average death rate rose nearly threefold in the sectors where the fence was not built. These results support our hypotheses that fence construction induced some migrants to cross in unfenced sectors, while others were diverted to cross in more dangerous locations within fenced sectors.
Abstract
					The animal slaughtering and processing industry was the epicenter of work site immigration raids from 2006 to 2008 that were aimed at rooting out unauthorized immigrant workers in the United States. This study examines whether the industry shifted toward legal workers in the wake of the raids and whether wages, worker turnover, and other labor market outcomes changed as well. We find that the industry initially shifted toward legal foreign-born workers, particularly refugees, but the change faded over time. We also find a substantial increase in industry worker turnover, but not in average wages, at the national level.
Abstract
					Over four million US-born children living in households with at least one unauthorized immigrant parent are the unintended victims of intensified immigration enforcement. In an effort to address these disadvantages, many schools and school districts throughout the country have implemented "safe-zone" policies to limit their cooperation with immigration authorities, restrict agents' access to campuses, and provide resources for students and their immigrant families. Using data from a binational survey that collected information on children from mixed-status households, we document positive and significant correlations between safe-zone policies and children's externalizing, internalizing, and total difficulties scores, as well as their prosocial behaviors.
Abstract
					We study the relationship between teachers' stereotypes and students' high school choice in a setting where students can enroll in more or less demanding high school tracks. We show that teachers with negative stereotypes toward immigrants, as measured by an Implicit Association Test (IAT), are more likely to recommend lower-tier tracks to immigrant students, relative to natives with similar ability and socioeconomic background. Implicit stereotypes may thus prevent immigrant students from nurturing and developing their academic talents.
Abstract
					We present a speculative application of model estimates from Fudenberg and Puri (2021) to prize-linked savings in South Africa. The models used include one combining simplicity theory (Puri 2018, 2022), a preference for lotteries with fewer possible outcomes, with cumulative prospect theory. The results and those of prior literature indicate that both simplicity and probability weighting have a role to play in understanding behavior in choice under risk. We discuss the properties of these models and their implications for behavior.
Abstract
					We calculate the time path of prices generated by algorithmic pricing games that differ in their learning protocols. Asynchronous learning occurs when the algorithm only learns about the return from the action it actually took. Synchronous learning occurs when the artificial intelligence conducts counterfactuals to learn about the returns it would have earned had it taken an alternative action. In a simple market setting, we show that synchronous updating can lead to competitive pricing, while asynchronous updating can lead to pricing close to monopoly levels. However, building simple economic reasoning into the asynchronous algorithms significantly modifies the prices it generates.
Abstract
					While recent theoretical literature shows that algorithmic pricing (AP) may increase retail prices by facilitating collusive behavior, there has been no empirical evidence relating the adoption of AP technology to higher prices and/or collusion. One key reason is that information about firms' pricing technologies and their adoption of new pricing software is rarely available. In this paper, we use detailed price data from the German retail gasoline market, where AP was supposedly introduced in 2017. We show how to identify changes in pricing technology using structural breaks in pricing behaviors associated with AP.
Abstract
					Retail electricity competition has been introduced for over a decade in many markets, but challenges in having an active retail market remain. Universal smart meters have also emerged as a trend. What is the interaction between competition and smart meters? What role can information via smart meters play in these markets? Has it enabled enhanced competition? Or has it further increased the incumbent's advantage? We present an overview and preliminary exploration using an aggregate data set from the Spanish electricity market. The evidence suggests that competition challenges remain large, although some modest evidence of increased pricing innovation exists.
Abstract
					The problem of identification is often the core challenge of empirical economic research. The traditional approach to identification is to bring in additional information in the form of identifying assumptions, such as restrictions that certain magnitudes have to be zero. In this paper, we suggest that what are usually thought of as identifying assumptions should more generally be described as information that the analyst had about the economic structure before seeing the data. Such information is most naturally represented as a Bayesian prior distribution over certain features of the economic structure.
Abstract
					I use a simple business cycle model to illustrate the workings and limitations of sign restrictions in structural vector autoregressions. Three lessons emerge. First, such sign-based identification is vulnerable to "shock masquerading": linear combinations of other shocks may be misidentified as the shock of interest. Second, since the popular Haar prior automatically overweights more volatile shocks, the implied posterior is decisively shaped by relative shock volatilities—a feature of shocks that has nothing to do with their dynamic causal effects. Third, sign restrictions on structural elasticities—rather than just the usual restrictions on impulse responses—can be highly informative.
Abstract
					Recent papers have examined the dominant drivers of business cycles using variance-maximizing techniques for identification. However, identification is poor when shocks other than the target of interest play large roles in driving volatility at the targeted frequency or horizon, leading them to capture a "hybrid" shock. This paper suggests a simple fix that lowers biases in the impulse responses. The fix is to include theoretically informed sign and magnitude restrictions at the identification stage of the vector autoregression. Applying this to US data, we find an equal role for demand and supply shocks in generating business cycle fluctuations.
Abstract
					Two recent strands of the structural vector autoregression literature use higher moments for identification, exploiting either non-Gaussianity or heteroskedasticity. These approaches achieve point identification without exclusion or sign restrictions. We review this work critically and contrast its goals with the separate research program that has pushed for macroeconometrics to rely more heavily on credible economic restrictions. Identification from higher moments imposes stronger assumptions on the shock process than second-order methods do. We recommend that these assumptions be tested. Since inference from higher moments places high demands on a finite sample, weak identification issues should be given priority by applied users.
Abstract
					We measure the labor market outcomes of employees with downward rigid base wages after an unexpected deflationary shock in Switzerland using a firm survey matched with Social Security register data. The employees that additionally receive downward flexible compensation, such as bonuses, are less likely to lose their job after a deflationary shock than those only receiving a base wage. Only a modest share of employees receives downward flexible compensation, however. Therefore, these compensation schemes do not offset the overall allocative effects of downward rigid base wages.
Abstract
					Life insurers' business model has changed with the growth of insurance products with minimum return guarantees that are exposed to market and interest risks. The interest risk exposure of US and European insurers increased in the low-rate environments after the global financial crisis and the European sovereign debt crisis, respectively. The relative fragility of life insurers is highly persistent across the global financial crisis, the European sovereign debt crisis, and the COVID-19 crisis. European insurers with a higher share of liabilities with minimum return guarantees in 2016 had lower stock returns during the COVID-19 crisis.
Abstract
					"Zombie lending"—lending to less-productive firms at subsidized rates—can help banks with misaligned incentives in the short run, but it prolongs economic downturns. We propose that inefficient resolution of insolvency is a significant contributor to this problem. We exploit variation in the efficiency of insolvency across countries to show that lack of formal bankruptcies, cheap (zombie) credit, and stickiness of existing creditors is more common in bad economic periods when insolvency works less well.
Abstract
					Over the past decade, non-Paris Club creditors, notably China, have become an important source of financing for low- and middle-income countries. In contrast with typical sovereign debt, these lending arrangements are not public, and other creditors have no information about their magnitude. We transform the traditional sovereign debt and default model to quantitatively study incomplete information arrangements and find that they greatly reduce traditional Paris Club creditors' debt sustainability. Disclosure of nontraditional debt would imply significant welfare gains for the recipient countries but would reduce its sustainability. We discuss the implications of nontraditional lending on standard assumptions of sovereign debt models.
Abstract
					We use a model of multiunit discriminatory auctions with asymmetrically informed risk-averse bidders to analyze Mexican sovereign bond auctions during periods of macroeconomic stress. We argue that the discriminatory protocol provides insurance benefits to the government in bad times because it allows for uninformed bids above the marginal price to be executed at the bid price. Uninformed investors are willing to make such bids if the inframarginal risk premium is large enough to offset the winner's curse. In crisis periods, we infer 1 p.p. lower borrowing costs in the worst states of the world, but 2.2 p.p. higher average costs.
Abstract
					China's lending boom to developing countries is morphing into defaults and debt distress. Given the secrecy surrounding China's loans, the associated defaults remain "hidden," as missed payments and restructuring details are not disclosed. We construct an encompassing dataset of sovereign debt restructurings with Chinese lenders and find that these credit events are surprisingly frequent, exceeding the number of sovereign bond or Paris Club restructurings. Chinese lenders follow a resolution approach reminiscent of 1980s Western lenders; they seldom provide deep debt relief with face value reduction. If history is any guide, multiyear debt workouts with serial restructurings lie in store.
Abstract
					We study the role of transparency in debt and default dynamics in a quantitative sovereign default model augmented with asymmetric information. We assume that the sovereign debt portfolio is not transparent and part of the debt is not observable to lenders. The quantitative model is calibrated to the Bolivian economy and matches its long-term and business cycle properties. The quantitative results show that when the government moves to a transparent reporting regime, bond prices improve and the sovereign debt portfolio shifts toward noncontingent debt with an increase in overall debt level. However, higher debt increases default frequency and reduces welfare.
Abstract
					It is widely believed that female employment and empowerment are intimately related. This paper presents relationships between women's employment and various measures of their empowerment, using data from rural India. The measures capture several dimensions of empowerment, including control in economic decision-making, psychosocial aspects of empowerment, and women's own internalization of a lesser status. A number of these measures correlate positively with women's employment, supporting the notion that female employment and empowerment are closely linked.
Abstract
					We propose and validate a simple way to augment the standard Becker-DeGroot-Marschak method that researchers use to elicit willingness to pay (WTP) for a good. The augmentation is to measure WTP for another good ("benchmark good"), one unrelated to both the good the researcher is interested in and the independent variables of interest, and to use WTP for the benchmark good as a control variable in analyses. We illustrate the method and how it can eliminate noise in measured WTP using data collected in Uganda.
Abstract
					Mothers-in-law, especially those in South Asia, can exert significant influence over women, often even more so than women's husbands or other household members. Using data from rural India, we first show that mothers-in-law are more likely than husbands to (i) disapprove of women's family planning use and (ii) want women to have more children, particularly sons, than women themselves want. Next, using a field experiment, we show that providing women with vouchers for subsidized family planning services not only enabled them to initiate discussions about family planning with their mothers-in-law but also increased their mothers-in-law's approval of family planning.
Abstract
					Who are the girls who decide to sign up for science, technology, engineering, and mathematics (STEM) programs and coding clubs? In this paper, we rely on a large set of survey data from students to analyze how female students who apply to coding clubs differ from other students in the schools. Girls applying to coding clubs have higher STEM interest, but they perceive their own gender as a stronger barrier to achieve their educational goals. Supporting this pool of female applicants with STEM programs might have a substantial role in affecting their educational and occupational careers and closing the gender gaps in occupational choices.
Abstract
					Research in disciplines outside of economics has found that male-authored articles often exhibit a positivity bias in writing style and are more likely to portray their results as "novel" and "progressive" than female-authored articles. Such positively marketed research has also been found to garner more citations over time. The primary question this research asks is whether writing style in academic economics research differs by gender and, in particular, whether the positivity bias differs by gender. It appears that it does and that this does affect citation rates, to the detriment of articles with any level of female authorship.
Abstract
					We use an RCT at an elite public university to evaluate whether undergraduate students in introductory economics courses could be nudged to pursue economics further. Two treatment arms provided information and framed the economics major as either having wide applicability or high financial returns. Both treatments nudged men to take more courses similarly, with no effects on women. Women with a lower-than-expected introductory course grade reduced course-taking in response to either treatment; men in this position were nudged to take more courses. Men with female TAs were also nudged to take more courses, while women were not.
Abstract
					Parental investments shape children's educational specializations. Using a longitudinal study, we find that parents invest more in daughters than sons at ages three through five. We find that early parental investment can explain persistently higher English scores for girls than boys four to six years later. However, there is no gender gap in math. Parental investments at ages three through five appear to contribute to girls' advantage in English but have little impact on math. Our results suggest that parental investments at early ages contributes to girls' comparative advantage in English.
Abstract
					Leveraging data from Sweden and Chicago, we study the educational pipeline for science, technology, engineering, and mathematics (STEM) and economics majors to better understand the determinants of the gender gap and when these determinants arise. We present three findings. First, females are less likely to select STEM courses in high school despite equal or better preparation. Second, there are important gender differences in preferences and beliefs, even conditional on ability. Third, early differences in preferences and beliefs explain more of the gaps in high school sorting than other candidate variables. High school sorting then explains a large portion of the gender difference in college majors.
Abstract
					In-person tutoring programs can have large impacts on K-12 student achievement, but high program costs and limited local supply of tutors have hampered scale-up. Online tutoring provided by volunteers can potentially reach more students in need. We implemented a randomized pilot program of online tutoring that paired college volunteers with middle school students. We estimate consistently positive but statistically insignificant effects on student achievement, 0.07 standard deviations for math and 0.04 standard deviations for reading. While our estimated effects are smaller than those for many higher-dosage in-person programs, they are from a significantly lower-cost program delivered within the challenging context of the COVID-19 pandemic.
Abstract
					Classroom experiments are a popular tool among economics instructors. A rich experimental literature studies their impact on student learning with between-subject designs that randomize classroom experiment use across course sections. Such designs are difficult to set up and conduct in a way that achieves adequate statistical power. We complement this literature with a within-subject experiment where classroom experiments are randomized across topics within a section, which enhances power and is easier to implement. We find little impact of our classroom experiments on student achievement for either male or female students, but these null results may mask heterogeneous effects across topics.
Abstract
					Economists are obsessed with rankings of institutions, journals, or scholars according to the value of some feature of interest. These rankings are invariably computed using estimates rather than the true values of such features. As a result, there may be considerable uncertainty concerning the ranks. In this paper, we consider the problem of accounting for such uncertainty by constructing confidence sets for the ranks. We consider the problem of constructing marginal confidence sets for the rank of, say, a particular journal as well as simultaneous confidence sets for the ranks of all journals.
Abstract
					In the presence of markup differences, externalities, and other social effects, the direction of innovation can be systematically distorted. I build a simple model of endogenous technology to study distortions in the direction of innovation. Empirical findings across a number of different areas are consistent with this framework's predictions. I use data from several studies to estimate the framework's key parameters and combine them with rough estimates of differential externalities and markups to provide suggestive evidence that innovation distortions can be substantial in the context of industrial automation, health care, and energy, and that correcting them could have sizable welfare benefits.
Abstract
					We quantify how market integration affects the economic propagation of sectoral supply shocks at the example of a Russian gas shutoff to the European Union. An open-economy, multisector general equilibrium model suggests that the adverse output impact on the European Union shrinks fourfold if integration with the global liquified natural gas (LNG) market is considered. On the flip side, other LNG importers also see adverse output effects. Due to nonlinearities, the combined total economic damage is less than half with integration, compared to the counterfactual case without. Governments should foster further integration to make economies more resilient to supply shocks.
Abstract
					The seminal work of Jonung (1981) showed that households' perceptions of inflation are the strongest predictor of households' inflation expectations. This fact has been a key ingredient for testing and developing theoretical models of how economic agents form expectations (e.g., the famous Lucas (1972) island model). However, little is known about whether perceptions play a similar role for firms. Using a new survey of American CEOs, we document that inflation perceptions shape the inflation expectations of firms just as Jonung (1981) found for households. These results suggest that information rigidities apply not only for households but also for CEOs.
Abstract
					We introduce a new measure of own-price inflation uncertainty using firm-level data from a large and representative survey of UK businesses. Inflation uncertainty has increased significantly since the start of 2021, even as a similar measure of sales uncertainty has declined. We also find large cross-sectional differences in inflation uncertainty, with uncertainty particularly elevated for smaller firms and those in the goods sector. Finally, we show that firms that are more uncertain about their own price expectations experience higher forecast errors 12 months later. These findings suggest that inflation uncertainty may be important for understanding firm performance.
Abstract
					In an effort to stabilize the economy during the COVID-19 pandemic, the German government reduced value-added taxes (VAT) by 3 percentage points for a period of six months in the latter half of 2020. This measure resulted in a boost in aggregate consumer spending on both durable and semidurable goods during the six-month period, with spending decreasing once the VAT reduction was reversed. The effect of the temporary VAT cut on durable spending was stronger than on semidurable spending. Additionally, the temporary VAT cut also stabilized, and even slightly increased, inflation expectations in the second half of 2020.
Abstract
					We provide a simple framework connecting the distribution of excess savings across households to the dynamics of aggregate demand. Deficit-financed fiscal transfers generate excess savings. The poorest households with the highest marginal propensities to consume (MPCs) spend down their excess savings the fastest, increasing other households' incomes and their excess savings. This leads to a long-lasting increase in aggregate demand until, ultimately, excess savings have "trickled up" to the richest savers with the lowest MPCs, raising wealth inequality.
Abstract
					This paper builds on Baqaee and Farhi (2022) and di Giovanni et al. (2022) to quantify the contribution of fiscal policy on US inflation over the December 2019 to June 2022 period. Model calibrations show that aggregate demand shocks explain roughly two-thirds of total model-based inflation and that the fiscal stimulus contributed half or more of the total aggregate demand effect.
Abstract
					We use Belgian data on domestic firm-to-firm transactions and ask how the measurement of the share of imports in final consumption is affected when one uses data recorded at higher levels of aggregation. We find that aggregating detailed firm-to-firm transaction data to the firm level and imposing homogeneity assumptions in the composition of firms' input and output do not substantially affect the measurement of the share of imports in final consumption. However, using the national input-output tables alone may understate the share of imports in final consumption and, thereby, the gains from trade.
Abstract
					We study the joint process of urbanization and industrialization in the US economy between 1880 and 1940. We show that only a small share of aggregate industrialization is accounted for by the relocation of workers from remote rural areas to industrial hubs like Chicago or New York City. Instead, most sectoral shifts occurred within rural counties, dramatically transforming their sectoral structure. Most within-county industrialization occurred through the emergence of new "factory" cities with notably higher manufacturing shares rather than the expansion of incumbent cities. In contrast, today's shift toward services seems to benefit large incumbent cities the most.
Abstract
					We measure export participation rates in the US manufacturing sector using a new administrative dataset and compare them to participation rates constructed from the commonly used census of manufacturers (CM). At both the establishment and firm levels, export participation rates are near 40 percent in the administrative data, almost twice as high as in the CM. The discrepancy appears to result predominantly from undercounting of small exporters in the CM. Our findings call for reconsidering the conventional wisdom that around 20 percent of manufacturing firms export.
Abstract
					There is growing evidence that corporate market power is increasing and affecting monetary policy transmission. This paper develops a partial equilibrium model that highlights the role of financial constraints in shaping the role of markups for the response of firms to monetary policy shocks. We find support for such a role using a large cross-country firm-level dataset for 14 advanced economies.
Abstract
					Monetary policy aims to affect corporate borrowing by influencing the marginal costs of firms, but its potency can be conditioned by the degree of market competition. We first identify conditions under which changes in marginal costs have different effects on credit constraints and output under different competitive environments, in a simple Cournot competition setting. We then exploit a monetary policy easing shock in the euro area to examine whether policy pass-through is conditioned by market structure. We show that small firms within less concentrated sectors experienced a larger reduction in credit constraints than similar firms in more concentrated sectors.
Abstract
					Using the near universe of online vacancy postings in the United States, we explore linkages between labor market power and the trade-off between unemployment and wages. We estimate the Phillips curve at the commuting zone level and find that the relationship between unemployment and wage inflation is weak in regions with high labor market power. These results help explain the flattening of the wage Phillips curve following the global financial crisis. In the context of rising interest rates, unemployment is likely to rise more in poorer US regions because labor market power is more prevalent there, thus leading to rising inequality.
Abstract
					We document the rise of China in offshore capital markets. Chinese firms use global tax havens to access foreign capital in both equity and bond markets. In the last 20 years, China's presence went from raising a negligible amount of capital in these markets to accounting for more than half of equity issuance and around a fifth of global corporate bonds outstanding in tax havens. Using rich micro data, we show that a range of Chinese firms, including both tech giants and state-owned enterprises, use these offshore centers. We conclude by discussing the macroeconomic and financial stability implications of these patterns.
Abstract
					We document the decline in market power of the United Kingdom in safe assets and quantify the resulting losses. We estimate an increasing elasticity of demand for UK public debt during the latter half of the twentieth century. This is in sharp contrast to the United States, which displays the opposite pattern with decreasing elasticities of demand during this time. We argue that the decline in market power of the United Kingdom in safe assets resulted in a sizable decline in seigniorage revenues.
Abstract
					As a bridge between Chinese mainland and international financial markets, the Stock Connect program allows investors on both sides to gain mutual access. By analyzing how cross-border flows respond to macro-related shocks, we show that compared with possibly homemade foreign investors, genuine foreign investors are more likely affected by the US monetary shocks, the exchange rate risk, the US market performance, and the cross-market valuation disparity. The paper highlights the importance of profiling different groups of cross-border participants over market integration.
Abstract
					This paper shows that China's lending boom to developing country sovereigns has largely ended and that debt distress and defaults are increasingly common. Chinese lenders react to this challenge through two main coping strategies: first, bilateral sovereign debt restructurings—typically with maturity extensions but no face value cuts—and, second, rescue loans that allow debtors to avoid or delay default. Low-income countries tend to receive debt restructurings, whereas emerging market countries are more likely to receive rescue loans. We speculate that the differential crisis response is due to the different exposure levels of Chinese state banks.
Abstract
					We introduce a new real-time method to measure business opening and closure rates by relying on Google Places, the data behind the Google Maps platform. We collect data on establishments of customer-facing industries (food, retail, accommodation) and provide evidence that the opening and closure rates reflect well the temporary closures and reopening during the pandemic. We find that the operational or closed status of establishments is correlated with business reviews: fewer reviews are associated with impending business exit, and more reviews are associated with expanding businesses posting new job vacancies.
Abstract
					The Census Bureau's new Business Trends and Outlook Survey (BTOS) provides timely information from businesses on their current trends and expectations over core concepts such as prices, employment, and revenue. The BTOS collects qualitative information in order to produce extensive margins for core economic phenomena. BTOS results are representative of all single-location nonfarm businesses in the United States. We highlight sectoral differences in extensive margins of employment and prices using the Finance and Insurance sector and the Accommodation and Food Services sector as examples. We find that businesses, especially in Accommodation and Food Services, anticipate future output price increases, possibly to accommodate rising current input prices.
Abstract
					Nontraditional data can provide critical economic insights in real time. We document the development of weekly employment indexes based on microdata from the payroll processor ADP. These data have provided insights into labor market developments in the fast-moving pandemic environment of recent years, as well as in more quiescent periods. We describe processes for weighting and benchmarking, seasonally adjusting weekly data, and ultimately combining the signals from ADP and official data. Finally, we show how the weekly employment indexes have fared during the pandemic jobs recovery, focusing on revisions to official data for the second half of 2021.
Abstract
					Professional networks affect labor market outcomes, efficiency, and knowledge diffusion. We study a large business card exchange network from Eight, a contact and career management app popular in Japan. Our empirical analysis is guided by a structural model of equilibrium network formation, with observable and unobservable heterogeneity, estimated via a two-steps approach that reduces computational challenges. In the first step, we recover the unobservable types; in the second step, we estimate the structural parameters, conditioning on estimated unobservables. Our results highlight the role of shared contacts and homophily in observables and unobservables in shaping the network of professional contacts.
Abstract
					This paper estimates the heterogeneous impact of advertising networks from the perspective of a publisher who has access to limited information provided by the advertising platform in the form of grouped data over different auctions and users. The models account for the high-dimensional nature of the data and allow for time-varying interactive effects. We estimate models for different countries, and the measured heterogeneity may reflect factors such as local competition or cost effectiveness.
Abstract
					We study how inheriting parents' credit histories affects the initial credit scores, access to credit, and life cycle borrowing of young individuals entering the credit market. We establish that inherited histories significantly positively affect initial scores, which in turn are very persistent. Inherited histories only affect outcomes through initial credit scores, which then have significant persistent effects on credit use and access, such as having a mortgage. Our results are consistent with mechanisms of self-fulfilling liquidity traps: low credit scores mean lack of access to credit, reinforcing low credit scores. Future research should address the contribution of such mechanisms to wealth inequality.
Abstract
					We study the relationship between media portrayals of inflation and consumer sentiment. Using tools from natural language processing, we uncover two competing narratives in US news coverage of inflation: the first relates inflation to financial variables, while the second relates inflation to real variables. As inflation rose in 2021, media increasingly emphasized the real economy. Linking inflation news to social network data from Twitter, we find that exposure to articles emphasizing the connection between inflation and the real economy significantly reduces sentiment, particularly in periods of high inflation. Shifting media narratives may therefore have contributed to declining consumer sentiment in 2021.
Abstract
					Using a proprietary transaction-level database of nearly 30,000 multiple-draw construction loans and their on-site inspection reports, we empirically examine the relationship between geographic distance and bank information acquisition over the course of the loans (i.e., monitoring). We find that projects farther from the nearest bank branch are more intensely monitored by bank-contracted, third-party inspectors (delegated monitors) and that projects farther from these inspectors receive less intense monitoring, potentially because inspectors face distance-related frictions. These results are consistent with the prediction that distance increases informational frictions but also suggest that banks may offset these frictions by delegating monitoring to closer inspectors.
Abstract
					Blockchain technology has facilitated the emergence of a new type of organizational form, decentralized autonomous organizations (DAOs). In contrast to corporations and other types of business organizations, DAOs do not have managers or directors with formal decision rights. Instead, the members of DAOs collectively make decisions by voting on proposals. The governance process is encoded and executed via smart contracts, negating the need for centralized leadership. We examine the control of DAOs by analyzing 10,639 proposals across 151 DAOs. We find that rather than democratizing decision-making, a small number of entities, often three or fewer, exert control over most decisions.
Abstract
					What comes to mind when thinking about a successful entrepreneur? Belief formation models suggest that what comes to mind is an oversimplified picture of the characteristics of successful entrepreneurs—that is, stereotypes about successful entrepreneurs. Using French administrative data on 48,767 new firms, we show that some characteristics are stereotypical of success and have distributions that can generate miscalibrated beliefs. To illustrate how stereotypical thinking can lead to biased assessments, we report the discrepancies between the implied fraction of successful entrepreneurs under Bayesian versus stereotypical thinking for several stereotypes. We discuss the consequences of stereotyping for venture capital allocation.
Abstract
					This paper uses data from the 2019 Annual Business Survey to document that firms adopting advanced technologies are larger in terms of employment than other firms in their same industry and cohort. Using data from the Longitudinal Business Survey, we show that adopters were already large and growing faster before artificial intelligence, robotics, cloud computing, and specialized software systems became broadly available. These findings support the view that adopters are large because of selection and not because adopting advanced technologies for automation causally expands their employment.
Abstract
					We use establishment-level data from the US Census Bureau's Annual Survey of Manufactures to study the characteristics and geographic locations of investments in robots. We find that the distribution of robots is highly skewed across locations. Some locations, which we call Robot Hubs, have far more robots than one would expect even after accounting for industry and manufacturing employment. We characterize these Robot Hubs along several industry, demographic, and institutional dimensions. The presences of robot integrators, which specialize in helping manufacturers install robots, and of higher levels of union membership are positively correlated with being a Robot Hub.
Abstract
					Using an event study methodology and comprehensive micro data from the French manufacturing sector, we analyze the local labor market effects of investments in modern manufacturing capital, including modern automation technologies. We estimate that commuting zones with higher investments in modern manufacturing capital and automation benefit from higher labor demand, with an increase in both local employment and wages. Our findings are consistent with a task-based model where the productivity effects of modern capital investments and automation outweigh their displacement effect.
Abstract
					We analyze the impact of robot adoption on female employment. Our analysis is based on novel micro data on robot use by German manufacturing establishments linked with social security records. An event study analysis for robot adoption shows increased churning among female workers. Whereas hiring rises significantly at robot adoption, separations increase with a smaller magnitude one year later. Overall, employment effects are modestly positive and strongest for medium-qualified women. We find no adverse employment effects for female workers in any of our broad qualification groups.
Abstract
					We examine the demand-side implications of Amazon's distribution and logistics investments. Our results indicate that online demand—transactions at Amazon and its competitors—does not respond to the consumer's proximity to Amazon's upstream fulfillment distribution facilities, suggesting that their densification did not differentially improve local shipping times and on-time delivery. Instead, we find that investments in last-mile delivery facilities and services allow the company to improve shipping times more directly in the urban markets served by these facilities, simultaneously increasing demand through the rollout of same-day service options and reducing the visits to traditional brick-and-mortar retail.
Abstract
					We study the 2013 merger of three multiple listings services (MLSes) in Florida, the primary platforms where properties are transacted. We use MLS listings data from 2009 to 2019 to trace out the effects of the merger on the likelihood that listings by brokerages from different platforms are traded. The merger sharply increased the platform scale for brokerages whose platforms were not dominant in a local market prior to the merger. This exposed their listings to more agents and also expanded their access to more listings. Difference-in-difference estimates indicate that nondominant brokerages are more likely to have interplatform trades.
Abstract
					We study whether Amazon engages in self-preferencing on its marketplace by favoring its own brands (e.g., Amazon Basics) in search. To address this question, we collect new micro-level consumer search data using a custom browser extension installed by a panel of study participants. Using this methodology, we observe search positions, search behavior, and product characteristics. We find that Amazon-branded products are indeed ranked higher than observably similar products in consumer search results. The prominence given to Amazon brands is 30 percent to 60 percent of the prominence granted to sponsored products.
Abstract
					A recent empirical literature models search and matching frictions by means of a reduced-form matching function. An alternative approach is to simulate the matching process directly. In this paper, we follow the latter approach to model matching in ride-hailing. We compute the matching function implied by the matching process. It exhibits increasing returns to scale, and it does not resemble the commonly used Cobb-Douglas functional form. We then use this matching function to quantify network externalities. A subsidy on the order of $2 per trip is needed to correct for these externalities and induce the market to operate efficiently.
Abstract
					This paper examines the characteristics of firms that adopt new financial products and their association with measures of performance. We build a novel firm-level panel dataset and document a positive association between intangible capital and the adoption of new products. We also find that access to external financing through new types of securities is associated with size growth and further investments into intangibles. These findings have important implications for understanding the role that financial innovation can play in meeting the financing needs of firms that rely heavily on intangible capital.
Abstract
					We document a secular shift from initial public offerings to acquisitions of venture capital-backed start-ups and show that this trend is accompanied by an increase in the opportunity cost of going public over the last quarter-century. Dominant companies that are disproportionately active in the corporate control market for start-ups have become more insulated from the pressures of product market competition over the same period. These facts are consistent with the hypothesis that start-up acquisitions have contributed to rising oligopoly power.
Abstract
					The rise in markups and market power documented by De Loecker, Eeckhout, and Unger (2020) has recently generated much discussion in economics. We measure the correlation between the change in firm level markups and the change in industry level prices as measured by the Producer Price Index and find little to no relationship both for 1980–2018 and 2018–present. While a "false negative" result due to mismeasurement is possible, it also raises the possibility that firms have not passed along declines in marginal costs to consumers or that there have been significant changes in scale elasticities.
Abstract
					Most economy-wide studies of merger activity ignore deals whose terms are not announced. Using US data, I find that restricting attention to mergers with publicized values eliminates 60 percent or more of transactions. Exploiting a change in antitrust law, I find that mergers with unpublicized values are competitively significant. The data even suggest that these transactions reflect, at least in part, strategic attempts to avoid enforcement actions by escaping detection. Last, relying on an idiosyncratic feature of accounting standards to infer their size distribution, I find that ignoring mergers with unpublicized values undermeasures the extent of stealth consolidation by 40 percent.
Abstract
					Policymakers are increasingly concerned that incumbent acquisitions of small or young firms may slow down rather than speed up innovation, but it is difficult to identify which firms are related in the fast-changing space of technological innovation. This paper proposes a new, data-driven method to classify patent data into tech-business zones on a probabilistic basis, using patent assignee information. After combining mergers and acquisitions data from S&P Global Market Intelligence with PatentsView data from the US Patent and Trademark Office, we discuss how the zone classification can aid merger reviews and other lines of research.
Abstract
					We provide new facts about the cross section and evolution of mergers and acquisitions for US public firms. Using a general equilibrium model with a hedonic demand system and data on institutional ownership, we document that mergers are increasingly concentrated among firm pairs with a high degree of product market interaction and a moderate to high degree of common ownership. We estimate how much mergers have raised aggregate corporate profits and reduced consumer surplus and quantify how the anticompetitive effects of mergers are affected by common ownership and shareholder value maximization motives.
Abstract
					We describe the initial impact of risk-based flood insurance pricing in the United States. More than two-thirds of National Flood Insurance Program policyholders are paying higher premiums under "Risk Rating 2.0" (RR2.0), and increases will continue in the coming years. Premium increases are largest for policyholders classified as low risk on the Federal Emergency Management Agency's (FEMA's) flood maps, and the average premium gap between those in and out of the FEMA-mapped floodplain is narrowing. FEMA's flood maps, which fail to account for the new risk information, are still relied on by homeowners and regulators, blunting the adaptation benefits of RR2.0.
Abstract
					This paper studies whether private adaptation to flood risk is economically efficient. We estimate the return to elevating houses, one of the most significant private defensive investments against flooding, using two decades of microdata on the universe of houses and flood damages in high-risk flood zones in the Atlantic and Gulf Coast United States. We find that undertaking adaptation is socially optimal in the highest-risk areas over a house's lifetime but that individual homeowners may underinvest in flood protection because the benefits do not accrue over their average tenure. We identify conditions under which adaptation yields the highest returns.
Abstract
					Decarbonization of light-duty vehicles (LDVs) in the United States is an important policy priority. We investigate the roles of the Infrastructure Investment and Jobs Act and the Inflation Reduction Act in accelerating the transition of LDVs to electric vehicles. We additionally consider alternate allocations of government funds for subsidized construction of charging stations and refundable tax credits for electric vehicles. We find that charging station subsidies are extremely effective as measured by impact for a given fiscal expenditure. All of the policies we consider have estimated costs below the most recent estimate of the social cost of carbon.
Abstract
					We investigate the pass-through of electric vehicle (EV) subsidies in 13 countries that account for 95 percent of global EV sales from 2013 to 2020. Our results indicate high pass-through rates of 70-80 percent on average. Pass-through is highest for global firms that sell the same EV models across multiple countries, consistent with uniform pricing by these firms, as well as avoidance of third-party arbitrage. We find suggestive evidence that pass-through is higher for tax incentives than for direct consumer subsidies.
Abstract
					Electric vehicle (EV) sales have been rapidly growing around the world, spurred by technology advances and policy actions. This study leverages rich data on all individual new light-duty vehicles sold in the United States from 2014 to 2020. We examine how EV attributes, prices, and sales have evolved, exploring substantial heterogeneity across geography, vehicle class, price range, and demographics. We use a matching analysis to compare EVs to similar conventional vehicles to find that EVs have been surprisingly competitive in very recent years. This suggests that constrained supply is an important determinant of the low overall EV market share.
Abstract
					We analyze the effects of conflict-related violence on the mental health of caregivers and young children, as well as the role of caregivers' mental health in explaining the toll of conflict on early childhood mental health. Although an upcoming body of work has demonstrated the link between caregivers' and children's mental health, the role of caregivers' psychological constraints has been largely ignored in research and programming in conflict-affected settings. We demonstrate how these constraints play a role in the intergenerational transmission of mental health problems and emphasize the urgency of addressing caregivers' mental health within early childhood development programs in conflict-affected settings.
Abstract
					Reparations recognize and address the harm that victims suffered during war, conflict, or authoritarianism, and some experts argue that the compensation can also help victims to rebuild life projects. Using linked administrative microdata, we study the world's largest reparations program, currently being implemented in Colombia. First, we provide descriptive evidence on Colombia's conflict victims. Then, we shed light on how reparations' various aims have shaped the program's design and implementation features and on who has received compensation. Last, we discuss the practical challenges and tensions in balancing the various goals of reparations programs under tight fiscal constraints and limited state capacity.
Abstract
					How can regularization programs improve forced migrants' resilience to shocks? We leverage panel data collected during the COVID-19 pandemic to assess whether Venezuelan forced migrants who were eligible for a regularization program in Colombia were more resilient and less affected by the pandemic than similar but noneligible forced migrants. Results indicate that access to the program promoted better health access for eligible migrants, facilitating adherence to prevention guidelines and increasing detection rates. Additionally, eligible migrants had better housing and labor conditions, relative to noneligible migrants.
Abstract
					This paper analyzes the entire business registry of Colombia during 2015–2022, a period when Colombia received two million Venezuelan immigrants and refugees. We present two main findings. First, firms owned by foreigners, most of them Venezuelans, tend to be 10 to 20 percent more capitalized when founded as compared to firms owned by locals within the same industry, geographic location, and year of registration. Second, while more intensive in capital, these firms owned by foreigners are just as likely to survive the first two and three years as firms owned by locals are. We discuss the implications for these findings.
Abstract
					Unaccompanied migrant children (UMC) account for a growing share of apprehensions along the US-Mexico border. Contrary to past UMC flows, which were primarily comprised of older youth fleeing violence in Mexico, recent UMC flows include children of all ages escaping life-threatening conditions in Central America's Northern Triangle. To manage the growing influx of UMC, the Biden Administration established surge facilities, which rely on emergency standards to house and care for the children. We show that surge facilities created capacity in traditional shelters, enabling them to accommodate tender-age children and reducing the number of children in foster care.
Abstract
					Illegal immigration has increased substantially in recent years. In this paper, we analyze how Secure Communities (SC), a major internal immigration enforcement program, affected self-employment participation and income in the United States between 2008 and 2013. Following a difference-in-difference approach, we find that the staggered implementation of the SC reduced self-employment rates across the country, but not substantially. However, the policy had a significant negative impact on the income of the self-employed, particularly affecting White and male individuals and workers in the manufacturing and service sectors. Overall, our results highlight the unintended consequences of SC on entrepreneurship in the United States.
Abstract
					Pollution concentrations (PM2.5) in the United States have fallen in recent decades. Despite these improvements, disparities in concentrations between racial/ethnic groups persist. We combine administrative data on the universe of emergency room (ER) admissions across California with satellite information on PM2.5 concentrations and compare recent trends in racial/ethnic disparities for PM2.5 and asthma rates. We find that PM2.5 concentrations fell for the average Black, Hispanic, and White individual. Similarly, disparities in PM2.5Citation
					

                        Hernandez-Cortes, Danae, and Kyle C. Meng.
						2023.

						
						
							"Do Health Disparities Narrow with Pollution Disparities? Trends from California."
						
						AEA Papers and Proceedings,

							  
					113:
					 372-76.
				  
						DOI: 10.1257/pandp.20231128
					

					
												
							
								
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				Additional Materials

						
						                    
                Replication Package                                            
                            
                Online Appendix                                                    (203.85 KB)
                            
                            
                Author Disclosure Statement(s)                                                    (137.11 KB)
                            
        
						JEL Classification
						
								D31
								Personal Income, Wealth, and Their Distributions
															
								I12
								Health Behavior
															
								I14
								Health and Inequality
															
								Q51
								Valuation of Environmental Effects
															
								Q53
								Air Pollution; Water Pollution; Noise; Hazardous Waste; Solid Waste; Recycling
															
								R11
								Regional Economic Activity: Growth, Development, Environmental Issues, and Changes
Abstract
					The answer is "yes" for personal income taxes but "no" for corporate income taxes. Using narrative-identified US federal tax changes post-World War II and disaggregated sectoral data on consumer and producer prices, we show that higher average personal income tax rates lower prices across a broad range of sectors, but higher average corporate tax rates do not. There is also significant sectoral heterogeneity in the size of the effects. Finally, only personal tax increases lower inflation expectations, while corporate tax increases lead to persistent declines in stock prices. Our results are consistent with personal taxes affecting aggregate demand and corporate taxes persistently affecting supply conditions.
Abstract
					We analyze whether government spending multipliers differ by the sign of the shock. Using aggregate historical US data, we apply Ben Zeev's (2020) nonlinear diagnostic tests and find evidence of nonlinearities in the impulse response functions of both government spending and GDP. We then extend Ramey and Zubairy's (2018) framework to allow for asymmetric effects as a type of state dependence to estimate multipliers. While we find differences in the impulse response functions, the resulting multipliers do not differ by sign of the shock. Thus, declines in government spending do not have different effects on economic activity than rises in spending.
Abstract
					Economic theory suggests that the effects of fiscal stimulus can vary substantially with the systematic response of monetary policy. Empirical estimates of the causal effects of fiscal shocks implicitly embed a particular monetary reaction: they provide treatment effects that average across in-sample monetary policy. Building on McKay and Wolf (2022), I discuss how evidence on monetary policy shocks can be used to predict the effects of fiscal stimulus under arbitrary monetary policy reaction. I review the underlying theory, propose a simple empirical strategy, and present an application.
Abstract
					I estimate the effects of Federal Open Market Committee (FOMC) announcements, post-FOMC press conferences, and speeches and Congressional testimony by the Fed chair on stock prices, Treasury yields, and interest rate futures from 1988 to 2019. I show that for all but the very shortest-maturity interest rate futures, Fed chair speeches are more important than FOMC announcements. My results suggest that the previous literature's focus on FOMC announcements has ignored the most important source of variation in US monetary policy.
Abstract
					We estimate the extensive and intensive margin labor supply response to the monthly Child Tax Credit disbursed in 2021 as a part of the American Rescue Plan Act. Using Current Population Survey microdata, we compare labor supply outcomes among households who qualify for varying relative increases in household income as a result of their income level and household size. We do not find strong evidence of a change in labor supply for families receiving the credit. The results are robust to alternative labor supply models, where households respond mainly to cash on hand or changes in the annual budget set.
Abstract
					We investigate the effects of the expanded 2021 Child Tax Credit (CTC) on material hardship among households with children over April 2021–May 2022, using the Census Household Pulse Survey and difference-in-difference analyses of household types with different eligibility. Monthly CTC payments (July–December 2021) reduced food insufficiency by at least 2.4 pp (20 percent); the spring 2022 lump-sum payment reduced the likelihood that households were behind on rent by at least 1.2 pp (10 percent). Results are consistent with spending lump sums differently from monthly payments, the former going disproportionately toward arrears and the latter toward ongoing food/nutrition costs.
Abstract
					In March of 2021, Congress passed a one-year expansion of the Child Tax Credit (CTC), creating a temporary, near-universal child benefit. Despite expanding eligibility to millions of previously ineligible children living in low-income households, only two-thirds received the monthly benefit. We illustrate that some historic gaps in receipt of the CTC remain despite the efforts to make the credit more universal: prior tax filing, household income, and survey language were among the strongest predictors of monthly receipt. More work is needed to understand why families did not receive the CTC and how to reach these vulnerable populations.
Abstract
					The COVID-19 pandemic increased the rate of mental health disorders, as well as demand for mental health services. It remains unclear, however, the extent to which it impacted access to mental health care. Using data from an audit field experiment, which ran from January to May 2020 and overlapped with the onset of the COVID-19 pandemic, we examine the impact of COVID-19 on access to mental health care appointments in the United States. We find that increased intensity of COVID-19—measured by daily cases, daily fatalities, and weekly excess deaths—is associated with decreased access to mental health care appointments.
Abstract
					Job applicants use resumes to send signals to potential employers. Applicants are free to select the items that go in their resumes and are expected to include signals they perceive will help them achieve their goals and avoid those that they anticipate could hurt them. We show that 92 percent of beneficiaries of a highly selective scholarship for poor and talented students avoid listing this award when applying for jobs. This is consistent with beneficiaries perceiving a negative labor market return from sending that signal. A correspondence study shows instead that listing the scholarship increases callback rates by 20 percent.
Abstract
					This study investigates discrimination against women when searching and applying for childcare in a nationwide field experiment. We send emails from fictitious parents to 9,313 childcare centers in Germany inquiring about access to childcare. We randomize whether the email is sent by the child's mother or father. Our results show that women receive shorter and less positive responses than men. The probability of receiving a response does not differ by gender, highlighting the importance of going beyond response rates to detect discrimination. We provide suggestive evidence that regional differences in gender discrimination are related to gender norms.
Abstract
					We conduct a natural field experiment to test whether offering financial incentives encourages more female job seekers to complete their applications for a tech job. All eligible applicants for the job were invited to perform an online skill assessment. We randomized whether or not they were offered an incentive of up to $10 for completing the assessment. We find no significant effect of the incentive for female applicants (or male applicants).
Abstract
					We design a survey experiment to investigate the effect of intervention with diversity on preferences for diverse outcomes. First, subjects report their perceptions of the archetypical occupations boss, professor, nurse, and clerk, rating boss/professor as higher status than nurse/clerk. Importantly, while respondents expect overrepresentation of women among nurses and clerks, they expect a relatively equal gender distribution among bosses and professors. We then randomize participants to view either diverse or nondiverse images for each occupation. Diversifying the image sets significantly increases the likelihood of underrepresented individuals being selected in both domains, but correctness of preexisting beliefs only matters in female-typed domains.
Abstract
					Historically Black colleges and universities (HBCUs) play an important role in the postsecondary education of Black students in the United States. Using data on where 1.2 million Black SAT takers send their SAT scores, we examine which students consider attending HBCUs and the common alternatives to HBCUs. Students with average SAT scores are the most likely to consider HBCUs, and students with the highest SAT scores are the least likely. Students who are relatively interested in HBCUs tend to also consider less selective, in-state, public options. However, that relationship is counteracted when the HBCUs under consideration are relatively more selective.
Abstract
					Relying on a panel of more than 600 four-year colleges (including 49 historically Black colleges and universities (HBCUs)), we show that HBCUs as a group outperform other major classes of institutions (for example, flagship state universities) in generating upward economic mobility for their graduates.
Abstract
					In a managed retreat, or "buyout," program, homeowners are offered their property's fair-market value to relocate from a flood-prone area. Using a nationwide sample of federal buyout acquisitions and the universe of US housing transactions over the last two decades, we estimate whether the discount in buyout price compensation, calculated using a hedonic prediction model, depends on a homeowner's race. We provide the first systematic evidence of inequitable compensation in a federal buyout program using nationwide administrative data. Disproportionate compensation, in an attempt to adapt to a warming climate, may further widen the wealth and social mobility gaps.
Abstract
					This paper investigates income and wealth gaps by household incarceration history within and across racial groups using the Blinder-Oaxaca decomposition. We study this in the context of 2017 Baltimore. We find that households exposed to incarceration have lower levels of income and wealth and that these differences are largest for White households. Additionally, we find that Black households without incarceration exposure fare no better in household income than White households with exposure but have higher levels of wealth (driven by lower debt levels). These results highlight the importance of studying the relationship between the criminal legal system and economic inequality.
Abstract
					We evaluate the impact of an intervention aimed at informing high school counselors about the field of economics, with the aim of attracting a more diverse student population into the major. Our study involves 234 Texas high schools that send a large number of students to Texas A&M University. Half of the schools were randomly selected and invited to send a guidance counselor to an in-person informational counselor workshop. While the intervention did not significantly increase applications into the major in the full student population, it significantly increased the economics applications of top-performing women and underrepresented minority students.
Abstract
					In this paper, we document the distribution and determinants of full professorship in the economics profession. Using department-level data from the Committee on the Status of Women in the Economics Profession, we show that while the share of female full professors has increased over time, doctoral departments still only have 2 female full professors on average, and liberal arts departments 1.14. Moreover, 25 percent of doctoral departments and 32 percent of liberal arts departments don't have any female full professors. Using individual-level data from Academic Analytics combined with survival analysis, we find that women are 18 percent less likely to be promoted to full professor, after controlling for institution and individual characteristics.
Abstract
					Seminars are an important channel through which researchers receive feedback on their work and disseminate it. This paper presents descriptive evidence on the representation of female, male, and mixed teams in economics seminars. I use a balanced panel of 270 institutions in the academic years 2018–2020. I find that before COVID-19, only 7.4 percent of presented projects were authored by female teams, 59.2 percent of projects were authored by male teams, and 33.5 percent of projects were authored by mixed teams. The introduction of virtual seminars during the COVID-19 pandemic led to more balanced distribution across team types.
Abstract
					We show that negative effects of parental disability on schooling investments are larger for economically advantaged families. Among children with a veteran father, private school attendance declines with the severity of a father's service-related disability by more when fathers have completed college relative to when fathers have not. Paternal disability also lowers the mobility of young adults, suggesting that reduced educational investment persists into young adulthood. Lost earnings are one mechanism; disability decreases labor supply for all, but foregone earnings are larger for highly educated fathers. Losses are offset by Veterans Affairs transfers for less educated fathers but not for educated fathers.
Abstract
					We present detailed monitoring data across a five-country randomized trial of phone-based targeted tutoring—one of the largest multicountry replication efforts in education to date. We study an approach shown to work in Botswana and replicated in India, Kenya, Nepal, the Philippines, and Uganda. While the existing literature often finds diminishing effects as proof-of-concept studies are replicated and scaled, we find the opposite: implementation fidelity (the degree of targeted educational instruction) improves across replications and over time. This demonstrates that replication is not intractable; rather, equipped with mechanisms to learn from experience, organizational "learning curves" can enable effective replication and scale-up.
Abstract
					Using administrative data on the universe of eighth graders, we study learning losses in Italy between 2021 and 2019 to estimate the effect of schools' closures due to the COVID-19 pandemic. We find an average learning loss of 0.14 SD in math and 0.05 SD in reading. The pandemic widened preexisting gaps by socioeconomic status (SES): students in the bottom quintile of SES learned 0.21 SD less in math and 0.10 SD less in reading. Learning losses for immigrant students in math are larger than those for native ones. We do not find economically significant differences by gender.
Abstract
					In a companion paper (Lichand, Christen and Van Egeraat, 2022), we documented that learning losses in the context of the COVID-19 pandemic were magnified by the fact that most schools neglected students' socio-emotional skills during remote learning. Taking advantage of a cluster randomized control trial that sent high school students or their parents text messages targeting their socio-emotional skills over 2020, we showed that such messages prevented 7.5 percent of learning losses in math and 24 percent of those in Portuguese. In this paper, we study whether the intervention also reduced dropout risk, especially among students at the highest risk of abandoning school.
Abstract
					We examine the emotional and behavioral impacts of a randomized telementoring intervention on Bangladeshi primary school-aged children during COVID-19 school closures. We measured the prevalence of emotional, conduct, hyperactivity/inattention, and peer-relation problems among children twice. We found significant reductions in conduct and hyperactivity problems among the treated one month after the intervention ended. However, these impacts disappeared after one year. We also observed significant deterioration in the mental health problems of all children. These results highlight that remote learning can prevent mental health problems among children in the short term, but sustained support is necessary to effectively address the problems.
Abstract
					We use a field experiment in a large college classroom to study the use of written representations of emotion ("emoticons") as a form of feedback on exams. We find that treatment improved student attendance, quiz scores, homework scores, and test scores. We document heterogeneous impacts based on the type of emoticon received and gender. Improvements were driven by those who received disapproving emoticons but scored above the mean. Female students were responsible for the improved homework and test scores, while men drove improvements in attendance. Both genders improved similarly on quiz scores. We discuss two psychological theories supporting a treatment effect.
Abstract
					We consider the gamification aspect of a technology that delivers small daily tasks to students to analyze how competition motivates engagement. We randomly assigned 400 students into teams of up to 10, who compete by committing to the daily task and then acknowledging their completion later in the day. Using data collected from the leaderboard, we test whether student engagement with respect to competition varies systematically by gender and by the level of anonymity. Not surprisingly, being ranked in the top three is highly motivating. However, among lower-ranked students, male students tend to disengage when usernames are not anonymous.
Abstract
					The literature in pedagogy has shown that having a sense of belonging affects learning. This paper shows the result of a communication experiment in an online environment. For six consecutive terms, the instructor taught Introduction to Statistics. The instructor added a more direct communication strategy during two of those five terms. She used weekly communications that linked course material with events discussed by students previously and a personal message to each student. The intervention resulted in improved learning, measured by better grades, and more enjoyment of the course, measured using student comments in teaching evaluations.
Abstract
					Using data collected over five years for an introductory economics course, this study investigates the relationship between anxiety, test-taking aid, and test performance. The results show that test aid is associated with a 0.21 standard deviation increase in test scores. Although anxiety decreases test performance, accounting for anxiety does not eliminate the significant impact of test aid. The positive impact of test aid has heterogenous effects. Test aids play a moderating role in reducing unwanted stress while maintaining test integrity. Our results suggest that the effect of high anxiety may have implications for a student's academic trajectory.
Abstract
					We study the causal effect of the net price of college on student debt, schooling investment, and parental transfers by exploiting a natural experiment. A large public US university introduced a program to match Pell Grants in academic year 2019–2020. We use a difference-in-difference approach to measure the impact of this policy on the variables of interest and interpret our findings using a simple structural model of human capital investment under credit constraints.
Abstract
					Graduate student debt is the predominant form of financial aid for postbaccalaureate students and represents almost half of outstanding student debt, yet little is known about the effect of publicly funded graduate loans on student outcomes. To fill this gap, we examine the creation of the federal Graduate PLUS Student Loan program, which effectively eliminated loan limits for graduate students. Using a difference-in-difference identification strategy and administrative data on graduate students entering public and nonprofit universities in Texas, we show that access to additional liquidity through Grad PLUS had no effect on underrepresented students' access to high-earnings graduate programs.
Abstract
					We use new administrative data that link detailed information on Canadian student loan recipients with their repayment and income histories from the Canada Student Loans Program, income tax filings, and postsecondary schooling records to measure the extent to which student borrowers adjust loan repayments to insure against income variation. Loan payments are shown to increase in income, more so in early years and for individuals with higher initial debt. We estimate that on average an unexpected $1,000 change in annual income is associated with a $30 change in loan payment. Loan repayments are also used to absorb persistent income variation.
Abstract
					Using a US nationally representative online sample, we measure the level of knowledge on employment nondiscrimination laws. Although Americans are well informed about sex, race, and disability being protected characteristics, only about 71 percent think that sexual orientation is a protected characteristic. Sexual minorities are as uninformed as heterosexual individuals that sexual orientation is legally protected from employment discrimination. Furthermore, sexual minorities living in states that did not previously have statewide employment nondiscrimination protections prior to the 2020 Supreme Court ruling in Bostock v. Clayton County are less likely to think that sexual orientation is a protected characteristic.
Abstract
					This study uses the 2015 US Transgender Survey to test how initiation of hormone replacement therapy (HRT) affects the risk of attempting suicide among transgender individuals. We constructed a retrospective panel and employed a stacked event study design to demonstrate that HRT is associated with a substantially lower risk of suicide attempt. The average treatment effect on the treated is a decrease of 5.7 percentage points in the risk of ever attempting suicide if HRT is started between the ages of 14 and 17, which amounts to a 14.4 percent reduction in the risk of attempting suicide relative to the pretreatment mean.
Abstract
					We study how COVID-19 affected the prevalence, expectations, and attitudes toward remote work using specially designed surveys. The incidence of remote work remains higher than prepandemic levels, and both men and women expect this to persist postpandemic. Workers also report increased preference for remote work as a result of the pandemic. These changes are strongly correlated with individuals' exposure to the pandemic-induced work-from-home shock, indicating that experience with remote work during the pandemic likely shaped expectations and preferences toward WFH. The magnitude of the effects on preferences and expectations are similar across gender, marital status, and presence of children.
Abstract
					We use data from a serological study that experimentally varied financial incentives for participation to detect and characterize selection bias. Participants are from neighborhoods with substantially lower COVID-19 risks. Existing methods to account for the resulting selection bias produce wide bounds or estimates that are inconsistent with the population. One explanation for these inconsistent estimates is that the underlying methods presume a single dimension of unobserved heterogeneity. The data suggest that there are two types of nonparticipants with opposing selection patterns. Allowing for these different types may lead to better accounting for selection bias.
Abstract
					The COVID-19 outbreak had severe adverse impacts on the health and wealth of households in lower-income countries (LICs), and has affected even more severely female-headed households in LICs. Using high-frequency phone surveys in Sierra Leone, we show that female-headed households are likely to rely on cheaper food alternatives (e.g., Cassava) compared to male-headed households and are more food insecure. These effects are more nuanced among the poorest families owning one or no assets. Furthermore, female-headed households had less access to COVID-19 information, were less likely to adopt preventive measures (e.g., masks and social distancing) at the onset of the pandemic, and show greater signs of vaccine hesitancy in the early stages of the COVID-19 vaccine campaign.
Abstract
					Concerns have been raised about the "demise of democracy," possibly accelerated by pandemic-related restrictions. Using a survey experiment involving 8,206 respondents from 5 Western democracies, we find that subjects randomly exposed to information regarding civil liberties infringements undertaken by China and South Korea to contain COVID-19 became less willing to sacrifice rights and more worried about their long-term erosion. However, our treatment did not increase support for democratic procedures more generally despite our prior evidence that pandemic-related health risks diminished such support. These results suggest that the start of the COVID-19 crisis was a particularly vulnerable time for democracies.
Abstract
					European countries experienced a large increase in labor supply due to the influx of Ukrainian refugees after the 2022 Russia invasion of Ukraine. We study its dynamic effects in a spatial model with forward-looking households of different skills, trade, and endogenous capital accumulation. We find that real GDP increases in Europe in the long term, with large distributional effects across countries and skill groups. In the short run, an increase in the supply of labor strains the use of capital structures that takes time to build. Over time, countries that build capital structures increase output, resulting in potential long-run benefits.
Abstract
					We examine the effects of the 1988 Canada-US Free Trade Agreement (FTA) on employment and earnings inequality among low-, medium-, and high-income Canadian workers initially employed in manufacturing. Although the FTA tariff cuts drove large changes in trade flows, we find generally small effects on employment and cumulative earnings during 1989–2004. Workers faced negative effects of import competition and positive effects of access to the US export market, but these effects were largely offset by transitions into other industries and sectors. The effect on earnings inequality was small, with point estimates implying a slight reduction in earnings inequality.
Abstract
					We estimate the responsiveness of net labor migration to regional differences in unemployment rates across the United States since the mid-1970s. Our baseline estimate suggests an elasticity of roughly -0.3. For typical labor force participation ratios, an increase of 100 unemployed workers in an area is associated with net out-migration of roughly 47 workers. Instrumenting for regional unemployment produces even higher estimates. Our estimates are stable over time, inclusive of the Great Recession. The estimates depend crucially on accurate data and accounting for long-term trends in migration and unemployment.
Abstract
					We quantify the commute time savings associated with work from home, drawing on data for 27 countries. The average daily time savings when working from home are 72 minutes in our sample. We estimate that work from home saved about two hours per week per worker in 2021 and 2022, and that it will save about one hour per week per worker after the pandemic ends. Workers allocate 40 percent of their time savings to their jobs and about 11 percent to caregiving activities. People living with children allocate more of their time savings to caregiving.
Abstract
					Starting from over 1.2 billion job postings, we construct and make publicly available a novel dataset on postings advertising work from home (WFH) in 20 countries and 55 occupational categories from January 2019 to September 2022. We document three stylized facts. First, in the average country, WFH surged during the pandemic but declined only marginally as the pandemic receded. Second, across countries, increases in WFH were more pronounced where mobility restrictions were more severe. Third, across occupations, the shift toward WFH was concentrated in occupations where WFH was technically and organizationally feasible even before the pandemic.
Abstract
					We quantify the impact of work from home (WFH) on housing demand by leveraging a unique dataset of online housing sales advertisements in Italy and considering intensity in the adoption of WFH. By exploiting both the time series and the geographical variation in WFH adoption after the outbreak of the COVID-19 pandemic, we estimate that intensive WFH is the main driver of a significant recomposition of housing demand toward larger, single-family properties with outdoor spaces. This suggests that hybrid working arrangements involving a sizable amount of home-office work may have long-lasting consequences on housing markets and the organization of cities.
Abstract
					We compare survey-based measures of work from home (WFH) in the cross section. While the surveys differ in how comprehensively they measure WFH, they are highly correlated in the cross section of US states, suggesting that they will yield similar causal effects. Researchers should carefully consider the trade-off between how comprehensively WFH is measured and measurement error, with the American Community Survey well suited for low levels of aggregation and the Survey of Working Arrangements and Attitudes and Real-Time Population Survey well suited to measuring distinct types of WFH. We also document that the experimental 2020 ACS replicate weights produce errors that are too small.
Abstract
					The shift of working time from the household to the market, or marketization, was one of the most important changes in the US economy. This paper estimates US household production (HP) by product and examines the marketization of these products. I find that most HP products show little marketization despite a decline in HP's importance relative to GDP. Only cooking had significant marketization between 1965 and 2021. The COVID-19 pandemic led to a demarketization of most products, consistent with market options being disrupted.
Abstract
					In this paper, we compare patterns of family care provided to children and to adults, and discuss what these patterns suggest about how individuals make decisions over, and ultimately value, such care. We show that patterns of informal adult care do not resemble patterns of informal childcare along three important dimensions: caregiver age, caregiver education, and the response of caregiving to macroeconomic conditions. The finding that childcare and adult care are economically distinct suggest that policies, like paid family leave, that support caregivers should more carefully consider these differences.
Abstract
					In 2022, childhood immunization in the Sindh province of Pakistan was disrupted by the worst floods in Pakistan's history and by vaccinator strikes. We use weekly data on all vaccinations from 12 of the lowest immunization districts in Sindh, strike timing, and satellite flood data to examine 2.5-month impacts. Despite intensive catchup efforts by the government and the international community, immunizations declined 19 percent more in flooded towns than nonflooded towns postfloods, and 11,500 children missed vaccinations as result of the floods. Immunizations in strike towns were 48 percent lower than in nonstrike towns, with 15,300 lost immunizations over the entire postperiod.
Abstract
					We use data on the universe of COVID-19 vaccines in Sierra Leone to examine the relationship between COVID-19 vaccination take-up and support for the party in power and whether interruptions to vaccine supply reduced take-up of second doses. We find that COVID-19 vaccine take-up is higher in areas that support the ruling party, but this mirrors long-term vaccination patterns and not the politicization of COVID-19 vaccines. People whose second dose was due just before and after a vaccine stockout had similar second take-up rates (around 50 percent)—that is, delayed access to second doses did not deter eventual take-up.
Abstract
					COVID-19 vaccines are widely available in wealthy countries, yet many remain unvaccinated. We report on two studies (United States and France) with millions of Facebook users that tested two strategies central to vaccination outreach: health professionals addressing common concerns and motivating "ambassadors" to encourage vaccination in their social networks. We can reject very small effects of any intervention on new first doses (0.16 pp, United States; 0.021 pp, France), with similar results for second doses and boosters (United States). During the Omicron wave, messaging aimed at the unvaccinated or those tasked with encouraging others did not change vaccination decisions.
Abstract
					Using a laboratory experiment, we investigate the extent to which learning is transferred between related problems in the context of an updating task. The updating principle we study requires updating positively after a positive signal and negatively after a negative signal. In the first environment, most subjects initially fail to satisfy the principle but eventually adjust after feedback. The environment they face subsequently presents the same challenges but with different parameter values. We find weak evidence for transfer learning: only half of the subjects who learn to be consistent with the principle remain so when the parameter values are changed.
Abstract
					Rather than facing an isolated climate change challenge, this paper argues that the
world must confront the Global Energy Challenge (GEC) that requires all countries
to make trade-offs between three often competing and interrelated goals: inexpensive
and reliable energy, clean air, and limiting damages from climate change. This paper
presents seven facts that help illuminate the contours of the GEC and the interactions
between the three goals. It concludes by outlining potential solutions: pricing energy at
its full social cost, investing in technical and policy innovation, improving information
on pollution and climate damages, and treating energy as a private good.
Abstract
					The quality and inequality of US drinking water investments have gained attention after recent environmental disasters in Flint, Michigan, and elsewhere. We compare the targeting of subsidized loans provided through the Safe Drinking Water Act with the targeting of congressional drinking water earmarks ("pork barrel" spending). Earmarks are critiqued for potentially privileging wealthier and politically connected communities. We find that earmarks target Black, Hispanic, and low-income communities, partly due to targeting water systems serving large populations. Earmark and loan targeting differ across all demographics we analyze. Compared to loans, earmarks disproportionately target Hispanic but not Black or low-income communities.
Abstract
					This paper uses tax records linked to administrative Census data and high-resolution measures of air pollution exposure (PM2.5) to study the evolution of the Black-White pollution exposure gap since 1984. We decompose changes in the racial exposure gap into (i) rank-preserving compression of the pollution distribution and (ii) changes stemming from a reordering of Black and White households within the pollution distribution. We find a narrowing of the racial exposure gap that is overwhelmingly driven by rank-preserving changes rather than positional changes. Recently, however, the relative positions of Black and White households in the upper tail of the pollution distribution have converged.
Abstract
					Sea level rise threatens coastal cities around the world. Will it exacerbate inequality in these already unequal places? The rich may adapt by moving to higher ground, bidding up prices and pushing the poor elsewhere. I study the distributional consequences of this spatial sorting with a simple quantitative model and granular data from Jakarta, a flood-prone megacity of 32 million. I find that sea level rise will double inequality in flood exposure.
Abstract
					The Massachusetts Firearms Records Bureau recently published administrative data covering the universe of legal firearm transactions in the state. We use these data to validate state-level background checks as a proxy for firearm transactions and show that historical trends in transactions within Massachusetts align with the rest of the United States. Using auxiliary data from a national survey, we show that the Massachusetts dataset can detect patterns in the demographics of both gun ownership and type of firearm purchased. Our analysis suggests that this dataset is a promising source of information for studying interactions in the market for legal firearms.
Abstract
					Since Becker (1968), economists have modeled crime as resulting from higher returns to criminal activity than legal work. Yet contemporary employment data for people engaged in crime is scarce. We surveyed men at extreme risk of gun violence in Chicago about their work in the formal, informal, and criminal sectors. Noncriminal work is common. Two-thirds of respondents specialize solely in the criminal or noncriminal sectors, both earning about minimum wage at the median. Those who mix across sectors typically earn higher wages. We describe workers by type to demonstrate how better understanding sectoral specialization could inform program design.
Abstract
					This study estimates the moderating impact of economic development on climate-conflict linkages during 1989–2019 in Africa, the world region that in recent decades has experienced the most armed conflict. We build a spatially disaggregated dataset that merges multiple decades of georeferenced data on climate shocks and conflict events with both local- and national-level measures of economic development to help shed light on the relative importance of local opportunity costs versus state capacity. We find that higher national GDP per capita greatly dampens the conflict risk associated with higher temperatures, suggesting that enhanced state capacity is a key factor.
Abstract
					This study investigates how social media data can be used to study shifts in identity, focusing on Ukraine during the Russia-Ukraine war. We analyze VK users' reported language proficiency and the language of tweets and note a significant shift from Russian to Ukrainian during both the early (2014–2022) and later (2022–) phases of the war. Additionally, we observe a positive association at the province level between these language changes and shifts in ethnic identity reported in nationally representative surveys. The findings underscore the effectiveness of social media data in tracking and quantifying shifts in identity.
Abstract
					Low- and middle-income nations host 76 percent of the world's refugees. This study uses original data to explore within-country spatial variability in refugee-hosting responsibilities. We find that hosting responsibilities for the displaced Rohingya people in Bangladesh are allocated in similarly unequal fashion when analyzed at the national, regional, and microregional levels. Refugee camps are placed in socioeconomically disadvantaged communities relative to both Bangladesh as a whole and surrounding areas. Our findings underscore the importance of considering host communities in the coordination of humanitarian responses to refugee crises to prevent economic hardship and political backlash.
Abstract
					This study uses historical conflict and weather data for the period 1400–1900 CE to investigate the long-run effects of climate change on political instability in a context that suffered extensive cooling. The results show that temperature changes have little effect on conflict if they are isolated events but that consecutive periods of cooling are associated with increased conflict. This is consistent with the conventional wisdom that societies and economies are able to adapt to a certain amount of environmental change. But if climate change is prolonged, then the disruptions they cause can cumulate and lead to political instability.
Abstract
					A slanted-L curve is well suited to represent the nonlinearity of the celebrated Phillips curve. We show this using cross-country data of major industrialized economies since 2009, including the inflationary surge of the 2020s. At high unemployment rates, an increase in demand reduces unemployment without creating strong inflationary pressures. Meanwhile, supply shocks have a muted effect. At sufficiently low unemployment, there is a labor shortage, so that the economy is at full capacity. Then, higher demand is inflationary and supply shocks are amplified. We derive a model of a slanted-L curve.
Abstract
					We document the real-time forecasting performance for output and inflation of the New York Fed dynamic stochastic general equilibrium (DSGE) model since 2011. We find the DSGE's accuracy to be comparable to that of private forecasters before COVID but somewhat worse thereafter.
Abstract
					Is postwar data enough to estimate the permanent component of inflation? We find that it is not for episodes of sudden and large inflation spikes like the one observed after the COVID-19 pandemic because such episodes are rare in the prewar sample (the inflation of the 1980s took 15 years to develop). However, prewar data is rich in sudden inflation spikes, thus providing useful information. Estimates using data over the period 1900–2022 predict that the permanent component of inflation increased by only 1.3 percentage points from 2019–2022 but by 5.0 percentage points when estimated using 1955–2022 data.
Abstract
					Inflation has risen sharply in many countries since the COVID-19 outbreak, and economists have debated the underlying causes. In this paper, we examine the drivers of the global import price inflation, which peaked at approximately 11 percent a year. We find that a common global component closely tracks movements in aggregate US import prices until late 2022. Afterward, idiosyncratic US demand shocks started to dominate.
Abstract
					We study the impact of demand and supply factors on bottlenecks and inflation during the COVID-19 pandemic. Initial policy interventions, from lockdowns to fiscal stimuli, triggered shifts in consumer spending and supply chain disruptions. The reopening of economies normalized consumption patterns, but attributing bottlenecks to specific factors remains challenging due to diverse policy responses. This paper empirically integrates fiscal spending, mobility measures, and supply constraints to analyze interconnected factors influencing bottlenecks and inflation internationally. We find an important role played by fiscal shocks and the international propagation of demand and supply forces in shaping bottlenecks and inflation dynamics.
Abstract
					During the recovery from the COVID-19 pandemic, international shipping and logistics capacity was strained, limiting the quantity of imports. We investigate the impact of an import constraint on inflation, following an increase in domestic demand. Whether the binding import constraint raises inflation depends on how it affects trade intermediation costs. If the binding constraint raises trade costs, then import price inflation also increases. In this case, however, foreign producer price inflation falls and import quantities rise more for inputs than final goods. Both these model results appear counterfactual, which suggests that import constraints may not explain observed import price inflation.
Abstract
					This paper uses input-output relationships across highly disaggregated products to establish two empirical regularities with bilateral trade data. First, countries are likely to have revealed comparative advantage (RCA) in a product if they also have RCA in products that are upstream or downstream to that product. Second, the RCA of a product improves over time if the country experiences export demand shocks to its inputs or outputs. This suggests that being integrated as suppliers into the global production network can benefit countries by improving their capabilities across different stages of production.
Abstract
					This paper employs US census microdata to construct establishment-level measures of global value chains (GVCs) and then assesses aggregation bias—the bias occurring when an entire industry is essentially treated as a single establishment. Our establishment-level measures indicate little slowdown in GVC expansion between 2002 and 2012. Related, the aggregation bias is negative, and it increased during this period. A decomposition reveals that most of the increase is from within establishments with high export and import intensities. Our results suggest that granular GVC measures will provide further understanding about how firms and economies adjust to shocks.
Abstract
					We study the extent to which the perceived cost of losing the exorbitant privilege the United States holds in global safe asset markets sustains its public debt safety. Our findings indicate that losing this special status in the event of a default significantly augments the debt capacity for the United States. Debt levels would be up to 30 percent lower if the United States did not have this special status. Most of this extra debt capacity arises from the loss of convenience yields on Treasuries, which makes debt more expensive following its loss, providing strong incentives to repay debt.
Abstract
					China's lending to developing nations has surged since the mid–2000s, making it these nations' largest official creditor. Contracts frequently feature unique terms, indicating China's substantial privileges as a lender. However, other lenders are also involved. We examine how these lending relationships with China affect access to credit from international bondholders. Combining data on external marketable debt and prices with Chinese lending data, we find that Chinese funding events decrease marketable debt issuance and sovereign yields. Conversely, debt restructuring with China leads to higher spreads. These findings underscore the impact of China's lending on international credit access.
Abstract
					We study the international transmission of US monetary policy shocks and a strong US dollar. We show that monetary tightening is linked to a higher risk premium, only in emerging markets, measured by deviations from uncovered interest parity. An appreciation of the US dollar, on the other hand, does not lead to higher risk premia anywhere, even though countries' currencies depreciate vis-à-vis the dollar. Our interpretation is that monetary policy shocks are a better proxy for global financial conditions than the exchange rate movements that may be capturing more fundamental shocks.
Abstract
					We find an economically and statistically significant effect of race-based police violence on home ownership and retirement savings. Using restricted-use Panel Study of Income Dynamics data, we show that Black individuals exposed to the fatality of a Black person caused by or involving police subsequently experience decreased homeownership, home equity, and defined contribution pension participation relative to non-Black individuals in the same zip code. Our findings suggest that race-based violence affects not only those immediately involved but also entire racial communities in the vicinity. These decreases in illiquid assets imply negative long-term consequences for Black households' wealth accumulation.
Abstract
					The racial wealth gap in the United States is the object of much misrepresentation and misunderstanding. Our paper is intended to provide a corrective. We will address how the mainstream economic view of the drivers of racial disparities in wealth is a human capital view that promotes anti-Black and personal responsibility narratives while ignoring the significance of the racially uneven transmission of resources across generations. It also fails to acknowledge the cumulative impact of US racial history on present wealth gaps.
Abstract
					This paper analyzes the effects of high economic uncertainty on racial and gender behavior in payment methods. Using US consumer transaction-level data, we find that consumers alter their payment behavior patterns in periods of high economic uncertainty by moving away from costly and risky payment methods with high interest rates, such as credit cards. We find that females reduce their cash usage but increase their credit card usage relative to males, thus exposing themselves to higher financial vulnerability. We find no major differences in payment behavior between Blacks and Whites.
Abstract
					This paper evaluates racial inequalities in health-care affordability between high-deductible and conventional insurance. Using the 2011–2017 National Health Interview Survey, the study finds that Blacks in high-deductible plans are not disproportionately higher income, nor more engaged in other savings vehicles, unlike their White counterparts, indicating they may be income constrained rather than desiring to partially self-insure. Furthermore, conditional on income, wealth explained more of the racial disparity in health-care access among high-deductible enrollees than conventional enrollees, consistent with the hypothesis that benefit designs relying on households' cash reserves would yield greater disparities due to the magnitude of racial inequalities in assets.
Abstract
					Does the measurement of the racial wealth gap shift depending on the model, method, and dataset used? We contrast the traditional mean Oaxaca-Blinder decomposition with the distributional Recentered Influence Function (RIF) methods. The untransformed, logarithm-transformed, and inverse hyperbolic sine-transformed versions in both the Survey of Consumer Finances and Panel Study of Income Dynamics datasets exhibit similarities. The Oaxaca-Blinder (mean) decomposition highlights that receiving an inheritance explains a larger portion of the racial wealth gap than educational attainment. Conversely, the RIF method at the median suggests that educational attainment accounts for more of the wealth gap than inheritance receipt.
Abstract
					This paper investigates the proximate causes of excessively cyclical employment growth and persistently high unemployment among Black workers, relative to White workers. Using data from the Quarterly Workforce Indicators and Job-to-Job Flows, we find that the concentration of Black workers in highly cyclical industries cannot account for the excess cyclicality; rather, Black employment tends to be more volatile regardless of industry. The high level and excessive cyclicality of unemployment among Blacks compared to Whites can be traced to lower job finding rates overall and higher and more cyclical separation rates in most industries.
Abstract
					Using data from the largest online job portal in Nigeria, we document (i) gender differences in salary offers for jobs and (ii) the response of (i) to recessions. Jobs in industries where the number of job applicants skews female offer lower starting salaries than jobs in industries where applicants skews male. During Nigeria's 2016 recession, applications to jobs in industries that skew female fell, and salary offers rose. In contrast, applications to jobs in industries that skew male rose, and salary offers fell. In accordance with this relative shift in applications, in 2016 the salary-offer gap almost disappears.
Abstract
					We study racial disparities in the US mortgage market. Using new data from Hurtado and Sakong (2024), we present three findings. First, we document access disparities between minority and otherwise-identical White borrowers even within the same bank and with the same loan officer. In contrast, cost disparities are nearly zero. Second, the use of automated underwriting algorithms is associated with smaller access disparities but slightly larger cost disparities. Third, individual factors such as loan officers' race and whether borrowers' race is observed at application do not seem to matter much.
Abstract
					Using a variation of a correspondence audit study, we show that even after controlling for how prepared a candidate seems, White males are more likely to be recommended for AP Calculus. In this setting, name-blind review does not improve the likelihood of recommendation for any race/gender group and can actually be harmful rather than simply bias reducing.
Abstract
					We use data from the Bureau of Indian Affairs annual reports between 1912 and 1927 to examine the wealth of Indigenous nations in the contiguous United States during the early twentieth century. Our estimates reveal considerable heterogeneity in wealth holdings across Indigenous nations. In 1912, the average real per capita wealth of Indigenous nations was high relative to other groups, but it declined systematically throughout the period of our study. Given the available contemporary evidence, our estimates imply a dramatic widening of the wealth gap over the last century.
Abstract
					We merge the longitudinally linked historical US Census records with data on lynchings of Hispanics in Texas to investigate the impacts of historical lynchings of ethnic Mexicans in Texas on US-born Mexican Americans. Using variation in lynching incidents across counties over time, we explore the impacts of local exposure to lynchings during childhood on long-run outcomes such as earnings, education, and home ownership of adults in 1940. Our findings are suggestive of small, negative impacts, but we caution that more research in this area is needed for a more robust interpretation of the results.
Abstract
					Using Longitudinal Employer-Household Dynamics data, we demonstrate several facts that are not consistent with the "spatial mismatch" hypothesis that residential segregation and uneven distribution of jobs limit Black workers' opportunities. We show that (a) there is no Black-White gap in the firm premium component of wages in an Abowd-Kramarz-Margolis wage decomposition; (b) there are both more jobs and more good jobs within commuting distance of Black than White workers; and (c) Black workers' commutes are shorter. We conclude that geographic proximity to good jobs is not a major source of racial earnings gaps in major US cities today.
Abstract
					Using the EconLit dissertation database and large-scale algorithmic methods that identify author demographics from names, we investigate the connection between the gender of economics dissertators and dissertation topics. Despite stagnation in the share of women among economics PhDs in recent years, there has been a remarkable rise in gender-related dissertations in economics over time and in many subfields. Women economists are significantly more likely to write gender-related dissertations and bring gender-related topics into a wide range of fields within economics. Men in economics have also substantially increased their interest in gender-related topics.
Abstract
					We study labor mobility among academic economists in the United States. Analyzing CV data from over 6,000 economists at Research 1 institutions, we document that female assistant and associate professors are 8 percentage points less likely to move with promotion than their male counterparts. Women are also more likely than men to relocate to lower-ranked institutions. Event study graphs reveal that men working in departments that receive a new faculty member see their publication output increase by more than twice as much as that of women in these departments. Our findings highlight significant gender differences in who moves and what happens after.
Abstract
					Women continue to be underrepresented in the field of economics, especially among permanent faculty. As parenthood is an important driver of gender inequality in the labor market, we study the impact of children on the academic careers of economists. We find no evidence of delayed or reduced fertility among researchers. Event study estimates reveal that both men's and women's career trajectories are affected by parenthood and face increasing attrition from universities. Men move into the broader research sector, while women leave research completely. We also find a gender gap in the promotion to tenured faculty in the years following parenthood.
Abstract
					Youth unemployment and gender gaps in labor market outcomes are key policy challenges across developing countries. Young job seekers may struggle to find jobs because of their biased beliefs and unrealistic aspirations about the labor market. We study whether exposure to the COVID-19 pandemic influenced the labor market aspirations and expectations of female vocational students in Haryana, India. We find that exposure to the pandemic lowered young women's wage aspirations and made them more realistic, especially in rural areas. A potential mechanism for these effects is the decline in rural women's willingness to migrate for work due to the pandemic.
Abstract
					No: it is at least as large at bottom percentiles of the earnings distribution. Conditional quantile regressions reveal that while the gap at top percentiles is largest among the most educated, the gap at bottom percentiles is largest among the least educated. Gender differences in work hours create more pay inequality among the least educated than they do among the most educated. The pay gap has declined throughout the distribution since 2006, but it declined more for the most educated women. Current economics-of-gender research focuses heavily on the top; equal emphasis should be placed on gender inequality among non-college-educated workers.
Abstract
					Globally, women remain underrepresented in STEM. Our lab-in-the-field study delves into parental influence on adolescents' perceptions of scientific versus humanistic aptitude. We find that thinking about parental recommendation affects students' beliefs on their comparative advantage in a gender-stereotypical way. Girls are 23 percent less likely to choose math when they think about their mothers' recommendation before selecting their field. The paper underscores the critical role that parents play in shaping gender-specific beliefs about academic strengths, highlighting potential avenues for fostering diversity in STEM.
Abstract
					There is a large gender wage gap among college graduates. This gender gap could be partially driven by differences in college major and prior skills. We use Swedish register data to study how much of the gender gap can be explained by differences in majors, skills, and skill prices. College majors explain 60 percent of the gender wage gap, but large gaps remain within majors. We find that within-major wage gaps are driven by neither differences in multidimensional skills nor returns to these skills. In fact, women are positively selected in terms of college preparation and skills in almost every major.
Abstract
					This paper examines the impact on skilled labor migration to the United States of same-sex marriage legalization in European countries and US federal recognition of foreign same-sex marriages. Analyzing US Department of Homeland Security data, we find that European legalization decreased skilled labor admissions to the United States by 22 percent, most notably after six years. However, US recognition of foreign same-sex marriages mitigated this effect post–2013, indicating that such legalizations facilitate skilled labor movement between nations.
Abstract
					LGBTQ+ adults had a lower homeownership rate (53 percent) than non-LGBTQ+ adults (72.5 percent). Looking at LGBTQ+ subgroups by sexual orientation and gender identity revealed important nuances. Transgender people and bisexual people had the lowest homeownership rates. Lesbian cis women had a higher rate of homeownership than gay cis men, whereas in other sexual orientation groups cis men had higher rates than cis women. Transgender people of all sexual orientations, except straight, were between 6 and 12 percentage points less likely to own a home than straight cis men, and lesbian cis women were 4 percentage points less likely.
Abstract
					This study examines the relationship between gender identity milestones, family support, and exposure to gender-affirming or gender-denying practices. Leveraging a retrospective panel from the 2015 US Transgender Survey, we compare changes in exposure to hormone replacement therapy (HRT) and conversion therapy among transgender youth who initiate gender identity milestones and those who initiate a year later—stratified by level of family support. Results indicate that transgender youth initiating milestones in supportive families have increased access to HRT and are shielded from conversion therapy, whereas children in unsupportive families have limited access to HRT and are more exposed to conversion therapy.
Abstract
					Using microdata from the censuses of eight countries in Latin America (Argentina, Brazil, Chile, Colombia, Guatemala, Mexico, Peru, and Uruguay), this paper describes matching patterns by age, ethnicity, and education among same-sex and different-sex couples. It shows that same-sex couples are more diverse than different-sex couples in terms of age, ethnicity, and education, although the differences are not large or statistically significant for ethnicity and education in all countries. It also reports notable differences between male and female same-sex couples, particularly in age and education matching.
Abstract
					I study how universities changed the specificity of their sexual harassment policies around #MeToo. I observe a trend toward increasing policy specificity after #MeToo, particularly in private universities, those with publicized harassment cases, or universities led by presidents from male-dominated academic backgrounds. Additionally, I present suggestive evidence of a link between the hiring of junior female faculty and the adoption of more specific policies in environments where the composition of senior faculty is more male dominated after #MeToo. Overall, my results indicate that universities prioritize clearer guidance for behavior through narrower policies over retaining flexibility with broader policies post-#MeToo.
Abstract
					We examine trends in author representation, research topics, and impact of citations to articles in the American Economic Review and what was formerly its Papers and Proceedings (P&P). Over what we refer to as the P&P expansion period (2008–2017), we see a significant shift toward greater diversity of P&P authors with respect to gender, institutions, and the range of topics covered. Importantly, the rise in inclusivity during this time period occurred without any loss of impact, with P&P article citations actually rising relative to regular-issue articles. Thus, our analysis suggests that there is no trade-off between impact and inclusion.
Abstract
					This paper examines racial disparities in economic publishing using bibliometric data from over 200 economic journals. We find notable differences in authorship between White and non-White authors, with Black, Hispanic, and Asian economists significantly underrepresented in comparison to their share of the overall population. While the publication of non-White economists has increased over the last three decades, the average number of Top 5 journal publications by non-White economists is 25 to 50 percent lower than that of White economists in comparable positions. These disparities highlight the need for measures to enhance knowledge diversity within the economics profession.
Abstract
					For Canada, the United Kingdom, and the United States, we illuminate the landscape for a relatively new and evolving role: full-time, teaching-track economists who work in the same departments as research-track economists, but with a greater emphasis on teaching. We use in-depth interviews and a large-scale survey. We employ a mixed-methods approach. A cohesive, cross-country, multi-institution comparison enables learning from a variety of contexts. Our findings inform decision-making processes, initiate conversations among multiple constituents, generate ideas, raise salient questions, and identify relative strengths and weaknesses of different teaching-track models.
Abstract
					This paper (alongside the other papers in this session) reports the findings from a mixed-methods study of teaching-track faculty in the United States, the United Kingdom, and Canada. Our approach combines a qualitative analysis of interviews with a quantitative analysis of survey responses. A key finding is that US teaching-track faculty are much less likely to have the possibility of job security through tenure relative to their counterparts in Canada and the United Kingdom. And while US teaching-track faculty have multifaceted jobs that might include research, service, and administrative duties, their roles are more teaching focused than UK teaching-track faculty.
Abstract
					We find that over two-thirds of economics departments in large Canadian universities have full-time teaching-track faculty positions that parallel traditional research-track positions but with a heavier teaching focus. Teaching-track economists approach one-sixth of the faculty complement—a substantial shift in resource allocations since 2000. This paper—a companion to Arico et al. (2024)—uses a mixed-methods approach with interview and survey data to draw on the firsthand experience of teaching-track economists. Pioneers helped craft a Canadian model that allows economics departments to attract passionate educators, and the teaching track continues to evolve.
Abstract
					In this companion paper to Arico et al (2024), we use a mixed-methods approach to characterize teaching-track faculty positions in the United Kingdom. We find these roles are more prevalent in the United Kingdom compared to the United States or Canada, and notably more oriented toward scholarship and administration duties. A high value is placed by role holders on the existence of formal networks that connect teaching-track economists across universities. We provide some context to help understand these findings, which will be relevant for academics considering these roles as well as department and university leaders.
Abstract
					This paper documents three new stylized facts showing that truckers in Colombia frequently choose to make complex chains of shipments in a single trip before returning home. It then provides a new model of optimal trucker trip-chaining with a general geography that is consistent with these facts.
Abstract
					This paper compares the affordability of owner-occupied housing across US cities. We apply a new method for imputing the rental value of owner-occupied housing developed in Diamond and Diamond (2024) that accounts for unobserved house quality. On average, the rental value of owner-occupied housing is 3.2 percent above that implied by standard hedonic methods. Hedonic methods overestimate rental value of owner-occupied housing in the most regulated cities and sharply underestimate it in the least regulated cities. We provide suggestive evidence that this heterogeneity reflects misallocation, where high-quality housing stock cannot be built in the most desirable parts of regulated cities.
Abstract
					We study how corporate tax incidence on worker earnings varies across worker characteristics: gender, age, and employment tenure. To do so, we examine effects of the corporate tax cuts introduced by the Tax Cuts and Jobs Act (TCJA), using data from federal tax records and a difference-in-differences empirical design. We find no systematic differential effects by gender but find that TCJA resulted in larger earnings gaps for older workers and long-tenured workers. These gaps become larger towards the top of the within-firm earnings distribution.
Abstract
					We analyze the incidence of a linear corporate tax using a simple and portable competitive general equilibrium model in which capital owners choose to invest either in domestic production or a foreign investment opportunity and workers make extensive margin labor supply decisions. Our analysis explores the effect of corporate taxation on wages, employment, domestic profits, and domestic investment. Analytical results and numerical simulations generate insights in line with recent empirical evidence on corporate tax incidence: the burden of the corporate tax is shared between workers and firms, with larger responses among more capital-intensive firms.
Abstract
					This paper estimates state corporate tax incidence using new data and methods for estimating the effects on profits. Extending Suárez Serrato and Zidar (2016), we develop two identification approaches that use the effects on incumbent firm labor demand and local productivity. We estimate these effects using data from census, show how they identify parameters, and provide incidence estimates using reduced-form and structural approaches. Across these approaches, we find that owners bear a substantial portion of incidence. Our central estimate is that firm owners bear half of the incidence, while workers and landowners bear 25–40 percent and 10–15 percent, respectively.
Abstract
					This study examines a 2014 policy change in the Netherlands that simplified the process to legally transition gender. Administrative data for 2006–2022 indicate that there was a 725 percent increase in transitions after the policy change, suggesting that legal gender transitions are elastic to costs and barriers. The policy change was followed by a ten-year reduction in the average age at transition and a reduction in the use of gender-affirming care in the three years prior to transitioning. This research sheds light on how policy changes can influence decisions related to gender transitioning and the use of gender-affirming care.
Abstract
					This paper examines how delaying the age of school tracking affects long-term health behaviors and access to preventive care. I exploit a reform of the French middle school system, which delayed the placement of students into vocational and academic education by two years. Tracking was mostly replaced by grouping students into achievement-based classrooms. I find that the reform has no significant effects on health behaviors that are associated with increased mortality, such as smoking, drinking alcohol, and obesity. It does, however, increase the likelihood of getting on-time preventive screening for chronic illnesses, such as cholesterol and glycemic index tests.
Abstract
					We study the effect of the first wave of COVID-19 and the accompanying containment measures on fertility in Spain. We use earlier years to predict births in the absence of the pandemic and then compare our prediction to actual births. We document a large fall in births in December 2020 and January 2021 and a complete catch-up during the rest of 2021. The fall in fertility was moderate among native women, with a substantial rebound and a positive net effect of 5% by the end of 2021, while the decline in births among foreign women started early and was persistent.
Abstract
					This paper estimates the effects of fatal school shootings on youth psychotropic drug use over the subsequent five and a half years. Using an event study approach that compares trends in drugs prescribed by providers practicing close to a school shooting relative to those practicing slightly farther away, we find that fatal school shootings lead to large increases in youth psychotropic drug use that persist for years after the event. These effects are driven primarily by increases in prescriptions for antidepressants and antipsychotics and are observed among both youths who were previously taking psychotropic medication and those who were not.
Abstract
					We use data on all prescriptions filled at US retail pharmacies from 2006 to 2018 to examine deviations from best practice in prescribing psychiatric medications to children. The results demonstrate the importance of spillovers from other doctors in the same area. However, individual doctor fixed effects remain extremely important. We also show that the practice styles of doctors who graduated in the same year from schools of the same rank evolve in a similar way across the country. Psychiatrists are less affected by area-level prescribing than general practitioners, suggesting that specific training can reduce spillovers in questionable prescribing practices.
Abstract
					We study the impacts of a prenatal and infancy home visiting program targeting disadvantaged families on mental health outcomes, assessed through diagnostic interviews. The program significantly reduced the prevalence of mental health conditions for both mothers and children, measured at primary-school age, and broke the intergenerational association of these conditions. The impacts are predominantly associated with a particular delivery model, wherein a single home visitor interacts with the family, as opposed to a model involving two home visitors.
Abstract
					In this paper, we investigate the association between a battery of mental health measures and experienced morbidity and mortality due to COVID-19, worry about disease risk, experienced economic shocks, and economic uncertainty about the future. We find that an environment of heightened economic uncertainty might impact mental health above and beyond the effects of realized shocks. A 1 standard deviation increase in economic uncertainty is associated with a 0.223 standard deviation decrease in mental health. This association is strongest among women who were depressed at baseline. We also find that current uncertainty is associated with future economic shocks.
Abstract
					This paper examines the correlations between socioeconomic status, economic shocks, and depression, and how these vary by gender, in a sample of adults from India. Poverty and the exposure to negative shocks are both associated with depression. However, the frequency of negative shocks varies only slightly by socioeconomic status and gender. Instead, poor people and women appear to be more vulnerable to negative shocks. These patterns suggest that social protection programs may foster mental health for these groups and reduce mental health disparities.
Abstract
					This paper provides the first estimate of the economic cost borne by Indian individuals living with dementia and their families based on nationally and state-wise representative data from the Longitudinal Aging Study in India (LASI). We found that the annual household cost attributable to dementia was $571. This is a significant figure, equivalent to 20 percent of annual healthcare spending by the Indian government. Our results identify important differences in cost components relative to high-income countries, emphasizing the need for culturally tailored interventions to support people living with the condition and their families in the Indian context.
Abstract
					We estimate the short-run effect of air pollution on mental illness. Using the China Family Panel Studies covering 12,615 urban residents during 2014–2015, we find a significantly positive effect of air pollution—instrumented by thermal inversions—on mental illness measured by the Kessler Psychological Distress Scale. Specifically, a 1 SD (18.04 μg/m3) increase in PM2.5 concentrations over a month increases the probability of having a score value associated with severe mental illness by 7.58 percentage points, or 0.37 SD. We find suggestive evidence that indirect channels—like reduced exercise and physical health—play a role in the effect.
Abstract
					We leverage recent income support reforms for families with children in Canada to investigate the impact of child benefits on child health and educational outcomes. Using administrative school data from British Columbia linked to parents' tax files, we find evidence that increased family benefit generosity improved children's mental health, but little evidence of any change in test scores from standardized exams. Our results suggest that most of the mental health effect is concentrated among girls and that relative improvements in mental health were larger among children in higher-income families.
Abstract
					In this analysis, we examine what types of households migrate to American Indian reservation lands after the start of casino operations using longitudinal household data for 1989–2017. We find heterogeneous effects on migration by households of different types. American Indians who are single parents are significantly more likely to move to reservation lands after gaming operations commence. No significant changes in mobility were found among married households with children. These results suggest that pull factors may also affect how households decide to relocate when there are changes to economic opportunities and other community or social amenities.
Abstract
					The Michigan Contraceptive Access, Research, and Evaluation Study (M-CARES) is a randomized control trial that examines how financial constraints affect the choice of contraceptives among uninsured individuals. Although all M-CARES participants are highly financially constrained, these constraints are more binding in some subgroups. Black women, women with less than a high school degree, and women with incomes above 250 percent of the federal poverty line are less financially constrained, whereas married women and those with three or more children are more financially constrained. A mediation analysis shows that attitudes and beliefs about contraception do not explain this heterogeneity across groups.
Abstract
					Extended family members can help women with childcare. Using data from 32 sub-Saharan African countries, we find that the prevalence of nuclear families relative to extended families is increasing over time. The overall share of nuclear families is 56 percent and is higher in rural areas. We then use detailed time-use data on childcare provision from 110 rural villages in the Democratic Republic of the Congo. We find that while women do receive childcare assistance from their extended family, they provide 84 percent of childcare hours. These results highlight the need for formal childcare provision, particularly in rural areas.
Abstract
					What determines childcare center use for low-income urban households? And how does subsidizing provision change access to childcare services? We study these questions using data from a randomized evaluation that subsidized childcare center use for women participating in a public works program in Burkina Faso. One-quarter of eligible women use these childcare services, tripling childcare center use for zero- to six-year-olds in our sample. Household wealth significantly predicts childcare center use. However, the public works childcare centers increased access for disadvantaged households and young children. Women employed as childcare providers were also more likely to use the childcare centers.
Abstract
					Shortly before the onset of the COVID-19 pandemic, three-to-five-year-old children in Uganda were randomly offered a subsidy to attend full-day preschool for one year. A second treatment group received cash transfers that were at least as large as the cost of the preschool subsidy provided, while a third group received both. Children who attended preschool prior to the pandemic have better anthropometric outcomes three years later. We do not find persistent effects on their learning outcomes. Effects of cash transfers on child development are similar to those of the preschool subsidy.
Abstract
					Transitional kindergarten (TK) is a relatively recent entrant into the US early education landscape, combining features of public pre-K and regular kindergarten. We provide the first estimates of the impact of Michigan's TK program on third-grade test scores. Using an augmented regression discontinuity design, we find that TK improves third-grade test scores by 0.29 (math) and 0.19 (English language arts) standard deviations relative to a counterfactual that includes other formal and informal early learning options. These impacts are notably large relative to the prior pre-K literature.
Abstract
					We investigate enrollment in a mentoring program aimed at promoting transition to tertiary education for high school students. Females exhibit both higher initial interest and application completion, while immigrants and financially constrained students initially express higher interest but ultimately are not more likely to apply. Survey results highlight a common preference for shared academic interests, but variations emerge: females prefer same-gender mentors, immigrants value shared cultural traits, and financially constrained individuals lean toward mentors from the same municipality. This suggests that programs targeting underrepresented students should be aware of potential barriers to take-up and promote recruiting mentors with similar background.
Abstract
					Centralized admissions are an integral part of parental school choice programs. Most districts use a version of the deferred acceptance algorithm to assign applicants to schools. Centralized admissions produce data with quasi-experimental variation in student assignment that is integral in program evaluation. Recent developments in research design consider the basic version of the deferred acceptance algorithm. However, most districts adapt advanced versions of the deferred acceptance algorithm to implement their diversity policy in admissions, such as favoring applicants from disadvantaged backgrounds in lottery tie-breaking. We develop research design for data from the deferred acceptance algorithm with weighted lotteries.
Abstract
					Prior research has shown that most educational interventions boost student outcomes to a greater extent when delivered in person as opposed to online. However, we know little about whether this is true for enrichment programs targeted to highly motivated populations. By using a randomized controlled trial to study a suite of such programs intended to increase diversity in the STEM pipeline, we reveal that all experiences increase college six-year graduation, especially from competitive universities, but increases in STEM degree production come only from in-person experiences.
Abstract
					This study leverages the rollout of restorative practices (RP) within Chicago Public Schools to investigate whether younger siblings in elementary school who are not directly exposed to RP are affected by their older siblings' RP exposure in high school. We find suggestive evidence that younger siblings' absent days decline in response to indirect RP exposure. In contrast, we do not find any evidence that indirect exposure affects perceived behavior or academic outcomes. Our analysis is intended to provide a useful data point for future work that more comprehensively assesses the scope of spillover effects associated with noncognitive skill development.
Abstract
					We provide the first evidence on the effect of teacher generation on student absences. Using administrative matched student-teacher data, we find that Millennial teachers are more effective at reducing absences compared to teachers from earlier generations. This effect is heterogeneous across Black and White students, with Black students deriving a larger benefit from assignment to a Millennial teacher. Although both Black and White Millennial teachers are more effective at reducing student absences than Baby Boomer teachers, the race-specific improvement of Millennial teachers is driven by White teachers.
Abstract
					This paper investigates potential disparities in how teachers perceive academic achievement between English Learner (EL) students and their non-EL counterparts. Using data on elementary and middle school students in North Carolina, I compare teachers' academic assessments of EL students to those of non-EL students in the same class with the same standardized-test-based achievement. Results reveal that teachers hold more negative perceptions of achievement for EL students compared to academically comparable non-EL peers. These results emphasize the added difficulties experienced by EL students in academic settings, compounding the challenges they already encounter from language barriers.
Abstract
					Using dissertation research topics found in the EconLit database and large-scale algorithmic methods that identify author demographics based on names, we explore the link between race and ethnicity and fields of economic research. We find that underrepresented racial and ethnic minority (URM) researchers are more likely to write dissertations in some unexpected subfields of economics but limited evidence that they are more likely to write dissertations on racial topics once we include basic controls. These descriptive results may be due to limitations in the data, intrinsic motivations, or external constraints.
Abstract
					The Biden-Harris Administration released a plan to cancel federal student loans for 43 million borrowers on August 24, 2022. While the Supreme Court struck down the Biden-Harris student debt relief plan on June 30, 2023, the White House is now planning to use the Higher Education Act of 1965, a federal law that governs the student loan program, to bring about relief for student borrowers. This article estimates the potential impact of broad-based student debt relief on racial and ethnic wealth gaps. On average, federal student debt potentially eligible for relief explains 3 percent of the White-Black wealth gaps, suggesting that broad-based student debt relief could significantly mitigate racial wealth inequities.
Abstract
					We study the heterogenous impact of monetary policy, through high-frequency identified shocks, across demographic and income groups. Our evidence shows significant heterogeneity in the monetary transmission across income groups, while significant differences across demographics emerge only for individuals whose income is below the median. We then build a model with idiosyncratic risk and occupational choices that provides a rationale for the channels we uncover: with uninsurable risk, low earners experience a larger decline in earnings, which reduces their likelihood of participating in the labor market and moving across occupations.
Abstract
					Progressive income taxes distort hiring and wages when firms have labor market power. We characterize this novel monopsony cost of progressivity in a simple monopsony economy and derive efficiency wedges that depend on progressivity. A simple quantification of these wedges points to the possibility that the monopsony cost may be of similar magnitudes to redistribution and insurance benefits.
Abstract
					We use a heterogeneous agent New Keynesian model with a frictional labor market featuring on-the-job-search to study how job switching affects consumption decisions for individuals with different wealth levels. We find that an increased job switching rate, driven by an exogenous shift in employed individuals' job search efficiency—acting as a positive future income shock—results in a larger decline in current demand for the wealth rich relative to the wealth poor. This larger consumption reduction for the wealth rich is due to the equilibrium decline in their financial wealth.
Abstract
					We combine a high-frequency survey on job search effort with administrative data on caseworker interactions from the German unemployment insurance system to estimate how the dynamics of search effort respond to caseworker meetings and vacancy referrals. Meetings alone do not increase individuals' search time beyond a mechanical meeting-day effect; however, we find suggestive evidence that they do when combined with a formal contract on job search obligations. Referrals lead to a modest increase in effort over the three weeks following the event. Our findings leave room for caseworkers affecting employment outcomes through other channels, for example, by altering search effectiveness.
Abstract
					This paper analyses how risk profiling is used to assign unemployed job seekers to job search counseling in Flanders, Belgium. We compare algorithmic selection to self-selection and selection by job search counselors. We discuss practical challenges for the implementation of risk profiling and highlight avenues for further research. We find that algorithmic assignment is used for only a small fraction of the sample and that job search counselors appear to have valuable private information on job seekers' reemployment prospects beyond what is captured by the algorithmic risk score.
Abstract
					We analyze the effects of a job search assistance (JSA) program for the long-term unemployed. JSA increases employment in the first year after assignment by about 4 percentage points. However, averaged over five years, JSA decreases employment, albeit insignificantly so. JSA increases job finding chances early on, but two to four years after it starts, job seekers assigned to JSA are 6 percentage points less likely to have a job compared to job seekers in the control group. JSA manages to find jobs quickly for the long-term unemployed, but the duration of the new jobs is shorter.
Abstract
					How are wages set within a multinational firm? Combining cross-country data on wages and labor regulations with personnel records of a large multinational firm, I find that wage setting depends on the rank of the employee in the firm hierarchy. For managers, wages are set by the headquarters regardless of local labor market conditions. For factory workers, wages are adjusted according to country-specific wages and labor regulations. These results suggest that the multinational's internal labor market shields managers from changes in external market conditions, while the firm adapts to local labor markets for factory workers.
Abstract
					This paper studies whether regional differences in the productivity of Italian Social Security Agency offices can be explained by variation in manager characteristics. Consistent with other settings, offices in the North are more productive on average than those in the South. However, managers differ primarily in demographic characteristics, attaining similar levels of education. Because most of the variation in office productivity is within rather than across region, reassigning managers to more productive offices increases total (and within-region) inequality in productivity while decreasing across-region inequality.
Abstract
					This paper builds on the identification results and estimation tools for continuous difference-in-difference designs in Callaway, Goodman-Bacon, and Sant'Anna (2024) to discuss aggregation strategies for event studies with continuous treatments. Estimates from continuous designs are functions of the treatment dosage/intensity variable. Nonparametric plots of these functions show heterogeneity across doses but not heterogeneity over time. Event-study-type plots of aggregated parameters achieve the opposite. We describe how partially aggregating across treatment doses and event time can lead to readable yet nuanced figures that reflect how causal effects evolve over time, potentially in different parts of the treatment dose distribution.
Abstract
					We consider Bayes and Empirical Bayes (EB) approaches for dealing with violations of parallel trends. In the Bayes approach, the researcher specifies a prior over both the pretreatment violations of parallel trends δpre and the posttreatment violations δpost. The researcher then updates their posterior about the posttreatment bias δpost given an estimate of the pre-trends δpre. This allows them to form posterior means and credible sets for the treatment effect of interest, τpost. In the EB approach, the prior on the violations of parallel trends is learned from the pretreatment observations. We illustrate these approaches in two empirical applications.
Abstract
					Many treatments, such as prices, taxes, or temperatures, are continuous in nature. Empirical researchers usually rely on two-way fixed effect regressions to estimate treatment effects in such cases. However, such estimators are not robust to heterogeneous treatment effects in general and rely on the linearity of treatment effects. We develop a difference-in-difference strategy for continuous treatments without imposing such restrictions when there are no stayers: treatment of all units changes between consecutive periods. We extend the nonparametric results of de Chaisemartin et al. (2023) to this setup and present a parametric approach that overcomes some limitations of the nonparametric approach.
Abstract
					The synthetic control method (SCM) is a popular approach for estimating the impact of a treatment on a single unit with panel data. Two challenges arise with higher-frequency data (e.g., monthly versus yearly): (i) achieving excellent pretreatment fit is typically more challenging, and (ii) overfitting to noise is more likely. Aggregating data over time can mitigate these problems but can also destroy important signal. In this paper, we bound the bias for SCM with disaggregated and aggregated outcomes and give conditions under which aggregating tightens the bounds. We then propose finding weights that balance both disaggregated and aggregated series.
Abstract
					Machine learning algorithms now exceed human performance on several predictive tasks, generating concerns about widespread job displacement. However, supervised learning approaches rely on large amounts of high-quality labeled data and are designed for specific predictive tasks. Thus, humans may be required for a large number of tasks, each of which is not commonly encountered—the long tail—because humans can make predictions for a broader range of outcomes and with exposure to much less data. We show that a self-supervised algorithm for chest X-rays, which does not require specifically annotated disease labels, closes this gap even in the long tail of diseases.
Abstract
					We ask whether increased public scrutiny leads to the more effective use of predictive algorithms. We focus on the context of bail, where judges face heightened public scrutiny during competitive partisan elections. We find that judges up for reelection are much more likely to follow the algorithmic recommendation to detain high-risk defendants just before an election. However, release decisions return to normal shortly after the election, and there is little change in pretrial misconduct rates, indicating that heightened public scrutiny, at least through competitive partisan elections, will not lead to the more effective use of predictive algorithms in bail.
Abstract
					The Office of Tax Analysis of the Treasury Department imputes race and ethnicity information to its tax model. We apply the imputed information to the calculation of marriage penalties and bonuses for married couples and find differences in the penalty and bonus rates facing married couples of different races and ethnic backgrounds; the differences vary by income. The results show that for couples in higher-income classes, the penalty is more prevalent for Black and Hispanic couples than White couples, and the Black-White differences by income are consistent with the patterns of spousal income splits in the underlying data.
Abstract
					Using the US Department of the Treasury's tax model with an updated race and Hispanic ethnicity (RH) imputation, we find that Hispanic and Black families are not more likely than White families to benefit from the Earned Income Tax Credit (EITC) or Child Tax Credit (CTC) within strata defined by income, RH, filing status, and the presence of children. Average EITC and CTC benefits are still generally higher for Hispanic families, but average CTC benefits are generally lower for Asian and Hispanic families who are married with children.
Abstract
					Recently, studying income by race and ethnicity has gained interest among policymakers. The Congressional Budget Office (CBO) regularly reports on the distribution of household income, using a statistically matched dataset with survey and administrative tax data to account for the household resources for both tax filers and nonfilers. CBO has not evaluated whether the statistical match preserves the distribution of income by race and ethnicity reported in the survey. This preliminary analysis of CBO's statistically matched data by race and ethnicity uses information from survey data linked to administrative tax data at the individual level from the US Census Bureau.
Abstract
					This study documents sleep norms and studies the effect of norm information on anticipated behavioral change. Participants were shown either a small or large gap between others' ideal sleep duration (injunctive norm) and actual sleep patterns (descriptive norm). While we find limited effects of injunctive norm information alone, alignment between perceived behavior and societal expectations led to greater intention for longer sleep and earlier bedtimes. Conversely, a large gap between norms and actual behavior heightened interest in advice for improving sleep. These results suggest that understanding and communicating social norms can be crucial in promoting healthy sleep practices.
Abstract
					Why do social media users spend so much time consuming content that seemingly harms them? We build a simple model to argue that advertising-driven platforms can find it profitable to display content that harms users when it is complementary to their time spent on the platform. These incentives disappear, absent network effects, in the case of a subscription-based business model because harmful content reduces the willingness to pay for the platform. Our results warn against interpreting increases in engagement on social media as welfare increases.
Abstract
					We study how exposure to partisan news channels (Fox News and MSNBC) affects individual views on four policy issues: climate change, gun rights, abortion, and immigration. First, using GPT to annotate news transcripts, we document large differences in the way the two networks cover these issues. Second, exploiting exogenous variation in viewership due to channels' positions in cable lineups, we show that exposure to Fox News (MSNBC) is associated with more conservative (progressive) views, even when controlling for self-reported ideology and party affiliation. Our findings indicate that partisan media contribute to the rise of political polarization in the United States.
Abstract
					This paper investigates disparities among objective poverty measures, individuals' subjective perceptions, and poverty-related social media discourse in US counties. We find that while poverty and perceived poverty are positively correlated, poverty-related social media discourse is unrelated to a county's level of poverty. We document that the county-level predictors of the three poverty dimensions differ widely, suggesting that poverty-related social media discussions do not take place in the counties that are most affected by poverty or perceive themselves as poor. The paper concludes by highlighting discrepancies in social media discourse, revealing a skewed portrayal of poverty, particularly concerning gender and ethnicity.
I show that sharp identified sets in a large class of econometric models can be characterized by solving linear systems of equations. These linear systems determine whether, for a given value of a parameter of interest, there exists an admissible joint distribution of unobservables that can generate the distribution of the observed variables. The joint distribution of unobservables is not required to satisfy any parametric restrictions, but can (if desired) be assumed to satisfy a variety of location, shape, and/or conditional independence restrictions. To prove sharpness of the characterization, I generalize a classic result in copula theory concerning the extendibility of subcopulas to show that related objects—termed subdistributions—can be extended to proper distribution functions. I describe this characterization argument as partial identification by extending subdistributions, or PIES. One particularly attractive feature of PIES is that it focuses directly on the sharp identified set for a parameter of interest, such as an average treatment effect, without needing to construct the identified set for the entire model. I apply PIES to univariate and bivariate binary response models. A notable product of the analysis is a method for characterizing the sharp identified set for the average treatment effect in Manski's ( 1975, 1985, 1988) semiparametric binary response model.
I propose to estimate structural impulse responses from macroeconomic time series by doing Bayesian inference on the Structural Vector Moving Average representation of the data. This approach has two advantages over Structural Vector Autoregressions. First, it imposes prior information directly on the impulse responses in a flexible and transparent manner. Second, it can handle noninvertible impulse response functions, which are often encountered in applications. Rapid simulation of the posterior distribution of the impulse responses is possible using an algorithm that exploits the Whittle likelihood. The impulse responses are partially identified, and I derive the frequentist asymptotics of the Bayesian procedure to show which features of the prior information are updated by the data. The procedure is used to estimate the effects of technological news shocks on the U.S. business cycle.
We obtain rich measurements of risk preferences for 2939 subjects across 30 countries, and use the data to paint a picture of the distribution of risk preferences across the globe using structural equation models. Reference-dependence and likelihood-dependence are found to be important everywhere. Model parameters in non-Western countries differ systematically from those in Western countries, with poorer countries substantially more risk tolerant than rich countries on average. We qualify previous findings on gender effects and cognitive ability by showing how they mainly impact likelihood-dependence. We further add novel evidence on the correlation between risk preferences and study major. Whereas we confirm previous results on observable characteristics of subjects explaining little of overall preference heterogeneity, a few macroeconomic indicators can explain a considerable part of the between-country heterogeneity.
We study the effect of embedding pairwise choices between lotteries within a choice list on measured risk attitude. Using an experiment with online workers, we find that subjects choose the risky lottery rather than a sure payment significantly more often when responding to a choice list. This behavior can be rationalized by the interaction between nonexpected utility and the random incentive system, as suggested by Karni and Safra (1987).
Tax credits are a popular way to alleviate in-work poverty. A common empirical assumption is that the benefit of the tax credit is borne solely by the claimant workers. However, economic theory suggests no particular reason why this should be the case. This paper investigates the impact of the Working Families' Tax Credit, introduced in the UK in 1999, on wages. Unlike similar tax credit policies, this tax credit was paid through employers rather than directly to workers, making it more salient to the employer. Using a novel identification strategy, we can separately identify the effect on wages associated with an increase in the amount of tax credit and that associated with the change in salience. We find evidence that: (1) through the salience mechanism the firm cuts the wage of claimant workers relative to similarly skilled nonclaimants by 30 percent of the tax credit, which is approximately 7 percent of the wage, and (2) there is a negative spillover effect onto the wages of claimant and nonclaimant workers of 1.7 percent, which is approximately 8 percent of the tax credit for claimant workers.
This paper estimates demand for residential solar photovoltaic (PV) systems using a new approach to address three empirical challenges that often arise with count data: excess zeros, unobserved heterogeneity, and endogeneity of price. Our results imply a price elasticity of demand for solar PV systems of −0.65. Counterfactual policy simulations indicate that reducing state financial incentives in half would have led to 9% fewer new installations in Connecticut in 2014. Calculations suggest a subsidy program cost of $364/tCO2 assuming solar displaces natural gas. Our Poisson hurdle approach holds promise for modeling the demand for many new technologies.
We characterize the equilibrium of a complete markets economy with multiple agents featuring a preference for the timing of the resolution of uncertainty. Utilities are defined over an aggregate of two goods. We provide conditions under which the solution of the planner's problem exists, and it features a nondegenerate invariant distribution of Pareto weights. We also show that perturbation methods replicate the salient features of our recursive risk-sharing scheme, provided that higher-order terms are included.
This paper determines conditions for the existence of a unique rational expectations equilibrium—determinacy—in a monetary policy switching economy. We depart from the existing literature by providing such conditions considering all bounded equilibria. We then apply these conditions to a new Keynesian model with switching Taylor rules. First, deviation from the Taylor principle in one regime does not necessarily cause indeterminacy. Second, very different responses to inflation may trigger indeterminacy even if both regimes satisfy the Taylor principle. Determinacy thus results from the adequacy between monetary regimes rather than the determinacy of each of them taken in isolation.
We study discretionary equilibrium in the Calvo pricing model for a monetary authority that chooses the money supply, producing three main contributions. First, price-adjusting firms have a unique equilibrium price for a broad range of parameterizations, in contrast to earlier results for the Taylor pricing model. Second, a generalized Euler equation makes transparent how the monetary authority affects future welfare through its influence on the future state of the economy. Third, we provide global solutions, including welfare analysis, for the transitional dynamics that occur if the monetary authority gains or loses the ability to commit.
We develop tests for deciding whether a large cross-section of asset prices obey an exact factor structure at the times of factor jumps. Such jump dependence is implied by standard linear factor models. Our inference is based on a panel of asset returns with asymptotically increasing cross-sectional dimension and sampling frequency, and essentially no restriction on the relative magnitude of these two dimensions of the panel. The test is formed from the high-frequency returns at the times when the risk factors are detected to have a jump. The test statistic is a cross-sectional average of a measure of discrepancy in the estimated jump factor loadings of the assets at consecutive jump times. Under the null hypothesis, the discrepancy in the factor loadings is due to a measurement error, which shrinks with the increase of the sampling frequency, while under an alternative of a noisy jump factor model this discrepancy contains also nonvanishing firm-specific shocks. The limit behavior of the test under the null hypothesis is nonstandard and reflects the strong-dependence in the cross-section of returns as well as their heteroskedasticity which is left unspecified. We further develop estimators for assessing the magnitude of firm-specific risk in asset prices at the factor jump events. Empirical application to S&P 100 stocks provides evidence for exact one-factor structure at times of big market-wide jump events.
This paper considers tests and confidence sets (CSs) concerning the coefficient on the endogenous variable in the linear IV regression model with homoskedastic normal errors and one right-hand side endogenous variable. The paper derives a finite-sample lower bound function for the probability that a CS constructed using a two-sided invariant similar test has infinite length and shows numerically that the conditional likelihood ratio (CLR) CS of Moreira (2003) is not always “very close,” say 0.005 or less, to this lower bound function. This implies that the CLR test is not always very close to the two-sided asymptotically-efficient (AE) power envelope for invariant similar tests of Andrews, Moreira, and Stock (2006) (AMS).

On the other hand, the paper establishes the finite-sample optimality of the CLR test when the correlation between the structural and reduced-form errors, or between the two reduced-form errors, goes to 1 or −1 and other parameters are held constant, where optimality means achievement of the two-sided AE power envelope of AMS. These results cover the full range of (nonzero) IV strength.

The paper investigates in detail scenarios in which the CLR test is not on the two-sided AE power envelope of AMS. Also, theory and numerical results indicate that the CLR test is close to having the greatest average power, where the average is over a specified grid of concentration parameter values and over a pair of alternative hypothesis values of the parameter of interest, uniformly over all such pairs of alternative hypothesis values and uniformly over the correlation between the structural and reduced-form errors. Here, “close” means 0.015 or less for k ≤ 20, where k denotes the number of IVs, and 0.025 or less for 0 < k ≤ 40.

The paper concludes that, although the CLR test is not always very close to the two-sided AE power envelope of AMS, CLR tests and CSs have very good overall properties.
We study subvector inference in the linear instrumental variables model assuming homoskedasticity but allowing for weak instruments. The subvector Anderson and Rubin (1949) test that uses chi square critical values with degrees of freedom reduced by the number of parameters not under test, proposed by Guggenberger, Kleibergen, Mavroeidis, and Chen (2012), controls size but is generally conservative. We propose a conditional subvector Anderson and Rubin test that uses data-dependent critical values that adapt to the strength of identification of the parameters not under test. This test has correct size and strictly higher power than the subvector Anderson and Rubin test by Guggenberger et al. (2012). We provide tables with conditional critical values so that the new test is quick and easy to use. Application of our method to a model of risk preferences in development economics shows that it can strengthen empirical conclusions in practice.
In this paper, I study identification of a nonseparable model with endogeneity arising due to unobserved heterogeneity. Identification relies on the availability of binary proxies that can be used to control for the unobserved heterogeneity. I show that the model is identified in the limit as the number of proxies increases. The argument does not require an instrumental variable that is excluded from the outcome equation nor does it require the support of the unobserved heterogeneity to be finite. I then propose a nonparametric estimator that is consistent as the number of proxies increases with the sample size. I also show that, for a fixed number of proxies, nontrivial bounds on objects of interest can be obtained. Finally, I study two real data applications that illustrate computation of the bounds and estimation with a large number of items.
Rural-urban migration is an integral part of the structural transformation as societies move from a traditional agricultural economy to a modern economy. This process has many potential consequences for migrants. Our study focuses on the lifetime health effects of the large mid-20th century migration out of rural U.S. Northern Great Plains states, primarily to urban locations in the West and Midwest. An analysis of marginal treatment effects (MTEs) shows that (a) migrants are positively selected, and (b) the causal impact of migration is decreased longevity. Our evidence suggests that elevated mortality among migrants is linked to increased smoking and alcohol consumption.
We use unique data from the Berea Panel Study to characterize how much earnings uncertainty is present for students at college entrance and how quickly this uncertainty is resolved. We characterize uncertainty using survey questions that elicit the entire distribution describing one's beliefs about future earnings. Taking advantage of the longitudinal nature of the expectations data, we find that roughly two-thirds of the income uncertainty present at the time of entrance remains at the end of college. Taking advantage of a variety of additional survey questions, we provide evidence about how the resolution of income uncertainty is influenced by factors such as college GPA and college major, and also examine why much income uncertainty remains unresolved at the end of college. This paper also contributes to a literature interested in understanding the relative importance of uncertainty and heterogeneity in determining observed earnings distributions.
We construct a structural model of entry into self-employment to evaluate the impact of policies supporting entrepreneurship. Previous work has recognized that workers may opt for self-employment due to the nonpecuniary benefits of running a business and not necessarily because they are good at it. Other literature has examined how socio-emotional skills, such as personality traits, affect selection into self-employment. We link these two lines of inquiry. The model we estimate captures three factors that affect selection into self-employment: credit constraints, relative earnings, and preferences. We incorporate personality traits by allowing them to affect sector-specific earnings as well as preferences. The estimated model reveals that the personality traits that make entrepreneurship profitable are not always the same traits driving people to open a business. This has important consequences for entrepreneurship policies. For example, subsidies for small businesses do not attract talented-but-reluctant entrepreneurs, but instead attract individuals with personality traits associated with strong preferences for running a business and low-quality business ideas.
I model job-search monitoring in the optimal unemployment insurance framework, in which job-search effort is the worker's private information. In the model, monitoring provides costly information upon which the government conditions unemployment benefits. Using a simple one-period model with two effort levels, I show analytically that the monitoring precision increases and the utility spread decreases if and only if the inverse of the worker's utility in consumption has a convex derivative. The quantitative analysis that follows extends the model by allowing a continuous effort and separations from employment. That analysis highlights two conflicting economic forces affecting the optimal precision of monitoring with respect to the generosity of the welfare system: higher promised utility is associated not only with a higher cost of moral hazard, but also with lower effort and lower value of employment. The result is an inverse U-shaped precision profile with respect to promised utility.
We study the causes behind the shift in the level of U.S. GDP following the Great Recession. To this end, we propose a model featuring endogenous productivity à la Romer and a financial friction à la Kiyotaki–Moore. Adverse financial disturbances during the recession and the lack of strong tailwinds post-crisis resulted in a severe contraction and the downward shift in the economy's trend. Had financial conditions remained stable during the crisis, the economy would have grown at its average growth rate. From a historical perspective, the Great Recession was unique because of the size and persistence of adverse shocks, and the lackluster performance of favorable shocks since 2010.
We design a laboratory experiment to study behavior in a multidivisional organization. The organization faces a trade-off between coordinating its decisions across the divisions and meeting division-specific needs that are known only to the division managers, who can communicate their private information through cheap talk. While the results show close to optimal communication, we also find systematic deviations from optimal behavior in how the communicated information is used. Specifically, subjects' decisions show worse than predicted adaptation to the needs of the divisions in decentralized organizations and worse than predicted coordination in centralized organizations. We show that the observed deviations disappear when uncertainty about the divisions' local needs is removed and discuss the possible underlying mechanisms.
Labor market frictions are able to induce sluggish aggregate employment dynamics. However, these frictions have strong implications for the source of this propagation: they distort the path of aggregate employment by impeding the flow of labor across firms. For a canonical class of frictions, we show how observable measures of such flows can be used to assess the effect of frictions on aggregate employment dynamics. Application of this approach to establishment microdata for the United States reveals that the empirical flow of labor across firms deviates markedly from the predictions of canonical labor market frictions. Despite their ability to induce persistence in aggregate employment, firm-size flows in these models are predicted to respond aggressively to aggregate shocks, but react sluggishly in the data. The paper therefore concludes that the propagation mechanism embodied in standard models of labor market frictions fails to account for the sources of observed employment dynamics.
The estimation of nonstationary dynamic discrete choice models typically requires making assumptions far beyond the length of the data. We extend the class of dynamic discrete choice models that require only a few-period-ahead conditional choice probabilities, and develop algorithms to calculate the finite dependence paths. We do this both in single agent and games settings, resulting in expressions for the value functions that allow for much weaker assumptions regarding the time horizon and the transitions of the state variables beyond the sample period.
This paper develops a dynamic model of consumer search that, despite placing very little structure on the dynamic problem faced by consumers, allows us to exploit intertemporal variation in price distributions to estimate the distribution from which consumer search costs are initially drawn. We show that static approaches to estimating this distribution may suffer from dynamic sample selection bias. This can happen if consumers are forward-looking and delay their purchases in a way that systematically depends on their individual search costs. We consider identification of the population search cost distribution using only price data and develop estimable nonparametric upper and lower bounds on the distribution function, as well as a nonlinear least squares estimator for parametric models. We also consider the additional identifying power of weak, theoretical assumptions such as monotonicity of purchase probabilities in search costs. We apply our estimators to analyze the online market for two widely used econometrics textbooks. Our results suggest that static estimates of the search cost distribution are biased upwards, in a distributional sense, relative to the true population distribution. We illustrate this and other forms of bias in a small-scale simulation study.
This paper studies the averaging GMM estimator that combines a conservative GMM estimator based on valid moment conditions and an aggressive GMM estimator based on both valid and possibly misspecified moment conditions, where the weight is the sample analog of an infeasible optimal weight. We establish asymptotic theory on uniform approximation of the upper and lower bounds of the finite-sample truncated risk difference between any two estimators, which is used to compare the averaging GMM estimator and the conservative GMM estimator. Under some sufficient conditions, we show that the asymptotic lower bound of the truncated risk difference between the averaging estimator and the conservative estimator is strictly less than zero, while the asymptotic upper bound is zero uniformly over any degree of misspecification. The results apply to quadratic loss functions. This uniform asymptotic dominance is established in non-Gaussian semiparametric nonlinear models.
We exploit the rationale behind the Expectation Maximization algorithm to derive simple to implement and interpret LM normality tests for the innovations of the latent variables in linear state space models against generalized hyperbolic alternatives, including symmetric and asymmetric Student ts. We decompose our tests into third and fourth moment components, and obtain one-sided likelihood ratio analogues, whose asymptotic distribution we provide. When we apply our tests to a common trend model which combines the expenditure and income versions of US aggregate real output to improve its measurement, we reject normality if the sample period extends beyond the Great Moderation.
This paper develops extremum estimation and inference results for nonlinear models with very general forms of potential identification failure when the source of this identification failure is known. We examine models that may have a general deficient rank Jacobian in certain parts of the parameter space. When identification fails in one of these models, it becomes underidentified and the identification status of individual parameters is not generally straightforward to characterize. We provide a systematic reparameterization procedure that leads to a reparametrized model with straightforward identification status. Using this reparameterization, we determine the asymptotic behavior of standard extremum estimators and Wald statistics under a comprehensive class of parameter sequences characterizing the strength of identification of the model parameters, ranging from nonidentification to strong identification. Using the asymptotic results, we propose hypothesis testing methods that make use of a standard Wald statistic and data-dependent critical values, leading to tests with correct asymptotic size regardless of identification strength and good power properties. Importantly, this allows one to directly conduct uniform inference on low-dimensional functions of the model parameters, including one-dimensional subvectors. The paper illustrates these results in three examples: a sample selection model, a triangular threshold crossing model, and a collective model for household expenditures.
We propose an empirical framework for analyzing the macroeconomic effects of quantitative easing (QE) and apply it to Japan. The framework is a regime-switching structural vector autoregression in which the monetary policy regime, chosen by the central bank responding to economic conditions, is endogenous and observable. QE is modeled as one of the regimes. The model incorporates an exit condition for terminating QE. We find that higher reserves at the effective lower bound raise inflation and output, and that terminating QE may be contractionary or expansionary, depending on the state of the economy at the point of exit.
Formal dynamic analyses of household portfolio choice in the literature focus on holdings of equity and a risk-free asset or bonds of different maturities, neglecting the interdependence of the decisions to invest in equity, short-term and long-term bonds made by households. Data from the Survey of Consumer Finances is used to derive stylized facts about participation in the long-term government-debt market and conditional portfolio shares. To explain the mechanisms underlying these facts, I draw on a life-cycle model in which investors have access to three financial assets—equity, long-term debt, and a riskless short-term bond—and are exposed to uninsurable idiosyncratic risk through nonfinancial income as well as aggregate risk through the asset returns. An application shows that the low Treasury returns observed in the US between 2009 and 2013 have quantitatively significant yet transitory effects on the composition of household portfolios. In combination with the observed rise in stock returns, they lead to persistent changes in the participation rate, the conditional portfolio shares, and the distribution of wealth.
More than of US grain is used for energy due to the Renewable Fuel Mandate (RFS). There are no studies of the global distributional consequences of this purely domestic policy. Using micro-level survey data, we trace the effect of the RFS on world food prices and their impact on household level consumption and wage incomes in India. We first develop a partial equilibrium model to estimate the effect of the RFS on the price of selected food commodities—rice, wheat, corn, sugar, and meat and dairy, which together provide almost of Indian food calories. Our model predicts that world prices for these commodities rise by 8– due to the RFS. We estimate the price pass-through to domestic Indian prices and the effect of the price shock on household welfare through consumption and wage incomes. Poor rural households suffer significant welfare losses due to higher prices of consumption goods, which are regressive. However, they benefit from a rise in wage incomes, mainly because most of them are employed in agriculture. Urban households also bear the higher cost of food, but do not see a concomitant rise in wages because only a small fraction of them work in food-related industries. Welfare losses are greater among urban households. However, more poor people in India live in villages, so rural poverty impacts are larger in magnitude. We estimate that the mandate leads to about 25 million new poor: 21 million in rural and 4 million in the urban population.
This paper constructs and estimates a dynamic discrete choice structural model of female employment and fertility decisions that incorporates job protection and cash benefits of parental leave legislation. The structural model is used for ex ante evaluation of policies that change the duration of job protection and/or the arrangement for cash benefits. Counterfactual simulations indicate that introducing an initial 1-year job protection policy increases maternal employment significantly, but extending the existing job protection period from 1 to 3 years has little effect. In addition, the employment effects of cash benefits seem modest. Overall, parental leave policies have little effect on fertility.
We use rich microeconomic data on performance and choices of students at college entry to analyze interactions between the selection mechanism, eliciting college preferences through exams, and the allocation mechanism. We set up a framework in which success probabilities and student preferences are shown to be identified from data on their choices and their exam grades under exclusion restrictions and support conditions. The counterfactuals we consider balance the severity of congestion and the quality of the match between schools and students. Moving to deferred acceptance or inverting the timing of choices and exams are shown to increase welfare. Redistribution among students and among schools is also sizeable in all counterfactual experiments.
How much additional tax revenue can the government generate by increasing the level of labor income taxes? In this paper, we argue that the degree of tax progressivity is a quantitatively important determinant of the answer to this question. To make this point, we develop a large scale overlapping generations model with single and married households facing idiosyncratic income risk, extensive and intensive margins of labor supply, as well as endogenous accumulation of human capital through labor market experience. We calibrate the model to U.S. macro, micro, and tax data and characterize the labor income tax Laffer curve for various degrees of tax progressivity. We find that the peak of the U.S. Laffer curve is attained at an average labor income tax rate of . This peak (the maximal tax revenues the government can raise) increases by if the current progressive tax code is replaced with a flat labor income tax. Replacing the current U.S. tax system with one that has Denmark' s progressivity would lower the peak by . We show that modeling the extensive margin of labor supply and endogenous human capital accumulation is crucial for these findings. With joint taxation of married couples (as in the U.S.), higher tax progressivity leads to significantly lower labor force participation of married women and substantially higher labor force participation of single women, an effect that is especially pronounced when future wages of females depend positively on past labor market experience.
A well-established result in the literature is that Social Security reduces steady state welfare in a standard life cycle model. However, less is known about the historical quantitative effects of the program on agents who were alive when the program was adopted. In a computational life cycle model that simulates the Great Depression and the enactment of Social Security, this paper quantifies the welfare effects of the program's enactment on the cohorts of agents who experienced it. In contrast to the standard steady state results, we find that the adoption of the original Social Security generally improved these cohorts' welfare, in part because these cohorts received far more benefits relative to their contributions than they would have received if they lived their entire life in the steady state with Social Security. Moreover, the negative general equilibrium welfare effect of Social Security associated with capital crowd-out was reduced during the transition, because it took many periods for agents to adjust their savings levels in response to the program's adoption. The positive welfare effect experienced by these transitional agents offers one explanation for why the program that may reduce welfare in the steady state was originally adopted.
This paper develops and estimates a life-cycle equilibrium labor search model in which heterogeneous firms determine health insurance provisions and heterogeneous workers sort themselves into jobs with different compensation packages over the life cycle. I study the optimal joint design of major policies in the Affordable Care Act (ACA) and the implications of targeting these policies to certain individuals. Compared with the health insurance system under the ACA, the optimal structure lowers the tax benefit of employer-sponsored health insurance and makes individual insurance more attractive to younger workers. Through changes in firms' insurance provisions, a greater number of younger workers sort into individual markets, which contributes to improving the risk pool in individual insurance and lowering the uninsured risk.
This paper estimates a lifecycle model of consumption, housing choice, and migration in the presence of aggregate and regional shocks, using the Survey of Income and Program Participation (SIPP). The model delivers structural estimates of moving costs by ownership status, age, and family size that complement the previous literature. Using the model, I first show that migration elasticities vary substantially between renters and owners, and I estimate the consumption value of having the option to migrate across regions when there are regional shocks. This value is of lifetime consumption on average, and it varies substantially with household type.
This paper presents identification and estimation results for a flexible state space model. Our modification of the canonical model allows the permanent component to follow a unit root process and the transitory component to follow a semiparametric model of a higher-order autoregressive-moving-average (ARMA) process. Using panel data of observed earnings, we establish identification of the nonparametric joint distributions for each of the permanent and transitory components over time. We apply the identification and estimation method to the earnings dynamics of U.S. men using the Panel Survey of Income Dynamics (PSID). The results show that the marginal distributions of permanent and transitory earnings components are more dispersed, more skewed, and have fatter tails than the normal and that earnings mobility is much lower than for the normal. We also find strong evidence for the existence of higher-order ARMA processes in the transitory component, which lead to much different estimates of the distributions of and earnings mobility in the permanent component, implying that misspecification of the process for transitory earnings can affect estimated distributions of the permanent component and estimated earnings dynamics of that component. Thus our flexible model implies earnings dynamics for U.S. men different from much of the prior literature.
Researchers commonly “shrink” raw quality measures based on statistical criteria. This paper studies when and how this transformation's statistical properties would confer economic benefits to a utility-maximizing decision-maker across common asymmetric information environments. I develop the results for an application measuring teacher quality. The presence of a systematic relationship between teacher quality and class size could cause the data transformation to do either worse or better than the untransformed data. I use data from Los Angeles to confirm the presence of such a relationship and show that the simpler raw measure would outperform the one most commonly used in teacher incentive schemes.
This paper considers identification and estimation of the Quantile Treatment Effect on the Treated (QTT) under a straightforward distributional extension of the most commonly invoked Mean Difference in Differences Assumption used for identifying the Average Treatment Effect on the Treated (ATT). Identification of the QTT is more complicated than the ATT though because it depends on the unknown dependence (or copula) between the change in untreated potential outcomes and the initial level of untreated potential outcomes for the treated group. To address this issue, we introduce a new Copula Stability Assumption that says that the missing dependence is constant over time. Under this assumption and when panel data is available, the missing dependence can be recovered, and the QTT is identified. We use our method to estimate the effect of increasing the minimum wage on quantiles of local labor markets' unemployment rates and find significant heterogeneity.
This paper studies measuring various average effects of X on Y in general structural systems with unobserved confounders U, a potential instrument Z, and a proxy W for U. We do not require X or Z to be exogenous given the covariates or W to be a perfect one-to-one mapping of U. We study the identification of coefficients in linear structures as well as covariate-conditioned average nonparametric discrete and marginal effects (e.g., average treatment effect on the treated), and local and marginal treatment effects. First, we characterize the bias, due to the omitted variables U, of (nonparametric) regression and instrumental variables estimands, thereby generalizing the classic linear regression omitted variable bias formula. We then study the identification of the average effects of X on Y when U may statistically depend on X and Z. These average effects are point identified if the average direct effect of U on Y is zero, in which case exogeneity holds, or if W is a perfect proxy, in which case the ratio (contrast) of the average direct effect of U on Y to the average effect of U on W is also identified. More generally, restricting how the average direct effect of U on Y compares in magnitude and/or sign to the average effect of U on W can partially identify the average effects of X on Y. These restrictions on confounding are weaker than requiring benchmark assumptions, such as exogeneity or a perfect proxy, and enable a sensitivity analysis. After discussing estimation and inference, we apply this framework to study earnings equations.
This paper introduces a new identification- and singularity-robust conditional quasi-likelihood ratio (SR-CQLR) test and a new identification- and singularity-robust Anderson and Rubin (1949) (SR-AR) test for linear and nonlinear moment condition models. Both tests are very fast to compute. The paper shows that the tests have correct asymptotic size and are asymptotically similar (in a uniform sense) under very weak conditions. For example, in i.i.d. scenarios, all that is required is that the moment functions and their derivatives have 2 + γ bounded moments for some γ > 0. No conditions are placed on the expected Jacobian of the moment functions, on the eigenvalues of the variance matrix of the moment functions, or on the eigenvalues of the expected outer product of the (vectorized) orthogonalized sample Jacobian of the moment functions.

The SR-CQLR test is shown to be asymptotically efficient in a GMM sense under strong and semi-strong identification (for all k ≥ p, where k and p are the numbers of moment conditions and parameters, respectively). The SR-CQLR test reduces asymptotically to Moreira's CLR test when p = 1 in the homoskedastic linear IV model. The same is true for p ≥ 2 in most, but not all, identification scenarios.

We also introduce versions of the SR-CQLR and SR-AR tests for subvector hypotheses and show that they have correct asymptotic size under the assumption that the parameters not under test are strongly identified. The subvector SR-CQLR test is shown to be asymptotically efficient in a GMM sense under strong and semi-strong identification.
This paper develops a general framework for conducting inference on the rank of an unknown matrix Π0. A defining feature of our setup is the null hypothesis of the form . The problem is of first-order importance because the previous literature focuses on by implicitly assuming away , which may lead to invalid rank tests due to overrejections. In particular, we show that limiting distributions of test statistics under may not stochastically dominate those under . A multiple test on the nulls , though valid, may be substantially conservative. We employ a testing statistic whose limiting distributions under are highly nonstandard due to the inherent irregular natures of the problem, and then construct bootstrap critical values that deliver size control and improved power. Since our procedure relies on a tuning parameter, a two-step procedure is designed to mitigate concerns on this nuisance. We additionally argue that our setup is also important for estimation. We illustrate the empirical relevance of our results through testing identification in linear IV models that allows for clustered data and inference on sorting dimensions in a two-sided matching model with transferrable utility.
In dynamic environments where the strategic setting evolves across time, the specific rule governing the transitions can substantially alter the incentives agents face. This is particularly true when history-dependent strategies are used. In a laboratory study, we examine whether subjects respond to the transition rule and internalize its effects on continuation values. Our main comparison is between an endogenous transition where future states directly depend on current choices, and exogenous transitions where the future environment is random and independent of actions. Our evidence shows that subjects readily internalize the effect of the dynamic game transition rule on their incentives, in line with history-dependent theoretical predictions.
We consider the problem of constructing honest confidence intervals (CIs) for a scalar parameter of interest, such as the regression discontinuity parameter, in nonparametric regression based on kernel or local polynomial estimators. To ensure that our CIs are honest, we use critical values that take into account the possible bias of the estimator upon which the CIs are based. We show that this approach leads to CIs that are more efficient than conventional CIs that achieve coverage by undersmoothing or subtracting an estimate of the bias. We give sharp efficiency bounds of using different kernels, and derive the optimal bandwidth for constructing honest CIs. We show that using the bandwidth that minimizes the maximum mean-squared error results in CIs that are nearly efficient and that in this case, the critical value depends only on the rate of convergence. For the common case in which the rate of convergence is n−2/5, the appropriate critical value for 95% CIs is 2.18, rather than the usual 1.96 critical value. We illustrate our results in a Monte Carlo analysis and an empirical application.
Given a set of baseline assumptions, a breakdown frontier is the boundary between the set of assumptions which lead to a specific conclusion and those which do not. In a potential outcomes model with a binary treatment, we consider two conclusions: First, that ATE is at least a specific value (e.g., nonnegative) and second that the proportion of units who benefit from treatment is at least a specific value (e.g., at least 50%). For these conclusions, we derive the breakdown frontier for two kinds of assumptions: one which indexes relaxations of the baseline random assignment of treatment assumption, and one which indexes relaxations of the baseline rank invariance assumption. These classes of assumptions nest both the point identifying assumptions of random assignment and rank invariance and the opposite end of no constraints on treatment selection or the dependence structure between potential outcomes. This frontier provides a quantitative measure of the robustness of conclusions to relaxations of the baseline point identifying assumptions. We derive -consistent sample analog estimators for these frontiers. We then provide two asymptotically valid bootstrap procedures for constructing lower uniform confidence bands for the breakdown frontier. As a measure of robustness, estimated breakdown frontiers and their corresponding confidence bands can be presented alongside traditional point estimates and confidence intervals obtained under point identifying assumptions. We illustrate this approach in an empirical application to the effect of child soldiering on wages. We find that sufficiently weak conclusions are robust to simultaneous failures of rank invariance and random assignment, while some stronger conclusions are fairly robust to failures of rank invariance but not necessarily to relaxations of random assignment.
Indirect Inference (I-I) estimation of structural parameters θ requires matching observed and simulated statistics, which are most often generated using an auxiliary model that depends on instrumental parameters β. The estimators of the instrumental parameters will encapsulate the statistical information used for inference about the structural parameters. As such, artificially constraining these parameters may restrict the ability of the auxiliary model to accurately replicate features in the structural data, which may lead to a range of issues, such as a loss of identification. However, in certain situations the parameters β naturally come with a set of q restrictions. Examples include settings where β must be estimated subject to q possibly strict inequality constraints g(β)>0, such as, when I-I is based on GARCH auxiliary models. In these settings, we propose a novel I-I approach that uses appropriately modified unconstrained auxiliary statistics, which are simple to compute and always exists. We state the relevant asymptotic theory for this I-I approach without constraints and show that it can be reinterpreted as a standard implementation of I-I through a properly modified binding function. Several examples that have featured in the literature illustrate our approach.
This paper analyzes the problem of weak instruments on identification, estimation, and inference in a simple nonparametric model of a triangular system. The paper derives a necessary and sufficient rank condition for identification, based on which weak identification is established. Then nonparametric weak instruments are defined as a sequence of reduced-form functions where the associated rank shrinks to zero. The problem of weak instruments is characterized as concurvity, which motivates the introduction of a regularization scheme. The paper proposes a penalized series estimation method to alleviate the effects of weak instruments and shows that it achieves desirable asymptotic properties. A data-driven procedure is proposed for the choice of the penalization parameter. The findings of this paper provide useful implications for empirical work. To illustrate them, Monte Carlo results are presented and an empirical example is given in which the effect of class size on test scores is estimated nonparametrically.
This paper shows how to decompose weakly stationary time series into the sum, across time scales, of uncorrelated components associated with different degrees of persistence. In particular, we provide an Extended Wold Decomposition based on an isometric scaling operator that makes averages of process innovations. Thanks to the uncorrelatedness of components, our representation of a time series naturally induces a persistence-based variance decomposition of any weakly stationary process. We provide two applications to show how the tools developed in this paper can shed new light on the determinants of the variability of economic and financial time series.
This paper develops a dynamic model of schooling and occupational choices that incorporates personality traits, as measured by the “big five” traits. The model is estimated using the HILDA dataset from Australia. Personality traits are found to play an important role in explaining education and occupation choices over the lifecycle. Results show that individuals with a comparative advantage in schooling and white-collar work have, on average, higher cognitive skills and higher personality trait scores. Allowing personality traits to evolve with age and with schooling proves to be important to capturing the heterogeneity in how people respond to educational policies. The estimated model is used to evaluate two education policies: compulsory senior secondary school and a 50% college tuition subsidy. Both policies increase educational attainment and also affect personality traits.
We develop a new dynamic equilibrium model with heterogeneous households that captures the most important frictions that arise in housing rental markets and explains the political popularity of affordable housing policies. We estimate the model using data collected by the New York Housing Vacancy Survey in 2011. We find that there are significant adjustment costs in all markets as well as serious search frictions in the market for affordable housing. Moreover, there are large queuing frictions in the market for public housing. Having access to rent-stabilized housing increases household welfare by up to . Increasing the supply of affordable housing by significantly improves the welfare of all renters in the city. Progressive taxation of higher-income households that live in public housing can also be welfare improving.
Combining weekly productivity data with weekly productivity beliefs for a large sample of truckers over 2 years, we show that workers tend to systematically and persistently overpredict their productivity. If workers are overconfident about their own productivity at the current firm relative to their outside option, they should be less likely to quit. Empirically, all else equal, having higher productivity beliefs is associated with an employee being less likely to quit. To study the implications of overconfidence for worker welfare and firm profits, we estimate a structural learning model with biased beliefs that accounts for many key features of the data. While worker overconfidence moderately decreases worker welfare, it also substantially increases firm profits.
We address empirically the issues of the optimality of simple linear compensation contracts and the importance of asymmetries between firms and workers. For that purpose, we consider contracts between the French National Institute of Statistics and Economics (Insee) and the interviewers it hired to conduct its surveys in 2001, 2002, and 2003. To derive our results, we exploit an exogenous change in the contract structure in 2003, the piece rate increasing from 20.2 to 22.9 euros. We argue that such a change is crucial for a structural analysis. It allows us, in particular, to identify and recover nonparametrically some information on the cost function of the interviewers and on the distribution of their types. This information is used to select correctly our parametric restrictions. Our results indicate that the loss of using such simple contracts instead of the optimal ones is no more than 16%, which might explain why linear contracts are so popular. We also find moderate costs of asymmetric information in our data, the loss being around 22% of what Insee could achieve under complete information.
To quantify contracting distortions in a real-world market, we develop and structurally estimate a model of contracting under payoff uncertainty in the south Indian groundwater economy. Uncertainty arises from unpredictable fluctuations in groundwater supply during the agricultural dry season. Our model highlights the tradeoff between the ex post inefficiency of long-term contracts and the ex ante inefficiency of spot contracts. We use unique data on both payoff uncertainty and relationship-specific investment collected from a large sample of well-owners in Andhra Pradesh to estimate the model's parameters. Our estimates imply that spot contracts entail a 3% efficiency loss due to hold-up. Counterfactual simulations also reveal that the equilibrium contracting distortion reduces the overall gains from trade by about 4% and the seasonal income of the median borewell owner by 2%, with proportionally greater costs borne by smaller landowners.
We study unemployment insurance in a framework where the main source of heterogeneity among agents is the type of household they live in: some agents live alone while others live with their spouses as a family. Our exercise is motivated by the fact that married individuals can rely on spousal income to smooth labor market shocks, while singles cannot. We extend a version of the standard incomplete-markets model to include two-agent households and calibrate it to the US economy with special emphasis on matching differences in labor market transitions across gender and marital status as well as aggregate wealth moments. Our central finding is that changes to the current unemployment insurance program are valued differently by married and single households. In particular, a more generous unemployment insurance reduces the welfare of married households significantly more than that of singles and vice versa. We show that this result is driven by the amount of self-insurance existing in married households, and thus, we highlight the interplay between self- and government-provided insurance and its implication for policy.
Empirical research often cites observed choice responses to variation that shifts expected discounted future utilities, but not current utilities, as an intuitive source of information on time preferences. We study the identification of dynamic discrete choice models under such economically motivated exclusion restrictions on primitive utilities. We show that each exclusion restriction leads to an easily interpretable moment condition with the discount factor as the only unknown parameter. The identified set of discount factors that solves this condition is finite, but not necessarily a singleton. Consequently, in contrast to common intuition, an exclusion restriction does not in general give point identification. Finally, we show that exclusion restrictions have nontrivial empirical content: The implied moment conditions impose restrictions on choices that are absent from the unconstrained model.
Triangular systems with nonadditively separable unobserved heterogeneity provide a theoretically appealing framework for the modeling of complex structural relationships. However, they are not commonly used in practice due to the need for exogenous variables with large support for identification, the curse of dimensionality in estimation, and the lack of inferential tools. This paper introduces two classes of semiparametric nonseparable triangular models that address these limitations. They are based on distribution and quantile regression modeling of the reduced form conditional distributions of the endogenous variables. We show that average, distribution, and quantile structural functions are identified in these systems through a control function approach that does not require a large support condition. We propose a computationally attractive three-stage procedure to estimate the structural functions where the first two stages consist of quantile or distribution regressions. We provide asymptotic theory and uniform inference methods for each stage. In particular, we derive functional central limit theorems and bootstrap functional central limit theorems for the distribution regression estimators of the structural functions. These results establish the validity of the bootstrap for three-stage estimators of structural functions, and lead to simple inference algorithms. We illustrate the implementation and applicability of all our methods with numerical simulations and an empirical application to demand analysis.
This paper proposes a new bivariate competing risks model in which both durations are the first passage times of dependent Lévy subordinators with exponential thresholds and multiplicative covariates effects. Our specification extends the mixed proportional hazards model, as it allows for the time-varying heterogeneity represented by the unobservable Lévy processes and it generates the simultaneous termination of both durations with positive probability. We obtain nonparametric identification of all model primitives given competing risks data. A flexible semiparametric estimation procedure is provided and illustrated through the analysis of a real dataset.
This study develops cluster robust inference methods for panel quantile regression (QR) models with individual fixed effects, allowing for temporal correlation within each individual. The conventional QR standard errors can seriously underestimate the uncertainty of estimators and, therefore, overestimate the significance of effects, when outcomes are serially correlated. Thus, we propose a clustered covariance matrix (CCM) estimator to solve this problem. The CCM estimator is an extension of the heteroskedasticity and autocorrelation consistent covariance matrix estimator for QR models with fixed effects. The autocovariance element in the CCM estimator can be substantially biased, due to the incidental parameter problem. Thus, we develop a bias-correction method for the CCM estimator. We derive an optimal bandwidth formula that minimizes the asymptotic mean squared errors, and propose a data-driven bandwidth selection rule. We also propose two cluster robust tests, and establish their asymptotic properties. We then illustrate the practical usefulness of the proposed methods using an empirical application.
This paper studies the inference problem of an infinite-dimensional parameter with a shape restriction. This parameter is identified by arbitrarily many unconditional moment equalities. The shape restriction leads to a convex restriction set. I propose a test of the shape restriction, which controls size uniformly and applies to both point-identified and partially identified models. The test can be inverted to construct confidence sets after imposing the shape restriction. Monte Carlo experiments show the finite-sample properties of this method. In an empirical illustration, I apply the method to ascending auctions held by the US Forest Service and show that imposing shape restrictions can significantly improve inference.
Using a lifecycle model of consumption, saving and portfolio choice combined with linked survey and administrative data on wealth and lifetime earnings we evaluate measures of retirement preparedness. We estimate heterogeneous discount factors for households and compare these estimates of their patience to their replacement rates—the simple measure often used to evaluate the adequacy of retirement savings. We find first that the specification of the model's asset structure matters quantitatively for preference parameter estimates—households appear to be much more patient when they are assumed to have access only to a risk-free asset compared to when we account for the fact that much of their wealth is stored in higher-return tax-advantaged private pensions and in housing. Second, we find that only the most patient households achieve the replacement rates out of final earnings that are often recommended by policymakers and industry as sensible benchmarks for retirement preparedness. Notwithstanding this, we find that even quite impatient households in the population we study achieve high replacement rates out of lifetime average income—a more sensible summary measure of preparedness for retirement.
This paper investigates whether assuming that households possess advance information on their income shocks helps to overcome the difficulty of standard models to understand consumption insurance in the US. As our main result, we find that the quantitative relevance of advance information crucially depends on the structure of insurance markets. For a realistic amount of advance information, a complete markets model with endogenous solvency constraints due to limited commitment explains several key consumption insurance measures better than existing models without advance information. In contrast, when advance information is integrated into a standard incomplete markets model, it affects household consumption-saving decisions too little to bridge the gap between the model and the data and can induce counterfactual correlations between current consumption growth and future income growth.
How has the microcredit movement managed to push financial frontiers? Theory shows that if borrowers vary in unobservable risk, then group-based, joint liability contracts price for risk more accurately than individual contracts, provided that borrowers match with others of similar project riskiness (Ghatak (1999, 2000)). This more accurate risk-pricing can attract safer borrowers and rouse an otherwise dormant credit market. We extend the theory to include correlated risk, and show that borrowers will match with partners exposed to similar shocks to lower their chances of facing liability for their partners. We use unique data on Thai microcredit borrowing groups to test for homogeneous matching by project riskiness and type of risk exposure. Evidence supports the theory, in that groups are more homogeneous in riskiness but less diversified in type of risk exposure than they would be under random matching. The results suggest that group lending is improving risk-pricing by embedding a discount for safe borrowers, and can thus explain part of the unprecedented rise in financial intermediation among the world's poor; but that a potential pitfall of voluntary group formation is antidiversification, which points to strategies for lender intervention.
This paper proposes a new approach to estimate task prices per efficiency unit of skill in the Roy model. I show how the sorting of workers into tasks and their associated wage growth can be used to identify changes in task prices under relatively weak assumptions. The estimation exploits the fact that the returns to observable talents will change differentially over time depending on the changes in prices of those tasks that they predict workers to sort into. In the generalized Roy model, also the average non-pecuniary amenities in each task are identified. I apply this approach to the literature on routine-biased technical change, a key prediction of which is that task prices should polarize. Empirical results for male workers in U.S. data indicate that abstract and manual tasks' relative prices indeed increased during the 1990s and 2000s.
Structural DSGE models are used for analyzing both policy and the sources of business cycles. Conclusions based on full structural models are, however, potentially affected by misspecification. A competing method is to use partially identified SVARs based on narrative shocks. This paper asks whether both approaches agree. Specifically, I use narrative data in a DSGE-SVAR that partially identify policy shocks in the VAR and assess the fit of the DSGE model relative to this narrative benchmark. In developing this narrative DSGE-SVAR, I develop a tractable Bayesian approach to proxy VARs and show that such an approach is valid for models with a certain class of Taylor rules. Estimating a DSGE-SVAR based on a standard DSGE model with fiscal rules and narrative data, I find that the DSGE model identification is at odds with the narrative information as measured by the marginal likelihood. I trace this discrepancy to differences in impulse responses, identified historical shocks and policy rules. The results indicate monetary accommodation of fiscal shocks.
The key assumption in regression discontinuity analysis is that the distribution of potential outcomes varies smoothly with the running variable around the cutoff. In many empirical contexts, however, this assumption is not credible; and the running variable is said to be manipulated in this case. In this paper, we show that while causal effects are not point identified under manipulation, one can derive sharp bounds under a general model that covers a wide range of empirical patterns. The extent of manipulation, which determines the width of the bounds, is inferred from the data in our setup. Our approach therefore does not require making a binary decision regarding whether manipulation occurs or not, and can be used to deliver manipulation-robust inference in settings where manipulation is conceivable, but not obvious from the data. We use our methods to study the disincentive effect of unemployment insurance on (formal) reemployment in Brazil, and show that our bounds remain informative, despite the fact that manipulation has a sizable effect on our estimates of causal parameters.
Causal effects of a policy change on hazard rates of a duration outcome variable are not identified from a comparison of spells before and after the policy change if there is unobserved heterogeneity in the effects and no model structure is imposed. We develop a discontinuity approach that overcomes this by considering spells that include the moment of the policy change and by exploiting variation in the moment at which different cohorts are exposed to the policy change. We prove identification of average treatment effects on hazard rates without model structure. We estimate these effects by kernel hazard regression. We use the introduction of the NDYP program for young unemployed individuals in the UK to estimate average program participation effects on the exit rate to work as well as anticipation effects.
In various economic environments, people observe other people with whom they strategically interact. We can model such information-sharing relations as an information network, and the strategic interactions as a game on the network. When any two agents in the network are connected either directly or indirectly in a large network, empirical modeling using an equilibrium approach can be cumbersome, since the testable implications from an equilibrium generally involve all the players of the game, whereas a researcher's data set may contain only a fraction of these players in practice. This paper develops a tractable empirical model of linear interactions where each agent, after observing part of his neighbors' types, not knowing the full information network, uses best responses that are linear in his and other players' types that he observes, based on simple beliefs about the other players' strategies. We provide conditions on information networks and beliefs such that the best responses take an explicit form with multiple intuitive features. Furthermore, the best responses reveal how local payoff interdependence among agents is translated into local stochastic dependence of their actions, allowing the econometrician to perform asymptotic inference without having to observe all the players in the game or having to know the precise sampling process.
In this paper, we study the estimation and inference of the quantile treatment effect under covariate-adaptive randomization. We propose two estimation methods: (1) the simple quantile regression and (2) the inverse propensity score weighted quantile regression. For the two estimators, we derive their asymptotic distributions uniformly over a compact set of quantile indexes, and show that, when the treatment assignment rule does not achieve strong balance, the inverse propensity score weighted estimator has a smaller asymptotic variance than the simple quantile regression estimator. For the inference of method (1), we show that the Wald test using a weighted bootstrap standard error underrejects. But for method (2), its asymptotic size equals the nominal level. We also show that, for both methods, the asymptotic size of the Wald test using a covariate-adaptive bootstrap standard error equals the nominal level. We illustrate the finite sample performance of the new estimation and inference methods using both simulated and real datasets.
This paper proposes a new model selection test for the statistical comparison of semi/non-parametric models based on a general quasi-likelihood ratio criterion. An important feature of the new test is its uniformly exact asymptotic size in the overlapping nonnested case, as well as in the easier nested and strictly nonnested cases. The uniform size control is achieved without using pretesting, sample-splitting, or simulated critical values. We also show that the test has nontrivial power against all -local alternatives and against some local alternatives that converge to the null faster than . Finally, we provide a framework for conducting uniformly valid post model selection inference for model parameters. The finite sample performance of the nondegenerate test and that of the post model selection inference procedure are illustrated in a mean-regression example by Monte Carlo.
We provide a comprehensive treatment for the problem of testing jointly for structural changes in both the regression coefficients and the variance of the errors in a single equation system involving stationary regressors. Our framework is quite general in that we allow for general mixing-type regressors and the assumptions on the errors are quite mild. Their distribution can be nonnormal and conditional heteroskedasticity is permitted. Extensions to the case with serially correlated errors are also treated. We provide the required tools to address the following testing problems, among others: (a) testing for given numbers of changes in regression coefficients and variance of the errors; (b) testing for some unknown number of changes within some prespecified maximum; (c) testing for changes in variance (regression coefficients) allowing for a given number of changes in the regression coefficients (variance); (d) a sequential procedure to estimate the number of changes present. These testing problems are important for practical applications as witnessed by interests in macroeconomics and finance where documenting structural changes in the variability of shocks to simple autoregressions or vector autoregressive models have been a concern.
In this paper, we investigate the causes and consequences of “unclaimed” unemployment insurance (UI) benefits. A search model is developed where the costs to collecting UI benefits include both a traditional “fixed” administrative cost and an endogenous cost arising from worker and firm interactions. Experience rated taxes give firms an incentive to challenge a worker's UI claim, and these challenges are costly for the worker. Exploiting data on improper denials of UI benefits across states in the U.S. system, a two-way fixed effects analysis shows a statistically significant negative relationship between the improper denials and the UI take-up rate, providing empirical support for our model. We calibrate the model to elasticities implied by the two-way fixed effects regression to quantify the relative size of these UI collection costs. The results imply that on average the costs associated with firm challenges of UI claims account for 41% of the total costs of collecting, with improper denials accounting for 8% of the total cost. The endogenous collection costs imply the unemployment rate responds much slower to changes in UI benefits relative to a model with fixed collection costs. Finally, removing all eligibility requirements and allowing workers to collect UI benefits without cost shows these costs to be 4.5% of expected output net of vacancy costs. Moreover, this change has minimal impact on the unemployment rate.
This paper aims to fill the gaps in the analysis of risk-sharing channels at the microlevel, both within and across households. Using data from the Bank of Italy's Survey on Household Income and Wealth covering the financial crisis, we are able to quantify in a unified and consistent framework several risk-sharing mechanisms that so far have been documented separately. We find that Italian households were able to smooth on average about 85% of shocks to household head's earnings in both 2008–2010 and 2010–2012 spells. The most important smoothing mechanisms turn out to be self-insurance through savings/dissavings (40% and 47% in 2008–2010 and 2010–2012, respectively), and within-household risk-sharing (16% and 14%). Interestingly, risk-sharing through portfolio diversification and private transfers is rather limited, but the overall percentage of shock absorption occurring through private risk-sharing channels hovers around four-fifths, as opposed to around one-fifth of a shock cushioned by taxes and public transfers, excluding pensions. In addition, by exploiting subjective expectations on the following year's household income, we find significant evidence of a lower degree of smoothing of persistent shocks.
We use data from a large US life expectancy provider to test for asymmetric information in the secondary life insurance—or life settlements—market. We compare realized lifetimes for a subsample of settled policies relative to all (settled and nonsettled) policies, and find a positive settlement-survival correlation indicating the existence of informational asymmetry between policyholders and investors. Estimates of the “excess hazard” associated with settling show the effect is temporary and wears off over approximately 8 years. This indicates individuals in our sample possess private information with regards to their near-term survival prospects and make use of it, which has economic consequences for this market and beyond.
We propose a new category of consumption goods, memorable goods, that generate a utility flow even after physical consumption. Empirically, memorable goods expenditures exhibit frequent zero monthly purchases and lumpy expenditure spikes. Memorable goods expenditures are 20% the size of nondurable expenditures, but three times as volatile. We then develop a consumption-savings model with borrowing constraints and income risk that formalizes the notion of memorable goods and distinguishes them from other nondurable goods. We show that consumers optimally choose lumpy consumption of memorable goods. We then measure the welfare cost of consumption fluctuations using our calibrated model and empirically evaluate our calibrated model's predictions for the consumption response to predictable income changes. We find that the welfare cost of household-level consumption fluctuations induced by income shocks fall from 20.4 to 12.3 percentage points if memorable goods are accounted for, and that empirical estimates of excess sensitivity of consumption may significantly be driven by memorable goods expenditures.
We consider discrete-time dynamic principal–agent problems with continuous choice sets and potentially multiple agents. We prove the existence of a unique solution for the principal's value function only assuming continuity of the functions and compactness of the choice sets. We do this by a contraction mapping theorem and so also obtain a convergence result for the value function iteration. To numerically compute a solution for the problem, we have to solve a collection of static principal–agent problems at each iteration. As a result, in the discrete-time setting solving the static problem is the difficult step. If the agent's expected utility is a rational function of his action, then we can transform the bi-level optimization problem into a standard nonlinear program. The final results of our solution method are numerical approximations of the policy and value functions for the dynamic principal–agent model. We illustrate our solution method by solving variations of two prominent social planning models from the economics literature.
This paper describes a method for solving heterogeneous agent models with aggregate risk and many idiosyncratic states formulated in discrete time. It extends the method proposed by Reiter (2009) and complements recent work by Ahn, Kaplan, Moll, Winberry, and Wolf (2017) on how to solve such models in continuous time. We suggest first solving for the stationary equilibrium of the model without aggregate risk. We then write the functionals that describe the dynamic equilibrium as sparse expansions around their stationary equilibrium counterparts. Finally, we use the perturbation method of Schmitt-Grohé and Uribe (2004) to approximate the aggregate dynamics of the model.
We consider a class of infinite-horizon dynamic Markov economic models in which the parameters of utility function, production function, and transition equations change over time. In such models, the optimal value and decision functions are time-inhomogeneous: they depend not only on state but also on time. We propose a quantitative framework, called extended function path (EFP), for calibrating, solving, simulating, and estimating such nonstationary Markov models. The EFP framework relies on the turnpike theorem which implies that the finite-horizon solutions asymptotically converge to the infinite-horizon solutions if the time horizon is sufficiently large. The EFP applications include unbalanced stochastic growth models, the entry into and exit from a monetary union, information news, anticipated policy regime switches, deterministic seasonals, among others. Examples of MATLAB code are provided.
Counterfactual policy evaluation often requires computation of game-theoretic equilibria. We provide new algorithms for computing pure-strategy Nash equilibria of games on networks with finite action spaces. The algorithms exploit the fact that many agents may be endowed with types such that a particular action is a dominant strategy. These agents can be used to partition the network into smaller subgames whose equilibrium sets may be more feasible to compute. We provide bounds on the complexity of our algorithms for models obeying certain restrictions on the strength of strategic interactions. These restrictions are analogous to the assumption in the widely used linear-in-means model of social interactions that the magnitude of the endogenous peer effect is bounded below one. For these models, our algorithms have complexity Op(nc), where the randomness is with respect to the data-generating process, n is the number of agents, and c depends on the strength of strategic interactions. We also provide algorithms for computing pairwise stable and directed Nash stable networks in network formation games.
We model network formation and interactions under a unified framework by considering that individuals anticipate the effect of network structure on the utility of network interactions when choosing links. There are two advantages of this modeling approach: first, we can evaluate whether network interactions drive friendship formation or not. Second, we can control for the friendship selection bias on estimated interaction effects. We provide microfoundations of this statistical model based on the subgame perfect equilibrium of a two-stage game and propose a Bayesian MCMC approach for estimating the model. We apply the model to study American high school students' friendship networks using the Add Health dataset. From two interaction variables, GPA and smoking frequency, we find that the utility of interactions in academic learning is important for friendship formation, whereas the utility of interactions in smoking is not. However, both GPA and smoking frequency are subject to significant peer effects.
We study potential impacts of future climate change on U.S. agricultural productivity using county-level yield and weather data from 1950 to 2015. To account for adaptation of production to different weather conditions, it is crucial to allow for both spatial and temporal variation in the production process mapping weather to crop yields. We present a new panel data estimation technique, called mean observation OLS (MO-OLS) that allows for spatial and temporal heterogeneity in all regression parameters (intercepts and slopes). Both forms of heterogeneity are important: We find strong evidence that production function parameters adapt to local climate, and also that sensitivity of yield to high temperature declined from 1950–89. We use our estimates to project corn yields to 2100 using 19 climate models and three greenhouse gas emission scenarios. We predict unmitigated climate change will greatly reduce yield. Our mean prediction (over climate models) is that adaptation alone can mitigate 36% of the damage, while emissions reductions consistent with the Paris targets would mitigate 76%.
We propose and estimate a model of family job search and wealth accumulation with data from the Survey of Income and Program Participation (SIPP). This dataset reveals a very asymmetric labor market for household members who share that their job finding is stimulated by their partners' job separation. We uncover a job search-theoretic basis for this added worker effect, which occurs mainly during economic downturns, but also by increased nonemployment transfers. Thus, our analysis shows that the policy goal of increasing nonemployment transfers to support a worker's job search is partially offset by the spouse's cross effect of decreased nonemployment and wages. The added worker effect is robust to having more children and more education in the household and does not just result as a composition of heterogeneous individuals. We also show that the interdependency between household members is understated if wealth and savings are not considered. Finally, we show that gender equality in the labor market not only improves women's labor market performance, but it also increases men's accepted wages and nonemployment rates.
Gaussian affine term structure models attribute time-varying bond risk premia to changing risk prices driven by the conditional means of the risk factors, while structural models with recursive preferences credit it to stochastic volatility. We reconcile these competing channels by introducing a novel form of stochastic rate of time preference into an otherwise standard model with recursive preferences. Our model is affine and has analytical bond prices making it empirically tractable. We use particle Markov chain Monte Carlo to estimate the model, and find that time variation in bond term premia is predominantly driven by the risk price channel.
This paper studies the joint dynamics of U.S. inflation and a term structure of average inflation predictions taken from the Survey of Professional Forecasters (SPF). We estimate these joint dynamics by combining an unobserved components (UC) model of inflation and a sticky-information forecast mechanism. The UC model decomposes inflation into trend and gap components, and innovations to trend and gap inflation are affected by stochastic volatility. A novelty of our model is to allow for time-variation in inflation-gap persistence as well as in the frequency of forecast updating under sticky information. The model is estimated with sequential Monte Carlo methods that include a particle learning filter and a Rao–Blackwellized particle smoother. Based on data from 1968Q4 to 2018Q3, estimates show that (i) longer horizon average SPF inflation predictions inform estimates of trend inflation; (ii) inflation gap persistence is countercyclical before the Volcker disinflation and acyclical afterwards; (iii) by 1990 sticky-information inflation forecast updating is less frequent than it was earlier in the sample; and (iv) the drop in the frequency of the sticky-information forecast updating occurs at the same time persistent shocks become less important for explaining movements in inflation. Our findings support the view that stickiness in survey forecasts is not invariant to the inflation process.
We propose to add ranking restrictions on impulse-responses to sign restrictions to narrow the identified set in vector autoregressions (VARs). Ranking restrictions come from micro data on heterogeneous industries in VARs, bounds on elasticities, or restrictions on dynamics. Using both a fully Bayesian conditional uniform prior and prior-robust inference, we show that these restrictions help to identify productivity news shocks in the data. In the prior-robust paradigm, ranking restrictions, but not sign restrictions alone, imply that news shocks raise output temporarily, but significantly. This holds both in an application with rankings in the form of heterogeneity restrictions and in another applications with slope restrictions as rankings. Ranking restrictions also narrow bounds on variance decompositions. For example, the bound of the contribution of news shocks to the forecast error variance of output narrows by about 30 pp at the one-year horizon. While misspecification can be a concern with added restrictions, they are consistent with the data in our applications.
Existing methods for estimating nonlinear dynamic models are either highly computationally costly or rely on local approximations which often fail adequately to capture the nonlinear features of interest. I develop a new method, the discretization filter, for approximating the likelihood of nonlinear, non-Gaussian state space models. I establish that the associated maximum likelihood estimator is strongly consistent, asymptotically normal, and asymptotically efficient. Through simulations, I show that the discretization filter is orders of magnitude faster than alternative nonlinear techniques for the same level of approximation error in low-dimensional settings and I provide practical guidelines for applied researchers. It is my hope that the method's simplicity will make the quantitative study of nonlinear models easier for and more accessible to applied researchers. I apply my approach to estimate a New Keynesian model with a zero lower bound on the nominal interest rate. After accounting for the zero lower bound, I find that the slope of the Phillips Curve is 0.076, which is less than 1/3 of typical estimates from linearized models. This suggests a strong decoupling of inflation from the output gap and larger real effects of unanticipated changes in interest rates in post Great Recession.
We consider inference in models defined by approximate moment conditions. We show that near-optimal confidence intervals (CIs) can be formed by taking a generalized method of moments (GMM) estimator, and adding and subtracting the standard error times a critical value that takes into account the potential bias from misspecification of the moment conditions. In order to optimize performance under potential misspecification, the weighting matrix for this GMM estimator takes into account this potential bias and, therefore, differs from the one that is optimal under correct specification. To formally show the near-optimality of these CIs, we develop asymptotic efficiency bounds for inference in the locally misspecified GMM setting. These bounds may be of independent interest, due to their implications for the possibility of using moment selection procedures when conducting inference in moment condition models. We apply our methods in an empirical application to automobile demand, and show that adjusting the weighting matrix can shrink the CIs by a factor of 3 or more.
Kotlarski's identity has been widely used in applied economic research based on repeated-measurement or panel models with latent variables. However, how to conduct inference for these models has been an open question for two decades. This paper addresses this open problem by constructing a novel confidence band for the density function of a latent variable in repeated measurement error model. The confidence band builds on our finding that we can rewrite Kotlarski's identity as a system of linear moment restrictions. Our approach is robust in that we do not require the completeness. The confidence band controls the asymptotic size uniformly over a class of data generating processes, and it is consistent against all fixed alternatives. Simulation studies support our theoretical results.
We bound the distribution of treatment effects under plausible and testable assumptions on the joint distribution of potential outcomes, namely that potential outcomes are mutually stochastically increasing. We show how to test the empirical restrictions implied by those assumptions. The resulting bounds substantially sharpen bounds based on classical inequalities. We apply our method to estimate bounds on the distribution of effects of attending a Knowledge is Power Program (KIPP) charter school on student achievement, and find that a substantial majority of students' math achievement benefited from attendance, especially those who would have fared poorly in a traditional classroom.
I use administrative and survey data from Chile and a structural model to evaluate teacher policies in a market-based school system. The model accommodates equilibrium effects on parental sorting across school sectors (public or private), on the self-selection of individuals into teaching and across school sectors, and on teacher wages in private schools. I use the estimated model to simulate a reform that is planned to be implemented in Chile in 2023. Tying public school teacher wages to teacher skills and introducing minimum competency requirements for teaching is predicted to increase student test scores by 0.30 standard deviations and decrease the achievement gap between the poorest and richest 25% of students by a third. These impacts are ten times as large as the impact of a flat wage increase in public schools, and over twice as large as the impact of only introducing minimum competency requirements. The key driver of policy outcomes is an improvement in the pool of teachers, amplified by equilibrium effects on teacher wages in private schools. The equilibrium effects are large, accounting for 70% of estimated policy impacts.
This paper studies the savings and employment effects of the asset means-test in US income support programs using a structural life-cycle model with productivity, disability, and unemployment risk. An asset means-test incentivizes low-income households to hold few financial assets making them vulnerable to predictable and unpredictable income changes. Moreover, it incentivizes relatively productive households that happen to have few financial assets to leave the labor force. However, it allows for relative generous transfers to households in most need. Moreover, it counteracts relatively productive households leaving the labor force after the age of 50. In terms of the welfare of an unborn household, the asset means-test that optimally trades off these effects is $150,000, and abolishing it is close to optimal.
Experimenters make theoretically irrelevant decisions concerning user interfaces and ordering or labeling of options. Reanalyzing dictator games, I first show that such decisions may drastically affect comparative statics and cause results to appear contradictory across experiments. This obstructs model testing, preference analyses, and policy predictions. I then propose a simple model of choice incorporating both presentation effects and stochastic errors, and test the model by reanalyzing the dictator game experiments. Controlling for presentation effects, preference estimates become consistent across experiments and predictive out-of-sample. This highlights both the necessity and the possibility to control for presentation in economic experiments.
We study games with natural-language labels (i.e., strategic problems where options are denoted by words), for which we propose and test a measurable characterization of prominence. We assume that—ceteris paribus—players find particularly prominent those strategies that are denoted by words more frequently used in their everyday language. To operationalize this assumption, we suggest that the prominence of a strategy-label is correlated with its frequency of occurrence in large text corpora, such as the Google Books corpus (“n-gram” frequency). In testing for the strategic use of word frequency, we consider experimental games with different incentive structures (such as incentives to and not to coordinate), as well as subjects from different cultural/linguistic backgrounds. Our data show that frequently-mentioned labels are more (less) likely to be selected when there are incentives to match (mismatch) others. Furthermore, varying one's knowledge of the others' country of residence significantly affects one's reliance on word frequency. Overall, the data show that individuals play strategies that fulfill our characterization of prominence in a (boundedly) rational manner.
We consider a set of potentially misspecified structural models, geometrically combine their likelihood functions, and estimate the parameters using composite methods. In a Monte Carlo study, composite estimators dominate likelihood-based estimators in mean squared error and composite models are superior to individual models in the Kullback–Leibler sense. We describe Bayesian quasi-posterior computations and compare our approach to Bayesian model averaging, finite mixture, and robust control procedures. We robustify inference using the composite posterior distribution of the parameters and the pool of models. We provide estimates of the marginal propensity to consume and evaluate the role of technology shocks for output fluctuations.
Dynamic discrete choice (DDC) models are not identified nonparametrically, but the non-identification of models does not necessarily imply the nonidentification of counterfactuals. We derive novel results for the identification of counterfactuals in DDC models, such as non-additive changes in payoffs or changes to agents' choice sets. In doing so, we propose a general framework that allows the investigation of the identification of a broad class of counterfactuals (covering virtually any counterfactual encountered in applied work). To illustrate the results, we consider a firm entry/exit problem numerically, as well as an empirical model of agricultural land use. In each case, we provide examples of both identified and nonidentified counterfactuals of interest.
We consider inference about a scalar coefficient in a linear regression model. One previously considered approach to dealing with many controls imposes sparsity, that is, it is assumed known that nearly all control coefficients are (very nearly) zero. We instead impose a bound on the quadratic mean of the controls' effect on the dependent variable, which also has an interpretation as an R2-type bound on the explanatory power of the controls. We develop a simple inference procedure that exploits this additional information in general heteroskedastic models. We study its asymptotic efficiency properties and compare it to a sparsity-based approach in a Monte Carlo study. The method is illustrated in three empirical applications.
The instrumental variable quantile regression (IVQR) model (Chernozhukov and Hansen (2005)) is a popular tool for estimating causal quantile effects with endogenous covariates. However, estimation is complicated by the nonsmoothness and nonconvexity of the IVQR GMM objective function. This paper shows that the IVQR estimation problem can be decomposed into a set of conventional quantile regression subproblems which are convex and can be solved efficiently. This reformulation leads to new identification results and to fast, easy to implement, and tuning-free estimators that do not require the availability of high-level “black box” optimization routines.
This paper examines New York City's Summer Youth Employment Program (SYEP). SYEP provides jobs to youth ages 14–24, and due to high demand for summer jobs, allocates slots through a random lottery system. We match student-level data from the SYEP program with educational records from the NYC Department of Education and use the random lottery to estimate the effects of SYEP participation on a number of academic outcomes, including test taking and performance. We find that SYEP participation has positive impacts on student academic outcomes, and these effects are particularly large for students who participate in SYEP multiple times.
Do individuals marry and divorce for economic reasons? Can we measure the economic attractiveness of a person's marriage market? We answer these questions using a structural model of consumer-producer households that is applied to rich data from Malawi. Using revealed preference conditions for a stable marriage market, we define the economic attractiveness of a potential match as the difference between the potential value of consumption and leisure with the new partner and the value of consumption and leisure in the current marriage. We estimate this marital instability measure for every possible pair in geographically defined marriage markets in 2010. We find that the marital instability measure is predictive of future divorces, particularly for women. We further show that this estimated effect on divorce is mitigated by the woman's age, and by a lack of men, relative to women, in the marriage market, showing that these factors interact with the economic attractiveness of the remarriage market. These findings provide out-of-sample validation of our model and evidence that the economic value of the marriage market matters for divorce decisions.
Three features of real-life reforms of dual employment protection legislation (EPL) systems are particularly hard to study through the lens of standard labor-market search models: (i) the excess job turnover implied by dual EPL, (ii) the nonretroactive nature of EPL reforms, and (iii) the transition dynamics from dual to a unified EPL system. In this paper, we develop a computationally tractable model addressing these issues. Our main finding is that the welfare gains of reforming a dual EPL system are sizeable and achieved mostly through a decrease in turnover at short job tenures. This conclusion continues to hold in more general settings featuring wage rigidities, heterogeneity in productivity upon matching, and human capital accumulation. We also find substantial cross-sectional heterogeneity in welfare effects along the transition to a unified EPL scheme. Given that the model is calibrated to data from Spain, often considered as the epitome of a labor market with dual EPL, our results should provide guidance for a wide range of reforms of dual EPL systems.
Precautionary pricing and increasing markups in representative-agent DSGE models with nominal rigidities are commonly used to generate negative output effects of uncertainty shocks. We assess whether this theoretical model channel is consistent with the data. Three things stand out. First, consistent with precautionary wage setting, we find that wage markups increase after uncertainty shocks. Second, the impulse responses of price markups are largely inconsistent with the standard model, both at the aggregate as well as the industry level. Finally, and in contrast to times-series evidence, our theoretical model robustly predicts that uncertainty shocks have a quantitatively small impact on the economy.
In Merton (1987), idiosyncratic risk is priced in equilibrium as a consequence of incomplete diversification. We modify his model to allow the degree of diversification to vary with average idiosyncratic volatility. This simple recognition results in a state-dependent idiosyncratic risk premium that is higher when average idiosyncratic volatility is low, and vice versa. The data appear to be consistent a positive state-dependent premium for idiosyncratic risk both in the US and other developed markets.
We study the temporal behavior of the cross-sectional distribution of assets' market exposure, or betas, using a large panel of high-frequency returns. The asymptotic setup has the sampling frequency of returns increasing to infinity, while the time span of the data remains fixed, and the cross-sectional dimension of the panel is either fixed or increasing. We derive functional limit results for the cross-sectional distribution of betas evolving over time. We demonstrate, for constituents of the S&P 500 market index, that the dispersion in betas is elevated at the market open and gradually declines over the trading day. This intraday pattern varies significantly over time and reacts to information shocks such as clustered earning announcements and releases of macroeconomic news. We find that earnings news increase beta dispersion while FOMC announcements have the opposite effect on market betas.
We propose generalized DWH specification tests which simultaneously compare three or more likelihood-based estimators in multivariate conditionally heteroskedastic dynamic regression models. Our tests are useful for Garch models and in many empirically relevant macro and finance applications involving Vars and multivariate regressions. We determine the rank of the differences between the estimators' asymptotic covariance matrices under correct specification, and take into account that some parameters remain consistently estimated under distributional misspecification. We provide finite sample results through Monte Carlo simulations. Finally, we analyze a structural Var proposed to capture the relationship between macroeconomic and financial uncertainty and the business cycle.
We explore inference on regression coefficients in semiparametric multinomial response models. We consider cross-sectional, and both static and dynamic panel settings where we focus throughout on inference under sufficient conditions for point identification. The approach to identification uses a matching insight throughout all three models coupled with variation in regressors: with cross-section data, we match across individuals while with panel data, we match within individuals over time. Across models, we relax the Indpendence of Irrelevant Alternatives (or IIA assumption, see McFadden (1974)) and allow for arbitrary correlation in the unobservables that determine utility of various alternatives. For the cross-sectional model, estimation is based on a localized rank objective function, analogous to that used in Abrevaya, Hausman, and Khan (2010), and presents a generalization of existing approaches. In panel data settings, rates of convergence are shown to exhibit a curse of dimensionality in the number of alternatives. The results for the dynamic panel data model generalize the work of Honoré and Kyriazidou (2000) to cover the semiparametric multinomial case. A simulation study establishes adequate finite sample properties of our new procedures. We apply our estimators to a scanner panel data set.
This paper presents a weighted optimization framework that unifies the binary, multivalued, and continuous treatment—as well as mixture of discrete and continuous treatment—under a unconfounded treatment assignment. With a general loss function, the framework includes the average, quantile, and asymmetric least squares causal effect of treatment as special cases. For this general framework, we first derive the semiparametric efficiency bound for the causal effect of treatment, extending the existing bound results to a wider class of models. We then propose a generalized optimization estimator for the causal effect with weights estimated by solving an expanding set of equations. Under some sufficient conditions, we establish the consistency and asymptotic normality of the proposed estimator of the causal effect and show that the estimator attains the semiparametric efficiency bound, thereby extending the existing literature on efficient estimation of causal effect to a wider class of applications. Finally, we discuss estimation of some causal effect functionals such as the treatment effect curve and the average outcome. To evaluate the finite sample performance of the proposed procedure, we conduct a small-scale simulation study and find that the proposed estimation has practical value. In an empirical application, we detect a significant causal effect of political advertisements on campaign contributions in the binary treatment model, but not in the continuous treatment model.
In this paper, we build a new test of rational expectations based on the marginal distributions of realizations and subjective beliefs. This test is widely applicable, including in the common situation where realizations and beliefs are observed in two different data sets that cannot be matched. We show that whether one can rationalize rational expectations is equivalent to the distribution of realizations being a mean-preserving spread of the distribution of beliefs. The null hypothesis can then be rewritten as a system of many moment inequality and equality constraints, for which tests have been recently developed in the literature. The test is robust to measurement errors under some restrictions and can be extended to account for aggregate shocks. Finally, we apply our methodology to test for rational expectations about future earnings. While individuals tend to be right on average about their future earnings, our test strongly rejects rational expectations.
We propose a novel approach to deal with the problem of indeterminacy in linear rational expectations models. The method consists of augmenting the original state space with a set of auxiliary exogenous equations to provide the adequate number of explosive roots in presence of indeterminacy. The solution in this expanded state space, if it exists, is always determinate, and is identical to the indeterminate solution of the original model. The proposed approach accommodates determinacy and any degree of indeterminacy, and it can be implemented even when the boundaries of the determinacy region are unknown. Thus, the researcher can estimate the model using standard software packages without restricting the estimates to the determinacy region. We combine our solution method with a novel hybrid Metropolis–Hastings algorithm to estimate the New–Keynesian model with rational bubbles by Galí (2021) over the period 1982:Q4–2007:Q3. We find that the data support the presence of two degrees of indeterminacy, implying that the central bank was not reacting strongly enough to the bubble component.
Unlike linear ones, nonlinear business cycle models can generate sustained fluctuations even in the absence of shocks (e.g., via limit cycles/chaos). A popular approach to solving nonlinear models is perturbation methods. I show that, as typically implemented, these methods are incapable of finding solutions featuring limit cycles or chaos. Fundamentally, solutions are only required not to explode, while standard perturbation algorithms seek solutions that meet the stronger requirement of convergence to the steady state. I propose a modification to standard algorithms that does not impose this overly strong requirement.
This study compares and contrasts the multiple characterizations of mean reversion in financial time series as regards the restrictions they imply. This is accomplished by translating them into statements about an alternative measure, the “Average Crossing Time” or ACT. We argue that the ACT measure, per se, provides not only a useful benchmark for the degree of mean reversion/aversion, but also an intuitive, and easily quantified sense of one time series being “more strongly mean-reverting/averting” than another. We conclude our discussion by deriving the ACT measure for a wide class of stochastic processes and detailing its statistical characteristics. Our analysis is principally undertaken within a class of well-understood production based asset pricing models.
Bullying cannot be tolerated as a normal social behavior portraying a child's life. This paper quantifies its negative consequences allowing for the possibility that victims and nonvictims differ in unobservable characteristics. To this end, we introduce a factor analytic model for identifying treatment effects of bullying in which latent cognitive and noncognitive skills determine victimization and multiple outcomes. We use early test scores to identify the distribution of these skills. Individual-, classroom- and district-level variables are also accounted for. Applying our method to longitudinal data from South Korea, we first show that while noncognitive skills reduce the chances of being bullied during middle school, the probability of being victimized is greater in classrooms with relatively high concentration of boys, previously self-assessed bullies and students that come from violent families. We report bullying at age 15 has negative effects on physical and mental health outcomes at age 18. We also uncover heterogeneous effects by latent skills, from which we document positive effects on the take-up of risky behaviors and negative effects on schooling attainment. Our findings suggest that investing in noncognitive development should guide policy efforts intended to deter this problematic behavior.
Using data on essentially every U.S. Supreme Court decision since 1946, we estimate a model of peer effects on the Court. We estimate the impact of justice ideology and justice votes on the votes of their peers. To identify the peer effects, we use two instruments that generate plausibly exogenous variation in the peer group itself, or in the votes of peers. The first instrument utilizes the fact that the composition of the Court varies from case to case due to recusals or absences for health reasons. The second utilizes the fact that many justices previously sat on Federal Circuit Courts, and justices are generally much less likely to overturn decisions in cases sourced from their former “home” court. We find large peer effects. For example, we can use our model to predict the impact of replacing Justice Ginsburg with Justice Barrett. Under the the assumption that Justice Barrett's ideological position aligns closely with Justice Scalia, for whom she clerked, we predict that her influence on the Court will increase the Conservative vote propensity of the other justices by 4.7 percentage points. That translates into 0.38 extra conservative votes per case on top of the impact of her own vote. In general, we find indirect effects are large relative to the direct mechanical effect of a justice's own vote.
We experimentally implement a dynamic public-good problem, where the public good in question is the dynamically evolving information about agents' common state of the world. Subjects' behavior is consistent with free-riding because of strategic concerns. We also find that subjects adopt more complex behaviors than predicted by the welfare-optimal equilibrium, such as noncut-off behavior, lonely pioneers, and frequent switches of action.
We present a new theory for the conduct of nonparametric inference about the latent spot volatility of a semimartingale asset price process. In contrast to existing theories based on the asymptotic notion of an increasing number of observations in local estimation blocks, our theory treats the estimation block size k as fixed. While the resulting spot volatility estimator is no longer consistent, the new theory permits the construction of asymptotically valid and easy-to-calculate pointwise confidence intervals for the volatility at any given point in time. Extending the theory to a high-dimensional inference setting with a growing number of estimation blocks further permits the construction of uniform confidence bands for the volatility path. An empirically realistically calibrated simulation study underscores the practical reliability of the new inference procedures. An empirical application based on intraday data for the S&P 500 equity index reveals highly significant abrupt changes, or jumps, in the market volatility at FOMC news announcement times, validating recent uses of various high-frequency-based identification schemes in asset pricing finance and monetary economics.
We propose a new approach to analyze economic shocks. Our new procedure identifies economic shocks as exogenous shifts in a function; hence, we call them “functional shocks.” We show how to identify such shocks and how to trace their effects in the economy via VARs using “VARs with functional shocks” and “functional local projections.” Using our new procedure, we address the crucial question of studying the effects of monetary policy by identifying monetary policy shocks as shifts in the whole term structure of government bond yields in a narrow window of time around monetary policy announcements. Our approach sheds new light on the effects of monetary policy shocks, both in conventional and unconventional periods, and shows that traditional identification procedures may miss important effects. Our new procedure has the advantage of identifying monetary policy shocks during both conventional and unconventional monetary policy periods in a unified manner and can be applied more generally to other economic shocks.
Using a Markov-switching VAR, we show that the effects of uncertainty shocks on output are four times higher in a regime of economic distress than in a tranquil regime. We then provide a structural interpretation of these facts. To do so, we develop a business cycle model in which agents are aware of the possibility of regime changes when forming expectations. The model is estimated using a Bayesian minimum distance estimator that minimizes, over the set of structural parameters, the distance between the regime-switching VAR-based impulse response functions and those implied by the model. Our results point to worsening credit-market conditions that amplify shocks during distress periods. Finally, we show that the expectation effect of regime switching in financial conditions is an important component of the financial accelerator mechanism. If agents are more pessimistic about future financial conditions, then the output effects of shocks are amplified.
In panel experiments, we randomly assign units to different interventions, measuring their outcomes, and repeating the procedure in several periods. Using the potential outcomes framework, we define finite population dynamic causal effects that capture the relative effectiveness of alternative treatment paths. For a rich class of dynamic causal effects, we provide a nonparametric estimator that is unbiased over the randomization distribution and derive its finite population limiting distribution as either the sample size or the duration of the experiment increases. We develop two methods for inference: a conservative test for weak null hypotheses and an exact randomization test for sharp null hypotheses. We further analyze the finite population probability limit of linear fixed effects estimators. These commonly-used estimators do not recover a causally interpretable estimand if there are dynamic causal effects and serial correlation in the assignments, highlighting the value of our proposed estimator.
We analyze the properties of the Synthetic Control (SC) and related estimators when the pre-treatment fit is imperfect. In this framework, we show that these estimators are generally biased if treatment assignment is correlated with unobserved confounders, even when the number of pre-treatment periods goes to infinity. Still, we show that a demeaned version of the SC method can improve in terms of bias and variance relative to the difference-in-difference estimator. We also derive a specification test for the demeaned SC estimator in this setting with imperfect pre-treatment fit. Given our theoretical results, we provide practical guidance for applied researchers on how to justify the use of such estimators in empirical applications.
Imposing equilibrium restrictions provides substantial gains in the estimation of dynamic discrete games. Estimation algorithms imposing these restrictions have different merits and limitations. Algorithms that guarantee local convergence typically require the approximation of high-dimensional Jacobians. Alternatively, the Nested Pseudo-Likelihood (NPL) algorithm is a fixed-point iterative procedure, which avoids the computation of these matrices, but—in games—may fail to converge to the consistent NPL estimator. In order to better capture the effect of iterating the NPL algorithm in finite samples, we study the asymptotic properties of this algorithm for data generating processes that are in a neighborhood of the NPL fixed-point stability threshold. We find that there are always samples for which the algorithm fails to converge, and this introduces a selection bias. We also propose a spectral algorithm to compute the NPL estimator. This algorithm satisfies local convergence and avoids the approximation of Jacobian matrices. We present simulation evidence and an empirical application illustrating our theoretical results and the good properties of the spectral algorithm.
Prominent features of differentiated product markets are segmentation and product proliferation blurring the boundaries between segments. I develop a tractable demand model, the Ordered Nested Logit, which allows for asymmetric substitution between segments. I apply the model to the automobile market where segments are ordered from small to luxury. I find that consumers, when substituting outside their vehicle segment, are more likely to switch to a neighboring segment. Accounting for such asymmetric substitution matters when evaluating the impact of new product introduction or the effect of subsidies on fuel-efficient cars.
Researchers and policy makers have explored the possibility of restricting the use of housing vouchers to neighborhoods that may positively affect the outcomes of children. Using the framework of a dynamic model of optimal location choice, we estimate preferences over neighborhoods of likely recipients of housing vouchers in Los Angeles. We combine simulations of the model with estimates of how locations affect adult earnings of children to understand how a voucher policy that restricts neighborhoods in which voucher-recipients may live affects both the location decisions of households and the adult earnings of children. We show the model can nearly replicate the impact of the Moving to Opportunity experiment on the adult wages of children. Simulations suggest a policy that restricts housing vouchers to the top 20% of neighborhoods maximizes expected aggregate adult earnings of children of households offered these vouchers.
Elite college attendance significantly impacts students' entrepreneurship decisions and career dynamics. We find that an elite college degree is positively correlated with entrepreneurship (i.e., owning an incorporated business) but not with other self-employment forms. Our overlapping generations model captures self-selection in education and career choices based on heterogeneous ability and family wealth endowments over the life cycle. Our estimates show that (1) entrepreneurs and other self-employed individuals require different types of human capital, and (2) elite colleges generate considerably more human capital gain than ordinary colleges, particularly for entrepreneurs. Distinguishing between elite and ordinary colleges improves our prediction of entrepreneurship decisions. Providing subsidies for elite colleges is more efficient than subsidizing their ordinary counterparts to encourage entrepreneurship, enhance intergenerational mobility, and enhance welfare. In contrast, although start-up subsidy increases entrepreneurship, it does not improve their performance, and it is inferior to education subsidy in generating efficiency, equality, and intergenerational mobility.
We set up a model with on-the-job search in which firms infrequently post vacancies for which workers occasionally apply. The model nests the standard job ladder and stock-flow models as special cases, while remaining analytically tractable and easy to estimate from standard panel data sets. The parameters from a structurally estimated model on US data are significantly different from either the restrictions imposed by a stock-flow or job ladder model. Imposing these restrictions significantly understates the search option associated with employment and are, unlike our model, inconsistent with recent survey evidence and declining job finding rates and starting wage with duration of unemployment, both of which are present in the data.
We propose a new specification test for assessing the validity of fuzzy regression discontinuity designs (FRD-validity). We derive a new set of testable implications, characterized by a set of inequality restrictions on the joint distribution of observed outcomes and treatment status at the cut-off. We show that this new characterization exploits all of the information in the data that is useful for detecting violations of FRD-validity. Our approach differs from and complements existing approaches that test continuity of the distributions of running variables and baseline covariates at the cut-off in that we focus on the distribution of the observed outcome and treatment status. We show that the proposed test has appealing statistical properties. It controls size in a large sample setting uniformly over a large class of data generating processes, is consistent against all fixed alternatives, and has non-trivial power against some local alternatives. We apply our test to evaluate the validity of two FRD designs. The test does not reject FRD-validity in the class size design studied by Angrist and Lavy (1999) but rejects it in the insurance subsidy design for poor households in Colombia studied by Miller, Pinto, and Vera-Hernández (2013) for some outcome variables. Existing density continuity tests suggest the opposite in each of the two cases.
There are many economic parameters that depend on nonparametric first steps. Examples include games, dynamic discrete choice, average exact consumer surplus, and treatment effects. Often estimators of these parameters are asymptotically equivalent to a sample average of an object referred to as the influence function. The influence function is useful in local policy analysis, in evaluating local sensitivity of estimators, and constructing debiased machine learning estimators. We show that the influence function is a Gateaux derivative with respect to a smooth deviation evaluated at a point mass. This result generalizes the classic Von Mises (1947) and Hampel (1974) calculation to estimators that depend on smooth nonparametric first steps. We give explicit influence functions for first steps that satisfy exogenous or endogenous orthogonality conditions. We use these results to generalize the omitted variable bias formula for regression to policy analysis for and sensitivity to structural changes. We apply this analysis and find no sensitivity to endogeneity of average equivalent variation estimates in a gasoline demand application.
This paper is concerned with estimation of functionals of a latent weight function that satisfies possibly high-dimensional multiplicative moment conditions. Main examples are functionals of stochastic discount factors in asset pricing, missing data problems, and treatment effects. We propose to estimate the latent weight function by an information theoretic approach combined with the ℓ1-penalization technique to deal with high-dimensional moment conditions under sparsity. We study asymptotic properties of the proposed method and illustrate it by a theoretical example on treatment effect analysis and empirical example on estimation of stochastic discount factors.
Uncertainty about the choice of identifying assumptions is common in causal studies, but is often ignored in empirical practice. This paper considers uncertainty over models that impose different identifying assumptions, which can lead to a mix of point- and set-identified models. We propose performing inference in the presence of such uncertainty by generalizing Bayesian model averaging. The method considers multiple posteriors for the set-identified models and combines them with a single posterior for models that are either point-identified or that impose nondogmatic assumptions. The output is a set of posteriors (post-averaging ambiguous belief), which can be summarized by reporting the set of posterior means and the associated credible region. We clarify when the prior model probabilities are updated and characterize the asymptotic behavior of the posterior model probabilities. The method provides a formal framework for conducting sensitivity analysis of empirical findings to the choice of identifying assumptions. For example, we find that in a standard monetary model one would need to attach a prior probability greater than 0.28 to the validity of the assumption that prices do not react contemporaneously to a monetary policy shock, in order to obtain a negative response of output to the shock.
Correct specification of a conditional quantile model implies that a particular conditional moment is equal to zero. We nonparametrically estimate the conditional moment function via series regression and test whether it is identically zero using uniform functional inference. Our approach is theoretically justified via a strong Gaussian approximation for statistics of growing dimensions in a general time series setting. We propose a novel bootstrap method in this nonstandard context and show that it significantly outperforms the benchmark asymptotic approximation in finite samples, especially for tail quantiles such as Value-at-Risk (VaR). We use the proposed new test to study the VaR and CoVaR (Adrian and Brunnermeier (2016)) of a collection of US financial institutions.
This paper introduces a maximum likelihood estimator of the value of job amenities and labor productivity in a single matching market based on the observation of equilibrium matches and wages. The estimation procedure simultaneously fits both the matching patterns and the wage curve. While our estimator is suited for a wide range of assignment problems, we provide an application to the estimation of the Value of a Statistical Life using compensating wage differentials for the risk of fatal injury on the job. Using US data for 2017, we estimate the Value of Statistical Life at $6.3 million ($2017).
Cities with cleaner power plants and lower energy demand tend also to have tighter land-use restrictions; these restrictions increase housing prices and reduce the incentive for households to live in these lower greenhouse gas-emitting cities. We use a spatial equilibrium model to quantify the overall effects of land-use restrictions on the levels and spatial distribution of household carbon emissions. Our model features heterogeneous households, cities that vary in both their power plant technologies and their utility benefits of energy usage, as well as endogenous wages and rents. Relaxation of the current land-use restrictions in California to the level faced by the median urban household in the US leads to a 0.6% drop in national household carbon emissions and a decrease in the social cost of carbon of $310 million annually.
A multivariate GARCH model of natural resources is specified to capture the effects of time varying portfolio risk. A special feature of the model is the inclusion of realized volatility for natural resource assets that are available at multiple frequencies as well as being sensitive to sudden changes in climatic conditions. Natural resource portfolios under climate change are simulated from bootstrapping schemes as well as being derived from global climate model projections. Both approaches are applied to a multiasset water portfolio model consisting of reservoir inflows, rainwater harvesting, and desalinated water. The empirical results show that while reservoirs remain the dominant water asset, adaptation to climate change involves increased contributions from rainwater harvesting and more frequent use of desalinated water. It is estimated that climate change increases annual water supply costs by between 7% and 44% over a 20-year forecast horizon.
This paper shows that the consumption-based capital asset pricing model (C-CAPM) with low-probability disaster risk rationalizes pricing errors. We find that implausible estimates of risk aversion and time preference are not puzzling if market participants expect a future catastrophic change in fundamentals, which just happens not to occur in the sample (a “peso problem”). A bias in structural parameter estimates emerges as a result of pricing errors in quiet times. While the bias essentially removes the pricing error in the simple models when risk-free rates are constant, time-variation may also generate large and persistent estimated pricing errors in simulated data. We also show analytically how the problem of biased estimates can be avoided in empirical research by resolving the misspecification in moment conditions.
We study the aggregate and distributional consequences of replacing corporate profit taxes with shareholder taxes, namely taxes on dividends and capital gains, in a setting with incomplete markets and heterogeneity at both the household and the firm level. The reform yields distributional gains with a large majority of households benefiting. Moreover, if dividend and capital gains are taxed at the same rate, the reform is also efficiency-enhancing and the implied optimal corporate income tax rate is zero. In contrast, an asymmetric tax treatment of dividend and capital gains induces a trade-off between efficiency and distributional concerns that is optimally resolved at a positive optimal corporate tax rate, implying double taxation.
We investigate if, and why, an initial success can trigger a string of successes. Using random variations in success in a real-effort laboratory experiment, we cleanly identify the causal effect of an early success in a competition. We confirm that an early success indeed leads to increased chances of a later success. By alternatively eliminating strategic features of the competition, we turn on and off possible mechanisms driving the effect of an early success. Standard models of dynamic contest predict a strategic effect due to asymmetric incentives between initial winners and losers. Surprisingly, we find no evidence that they can explain the positive effect of winning. Instead, we find that the effect of winning seems driven by an information revelation effect, whereby players update their beliefs about their relative strength after experiencing an initial success.
We build and estimate a dynamic model of teenagers' choices of schooling and crime, incorporating four factors that may contribute to the different paths taken by different teenagers: heterogeneous endowments, unequal opportunities, uncertainties about one's own ability, and contemporaneous shocks. We estimate the model using administrative panel data from Chile that link school records with juvenile criminal records. Counterfactual policy experiments suggest that, for teenagers with disadvantaged backgrounds, interventions that combine mild improvement in their schooling opportunities with free tuition (by adding 157 USD per teenager-year to the existing high school voucher) would lead to an 11% decrease in the fraction of those ever arrested by age 18 and a 13% increase in the fraction of those consistently enrolled throughout primary and secondary education.
We study the impact of child work on cognitive development in four Low- and Middle-Income Countries. We advance the literature by using cognitive test scores collected regardless of school attendance. We also address a key gap in the literature by controlling for children's complete time allocation budget. This allows us to estimate effects of different types of work, like chores and market/farm work, relative to specific alternative time-uses, like school or study or play/leisure. Our results show child work is more detrimental to child development to the extent that it crowds out school/study time rather than leisure. We also show the adverse effect of time spent on domestic chores is similar to time spent on market and farm work, provided they both crowd out school/study time. Thus, policies to enhance child development should target a shift from all forms of work toward educational activities.
Does economic uncertainty promote the implementation of structural reforms? We answer this question using one of the most exhaustive cross-country panel data sets on reforms in six major areas and measuring economic uncertainty with stock market volatility. To identify causality, we exploit exogenous differential variation in countries' exposure to foreign volatility shocks due to predetermined and time-invariant bilateral characteristics. Across all specifications, we find that stock market volatility has a positive and significant effect on the adoption of reforms. This result is robust to the inclusion of a large number of controls, such as political variables, economic variables, crisis indicators, and a host of country, reform and time fixed effects, as well as across various approaches for accommodating heterogeneous trends and contemporaneous shocks. Overall, this evidence suggests that times of market turmoil, which are characterized by a high degree of uncertainty, may facilitate the implementation of reforms that would otherwise not pass.
This study provides new identification and estimation results for ascending (traditional English or online) auctions with unobserved auction-level heterogeneity and an unknown number of bidders. When the seller's reserve price and two order statistics of bids are observed, we derive conditions under which the distributions of buyer valuations, unobserved heterogeneity, and number of participants are point identified. We also derive conditions for point identification in cases where reserve prices are binding and present general conditions for partial identification. We propose a nonparametric maximum likelihood approach for estimation and inference. We apply our approach to the online market for used iPhones and analyze the effects of recent regulatory changes banning consumers from circumventing digital rights management technologies used to lock phones to service providers. We find that buyer valuations for unlocked phones dropped by 39% on average after the unlocking ban took effect, from $231.30 to $141.50.
Demand estimates are essential for addressing a wide range of positive and normative questions in economics that are known to depend on the shape—and notably the curvature—of the true demand functions. The existing frontier approaches, while allowing flexible substitution patterns, typically require the researcher to commit to a parametric specification. An open question is whether these a priori restrictions are likely to significantly affect the results. To address this, I develop a nonparametric approach to estimation of demand for differentiated products, which I then apply to California supermarket data. While the approach subsumes workhorse models such as mixed logit, it allows consumer behaviors and preferences beyond standard discrete choice, including continuous choices, complementarities across goods, and consumer inattention. When considering a tax on one good, the nonparametric approach predicts a much lower pass-through than a standard mixed logit model. However, when assessing the market power of a multiproduct firm relative to that of a single-product firm, the models give similar results. I also illustrate how the nonparametric approach may be used to guide the choice among parametric specifications.
We estimate a model in which fiscal and monetary policy obey the targeting rules of distinct policy authorities, with potentially different objective functions. We find: (1) Time-consistent policy fits U.S. time series at least as well as instrument-rules-based behavior; (2) American policies often do not conform to the conventional mix of conservative monetary policy and debt-stabilizing fiscal policy, although economic agents expect fiscal policy to stabilize debt eventually; (3) Even after the Volcker disinflation, policies did not achieve that conventional mix, as fiscal policy did not begin to stabilize debt until the mid 1990s; (4) The high inflation of the 1970s could have been effectively mitigated by either a switch to a fiscal targeting rule or an increase in monetary policy conservatism; (5) If fiscal behavior follows its historic norm to eventually stabilize debt, current high debt levels produce only modest inflation; if confidence in those norms erodes, high debt may deliver substantially more inflation.
We integrate an epidemiological model, augmented with contact and mobility analyses, with a two-sector macroeconomic model, to assess the economic costs of labor supply disruptions in a pandemic. The model is designed to capture key characteristics of the U.S. input–output tables with a core sector that produces intermediate inputs not easily replaceable by the other sectors, possibly subject to minimum-scale requirements. Using epidemiological and mobility data to inform our exercises, we show that the reduction in labor services due to the observed social distancing (spontaneous and mandatory) could explain up to 6–8 percentage points of the roughly 12% U.S. GDP contraction in the second quarter of 2020. We show that public measures designed to protect workers in core industries and occupations with tasks that cannot be performed from home, can flatten the epidemiological curve at reduced economic costs—and contain vulnerabilities to supply disruptions, namely a new surge of infections. Using state-level data for the United States, we provide econometric evidence that spontaneous social distancing was no less costly than mandated social distancing.
This paper shows the success of valuation risk—time-preference shocks in Epstein–Zin utility—in resolving asset pricing puzzles rests sensitively on the way it is introduced. The specification used in the literature is at odds with several desirable properties of recursive preferences because the weights in the time-aggregator do not sum to one. When we revise the specification in a simple asset pricing model the puzzles resurface. However, when estimating a sequence of increasingly rich models, we find valuation risk under the revised specification consistently improves the ability of the models to match asset price and cash-flow dynamics.
Using a revealed preference approach, we conduct an experiment where subjects make choices from linear convex budgets in the domain of risk. We find that many individuals prefer mixtures of lotteries in ways that systematically rule out expected utility behavior. We explore the extent to which an individual's preference to choose mixtures is related to a preference for randomization by comparing choices from a convex choice task to the decisions made in a repeated discrete choice task. We find that a preference to mix is positively correlated with behavior from repeated discrete choice tasks.
The popularity of open ascending auctions is often attributed to the fact that openly observable bidding allows to aggregate dispersed information. Another reason behind the frequent utilization of open auction formats may be that they activate revenue enhancing biases. In an experiment, we compare three auctions that differ in how much information is revealed and in the potential activation of behavioral biases: (i) the ascending Vickrey auction, a closed format; and two open formats, (ii) the Japanese–English auction, and (iii) the Oral Outcry auction. Even though bidders react to information conveyed in others' bids, information aggregation fails in both open formats. In contrast, the Oral Outcry raises higher revenue than the other two formats by stimulating bidders to submit unprofitable jump bids and triggering a quasi-endowment effect.
We study the foundations for the development of optimal randomization in mixed strategy games. We consider a population of children and adolescents (7 to 16 years old) and study in the laboratory their behavior in a nonzero sum, hide-and-seek game with a unique interior mixed strategy equilibrium where each location has a known but different value. The vast majority of participants favor the high-value location not only as seekers (as predicted by theory) but also as hiders (in contradiction with theory). The behavior is extremely similar across all ages, and also similar to that of the college students control adult group. We also study the use of cheap talk (potentially deceptive) messages in this game. Hiders are excessively truthful in the messages they send while seekers have a slight tendency to (correctly) believe hiders. In general, however, messages have a small impact on outcomes. The results point to a powerful (erroneous) heuristic thinking in two-person randomization settings that does not get corrected, even partially, with age.
In this paper, we analyze a discrete choice model for partially ordered alternatives. The alternatives are differentiated along two dimensions: the first an unordered “horizontal” dimension, and the second an ordered “vertical” dimension. The model can be used in circumstances in which individuals choose among products of different brands, wherein each brand offers an ordered choice menu, for example, by offering products of varying quality. The unordered–ordered nature of the discrete choice problem is used to characterize the identified set of model parameters. Following an initial nonparametric analysis that relies on shape restrictions inherent in the ordered dimension of the problem, we then provide a specialized analysis for parametric specifications that generalize common ordered choice models. We characterize conditional choice probabilities as a function of model primitives with particular analysis focusing on cases in which unobservable taste for quality of each brand offering is multivariate normally distributed. We provide explicit formulae used for estimation and inference via maximum likelihood, and we consider inference based on Wald and quasi-likelihood ratio statistics, the latter of which can be robust to a possible lack of point identification. An empirical illustration is conducted using data on razor blade purchases in which each brand has product offerings vertically differentiated by quality.
We propose a framework for estimation and inference when the model may be misspecified. We rely on a local asymptotic approach where the degree of misspecification is indexed by the sample size. We construct estimators whose mean squared error is minimax in a neighborhood of the reference model, based on one-step adjustments. In addition, we provide confidence intervals that contain the true parameter under local misspecification. As a tool to interpret the degree of misspecification, we map it to the local power of a specification test of the reference model. Our approach allows for systematic sensitivity analysis when the parameter of interest may be partially or irregularly identified. As illustrations, we study three applications: an empirical analysis of the impact of conditional cash transfers in Mexico where misspecification stems from the presence of stigma effects of the program, a cross-sectional binary choice model where the error distribution is misspecified, and a dynamic panel data binary choice model where the number of time periods is small and the distribution of individual effects is misspecified.
This paper considers estimation and inference for heterogeneous counterfactual effects with high-dimensional data. We propose a novel robust score for debiased estimation of the unconditional quantile regression (Firpo, Fortin, and Lemieux (2009)) as a measure of heterogeneous counterfactual marginal effects. We propose a multiplier bootstrap inference and develop asymptotic theories to guarantee the size control in large sample. Simulation studies support our theories. Applying the proposed method to Job Corps survey data, we find that a policy, which counterfactually extends the duration of exposures to the Job Corps training program, will be effective especially for the targeted subpopulations of lower potential wage earners.
Although survey-based point predictions have been found to outperform successful forecasting models, corresponding variance forecasts are frequently diagnosed as heavily distorted. Professional forecasters who report inconspicuously low ex ante variances often produce squared forecast errors that are much larger on average. In this paper, we document the novel stylized fact that this variance misalignment is related to the rounding behavior of survey participants. Rounding may reflect the fact that some survey participants employ a rather judgmental approach to forecasting as opposed to using a formal model. We use the distinct numerical accuracies of panelists' reported probabilities as a way to propose several alternative and easily implementable corrections that (i) can be carried out in real time, that is, before outcomes are observed, and (ii) deliver a significantly improved match between ex ante and ex post forecast uncertainty. According to our estimates, uncertainty about inflation, output growth and unemployment in the U.S. and the Euro area is higher after correcting for the rounding effect. The increase in the share of nonrounded responses in recent years also helps to understand the trajectory of survey-based average uncertainty during the years since the financial and sovereign debt crisis.
Through certainty equivalent consumption (CE) measures, we show that dispersion of current earnings, expenditures, and net worth overstate welfare inequality. This is largely due to the unaccounted value of future earnings, which we call human wealth. The latter mitigates permanent-income inequality, though its influence is diminished by the growing importance of assets in lifetime wealth. Average expenditures and CE inequality roughly doubled between 1983 and 2016 and, to weigh these offsetting forces, we decompose aggregate welfare changes into contributions from the level and dispersion of consumption, as well as uncertainty and demographic composition. Rising inequality has offset about 1/4 of the welfare gains from higher consumption, with most of the losses accruing after 2000.
With capital-skill complementarity, the secular decline in the price of capital equipment due to equipment-specific technological progress (ESTP) keeps pushing up the demand for skilled relative to unskilled labor and raising the skill premium. This paper quantitatively characterizes the dynamics of optimal taxation in response. Two main results emerge, regardless of whether the Ramsey (1927) or the Mirrlees (1971) approach is adopted. First, a tax on capital equipment corrects the “pecuniary externalities” caused by ESTP. The correction prescribes a downward or an upward adjustment of tax rates over time, depending on whether ESTP takes place at an accelerated or a decelerated pace. Second, both Ramsey and Mirrlees approaches prescribe an increasing marginal tax rate on labor income over time. Interestingly, we find that the prescribed pattern of optimal taxation resembles the empirical decline in capital taxes and the increase in labor taxes observed in the United States. In particular, despite the significant rise in the skill premium, the welfare gains of tax reform toward optimal Ramsey taxes are modest and small.
Hiring is a costly activity reflecting firms' investment in their workers. Microdata show that hiring costs involve production disruption. Thus, cyclical fluctuations in the value of output, induced by price frictions, have consequences for the optimal allocation of hiring activities. We outline a mechanism based on cyclical markup fluctuations, placing emphasis on hiring frictions interacting with price frictions. This mechanism generates strong propagation and amplification of all key macroeconomic variables in response to technology shocks and mutes the traditional transmission of monetary policy shocks. A local projection analysis of aggregate U.S. data shows that the empirical results, including the cyclicality of markups, are consistent with the model's impulse response functions.
Large Bayesian VARs are now widely used in empirical macroeconomics. One popular shrinkage prior in this setting is the natural conjugate prior as it facilitates posterior simulation and leads to a range of useful analytical results. This is, however, at the expense of modeling flexibility, as it rules out cross-variable shrinkage, that is, shrinking coefficients on lags of other variables more aggressively than those on own lags. We develop a prior that has the best of both worlds: it can accommodate cross-variable shrinkage, while maintaining many useful analytical results, such as a closed-form expression of the marginal likelihood. This new prior also leads to fast posterior simulation—for a BVAR with 100 variables and 4 lags, obtaining 10,000 posterior draws takes less than half a minute on a standard desktop. We demonstrate the usefulness of the new prior via a structural analysis using a 15-variable VAR with sign restrictions to identify 5 structural shocks.
We introduce the extended perturbation method, which improves the accuracy of standard perturbation by reducing approximation errors under certainty equivalence. For the New Keynesian model with Calvo pricing, extended perturbation is more accurate than standard perturbation, which implies explosive dynamics because it omits the upper bound on inflation implied by this model. In contrast, extended perturbation enforces this bound and generates stable dynamics. We also show that extended perturbation can accurately solve a New Keynesian model that enforces the zero lower bound for the monetary policy rate by considering a smooth nonlinear modification of the standard Taylor rule.
If bidders are better informed than the seller about a common component of auction heterogeneity, the seller can allocate more efficiently by keeping her reserve price secret and revising it using submitted bids. We build a model of a first-price auction under unobserved auction heterogeneity—imperfectly observed by the seller—that captures this rationale and derive conditions for identification. An application to French timber auctions, where such revisions are widely used, shows that having perfect information about unobserved auction heterogeneity would increase surplus by 5.22%. Combining a secret reserve price with learning from submitted bids reduces this surplus gap by up to 84%.
We construct a peer effects model where mean expenditures of consumers in one's peer group affect utility through perceived consumption needs. We provide a novel method for obtaining identification in social interactions models like ours, using ordinary survey data, where very few members of each peer group are observed. We implement the model using standard household-level consumer expenditure survey microdata from India. We find that each additional rupee spent by one's peers increases perceived needs, and thereby reduces one's utility, by the equivalent of a 0.25 rupee decrease in one's own expenditures. These peer costs may be larger for richer households, meaning transfers from rich to poor could improve even inequality-neutral social welfare, by reducing peer consumption externalities. We show welfare gains of billions of dollars per year might be possible by replacing government transfers of private goods to households with providing public goods or services, to reduce peer effects.
We report on two novel choice experiments with real goods where subjects in one treatment are forced to choose, as is the norm in economic experiments, while in the other they are not but can instead incur a small cost to defer choice. Using a variety of measures, we find that the active choices (i.e., those that exclude the deferral outside option) of subjects in the nonforced-choice treatment are generally more consistent. We also find that the combined deferral and active-choice behavior of subjects in that treatment is explained better by a model of dominant choice with incomplete preferences than it is by rational choice. Our results suggest that nonforced-choice experiments and models can be helpful in separating people's rational, hesitant/not-yet-rational and genuinely irrational behavior, and can potentially offer important new insights in revealed preference analysis.
The Global Repository of Income Dynamics (GRID) is a new open-access, cross-country database that contains a wide range of micro statistics on income inequality, dynamics, and mobility. It has four key characteristics: it is built on micro panel data drawn from administrative records; it fully exploits the longitudinal dimension of the underlying data sets; it offers granular descriptions of income inequality and income dynamics for finely defined subpopulations; and it is designed from the ground up with the goals of harmonization and cross-country comparability. This paper introduces the database and presents a set of global trends in income inequality and income dynamics across the 13 countries that are currently in GRID. Our results are based on the statistics created for GRID by the 13 country teams who also contributed to this special issue with individual articles.
This paper studies earnings inequality and dynamics in Argentina between 1996 and 2015. Following the 2001–2002 crisis, the Argentine economy transitioned from a low- to a high-inflation regime, while collective bargaining and the minimum wage gained influence. This transition was associated with a persistent decrease in earnings dispersion and cyclical movements in higher-order moments of the distribution of earnings changes. To shed light on the changing nature of wage rigidity during this period, we develop a new method to estimate regular-wage processes. As the Argentine economy transitioned from low to high inflation, the monthly frequency of regular-wage changes almost doubled, while the distribution of regular-wage changes morphed from having a mode around zero and positive skewness to having a positive mode and more symmetric tails.
Using rich administrative and household survey data spanning 34 years from 1985 to 2018, we document a series of new facts on earnings inequality and dynamics in a developing country with a large informal sector: Brazil. Since the mid-1990s, both inequality and volatility of earnings have declined significantly in Brazil's formal sector. Higher-order moments of the distribution of earnings changes show cyclical movements in Brazil that are similar to those in developed countries like the US. Relative to the formal sector, the informal sector is associated with a significant earnings penalty and higher earnings volatility for identical workers. Earnings changes of workers who switch from formal to informal (from informal to formal) employment are relatively negative (positive) and large in magnitude, dispersed, negatively (positively) skewed, and less leptokurtic. Our results suggest that informal employment is an imperfect insurance mechanism.
This paper studies the evolution of individual earnings inequality and dynamics in Canada from 1983 to 2016 using tax files and administrative records. Linking individual tax filers to their employers (and rich administrative records on firms) beginning in 2001, it also documents the relationship between the earnings dynamics of workers and the size and growth of their employers. It highlights three main patterns over this period: First, with a few exceptions (sharp increase in top 1% and declining gender gap), Canada has experienced relatively modest changes in overall earnings inequality, volatility, and mobility between 1983 and 2016. Second, earnings inequality and the distribution of earnings growth vary substantially over the business cycle. Third, the earnings dynamics of individuals are strongly related to the size and employment growth of their employers.
We document facts about earnings and disposable income inequality and growth in Denmark in the period 1987–2016. During this period, the distribution of log earnings growth exhibits skewness that varies with the business cycle and has strong excess kurtosis. Denmark has a progressive income tax system with a high level of taxes and a relatively generous and heavily subsidized unemployment insurance system. Consequently, the dispersion of log disposable income growth is much smaller than for earnings, and the distribution exhibits very limited skewness and much reduced excess kurtosis. These results emphasize the importance of distinguishing between earnings and disposable income when modeling income dynamics, and they suggest that the Danish welfare state plays an important role in reducing the impact of earnings fluctuations on disposable income.
This paper provides new stylized facts about labor earnings inequality and dynamics in France for the period 1991–2016. Using linked employer–employee data, we show that (i) labor inequality in France is low compared to other developed countries and has been decreasing until the financial crisis of 2009 and increasing since then, (ii) women experienced high earnings growth, in particular at the bottom of the distribution, in contrast to the stability observed for men. Both result from a decrease in labor costs at the minimum wage and an increase in the hourly minimum in the aftermath of the 35h workweek policy, (iii) top earnings (top 5 and 1%) grew moderately while very top earnings (top 0.1 and 0.01%) experienced a much higher growth, (iv) inequality between and within cohorts follow the same U-shaped pattern as global inequality: it decreased before 2009 and then increased until 2016, (v) Individual earnings mobility is stable between 1991 and 2016, and very low at the top of the distribution, (vi) the distribution of earnings growth is negatively skewed, leptokurtic, and varies with age. Then, studying earnings dispersion both within and between territories, we document strong differences across cities as well as between urban and rural areas, even after controlling for observable characteristics. We also observe a continuous decrease in earnings inequality between territories. However, a larger inflation in rural territories mitigates this convergence. Finally, we document a strong reduction in inequality within rural and remote territories, again driven by changes at the bottom of the wage distribution.
We provide a comprehensive analysis of income inequality and income dynamics for Germany over the last two decades. Combining personal income tax and social security data allows us—for the first time—to offer a complete picture of the distribution of annual earnings in Germany. We find that cross-sectional inequality rose until 2009 for men and women. After the Great Recession, inequality continued to rise at a slower rate for men and fell slightly for women due to compression at the lower tail. We further document substantial gender differences in average earnings and inequality over the life cycle. While for men earnings rise and inequality falls as they grow older, many women reduce working hours when starting a family such that average earnings fall and inequality increases. Men's earnings changes are on average smaller than women's but are substantially more affected by the business cycle. During the Great Recession, men's earnings losses become magnified and gains are attenuated. Apart from recession years, earnings changes are significantly right-skewed reflecting the good overall state of the German labor market and increasing labor supply. In the second part of the paper, we study the distribution of total income including incomes of self-employed, business owners, and landlords. We find that total inequality increased significantly more than earnings inequality. Regarding income dynamics, entrepreneurs' income changes are more dispersed, less skewed, less leptokurtic, and less dependent on average past income than workers' income changes. Finally, we find that top income earners have become less likely to fall out of the top 1 and 0.1%.
This paper summarizes statistics on the key aspects of the distribution of earnings levels and earnings changes using administrative (social security) data from Italy between 1985 and 2016. During the time covered by our data, earnings inequality and earnings volatility increased, while earnings mobility did not change significantly. We connect these trends with some salient facts about the Italian labor market, in particular the labor market reforms of the 1990s and 2000s, which induced a substantial rise in fixed-term and part-time employment. The rise in part-time work explains much of the rise in earnings inequality, while the rise in fixed-term contracts explains much of the rise in volatility. Both of these trends affect the earnings distribution through hours worked: part-time jobs reduce hours worked within a week, while fixed-term contracts reduce the number of weeks worked during the year as well as increase their volatility. We only find weak evidence that fixed-term contracts represent a “stepping-stone” to permanent employment. Finally, we offer suggestive evidence that the labor market reforms contributed to the slowdown in labor productivity in Italy by delaying human capital accumulation (in the form of general and firm-specific experience) of recent cohorts.
We characterize the salient features of the distribution of (log) earnings of formal workers in Mexico using social security records for the period 2005–2019. The analysis is based on a nonparametric approach and is focused primarily on the properties of the distribution of earnings changes. We find strong evidence of deviations from normality of this distribution in terms of negative skewness and high kurtosis, with these deviations varying with income and along the worker's life cycle. A comparison between results obtained with administrative data and household survey data suggests that this latter source of information is inadequate to fully capture the evolution of inequality and the properties of earnings changes as nonresponse is nonrandom and concentrated among formal and highly educated workers—likely the highest earners. Due to the relative size of the informal sector in the Mexican economy, which results in a large number of workers maintaining a weak attachment to formal employment, we also study the impact of transitions out of and back into formal employment on wages earned in the formal sector. We document that workers who exit formal employment experience a significant wage penalty upon reentry taking, on average, 3 or more years to achieve comparable preexit wage levels.
Using administrative data, we provide an extensive characterization of labor earnings dynamics in Norway. Some of our findings are as follows: (i) Norway has not been immune to the increase in top earnings inequality seen in other countries, (ii) the earnings distribution compresses in the bottom 90% over the life cycle but expands in the top 10%, and (iii) the earnings growth distribution is left-skewed and leptokurtic, and the extent of these nonnormalities varies with age and past income.

Linking individuals to their parents, we also investigate the intergenerational transmission of income dynamics. We find that children of high-income, high-wealth fathers enjoy steeper income growth over the life cycle and face more volatile but more positively skewed income changes, suggesting that they are more likely to pursue high-return, high-risk careers. Income growth for children of poorer fathers is more gradual and more left skewed, displaying higher left tail risk. Furthermore, the income dynamics of fathers and children are strongly correlated: children of fathers with steeper life-cycle income growth, more volatile incomes, or higher downside risk also have income streams of similar properties. These findings shed new light on the determinants of intergenerational mobility.
In this paper, we use administrative data from the social security to study income dynamics and income risk inequality in Spain between 2005 and 2018. We construct individual measures of income risk as functions of past employment history, income, and demographics. Focusing on males, we document that income risk is highly unequal in Spain: More than half of the economy has close to perfect predictability of their income, while some face considerable uncertainty. Income risk is inversely related to income and age, and income risk inequality increases markedly in the recession. These findings are robust to a variety of specifications, including using neural networks for prediction and allowing for individual unobserved heterogeneity.
This paper analyzes earnings inequality and earnings dynamics in Sweden over 1985–2016. The deep recession in the early 1990s marks a historic turning point with a massive increase in earnings inequality and earnings volatility, and the impact of the recession and the recovery from it lasted for decades. In the aftermath of the recession, we find steady growth in real earnings across the entire distribution for men and women and decreasing inequality over more than 20 years. Despite the positive trend, large gender differences in earnings dynamics persist. While earnings growth for men is more closely tied to the business cycle, women face much higher volatility overall. Earnings volatility is also substantially higher among foreign-born workers, reflecting weaker labor market attachment and high risk of large negative shocks for low-income immigrants. We document an important role of social benefits usage for the overall trends and for differences across subpopulations. Higher benefits enrollment, especially for women and immigrants, is associated with higher earnings volatility. As the generosity and usage of benefit programs declined over time, we find stronger earnings growth among low-income workers, consistent with higher self-sufficiency.
In this paper, we use an employer-based survey of earnings and hours to set out the key patterns in UK earnings dynamics from 1975 to 2020, with a particular focus on the most recent recession. We demonstrate that (log) earnings changes exhibit strongly procyclical skewness and have become increasingly leptokurtic, and thus less well approximated by a log-normal distribution, over the period of study. This holds across genders and sectors. Exploiting the long duration of our panel, we then explore the responsiveness of earnings and hours to aggregate and firm-level shocks, finding ample heterogeneity in the exposure of different types of workers to aggregate shocks. Exposure is falling in age, firm size, skill level, and permanent earnings, and is lower for unionized and public sector workers. The qualitative patterns of earnings changes across workers observed in the Covid-19 recession of 2020 are broadly as predicted using the previously estimated exposures and size of the shock. Firm-specific shocks are important for wages given the variation in within-firm productivity and the patterns of heterogeneity are markedly different than for aggregate shocks.
This paper is part of the Global Repository of Income Dynamics (GRID) project cross-country comparison of earnings inequality, volatility, and mobility. Using data from the U.S. Census Bureau's Longitudinal Employer-Household Dynamics (LEHD) infrastructure files, we produce a uniform set of earnings statistics for the U.S. From 1998 to 2019, we find U.S. earnings inequality has increased and volatility has decreased. The combination of increased inequality and reduced volatility suggest earnings growth differs substantially across different demographic groups. We explore this further by estimating 12-year average earnings for a single cohort of age 25–54 eligible workers. Overall, differences in labor supply (hours paid and quarters worked) are found to explain almost 90% of the variation in worker earnings at the mean, although substantial earnings differences across and within groups remain unexplained. Using a quantile regression approach, we estimate counterfactual earnings distributions for each demographic group. We find that at the bottom of the earnings distribution differences in characteristics such as hours paid, geographic division, industry, and education explain almost the entire earnings gap; however, above the median the contribution of the differences in the returns to characteristics is the dominant component.
We develop a generally applicable full-information inference method for heterogeneous agent models, combining aggregate time series data and repeated cross-sections of micro data. To handle unobserved aggregate state variables that affect cross-sectional distributions, we compute a numerically unbiased estimate of the model-implied likelihood function. Employing the likelihood estimate in a Markov Chain Monte Carlo algorithm, we obtain fully efficient and valid Bayesian inference. Evaluation of the micro part of the likelihood lends itself naturally to parallel computing. Numerical illustrations in models with heterogeneous households or firms demonstrate that the proposed full-information method substantially sharpens inference relative to using only macro data, and for some parameters micro data is essential for identification.
We propose using a permutation test to detect discontinuities in an underlying economic model at a known cutoff point. Relative to the existing literature, we show that this test is well suited for event studies based on time-series data. The test statistic measures the distance between the empirical distribution functions of observed data in two local subsamples on the two sides of the cutoff. Critical values are computed via a standard permutation algorithm. Under a high-level condition that the observed data can be coupled by a collection of conditionally independent variables, we establish the asymptotic validity of the permutation test, allowing the sizes of the local subsamples to be either be fixed or grow to infinity. In the latter case, we also establish that the permutation test is consistent. We demonstrate that our high-level condition can be verified in a broad range of problems in the infill asymptotic time-series setting, which justifies using the permutation test to detect jumps in economic variables such as volatility, trading activity, and liquidity. These potential applications are illustrated in an empirical case study for selected FOMC announcements during the ongoing COVID-19 pandemic.
The random utility model (RUM, McFadden and Richter (1990)) has been the standard tool to describe the behavior of a population of decision makers. RUM assumes that decision makers behave as if they maximize a rational preference over a choice set. This assumption may fail when consideration of all alternatives is costly. We provide a theoretical and statistical framework that unifies well-known models of random (limited) consideration and generalizes them to allow for preference heterogeneity. We apply this methodology in a novel stochastic choice data set that we collected in a large-scale online experiment. Our data set is unique since it exhibits both choice set and (attention) frame variation. We run a statistical survival race between competing models of random consideration and RUM. We find that RUM cannot explain the population behavior. In contrast, we cannot reject the hypothesis that decision makers behave according to the logit attention model (Brady and Rehbeck (2016)).
We use a dynamic panel Tobit model with heteroskedasticity to generate forecasts for a large cross-section of short time series of censored observations. Our fully Bayesian approach allows us to flexibly estimate the cross-sectional distribution of heterogeneous coefficients and then implicitly use this distribution as prior to construct Bayes forecasts for the individual time series. In addition to density forecasts, we construct set forecasts that explicitly target the average coverage probability for the cross-section. We present a novel application in which we forecast bank-level loan charge-off rates for small banks.
We develop a structural vector autoregressive framework that combines external instruments and heteroskedasticity for identification of monetary policy shocks. We show that exploiting both types of information sharpens structural inference, allows testing the relevance and exogeneity condition for instruments separately using likelihood ratio tests, and facilitates the economic interpretation of the structural shock of interest. We test alternative instruments and find that narrative and model-based measures are valid, while high-frequency data instruments show signs of invalidity. Finally, we document that monetary shocks identified with both a valid instrument and heteroskedasticity have larger effects on production and prices than monetary shocks identified via an instrument only.
We develop an analytical framework designed to solve and analyze heterogeneous-agent models that endogenously generate fat-tailed wealth distributions. We exploit the asymptotic linearity of policy functions and the analytical characterization of the Pareto exponent to augment the conventional solution algorithm with a theory of the tail. Our framework allows for a precise understanding of the very top of the wealth distribution (e.g., analytical expressions for top wealth shares, type distribution in the tail, and transition probabilities in and out of the tail) in addition to delivering improved accuracy and speed.
A core mechanism of unified growth theory is that accelerating technological progress induces mass education and, through interaction with child quantity-quality substitution, a decline in fertility. Using unique new data for 21 OECD countries over the period 1750–2000, we test, for the first time, the validity of this core mechanism of unified growth theory. We measure a country's technological progress as patents per capita, R&D intensity, and investment in machinery, equipment, and intellectual property products. While controlling for confounders, such as income growth, mortality, and the gender wage gap, we establish (1) a significant impact of technological progress on education (positive) and fertility (negative); (2) that accelerating technological progress stimulated the fertility transition; and (3) that the baseline results are supported in 2SLS regressions using genetic-distance weighted foreign patent-intensity, compulsory schooling years, and minimum working age as instruments.
Quantitative models of sovereign default predict that governments reduce borrowing during recessions to avoid debt crises. A prominent implication of this behavior is that the resulting interest rate spread volatility is counterfactually low. We propose that governments borrow into debt crises because of frictions in the adjustment of their expenditures. We develop a model of government good production, which uses public employment and intermediate consumption as inputs. The inputs have varying degrees of downward rigidity, which means that it is costly to reduce them. Facing an adverse income shock, the government borrows to smooth out the reduction in public employment, which results in increasing debt and higher spread. We quantify this rigidity using the OECD Government Accounts data and show that it explains about 70% of the missing bond spread volatility.
Over the last several years, highly accurate methods of sex selection before conception have been developed. Given that strong preferences for sex variety in offspring have been documented for the U.S., we ask what the demographic consequences of sex-selection technology could be. Lacking variation across space and time in access to this technology, we estimate a dynamic programming model of fertility decisions with microdata on fertility histories. We leverage the quasi-experimental variation inherent in the random determination of sex to identify the key structural parameter characterizing preferences for sex variety in offspring. We then simulate the introduction of this technology. While this technology can reduce fertility by allowing parents to efficiently reach their preferred sex mix, it could also increase it. This is because without this technology, many parents may opt not to have another baby given the uncertainty about its sex. Results suggest that these two effects operate simultaneously, but on net, sex-selection technology ends up reducing the average family size among married women by less than 2% in the steady state, a much smaller decline than the one that would be predicted by alternative methods.
This paper studies gender differences in performance in a male-dominated competitive environment chess tournaments. We find that the gender composition of chess games affects the behaviors of both men and women in ways that worsen the outcomes for women. Using a unique measure of within-game quality of play, we show that women make more mistakes when playing against men. Men, however, play equally well against male and female opponents. We also find that men persist longer before losing to women. Our results shed some light on the behavioral changes that lead to differential outcomes when the gender composition of competitions varies.
In this paper, we introduce a new approach to estimating differentiated product demand systems that allows for products with zero sales in the data. Zeroes in demand are a common problem in differentiated product markets, but fall outside the scope of existing demand estimation techniques. We show that with a lower bound imposed on the expected sales quantities, we can construct upper and lower bounds for the conditional expectation of the inverse demand. These bounds can be translated into moment inequalities that are shown to yield consistent and asymptotically normal point estimators for demand parameters under natural conditions. In Monte Carlo simulations, we demonstrate that the new approach works well even when the fraction of zeroes is as high as 95%. We apply our estimator to supermarket scanner data and find that correcting the bias caused by zeroes has important empirical implications, for example, price elasticities become twice as large when zeroes are properly controlled.
This paper analyzes risk aversion in discriminatory share auctions. I generalize the k-step share auction model of Kastl (2011, 2012) and establish that marginal profits are set-identified for any given coefficient of constant absolute risk aversion. I also derive necessary conditions for best-response behavior, which allows determining risk preferences from bidding data. Further, I show how the bidders' optimality conditions allow computing bounds on the marginal profits that are tighter than those currently available. I use my results to estimate import rents from Swiss tariff-rate quotas on high-quality beef. Rents are overestimated when ignoring risk aversion, and rent extraction is underestimated. Small bidders (small, privately owned butcheries) are more risk averse than large bidders (general retailers). Best response violations are few and uniform across bidder sizes.
This paper provides estimation and inference methods for conditional average treatment effects (CATE) characterized by a high-dimensional parameter in both homogeneous cross-sectional and unit-heterogeneous dynamic panel data settings. In our leading example, we model CATE by interacting the base treatment variable with explanatory variables. The first step of our procedure is orthogonalization, where we partial out the controls and unit effects from the outcome and the base treatment and take the cross-fitted residuals. This step uses a novel generic cross-fitting method that we design for weakly dependent time series and panel data. This method “leaves out the neighbors” when fitting nuisance components, and we theoretically power it by using Strassen's coupling. As a result, we can rely on any modern machine learning method in the first step, provided it learns the residuals well enough. Second, we construct an orthogonal (or residual) learner of CATE—the lasso CATE—that regresses the outcome residual on the vector of interactions of the residualized treatment with explanatory variables. If the complexity of CATE function is simpler than that of the first-stage regression, the orthogonal learner converges faster than the single-stage regression-based learner. Third, we perform simultaneous inference on parameters of the CATE function using debiasing. We also can use ordinary least squares in the last two steps when CATE is low-dimensional. In heterogeneous panel data settings, we model the unobserved unit heterogeneity as a weakly sparse deviation from Mundlak's (1978) model of correlated unit effects as a linear function of time-invariant covariates and make use of L1-penalization to estimate these models. We demonstrate our methods by estimating price elasticities of groceries based on scanner data. We note that our results are new even for the cross-sectional (i.i.d.) case.
In this paper, we introduce a method of generating bootstrap samples with unknown patterns of cross- sectional/spatial dependence, which we call the spatial dependent wild bootstrap. This method is a spatial counterpart to the wild dependent bootstrap of Shao (2010) and generates data by multiplying a vector of independently and identically distributed external variables by the eigendecomposition of a bootstrap kernel. We prove the validity of our method for studentized and unstudentized statistics under a linear array representation of the data. Simulation experiments document the potential for improved inference with our approach. We illustrate our method in a firm-level regression application investigating the relationship between firms' sales growth and the import activity in their local markets using unique firm-level and imports data for Canada.
We analyze the role of selection bias in generating changes in the observed distribution of female hourly wages in the United States using CPS data for the years 1975 to 2020. We account for selection bias from the employment decision by modeling the distribution of the number of working hours and estimating a nonseparable model of wages. We decompose changes in the wage distribution into composition, structural, and selection effects. Composition effects increased wages at all quantiles while the impact of the structural effects varied by time period and quantile. Changes in the role of selection only appeared at the lower quantiles of the wage distribution. The evidence suggests that there was positive selection in the 1970s, which diminished until the later 1990s. This reduced wages at lower quantiles and increased wage inequality. Post 2000 there appears to be an increase in positive sorting, which reduced the selection effects on wage inequality.
Expectations affect economic decisions, and inaccurate expectations are costly. Expectations can be wrong due to either bias (systematic mistakes) or noise (unsystematic mistakes). We develop a framework for quantifying the level of noise in survey expectations. The method is based on the insight that theoretical models of expectation formation predict a factor structure for individual expectations. Using data from professional forecasters, we find that the magnitude of noise is large (10%–30% of forecast MSE) and comparable to bias. We illustrate how our estimates can be applied to calibrate models with incomplete information and bound the effects of measurement error.
We introduce a novel simulated certainty equivalent approximation (SCEQ) method for solving dynamic stochastic problems. Our examples show that SCEQ can quickly solve high-dimensional finite- or infinite-horizon, stationary or nonstationary dynamic stochastic problems with hundreds of state variables, a wide state space, and occasionally binding constraints. With the SCEQ method, a desktop computer will suffice for large problems, but it can also use parallel tools efficiently. The SCEQ method is simple, stable, and can utilize any solver, making it suitable for solving complex economic problems that cannot be solved by other algorithms.
We study the relationship between monetary policy and long-term rates in a structural, general equilibrium model estimated on both macro- and yield-data from the United States. Regime shifts in the conditional variance of productivity shocks, or “uncertainty shocks,” are a crucial driver of bond risk premia. We highlight three main results. First, our term premia on 10-year bonds are highly correlated with estimates from the affine literature, even if less markedly volatile. Second, uncertainty shocks also induce an increase in equity premia and exert downward pressure on consumption and inflation. An increase in equity premia will therefore be accompanied by a cut in policy interest rates, even if the policy rule does not directly react to equity prices. This model mechanism is consistent with the empirical evidence on the “Fed put.” Third, model-implied long-term inflation expectations are less dogmatically anchored than survey-based measures over the 2000s.
This paper uses an estimated Heterogeneous Agent New Keynesian (HANK) model to evaluate the quantitative importance of two channels in driving aggregate consumption fluctuations in the US: (i) precautionary savings against unemployment risk and (ii) MPC heterogeneity. I find that MPC heterogeneity is the dominant channel because a large fraction of households are close to the borrowing limit. The empirical average MPC target in HANK generates counterfactually volatile aggregate consumption, and thus makes it more difficult for the estimated model to match the persistence of the aggregate data, indicating an MPC puzzle. This is because the likelihood-based estimation favors a low degree of nominal rigidity and responsive monetary policy in the HANK model to reduce the discrepancy between consumption volatility in the model and in the data. The low degree of nominal rigidity and responsive monetary policy reduce the persistence of endogenous variables in the model.
We investigate how risk aversion (RA) shapes the informative content of prices in an experimental asset market, where traders are sorted according to their RA. RA should induce steeper individual demands and, under its most common parametrizations, drive equilibrium prices closer to revealing the state. Results support the prediction on individual demands, but not the prediction on prices, which do not vary with RA and are close to the risk-neutral benchmark. This purported conflict is due to traders, particularly the more risk-averse ones, conveying into prices only part of their information.
We use an analytically tractable heterogeneous-agent (HANK) version of the standard New Keynesian model to show how the size of fiscal multipliers depends on (i) the distribution of factor incomes, and (ii) the source of nominal rigidities. With sticky prices but flexible wages, the standard representative-agent (RANK) model predicts large multipliers because profits fall after a fiscal stimulus and the resulting negative income effect makes the representative worker work harder. Our HANK model, where workers do not own stock, and thus do not receive profit income, predicts smaller fiscal multipliers. In fact, they are smaller with sticky prices than with flexible prices. When wages are the source of nominal rigidity, in contrast, fiscal multipliers are close to one, independently of income heterogeneity and price stickiness.
We show that the effectiveness of redistribution policy is tied to how much inflation it generates, and thereby to monetary-fiscal adjustments that ultimately finance the transfers. In the monetary regime, taxes increase to finance transfers while in the fiscal regime, inflation rises, imposing inflation taxes on public debt holders. We show analytically that the fiscal regime generates larger and more persistent inflation than the monetary regime. In a two-sector model, we quantify the effects of the CARES Act in a COVID recession. We find that transfer multipliers are larger, and that moreover, redistribution is Pareto improving, under the fiscal regime.
We estimate a production-based general equilibrium model featuring demand- and supply-side uncertainty and an endogenous term premium. Using term structure and macroeconomic data, we find sizable effects of uncertainty on risk premia and business cycle fluctuations. Both demand- and supply-side uncertainty imply large contractions in real activity and an increase in term premia, but supply-side uncertainty has larger effects on inflation and investment. We introduce a novel analytical decomposition to illustrate how multiple distinct endogenous risk wedges account for these differences. Supply and demand uncertainty are strongly correlated in the beginning of our sample, but decouple after the Great Recession.
We identify the main shock driving fluctuations in long-horizon productivity expectations, consistent with theories of TFP news. The identified shock induces strong comovement patterns in output, consumption, investment, employment, and stock prices even though TFP does not change significantly for more than 2 years. A labor search model in which wages are determined by a cash-flow sharing rule, rather than the present value of match surplus, matches the observed responses to the news shock. The model also matches the empirical patterns of vacancies, labor force participation, hours, and job-finding rates. The proposed wage rule is consistent with empirical responses of wages to both anticipated and unanticipated productivity changes.
This paper develops a sufficient statistics approach for estimating the role of search frictions in wage dispersion and life-cycle wage growth. We show how the wage dynamics of displaced workers are directly informative of both for a large class of search models. Specifically, the correlation between pre- and post-displacement wages is informative of frictional wage dispersion. Furthermore, the fraction of displaced workers who suffer a wage loss is informative of frictional wage growth and job-to-job mobility, independent of the job-offer distribution and other labor-market parameters. Applying our methodology to US data, we find that search frictions account for less than 20% of wage dispersion. In addition, we estimate that between 40 to 80% of workers experience no frictional wage growth during an employment spell. Our approach allows us to estimate how frictions change over time. We find that frictional wage dispersion has declined substantially since 1980 and that frictional wage growth, while low, is more important toward the end of expansionary periods. We finish by estimating two versions of a random search model to show how at least two different mechanisms—involuntary job transitions or compensating differentials—can reconcile our results with the job-to-job mobility seen in the data. Regardless of the mechanism, the estimated models show that frictional wage growth accounts for about 15% of life-cycle wage growth.
We estimate sectoral spillovers around the Great Moderation with the help of forecast error variance decomposition tables. Obtaining such tables in high dimensions is challenging because they are functions of the estimated vector autoregressive coefficients and the residual covariance matrix. In a simulation study, we compare various regularization methods on both and conduct a comprehensive analysis of their performance. We show that standard estimators of large connectedness tables lead to biased results and high estimation uncertainty, both of which are mitigated by regularization. To explore possible causes for the Great Moderation, we apply a cross-validated estimator on sectoral spillovers of industrial production in the US from 1972 to 2019. We find that the spillover network has considerably weakened, which hints at structural change, for example, through improved inventory management, as a critical explanation for the Great Moderation.
This paper studies inference for the realized Laplace transform (RLT) of volatility in a fixed-span setting using bootstrap methods. Specifically, since standard wild bootstrap procedures deliver inconsistent inference, we propose a local Gaussian (LG) bootstrap, establish its first-order asymptotic validity, and use Edgeworth expansions to show that the LG bootstrap inference achieves second-order asymptotic refinements. Moreover, we provide new Laplace transform-based estimators of the spot variance as well as the covariance, correlation, and beta between two semimartingales, and adapt our bootstrap procedure to the requisite scenario. We establish central limit theory for our estimators and first-order asymptotic validity of their associated bootstrap methods. Simulations demonstrate that the LG bootstrap outperforms existing feasible inference theory and wild bootstrap procedures in finite samples. Finally, we illustrate the use of the new methods by examining the coherence between stocks and bonds during the global financial crisis of 2008 as well as the COVID-19 pandemic stock sell-off during 2020, and by a forecasting exercise.
We consider fixed-effects binary choice models with a fixed number of periods T and regressors without a large support. If the time-varying unobserved terms are i.i.d. with known distribution F, Chamberlain (2010) shows that the common slope parameter is point identified if and only if F is logistic. However, he only considers in his proof T = 2. We show that the result does not generalize to T ≥ 3: the common slope parameter can be identified when F belongs to a family including the logit distribution. Identification is based on a conditional moment restriction. Under restrictions on the covariates, these moment conditions lead to point identification of relative effects. If T = 3 and mild conditions hold, GMM estimators based on these conditional moment restrictions reach the semiparametric efficiency bound. Finally, we illustrate our method by revisiting Brender and Drazen (2008).
Keynes (1921) and Ellsberg (1961) have articulated an aversion toward betting on an urn containing balls of two colors of unknown proportion to one with a 50–50 composition. Keynes views this as reflecting different preferences for bets arising from different sources of uncertainty. Ellsberg describes this as weighting the priors arising from the unknown urn pessimistically. In two experiments, we observe substantial links between attitude toward almost-objective uncertainty and attitudes toward multiple-prior uncertainties in terms of ambiguity and its corresponding compound risk. Our findings point to a shared component across domains of uncertainty and motivate the need for further theoretical development.
When quantifying the importance of supply and demand for oil price fluctuations, a wide range of estimates have been reported. Models identified via a sharp upper bound on the short-run price elasticity of supply find supply shocks to be minor drivers. In turn, when replacing the upper bound with a weakly informative prior, supply shocks turn out to be substantially more important. In this paper, I revisit the evidence in a model that combines weakly informative priors with identification by non-Gaussianity. For this purpose, a SVAR is developed where the unknown distributions of the structural shocks are modeled nonparametrically. The empirical findings suggest that once identification by non-Gaussianity is incorporated into the model, posterior mass of the short-run oil supply elasticity shifts toward zero and oil supply shocks become minor drivers of oil prices. In terms of contributions to the forecast error variance of oil prices, the model arrives at median estimates of just 6% over a 16-month horizon.
It is well known that Local Projections (LP) residuals are autocorrelated. Conventional wisdom says that LP have to be estimated by OLS and that GLS is not possible because the autocorrelation process is unknown and/or because the GLS estimator would be inconsistent. I show that the autocorrelation process of LP can be written as a Vector Moving Average (VMA) process of the Wold errors and impulse responses and that autocorrelation can be corrected for using a consistent GLS estimator. Monte Carlo simulations show that estimating LP with GLS can lead to more efficient estimates.
We develop an importance sampler for sign restricted Bayesian structural vector autoregressive models. The algorithm nests as a special case the sampler associated with the popular Normal inverse Wishart Uniform prior, while allowing to move beyond such prior in medium sized models. We then propose a prior on contemporaneous impulse responses that provides flexibility on the magnitude and shape of the impact responses. We illustrate the quantitative relevance of the choice of the prior in an application to US monetary policy shocks. We find that the real effects of monetary policy shocks are stronger under our proposed prior than in the Normal inverse Wishart Uniform setup.
We propose a demand estimation method that allows for a large number of zero- sale observations, rich unobserved heterogeneity, and endogenous prices. We do so by modeling small market sizes through Poisson arrivals. Each of these arriving consumers solves a standard discrete choice problem. We present a Bayesian IV estimation approach that addresses sampling error in product shares and scales well to rich data environments. The data requirements are traditional market-level data as well as a measure of market sizes or consumer arrivals. After presenting simulation studies, we demonstrate the method in an empirical application of air travel demand.
This paper studies how the strength of social ties is affected by the geographical location of other individuals and their social capital. We characterize the equilibrium in terms of both social interactions and social capital. We show that lower travel costs increase not only the interaction frequency but also the social capital for all agents. We also show that the equilibrium frequency of interactions is lower than the efficient one. Using a unique geocoded data set of friendship networks among adolescents in the United States, we structurally estimate the model and show that indeed agents socially interact less than that at the first best optimum. Our policy analysis suggests that, at the same cost, subsidizing social interactions yield a higher total welfare than subsidizing transportation costs.
Capital reallocation between firms is procyclical and leads to variations in measured aggregate productivity. In this paper, we ask how much of the cyclical variation in measured productivity is the consequence of capital reallocation. We build a heterogeneous-firm model to study the effects of exogenous shocks to total factor productivity (TFP) and to the costs of reallocation. These shocks cause an endogenous cyclicality of measured aggregate productivity. Only a model driven by exogenous TFP shocks is able to generate both data-consistent cyclical movements in reallocation and sizeable variations in measured aggregate productivity. We find that capital reallocation does not play a major role in amplifying aggregate productivity variations over the business cycle.
This paper studies how tax-and-transfer progressivity influences aggregate fluctuations when interacting with household heterogeneity. Using a simple static model of the extensive margin labor supply, we analytically characterize how a degree of progressivity influences differential labor supply responses to aggregate conditions across heterogeneous households. We then build a quantitative dynamic general equilibrium model with both idiosyncratic and aggregate productivity shocks and show that it delivers moderately procyclical average labor productivity and a large cyclical volatility of aggregate hours relative to output. Our quantitative exercises suggest that progressivity at the bottom of the income distribution shaped by the phasing out of transfers is key for these findings. Finally, we provide suggestive empirical evidence on the heterogeneity of employment responses across the wage distribution.
We introduce Behavioral Learning Equilibria (BLE) into a multivariate linear framework and apply it to New Keynesian DSGE models. In a BLE, boundedly rational agents use simple, but optimal AR(1) forecasting rules whose parameters are consistent with the observed sample mean and autocorrelation of past data. We study the BLE concept in a standard 3-equation New Keynesian model and develop an estimation methodology for the canonical Smets and Wouters (2007) model. A horse race between Rational Expectations (REE), BLE, and constant gain learning models shows that the BLE model outperforms the REE benchmark and is competitive with constant gain learning models in terms of in-sample and out-of-sample fitness. Sample-autocorrelation learning of optimal AR(1) beliefs provides the best fit when short-term survey data on inflation expectations are taken into account in the estimation. As a policy application, we show that optimal Taylor rules under AR(1) expectations inherit history dependence and require a lower degrees of interest rate smoothing than REE.
When applying to a university, students and their parents devote considerable time acquiring information about university programs in order to form preferences. We explore ways to reduce wasteful information acquisition, that is, to help students avoid acquiring information about out-of-reach schools or universities, using a market design approach. Focusing on markets where students are ranked by universities based on exam scores, we find that, both theoretically and experimentally, a sequential serial dictatorship mechanism leads to higher student welfare than a direct serial dictatorship mechanism. This is because the sequential mechanism informs students about which universities are willing to admit them, thereby directing their search. Our experiments also show that the sequential mechanism has behavioral advantages because subjects deviate from the optimal search strategy less frequently than under the direct mechanism. Furthermore, providing historical cutoff scores under the direct mechanism can increase student welfare, especially when the information costs are high, although the observed effect is weaker than that of a sequential mechanism.
This paper proposes a new approach to identification of the semiparametric multinomial choice model with fixed effects. The framework employed is the semiparametric version of the traditional multinomial logit with the fixed-effects model (Chamberlain (1980)). This semiparametric multinomial choice model places no restrictions on either the joint distribution of the random utility disturbances across choices or their within group (or across time) correlations. We show that a novel within-group comparison leads to a set of conditional moment inequalities. Our main finding shows that the derived conditional moment inequalities yield the sharp identified set for the random utility covariate index, while avoiding the incidental parameter problem. Specializing this result to the binary choice case shows that Manski (1987)'s conditional moment inequalities still lead to sharp bounds without restrictions on covariates.
We develop a new permutation test for inference on a subvector of coefficients in linear models. The test is exact when the regressors and the error terms are independent. Then we show that the test is asymptotically of correct level, consistent, and has power against local alternatives when the independence condition is relaxed, under two main conditions. The first is a slight reinforcement of the usual absence of correlation between the regressors and the error term. The second is that the number of strata, defined by values of the regressors not involved in the subvector test, is small compared to the sample size. The latter implies that the vector of nuisance regressors is discrete. Simulations and empirical illustrations suggest that the test has good power in practice if, indeed, the number of strata is small compared to the sample size.
We present a geometric approach to the finite Rational Inattention (RI) model, recasting it as a convex optimization problem with reduced dimensionality that is well suited to numerical methods. We provide an algorithm that outperforms existing RI computation techniques in terms of both speed and accuracy in both static and dynamic RI problems. We further introduce methods to quantify the impact of numerical inaccuracy on the model's outcomes and to produce robust predictions regarding the most frequently implemented actions.
We use supervised machine learning to approximate the expectations typically contained in the optimality conditions of an economic model in the spirit of the parameterized expectations algorithm (PEA) with stochastic simulation. When the set of state variables is generated by a stochastic simulation, it is likely to suffer from multicollinearity. We show that a neural network-based expectations algorithm can deal efficiently with multicollinearity by extending the optimal debt management problem studied by Faraglia, Marcet, Oikonomou, and Scott (2019) to four maturities. We find that the optimal policy prescribes an active role for the newly added medium-term maturities, enabling the planner to raise financial income without increasing its total borrowing in response to expenditure shocks. Through this mechanism, the government effectively subsidizes the private sector during recessions.
We experimentally study how people form predictive models of simple data generating processes (DGPs), by showing subjects data sets and asking them to predict future outputs. We find that subjects: (i) often fail to predict in this task, indicating a failure to form a model, (ii) often cannot explicitly describe the model they have formed even when successful, and (iii) tend to be attracted to the same, simple models when multiple models fit the data. Examining a number of formal complexity metrics, we find that all three patterns are well organized by metrics suggested by Lipman (1995) and Gabaix (2014) that describe the information processing required to deploy models in prediction.
We propose a novel way of measuring trust in institutions, which draws on the experimental method used to elicit time preferences. Our measure is provided in the meaningful metric of the subjective probability of trustworthiness of the trustee. In a lab-in-the-field setting in the Philippines, we measure trust in two different financial institutions. Additionally, we exploit exogenous variation in the eligibility for a future payment to examine whether a promise fulfilled by the institution increases trust and changes individual financial behavior. We find that eligible individuals significantly increase savings held with the institution.
Our confidence set quantifies the statistical uncertainty from data-driven group assignments in grouped panel models. It covers the true group memberships jointly for all units with pre-specified probability and is constructed by inverting many simultaneous unit-specific one-sided tests for group membership. We justify our approach under N,T → ∞ asymptotics using tools from high-dimensional statistics, some of which we extend in this paper. We provide Monte Carlo evidence that the confidence set has adequate coverage in finite samples. An empirical application illustrates the use of our confidence set.
This paper studies inference in randomized controlled trials with multiple treatments, where treatment status is determined according to a “matched tuples” design. If there are possible treatments, then by a matched tuples design, we mean an experimental design where units are sampled i.i.d. from the population of interest, grouped into “homogeneous” blocks of size , and finally, within each block, exactly one individual is randomly assigned to each of the treatments. We first study estimation and inference for matched tuples designs in the general setting where the parameter of interest is a vector of linear contrasts over the collection of average potential outcomes for each treatment. Parameters of this form include standard average treatment effects used to compare one treatment relative to another, but also include parameters that may be of interest in the analysis of factorial designs. We first establish conditions under which a sample analog estimator is asymptotically normal and construct a consistent estimator of its corresponding asymptotic variance. Combining these results establish the asymptotic exactness of tests based on these estimators. In contrast, we show that, for two common testing procedures based on t-tests constructed from linear regressions, one test is generally conservative while the other is generally invalid. We go on to apply our results to study the asymptotic properties of what we call “fully-blocked” 2K factorial designs, which are simply matched tuples designs applied to a full factorial experiment. Leveraging our previous results, we establish that our estimator achieves a lower asymptotic variance under the fully-blocked design than that under any stratified factorial design, which stratifies the experimental sample into a finite number of “large” strata. A simulation study and empirical application illustrate the practical relevance of our results.
In many set-identified models, it is difficult to obtain a tractable characterization of the identified set. Therefore, researchers often rely on nonsharp identification conditions, and empirical results are often based on an outer set of the identified set. This practice is often viewed as conservative yet valid because an outer set is always a superset of the identified set. However, this paper shows that when the model is refuted by the data, two sets of nonsharp identification conditions derived from the same model could lead to disjoint outer sets and conflicting empirical results. We provide a sufficient condition for the existence of such discordancy, which covers models characterized by conditional moment inequalities and the Artstein (1983) inequalities. We also derive sufficient conditions for the nonexistence of discordant submodels, therefore providing a class of models for which constructing outer sets cannot lead to misleading interpretations. In the case of discordancy, we follow Masten and Poirier (2021) by developing a method to salvage misspecified models, but unlike them, we focus on discrete relaxations. We consider all minimum relaxations of a refuted model that restores data consistency. We find that the union of the identified sets of these minimum relaxations is robust to detectable misspecifications and has an intuitive empirical interpretation.
Property transaction taxes—also known as stamp duty—are widely viewed as an inefficient form of taxation. In this paper, we examine the welfare implications of removing stamp duty in a general equilibrium overlapping generation model with heterogeneous agents. Our model features an idiosyncratic shock to housing preferences, which may create mismatch or induce households to move. We calibrate the model to the Australian housing market, and conduct counterfactual policy experiments where stamp duty is replaced with recurrent property or consumption taxes. We find that removing stamp duty raises household mobility and reduces the degree of housing mismatch substantially. When examining steady states, we find that newborn households prefer entering an economy with a recurring property tax rather than one with stamp duty. In contrast, when examining the transition we find that existing households prefer replacing stamp duty with a consumption tax.
We study how technological change affects between- and within-education-group inequality in the United States. We develop a model with heterogeneous workers and firms in which the demand for skills is characterized by firms' recruiting behavior. We use the model to quantify the relative contribution of two types of technological change that affect the relative demand for skilled labor: technological change in firm-specific productivity and technological change in labor productivity. We find that technological change in labor productivity, in the form of higher returns to skill in production, is the main driver of the increase in between- and within-group inequality. Technological change in firm productivity, in the form of higher firm productivity dispersion, plays a less important role in explaining rising inequality, except for the increase in within-group inequality for workers without a college degree.
Structural quantitative work in international economics typically models trade costs as a log-linear function of exogenous trade-policy variables. We propose a structural approach that allows for a nonparametric relationship and for treating tariff and nontariff trade-policy variables as potentially endogenous. The data reject the assumption of log-linearity of trade costs in both tariff- and nontariff-policy variables. We assess the effects of a unilateral increase of US tariffs on Chinese imports by 10 percentage points and document that the estimated effects on real bilateral trade-flow changes would be substantially underestimated by standard approaches.
All parameters in structural vector autoregressive (SVAR) models are locally identified when the structural shocks are independent and follow non-Gaussian distributions. Unfortunately, standard inference methods that exploit such features of the data for identification fail to yield correct coverage for structural functions of the model parameters when deviations from Gaussianity are small. To this extent, we propose a locally robust semiparametric approach to conduct hypothesis tests and construct confidence sets for structural functions in SVAR models. The methodology fully exploits non-Gaussianity when it is present, but yields correct size/coverage for local-to-Gaussian densities. Empirically, we revisit two macroeconomic SVAR studies where we document mixed results. For the oil price model of Kilian and Murphy (2012), we find that non-Gaussianity can robustly identify reasonable confidence sets, whereas for the labor supply–demand model of Baumeister and Hamilton (2015) this is not the case. Moreover, these exercises highlight the importance of using weak identification robust methods to assess estimation uncertainty when using non-Gaussianity for identification.
Evaluating policy in imperfectly competitive markets requires understanding firm behavior. While researchers test conduct via model selection and assessment, we present the advantages of Rivers and Vuong (2002) (RV) model selection under misspecification. However, degeneracy of RV invalidates inference. With a novel definition of weak instruments for testing, we connect degeneracy to instrument strength, derive weak instrument properties of RV, and provide a diagnostic for weak instruments by extending the framework of Stock and Yogo (2005) to model selection. We test vertical conduct (Villas-Boas (2007)) using common instrument sets. Some are weak, providing no power. Strong instruments support manufacturers setting retail prices.
I show that stochastic contracts generate powerful incentives when agents suffer from probability distortion. When implementing these contracts, the principal can target probability distortions in order to inflate the agent's perceived benefits of exerting high levels of effort. This novel source of motivation is absent in contracts traditionally regarded as optimal. A theoretical framework and an experiment demonstrate that stochastic contracts implemented with small probabilities, which expose the agent to a high degree of risk, generate higher performance than cost-equivalent contracts with lower or no risk exposure. I find that probability distortions that result from likelihood insensitivity—cognitive limitations that prevent the accurate evaluation of probabilities—account for this finding. The results highlight the limits of contracts traditionally regarded as optimal.
Using rural household survey data from West Bengal, we find that voters respond positively to excludable government welfare benefits but not to local public good programs, while reporting having benefited from both. Consistent with these voting patterns, shocks to electoral competition induced by exogenous redistricting of villages resulted in upper-tier governments manipulating allocations across local governments only for excludable benefit programs. Using a hierarchical budgeting model, we argue these results provide credible evidence of the presence of clientelism rather than programmatic politics.
This paper examines how objective and subjective heterogeneity in life expectancy affects savings behavior of healthy and unhealthy people. Using data from the Health and Retirement Study, we first document systematic biases in survival beliefs across self-reported health: those in poor health not only have a shorter actual lifespan but also underestimate their remaining life time. To gauge the effect on savings behavior and wealth accumulation, we use an overlapping-generations model where survival probabilities and beliefs evolve according to a health and survival process estimated from data. We conclude that differences in life expectancy are important to understand savings behavior, and that the belief biases, especially among the unhealthy, can explain up to a fifth of the observed health-wealth gap.
Social scientists have long been interested in marital homogamy and its relationship with inequality. However, measuring homogamy is not straightforward, particularly when one is interested in assessing marital sorting based on multiple traits. In this paper, we argue that Separate Extreme Value (SEV) models not only generate a matching function with several desirable theoretical properties, but they are also suited for the study of multidimensional sorting. Specifically, we use rich small-scale survey data to examine sorting among parents of school-age children in Naples. We show that homogamy is pervasive; not only do men and women sort by age, education, and physical characteristics, but they also look for partners that share similar health-related behavior and risk attitude. However, we also show that these marital patterns are well explained by a low number of dimensions, the most important being age cohort and human capital. In particular, human capital relates to various “outcomes” of the post-matching relationship. Children of parents with a high human capital endowment perform better at school, although they report lower levels of subjective well-being and of perceived quality of relationship with their mothers.
Bias correction can often improve the finite sample performance of estimators. We show that the choice of bias correction method has no effect on the higher-order variance of semiparametrically efficient parametric estimators, so long as the estimate of the bias is asymptotically linear. It is also shown that bootstrap, jackknife, and analytical bias estimates are asymptotically linear for estimators with higher-order expansions of a standard form. In particular, we find that for a variety of estimators the straightforward bootstrap bias correction gives the same higher-order variance as more complicated analytical or jackknife bias corrections. In contrast, bias corrections that do not estimate the bias at the parametric rate, such as the split-sample jackknife, result in larger higher-order variances in the i.i.d. setting we focus on. For both a cross-sectional MLE and a panel model with individual fixed effects, we show that the split-sample jackknife has a higher-order variance term that is twice as large as that of the “leave-one-out” jackknife.
We develop a test for deciding whether the linear spaces spanned by the factor exposures of a large cross-section of assets toward latent systematic risk factors at two distinct points in time are the same. The test uses a panel of asset returns in local windows around the two time points. The asymptotic setup is of joint type: the number of assets and the number of return observations per asset increase asymptotically while the length of both time windows shrinks. We estimate the factor exposures, up to rotation, over the two periods using classical principal component analysis and evaluate their projection discrepancy, which is rotation invariant. This projection discrepancy is then centered with one between factor exposures computed over a partition of the pooled return data into odd and even increments. We derive the limit distribution of the statistic under the null hypothesis and develop an easy-to-implement bootstrap for constructing the critical region of the test. The test is applied to intraday financial data to determine whether the linear span of assets' systematic risk exposures differ during a trading day or after a release of important economic information.
In this paper, we study the asymptotic behavior of specification tests in conditional moment restriction models under first-order local identification failure with dependent data. More specifically, we obtain conditions under which the conventional specification test for conditional moment restrictions retains its standard normal limit when first-order local identification fails but global identification is still attainable. In the process, we derive some novel intermediate results that include extending the first- and second-order local identification framework to models defined by conditional moment restrictions, establishing the rate of convergence of the GMM estimator and characterizing the asymptotic representation for degenerate U-statistics under strong mixing dependence. Importantly, the specification test is robust to first-order local identification failure regardless of the number of directions in which the Jacobian of the conditional moment restrictions is degenerate and remains valid even if the model is first-order identified.
Building on the sequential identification result of Aguirregabiria and Mira (2019), this paper develops estimation and inference procedures for static games of incomplete information with payoff-relevant unobserved heterogeneity and multiple equilibria. With payoff-relevant unobserved heterogeneity, sequential estimation and inference face two main challenges: the matching-types problem and a large number of matchings. We tackle the matching-types problem by constructing a new minimum-distance criterion for the correct matching and the payoff function with both correct and incorrect “moments.” To handle large numbers of matchings, we propose a novel and computationally fast multistep moment selection procedure. We show that asymptotically, it achieves a time complexity that is linear in the number of “moments” when the occurrence of multiple equilibria does not depend on the number of “moments.” Based on this procedure, we construct a consistent estimator of the payoff function, an asymptotically uniformly valid and easy-to-implement test for linear hypotheses on the payoff function, and a consistent method to group payoff functions according to the unobserved heterogeneity. Extensive simulations demonstrate the finite sample efficacy of our procedures.
We study the Latent Dirichlet Allocation model, a popular Bayesian algorithm for text analysis. We show that the model's parameters are not identified, which suggests that the choice of prior matters. We characterize the range of values that the posterior mean of a given functional of the model's parameters can attain in response to a change in the prior, and we suggest two algorithms that report this range. Both of our algorithms rely on obtaining multiple Nonnegative Matrix Factorizations of either the posterior draws of the corpus' population term-document frequency matrix or of its maximum likelihood estimator. The key idea is to maximize/minimize the functional of interest over all these nonnegative matrix factorizations. To illustrate the applicability of our results, we revisit recent work studying the effects of increased transparency on the communication structure of monetary policy discussions in the United States.
This paper studies covariate adjusted estimation of the average treatment effect in stratified experiments. We work in a general framework that includes matched tuples designs, coarse stratification, and complete randomization as special cases. Regression adjustment with treatment-covariate interactions is known to weakly improve efficiency for completely randomized designs. By contrast, we show that for stratified designs such regression estimators are generically inefficient, potentially even increasing estimator variance relative to the unadjusted benchmark. Motivated by this result, we derive the asymptotically optimal linear covariate adjustment for a given stratification. We construct several feasible estimators that implement this efficient adjustment in large samples. In the special case of matched pairs, for example, the regression including treatment, covariates, and pair fixed effects is asymptotically optimal. We also provide novel asymptotically exact inference methods that allow researchers to report smaller confidence intervals, fully reflecting the efficiency gains from both stratification and adjustment. Simulations and an empirical application demonstrate the value of our proposed methods.
We propose a new estimator for average causal effects of a binary treatment with panel data in settings with general treatment patterns. Our approach augments the popular two-way-fixed-effects specification with unit-specific weights that arise from a model for the assignment mechanism. We show how to construct these weights in various settings, including the staggered adoption setting, where units opt into the treatment sequentially but permanently. The resulting estimator converges to an average (over units and time) treatment effect under the correct specification of the assignment model, even if the fixed- effect model is misspecified. We show that our estimator is more robust than the conventional two-way estimator: it remains consistent if either the assignment mechanism or the two-way regression model is correctly specified. In addition, the proposed estimator performs better than the two-way-fixed-effect estimator if the outcome model and assignment mechanism are locally misspecified. This strong robustness property underlines and quantifies the benefits of modeling the assignment process and motivates using our estimator in practice. We also discuss an extension of our estimator to handle dynamic treatment effects.
Regression discontinuity is a popular tool for analyzing economic policies or treatment interventions. This research extends the classic static RD model to a dynamic framework, where observations are eligible for repeated RD events and, therefore, treatments. Such dynamics often complicate the identification and estimation of long-term average treatment effects. Empirical papers with such designs have so far ignored the dynamics or adopted restrictive identifying assumptions. This paper presents identification strategies under various sets of weaker identifying assumptions and proposes associated estimation and inference methods. The proposed methods are applied to revisit the seminal study of Cellini, Ferreira, and Rothstein (2010) on long-term effects of California local school bonds.
Economic data are often contaminated by measurement errors and truncated by ranking. This paper shows that the classical measurement error model with independent and additive measurement errors is identified nonparametrically using only two order statistics of repeated measurements. The identification result confirms a hypothesis by Athey and Haile (2002) for a symmetric ascending auction model with unobserved heterogeneity. Extensions allow for heterogeneous measurement errors, broadening the applicability to additional empirical settings, including asymmetric auctions and wage offer models. We adapt an existing simulated sieve estimator and illustrate its performance in finite samples.
This paper considers the problem of deriving heteroskedasticity and autocorrelation robust (HAR) inference about a scalar parameter of interest. The main assumption is that there is a known upper bound on the degree of persistence in data. I derive finite-sample optimal tests in the Gaussian location model and show that the robustness-efficiency tradeoffs embedded in the optimal tests are essentially determined by the maximal persistence. I find that with an appropriate adjustment to the critical value, it is nearly optimal to use the so-called equal-weighted cosine (EWC) test, where the long-run variance is estimated by projections onto q type II cosines. The practical implications are an explicit link between the choice of q and assumptions on the underlying persistence, as well as a corresponding adjustment to the usual Student-t critical value. I illustrate the results in two empirical examples.
We study a mechanism that gives students the option of paying higher tuition to attend their preferred schools. This seat-purchasing mechanism is neither strategyproof nor stable. Our paper combines administrative and survey data to estimate students' preferences and conducts welfare analysis. We find that changing from a deferred acceptance mechanism to the cadet-optimal stable mechanism reduces students' welfare but that adopting the observed seat-purchasing mechanism alleviates this welfare loss. Moreover, students from affluent communities prefer to pay higher tuition to stay at preferred schools, while those from less affluent communities are more likely be priced out to lower-quality schools.
Compared to the distributions of earnings, the distributions of wealth in the US and many other countries are strikingly concentrated on the top and skewed to the right. To explain the income and wealth inequality, we provide a tractable heterogeneous-agent model with incomplete markets in continuous time. We separate illiquid capital assets from liquid bond assets and introduce jump risks to capital income, which are crucial for generating a thicker tail of the wealth distribution than that of the labor income distribution. Under recursive utility, we derive optimal consumption and wealth in closed form and show that the stationary wealth distribution has an exponential right tail that closely approximates a power-law distribution. Our calibrated model can match the income and wealth distributions in the US data including the extreme right tail of the wealth distribution.
This paper quantifies mechanisms through which heterogeneity in household finances affects the transmission of monetary policy, considering housing tenure choices over the life cycle. Our analysis also identifies challenges for monetary policy related to housing busts. It focuses on the four largest economies in the euro area: France, Germany, Italy, and Spain. Through the lens of our model, we find that home ownership and endogenous transitions from renting to owning are key elements for the extent of cross-country asymmetries in aggregate consumption responses to changes in the real interest rate. Across groups with different housing tenure, we find that the consumption response of homeowners to interest rate changes tends to be larger than the response of renters, particularly if these homeowners are indebted and do not adjust their illiquid housing wealth.
We develop a new model of cycles and crises in emerging markets, featuring an occasionally binding borrowing constraint and stochastic volatility, and estimate it with quarterly data for Mexico since 1981. We propose an endogenous regime-switching formulation of the occasionally binding borrowing constraint, develop a general perturbation method to solve the model, and estimate it using Bayesian methods. We find that the model fits the Mexican data well without systematically relying on large shocks, matching the typical stylized facts of emerging market business cycles and Mexico's history of sudden stops in capital flows. We also find that interest rate shocks play a smaller role in driving both cycles and crises than previously found in the literature.
We show how to use field-programmable gate arrays (FPGAs) and their associated high-level synthesis (HLS) compilers to solve heterogeneous agent models with incomplete markets and aggregate uncertainty (Krusell and Smith (1998)). We document that the acceleration delivered by one single FPGA is comparable to that provided by using 69 CPU cores in a conventional cluster. The time to solve 1200 versions of the model drops from 8 hours to 7 minutes, illustrating a great potential for structural estimation. We describe how to achieve multiple acceleration opportunities—pipeline, data-level parallelism, and data precision—with minimal modification of the C/C++ code written for a traditional sequential processor, which we then deploy on FPGAs easily available at Amazon Web Services. We quantify the speedup and cost of these accelerations. Our paper is the first step toward a new field, electrical engineering economics, focused on designing computational accelerators for economics to tackle challenging quantitative models. Replication code is available on Github.
Aimed at pandemic preparedness, we construct a framework for integrated epi-econ assessment that we believe would be useful for policymakers, especially at the early stages of a pandemic outbreak. We offer theory, calibration to micro-, macro-, and epi-data, and numerical methods for quantitative policy evaluation. The model has an explicit microeconomic, market-based structure. It highlights trade-offs, within period and over time, associated with activities that involve both valuable social interaction and harmful disease transmission. We compare market solutions with socially optimal allocations. Our calibration to Covid-19 implies that households shift their leisure and work activities away from social interactions. This is especially true for older individuals, who are more vulnerable to disease. The optimal allocation may or may not involve lockdown and changes the time allocations significantly across age groups. In this trade-off, people's social leisure time becomes an important factor, aside from deaths and GDP. We finally compare optimal responses to different viruses (SARS, seasonal flu) and argue that, going forward, economic analysis ought to be an integral element behind epidemiological policy.
This paper develops and estimates a dynamic model, which integrates value-added and school-choice models, to evaluate grade-by-grade and cumulative impacts of the Mexican Prospera conditional cash transfer (CCT) program on educational achievement. The empirical application advances the previous literature by estimating policy impacts on learning, accounting for dynamic selective school attendance, and incorporating both observed and unobserved heterogeneity. A dynamic framework is critical for estimating cumulative learning effects because lagged achievements are important determinants of current achievements. The model is estimated using rich nationwide Mexican administrative data on schooling progression and mathematics and Spanish test scores in grades 4–9 along with student and family survey data. The estimates show significant CCT impacts on learning and educational attainment, particularly for students from poorer households. Results show that telesecondary schools (distance learning) play a crucial role in facilitating school attendance and in fostering skill accumulation.
We evaluate the impact of a large-scale teacher coaching program in Peru, a context with high teacher turnover, on teachers' pedagogical skills and student learning. Previous studies find that small-scale coaching programs can improve teaching of reading and science in developing countries. However, scaling up can reduce programs' effectiveness, and teacher turnover can erode compliance and cause spillovers onto non-program schools. We develop a framework that defines different treatment effects when teacher turnover is present, and explains which effects can be estimated. We evaluate this teacher coaching program, exploiting random assignment of that program's expansion to 3797 rural schools in 2016. After two years, teachers assigned to the program increased their aggregate pedagogical skills by 0.20 standard deviations. The program also increased student learning; after 1 year, Grade 2 students' mathematics and reading scores increased by 0.106 and 0.075 standard deviations (of the distributions of those test scores), respectively. After three years, the cumulative effect increases slightly, to 0.114 and 0.100, respectively. One reason why these impacts are low is that some uncoached teachers moved into treated schools in years 2 and 3. Following our framework, we estimate that the impacts on students of having a “fully” coached teacher for all three years are 0.18 and 0.16 standard deviations for mathematics and reading comprehension, respectively.
We develop a nonparametric and ordinal approach for testing pure strategy Nash equilibrium play in games with monotone best responses, such as those with strategic complements/substitutes. The approach makes minimal assumptions on unobserved heterogeneity, requires no parametric assumptions on payoff functions, and no restriction on equilibrium selection from multiple equilibria. The approach can also be extended in order to make inferences and predictions. Both model-testing and inference can be implemented by a tractable computation procedure based on column generation. To illustrate how our approach works, we include an application to an IO entry game.
In this paper, we address the identification and estimation of insurance models where insurees have private information about their risk and risk aversion. The model includes random damages and allows for several claims, while insurees choose from a finite number of coverages. We show that the joint distribution of risk and risk aversion is nonparametrically identified despite bunching due to multidimensional types and a finite number of coverages. Our identification strategy exploits the observed number of claims as well as an exclusion restriction, and a full support assumption. Furthermore, our results apply to any form of competition. We propose a novel estimation procedure combining nonparametric estimators and GMM estimation that we illustrate in a Monte Carlo study.
We propose the double robust Lagrange multiplier (DRLM) statistic for testing hypotheses specified on the minimizer of the population continuous updating objective function. The (bounding) χ2 limiting distribution of the DRLM statistic is robust to both misspecification and weak identification, hence its name. The minimizer is the so-called pseudo-true value, which equals the true value of the structural parameter under correct specification. To emphasize its importance for applied work where misspecification and weak identification are common, we use the DRLM test to analyze: the risk premia in Adrian et al. (2014) and He et al. (2017); the structural parameters in a nonlinear asset pricing model with constant relative risk aversion.
Belief-updating biases hinder the correction of inaccurate beliefs and lead to suboptimal decisions. We complement Rabin and Schrag's (1999) portable extension of the Bayesian model by including conservatism in addition to confirmatory bias. Additionally, we show how to identify these two forms of biases from choices. In an experiment, we found that the subjects exhibited confirmatory bias by misreading 19% of the signals that contradicted their priors. They were also conservative and acted as if they missed 28% of the signals.
There is a fast growing literature that set-identifies structural vector autoregressions (SVARs) by imposing sign restrictions on the responses of a subset of the endogenous variables to a particular structural shock (sign-restricted SVARs). Most methods that have been used to construct pointwise coverage bands for impulse responses of sign-restricted SVARs are justified only from a Bayesian perspective. This paper demonstrates how to formulate the inference problem for sign-restricted SVARs within a moment-inequality framework. In particular, it develops methods of constructing confidence bands for impulse response functions of sign-restricted SVARs that are valid from a frequentist perspective. The paper also provides a comparison of frequentist and Bayesian coverage bands in the context of an empirical application—the former can be substantially wider than the latter.
I develop a computational method for solving and estimating heterogeneous agent macro models with aggregate shocks. The main challenge is that the aggregate state vector contains the distribution of agents, which is typically infinite-dimensional. I approximate the distribution with a flexible parametric family, reducing its dimensionality to a finite set of endogenous parameters, and solve for the dynamics of these endogenous parameters by perturbation. I implement the method in Dynare and show that it is fast, general, and easy to use. As an illustration, I use the method to perform a Bayesian estimation of a heterogeneous firm model with aggregate shocks to neutral and investment-specific productivity. I find that the behavior of investment at the firm level quantitatively shapes inference about the aggregate shock processes, suggesting an important role for micro data in estimating DSGE models.
Most empirical and theoretical econometric studies of dynamic discrete choice models assume the discount factor to be known. We show the knowledge of the discount factor is not necessary to identify parts, or even all, of the payoff function. We show the discount factor can be generically identified jointly with the payoff parameters. On the other hand, it is known the payoff function cannot be nonparametrically identified without any a priori restrictions. Our identification of the discount factor is robust to any normalization choice on the payoff parameters. In IO applications, normalizations are usually made on switching costs, such as entry costs and scrap values. We also show that switching costs can be nonparametrically identified, in closed-form, independently of the discount factor and other parts of the payoff function. Our identification strategies are constructive. They lead to easy to compute estimands that are global solutions. We illustrate with a Monte Carlo study and the dataset used in Ryan (2012).
This paper explores the estimation of a class of life-cycle discrete choice dynastic models. It provides a new representation of the value function for these class of models. It compare a multistage conditional choice probability (CCP) estimator based on the new value function representation with a modified version of the full solution maximum likelihood estimator (MLE) in a Monte Carlo study. The modified CCP estimator performs comparably to the MLE in a finite sample but greatly reduces the computational cost. Using the proposed estimator, we estimate a dynastic model and use the estimated model to conduct counterfactual simulations to investigate the role Nature versus Nurture in intergenerational mobility. We find that Nature accounts for 20 percent of the observed intergenerational immobility at the bottom of income distribution. That means that 80 percent of mobility at the bottom of the income distribution is explained by economic decision and economic/institutional constraints.
This paper introduces a computational framework to analyze global identification of linearized DSGE models. A formal identification condition is established that relies on the restrictions linking the observationally equivalent state space representations and on the inherent constraints imposed by the model solution on the deep parameters. This condition is next used to develop an algorithm that checks global identification by searching for observationally equivalent model parametrizations. The algorithm is efficient as the identification conditions it employs shrink considerably the space of candidate deep parameter points and the model does not need to be solved at each of these points. The working of the algorithm is demonstrated with two examples.
In this paper, we establish the consistency of the model selection criterion based on the quasi-marginal likelihood (QML) obtained from Laplace-type estimators. We consider cases in which parameters are strongly identified, weakly identified and partially identified. Our Monte Carlo results confirm our consistency results. Our proposed procedure is applied to select among New Keynesian macroeconomic models using US data.
This paper introduces a bivariate version of the generalized accelerated failure time model. It allows for simultaneity in the econometric sense that the two realized outcomes depend structurally on each other. Another feature of the proposed model is that it will generate equal durations with positive probability. Our approach takes a stylized economic model that leads to a univariate generalized accelerated failure time model as a starting point. In this model, agents decide when to transition from an initial state to a new one, and the covariates influence the difference in the utility flow in the two states. We introduce simultaneity by allowing the utility flow to depend on the status of the other person. The econometric model is then completed by assuming that the observed outcome is the Nash bargaining solution in that simple economic model. The advantage of this approach is that it includes independent realizations from the generalized accelerated failure time model as a special case, and deviations from this special case can be given an economic interpretation. We established identification under assumptions that are similar to those in the literature on nonparametric estimation of duration models. We illustrate the model by studying the joint retirement decisions in married couples using the Health and Retirement Study. In that example, it seems reasonable to allow for the possibility that each partner's optimal retirement time depends on the retirement time of the spouse. Moreover, the data suggest that the wife and the husband retire at the same time for a nonnegligible fraction of couples. The main empirical finding is that the simultaneity is economically important. In our preferred specification, the indirect utility associated with being retired increases by approximately when one's spouse retires.
This paper studies the identifying power of an instrumental variable in the nonparametric heterogeneous treatment effect framework when a binary treatment is mismeasured and endogenous. Using a binary instrumental variable, I characterize the sharp identified set for the local average treatment effect under the exclusion restriction of an instrument and the deterministic monotonicity of the true treatment in the instrument. Even allowing for general measurement error (e.g., the measurement error is endogenous), it is still possible to obtain finite bounds on the local average treatment effect. Notably, the Wald estimand is an upper bound on the local average treatment effect, but it is not the sharp bound in general. I also provide a confidence interval for the local average treatment effect with uniformly asymptotically valid size control. Furthermore, I demonstrate that the identification strategy of this paper offers a new use of repeated measurements for tightening the identified set.
In this paper, we suggest and analyze a new class of specification tests for random coefficient models. These tests allow to assess the validity of central structural features of the model, in particular linearity in coefficients, generalizations of this notion like a known nonlinear functional relationship, or degeneracy of the distribution of a random coefficient, that is, whether a coefficient is fixed or random, including whether an associated variable can be omitted altogether. Our tests are nonparametric in nature, and use sieve estimators of the characteristic function. We provide formal power analysis against global as well as against local alternatives. Moreover, we perform a Monte Carlo simulation study, and apply the tests to analyze the degree of nonlinearity in a heterogeneous random coefficients demand model. While we find some evidence against the popular QUAIDS specification with random coefficients, it is not strong enough to reject the specification at the conventional significance level.
Zipf's law is one of the best known empirical regularities in urban economics. There is extensive research on the subject, where each city is treated symmetrically in terms of the cost of transactions with other cities. Recent developments in network theory facilitate the examination of an asymmetric transport network. In a scale-free network, the chance of observing extremes in network connections becomes higher than the Gaussian distribution predicts and, therefore, it explains the emergence of large clusters. The city-size distribution shares the same pattern. This paper decodes how accessibility of a city to other cities on the transportation network can boost its local economy and explains the city-size distribution as a result of its underlying transportation network structure. We confirm our model predictions with US and Belgian data. Finally, we discuss the endogenous evolution of transport networks.
This paper develops a notion of consumer confidence within a dynamic competitive equilibrium framework. In any situation where multiple equilibrium prices on next-period spot markets are equally supported by the state of the economy, confidence is encoded in the subjective probabilities consumers attach to these multiple future outcomes. Our approach characterizes the set of all equilibrium-consistent subjective probabilities, and thereby endogenizes the extent of uncertainty faced by consumers. We use the structure of an economy with collateralized household debt and housing markets to develop and illustrate this concept. Our approach determines the specific range of debt levels at which this economy is vulnerable to crises of confidence, as well as the debt-level-specific extent of confidence-driven house price fluctuations.
Standard vector autoregression (VAR) identification methods find that government spending raises consumption and real wages; the Ramey–Shapiro narrative approach finds the opposite. I show that a key difference in the approaches is the timing. Both professional forecasts and the narrative approach shocks Granger-cause the VAR shocks, implying that these shocks are missing the timing of the news. Motivated by the importance of measuring anticipations, I use a narrative method to construct richer government spending news variables from 1939 to 2008. The implied government spending multipliers range from 0.6 to 1.2.
For U.S. annual data that include World War II, the estimated multiplier for temporary defense spending is 0.4–0.5 contemporaneously and 0.6–0.7 over 2 years. If the change in defense spending is “permanent” (gauged by Ramey's defense news variable), the multipliers are higher by 0.1–0.2. Since all estimated multipliers are significantly less than 1, greater spending crowds out other components of GDP, particularly investment. The lack of good instruments prevents estimation of reliable multipliers for nondefense purchases; multipliers in the literature of two or more likely reflect reverse causation from GDP to nondefense purchases. Increases in average marginal income tax rates (measured by a newly constructed time series) have significantly negative effects on GDP. When interpreted as a tax multiplier, the magnitude is around 1.1. The combination of the estimated spending and tax multipliers implies that the balanced-budget multiplier for defense spending is negative. We have some evidence that tax changes affect GDP mainly through substitution effects, rather than wealth effects.
We study the link between family violence and the emotional cues associated with wins and losses by professional football teams. We hypothesize that the risk of violence is affected by the “gain-loss” utility of game outcomes around a rationally expected reference point. Our empirical analysis uses police reports of violent incidents on Sundays during the professional football season. Controlling for the pregame point spread and the size of the local viewing audience, we find that upset losses (defeats when the home team was predicted to win by four or more points) lead to a 10% increase in the rate of at-home violence by men against their wives and girlfriends. In contrast, losses when the game was expected to be close have small and insignificant effects. Upset wins (victories when the home team was predicted to lose) also have little impact on violence, consistent with asymmetry in the gain-loss utility function. The rise in violence after an upset loss is concentrated in a narrow time window near the end of the game and is larger for more important games. We find no evidence for reference point updating based on the halftime score.
Using a randomized evaluation in Kenya, we measure health impacts of spring protection, an investment that improves source water quality. We also estimate households' valuation of spring protection and simulate the welfare impacts of alternatives to the current system of common property rights in water, which limits incentives for private investment. Spring infrastructure investments reduce fecal contamination by 66%, but household water quality improves less, due to recontamination. Child diarrhea falls by one quarter. Travel-cost based revealed preference estimates of households' valuations are much smaller than both stated preference valuations and health planners' valuations, and are consistent with models in which the demand for health is highly income elastic. We estimate that private property norms would generate little additional investment while imposing large static costs due to above-marginal-cost pricing, private property would function better at higher income levels or under water scarcity, and alternative institutions could yield Pareto improvements.
We study entry and bidding patterns in sealed bid and open auctions. Using data from the U.S. Forest Service timber auctions, we document a set of systematic effects: sealed bid auctions attract more small bidders, shift the allocation toward these bidders, and can also generate higher revenue. A private value auction model with endogenous participation can account for these qualitative effects of auction format. We estimate the model's parameters and show that it can explain the quantitative effects as well. We then use the model to assess bidder competitiveness, which has important consequences for auction design.
We investigate whether individual experiences of macroeconomic shocks affect financial risk taking, as often suggested for the generation that experienced the Great Depression. Using data from the Survey of Consumer Finances from 1960 to 2007, we find that individuals who have experienced low stock market returns throughout their lives so far report lower willingness to take financial risk, are less likely to participate in the stock market, invest a lower fraction of their liquid assets in stocks if they participate, and are more pessimistic about future stock returns. Those who have experienced low bond returns are less likely to own bonds. Results are estimated controlling for age, year effects, and household characteristics. More recent return experiences have stronger effects, particularly on younger people.
We develop a method for decomposing countries' observed export prices into quality versus quality-adjusted components using information contained in trade balances. Holding observed export prices constant, countries with trade surpluses are inferred to offer higher quality than countries running trade deficits. We account for variation in trade balances induced by horizontal and vertical differentiation, and we estimate the evolution of manufacturing quality for top exporters from 1989 to 2003. We find that observed unit value ratios can be a poor approximation for relative quality differences, countries' quality is converging more rapidly than their income, and countries appear to vary in terms of displaying “high-quality” versus “low-price” growth strategies.
Although disputes are typically treated as synonymous with concerns about enforcement in economic models of trade agreements, in reality most WTO disputes seem to concern the interpretation of vague provisions, or instances where the agreement is silent. And some have suggested that the WTO's Dispute Settlement Body (DSB) could usefully grant exceptions to rigid contractual obligations. These activist DSB roles could help “complete” an incomplete contract. But how activist should the DSB be? Should DSB rulings set precedent? We address these questions by characterizing the optimal choice of contract form and DSB mandate under various contracting conditions. JEL Codes: D02, D78, D86, F13, K12, K33.
Using geographic differences in the availability of payday loans, I estimate the real effects of credit access among low-income households. Payday loans are small, high interest rate loans that constitute the marginal source of credit for many high risk borrowers. I find no evidence that payday loans alleviate economic hardship. To the contrary, loan access leads to increased difficulty paying mortgage, rent and utilities bills. The empirical design isolates variation in loan access that is uninfluenced by lenders' location decisions and state regulatory decisions, two factors that might otherwise correlate with economic hardship measures. Further analysis of differences in loan availability—over time and across income groups—rules out a number of alternative explanations for the estimated effects. Counter to the view that improving credit access facilitates important expenditures, the results suggest that for some low-income households the debt service burden imposed by borrowing inhibits their ability to pay important bills.
Is there any need to clean up a banking system by closing some banks and forcing others to sell assets if the risk of a crisis becomes high? Impaired banks that may be forced to sell illiquid assets in the future have private incentives to hold, rather than sell, those assets Anticipating a potential fire sale, liquid buyers expect high returns, reducing their incentive to lend. Privately optimal trading decisions therefore lead to a worse fire sale and a larger drop in lending than is necessary. We discuss alternative ways of cleaning up the system and the associated costs and benefits.
We propose a tractable variant of the open economy neoclassical growth model that emphasizes political economy and contracting frictions. The political economy frictions involve a preference for immediate spending, while the contracting friction is a lack of commitment regarding foreign debt and expropriation. We show that the political economy frictions slow an economy's convergence to the steady state due to the endogenous evolution of capital taxation. The model rationalizes why openness has different implications for growth depending on the political environment, why institutions such as the treatment of capital income evolve over time, why governments in countries that grow rapidly accumulate net foreign assets rather than liabilities, and why foreign aid may not affect growth.
We use student assignment lotteries to estimate the effect of charter school attendance on student achievement in Boston. We also evaluate a related alternative, Boston's pilot schools. Pilot schools have some of the independence of charter schools but are in the Boston Public School district and are covered by some collective bargaining provisions. Lottery estimates show large and significant score gains for charter students in middle and high school. In contrast, lottery estimates for pilot school students are mostly small and insignificant, with some significant negative effects. Charter schools with binding assignment lotteries appear to generate larger gains than other charters.
We show that the effects of taxes on labor supply are shaped by interactions between adjustment costs for workers and hours constraints set by firms. We develop a model in which firms post job offers characterized by an hours requirement and workers pay search costs to find jobs. We present evidence supporting three predictions of this model by analyzing bunching at kinks using Danish tax records. First, larger kinks generate larger taxable income elasticities. Second, kinks that apply to a larger group of workers generate larger elasticities. Third, the distribution of job offers is tailored to match workers' aggregate tax preferences in equilibrium. Our results suggest that macro elasticities may be substantially larger than the estimates obtained using standard microeconometric methods.
We develop a theory of moral behavior, individual and collective, based on a general model of identity in which people care about “who they are” and infer their own values from past choices. The model sheds light on many empirical puzzles inconsistent with earlier approaches. Identity investments respond nonmonotonically to acts or threats, and taboos on mere thoughts arise to protect beliefs about the “priceless” value of certain social assets. High endowments trigger escalating commitment and a treadmill effect, while competing identities can cause dysfunctional capital destruction. Social interactions induce both social and antisocial norms of contribution, sustained by respectively shunning free riders or do-gooders.
This article examines how a decision maker who is only partially aware of his temptations learns about them over time. In facing temptations, individuals use their experience to forecast future self-control problems and choose the appropriate level of commitment. I demonstrate that rational learning can be perpetually partial and need not result in full sophistication. The main result of this article characterizes necessary and sufficient conditions for learning to converge to full sophistication. I apply this result to a consumption-savings environment in which a decision maker is tempted by present bias and establish a learning-theoretic justification for assuming sophistication in this setting.  “An individual who finds himself continuously repudiating his past plans may learn to distrust his future behavior, and may do something about it.” — Strotz (1955)
We document a statistical association between the severity of the persecution, displacement and mass murder of Jews by the Nazis during World War II and long-run economic and political outcomes within Russia. Cities that experienced the Holocaust most intensely have grown less, and both cities and administrative districts (oblasts) where the Holocaust had the largest impact have worse economic and political outcomes since the collapse of the Soviet Union. We provide evidence that the lasting impact of the Holocaust may be attributable to a permanent change it induced in the social structure across different regions of Russia.
This paper uses a regression discontinuity design to estimate the effect of home computers on child and adolescent outcomes by exploiting a voucher program in Romania. Our main results indicate that home computers have both positive and negative effects on the development of human capital. Children who won a voucher to purchase a computer had significantly lower school grades but show improved computer skills. There is also some evidence that winning a voucher increased cognitive skills, as measured by Raven's Progressive Matrices. We do not find much evidence for an effect on non-cognitive outcomes. Parental rules regarding homework and computer use attenuate the effects of computer ownership, suggesting that parental monitoring and supervision may be important mediating factors.
This article attempts to document and account for the long-run evolution of inheritance. We find that in a country like France the annual flow of inheritance was about 20–25% of national income between 1820 and 1910, down to less than 5% in 1950, and back up to about 15% by 2010. A simple theoretical model of wealth accumulation, growth, and inheritance can fully account for the observed U-shaped pattern and levels. Using this model, we find that under plausible assumptions the annual bequest flow might reach about 20–25% of national income by 2050. This corresponds to a capitalized bequest share in total wealth accumulation well above 100%. Our findings illustrate the fact that when the growth rate g is small, and when the rate of return to private wealth r is permanently and substantially larger than the growth rate (say, r = 4–5% versus g = 1–2%), which was the case in the nineteenth century and early twentieth century and is likely to happen again in the twenty-first century, then past wealth and inheritance are bound to play a key role for aggregate wealth accumulation and the structure of lifetime inequality. Contrary to a widespread view, modern economic growth did not kill inheritance.
The printing press was the great innovation in early modern information technology, but economists have found no macroeconomic evidence of its impact. This article exploits city-level data. Between 1500 and 1600, European cities where printing presses were established in the 1400s grew 60% faster than otherwise similar cities. Cities that adopted printing in the 1400s had no prior advantage, and the association between adoption and subsequent growth was not due to printers choosing auspicious locations. These findings are supported by regressions that exploit distance from Mainz, Germany—the birthplace of printing—as an instrument for adoption.
In public procurement, social welfare often depends on how quickly the good is delivered. A leading example is highway construction, where slow completion inflicts a negative externality on commuters. In response, highway departments award some contracts using scoring auctions, which give contractors explicit incentives for accelerated delivery. We characterize efficient design of these mechanisms. We then gather an extensive data set of highway projects awarded by the California Department of Transportation between 2003 and 2008. By comparing otherwise similar contracts, we show that where the scoring design was used, contracts were completed 30–40% faster and the welfare gains to commuters exceeded the increase in procurement costs. Using a structural model that endogenizes participation and bidding, we estimate that the counterfactual welfare gain from switching all contracts from the standard design to the efficient A+B design is nearly 22% of the total contract value ($1.14 billion).
This article develops a general equilibrium model of multiple-product, multiple-destination firms, which allows for heterogeneity in ability across firms and in product attributes within firms. Firms make endogenous entry and exit decisions and each surviving firm chooses optimally the range of products to supply to each market. We show that the resulting selection, across and within firms, provides a natural explanation for a number of features of trade across firms, products, and countries. Using both time-series changes in trade policy and cross-section variation in trade, we provide empirical evidence in support of the predictions of the model.
This paper develops a simple model of international trade with intermediation. We consider an economy with two islands and two types of agents, farmers and traders. Farmers can produce two goods, but to sell these goods in centralized (Walrasian) markets, they need to be matched with a trader, and this entails costly search. In the absence of search frictions, our model reduces to a standard Ricardian model of trade. We use this simple model to contrast the implications of changes in the integration of Walrasian markets, which allow traders from different islands to exchange their goods, and changes in the access to these Walrasian markets, which allow farmers to trade with traders from different islands. We find that intermediation always magnifies the gains from trade under the former type of integration, but leads to more nuanced welfare results under the latter, including the possibility of aggregate losses.
We estimate the impact of coups and top-secret coup authorizations on asset prices of partially nationalized multinational companies that stood to benefit from U.S.-backed coups. Stock returns of highly exposed firms reacted to coup authorizations classified as top-secret. The average cumulative abnormal return to a coup authorization was 9% over 4 days for a fully nationalized company, rising to more than 13% over 16 days. Precoup authorizations accounted for a larger share of stock price increases than the actual coup events themselves. There is no effect in the case of the widely publicized, poorly executed Cuban operations, consistent with abnormal returns to coup authorizations reflecting credible private information. We also introduce two new intuitive and easy to implement nonparametric tests that do not rely on asymptotic justifications.
We study ingroup bias—the preferential treatment of members of one's group—in naturally occurring data, where economically significant allocation decisions are made under a strong non-discriminatory norm. Data come from Israeli small claims courts during 2000–2004, where the assignment of a case to an Arab or Jewish judge is effectively random. We find robust evidence for judicial ingroup bias. Furthermore, this bias is strongly associated with terrorism intensity in the vicinity of the court in the year preceding the ruling. The results are consistent with theory and lab evidence according to which salience of group membership enhances social identification.
In Project STAR, 11,571 students in Tennessee and their teachers were randomly assigned to classrooms within their schools from kindergarten to third grade. This article evaluates the long-term impacts of STAR by linking the experimental data to administrative records. We first demonstrate that kindergarten test scores are highly correlated with outcomes such as earnings at age 27, college attendance, home ownership, and retirement savings. We then document four sets of experimental impacts. First, students in small classes are significantly more likely to attend college and exhibit improvements on other outcomes. Class size does not have a significant effect on earnings at age 27, but this effect is imprecisely estimated. Second, students who had a more experienced teacher in kindergarten have higher earnings. Third, an analysis of variance reveals significant classroom effects on earnings. Students who were randomly assigned to higher quality classrooms in grades K–3—as measured by classmates' end-of-class test scores—have higher earnings, college attendance rates, and other outcomes. Finally, the effects of class quality fade out on test scores in later grades, but gains in noncognitive measures persist.
This article assesses the role of conditionality in cash transfer programs using a unique experiment targeted at adolescent girls in Malawi. The program featured two distinct interventions: unconditional transfers (UCT arm) and transfers conditional on school attendance (CCT arm). Although there was a modest decline in the dropout rate in the UCT arm in comparison with the control group, it was only 43% as large as the impact in the CCT arm at the end of the 2-year program. The CCT arm also outperformed the UCT arm in tests of English reading comprehension. However, teenage pregnancy and marriage rates were substantially lower in the UCT than the CCT arm, entirely due to the impact of UCTs on these outcomes among girls who dropped out of school.
This article describes a series of school-based field experiments in over 200 urban schools across three cities designed to better understand the impact of financial incentives on student achievement. In Dallas, students were paid to read books. In New York, students were rewarded for performance on interim assessments. In Chicago, students were paid for classroom grades. I estimate that the impact of financial incentives on student achievement is statistically 0, in each city. Due to a lack of power, however, I cannot rule out the possibility of effect sizes that would have positive returns on investment. The only statistically significant effect is on English-speaking students in Dallas. The article concludes with a speculative discussion of what might account for intercity differences in estimated treatment effects.
We use individual and aggregate data to ask how the Internet is changing the ideological segregation of the American electorate. Focusing on online news consumption, offline news consumption, and face-to-face social interactions, we define ideological segregation in each domain using standard indices from the literature on racial segregation. We find that ideological segregation of online news consumption is low in absolute terms, higher than the segregation of most offline news consumption, and significantly lower than the segregation of face-to-face interactions with neighbors, co-workers, or family members. We find no evidence that the Internet is becoming more segregated over time.
While evidence suggests that people evaluate outcomes with respect to reference points, little is known about what determines them. We conduct two experiments that show that reference points are determined, at least in part, by expectations. In an exchange experiment, we endow subjects with an item and randomize the probability they will be allowed to trade. Subjects that are less likely to be able to trade are more likely to choose to keep their item. In a valuation experiment, we randomly assign subjects a high or low probability of obtaining an item and elicit their willingness-to-accept for it. The high probability treatment increases valuation of the item by 20–30%.
We study the price-setting problem of a firm in the presence of both observation and menu costs. The firm optimally decides when to “review” costly information on the adequacy of its price. Upon each review, the firm chooses whether to adjust its price, one or more times, before the next price review. Each price adjustment entails paying a menu cost. The firm's choices map into several statistics: the frequency of price reviews, the frequency of price adjustments, the size distribution of price changes, and the hazard rate of price adjustments. The simultaneous presence of observation and menu costs produces complementarities that change the predictions of simpler models featuring one cost only. For instance, infrequent observations may reflect a high menu cost rather than high observation costs: in spite of these complementarities, we show that the ratio of the two costs is identified by several statistics on price observations and adjustments.
This article examines learning-by-doing that is specific not just to individual firms but to pairs of firms working together in a contracting relationship. Using data from the oil and gas industry, I find that the productivity of an oil production company and its drilling contractor increases with their joint experience. This learning is relationship-specific: drilling rigs cannot fully appropriate the productivity gains acquired through experience with one production company to their work for another.This result is robust to ex ante match specificities. Moreover, producers' and rigs'contracting behavior is consistent with maximization of relationship-specific learning's productivity benefits.
I estimate the impact of attending a first-choice middle or high school on adult crime, using data from public school choice lotteries in Charlotte-Mecklenburg school district (CMS). Seven years after random assignment, lottery winners had been arrested for fewer serious crimes and had spent fewer days incarcerated. The gain in school quality as measured by peer and teacher inputs was equivalent to moving from one of the lowest-ranked schools to one at the district average. The reduction in crime comes largely from years after enrollment in the preferred school is complete. The impacts are concentrated among high-risk youth, who commit about 50% less crime across several different outcome measures and scalings of crime by severity. I find suggestive evidence that school quality explains more of the impact in high school, whereas peer effects are more important in middle school.
Every year, 90% of Americans give money to charities. Is such generosity necessarily welfare enhancing for the giver? We present a theoretical framework that distinguishes two types of motivation: individuals like to give, for example, due to altruism or warm glow, and individuals would rather not give but dislike saying no, for example, due to social pressure. We design a door-to-door fund-raiser in which some households are informed about the exact time of solicitation with a flyer on their doorknobs. Thus, they can seek or avoid the fund-raiser. We find that the flyer reduces the share of households opening the door by 9% to 25% and, if the flyer allows checking a Do Not Disturb box, reduces giving by 28% to 42%. The latter decrease is concentrated among donations smaller than $ 10. These findings suggest that social pressure is an important determinant of door-to-door giving. Combining data from this and a complementary field experiment, we structurally estimate the model. The estimated social pressure cost of saying no to a solicitor is $ 3.80 for an in-state charity and $ 1.40 for an out-of-state charity. Our welfare calculations suggest that our door-to-door fund-raising campaigns on average lower the utility of the potential donors.
In 2003, a new law required that 40% of Norwegian firms' directors be women—at the time only 9% of directors were women. We use the prequota cross-sectional variation in female board representation to instrument for exogenous changes to corporate boards following the quota. We find that the constraint imposed by the quota caused a significant drop in the stock price at the announcement of the law and a large decline in Tobin's Q over the following years, consistent with the idea that firms choose boards to maximize value. The quota led to younger and less experienced boards, increases in leverage and acquisitions, and deterioration in operating performance.
Consumers need information to compare alternatives for markets to function efficiently. Recognizing this, public policies often pair competition with easy access to comparative information. The implicit assumption is that comparison friction—the wedge between the availability of comparative information and consumers' use of it—is inconsequential because when information is readily available, consumers will access this information and make effective choices. We examine the extent of comparison friction in the market for Medicare Part D prescription drug plans in the United States. In a randomized field experiment, an intervention group received a letter with personalized cost information. That information was readily available for free and widely advertised. However, this additional step—providing the information rather than having consumers actively access it—had an impact. Plan switching was 28% in the intervention group, versus 17% in the comparison group, and the intervention caused an average decline in predicted consumer cost of about $100 a year among letter recipients—roughly 5% of the cost in the comparison group. Our results suggest that comparison friction can be large even when the cost of acquiring information is small and may be relevant for a wide range of public policies that incorporate consumer choice.
This paper explores the consequences of improving property rights to facilitate the use of fixed assets as collateral, popularly attributed to the influential policy advocate Hernando de Soto. We use an equilibrium model of a credit market with moral hazard to characterize the theoretical effects and also develop a quantitative analysis using data from Sri Lanka. We show that the effects are likely to be nonlinear and heterogeneous by wealth group. They also depend on the extent of competition between lenders. There can be significant increases in profits and reductions in interest rates when credit markets are competitive. However, since these are due to reductions in moral hazard, that is, increased effort, the welfare gains tend to be modest when cost of effort is taken into account. Allowing for an extensive margin where borrowers gain access to the credit market can make these effects larger depending on the underlying wealth distribution.
We develop a dynamic theory of resource wars and study the conditions under which such wars can be prevented. Our focus is on the interaction between the scarcity of resources and the incentives for war in the presence of limited commitment. We show that a key parameter determining the incentives for war is the elasticity of demand. Our first result identifies a novel externality that can precipitate war: price-taking firms fail to internalize the impact of their extraction on military action. In the case of inelastic resource demand, war incentives increase over time and war may become inevitable. Our second result shows that in some situations, regulation of prices and quantities by the resource-rich country can prevent war, and when this is the case, there will also be slower resource extraction than the Hotelling benchmark (with inelastic demand). Our third result is that because of limited commitment and its implications for armament incentives, regulation of prices and quantities might actually precipitate war even in some circumstances where wars would not have arisen under competitive markets.
We estimate the effect of new private-sector unionization on publicly traded firms' equity value in the United States over the 1961–1999 period using a newly assembled sample of National Labor Relations Board (NLRB) representation elections matched to stock market data. Event-study estimates show an average union effect on the equity value of the firm equivalent to $40,500 per unionized worker, an effect that takes 15 to 18 months after unionization to fully materialize, and one that could not be detected by a short-run event study. At the same time, point estimates from a regression discontinuity design—comparing the stock market impact of close union election wins to close losses—are considerably smaller and close to zero. We find a negative relationship between the cumulative abnormal returns and the vote share in support of the union, allowing us to reconcile these seemingly contradictory findings.
This article analyzes the heterogeneous reaction of exporters to real exchange rate changes using a very rich French firm-level data set with destination-specific export values and volumes on the period 1995–2005. We find that high–performance firms react to a depreciation by increasing significantly more their markup and by increasing less their export volume. This heterogeneity in pricing-to-market is robust to different measures of performance, samples, and econometric specifications. It is consistent with models where the demand elasticity decreases with firm performance. Since aggregate exports are concentrated on high-productivity firms, precisely those that absorb more exchange rate movements in their markups, heterogeneous pricing-to-market may partly explain the weak impact of exchange rate movements on aggregate exports.
This article analyzes the response of earnings to payroll tax rates using a cohort-based reform in Greece. Individuals who started working on or after 1993 face permanently a much higher earnings cap for payroll taxes, creating a large and permanent discontinuity in marginal payroll tax rates by date of entry in the labor force for upper earnings workers. Using full-population administrative social security data and a regression discontinuity design, we estimate the long-term labor supply effects and incidence of payroll tax rates on earnings. Standard theory predicts that in the long run, new regime workers should bear the entire burden of the payroll tax increase (relative to old regime workers). In contrast, we find that employers compensate new regime workers for the extra employer payroll taxes but not for the extra employee payroll taxes. We do not find any evidence of labor supply responses along the extensive or intensive margins around the discontinuity, suggesting low efficiency costs of payroll taxes. We discuss various possible explanations for those results.
We examine urbanization using new data that allow us to track the evolution of population in rural and urban areas in the United States from 1880 to 2000. We find a positive correlation between initial population density and subsequent population growth for intermediate densities, which increases the dispersion of the population density distribution over time. We use theory and empirical evidence to show this pattern of population growth is the result of differences in agriculture's initial share of employment across population densities, combined with structural transformation that shifts employment away from agriculture.
Many cities in North America formed at obstacles to water navigation, where continued transport required overland hauling or portage . Portage sites attracted commerce and supporting services, and places where the falls provided water power attracted manufacturing during early industrialization. We examine portage sites in the U.S. South, Mid-Atlantic, and Midwest, including those on the fall line , a geomorphological feature in the southeastern United States marking the final rapids on rivers before the ocean. Although their original advantages have long since become obsolete, we document the continuing importance of historical portage sites. We interpret these results as path dependence and contrast explanations based on sunk costs interacting with decreasing versus increasing returns to scale.
This article incorporates a time-varying severity of disasters into the hypothesis proposed by Rietz (1988) and Barro (2006) that risk premia result from the possibility of rare large disasters. During a disaster an asset's fundamental value falls by a time-varying amount. This in turn generates time-varying risk premia and, thus, volatile asset prices and return predictability. Using the recent technique of linearity-generating processes, the model is tractable and all prices are exactly solved in closed form. In this article's framework, the following empirical regularities can be understood quantitatively: (i) equity premium puzzle; (ii) risk-free rate puzzle; (iii) excess volatility puzzle; (iv) predictability of aggregate stock market returns with price-dividend ratios; (v) often greater explanatory power of characteristics than covariances for asset returns; (vi) upward-sloping nominal yield curve; (vii) predictability of future bond excess returns and long-term rates via the slope of the yield curve; (viii) corporate bond spread puzzle; (ix) high price of deep out-of-the-money puts; and (x) high put prices being followed by high stock returns. The calibration passes a variance bound test, as normal-times market volatility is consistent with the wide dispersion of disaster outcomes in the historical record. The model extends to a setting with many factors and to Epstein-Zin preferences.
One goal of extending the duration of unemployment insurance (UI) in recessions is to increase UI coverage in the face of longer unemployment spells. Although it is a common concern that such extensions may themselves raise nonemployment durations, it is not known how recessions would affect the magnitude of this moral hazard. To obtain causal estimates of the differential effects of UI in booms and recessions, this article exploits the fact that in Germany, potential UI benefit duration is a function of exact age which is itself invariant over the business cycle. We implement a regression discontinuity design separately for 20 years and correlate our estimates with measures of the business cycle. We find that the nonemployment effects of a month of additional UI benefits are, at best, somewhat declining in recessions. Yet the UI exhaustion rate, and therefore the additional coverage provided by UI extensions, rises substantially during a downturn. The ratio of these two effects represents the nonemployment response of workers weighted by the probability of being affected by UI extensions. Hence, our results imply that the effective moral hazard effect of UI extensions is significantly lower in recessions than in booms. Using a model of job search with liquidity constraints, we also find that in the absence of market-wide effects, the net social benefits from UI extensions can be expressed either directly in terms of the exhaustion rate and the nonemployment effect of UI durations, or as a declining function of our measure of effective moral hazard.
Do labor market opportunities for women affect marriage and fertility decisions? We provided three years of recruiting services to help young women in randomly selected rural Indian villages get jobs in the business process outsourcing industry. Because the industry was so new at the time of the study, there was almost no awareness of these jobs, allowing us in effect to exogenously increase women's labor force opportunities from the perspective of rural households. We find that young women in treatment villages were significantly less likely to get married or have children during this period, choosing instead to enter the labor market or obtain more schooling or postschool training. Women also report wanting to have fewer children and to work more steadily throughout their lifetime, consistent with increased aspirations for a career.
This article characterizes optimal policy when a government uses indirect control to exert its authority. We develop a dynamic principal-agent model in which a principal (a government) delegates the prevention of a disturbance–such as riots, protests, terrorism, crime, or tax evasion–to an agent who has an advantage in accomplishing this task. Our setting is a standard repeated moral hazard model with two additional features. First, the principal is allowed to exert direct control by intervening with an endogenously determined intensity of force which is costly to both players. Second, the principal suffers from limited commitment. Using recursive methods, we derive a fully analytical characterization of the intensity, likelihood, and duration of intervention. The first main insight from our model is that repeated and costly equilibrium interventions are a feature of optimal policy. This is because they are the most efficient credible means for the principal of providing incentives for the agent. The second main insight is a detailed analysis of a fundamental trade-off between the intensity and duration of intervention which is driven by the principal's inability to commit. Finally, we derive sharp predictions regarding the impact of various factors on the optimal intensity, likelihood, and duration of intervention. We discuss these results in the context of some historical episodes.
In 2008, a group of uninsured low-income adults in Oregon was selected by lottery to be given the chance to apply for Medicaid. This lottery provides an opportunity to gauge the effects of expanding access to public health insurance on the health care use, financial strain, and health of low-income adults using a randomized controlled design. In the year after random assignment, the treatment group selected by the lottery was about 25 percentage points more likely to have insurance than the control group that was not selected. We find that in this first year, the treatment group had substantively and statistically significantly higher health care utilization (including primary and preventive care as well as hospitalizations), lower out-of-pocket medical expenditures and medical debt (including fewer bills sent to collection), and better self-reported physical and mental health than the control group.
We evaluate the impact of the 2009 Cash for Clunkers program on short- and medium-run auto purchases. Our empirical strategy exploits variation across U.S. cities in ex ante exposure to the program as measured by the number of “clunkers” in the city as of summer 2008. We find that the program induced the purchase of an additional 370,000 cars in July and August 2009. However, we find strong evidence of reversal; high clunker counties bought fewer autos in the 10 months after the program expired, which offset most of the initial purchases. We find no evidence of an effect on employment, house prices, or household default rates in cities with higher exposure to the program.
It has been difficult to open up the black box of knowledge production. We use unique international data on the publications, citations, and affiliations of mathematicians to examine the impact of a large, post-1992 influx of Soviet mathematicians on the productivity of their U.S. counterparts. We find a negative productivity effect on those mathematicians whose research overlapped with that of the Soviets. We also document an increased mobility rate (to lower quality institutions and out of active publishing) and a reduced likelihood of producing “home run” papers. Although the total product of the preexisting American mathematicians shrank, the Soviet contribution to American mathematics filled in the gap. However, there is no evidence that the Soviets greatly increased the size of the “mathematics pie.” Finally, we find that there are significant international differences in the productivity effects of the collapse of the Soviet Union, and these international differences can be explained by both differences in the size of the émigré flow into the various countries and in how connected each country is to the global market for mathematical publications.
Growing concerns about low awareness and take-up rates for government support programs like college financial aid have spurred calls to simplify the application process and enhance visibility. We present results from a randomized field experiment in which low-income individuals receiving tax preparation help were also offered immediate assistance and a streamlined process to complete the Free Application for Federal Student Aid (FAFSA) for themselves or their children. Treated participants were also provided with aid estimates that were compared against tuition cost amounts for nearby colleges. The combined assistance and information treatment substantially increased FAFSA submissions and ultimately the likelihood of college attendance, persistence, and aid receipt. In particular, high school seniors whose parents received the treatment were 8 percentage points more likely to have completed two years of college, going from 28% to 36%, during the first three years following the experiment. Families who received aid information but no assistance with the FAFSA did not experience improved outcomes. The findings suggest many other opportunities for using personal assistance to increase participation in programs that require filling out forms to become eligible.
We present a theory of choice among lotteries in which the decision maker's attention is drawn to (precisely defined) salient payoffs. This leads the decision maker to a context-dependent representation of lotteries in which true probabilities are replaced by decision weights distorted in favor of salient payoffs. By specifying decision weights as a function of payoffs, our model provides a novel and unified account of many empirical phenomena, including frequent risk-seeking behavior, invariance failures such as the Allais paradox, and preference reversals. It also yields new predictions, including some that distinguish it from prospect theory, which we test.
We examine how the speed of learning and best-response processes depends on homophily: the tendency of agents to associate disproportionately with those having similar traits. When agents' beliefs or behaviors are developed by averaging what they see among their neighbors, then convergence to a consensus is slowed by the presence of homophily but is not influenced by network density (in contrast to other network processes that depend on shortest paths). In deriving these results, we propose a new, general measure of homophily based on the relative frequencies of interactions among different groups. An application to communication in a society before a vote shows how the time it takes for the vote to correctly aggregate information depends on the homophily and the initial information distribution.
How persistent are cultural traits? Using data on anti-Semitism in Germany, we find local continuity over 600 years. Jews were often blamed when the Black Death killed at least a third of Europe’s population during 1348–50. We use plague-era pogroms as an indicator for medieval anti-Semitism. They reliably predict violence against Jews in the 1920s, votes for the Nazi Party, deportations after 1933, attacks on synagogues, and letters to Der Stürmer . We also identify areas where persistence was lower: cities with high levels of trade or immigration. Finally, we show that our results are not driven by political extremism or by different attitudes toward violence.
In this article we present a simple new Keynesian–style model of debt-driven slumps—that is, situations in which an overhang of debt on the part of some agents, who are forced into rapid deleveraging, is depressing aggregate demand. Making some agents debt-constrained is a surprisingly powerful assumption. Fisherian debt deflation, the possibility of a liquidity trap, the paradox of thrift and toil, a Keynesian-type multiplier, and a rationale for expansionary fiscal policy all emerge naturally from the model. We argue that this approach sheds considerable light both on current economic difficulties and on historical episodes, including Japan’s lost decade (now in its 18th year) and the Great Depression itself.
We study the allocation and compensation of human capital in the U.S. finance industry over the past century. Across time, space, and subsectors, we find that financial deregulation is associated with skill intensity, job complexity, and high wages for finance employees. All three measures are high before 1940 and after 1985, but not in the interim period. Workers in finance earn the same education-adjusted wages as other workers until 1990, but by 2006 the premium is 50% on average. Top executive compensation in finance follows the same pattern and timing, where the premium reaches 250%. Similar results hold for other top earners in finance. Changes in earnings risk can explain about one half of the increase in the average premium; changes in the size distribution of firms can explain about one fifth of the premium for executives.
Tropical deforestation accounts for almost one-fifth of greenhouse gas emissions and threatens the world’s most diverse ecosystems. Much of this deforestation is driven by illegal logging. We use novel satellite data that tracks annual deforestation across eight years of Indonesian institutional change to examine how local officials’ incentives affect deforestation. Increases in the number of political jurisdictions lead to increased deforestation and lower timber prices, consistent with Cournot competition between jurisdictions. Illegal logging and local oil and gas rents are short-run substitutes, but this effect disappears over time with political turnover. The results illustrate how local officials’ incentives affect deforestation and show how standard economic theories can explain illegal behavior.
Despite their importance, there is limited evidence on how institutions can be strengthened. Evaluating the effects of specific reforms is complicated by the lack of exogenous variation in institutions, the difficulty of measuring institutional performance, and the temptation to “cherry pick” estimates from among the large number of indicators required to capture this multifaceted subject. We evaluate one attempt to make local institutions more democratic and egalitarian by imposing participation requirements for marginalized groups (including women) and test for learning-by-doing effects. We exploit the random assignment of a governance program in Sierra Leone, develop innovative real-world outcome measures, and use a preanalysis plan (PAP) to bind our hands against data mining. The intervention studied is a “community-driven development” program, which has become a popular strategy for foreign aid donors. We find positive short-run effects on local public goods and economic outcomes, but no evidence for sustained impacts on collective action, decision making, or the involvement of marginalized groups, suggesting that the intervention did not durably reshape local institutions. We discuss the practical trade-offs faced in implementing a PAP and show how in its absence we could have generated two divergent, equally erroneous interpretations of program impacts on institutions.
We analyze a rational-expectations model of price formation in an intermediate-good market under uncertainty. There is a continuum of firms, each consisting of a party who can reduce production cost and a party who can discover information about demand. Both parties can make specific investments at private cost, and there is a machine that either party can control. As in incomplete-contracting models, different governance structures (i.e., different allocations of control of the machine) create different incentives for the parties’ investments. As in rational-expectations models, some parties may invest in acquiring information, which is then incorporated into the market-clearing price of the intermediate good by these parties’ production decisions. The informativeness of the price mechanism affects the returns to specific investments and hence the optimal governance structure for individual firms; meanwhile, the governance choices by individual firms affect the informativeness of the price mechanism. In equilibrium, the informativeness of the price mechanism can induce ex ante homogeneous firms to choose heterogeneous governance structures.
We consider the robustness of extensive form mechanisms to deviations from common knowledge about the state of nature, which we refer to as information perturbations . First, we show that even under arbitrarily small information perturbations the Moore-Repullo mechanism does not yield (even approximately) truthful revelation and that in addition the mechanism has sequential equilibria with undesirable outcomes. More generally, we prove that any extensive form mechanism is fragile in the sense that if a non-Maskin monotonic social objective can be implemented with this mechanism, then there are arbitrarily small information perturbations under which an undesirable sequential equilibrium also exists. Finally, we argue that outside options can help improve efficiency in asymmetric information environments, and that these options can be thought of as reflecting ownership of an asset.
In this article, we analyze the 1920s Ku Klux Klan, those who joined it, and its social and political impact by combining a wide range of archival data sources with data from the 1920 and 1930 U.S censuses. We find that individuals who joined the Klan in some cities were more educated and more likely to hold professional jobs than the typical American. Surprisingly, we find little evidence that the Klan had an effect on black or foreign-born residential mobility or vote totals. Rather than a terrorist organization, the 1920s Klan is best described as social organization with a very successful multilevel marketing structure fueled by an army of highly incentivized sales agents selling hatred, religious intolerance, and fraternity in a time and place where there was tremendous demand.
What is the best way to reward innovation? While prizes avoid deadweight loss, intellectual property (IP) selects high social surplus projects. Optimal innovation policy thus trades off the ex ante screening benefit and the ex post distortion. It solves a multidimensional screening problem in the private information held by the innovator: research cost, quality, and market size of the innovation. The appropriate degree of market power is never full monopoly pricing and is determined by measurable market characteristics, the inequality and elasticity of innovation supply, making the analysis open to empirical calibration. The framework has applications beyond IP policy to the optimal pricing of platforms or the optimal procurement of public infrastructure.
A long-standing question is whether differences in management practices across firms can explain differences in productivity, especially in developing countries where these spreads appear particularly large. To investigate this, we ran a management field experiment on large Indian textile firms. We provided free consulting on management practices to randomly chosen treatment plants and compared their performance to a set of control plants. We find that adopting these management practices raised productivity by 17% in the first year through improved quality and efficiency and reduced inventory, and within three years led to the opening of more production plants. Why had the firms not adopted these profitable practices previously? Our results suggest that informational barriers were the primary factor explaining this lack of adoption. Also, because reallocation across firms appeared to be constrained by limits on managerial time, competition had not forced badly managed firms to exit.
We investigate the determinants of regional development using a newly constructed database of 1,569 subnational regions from 110 countries covering 74% of the world’s surface and 97% of its GDP. We combine the cross-regional analysis of geographic, institutional, cultural, and human capital determinants of regional development with an examination of productivity in several thousand establishments located in these regions. To organize the discussion, we present a new model of regional development that introduces into a standard migration framework elements of both the Lucas (1978) model of the allocation of talent between entrepreneurship and work, and the Lucas (1988) model of human capital externalities. The evidence points to the paramount importance of human capital in accounting for regional differences in development, but also suggests from model estimation and calibration that entrepreneurial inputs and possibly human capital externalities help understand the data.
Unlike economies as a whole, manufacturing industries exhibit strong unconditional convergence in labor productivity. The article documents this at various levels of disaggregation for a large sample covering more than 100 countries over recent decades. The result is highly robust to changes in the sample and specification. The coefficient of unconditional convergence is estimated quite precisely and is large, at between 2–3% in most specifications and 2.9% a year in the baseline specification covering 118 countries. The article also finds substantial sigma convergence at the two-digit level for a smaller sample of countries. Despite strong convergence within manufacturing, aggregate convergence fails due to the small share of manufacturing employment in low-income countries and the slow pace of industrialization. Because of data coverage, these findings should be as viewed as applying to the organized, formal parts of manufacturing.
Extending Barro (1999) and Luttmer and Mariotti (2003), we introduce a new model of time preferences: the instantaneous-gratification model. This model applies tractably to a much wider range of settings than existing models. It applies to both complete- and incomplete-market settings and it works with generic utility functions. It works in settings with linear policy rules and in settings in which equilibrium cannot be supported by linear rules. The instantaneous-gratification model also generates a unique equilibrium, even in infinite-horizon applications, thereby resolving the multiplicity problem hitherto associated with dynamically inconsistent models. Finally, it simultaneously features a single welfare criterion and a behavioral tendency towards overconsumption.
This article evaluates the long-term effects of class size in primary school. We use rich data from Sweden and exploit variation in class size created by a maximum class size rule. Smaller classes in the last three years of primary school (age 10 to 13) are beneficial for cognitive and noncognitive ability at age 13, and improve achievement at age 16. Most important, we find that smaller classes have positive effects on completed education, wages, and earnings at age 27 to 42. The estimated wage effect is large enough to pass a cost-benefit test.
We study explicit gender discrimination in a population of ads on a Chinese Internet job board. Gender-targeted job ads are common, favor women as often as men, and are much less common in jobs requiring higher levels of skill. Employers’ relative preferences for female versus male workers, on the other hand, are more strongly related to the preferred age, height, and beauty of the worker than to job skill levels. Almost two thirds of the variation in advertised gender preferences occurs within firms, and one third occurs within firm*occupation cells. Overall, these patterns are not well explained by a firm-level animus model, by a glass-ceiling model, or by models in which broad occupational categories are consistently gendered across firms. Instead, the patterns suggest a model in which firms have idiosyncratic preferences for particular job-gender matches, which are overridden in skilled positions by factors such as thinner labor markets or a greater incentive to search broadly for the most qualified candidate.
Over the past 30 years, many states have abolished parole boards, which traditionally have had the discretion to release inmates before the expiration of their full sentence, in favor of fixed-sentence regimes in which the original sentence is binding. However, if prison time lowers recidivism risk and if parole boards can accurately estimate inmates’ recidivism risk, then relative to a fixed-sentence regime, parole can provide allocative-efficiency benefits (costly prison space is allocated to the highest-risk offenders) and incentive benefits (prisoners know they must reduce their recidivism risk to gain an early release, so invest in their own rehabilitation). Exploiting quasi-experiments from the state of Georgia, I show that prison time reduces recidivism risk and that parole boards set prison time in an allocatively efficient manner. Prisoners respond to these incentives; after a reform that eliminated parole for certain offenders, they accumulated a greater number of disciplinary infractions, completed fewer prison rehabilitative programs, and recidivated at higher rates than inmates unaffected by the reform. I estimate that eliminating parole for all prisoners would increase the prison population by 10% while also increasing the crime rate through deleterious effects on recidivism.
We present a method of ranking U.S. undergraduate programs based on students’ revealed preferences. When a student chooses a college among those that have admitted him, that college “wins” his “tournament.” Our method efficiently integrates the information from thousands of such tournaments. We implement the method using data from a national sample of high-achieving students. We demonstrate that this ranking method has strong theoretical properties, eliminating incentives for colleges to adopt strategic, inefficient admissions policies to improve their rankings. We also show empirically that our ranking is (1) not vulnerable to strategic manipulation; (2) similar regardless of whether we control for variables, such as net cost, that vary among a college’s admits; (3) similar regardless of whether we account for students selecting where to apply, including Early Decision. We exemplify multiple rankings for different types of students who have preferences that vary systematically.
The study examines the historical origins of existing cross-cultural differences in beliefs and values regarding the appropriate role of women in society. We test the hypothesis that traditional agricultural practices influenced the historical gender division of labor and the evolution of gender norms. We find that, consistent with existing hypotheses, the descendants of societies that traditionally practiced plough agriculture today have less equal gender norms, measured using reported gender-role attitudes and female participation in the workplace, politics, and entrepreneurial activities. Our results hold looking across countries, across districts within countries, and across ethnicities within districts. To test for the importance of cultural persistence, we examine the children of immigrants living in Europe and the United States. We find that even among these individuals, all born and raised in the same country, those with a heritage of traditional plough use exhibit less equal beliefs about gender roles today.
This article reports the results from a randomized experiment designed to evaluate the direct and indirect (displacement) impacts of job placement assistance on the labor market outcomes of young, educated job seekers in France. We use a two-step design. In the first step, the proportions of job seekers to be assigned to treatment (0%, 25%, 50%, 75%, or 100%) were randomly drawn for each of the 235 labor markets (e.g., cities) participating in the experiment. Then, in each labor market, eligible job seekers were randomly assigned to the treatment, following this proportion. After eight months, eligible, unemployed youths who were assigned to the program were significantly more likely to have found a stable job than those who were not. But these gains are transitory, and they appear to have come partly at the expense of eligible workers who did not benefit from the program, particularly in labor markets where they compete mainly with other educated workers, and in weak labor markets. Overall, the program seems to have had very little net benefits.
This paper is the first to study vacancies, hires, and vacancy yields at the establishment level in the Job Openings and Labor Turnover Survey, a large sample of US employers. To interpret the data, we develop a simple model that identifies the flow of new vacancies and the job-filling rate for vacant positions. The fill rate moves counter to aggregate employment but rises steeply with employer growth rates in the cross section. It falls with employer size, rises with worker turnover rates, and varies by a factor of four across major industry groups. We also develop evidence that the employer-level hiring technology exhibits mild increasing returns in vacancies, and that employers rely heavily on other instruments, in addition to vacancies, as they vary hires. Building from our evidence and a generalized matching function, we construct a new index of recruiting intensity (per vacancy). Recruiting intensity partly explains the recent breakdown in the standard matching function, delivers a better-fitting empirical Beveridge curve, and accounts for a large share of fluctuations in aggregate hires. Our evidence and analysis provide useful inputs for assessing, developing, and calibrating theoretical models of search, matching, and hiring in the labor market.
We develop a framework for nonparametrically identifying optimization frictions and structural elasticities using notches—discontinuities in the choice sets of agents—introduced by tax and transfer policies. Notches create excess bunching on the low-tax side and missing mass on the high-tax side of a cutoff, and they are often associated with a region of strictly dominated choice that would have zero mass in a frictionless world. By combining excess bunching (observed response attenuated by frictions) with missing mass in the dominated region (frictions), it is possible to uncover the structural elasticity that would govern behavior in the absence of frictions and arguably capture long-run behavior. We apply our framework to tax notches in Pakistan using rich administrative data. While observed bunching is large and sharp, optimization frictions are also very large as the majority of taxpayers in dominated ranges are unresponsive to tax incentives. The combination of large observed bunching and large frictions implies that the frictionless behavioral response to notches is extremely large, but the underlying structural elasticity driving this response is nevertheless modest. This highlights the inefficiency of notches: by creating extremely strong price distortions, they induce large behavioral responses even when structural elasticities are small.
When voters fear that politicians may be influenced or corrupted by the rich elite, signals of integrity are valuable. As a consequence, an honest politician seeking reelection chooses “populist” policies—that is, policies to the left of the median voter—as a way of signaling that he is not beholden to the interests of the right. Politicians that are influenced by right-wing special interests respond by choosing moderate or even left-of-center policies. This populist bias of policy is greater when the value of remaining in office is higher for the politician; when there is greater polarization between the policy preferences of the median voter and right-wing special interests; when politicians are perceived as more likely to be corrupt; when there is an intermediate amount of noise in the information that voters receive; when politicians are more forward-looking; and when there is greater uncertainty about the type of the incumbent. We also show that soft term limits may exacerbate, rather than reduce, the populist bias of policies.
Proximity to plants makes it easier for headquarters to monitor and acquire information about plants. In this article, I estimate the effects of headquarters’ proximity to plants on plant-level investment and productivity. Using the introduction of new airline routes as a source of exogenous variation in proximity, I find that new airline routes that reduce the travel time between headquarters and plants lead to an increase in plant-level investment of 8% to 9% and an increase in plants’ total factor productivity of 1.3% to 1.4%. The results are robust when I control for local and firm-level shocks that could potentially drive the introduction of new airline routes, when I consider only new airline routes that are the outcome of a merger between two airlines or the opening of a new hub, and when I consider only indirect flights where either the last leg of the flight (involving the plant’s home airport) or the first leg of the flight (involving headquarters’ home airport) remains unchanged. Moreover, the results are stronger in the earlier years of the sample period and for firms whose headquarters is more time-constrained. In addition, they also hold at the extensive margin, that is, when I consider plant openings and closures.
We study the role of establishment-specific wage premiums in generating recent increases in West German wage inequality. Models with additive fixed effects for workers and establishments are fit into four subintervals spanning the period from 1985 to 2009. We show that these models provide a good approximation to the wage structure and can explain nearly all of the dramatic rise in West German wage inequality. Our estimates suggest that the increasing dispersion of West German wages has arisen from a combination of rising heterogeneity between workers, rising dispersion in the wage premiums at different establishments, and increasing assortativeness in the assignment of workers to plants. In contrast, the idiosyncratic job-match component of wage variation is small and stable over time. Decomposing changes in mean wages between different education groups, occupations, and industries, we find that increasing plant-level heterogeneity and rising assortativeness in the assignment of workers to establishments explain a large share of the rise in inequality along all three dimensions.
Using data from South Asia, this article examines how arranged marriage cultivates rivalry among sisters. During marriage search, parents with multiple daughters reduce the reservation quality for an older daughter’s groom, rushing her marriage to allow sufficient time to marry off her younger sisters. Relative to younger brothers, younger sisters increase a girl’s marriage risk; relative to younger singleton sisters, younger twin sisters have the same effect. These effects intensify in marriage markets with lower sex ratios or greater parental involvement in marriage arrangements. In contrast, older sisters delay a girl’s marriage. Because girls leave school when they marry and face limited earning opportunities when they reach adulthood, the number of sisters has well-being consequences over the life cycle. Younger sisters cause earlier school-leaving, lower literacy, a match to a husband with less education and a less skilled occupation, and (marginally) lower adult economic status. Data from a broader set of countries indicate that these cross-sister pressures on marriage age are common throughout the developing world, although the schooling costs vary by setting.
This article studies the role of employer behavior in generating “negative duration dependence”—the adverse effect of a longer unemployment spell—by sending fictitious résumés to real job postings in 100 U.S. cities. Our results indicate that the likelihood of receiving a callback for an interview significantly decreases with the length of a worker’s unemployment spell, with the majority of this decline occurring during the first eight months. We explore how this effect varies with local labor market conditions and find that duration dependence is stronger when the local labor market is tighter. This result is consistent with the prediction of a broad class of screening models in which employers use the unemployment spell length as a signal of unobserved productivity and recognize that this signal is less informative in weak labor markets.
We study a recent recruitment drive for public sector positions in Mexico. Different salaries were announced randomly across recruitment sites, and job offers were subsequently randomized. Screening relied on exams designed to measure applicants’ intellectual ability, personality, and motivation. This allows the first experimental estimates of (1) the role of financial incentives in attracting a larger and more qualified pool of applicants, (2) the elasticity of the labor supply facing the employer, and (3) the role of job attributes (distance, attractiveness of the municipal environment) in helping fill vacancies, as well as the role of wages in helping fill positions in less attractive municipalities. A theoretical model of job applications and acceptance guides the empirical inquiry. We find that higher wages attract more able applicants as measured by their IQ, personality, and proclivity toward public sector work—that is, we find no evidence of adverse selection effects on motivation; higher wage offers also increased acceptance rates, implying a labor supply elasticity of around 2 and some degree of monopsony power. Distance and worse municipal characteristics strongly decrease acceptance rates, but higher wages help bridge the recruitment gap in worse municipalities.
We use the fall of the Berlin Wall in 1989 to show that personal relationships which individuals maintain for noneconomic reasons can be an important determinant of regional economic growth. We show that West German households who had social ties to East Germany in 1989 experienced a persistent rise in their personal incomes after the fall of the Berlin Wall. Moreover, the presence of these households significantly affects economic performance at the regional level: it increases the returns to entrepreneurial activity, the share of households who become entrepreneurs, and the likelihood that firms based within a given West German region invest in East Germany. As a result, West German regions that (for idiosyncratic reasons) have a high concentration of households with social ties to the East exhibit substantially higher growth in income per capita in the early 1990s. A one standard deviation rise in the share of households with social ties to East Germany in 1989 is associated with a 4.7 percentage point rise in income per capita over six years. We interpret our findings as evidence of a causal link between social ties and regional economic development.
To ensure that individual actors take certain actions, community enforcement may be required. This can present a rules-versus-discretion dilemma: it can become impossible to employ discretion based on information that is not widely held, because the wider community is unable to verify how the information was used. Instead, actions may need to conform to simple and widely verifiable rules. We study when discretion in the form of exceptions to a simple rule can be implemented, if the information is shared by the action taker and a second party, who is able to verify for the larger group that an exception is warranted. In particular, we compare protocols where the second party excuses the action taker from taking the action ex ante with protocols where the second party instead forgives a rule-breaking actor ex post.
This article shows that official statistics substantially underestimate the net foreign asset positions of rich countries because they fail to capture most of the assets held by households in offshore tax havens. Drawing on a unique Swiss data set and exploiting systematic anomalies in countries’ portfolio investment positions, I find that around 8% of the global financial wealth of households is held in tax havens, three-quarters of which goes unrecorded. On the basis of plausible assumptions, accounting for unrecorded assets turns the eurozone, officially the world’s second largest net debtor, into a net creditor. It also reduces the U.S. net debt significantly. The results shed new light on global imbalances and challenge the widespread view that after a decade of poor-to-rich capital flows, external assets are now in poor countries and debts in rich countries. I provide concrete proposals to improve international statistics.
We formulate a test of the fungibility of money based on parallel shifts in the prices of different quality grades of a commodity. We embed the test in a discrete-choice model of product quality choice and estimate the model using panel microdata on gasoline purchases. We find that when gasoline prices rise, consumers substitute to lower octane gasoline, to an extent that cannot be explained by income effects. Across a wide range of specifications, we consistently reject the null hypothesis that households treat “gas money” as fungible with other income. We compare the empirical fit of three psychological models of decision making. A simple model of category budgeting fits the data well, with models of loss aversion and salience both capturing important features of the time series.
In many regulated markets, private, third-party auditors are chosen and paid by the firms that they audit, potentially creating a conflict of interest. This article reports on a two-year field experiment in the Indian state of Gujarat that sought to curb such a conflict by altering the market structure for environmental audits of industrial plants to incentivize accurate reporting. There are three main results. First, the status quo system was largely corrupted, with auditors systematically reporting plant emissions just below the standard, although true emissions were typically higher. Second, the treatment caused auditors to report more truthfully and very significantly lowered the fraction of plants that were falsely reported as compliant with pollution standards. Third, treatment plants, in turn, reduced their pollution emissions. The results suggest reformed incentives for third-party auditors can improve their reporting and make regulation more effective.
Using a unique 10-year panel that includes more than 13,300 expected stock market return probability distributions, we find that executives are severely miscalibrated, producing distributions that are too narrow: realized market returns are within the executives’ 80% confidence intervals only 36% of the time. We show that executives reduce the lower bound of the forecast confidence interval during times of high market uncertainty; however, ex post miscalibration is worst during periods of high uncertainty. We also find that executives who are miscalibrated about the stock market show similar miscalibration regarding their own firms’ prospects. Finally, firms with miscalibrated executives seem to follow more aggressive corporate policies: investing more and using more debt financing.
Accommodating couples has been a long-standing issue in the design of centralized labor market clearinghouses for doctors and psychologists, because couples view pairs of jobs as complements. A stable matching may not exist when couples are present. This article’s main result is that a stable matching exists when there are relatively few couples and preference lists are sufficiently short relative to market size. We also discuss incentives in markets with couples. We relate these theoretical results to the job market for psychologists, in which stable matchings exist for all years of the data, despite the presence of couples.
Can protests cause political change, or are they merely symptoms of underlying shifts in policy preferences? We address this question by studying the Tea Party movement in the United States, which rose to prominence through coordinated rallies across the country on Tax Day, April 15, 2009. We exploit variation in rainfall on the day of these rallies as an exogenous source of variation in attendance. We show that good weather at this initial, coordinating event had significant consequences for the subsequent local strength of the movement, increased public support for Tea Party positions, and led to more Republican votes in the 2010 midterm elections. Policy making was also affected, as incumbents responded to large protests in their district by voting more conservatively in Congress. Our estimates suggest significant multiplier effects: an additional protester increased the number of Republican votes by a factor well above 1. Together our results show that protests can build political movements that ultimately affect policy making and that they do so by influencing political views rather than solely through the revelation of existing political preferences.
We investigate the consumption consequences of the 2006–9 housing collapse using the highly unequal geographic distribution of wealth losses across the United States. We estimate a large elasticity of consumption with respect to housing net worth of 0.6 to 0.8, which soundly rejects the hypothesis of full consumption risk-sharing. The average marginal propensity to consume (MPC) out of housing wealth is 5–7 cents with substantial heterogeneity across ZIP codes. ZIP codes with poorer and more levered households have a significantly higher MPC out of housing wealth. In line with the MPC result, ZIP codes experiencing larger wealth losses, particularly those with poorer and more levered households, experience a larger reduction in credit limits, refinancing likelihood, and credit scores. Our findings highlight the role of debt and the geographic distribution of wealth shocks in explaining the large and unequal decline in consumption from 2006 to 2009.
Using population and product consumption data from the Demographic and Health Surveys, I construct comparable measures of inequality and migration for 65 countries, including some of the poorest countries in the world. I find that the urban-rural gap accounts for 40% of mean country inequality and much of its cross-country variation. One out of every four or five individuals raised in rural areas moves to urban areas as a young adult, where they earn much higher incomes than nonmigrant rural permanent residents. Equally, one out of every four or five individuals raised in urban areas moves to rural areas as a young adult, where they earn much lower incomes than their nonmigrant urban cousins. These flows and relative incomes are suggestive of a world where the population sorts itself geographically on the basis of its human capital and skill. I show that a simple model of this sort explains the urban-rural gap in living standards.
This article uses linked worker-firm data in the United States to estimate the transitional costs associated with reallocating workers from newly regulated industries to other sectors of the economy in the context of new environmental regulations. The focus on workers rather than industries as the unit of analysis allows me to examine previously unobserved economic outcomes such as nonemployment and long-run earnings losses from job transitions, both of which are critical to understanding the reallocative costs associated with these policies. Using plant-level panel variation induced by the 1990 Clean Air Act Amendments (CAAA), I find that the reallocative costs of environmental policy are significant. Workers in newly regulated plants experienced, in aggregate, more than $5.4 billion in forgone earnings for the years after the change in policy. Most of these costs are driven by nonemployment and lower earnings in future employment, highlighting the importance of longitudinal data for characterizing the costs and consequences of labor market adjustment. Relative to the estimated benefits of the 1990 CAAA, these one-time transitional costs are small.
Recently, Gene Grossman and Esteban Rossi-Hansberg (GRH; “External Economies and International Trade: Redux,” Quarterly Journal of Economics 125 [2010], 829–858) proposed a novel way to think about the implications of international trade in the presence of national external economies at the industry level. Instead of perfect competition and two industries, GRH assume Bertrand competition and a continuum of industries. GRH conclude that the equilibrium is unique if transport costs are low, that there is no trade for high transport costs, and that there is no equilibrium in pure strategies when transport costs are intermediate. In this note we reexamine the equilibrium analysis under different transport costs for a single industry (partial equilibrium) version of GRH’s model. We confirm many of GRH’s results, but also find that there are circumstances under which there are multiple equilibria, including equilibria in which trade patterns run counter to “natural” comparative advantage, and also find that there is a profitable deviation to the mixed-strategy equilibrium postulated by GRH for intermediate trading costs. We propose an alternative set of strategies for this case and establish that they constitute an equilibrium.
This article investigates the effect of bank lending frictions on employment outcomes. I construct a new data set that combines information on banking relationships and employment at 2,000 nonfinancial firms during the 2008–9 crisis. The article first verifies empirically the importance of banking relationships, which imply a cost to borrowers who switch lenders. I then use the dispersion in lender health following the Lehman crisis as a source of exogenous variation in the availability of credit to borrowers. I find that credit matters. Firms that had precrisis relationships with less healthy lenders had a lower likelihood of obtaining a loan following the Lehman bankruptcy, paid a higher interest rate if they did borrow, and reduced employment by more compared to precrisis clients of healthier lenders. Consistent with frictions deriving from asymmetric information, the effects vary by firm type. Lender health has an economically and statistically significant effect on employment at small and medium firms, but the data cannot reject the hypothesis of no effect at the largest or most transparent firms. Abstracting from general equilibrium effects, I find that the withdrawal of credit accounts for between one-third and one-half of the employment decline at small and medium firms in the sample in the year following the Lehman bankruptcy.
We present evidence from laboratory experiments showing that individuals are “last-place averse.” Participants choose gambles with the potential to move them out of last place that they reject when randomly placed in other parts of the distribution. In modified dictator games, participants randomly placed in second-to-last place are the most likely to give money to the person one rank above them instead of the person one rank below. Last-place aversion suggests that low-income individuals might oppose redistribution because it could differentially help the group just beneath them. Using survey data, we show that individuals making just above the minimum wage are the most likely to oppose its increase. Similarly, in the General Social Survey, those above poverty but below median income support redistribution significantly less than their background characteristics would predict.
We investigate the role of national institutions on subnational African development in a novel framework that accounts for both local geography and cultural-genetic traits. We exploit the fact that the political boundaries on the eve of African independence partitioned more than 200 ethnic groups across adjacent countries subjecting similar cultures, residing in homogeneous geographic areas, to different formal institutions. Using both a matching type and a spatial regression discontinuity approach we show that differences in countrywide institutional structures across the national border do not explain within-ethnicity differences in economic performance, as captured by satellite images of light density. The average noneffect of national institutions on ethnic development masks considerable heterogeneity partially driven by the diminishing role of national institutions in areas further from the capital cities.
Is monetary policy less effective at increasing real output during periods of high volatility than during normal times? In this article, I argue that greater volatility leads to an increase in aggregate price flexibility so that nominal stimulus mostly generates inflation rather than output growth. To do this, I construct price-setting models with “volatility shocks” and show these models match new facts in CPI micro data that standard price-setting models miss. I then show that these models imply that output responds less to nominal stimulus during times of high volatility. Furthermore, because volatility is countercyclical, this implies that nominal stimulus has smaller real effects during downturns. For example, the estimated output response to additional nominal stimulus in September 1995, a time of low volatility, is 55% larger than the response in October 2001, a time of high volatility.
In a pure-currency economy, money is the only durable object and people have private histories. In such economies, taxation is not feasible and in some of them trade is enhanced through the use of money. For economies of that kind in which a nondegenerate distribution of money, part of the state of the economy, affects trades and real outcomes, and in which trades affect the state at the next date, the conjecture is that there are transfer schemes financed by money creation that improve ex ante representative-agent welfare relative to what can be achieved holding the stock of money fixed.
We study the long-run effects of one of the most ambitious regional development programs in U.S. history: the Tennessee Valley Authority (TVA). Using as controls authorities that were proposed but never approved by Congress, we find that the TVA led to large gains in agricultural employment that were eventually reversed when the program’s subsidies ended. Gains in manufacturing employment, by contrast, continued to intensify well after federal transfers had lapsed—a pattern consistent with the presence of agglomeration economies in manufacturing. Because manufacturing paid higher wages than agriculture, this shift raised aggregate income in the TVA region for an extended period of time. Economists have long cautioned that the local gains created by place-based policies may be offset by losses elsewhere. We develop a structured approach to assessing the TVA’s aggregate consequences that is applicable to other place-based policies. In our model, the TVA affects the national economy both directly through infrastructure improvements and indirectly through agglomeration economies. The model’s estimates suggest that the TVA’s direct investments yielded a significant increase in national manufacturing productivity, with benefits exceeding the program’s costs. However, the program’s indirect effects appear to have been limited: agglomeration gains in the TVA region were offset by losses in the rest of the country. Spillovers in manufacturing appear to be the rare example of a localized market failure that cancels out in the aggregate.
This article analyzes the effects of income taxation on the international migration and earnings of top earners using a Danish preferential foreigner tax scheme and population-wide Danish administrative data. This scheme, introduced in 1991, allows new immigrants with high earnings to be taxed at a preferential flat rate for a duration of three years. We obtain two main results. First, the scheme has doubled the number of highly paid foreigners in Denmark relative to slightly less paid—and therefore ineligible—foreigners. This translates into a very large elasticity of migration with respect to 1 minus the average tax rate on foreigners, between 1.5 and 2. Second, we find compelling evidence of a negative effect of the scheme-induced reduction in the average tax rate on pretax earnings of foreign migrants at the individual level. This finding can be rationalized by a matching frictions model with wage bargaining where there is a gap between pay and marginal productivity.
The Voting Rights Act of 1965, called one of the most effective pieces of civil rights legislation in U.S. history, generated dramatic increases in black voter registration across the South. We ask whether the increase in black voting rights was accompanied by an increase in blacks’ share of public spending. We exploit a key provision of the act—removal of literacy tests at registration—for identification. Employing a triple-difference framework over a 20-year period, we find that counties with higher black population shares in former literacy test states saw greater increases in both voter turnout and state transfers than comparison counties in non–literacy test states, a finding that is consistent with models of distributive politics.
We study the end of race-based busing in Charlotte-Mecklenburg schools (CMS). In 2001, school boundaries in CMS were redrawn dramatically, and half of students received a new assignment. Using addresses measured prior to the policy change, we compare students in the same neighborhood that lived on opposite sides of a newly drawn boundary. We find that both white and minority students score lower on high school exams when they are assigned to schools with more minority students. We also find decreases in high school graduation and four-year college attendance for whites and large increases in crime for minority males. We conclude that the end of race-based busing widened racial inequality, despite efforts by CMS to mitigate the effect of segregation through compensatory resource allocation.
The unit values of internationally traded goods are heavily influenced by quality. We model this in an extended monopolistic competition framework where, in addition to choosing price, firms simultaneously choose quality subject to nonhomothetic demand. We estimate quality and quality-adjusted price indexes for 185 countries over 1984–2011. Our estimates are less sensitive to assumptions about the extensive margin of firms than are purely “demand-side” estimates. We find that quality-adjusted prices vary much less across countries than do unit values and, surprisingly, the quality-adjusted terms of trade are negatively related to countries’ level of income.
The investment decisions of small-scale farmers in developing countries are conditioned by their financial environment. Binding credit market constraints and incomplete insurance can limit investment in activities with high expected profits. We conducted several experiments in northern Ghana in which farmers were randomly assigned to receive cash grants, grants of or opportunities to purchase rainfall index insurance, or a combination of the two. Demand for index insurance is strong, and insurance leads to significantly larger agricultural investment and riskier production choices in agriculture. The binding constraint to farmer investment is uninsured risk: when provided with insurance against the primary catastrophic risk they face, farmers are able to find resources to increase expenditure on their farms. Demand for insurance in subsequent years is strongly increasing with the farmer’s own receipt of insurance payouts, with the receipt of payouts by others in the farmer’s social network and with recent poor rain in the village. Both investment patterns and the demand for index insurance are consistent with the presence of important basis risk associated with the index insurance, imperfect trust that promised payouts will be delivered and overweighting recent events.
We study the effect of public health insurance on labor supply by exploiting a large public health insurance disenrollment. In 2005, approximately 170,000 Tennessee residents abruptly lost Medicaid coverage. Using both across- and within-state variation in exposure to the disenrollment, we estimate large increases in labor supply, primarily along the extensive margin. The increased employment is concentrated among individuals working at least 20 hours a week and receiving private, employer-provided health insurance. We explore the dynamic effects of the disenrollment and find an immediate increase in job search behavior and a steady rise in both employment and health insurance coverage following the disenrollment. Our results are consistent with a significant degree of “employment lock”—workers who are employed primarily to secure private health insurance coverage.
We study a government program in Uganda designed to help the poor and unemployed become self-employed artisans, increase incomes, and thus promote social stability. Young adults in Uganda’s conflict-affected north were invited to form groups and submit grant proposals for vocational training and business start-up. Funding was randomly assigned among screened and eligible groups. Treatment groups received unsupervised grants of $382 per member. Grant recipients invest some in skills training but most in tools and materials. After four years, half practice a skilled trade. Relative to the control group, the program increases business assets by 57%, work hours by 17%, and earnings by 38%. Many also formalize their enterprises and hire labor. We see no effect, however, on social cohesion, antisocial behavior, or protest. Effects are similar by gender but are qualitatively different for women because they begin poorer (meaning the impact is larger relative to their starting point) and because women’s work and earnings stagnate without the program but take off with it. The patterns we observe are consistent with credit constraints.
We present new data documenting medieval Europe’s Commercial Revolution using information on the establishment of markets in Germany. We use these data to test whether medieval universities played a causal role in expanding economic activity, examining the foundation of Germany’s first universities after 1386 following the papal schism. We find that the trend rate of market establishment breaks upward in 1386 and this break is greatest where the distance to a university shrank most. There is no differential pre-1386 trend associated with the reduction in distance to a university, and there is no break in trend in 1386 where university proximity did not change. These results are robust to estimating a variety of specifications that address concerns about the endogeneity of university location. Universities provided training in newly rediscovered Roman and canon law; students with legal training served in positions that reduced the uncertainty of trade in the Middle Ages. We argue that training in the law, and the consequent development of legal and administrative institutions, was an important channel linking universities and greater economic activity in medieval Germany.
We find that regulators can implement identical rules inconsistently due to differences in their institutional design and incentives, and this behavior may adversely impact the effectiveness with which regulation is implemented. We study supervisory decisions of U.S. banking regulators and exploit a legally determined rotation policy that assigns federal and state supervisors to the same bank at exogenously set time intervals. Comparing federal and state regulator supervisory ratings within the same bank, we find that federal regulators are systematically tougher, downgrading supervisory ratings almost twice as frequently as do state supervisors. State regulators counteract these downgrades to some degree by upgrading more frequently. Under federal regulators, banks report worse asset quality, higher regulatory capital ratios, and lower return on assets. Leniency of state regulators relative to their federal counterparts is related to costly outcomes, such as higher failure rates and lower repayment rates of government assistance funds. The discrepancy in regulator behavior is related to different weights given by regulators to local economic conditions and, to some extent, differences in regulatory resources. We find no support for regulator self-interest, which includes “revolving doors” as a reason for leniency of state regulators.
According to national accounts data, value added per worker is much higher in the nonagricultural sector than in agriculture in the typical country, particularly in developing countries. Taken at face value, this “agricultural productivity gap” suggests that labor is greatly misallocated across sectors. In this article, we draw on new micro evidence to ask to what extent the gap is still present when better measures of sector labor inputs and value added are taken into consideration. We find that even after considering sector differences in hours worked and human capital per worker, as well as alternative measures of sector output constructed from household survey data, a puzzlingly large gap remains.
We complement the literature on distributive politics by taking a systematic look at regional favoritism in a large and diverse sample of countries and by employing a broad measure that captures the aggregate distributive effect of many different policies. In particular, we use satellite data on nighttime light intensity and information about the birthplaces of the countries’ political leaders. In our panel of 38,427 subnational regions from 126 countries with yearly observations from 1992 to 2009, we find that subnational regions have more intense nighttime light when being the birth region of the current political leader. We argue that this finding provides evidence for regional favoritism. We explore the dynamics and the geographical extent of regional favoritism and show that regional favoritism is most prevalent in countries with weak political institutions and poorly educated citizens. Furthermore, foreign aid inflows and oil rents tend to fuel regional favoritism in weakly institutionalized countries, but not elsewhere.
In the United States, the average 40-year-old plant employs more than seven times as many workers as the typical plant 5 years or younger. In contrast, surviving plants in India and Mexico exhibit much slower growth, roughly doubling in size over the same age range. The divergence in plant dynamics suggests lower investments by Indian and Mexican plants in process efficiency, quality, and in accessing markets at home and abroad. In simple general equilibrium models, we find that the difference in life cycle dynamics could lower aggregate manufacturing productivity on the order of 25 percent in India and Mexico relative to the United States.
We develop a general equilibrium framework to determine the spatial distribution of economic activity on any surface with (nearly) any geography. Combining the gravity structure of trade with labor mobility, we provide conditions for the existence, uniqueness, and stability of a spatial economic equilibrium and derive a simple set of equations that govern the relationship between economic activity and the geography of the surface. We then use the framework to estimate the topography of trade costs, productivities and amenities in the United States. We find that geographic location accounts for at least twenty percent of the spatial variation in U.S. income. Finally, we calculate that the construction of the interstate highway system increased welfare by 1.1 to 1.4 percent, which is substantially larger than its cost.
Using 41 million observations on savings for the population of Denmark, we show that the effects of retirement savings policies on wealth accumulation depend on whether they change savings rates by active or passive choice. Subsidies for retirement accounts, which rely on individuals to take an action to raise savings, primarily induce individuals to shift assets from taxable accounts to retirement accounts. We estimate that each $1 of government expenditure on subsidies increases total saving by only 1 cent. In contrast, policies that raise retirement contributions if individuals take no action—such as automatic employer contributions to retirement accounts—increase wealth accumulation substantially. We estimate that approximately 15% of individuals are “active savers” who respond to tax subsidies primarily by shifting assets across accounts; 85% of individuals are “passive savers” who are unresponsive to subsidies but are instead heavily influenced by automatic contributions made on their behalf. Active savers tend to be wealthier and more financially sophisticated. We conclude that automatic contributions are more effective at increasing savings rates than subsidies for three reasons: (i) subsidies induce relatively few individuals to respond, (ii) they generate substantial crowd-out conditional on response, and (iii) they do not increase the savings of passive individuals, who are least prepared for retirement.
We introduce the model of asset management developed in Gennaioli, Shleifer, and Vishny (“Money Doctors,” Journal of Finance , forthcoming 2015) into a Solow-style neoclassical growth model with diminishing returns to capital. Savers rely on trusted intermediaries to manage their wealth (claims on capital stock), who can charge fees above costs to trusting investors. In this model, the ratio of financial income to GDP increases with the ratio of aggregate wealth to GDP. Both rise along the convergence path to steady state growth. We examine several further implications of the model for management fees, unit costs of finance, and the consequences of shocks to trust and to the capital stock.
How do aggregate wealth-to-income ratios evolve in the long run and why? We address this question using 1970–2010 national balance sheets recently compiled in the top eight developed economies. For the United States, United Kingdom, Germany, and France, we are able to extend our analysis as far back as 1700. We find in every country a gradual rise` of wealth-income ratios in recent decades, from about 200–300% in 1970 to 400–600% in 2010. In effect, today’s ratios appear to be returning to the high values observed in Europe in the eighteenth and nineteenth centuries (600–700%). This can be explained by a long-run asset price recovery (itself driven by changes in capital policies since the world wars) and by the slowdown of productivity and population growth, in line with the β=sg Harrod-Domar-Solow formula. That is, for a given net saving rate s = 10%, the long-run wealth-income ratio β is about 300% if g = 3% and 600% if g = 1.5%. Our results have implications for capital taxation and regulation and shed new light on the changing nature of wealth, the shape of the production function, and the rise of capital shares.
We consider a model of technological learning under which people “learn through noticing”: they choose which input dimensions to attend to and subsequently learn about from available data. Using this model, we show how people with a great deal of experience may persistently be off the production frontier because they fail to notice important features of the data they possess. We also develop predictions on when these learning failures are likely to occur, as well as on the types of interventions that can help people learn. We test the model’s predictions in a field experiment with seaweed farmers. The survey data reveal that these farmers do not attend to pod size, a particular input dimension. Experimental trials suggest that farmers are particularly far from optimizing this dimension. Furthermore, consistent with the model, we find that simply having access to the experimental data does not induce learning. Instead, behavioral changes occur only after the farmers are presented with summaries that highlight previously unattended-to relationships in the data.
This study examines the impact on student achievement of implementing a bundle of best practices from high-performing charter schools into low-performing, traditional public schools in Houston, Texas, using a school-level randomized field experiment and quasi-experimental comparisons. The five practices in the bundle are increased instructional time, more effective teachers and administrators, high-dosage tutoring, data-driven instruction, and a culture of high expectations. The findings show that injecting best practices from charter schools into traditional Houston public schools significantly increases student math achievement in treated elementary and secondary schools—by 0.15 to 0.18 standard deviations a year—and has little effect on reading achievement. Similar bundles of practices are found to significantly raise math achievement in analyses for public schools in a field experiment in Denver and program in Chicago.
Gender differences in competitiveness have been hypothesized as a potential explanation for gender differences in education and labor market outcomes. We examine the predictive power of a standard laboratory experimental measure of competitiveness for the later important choice of academic track of secondary school students in the Netherlands. Although boys and girls display similar levels of academic ability, boys choose substantially more prestigious academic tracks, where more prestigious tracks are more math- and science-intensive. Our experimental measure shows that boys are also substantially more competitive than girls. We find that competitiveness is strongly positively correlated with choosing more prestigious academic tracks even conditional on academic ability. Most important, we find that the gender difference in competitiveness accounts for a substantial portion (about 20%) of the gender difference in track choice.
This article provides an axiomatic characterization of quasi-hyperbolic discounting and a more general class of semi-hyperbolic preferences. We impose consistency restrictions directly on the intertemporal trade-offs by relying on what we call “annuity compensations.” Our axiomatization leads naturally to an experimental design that disentangles discounting from the elasticity of intertemporal substitution. In a pilot experiment we use the partial identification approach to estimate bounds for the distributions of discount factors in the subject pool. Consistent with previous studies, we find evidence for both present and future bias.
International trade literature tends to focus heavily on the production side of general equilibrium, leaving us with a number of empirical puzzles. There is, for example, considerably less world trade than predicted by Heckscher-Ohlin-Vanek (HOV) models. Trade among rich countries is higher and trade between rich and poor countries lower than suggested by HOV and other supply-driven theories, and trade-to-GDP ratios are higher in rich countries. Our approach focuses on the relationship between characteristics of goods and services in production and characteristics of preferences. In particular, we find a strong and significant positive correlation of more than 45% between a good’s skilled-labor intensity and its income elasticity, even when accounting for trade costs and cross-country price differences. Exploring the implications of this correlation for empirical trade puzzles, we find that it can reduce HOV’s overprediction of the variance of the net factor content of trade relative to that in the data by about 60%. Since rich countries are relatively skilled-labor abundant, they are relatively specialized in consuming the same goods and services that they are specialized in producing, and so trade more with one another than with poor countries. We also find a positive sector-level correlation between income elasticity and a sector’s tradability, which helps explain the higher trade-to-GDP ratios in high-income relative to low-income countries.
We use administrative records on the incomes of more than 40 million children and their parents to describe three features of intergenerational mobility in the United States. First, we characterize the joint distribution of parent and child income at the national level. The conditional expectation of child income given parent income is linear in percentile ranks. On average, a 10 percentile increase in parent income is associated with a 3.4 percentile increase in a child’s income. Second, intergenerational mobility varies substantially across areas within the United States. For example, the probability that a child reaches the top quintile of the national income distribution starting from a family in the bottom quintile is 4.4% in Charlotte but 12.9% in San Jose. Third, we explore the factors correlated with upward mobility. High mobility areas have (i) less residential segregation, (ii) less income inequality, (iii) better primary schools, (iv) greater social capital, and (v) greater family stability. Although our descriptive analysis does not identify the causal mechanisms that determine upward mobility, the publicly available statistics on intergenerational mobility developed here can facilitate research on such mechanisms.
We use a lab experiment to explore the factors that predict an individual’s decision to contribute her idea to a group. We find that contribution decisions depend on the interaction of gender and the gender stereotype associated with the decision-making domain: conditional on measured ability, individuals are less willing to contribute ideas in areas that are stereotypically outside of their gender’s domain. Importantly, these decisions are largely driven by self-assessments, rather than fear of discrimination. Individuals are less confident in gender-incongruent areas and are thus less willing to contribute their ideas. Because even very knowledgeable group members undercontribute in gender-incongruent categories, group performance suffers and, ex post, groups have difficulty recognizing who their most talented members are. Our results show that even in an environment where other group members show no bias, women in male-typed areas and men in female-typed areas may be less influential. An intervention that provides feedback about a woman’s (man’s) strength in a male-typed (female-typed) area does not significantly increase the probability that she contributes her ideas to the group. A back-of-the-envelope calculation reveals that a “lean in”–style policy that increases contribution by women would significantly improve group performance in male-typed domains.
This article defines and analyzes a “sparse max” operator, which is a less than fully attentive and rational version of the traditional max operator. The agent builds (as economists do) a simplified model of the world which is sparse, considering only the variables of first-order importance. His stylized model and his resulting choices both derive from constrained optimization. Still, the sparse max remains tractable to compute. Moreover, the induced outcomes reflect basic psychological forces governing limited attention. The sparse max yields a behavioral version of basic chapters of the microeconomics textbook: consumer demand and competitive equilibrium. I obtain a behavioral version of Marshallian and Hicksian demand, Arrow-Debreu competitive equilibrium, the Slutsky matrix, the Edgeworth box, Roy’s identity, and so on. The Slutsky matrix is no longer symmetric: nonsalient prices are associated with anomalously small demand elasticities. Because the consumer exhibits nominal illusion, in the Edgeworth box, the offer curve is a two-dimensional surface rather than a one-dimensional curve. As a result, different aggregate price levels correspond to materially distinct competitive equilibria, in a similar spirit to a Phillips curve. The Arrow-Debreu welfare theorems typically do not hold. This framework provides a way to assess which parts of basic microeconomics are robust, and which are not, to the assumption of perfect maximization.
We investigate the existence and importance of family welfare cultures, where the receipt of a welfare program by one generation causes increased participation in the next generation. Our context is Norway’s disability insurance (DI) system. To overcome the challenge of correlated unobservables across generations, we take advantage of random assignment of judges to DI applicants whose cases are initially denied. Some appeal judges are systematically more lenient, which leads to random variation in the probability a parent will be allowed DI. Using this exogenous variation, we find strong evidence for a causal link across generations: when a parent is allowed DI at the appeal stage, their adult child’s participation over the next five years increases by 6 percentage points. This effect grows over time, rising to 12 percentage points after 10 years. Although these findings are specific to our setting, they highlight that welfare reforms can have long-lasting effects on program participation, since any original effect on the current generation could be reinforced by changing the participation behavior of their children as well. The detailed nature of our data allows us to compare the intergenerational transmission with spillover effects in other networks and to explore mechanisms.
We analyze the effect of exposure to international trade on earnings and employment of U.S. workers from 1992 through 2007 by exploiting industry shocks to import competition stemming from China’s spectacular rise as a manufacturing exporter paired with longitudinal data on individual earnings by employer spanning close to two decades. Individuals who in 1991 worked in manufacturing industries that experienced high subsequent import growth garner lower cumulative earnings, face elevated risk of obtaining public disability benefits, and spend less time working for their initial employers, less time in their initial two-digit manufacturing industries, and more time working elsewhere in manufacturing and outside of manufacturing. Earnings losses are larger for individuals with low initial wages, low initial tenure, and low attachment to the labor force. Low-wage workers churn primarily among manufacturing sectors, where they are repeatedly exposed to subsequent trade shocks. High-wage workers are better able to move across employers with minimal earnings losses and are more likely to move out of manufacturing conditional on separation. These findings reveal that import shocks impose substantial labor adjustment costs that are highly unevenly distributed across workers according to their skill levels and conditions of employment in the pre-shock period.
A body of literature suggests that ethnic heterogeneity limits economic growth. This article provides microeconometric evidence on the direct effect of ethnic divisions on productivity. In team production at a plant in Kenya, an upstream worker supplies and distributes flowers to two downstream workers, who assemble them into bunches. The plant uses an essentially random rotation process to assign workers to positions, leading to three types of teams: (i) ethnically homogeneous teams, and teams in which (ii) one or (iii) both downstream workers belong to a tribe in rivalry with the upstream worker’s tribe. I find strong evidence that upstream workers undersupply non-coethnic downstream workers (vertical discrimination) and shift flowers from non-coethnic to coethnic downstream workers (horizontal discrimination), at the cost of lower own pay and total output. A period of ethnic conflict following Kenya’s 2007 election led to a sharp increase in discrimination. In response, the plant began paying the two downstream workers for their combined output (team pay). This led to a modest output reduction in (i) and (iii) teams—as predicted by standard incentive models—but an increase in output in (ii) teams, and overall. Workers’ behavior before conflict, during conflict, and under team pay is predicted by a model of taste-based discrimination. My findings suggest that interethnic rivalries lower allocative efficiency in the private sector, that the economic costs of ethnic diversity vary with the political environment, and that in high-cost environments firms are forced to adopt “second best” policies to limit discrimination distortions.
This article investigates the role of mass media in times of conflict and state-sponsored mass violence against civilians. We use a unique village-level data set from the Rwandan genocide to estimate the impact of a popular radio station that encouraged violence against the Tutsi minority population. The results show that the broadcasts had a significant effect on participation in killings by both militia groups and ordinary civilians. An estimated 51,000 perpetrators, or approximately 10% of the overall violence, can be attributed to the station. The broadcasts increased militia violence not only directly by influencing behavior in villages with radio reception but also indirectly by increasing participation in neighboring villages. In fact, spillovers are estimated to have caused more militia violence than the direct effects. Thus, the article provides evidence that mass media can affect participation in violence directly due to exposure and indirectly due to social interactions.
We estimate how households trade off immediate costs and uncertain future benefits that occur in the very long run, 100 or more years away. We exploit a unique feature of housing markets in the United Kingdom and Singapore, where residential property ownership takes the form of either leaseholds or freeholds. Leaseholds are temporary, prepaid, and tradable ownership contracts with maturities between 99 and 999 years, while freeholds are perpetual ownership contracts. The price difference between leaseholds and freeholds reflects the present value of perpetual rental income starting at leasehold expiration, and is thus informative about very long-run discount rates. We estimate the price discounts for varying leasehold maturities compared to freeholds and extremely long-run leaseholds via hedonic regressions using proprietary data sets of the universe of transactions in each country. Households discount very long-run cash flows at low rates, assigning high present value to cash flows hundreds of years in the future. For example, 100-year leaseholds are valued at more than 10% less than otherwise identical freeholds, implying discount rates below 2.6% for 100-year claims.
We study the link between investment boom and bust cycles and returns on capital in the dry bulk shipping industry. We show that high current ship earnings are associated with high used ship prices and heightened industry investment in new ships, but forecast low future returns. We propose and estimate a behavioral model of industry cycles that can account for the evidence. In our model, firms overextrapolate exogenous demand shocks and partially neglect the endogenous investment response of their competitors. As a result, firms overpay for ships and overinvest in booms and are disappointed by the subsequent low returns. Formal estimation of the model suggests that modest expectational errors can result in dramatic excess volatility in prices and investment.
We analyze the effectiveness of consumer financial regulation by considering the 2009 Credit Card Accountability Responsibility and Disclosure (CARD) Act. We use a panel data set covering 160 million credit card accounts and a difference-in-differences research design that compares changes in outcomes over time for consumer credit cards, which were subject to the regulations, to changes for small business credit cards, which the law did not cover. We estimate that regulatory limits on credit card fees reduced overall borrowing costs by an annualized 1.6% of average daily balances, with a decline of more than 5.3% for consumers with FICO scores below 660. We find no evidence of an offsetting increase in interest charges or a reduction in the volume of credit. Taken together, we estimate that the CARD Act saved consumers $11.9 billion a year. We also analyze a nudge that disclosed the interest savings from paying off balances in 36 months rather than making minimum payments. We detect a small increase in the share of accounts making the 36-month payment value but no evidence of a change in overall payments.
A rising share of employees now regularly engage in working from home (WFH), but there are concerns this can lead to “shirking from home.” We report the results of a WFH experiment at Ctrip, a 16,000-employee, NASDAQ-listed Chinese travel agency. Call center employees who volunteered to WFH were randomly assigned either to work from home or in the office for nine months. Home working led to a 13% performance increase, of which 9% was from working more minutes per shift (fewer breaks and sick days) and 4% from more calls per minute (attributed to a quieter and more convenient working environment). Home workers also reported improved work satisfaction, and their attrition rate halved, but their promotion rate conditional on performance fell. Due to the success of the experiment, Ctrip rolled out the option to WFH to the whole firm and allowed the experimental employees to reselect between the home and office. Interestingly, over half of them switched, which led to the gains from WFH almost doubling to 22%. This highlights the benefits of learning and selection effects when adopting modern management practices like WFH.
This article studies socially responsible behavior in markets. We develop a laboratory product market in which low-cost production creates a negative externality for third parties, but where alternative production with higher costs mitigates the externality. Our first study, conducted in Switzerland, reveals a persistent preference among many consumers and firms for avoiding negative social impact in the market, reflected both in the composition of product types and in a price premium for socially responsible products. Socially responsible behavior is generally robust to varying market characteristics, such as increased seller competition and limited consumer information, and it responds to prices in a manner consistent with a model in which positive social impact is a utility-enhancing feature of a consumer product. In a second study, we investigate whether market social responsibility varies across societies by comparing market behavior in Switzerland and China. While subjects in Switzerland and China do not differ in their degree of social concern in nonmarket contexts, we find that low-cost production that creates negative externalities is significantly more prevalent in markets in China. Across both studies, consumers in markets exhibit less social concern than subjects in a comparable individual choice context.
We establish a theoretical and empirical framework to assess the role of resource endowments and their geographic location in interstate conflict. The main predictions of the theory are that conflict is more likely when at least one country has natural resources, when the resources in the resource-endowed country are closer to the border, and, in the case where both countries have natural resources, when the resources are located asymmetrically vis-à-vis the border. We test these predictions on a novel data set featuring oilfield distances from bilateral borders. The empirical analysis shows that the presence and location of oil are significant and quantitatively important predictors of interstate conflicts after World War II.
Cumulative innovation is central to economic growth. Do patent rights facilitate or impede follow-on innovation? We study the causal effect of removing patent rights by court invalidation on subsequent research related to the focal patent, as measured by later citations. We exploit random allocation of judges at the U.S. Court of Appeals for the Federal Circuit to control for endogeneity of patent invalidation. Patent invalidation leads to a 50% increase in citations to the focal patent, on average, but the impact is heterogeneous and depends on characteristics of the bargaining environment. Patent rights block downstream innovation in computers, electronics, and medical instruments, but not in drugs, chemicals, or mechanical technologies. Moreover, the effect is entirely driven by invalidation of patents owned by large patentees that triggers more follow-on innovation by small firms.
When buying durable goods, consumers must forecast how much utility they will derive from future consumption, including consumption in different states of the world. This can be complicated for consumers because making intertemporal evaluations may expose them to a variety of psychological biases such as present bias, projection bias, and salience effects. We investigate whether consumers are affected by such intertemporal biases when they purchase automobiles. Using data for more than 40 million vehicle transactions, we explore the impact of weather on purchasing decisions. We find that the choice to purchase a convertible or a four-wheel-drive is highly dependent on the weather at the time of purchase in a way that is inconsistent with classical utility theory. We consider a range of rational explanations for the empirical effects we find, but none can explain fully the effects we estimate. We then discuss and explore projection bias and salience as two primary psychological mechanisms that are consistent with our results.
One long-standing motivation for low-income housing programs is the possibility that housing affordability and housing conditions generate externalities, including on children’s behavior and long-term life outcomes. We take advantage of a randomized housing voucher lottery in Chicago in 1997 to examine the long-term impact of housing assistance on a wide variety of child outcomes, including schooling, health, and criminal involvement. In contrast to most prior work focusing on families in public housing, we focus on families living in unsubsidized private housing at baseline, for whom voucher receipt generates large changes in both housing and nonhousing consumption. We find that the receipt of housing assistance has little, if any, impact on neighborhood or school quality or on a wide range of important child outcomes.
This article develops a model of unemployment fluctuations. The model keeps the architecture of the general-disequilibrium model of Barro and Grossman (1971) but takes a matching approach to the labor and product markets instead of a disequilibrium approach. On the product and labor markets, both price and tightness adjust to equalize supply and demand. Since there are two equilibrium variables but only one equilibrium condition on each market, a price mechanism is needed to select an equilibrium. We focus on two polar mechanisms: fixed prices and competitive prices. When prices are fixed, aggregate demand affects unemployment as follows. An increase in aggregate demand leads firms to find more customers. This reduces the idle time of their employees and thus increases their labor demand. This in turn reduces unemployment. We combine the predictions of the model and empirical measures of product market tightness, labor market tightness, output, and employment to assess the sources of labor market fluctuations in the United States. First, we find that product market tightness and labor market tightness fluctuate a lot, which implies that the fixed-price equilibrium describes the data better than the competitive-price equilibrium. Next, we find that labor market tightness and employment are positively correlated, which suggests that the labor market fluctuations are mostly due to labor demand shocks and not to labor supply or mismatch shocks. Last, we find that product market tightness and output are positively correlated, which suggests that the labor demand shocks mostly reflect aggregate demand shocks and not technology shocks.
We examine causes and consequences of relative income within households. We show that the distribution of the share of income earned by the wife exhibits a sharp drop to the right of 12 , where the wife’s income exceeds the husband’s income. We argue that this pattern is best explained by gender identity norms, which induce an aversion to a situation where the wife earns more than her husband. We present evidence that this aversion also impacts marriage formation, the wife’s labor force participation, the wife’s income conditional on working, marriage satisfaction, likelihood of divorce, and the division of home production. Within marriage markets, when a randomly chosen woman becomes more likely to earn more than a randomly chosen man, marriage rates decline. In couples where the wife’s potential income is likely to exceed the husband’s, the wife is less likely to be in the labor force and earns less than her potential if she does work. In couples where the wife earns more than the husband, the wife spends more time on household chores; moreover, those couples are less satisfied with their marriage and are more likely to divorce. These patterns hold both cross-sectionally and within couples over time.
We study the economic effects of religious practices in the context of the observance of Ramadan fasting, one of the central tenets of Islam. To establish causality, we exploit variation in the length of daily fasting due to the interaction between the rotating Islamic calendar and a country’s latitude. We report two key, quantitatively meaningful results: (i) longer Ramadan fasting has a negative effect on output growth in Muslim countries, and (ii) it increases subjective well-being among Muslims. We find evidence that these patterns are consistent with a standard club good explanation for the emergence of costly religious practices: increased strictness of fasting screens out the less committed members, while the more committed respond with an increase in their relative levels of participation. Together, our results underscore that religious practices can affect individual behavior and beliefs in ways that have negative implications for economic performance, but that nevertheless increase subjective well-being among followers.
The theory of comparative advantage is at the core of neoclassical trade theory. Yet we know little about its implications for how nations should conduct their trade policy. For example, should import sectors with weaker comparative advantage be protected more? Conversely, should export sectors with stronger comparative advantage be subsidized less? In this article we take a first stab at exploring these issues. Our main results imply that in the context of a canonical Ricardian model, optimal import tariffs should be uniform, whereas optimal export subsidies should be weakly decreasing with respect to comparative advantage, reflecting the fact that countries have more room to manipulate prices in their comparative-advantage sectors. Quantitative exercises suggest substantial gains from such policies relative to simpler tax schedules.
Using a unique data set on students from the first regional schools in colonial Benin, we investigate the effect of education on living standards, occupation, and political participation. Since both school locations and student cohorts were selected with very little information, treatment and control groups are balanced on observables. We can therefore estimate the effect of education by comparing the treated to the untreated living in the same village, as well as those living in villages where no schools were set up. We find a significant positive treatment effect of education for the first generation of students, as well as their descendants: they have higher living standards, are less likely to be farmers, and are more likely to be politically active. We find large village-level externalities—descendants of the uneducated in villages with schools do better than those in control villages. We also find extended family externalities—nephews and nieces directly benefit from their uncle’s education—and show that this represents a “family tax,” as educated uncles transfer resources to the extended family.
Over 130,000 juveniles are detained in the United States each year with 70,000 in detention on any given day, yet little is known about whether such a penalty deters future crime or interrupts social and human capital formation in a way that increases the likelihood of later criminal behavior. This article uses the incarceration tendency of randomly assigned judges as an instrumental variable to estimate causal effects of juvenile incarceration on high school completion and adult recidivism. Estimates based on over 35,000 juvenile offenders over a 10-year period from a large urban county in the United States suggest that juvenile incarceration results in substantially lower high school completion rates and higher adult incarceration rates, including for violent crimes. In an attempt to understand the large effects, we found that incarceration for this population could be very disruptive, greatly reducing the likelihood of ever returning to school and, for those who do return, significantly increasing the likelihood of being classified as having an emotional or behavioral disorder.
Using personnel data from nine large firms in three industries (call centers, trucking, and high-tech), we empirically assess the benefit to firms of hiring through employee referrals. Compared to nonreferred applicants, referred applicants are more likely to be hired and more likely to accept offers, even though referrals and nonreferrals have similar skill characteristics. Referred workers tend to have similar productivity compared to nonreferred workers on most measures, but referred workers have lower accident rates in trucking and produce more patents in high-tech. Referred workers are substantially less likely to quit and earn slightly higher wages than nonreferred workers. In call centers and trucking, the two industries for which we can calculate worker-level profits, referred workers yield substantially higher profits per worker than nonreferred workers. These profit differences are driven by lower turnover and lower recruiting costs for referrals.
We study the demand response to nonlinear price schedules using data on insurance contracts and prescription drug purchases in Medicare Part D. We exploit the kink in individuals’ budgets set created by the famous “donut hole,” where insurance becomes discontinuously much less generous on the margin, to provide descriptive evidence of the drug purchase response to a price increase. We then specify and estimate a simple dynamic model of drug use that allows us to quantify the spending response along the entire nonlinear budget set. We use the model for counterfactual analysis of the increase in spending from “filling” the donut hole, as will be required by 2020 under the Affordable Care Act. In our baseline model, which considers spending decisions within a single year, we estimate that filling the donut hole will increase annual drug spending by about $150, or about 8 percent. About one-quarter of this spending increase reflects anticipatory behavior, coming from beneficiaries whose spending prior to the policy change would leave them short of reaching the donut hole. We also present descriptive evidence of cross-year substitution of spending by individuals who reach the kink, which motivates a simple extension to our baseline model that allows—in a highly stylized way—for individuals to engage in such cross-year substitution. Our estimates from this extension suggest that a large share of the $150 drug spending increase could be attributed to cross-year substitution, and the net increase could be as little as $45 a year.
We study legislators who have a present bias for spending: they want to increase current spending and procrastinate spending cuts. We show that disagreement in legislatures can lead to policy persistence that attenuates the temptation to overspend. Depending on the environment, legislators’ decisions to be fiscally responsible may either complement or substitute other legislators’ decisions. When legislators have low discount factors, their actions are strategic complements. Thus, changes of the political environment that induce fiscal responsibility are desirable as they generate a positive responsibility multiplier and reduce spending. However, when the discount factor is high, the same changes induce some legislators to free ride on others’ responsibility which may lead to higher spending.
We present experimental evidence on the impact of a school choice program in the Indian state of Andhra Pradesh that provided students with a voucher to finance attending a private school of their choice. The study design featured a unique two-stage lottery-based allocation of vouchers that created both student-level and market-level experiments, which allows us to study the individual and the aggregate effects of school choice (including spillovers). After two and four years of the program, we find no difference between test scores of lottery winners and losers on Telugu (native language), math, English, and science/social studies, suggesting that the large cross-sectional differences in test scores across public and private schools mostly reflect omitted variables. However, private schools also teach Hindi, which is not taught by the public schools, and lottery winners have much higher test scores in Hindi. Furthermore, the mean cost per student in the private schools in our sample was less than a third of the cost in public schools. Thus, private schools in this setting deliver slightly better test score gains than their public counterparts (better on Hindi and same in other subjects), and do so at a substantially lower cost per student. Finally, we find no evidence of spillovers on public school students who do not apply for the voucher, or on private school students, suggesting that the positive effects on voucher winners did not come at the expense of other students.
Experimental tests of dynamically inconsistent time preferences have largely relied on choices over time-dated monetary rewards. Several recent studies have failed to find the standard patterns of present bias. However, such monetary studies contain often-discussed confounds. In this article, we sidestep these confounds and investigate choices over consumption (real effort) in a longitudinal experiment. We pair this effort study with a companion monetary discounting study. We confirm very limited time inconsistency in monetary choices. However, subjects show considerably more present bias in effort. Furthermore, present bias in the allocation of work has predictive power for demand of a meaningfully binding commitment device. Therefore our findings validate a key implication of models of dynamic inconsistency, with corresponding policy implications.
“Site selection bias” can occur when the probability that a program is adopted or evaluated is correlated with its impacts. I test for site selection bias in the context of the Opower energy conservation programs, using 111 randomized control trials involving 8.6 million households across the United States. Predictions based on rich microdata from the first 10 replications substantially overstate efficacy in the next 101 sites. Several mechanisms caused this positive selection. For example, utilities in more environmentalist areas are more likely to adopt the program, and their customers are more responsive to the treatment. Also, because utilities initially target treatment at higher-usage consumer subpopulations, efficacy drops as the program is later expanded. The results illustrate how program evaluations can still give systematically biased out-of-sample predictions, even after many replications.
Preventives are sold ex ante, before disease status is realized, while treatments are sold ex post. Even if the mean of the ex ante distribution of consumer values is the same as that ex post, the shape of the distributions may differ, generating a difference between the surplus each product can extract. If, for example, consumers differ only in ex ante disease risk, then a monopolist would have more difficulty extracting surplus with a preventive than with a treatment because treatment consumers, having contracted the disease, no longer differ in disease risk. We show that the ratio of preventive to treatment producer surplus can be arbitrarily small, in particular when the distribution of consumer values has a Zipf shape and the disease is rare. The firm’s bias toward treatments can be reversed, for example, if the source of private information is disease severity learned ex post. The difference between the producer surplus earned from the products can result in distorted R&D incentives; the deadweight loss from this distortion can be as large as the entire producer-surplus difference. Calibrations for HIV and heart attacks based on risk factors in the U.S. population suggest that the distribution of disease risk is sufficiently Zipf-similar to generate substantial differences between producer surplus from preventives and treatments. Empirically, we find that proxies for the Zipf-similarity of the disease-risk distribution are associated a significantly lower likelihood of vaccine development but not drug development.
Suppose an intermediary provides a benefit to buyers when they purchase from sellers using the intermediary’s technology. We develop a model to show that the intermediary would want to restrict sellers from charging buyers more for transactions it intermediates. With this restriction an intermediary can profitably raise demand for its services by eliminating any extra price buyers face for purchasing through the intermediary. We show that this leads to inflated retail prices, excessive adoption of the intermediaries’ services, over-investment in benefits to buyers, and a reduction in consumer surplus and sometimes welfare. Competition among intermediaries intensifies these problems by increasing the magnitude of their effects and broadening the circumstances in which they arise. We discuss applications to payment card systems, travel reservation systems, rebate services, and various other intermediaries.
When effort is observable to peers, students may try to avoid social penalties by conforming to prevailing norms. To test this hypothesis, we first consider a natural experiment that introduced a performance leaderboard into computer-based high school courses. The result was a 24 percent performance decline. The decline appears to be driven by a desire to avoid the leaderboard; top performing students prior to the change, those most at risk of appearing on the leaderboard, had a 40 percent performance decline, while poor performing students improved slightly. We next consider a field experiment that offered students complimentary access to an online SAT preparatory course. Sign-up forms differed randomly across students only in whether they said the decision would be kept private from classmates. In nonhonors classes, sign-up was 11 percentage points lower when decisions were public rather than private. Honors class sign-up was unaffected. For students taking honors and nonhonors classes, the response depended on which peers they were with at the time of the offer, and thus to whom their decision would be revealed. When offered the course in a nonhonors class (where peer sign-up rates are low), they were 15 percentage points less likely to sign up if the decision was public. But when offered the course in an honors class (where peer sign-up rates are high), they were 8 percentage points more likely to sign up if the decision was public. Thus, students are highly responsive to their peers are the prevailing norm when they make decisions. JEL Code: I21.
We provide a theory of the determination of exchange rates based on capital flows in imperfect financial markets. Capital flows drive exchange rates by altering the balance sheets of financiers that bear the risks resulting from international imbalances in the demand for financial assets. Such alterations to their balance sheets cause financiers to change their required compensation for holding currency risk, thus affecting both the level and volatility of exchange rates. Our theory of exchange rate determination in imperfect financial markets not only helps rationalize the empirical disconnect between exchange rates and traditional macroeconomic fundamentals, it also has real consequences for output and risk sharing. Exchange rates are sensitive to imbalances in financial markets and seldom perform the shock absorption role that is central to traditional theoretical macroeconomic analysis. Our framework is flexible; it accommodates a number of important modeling features within an imperfect financial market model, such as nontradables, production, money, sticky prices or wages, various forms of international pricing-to-market, and unemployment.
In developing countries, the extent to which women possess property rights is shaped in large part by transfers received at the time of marriage. Focusing on dowry, we develop a simple model of the marriage market with intrahousehold bargaining to understand the incentives for brides’ parents to allocate the rights over the dowry between their daughter and her groom. In doing so, we clarify and formalize the “dual role” of dowry—as a premortem bequest and as a market clearing price—identified in the literature. We use the model to shed light on the intriguing observation that in contrast to other rights, women’s rights over the dowry tend to deteriorate with development. We show how marriage payments are utilized even when they are inefficient, and how the marriage market mitigates changes in other dimensions of women’s rights even to the point where women are worse off following a strengthening of such rights. We also generate predictions for when marital transfers will disappear and highlight the importance of female human capital for the welfare of women.
The English Parliament’s struggle for supremacy against monarchical dictatorship during the Civil War (1642–1648) was crucial for the establishment of representative government, yet its lessons continue to be debated. I exploit novel data on individual MPs drawn from 1,842 biographies to show that the conflict was over overseas interests and other factors over which the executive enjoyed broad constitutional discretion, rather than over domestic property rights. I further exploit the coincidence of individual MPs’ ability to sign legally binding share contracts with novel share offerings by overseas companies to measure the effect of overseas share investment on their political attitudes. I show that overseas shareholding pushed moderates lacking prior mercantile interests to support reform. I interpret the effect of financial assetholding as allowing new investors to exploit emerging economic opportunities overseas, aligning their interests with traders. By consolidating a broad parliamentary majority that favored reform, the introduction of financial assets also broadened support for the institutionalization of parliamentary supremacy over dictatorial rule.
The high-frequency trading arms race is a symptom of flawed market design. Instead of the continuous limit order book market design that is currently predominant, we argue that financial exchanges should use frequent batch auctions: uniform price double auctions conducted, for example, every tenth of a second. That is, time should be treated as discrete instead of continuous, and orders should be processed in a batch auction instead of serially. Our argument has three parts. First, we use millisecond-level direct-feed data from exchanges to document a series of stylized facts about how the continuous market works at high-frequency time horizons: (i) correlations completely break down; which (ii) leads to obvious mechanical arbitrage opportunities; and (iii) competition has not affected the size or frequency of the arbitrage opportunities, it has only raised the bar for how fast one has to be to capture them. Second, we introduce a simple theory model which is motivated by and helps explain the empirical facts. The key insight is that obvious mechanical arbitrage opportunities, like those observed in the data, are built into the market design—continuous-time serial-processing implies that even symmetrically observed public information creates arbitrage rents. These rents harm liquidity provision and induce a never-ending socially wasteful arms race for speed. Last, we show that frequent batch auctions directly address the flaws of the continuous limit order book. Discrete time reduces the value of tiny speed advantages, and the auction transforms competition on speed into competition on price. Consequently, frequent batch auctions eliminate the mechanical arbitrage rents, enhance liquidity for investors, and stop the high-frequency trading arms race.
A fundamental implication of standard moral hazard models is overuse of low-value medical care because copays are lower than costs. In these models, the demand curve alone can be used to make welfare statements, a fact relied on by much empirical work. There is ample evidence, though, that people misuse care for a different reason: mistakes, or “behavioral hazard.” Much high-value care is underused even when patient costs are low, and some useless care is bought even when patients face the full cost. In the presence of behavioral hazard, welfare calculations using only the demand curve can be off by orders of magnitude or even be the wrong sign. We derive optimal copay formulas that incorporate both moral and behavioral hazard, providing a theoretical foundation for value-based insurance design and a way to interpret behavioral “nudges.” Once behavioral hazard is taken into account, health insurance can do more than just provide financial protection—it can also improve health care efficiency.
We estimate the effect of information and expertise on consumers’ willingness to pay for national brands in physically homogeneous product categories. In a detailed case study of headache remedies, we find that more informed or expert consumers are less likely to pay extra to buy national brands, with pharmacists choosing them over store brands only 9 percent of the time, compared to 26 percent of the time for the average consumer. In a similar case study of pantry staples such as salt and sugar, we show that chefs devote 12 percentage points less of their purchases to national brands than demographically similar nonchefs. We extend our analysis to cover 50 retail health categories and 241 food and drink categories. The results suggest that misinformation and related consumer mistakes explain a sizable share of the brand premium for health products, and a much smaller share for most food and drink products. We tie our estimates together using a stylized model of demand and pricing.
Does adoption of broadband internet in firms enhance labor productivity and increase wages? Is this technological change skill biased or factor neutral? We combine several Norwegian data sets to answer these questions. A public program with limited funding rolled out broadband access points and provides plausibly exogenous variation in the availability and adoption of broadband internet in firms. Our results suggest that broadband internet improves (worsens) the labor market outcomes and productivity of skilled (unskilled) workers. We explore several possible explanations for the skill complementarity of broadband internet. We find suggestive evidence that broadband adoption in firms complements skilled workers in executing nonroutine abstract tasks, and substitutes for unskilled workers in performing routine tasks. Taken together, our findings have important implications for the ongoing policy debate over government investment in broadband infrastructure to encourage productivity and wage growth.
While human capital is a strong predictor of economic development today, its importance for the Industrial Revolution has typically been assessed as minor. To resolve this puzzling contrast, we differentiate average human capital (literacy) from upper-tail knowledge. As a proxy for the historical presence of knowledge elites, we use city-level subscriptions to the famous Encyclopédie in mid-18th century France. We show that subscriber density is a strong predictor of city growth after the onset of French industrialization. Alternative measures of development such as soldier height, disposable income, and industrial activity confirm this pattern. Initial literacy levels, on the other hand, are associated with development in the cross-section, but they do not predict growth. Finally, by joining data on British patents with a large French firm survey from the 1840s, we shed light on the mechanism: upper-tail knowledge raised productivity in innovative industrial technology.
How do the media affect public support for democratic institutions in a fragile democracy? What role do they play in a dictatorial regime? We study these questions in the context of Germany of the 1920s and 1930s. During the democratic period, when the Weimar government introduced progovernment political news, the growth of Nazi popularity slowed down in areas with access to radio. This effect was reversed during the campaign for the last competitive election as a result of the pro-Nazi radio broadcast following Hitler’s appointment as chancellor. During the consolidation of dictatorship, radio propaganda helped the Nazis enroll new party members. After the Nazis established their rule, radio propaganda incited anti-Semitic acts and denunciations of Jews to authorities by ordinary citizens. The effect of anti-Semitic propaganda varied depending on the listeners’ predispositions toward the message. Nazi radio was most effective in places where anti-Semitism was historically high and had a negative effect in places with historically low anti-Semitism.
Twenty-five large field experiments with major U.S. retailers and brokerages, most reaching millions of customers and collectively representing $2.8 million in digital advertising expenditure, reveal that measuring the returns to advertising is difficult. The median confidence interval on return on investment is over 100 percentage points wide. Detailed sales data show that relative to the per capita cost of the advertising, individual-level sales are very volatile; a coefficient of variation of 10 is common. Hence, informative advertising experiments can easily require more than 10 million person-weeks, making experiments costly and potentially infeasible for many firms. Despite these unfavorable economics, randomized control trials represent progress by injecting new, unbiased information into the market. The inference challenges revealed in the field experiments also show that selection bias, due to the targeted nature of advertising, is a crippling concern for widely employed observational methods.
This article starts by unveiling a strong empirical regularity: multinational corporations exhibit higher stock market returns and earning yields than nonmultinational firms. Within nonmultinationals, exporters exhibit higher earning yields and returns than firms selling only in their domestic market. To explain this pattern, we develop a real option value model where firms are heterogeneous in productivity and have to decide whether and how to sell in a foreign market where demand is risky. Selling abroad is a source of risk exposure to firms: following a negative shock, they are reluctant to exit the foreign market because they would forgo the sunk cost they paid to enter. Multinational firms are the most exposed because of the higher costs they have to pay to invest. The calibrated model is able to match both aggregate U.S. export and foreign direct investment data, and the observed cross-sectional differences in earning yields and returns.
We propose a new model of exchange rates, based on the hypothesis that the possibility of rare but extreme disasters is an important determinant of risk premia in asset markets. The probability of world disasters as well as each country’s exposure to these events is time-varying. This creates joint fluctuations in exchange rates, interest rates, options, and stock markets. The model accounts for a series of major puzzles in exchange rates: excess volatility and exchange rate disconnect, forward premium puzzle and large excess returns of the carry trade, and comovements between stocks and exchange rates. It also makes empirically successful signature predictions regarding the link between exchange rates and telltale signs of disaster risk in currency options.
How do individuals form expectations about future inflation? We propose that individuals overweight inflation experienced during their lifetimes. This approach modifies existing adaptive learning models to allow for age-dependent updating of expectations in response to inflation surprises. Young individuals update their expectations more strongly than older individuals since recent experiences account for a greater share of their accumulated lifetime history. We find support for these predictions using 57 years of microdata on inflation expectations from the Reuters/Michigan Survey of Consumers. Differences in experiences strongly predict differences in expectations, including the substantial disagreement between young and old individuals in periods of highly volatile inflation, such as the 1970s. It also explains household borrowing and lending behavior, including the choice of mortgages.
This article develops an analytical framework to study firm and exporter growth and provides a dynamic foundation for a standard general equilibrium trade model. Firm-level growth is the result of idiosyncratic productivity improvements with a continuous arrival of new potential producers. A firm enters a market if it is profitable to incur the marginal cost to reach the first consumer and pays an increasing marketing cost to reach additional consumers. I calibrate the model using data on the cross section of firm sales and bilateral trade, as well as the rate of incumbent firm exit. The calibrated model predicts that a firm’s growth is inversely related to its initial size, and that the distribution of growth rates of small firms is heavily skewed to the right. These predictions are confirmed by looking at the growth of sales of U.S. firms and Brazilian exporters to the United States. I use this model to study the impact of cross-firm reallocations on economic activity and measured productivity.
Since the Coleman Report, many have questioned whether public school spending affects student outcomes. The school finance reforms that began in the early 1970s and accelerated in the 1980s caused dramatic changes to the structure of K–12 education spending in the United States. To study the effect of these school finance reform–induced changes in public school spending on long-run adult outcomes, we link school spending and school finance reform data to detailed, nationally representative data on children born between 1955 and 1985 and followed through 2011. We use the timing of the passage of court-mandated reforms and their associated type of funding formula change as exogenous shifters of school spending, and we compare the adult outcomes of cohorts that were differentially exposed to school finance reforms, depending on place and year of birth. Event study and instrumental variable models reveal that a 10% increase in per pupil spending each year for all 12 years of public school leads to 0.31 more completed years of education, about 7% higher wages, and a 3.2 percentage point reduction in the annual incidence of adult poverty; effects are much more pronounced for children from low-income families. Exogenous spending increases were associated with notable improvements in measured school inputs, including reductions in student-to-teacher ratios, increases in teacher salaries, and longer school years.
Performance pay for tax collectors has the potential to raise revenues, but might come at a cost if it increases the bargaining power of tax collectors vis-à-vis taxpayers. We report the first large-scale field experiment on these issues, where we experimentally allocated 482 property tax units in Punjab, Pakistan, into one of three performance pay schemes or a control. After two years, incentivized units had 9.4 log points higher revenue than controls, which translates to a 46% higher growth rate. The scheme that rewarded purely on revenue did best, increasing revenue by 12.9 log points (64% higher growth rate), with little penalty for customer satisfaction and assessment accuracy compared to the two other schemes that explicitly also rewarded these dimensions. The revenue gains accrue from a small number of properties becoming taxed at their true value, which is substantially more than they had been taxed at previously. The majority of properties in incentivized areas in fact pay no more taxes, but instead report higher bribes. The results are consistent with a collusive setting in which performance pay increases collectors’ bargaining power over taxpayers, who have to either pay higher bribes to avoid being reassessed or pay substantially higher taxes if collusion breaks down.
The incentives of political agents to enforce tax collection are key determinants of the levels of compliance. We study the electoral response to the Ghost Buildings program, a nationwide anti tax evasion policy in Italy that used innovative monitoring technologies to target buildings hidden from tax authorities. The program induced monetary and non-monetary benefits for non-evaders and an increase in local government expenditures. A one standard deviation increase in town-level program intensity leads to a 4.8% increase in local incumbent reelection rates. In addition, these political returns are higher in areas with lower tax evasion tolerance and with higher efficiency of public good provision, implying complementarity among enforcement policies, the underlying tax culture, and the quality of the government.
This article develops an idea flows theory of trade and growth with heterogeneous firms. Entrants learn from incumbent firms, and the diffusion technology is such that learning depends not on the frontier technology, but on the entire distribution of productivity. By shifting the productivity distribution upward, selection causes technology diffusion, and in equilibrium this dynamic selection process leads to endogenous growth without scale effects. On the balanced growth path, the productivity distribution is a traveling wave with a lower bound that increases over time. The free entry condition implies trade liberalization must increase the dynamic selection rate to offset the profits from new export opportunities. Consequently, trade integration raises long-run growth. Dynamic selection is a new source of gains from trade not found when firms are homogeneous. Calibrating the model implies dynamic selection approximately triples the gains from trade compared to heterogeneous firm economies with static steady states.
This article explains why decentralization can undermine accountability and answers three questions: what determines if power should be centralized or decentralized when regions are heterogeneous? How many levels of government should there be? How should state borders be drawn? We develop a model of political agency in which voters differ in their ability to monitor rent-seeking politicians. We find that rent extraction is a decreasing and convex function of the share of informed voters, because voter information improves monitoring but also reduces the appeal of holding office. As a result, information heterogeneity pushes toward centralization to reduce rent extraction. Taste heterogeneity pulls instead toward decentralization to match local preferences. Our model thus implies that optimal borders should cluster by tastes but ensure diversity of information. We also find economies of scope in accountability that explain why multiplying government tiers harms efficiency. A single government in charge of many policies has better incentives than many special-purpose governments splitting its budget and responsibilities. Hence, a federal system is desirable only if information varies enough across regions.
Programs to encourage labor market activity among youth, including public employment programs and wage subsidies like the Work Opportunity Tax Credit, can be supported by three broad rationales. They may (i) provide contemporaneous income support to participants; (ii) encourage work experience that improves future employment and/or educational outcomes of participants; and/or (iii) keep participants “out of trouble.” We study randomized lotteries for access to the New York City (NYC) Summer Youth Employment Program (SYEP), the largest summer youth employment program in the United States, by merging SYEP administrative data on 294,100 lottery participants to IRS data on the universe of U.S. tax records; to New York State administrative incarceration data; and to NYC administrative cause of death data. In assessing the three rationales, we find that (i) SYEP participation causes average earnings and the probability of employment to increase in the year of program participation, with modest contemporaneous crowdout of other earnings and employment; (ii) SYEP participation causes a modest decrease in average earnings for three years following the program and has no impact on college enrollment; and (iii) SYEP participation decreases the probability of incarceration and decreases the probability of mortality, which has important and potentially pivotal implications for analyzing the net benefits of the program.
We study political competition in an environment in which voters have private information about their preferences. Our framework covers models of income taxation, public-goods provision, or publicly provided private goods. Politicians are vote-share maximizers. They can propose any policy that is resource-feasible and incentive-compatible. They can also offer special favors to subsets of the electorate. We prove two main results. First, the unique symmetric equilibrium is such that policies are surplus-maximizing and hence first-best Pareto-efficient. Second, there is a surplus-maximizing policy that wins a majority against any welfare-maximizing policy. Thus, in our model, policies that trade off equity and efficiency considerations are politically infeasible.
This paper combines income tax returns with macroeconomic household balance sheets to estimate the distribution of wealth in the United States since 1913. We estimate wealth by capitalizing the incomes reported by individual taxpayers, accounting for assets that do not generate taxable income. We successfully test our capitalization method in three micro datasets where we can observe both income and wealth: the Survey of Consumer Finance, linked estate and income tax returns, and foundations’ tax records. We find that wealth concentration was high in the beginning of the twentieth century, fell from 1929 to 1978, and has continuously increased since then. The top 0.1% wealth share has risen from 7% in 1978 to 22% in 2012, a level almost as high as in 1929. Top wealth-holders are younger today than in the 1960s and earn a higher fraction of the economy’s labor income. The bottom 90% wealth share first increased up to the mid-1980s and then steadily declined. The increase in wealth inequality in recent decades is due to the upsurge of top incomes combined with an increase in saving rate inequality. We explain how our findings can be reconciled with Survey of Consumer Finances and estate tax data.
GDP per capita and household survey means present conflicting pictures of the rate of economic development in emerging countries. One of the areas in which the national accounts–household surveys debate is key is the measurement of developing world poverty. We propose a data-driven method to assess the relative quality of GDP per capita and survey means by comparing them to the evolution of satellite-recorded nighttime lights. Our main assumption, which is robust to a variety of specification checks, is that the measurement error in nighttime lights is unrelated to the measurement errors in either national accounts or survey means. We obtain estimates of weights on national accounts and survey means in an optimal proxy for true income; these weights are very large for national accounts and very modest for survey means. We conclusively reject the null hypothesis that the optimal weight on surveys is greater than the optimal weight on national accounts, and we generally fail to reject the null hypothesis that the optimal weight on surveys is zero. Additionally, we provide evidence that national accounts are good indicators of desirable outcomes for the poor (such as longer life expectancy, better education and access to safe water), and we show that surveys appear to perform worse in developing countries that are richer and that are growing faster. Therefore, we interpret our results as providing support for estimates of world poverty that are based on national accounts.
There is growing evidence that firm-specific pay premiums are an important source of wage inequality. These premiums will contribute to the gender wage gap if women are less likely to work at high-paying firms or if women negotiate (or are offered) worse wage bargains with their employers than men. Using longitudinal data on the hourly wages of Portuguese workers matched with income statement information for firms, we show that the wages of both men and women contain firm-specific premiums that are strongly correlated with simple measures of the potential bargaining surplus at each firm. We then show how the impact of these firm-specific pay differentials on the gender wage gap can be decomposed into a combination of sorting and bargaining effects. We find that women are less likely to work at firms that pay higher premiums to either gender, with sorting effects being most important for low- and middle-skilled workers. We also find that women receive only 90% of the firm-specific pay premiums earned by men. Importantly, we find the same gender gap in the responses of wages to changes in potential surplus over time. Taken together, the combination of sorting and bargaining effects explain about one-fifth of the cross-sectional gender wage gap in Portugal.
We use administrative data on Swedish lottery players to estimate the causal impact of substantial wealth shocks on players’ own health and their children’s health and developmental outcomes. Our estimation sample is large, virtually free of attrition, and allows us to control for the factors conditional on which the prizes were randomly assigned. In adults, we find no evidence that wealth impacts mortality or health care utilization, with the possible exception of a small reduction in the consumption of mental health drugs. Our estimates allow us to rule out effects on 10-year mortality one sixth as large as the cross-sectional wealth-mortality gradient. In our intergenerational analyses, we find that wealth increases children’s health care utilization in the years following the lottery and may also reduce obesity risk. The effects on most other child outcomes, including drug consumption, scholastic performance, and skills, can usually be bounded to a tight interval around zero. Overall, our findings suggest that in affluent countries with extensive social safety nets, causal effects of wealth are not a major source of the wealth-mortality gradients, nor of the observed relationships between child developmental outcomes and household income.
We document that in semiformal economies, banks lend to tax-evading individuals based on the bank’s assessment of the individual’s true income. This observation leads to a novel approach to estimate tax evasion. We use microdata on household credit from a Greek bank and replicate the bank underwriting model to infer the banks estimate of individuals’ true income. We estimate that 43–45% of self-employed income goes unreported and thus untaxed. For 2009, this implies €28.2 billion of unreported income, implying forgone tax revenues of over €11 billion or 30% of the deficit. Our method innovation allows for estimating the industry distribution of tax evasion in settings where uncovering the incidence of hidden cash transactions is difficult using other methods. Primary tax-evading industries are professional services—medicine, law, engineering, education, and media. We conclude with evidence that contemplates the importance of institutions, paper trail, and political willpower for the persistence of tax evasion.
This article examines the historical impact of railroads on the U.S. economy, with a focus on quantifying the aggregate impact on the agricultural sector in 1890. Expansion of the railroad network may have affected all counties directly or indirectly—an econometric challenge that arises in many empirical settings. However, the total impact on each county is captured by changes in that county’s “market access,” a reduced-form expression derived from general equilibrium trade theory. We measure counties’ market access by constructing a network database of railroads and waterways and calculating lowest-cost county-to-county freight routes. We estimate that county agricultural land values increased substantially with increases in county market access, as the railroad network expanded from 1870 to 1890. Removing all railroads in 1890 is estimated to decrease the total value of U.S. agricultural land by 60%, with limited potential for mitigating these losses through feasible extensions to the canal network or improvements to country roads.
Viruses are a major threat to human health, and—given that they spread through social interactions—represent a costly externality. This article addresses three main questions: (i) what are the unintended consequences of economic activity on the spread of infections; (ii) how efficient are measures that limit interpersonal contacts; (iii) how do we allocate our scarce resources to limit the spread of infections? To answer these questions, we use novel high frequency data from France on the incidence of a number of viral diseases across space, for different age groups, over a quarter of a century. We use quasi-experimental variation to evaluate the importance of policies reducing interpersonal contacts such as school closures or the closure of public transportation networks. While these policies significantly reduce disease prevalence, we find that they are not cost-effective. We find that expansions of transportation networks have significant health costs in increasing the spread of viruses, and that propagation rates are pro-cyclically sensitive to economic conditions and increase with inter-regional trade.
We propose a theory linking imperfect information to resource misallocation and hence to aggregate productivity and output. In our setup, firms look to a variety of noisy information sources when making input decisions. We devise a novel empirical strategy that uses a combination of firm-level production and stock market data to pin down the information structure in the economy. Even when only capital is chosen under imperfect information, applying this methodology to data from the United States, China, and India reveals substantial losses in productivity and output due to the informational friction. Our estimates for these losses range from 7% to 10% for productivity and 10% to 14% for output in China and India, and are smaller, though still significant, in the United States. Losses are substantially higher when labor decisions are also made under imperfect information. We find that firms turn primarily to internal sources for information; learning from financial markets contributes little, even in the United States.
This article examines the labor market payoffs to different types of postsecondary education, including field and institution of study. Instrumental variables (IV) estimation of the payoff to choosing one type of education compared to another is made particularly challenging by individuals choosing between several types of education. Not only does identification require one instrument per alternative, but it is also necessary to deal with the issue that individuals who choose the same education may have different next-best alternatives. We address these difficulties using rich administrative data for Norway’s postsecondary education system. A centralized admission process creates credible instruments from discontinuities that effectively randomize applicants near unpredictable admission cutoffs into different institutions and fields of study. The admission process also provides information on preferred and next-best alternatives from strategy-proof measures of individuals’ ranking of institutions and fields. The results from our IV approach may be summarized with three broad conclusions. First, different fields of study have substantially different labor market payoffs, even after accounting for institution and peer quality. Second, the effect on earnings from attending a more selective institution tends to be relatively small compared to payoffs to field of study. Third, the estimated payoffs to field of study are consistent with individuals choosing fields in which they have a comparative advantage. Comparing our estimates to those obtained from other approaches highlights the importance of using instruments to correct for selection bias and information on individuals’ ranking of institutions and fields to measure their preferred and next-best alternatives.
Individuals that consume different baskets of goods are differentially affected by relative price changes caused by international trade. We develop a methodology to measure the unequal gains from trade across consumers within countries. The approach requires data on aggregate expenditures and parameters estimated from a nonhomothetic gravity equation. We find that trade typically favors the poor, who concentrate spending in more traded sectors.
We find consistent evidence of negative autocorrelation in decision making that is unrelated to the merits of the cases considered in three separate high-stakes field settings: refugee asylum court decisions, loan application reviews, and Major League Baseball umpire pitch calls. The evidence is most consistent with the law of small numbers and the gambler’s fallacy—people underestimating the likelihood of sequential streaks occurring by chance—leading to negatively autocorrelated decisions that result in errors. The negative autocorrelation is stronger among more moderate and less experienced decision makers, following longer streaks of decisions in one direction, when the current and previous cases share similar characteristics or occur close in time, and when decision makers face weaker incentives for accuracy. Other explanations for negatively autocorrelated decisions such as quotas, learning, or preferences to treat all parties fairly are less consistent with the evidence, though we cannot completely rule out sequential contrast effects as an alternative explanation.
I present a framework for analyzing decision making under imperfect understanding of correlation structures and causal relations. A decision maker (DM) faces an objective long-run probability distribution p over several variables (including the action taken by previous DMs). The DM is characterized by a subjective causal model, represented by a directed acyclic graph over the set of variable labels. The DM attempts to fit this model to p , resulting in a subjective belief that distorts p by factorizing it according to the graph via the standard Bayesian network formula. As a result of this belief distortion, the DM’s evaluation of actions can vary with their long-run frequencies. Accordingly, I define a ”personal equilibrium” notion of individual behavior. The framework enables simple graphical representations of causal-attribution errors (such as coarseness or reverse causation), and provides tools for checking rationality properties of the DM’s behavior. I demonstrate the framework’s scope of applications with examples covering diverse areas, from demand for education to public policy.
We develop and structurally estimate a model of heterogeneous multiproduct firms that can be used to decompose the firm-size distribution into the contributions of costs, “appeal” (quality or taste), markups, and product scope. Using Nielsen barcode data on prices and sales, we find that variation in firm appeal and product scope explains at least four fifths of the variation in firm sales. We show that the imperfect substitutability of products within firms, and the fact that larger firms supply more products than smaller firms, implies that standard productivity measures are highly dependent on implicit demand system assumptions and probably dramatically understate the relative productivity of the largest firms. Although most firms are well approximated by the monopolistic competition benchmark of constant markups, we find that the largest firms that account for most of aggregate sales depart substantially from this benchmark, and exhibit both variable markups and substantial cannibalization effects.
We exploit variation in the congestion of civil courts across Brazilian municipalities, together with a bankruptcy reform increasing secured creditors’ protection, to estimate the effect of enforcement on firm access to finance, investment, and size. We find that firms operating in municipalities with less congested courts experienced a larger increase in the use of secured loans, as well as a larger increase in investment and value of output in the years after the reform. To establish the direction of causality, we use an instrumental variable strategy that exploits Brazilian state laws on judicial organization, and focus on differences in court congestion across otherwise similar neighboring municipalities located across judicial district borders within the same state. The evidence indicates that differences in court enforcement affect the impact of financial reform on firm access to finance, investment, and size.
We assigned two cohorts of kindergarten students, totaling more than 24,000 children, to teachers within schools with a rule that is as good as random. We collected data on children at the beginning of the school year and applied 12 tests of math, language, and executive function (EF) at the end of the year. All teachers were filmed teaching for a full day, and the videos were coded using the Classroom Assessment Scoring System (or CLASS). We find substantial classroom effects: A 1 standard deviation increase in classroom quality results in 0.11, 0.11, and 0.07 standard deviation higher test scores in language, math, and EF, respectively. Teacher behaviors, as measured by the CLASS, are associated with higher test scores. Parents recognize better teachers, but do not change their behaviors appreciably to take account of differences in teacher quality.
Does the lack of wealth constrain parents’ investments in the human capital of their descendants? We conduct a nearly 50-year follow-up of an episode in which such constraints would have been plausibly relaxed by a random allocation of substantial wealth to families. We track descendants of participants in Georgia’s Cherokee Land Lottery of 1832, in which nearly every adult white male in the state took part. Winners received close to the median level of wealth—a large financial windfall orthogonal to participants’ underlying characteristics that might have also affected their children’s human capital. Although winners had slightly more children than did nonwinners, they did not send them to school more. Sons of winners have no better adult outcomes (wealth, income, literacy) than the sons of nonwinners, and winners’ grandchildren do not have higher literacy or school attendance than nonwinners’ grandchildren. We can reject effects implied by the cross-sectional gradient of child outcomes by paternal wealth. This suggests only a limited role for family financial resources in the formation of human capital in the next generations in this environment and a potentially more important role for other factors that persist through family lines.
During the past three decades, many countries have lifted restrictions on cross-border financial transactions. We present a simple model that can account for the observed effects of financial globalization. The model emphasizes the role of imperfect enforcement of domestic debts and the interactions between domestic and foreign debts. Financial globalization can lead to a variety of outcomes: (i) domestic capital flight and ambiguous effects on net capital flows, investment, and growth; (ii) capital inflows and higher investment and growth; or (iii) volatile capital flows and unstable domestic financial markets. The model shows how the effects of financial globalization depend on the level of development, productivity, domestic savings, and the quality of institutions.
This article examines whether firm-level idiosyncratic shocks propagate in production networks. We identify idiosyncratic shocks with the occurrence of natural disasters. We find that affected suppliers impose substantial output losses on their customers, especially when they produce specific inputs. These output losses translate into significant market value losses, and they spill over to other suppliers. Our point estimates are economically large, suggesting that input specificity is an important determinant of the propagation of idiosyncratic shocks in the economy.
We develop a new index of economic policy uncertainty (EPU) based on newspaper
                    coverage frequency. Several types of evidence—including human readings of 12,000
                    newspaper articles—indicate that our index proxies for movements in
                    policy-related economic uncertainty. Our U.S. index spikes near tight
                    presidential elections, Gulf Wars I and II, the 9/11 attacks, the failure of
                    Lehman Brothers, the 2011 debt ceiling dispute, and other major battles over
                    fiscal policy. Using firm-level data, we find that policy uncertainty is
                    associated with greater stock price volatility and reduced investment and
                    employment in policy-sensitive sectors like defense, health care, finance, and
                    infrastructure construction. At the macro level, innovations in policy
                    uncertainty foreshadow declines in investment, output, and employment in the
                    United States and, in a panel vector autoregressive setting, for 12 major
                    economies. Extending our U.S. index back to 1900, EPU rose dramatically in the
                    1930s (from late 1931) and has drifted upward since the 1960s.
This study estimates long-run impacts of a child health investment, exploiting
community-wide experimental variation in school-based deworming. The program
increased labor supply among men and education among women, with accompanying
shifts in labor market specialization. Ten years after deworming treatment, men
who were eligible as boys stay enrolled for more years of primary school, work
17% more hours each week, spend more time in nonagricultural self-employment,
are more likely to hold manufacturing jobs, and miss one fewer meal per week.
Women who were in treatment schools as girls are approximately one quarter more
likely to have attended secondary school, halving the gender gap. They
reallocate time from traditional agriculture into cash crops and nonagricultural
self-employment. We estimate a conservative annualized financial internal rate
of return to deworming of 32%, and show that mass deworming may generate more in
future government revenue than it costs in subsidies.
We study the drivers of geographic variation in U.S. health care utilization,
using an empirical strategy that exploits migration of Medicare patients to
separate the role of demand and supply factors. Our approach allows us to
account for demand differences driven by both observable and unobservable
patient characteristics. Within our sample of over-65 Medicare beneficiaries, we
find that 40–50% of geographic variation in utilization is attributable to
demand-side factors, including health and preferences, with the remainder due to
place-specific supply factors.
Although largely absent from modern accounts of the Industrial Revolution, watches were the first mass-produced consumer durable and were Adam Smith’s preeminent example of technological progress. In fact, Smith makes the notable claim that watch prices may have fallen by up to 95% over the preceding century, a claim that this article attempts to evaluate. We look at changes in the reported value of over 3,200 stolen watches from criminal trials in the Old Bailey in London from 1685 to 1810. Before allowing for quality improvements, we find that the real price of watches in nearly all categories falls steadily by 1.3% a year, equivalent to a fall of 75% over a century, showing that sustained innovation in the production of a highly complex artifact had already appeared in one important sector of the British economy by the early eighteenth century.
We present a model of stereotypes based on Kahneman and Tversky’s representativeness heuristic. A decision maker assesses a target group by overweighting its representative types, defined as the types that occur more frequently in that group than in a baseline reference group. Stereotypes formed this way contain a “kernel of truth”: they are rooted in true differences between groups. Because stereotypes focus on differences, they cause belief distortions, particularly when groups are similar. Stereotypes are also context dependent: beliefs about a group depend on the characteristics of the reference group. In line with our predictions, beliefs in the lab about abstract groups and beliefs in the field about political groups are context dependent and distorted in the direction of representative types.
We use data from the Head Start Impact Study (HSIS) to evaluate the cost-effectiveness of Head Start, the largest early childhood education program in the United States. Head Start draws roughly a third of its participants from competing preschool programs, many of which receive public funds. We show that accounting for the fiscal impacts of such program substitution pushes estimates of Head Start’s benefit-cost ratio well above one under a wide range of assumptions on the structure of the market for preschool services and the dollar value of test score gains. To parse the program’s test score impacts relative to home care and competing preschools, we selection-correct test scores in each care environment using excluded interactions between experimental assignments and household characteristics. We find that Head Start generates larger test score gains for children who would not otherwise attend preschool and for children who are less likely to participate in the program.
Most projects, in most walks of life, require the participation of multiple
                    parties. While it is difficult to unite individuals in a common endeavor, some
                    people, who we call “movers and shakers,” seem able to do it. The article
                    specifically examines moving and shaking of an investment project, whose return
                    depends on its quality and the total capital invested in it. We analyze a model
                    with two types of agents: managers and investors. Managers and investors
                    initially form social connections. Managers then bid to buy control of the
                    project, and the winning bidder puts effort into making investors aware of it.
                    Finally, a subset of aware investors are given the chance to invest and they
                    decide whether to do so after receiving private signals of the project’s
                    quality. We first show that connections are valuable since they make it easier
                    for a manager to “move and shake” the project (i.e., obtain capital from
                    investors). When we endogenize the network, we find that while managers are
                    identical ex ante, a single manager emerges as most connected; he consequently
                    earns a rent. In extensions, we move away from the assumption of ex ante
                    identical managers to highlight forces that lead one manager or another to
                    become a mover and shaker. Our theory sheds light on a range of topics,
                    including entrepreneurship, venture capital, and anchor investments.
This article presents a unique historical experiment to explore the dynamics of
institutional change in the Middle Ages. We have assembled a novel data set,
where information on political institutions for northern central Italian cities
between 1000 and 1300 is matched with detailed information on the earthquakes
that occurred in the area and period of interest. Exploiting the panel structure
of the data, we document that the occurrence of an earthquake retarded
institutional transition from autocratic regimes to self-government (the
commune) in cities where the political and the religious leaders were the same
person (episcopal see cities), but not in cities where political and religious
powers were distinct (non–episcopal see cities). Such differential effect holds
for destructive seismic episodes and for events that were felt by the population
but did not cause any material damage to persons or objects. Ancillary results
show that seismic events provoked a positive and statistically significant
differential effect on the construction and further ornamentation of religious
buildings between episcopal and non–episcopal see cities. Our findings are
consistent with the idea that earthquakes, interpreted in the Middle Ages as
manifestation of the will and outrage of God, represented a shock to people’s
religious beliefs and, as a consequence, enhanced the ability of
political-religious leaders to restore social order after a crisis relative to
the emerging communal institutions. This interpretation is supported by
historical evidence.
This article examines the link between the opportunity cost of money and time-varying liquidity premia of near-money assets. Higher interest rates imply higher opportunity costs of holding money and hence a higher premium for the liquidity service benefits of assets that are close substitutes for money. Consistent with this theory, short-term interest rates in the United States, United Kingdom, and Canada have a strong positive relationship with the liquidity premium of Treasury bills and other near-money assets over periods going back to the 1920s. Once the opportunity cost of money is taken into account, Treasury security supply variables lose their explanatory power for the liquidity premium, except for transitory short-run effects. These findings indicate a high elasticity of substitution between money and near-money assets. As a consequence, a central bank that follows an interest rate operating target not only elastically accommodates and neutralizes shocks to money demand, but effectively also shocks to near-money asset supply and demand.
We use a randomized controlled trial to study the response of poor households in rural Kenya to unconditional cash transfers from the NGO GiveDirectly. The transfers differ from other programs in that they are explicitly unconditional, large, and concentrated in time. We randomized at both the village and household levels; furthermore, within the treatment group, we randomized recipient gender (wife versus husband), transfer timing (lump-sum transfer versus monthly installments), and transfer magnitude (US$404 PPP versus US$1,525 PPP). We find a strong consumption response to transfers, with an increase in household monthly consumption from $158 PPP to $193 PPP nine months after the transfer began. Transfer recipients experience large increases in psychological well-being. We find no overall effect on levels of the stress hormone cortisol, although there are differences across some subgroups. Monthly transfers are more likely than lump-sum transfers to improve food security, whereas lump-sum transfers are more likely to be spent on durables, suggesting that households face savings and credit constraints. Together, these results suggest that unconditional cash transfers have significant impacts on economic outcomes and psychological well-being.
We present the results of three large-scale randomized controlled trials (RCTs) carried out in Chicago, testing interventions to reduce crime and dropout by changing the decision making of economically disadvantaged youth. We study a program called Becoming a Man (BAM), developed by the nonprofit Youth Guidance, in two RCTs implemented in 2009–2010 and 2013–2015. In the two studies participation in the program reduced total arrests during the intervention period by 28–35%, reduced violent-crime arrests by 45–50%, improved school engagement, and in the first study where we have follow-up data, increased graduation rates by 12–19%. The third RCT tested a program with partially overlapping components carried out in the Cook County Juvenile Temporary Detention Center (JTDC), which reduced readmission rates to the facility by 21%. These large behavioral responses combined with modest program costs imply benefit-cost ratios for these interventions from 5-to-1 up to 30-to-1 or more. Our data on mechanisms are not ideal, but we find no positive evidence that these effects are due to changes in emotional intelligence or social skills, self-control or “grit,” or a generic mentoring effect. We find suggestive support for the hypothesis that the programs work by helping youth slow down and reflect on whether their automatic thoughts and behaviors are well suited to the situation they are in, or whether the situation could be construed differently.
This article develops a model of optimal government debt maturity in which the government cannot issue state-contingent bonds and cannot commit to fiscal policy. If the government can perfectly commit, it fully insulates the economy against government spending shocks by purchasing short-term assets and issuing long-term debt. These positions are quantitatively very large relative to GDP and do not need to be actively managed by the government. Our main result is that these conclusions are not robust to the introduction of lack of commitment. Under lack of commitment, large and tilted debt positions are very expensive to finance ex ante since they exacerbate the problem of lack of commitment ex post. In contrast, a flat maturity structure minimizes the cost of lack of commitment, though it also limits insurance and increases the volatility of fiscal policy distortions. We show that the optimal time-consistent maturity structure is nearly flat because reducing average borrowing costs is quantitatively more important for welfare than reducing fiscal policy volatility. Thus, under lack of commitment, the government actively manages its debt positions and can approximate optimal policy by confining its debt instruments to consols.
This article explores the effect of news shocks in open economies using worldwide giant oil and gas discoveries as a directly observable measure of news shocks about future output—the delay between a discovery and production is on average four to six years. We first analyze the effects of a discovery in a two-sector small open economy model with a resource sector. We then estimate the effects of giant oil and gas discoveries on a large panel of countries. Our empirical estimates are consistent with the predictions of the model. After an oil or gas discovery, the current account and saving rate decline for the first five years and then rise sharply during the ensuing years. Investment rises robustly soon after the news arrives, whereas GDP does not increase until after five years. Employment rates fall slightly and remain low for a sustained period.
Most international commerce is carried out by multinational firms, which use their foreign affiliates both to serve the market of the host country and to export to other markets outside the host country. In this article, I examine the determinants of multinational firms’ location and production decisions and the welfare implications of multinational production. The few existing quantitative general equilibrium models that incorporate multinational firms achieve tractability by assuming away export platforms—that is, they do not allow foreign affiliates of multinationals to export—or by ignoring fixed costs associated with foreign investment. I develop a quantifiable multicountry general equilibrium model, which tractably handles multinational firms that engage in export platform sales and that face fixed costs of foreign investment. I first estimate the model using German firm-level data to uncover the size and nature of costs of multinational enterprise and show that the fixed costs of foreign investment are large. Second, I calibrate the model to data on trade and multinational production for twelve European and North American countries. Counterfactual analysis reveals that multinationals play an important role in transmitting technological improvements to foreign countries and that the pending Canada-EU trade and investment agreement could divert a sizable fraction of the production of EU multinationals from the U.S. to Canada.
How are optimal taxes affected by superstar phenomena? To answer this question, we extend the Mirrlees model to incorporate an assignment problem in the labor market that generates superstar effects. Perhaps surprisingly, rather than providing a rationale for higher taxes, we show that superstar effects provide a force for lower marginal taxes conditional on the observed distribution of earnings. Superstar effects make the earnings schedule convex, which increases the responsiveness of individual earnings to tax changes. We show that various common elasticity measures must be adjusted upward in optimal tax formulas. Finally, we study a comparative static that does not keep the observed earnings distribution fixed: when superstar technologies are introduced, inequality increases but we obtain a neutrality result, finding optimal taxes unaltered.
This article argues that firms’ balance sheets were instrumental in the transmission of consumer demand shocks during the Great Recession. Using micro-level data from the U.S. Census Bureau, we find that establishments of more highly levered firms experienced significantly larger employment losses in response to declines in local consumer demand. These results are not driven by firms being less productive, having expanded too much prior to the Great Recession, or being generally more sensitive to fluctuations in either aggregate employment or house prices. Likewise, at the county level, we find that counties with more highly levered firms experienced significantly larger declines in employment in response to local consumer demand shocks. Accordingly, firms’ balance sheets also matter for aggregate employment. Our results suggest a possible role for employment policies that target firms directly besides conventional stimulus.
Illiquidity in short-term credit markets during the financial crisis might have severely curtailed the supply of nonbank consumer credit. Using a new data set linking every car sold in the United States to the credit supplier involved in each transaction, we find that the collapse of the asset-backed commercial paper market reduced the financing capacity of such nonbank lenders as captive leasing companies in the automobile industry. As a result, car sales in counties that traditionally depended on nonbank lenders declined sharply. Although other lenders increased their supply of credit, the net aggregate effect of illiquidity on car sales is large and negative. We conclude that the decline in auto sales during the financial crisis was caused in part by a credit supply shock driven by the illiquidity of the most important providers of consumer finance in the auto loan market. These results also imply that interventions aimed at arresting illiquidity in short-term credit markets might have helped contain the real effects of the crisis.
I derive a lower bound on the equity premium in terms of a volatility index, SVIX, that can be calculated from index option prices. The bound implies that the equity premium is extremely volatile and that it rose above 20% at the height of the crisis in 2008. The time-series average of the lower bound is about 5%, suggesting that the bound may be approximately tight. I run predictive regressions and find that this hypothesis is not rejected by the data, so I use the SVIX index as a proxy for the equity premium and argue that the high equity premia available at times of stress largely reflect high expected returns over the very short run. I also provide a measure of the probability of a market crash, and introduce simple variance swaps, tradable contracts based on SVIX that are robust alternatives to variance swaps.
By exploiting a commuting policy that led to a sharp and unexpected inflow of Czech workers to areas along the German-Czech border, we examine the impact of an exogenous immigration-induced labor supply shock on local wages and employment of natives. On average, the supply shock leads to a moderate decline in local native wages and a sharp decline in local native employment. These average effects mask considerable heterogeneity across groups: while younger natives experience larger wage effects, employment responses are particularly pronounced for older natives. This pattern is inconsistent with standard models of immigration but can be accounted for by a model that allows for a larger labor supply elasticity or a higher degree of wage rigidity for older than for young workers. We further show that the employment response is almost entirely driven by diminished inflows of natives into work rather than outflows into other areas or nonemployment, suggesting that “outsiders” shield “insiders” from the increased competition.
Technological advances and the development of social media have made petitions, public protests, and other form of spontaneous activism increasingly common tools for individuals to influence decision makers. To study these phenomena, in this article I present a theory of petitions and public protests that explores their limits as mechanisms to aggregate information. The key assumption is that valuable information is dispersed among citizens. Through petitions and protests, citizens can signal their private information to the policy maker, who can then choose to use it or not. I first show that if citizens’ individual signals are not sufficiently precise, information aggregation is impossible, no matter how large is the population of informed citizens, even if the conflict with the policy maker is small. I then characterize the conditions on conflict and the signal structure that guarantee information aggregation. When these conditions are satisfied, I show that full information aggregation is possible as the population grows to infinity. When they are not satisfied, I show that information aggregation may still be possible if social media are available.
We conduct a randomized experiment that generates exogenous variation in the access to foreign markets for rug producers in Egypt. Combined with detailed survey data, we causally identify the impact of exporting on firm performance. Treatment firms report 16–26% higher profits and exhibit large improvements in quality alongside reductions in output per hour relative to control firms. These findings do not simply reflect firms being offered higher margins to manufacture high-quality products that take longer to produce. Instead, we find evidence of learning-by-exporting whereby exporting improves technical efficiency. First, treatment firms have higher productivity and quality after controlling for rug specifications. Second, when asked to produce an identical domestic rug using the same inputs and same capital equipment, treatment firms produce higher quality rugs despite no difference in production time. Third, treatment firms exhibit learning curves over time. Finally, we document knowledge transfers with quality increasing most along the specific dimensions that the knowledge pertained to.
A Ramsey planner chooses a distorting tax on labor and manages a portfolio of securities in an economy with incomplete markets. We develop a method that uses second order approximations of Ramsey policies to obtain formulas for conditional and unconditional moments of government debt and taxes that include means and variances of the invariant distribution as well as speeds of mean reversion. The asymptotic mean of the planner's portfolio minimizes a measure of fiscal risk. We obtain analytic expressions that approximate moments of the invariant distribution and apply them to data on a primary government deficit, aggregate consumption, and returns on traded securities. For U.S. data, we find that the optimal target debt level is negative but close to zero, the invariant distribution of debt is very dispersed, and mean reversion is slow.
We propose a new measure of the economic importance of each innovation. Our measure uses newly collected data on patents issued to U.S. firms in the 1926 to 2010 period, combined with the stock market response to news about patents. Our patent-level estimates of private economic value are positively related to the scientific value of these patents, as measured by the number of citations the patent receives in the future. Our new measure is associated with substantial growth, reallocation, and creative destruction, consistent with the predictions of Schumpeterian growth models. Aggregating our measure suggests that technological innovation accounts for significant medium-run fluctuations in aggregate economic growth and TFP. Our measure contains additional information relative to citation-weighted patent counts; the relation between our measure and firm growth is considerably stronger. Importantly, the degree of creative destruction that is associated with our measure is higher than previous estimates, confirming that it is a useful proxy for the private valuation of patents.
We study how women's choices over labor activities in village economies correlate with poverty and whether enabling the poorest women to take on the activities of their richer counterparts can set them on a sustainable trajectory out of poverty. To do this we conduct a large-scale randomized control trial, covering over 21,000 households in 1,309 villages surveyed four times over a seven-year period, to evaluate a nationwide program in Bangladesh that transfers livestock assets and skills to the poorest women. At baseline, the poorest women mostly engage in low return and seasonal casual wage labor while wealthier women solely engage in livestock rearing. The program enables poor women to start engaging in livestock rearing, increasing their aggregate labor supply and earnings. This leads to asset accumulation (livestock, land, and business assets) and poverty reduction, both sustained after four and seven years. These gains do not crowd out the livestock businesses of noneligible households while the wages these receive for casual jobs increase as the poor reduce their labor supply. Our results show that (i) the poor are able to take on the work activities of the nonpoor but face barriers to doing so, and, (ii) one-off interventions that remove these barriers lead to sustainable poverty reduction.
Conventional value-added models (VAMs) compare average test scores across schools after regression-adjusting for students’ demographic characteristics and previous scores. This article tests for VAM bias using a procedure that asks whether VAM estimates accurately predict the achievement consequences of random assignment to specific schools. Test results from admissions lotteries in Boston suggest conventional VAM estimates are biased, a finding that motivates the development of a hierarchical model describing the joint distribution of school value-added, bias, and lottery compliance. We use this model to assess the substantive importance of bias in conventional VAM estimates and to construct hybrid value-added estimates that optimally combine ordinary least squares and lottery-based estimates of VAM parameters. The hybrid estimation strategy provides a general recipe for combining nonexperimental and quasi-experimental estimates. While still biased, hybrid school value-added estimates have lower mean squared error than conventional VAM estimates. Simulations calibrated to the Boston data show that, bias notwithstanding, policy decisions based on conventional VAMs that control for lagged achievement are likely to generate substantial achievement gains. Hybrid estimates that incorporate lotteries yield further gains.
We investigate how multinational firms contribute to the transmission of shocks across countries using a large multicountry firm-level data set that contains cross-border ownership information. We use these data to document two novel empirical patterns. First, foreign affiliate and headquarter sales exhibit strong positive comovement: a 10% growth in the sales of the headquarter is associated with a 2% growth in the sales of the affiliate. Second, shocks to the source country account for a significant fraction of the variation in sales growth at the source-destination level. We propose a parsimonious quantitative model to interpret these findings and to evaluate the role of multinational firms for international business cycle transmission. For the typical country, the impact of foreign shocks transmitted by all foreign multinationals combined is non-negligible, accounting for about 10% of aggregate productivity shocks. On the other hand, since bilateral multinational production shares are small, interdependence between most individual country pairs is minimal. Our results do reveal substantial heterogeneity in the strength of this mechanism, with the most integrated countries significantly more affected by foreign shocks.
To reduce poverty and food insecurity in Africa requires raising productivity in agriculture. Systematic use of fertilizer and hybrid seed is a pathway to increased productivity, but adoption of these technologies remains low. We investigate whether the quality of agricultural inputs can help explain low take-up. Testing modern products purchased in local markets, we find that 30% of nutrient is missing in fertilizer, and hybrid maize seed is estimated to contain less than 50% authentic seeds. We document that such low quality results in low average returns. If authentic technologies replaced these low-quality products, however, average returns are high. To rationalize the findings, we calibrate a learning model using data from our agricultural trials. Because agricultural yields are noisy, farmers’ ability to learn about quality is limited and this can help explain the low quality equilibrium we observe, but also why the market has not fully collapsed.
This article studies technology adoption in a cluster of soccer-ball producers in Sialkot, Pakistan. We invented a new cutting technology that reduces waste of the primary raw material and gave the technology to a random subset of producers. Despite the clear net benefits for nearly all firms, after 15 months take-up remained puzzlingly low. We hypothesize that an important reason for the lack of adoption is a misalignment of incentives within firms: the key employees (cutters and printers) are typically paid piece rates, with no incentive to reduce waste, and the new technology slows them down, at least initially. Fearing reductions in their effective wage, employees resist adoption in various ways, including by misinforming owners about the value of the technology. To investigate this hypothesis, we implemented a second experiment among the firms that originally received the technology: we offered one cutter and one printer per firm a lump-sum payment, approximately a month’s earnings, conditional on demonstrating competence in using the technology in the presence of the owner. This incentive payment, small from the point of view of the firm, had a significant positive effect on adoption. The results suggest that misalignment of incentives within firms is an important barrier to technology adoption in our setting.
The nature of the relationship between employers and employees has been changing over the past three decades, with firms increasingly relying on contractors, temp agencies, and franchises rather than hiring employees directly. We investigate the impact of this transformation on the wage structure by following jobs that are moved outside the boundary of lead employers to contracting firms. We develop a new method for identifying outsourcing of food, cleaning, security, and logistics services in administrative data using the universe of social security records in Germany. We document a dramatic growth of domestic outsourcing in Germany since the early 1990s. Event-study analyses show that wages in outsourced jobs fall by approximately 10–15% relative to similar jobs that are not outsourced. We find evidence that the wage losses associated with outsourcing stem from a loss of firm-specific rents, suggesting that labor cost savings are an important reason firms choose to contract out these services. Finally, we tie the increase in outsourcing activity to broader changes in the German wage structure, in particular showing that outsourcing of cleaning, security, and logistics services alone accounts for around 9% of the increase in German wage inequality since the 1980s.
Examining the performance of cashiers in a French grocery store chain, we find that manager bias negatively affects minority job performance. In the stores studied, cashiers work with different managers on different days and their schedules are determined quasi-randomly. When minority cashiers, but not majority cashiers, are scheduled to work with managers who are biased (as determined by an implicit association test), they are absent more often, spend less time at work, scan items more slowly, and take more time between customers. This appears to be because biased managers interact less with minorities, leading minorities to exert less effort. Manager bias has consequences for the average performance of minority workers: while on average minority and majority workers perform equivalently, on days where managers are unbiased, minorities perform significantly better than do majority workers. The findings are consistent with statistical discrimination in hiring whereby because minorities underperform when assigned to biased managers, the firm sets a higher hiring standard for minorities to get similar average performance from minority and nonminority workers.
Measuring consumer responsiveness to medical care prices is a central issue in health economics and a key ingredient in the optimal design and regulation of health insurance markets. We leverage a natural experiment at a large self-insured firm that required all of its employees to switch from an insurance plan that provided free health care to a nonlinear, high-deductible plan. The switch caused a spending reduction between 11.8% and 13.8% of total firm-wide health spending. We decompose this spending reduction into the components of (i) consumer price shopping, (ii) quantity reductions, and (iii) quantity substitutions and find that spending reductions are entirely due to outright reductions in quantity. We find no evidence of consumers learning to price shop after two years in high-deductible coverage. Consumers reduce quantities across the spectrum of health care services, including potentially valuable care (e.g., preventive services) and potentially wasteful care (e.g., imaging services). To better understand these changes, we study how consumers respond to the complex structure of the high-deductible contract. Consumers respond heavily to spot prices at the time of care, reducing their spending by 42% when under the deductible, conditional on their true expected end-of-year price and their prior year end-of-year marginal price. There is no evidence of learning to respond to the true shadow price in the second year post-switch.
We examine the health plan choices that 23,894 employees at a U.S. firm made from a large menu of options that differed only in financial cost-sharing and premium. These decisions provide a clear test of the predictions of the standard economic model of insurance choice in the absence of choice frictions because plans were priced so that nearly every plan with a lower deductible was financially dominated by an otherwise identical plan with a high deductible. We document that the majority of employees chose dominated plans, which resulted in excess spending equivalent to 24% of chosen plan premiums. Low-income employees were significantly more likely to choose dominated plans, and most employees did not switch into more financially efficient plans in the subsequent year. We show that the choice of dominated plans cannot be rationalized by standard risk preference or any expectations about health risk. Testing alternative explanations with a series of hypothetical-choice experiments, we find that the popularity of dominated plans was not primarily driven by the size and complexity of the plan menu, nor informed preferences for avoiding high deductibles, but by employees’ lack of understanding of health insurance. Our findings challenge the standard practice of inferring risk preferences from insurance choices and raise doubts about the welfare benefits of health reforms that expand consumer choice.
Using U.S. data from 1929 to 2015, we show that elevated credit-market sentiment in year t − 2 is associated with a decline in economic activity in years t and t + 1. Underlying this result is the existence of predictable mean reversion in credit-market conditions. When credit risk is aggressively priced, spreads subsequently widen. The timing of this widening is, in turn, closely tied to the onset of a contraction in economic activity. Exploring the mechanism, we find that buoyant credit-market sentiment in year t − 2 also forecasts a change in the composition of external finance: net debt issuance falls in year t, while net equity issuance increases, consistent with the reversal in credit-market conditions leading to an inward shift in credit supply. Unlike much of the current literature on the role of financial frictions in macroeconomics, this article suggests that investor sentiment in credit markets can be an important driver of economic fluctuations.
We study the effects of a credit crunch on consumer spending in a heterogeneous-agent incomplete-market model. After an unexpected permanent tightening in consumers’ borrowing capacity, constrained consumers are forced to repay their debt, and unconstrained consumers increase their precautionary savings. This depresses interest rates, especially in the short run, and generates an output drop, even with flexible prices. The output drop is larger with sticky prices, if the zero lower bound prevents the interest rate from adjusting downward. Adding durable goods to the model, households take larger debt positions and the output response can be larger.
This study investigates how banks design financial products to cater to yield-seeking investors. We focus on a large market of investment products targeted exclusively at households: retail structured products. These products typically offer a high return under their best-case scenario—the headline rate—that is nested in a complex payoff formula. Using a text analysis of the payoff formulas of the 55,000 products issued in Europe from 2002 to 2010, we measure product headline rates, complexity, and risk. Over this period, product headline rates depart from the prevailing interest rates as the latter decrease, complexity increases, and risky products become more common. In the cross section, the headline rate of a product is positively correlated with its level of complexity and risk. Higher headline rate, more complex, and riskier products appear more profitable to the banks distributing them. Our results suggest that financial complexity is a by-product of banks catering to yield-seeking investors.
We develop a theory of legislative competition in which voters care about local candidate valence and national party positions that are determined by the parties’ median legislators. As long as election outcomes are sufficiently predictable, the only stable equilibria exhibit policy divergence between the parties. If the degree of uncertainty about election outcomes decreases, and if voters place less weight on local candidates’ valence, polarization between the parties increases. Furthermore, a systematic electoral shock makes the party favored by the shock more moderate, while the disadvantaged party becomes more extreme. Finally, we examine data on state elections and the ideological positions of state legislatures and find patterns that are consistent with key predictions of our model.
We propose a local measure of the relationship between parameter estimates and the moments of the data they depend on. Our measure can be computed at negligible cost even for complex structural models. We argue that reporting this measure can increase the transparency of structural estimates, making it easier for readers to predict the way violations of identifying assumptions would affect the results. When the key assumptions are orthogonality between error terms and excluded instruments, we show that our measure provides a natural extension of the omitted variables bias formula for nonlinear models. We illustrate with applications to published articles in several fields of economics.
The labor market increasingly rewards social skills. Between 1980 and 2012, jobs requiring high levels of social interaction grew by nearly 12 percentage points as a share of the U.S. labor force. Math-intensive but less social jobs—including many STEM occupations—shrank by 3.3 percentage points over the same period. Employment and wage growth were particularly strong for jobs requiring high levels of both math skill and social skills. To understand these patterns, I develop a model of team production where workers “trade tasks” to exploit their comparative advantage. In the model, social skills reduce coordination costs, allowing workers to specialize and work together more efficiently. The model generates predictions about sorting and the relative returns to skill across occupations, which I investigate using data from the NLSY79 and the NLSY97. Using a comparable set of skill measures and covariates across survey waves, I find that the labor market return to social skills was much greater in the 2000s than in the mid-1980s and 1990s.
We develop a theory of endogenous uncertainty and business cycles in which short-lived shocks can generate long-lasting recessions. In the model, higher uncertainty about fundamentals discourages investment. Since agents learn from the actions of others, information flows slowly in times of low activity and uncertainty remains high, further discouraging investment. The economy displays uncertainty traps: self-reinforcing episodes of high uncertainty and low activity. Although the economy recovers quickly after small shocks, large temporary shocks may have long-lasting effects on the level of activity. The economy is subject to an information externality but uncertainty traps may remain in the efficient allocation. Embedding the mechanism in a standard business cycle framework, we find that endogenous uncertainty increases the persistence of large recessions and improves the performance of the model in accounting for the Great Recession.
What shapes the optimal degree of progressivity of the tax and transfer system? On the one hand, a progressive tax system can counteract inequality in initial conditions and substitute for imperfect private insurance against idiosyncratic earnings risk. On the other hand, progressivity reduces incentives to work and to invest in skills, distortions that are especially costly when the government must finance public goods. We develop a tractable equilibrium model that features all of these trade-offs. The analytical expressions we derive for social welfare deliver a transparent understanding of how preference, technology, and market structure parameters influence the optimal degree of progressivity. A calibration for the U.S. economy indicates that endogenous skill investment, flexible labor supply, and the desire to finance government purchases play quantitatively similar roles in limiting optimal progressivity. In a version of the model where poverty constrains skill investment, optimal progressivity is close to the U.S. value. An empirical analysis on cross-country data offers support to the theory.
An increase in the household debt to GDP ratio predicts lower GDP growth and higher unemployment in the medium run for an unbalanced panel of 30 countries from 1960 to 2012. Low mortgage spreads are associated with an increase in the household debt to GDP ratio and a decline in subsequent GDP growth, highlighting the importance of credit supply shocks. Economic forecasters systematically over-predict GDP growth at the end of household debt booms, suggesting an important role of flawed expectations formation. The negative relation between the change in household debt to GDP and subsequent output growth is stronger for countries with less flexible exchange rate regimes. We also uncover a global household debt cycle that partly predicts the severity of the global growth slowdown after 2007. Countries with a household debt cycle more correlated with the global household debt cycle experience a sharper decline in growth after an increase in domestic household debt.
We present a new channel for the transmission of monetary policy, the deposits channel. We show that when the Fed funds rate rises, banks widen the spreads they charge on deposits, and deposits flow out of the banking system. We present a model where this is due to market power in deposit markets. Consistent with the market power mechanism, deposit spreads increase more and deposits flow out more in concentrated markets. This is true even when we control for lending opportunities by only comparing different branches of the same bank. Since deposits are the main source of liquid assets for households, the deposits channel can explain the observed strong relationship between the liquidity premium and the Fed funds rate. Since deposits are also a uniquely stable funding source for banks, the deposits channel impacts bank lending. When the Fed funds rate rises, banks that raise deposits in concentrated markets contract their lending by more than other banks. Our estimates imply that the deposits channel can account for the entire transmission of monetary policy through bank balance sheets.
Can a democracy attract competent leaders, while attaining broad representation? Economic models suggest that free-riding incentives and lower opportunity costs give the less competent a comparative advantage at entering political life. Moreover, if elites have more human capital, selecting on competence may lead to uneven representation. This article examines patterns of political selection among the universe of municipal politicians and national legislators in Sweden, using extraordinarily rich data on competence traits and social background for the entire population. We document four new facts that together characterize an “inclusive meritocracy.” First, politicians are on average significantly smarter and better leaders than the population they represent. Second, this positive selection is present even when conditioning on family (and hence social) background, suggesting that individual competence is key for selection. Third, the representation of social background, whether measured by parental earnings or occupational social class, is remarkably even. Fourth, there is at best a weak trade-off in selection between competence and social representation, mainly due to strong positive selection of politicians of low (parental) socioeconomic status. A broad implication of these facts is that it is possible for democracy to generate competent and socially representative leadership.
Starting in the early 1990s, countries in southern Europe experienced low productivity growth alongside declining real interest rates. We use data for manufacturing firms in Spain between 1999 and 2012 to document a significant increase in the dispersion of the return to capital across firms, a stable dispersion of the return to labor, and a significant increase in productivity losses from capital misallocation over time. We develop a model with size-dependent financial frictions that is consistent with important aspects of firms’ behavior in production and balance sheet data. We illustrate how the decline in the real interest rate, often attributed to the euro convergence process, leads to a significant decline in sectoral total factor productivity as capital inflows are misallocated toward firms that have higher net worth but are not necessarily more productive. We show that similar trends in dispersion and productivity losses are observed in Italy and Portugal but not in Germany, France, and Norway.
We propose a model of job search with reference-dependent preferences, with loss aversion relative to recent income (the reference point). In this model, newly unemployed individuals search hard since consumption is below their reference point. Over time, though, they get used to lower income and thus reduce their search effort. In anticipation of a benefit cut, their search effort rises again, then declines once they get accustomed to the lower postcut benefit level. The model fits the typical pattern of exit from unemployment, even with no unobserved heterogeneity. To distinguish between this and other models, we use a unique reform in the unemployment insurance (UI) benefit path. In 2005, Hungary switched from a single-step UI system to a two-step system, with overall generosity unchanged. The system generated increased hazard rates in anticipation of, and especially following, benefit cuts in ways the standard model has a hard time explaining. We estimate a model with optimal consumption, endogenous search effort, and unobserved heterogeneity. The reference-dependent model fits the hazard rates substantially better than plausible versions of the standard model, including habit formation. Our estimates indicate a slow-adjusting reference point and substantial impatience, likely reflecting present-bias.
We present evidence that a significant fraction of commuters on the London Underground do not travel on their optimal route. We show that a strike on the Underground, which forced many commuters to experiment with new routes, brought lasting changes in behavior. This effect is stronger for commuters who live in areas where the Underground map is more distorted, which points to the importance of informational imperfections. Information resulting from the strike improved network efficiency. Search costs alone are unlikely to explain the suboptimal behavior.
In the centuries leading up to the Industrial Revolution, Western Europe gradually pulled ahead of other world regions in terms of technological creativity, population growth, and income per capita. We argue that superior institutions for the creation and dissemination of productive knowledge help explain the European advantage. We build a model of technological progress in a preindustrial economy that emphasizes the person-to-person transmission of tacit knowledge. The young learn as apprentices from the old. Institutions such as the family, the clan, the guild, and the market organize who learns from whom. We argue that medieval European institutions such as guilds, and specific features such as journeymanship, can explain the rise of Europe relative to regions that relied on the transmission of knowledge within closed kinship systems (extended families or clans).
We document a form of excess volatility that is difficult to reconcile with standard models of prices, even after accounting for variation in discount rates. We compare prices of claims on the same cash flow stream but with different maturities. Standard models impose precise internal consistency conditions on the joint behavior of long- and short-maturity claims and these are strongly rejected in the data. In particular, long-maturity prices are significantly more variable than justified by the behavior at short maturities. We reject internal consistency conditions in all term structures that we study, including equity options, currency options, credit default swaps, commodity futures, variance swaps, and inflation swaps.
We propose a new approach to studying the pass-through of credit expansion policies that focuses on frictions, such as asymmetric information, that arise in the interaction between banks and borrowers. We decompose the effect of changes in banks’ cost of funds on aggregate borrowing into the product of banks’ marginal propensity to lend (MPL) to borrowers and those borrowers’ marginal propensity to borrow (MPB), aggregated over all borrowers in the economy. We apply our framework by estimating heterogeneous MPBs and MPLs in the U.S. credit card market. Using panel data on 8.5 million credit cards and 743 credit limit regression discontinuities, we find that the MPB is declining in credit score, falling from 59% for consumers with FICO scores below 660 to essentially zero for consumers with FICO scores above 740. We use a simple model of optimal credit limits to show that a bank’s MPL depends on a small number of parameters that can be estimated using our credit limit discontinuities. For the lowest FICO score consumers, higher credit limits sharply reduce profits from lending, limiting banks’ optimal MPL to these consumers. The negative correlation between MPB and MPL reduces the impact of changes in banks’ cost of funds on aggregate household borrowing, and highlights the importance of frictions in bank-borrower interactions for understanding the pass-through of credit expansions.
“Ban the Box” (BTB) policies restrict employers from asking about applicants’ criminal histories on job applications and are often presented as a means of reducing unemployment among black men, who disproportionately have criminal records. However, withholding information about criminal records could risk encouraging racial discrimination: employers may make assumptions about criminality based on the applicant's race. To investigate BTB’s effects, we sent approximately 15,000 online job applications on behalf of fictitious young, male applicants to employers in New Jersey and New York City before and after the adoption of BTB policies. These applications varied whether the applicant had a distinctly black or distinctly white name and the felony conviction status of the applicant. We confirm that criminal records are a major barrier to employment: employers that asked about criminal records were 63% more likely to call applicants with no record. However, our results support the concern that BTB policies encourage racial discrimination: the black-white gap in callbacks grew dramatically at companies that removed the box after the policy went into effect. Before BTB, white applicants to employers with the box received 7% more callbacks than similar black applicants, but BTB increased this gap to 43%. We believe that the best interpretation of these results is that employers are relying on exaggerated impressions of real-world racial differences in felony conviction rates.
Can machine learning improve human decision making? Bail decisions provide a good test case. Millions of times each year, judges make jail-or-release decisions that hinge on a prediction of what a defendant would do if released. The concreteness of the prediction task combined with the volume of data available makes this a promising machine-learning application. Yet comparing the algorithm to judges proves complicated. First, the available data are generated by prior judge decisions. We only observe crime outcomes for released defendants, not for those judges detained. This makes it hard to evaluate counterfactual decision rules based on algorithmic predictions. Second, judges may have a broader set of preferences than the variable the algorithm predicts; for instance, judges may care specifically about violent crimes or about racial inequities. We deal with these problems using different econometric strategies, such as quasi-random assignment of cases to judges. Even accounting for these concerns, our results suggest potentially large welfare gains: one policy simulation shows crime reductions up to 24.7% with no change in jailing rates, or jailing rate reductions up to 41.9% with no increase in crime rates. Moreover, all categories of crime, including violent crimes, show reductions; these gains can be achieved while simultaneously reducing racial disparities. These results suggest that while machine learning can be valuable, realizing this value requires integrating these tools into an economic framework: being clear about the link between predictions and decisions; specifying the scope of payoff functions; and constructing unbiased decision counterfactuals.
We propose a simple model of the international monetary system. We study the world supply and demand for reserve assets denominated in different currencies under a variety of scenarios: a hegemon versus a multipolar world; abundant versus scarce reserve assets; and a gold exchange standard versus a floating rate system. We rationalize the Triffin dilemma, which posits the fundamental instability of the system, as well as the common prediction regarding the natural and beneficial emergence of a multipolar world, the Nurkse warning that a multipolar world is more unstable than a hegemon world, and the Keynesian argument that a scarcity of reserve assets under a gold standard or at the zero lower bound is recessionary. Our analysis is both positive and normative.
We explore the role of natural characteristics in determining the worldwide spatial distribution of economic activity, as proxied by lights at night, observed across 240,000 grid cells. A parsimonious set of 24 physical geography attributes explains 47% of worldwide variation and 35% of within-country variation in lights. We divide geographic characteristics into two groups, those primarily important for agriculture and those primarily important for trade, and confront a puzzle. In examining within-country variation in lights, among countries that developed early, agricultural variables incrementally explain over 6 times as much variation in lights as do trade variables, while among late developing countries the ratio is only about 1.5, even though the latter group is far more dependent on agriculture. Correspondingly, the marginal effects of agricultural variables as a group on lights are larger in absolute value, and those for trade smaller, for early developers than for late developers. We show that this apparent puzzle is explained by persistence and the differential timing of technological shocks in the two sets of countries. For early developers, structural transformation due to rising agricultural productivity began when transport costs were still high, so cities were localized in agricultural regions. When transport costs fell, these agglomerations persisted. In late-developing countries, transport costs fell before structural transformation. To exploit urban scale economies, manufacturing agglomerated in relatively few, often coastal, locations. Consistent with this explanation, countries that developed earlier are more spatially equal in their distribution of education and economic activity than late developers.
For 40 years, the Tuskegee Study of Untreated Syphilis in the Negro Male passively monitored hundreds of adult black men with syphilis despite the availability of effective treatment. The study’s methods have become synonymous with exploitation and mistreatment by the medical profession. To identify the study’s effects on the behavior and health of older black men, we use an interacted difference-in-difference-in-differences model, comparing older black men to other demographic groups, before and after the Tuskegee revelation, in varying proximity to the study’s victims. We find that the disclosure of the study in 1972 is correlated with increases in medical mistrust and mortality and decreases in both outpatient and inpatient physician interactions for older black men. Our estimates imply life expectancy at age 45 for black men fell by up to 1.5 years in response to the disclosure, accounting for approximately 35% of the 1980 life expectancy gap between black and white men and 25% of the gap between black men and women.
We use a hypothetical choice methodology to estimate preferences for workplace attributes from a sample of high-ability undergraduates attending a highly selective university. We estimate that women on average have a higher willingness to pay (WTP) for jobs with greater work flexibility and job stability, and men have a higher WTP for jobs with higher earnings growth. These job preferences relate to college major choices and to actual job choices reported in a follow-up survey four years after graduation. The gender differences in preferences explain at least a quarter of the early career gender wage gap.
More than half a century after the first experiment on the finitely repeated prisoner’s dilemma, evidence on whether cooperation decreases with experience—as suggested by backward induction—remains inconclusive. This article provides a meta-analysis of prior experimental research and reports the results of a new experiment to elucidate how cooperation varies with the environment in this canonical game. We describe forces that affect initial play (formation of cooperation) and unraveling (breakdown of cooperation). First, contrary to the backward induction prediction, the parameters of the repeated game have a significant effect on initial cooperation. We identify how these parameters impact the value of cooperation—as captured by the size of the basin of attraction of always defect—to account for an important part of this effect. Second, despite these initial differences, the evolution of behavior is consistent with the unraveling logic of backward induction for all parameter combinations. Importantly, despite the seemingly contradictory results across studies, this article establishes a systematic pattern of behavior: subjects converge to use threshold strategies that conditionally cooperate until a threshold round; conditional on establishing cooperation, the first defection round moves earlier with experience. Simulation results generated from a learning model estimated at the subject level provide insights into the long-term dynamics and the forces that slow down the unraveling of cooperation.
This article combines tax, survey, and national accounts data to estimate the distribution of national income in the United States since 1913. Our distributional national accounts capture 100% of national income, allowing us to compute growth rates for each quantile of the income distribution consistent with macroeconomic growth. We estimate the distribution of both pretax and posttax income, making it possible to provide a comprehensive view of how government redistribution affects inequality. Average pretax real national income per adult has increased 60% from 1980 to 2014, but we find that it has stagnated for the bottom 50% of the distribution at about $16,000 a year. The pretax income of the middle class—adults between the median and the 90th percentile—has grown 40% since 1980, faster than what tax and survey data suggest, due in particular to the rise of tax-exempt fringe benefits. Income has boomed at the top. The upsurge of top incomes was first a labor income phenomenon but has mostly been a capital income phenomenon since 2000. The government has offset only a small fraction of the increase in inequality. The reduction of the gender gap in earnings has mitigated the increase in inequality among adults, but the share of women falls steeply as one moves up the labor income distribution, and is only 11% in the top 0.1% in 2014.
Relative-pay concerns have potentially broad labor market implications. In a month-long experiment with Indian manufacturing workers, we randomize whether coworkers within production units receive the same flat daily wage or differential wages according to their (baseline) productivity ranks. When coworkers’ productivity is difficult to observe, pay inequality reduces output by 0.45 standard deviations and attendance by 18 percentage points. It also lowers coworkers’ ability to cooperate in their own self-interest. However, when workers can clearly perceive that their higher-paid peers are more productive than themselves, pay disparity has no discernible effect on output, attendance, or group cohesion. These findings help inform our understanding of when pay compression is more likely to arise in the labor market
We use new data on the pre- and postmigration wages of immigrants to the United States to measure wage gains at migration. The average immigrant from a middle-income or poor country increases their wage by a factor of two to three upon migration. This wage gain is small relative to the underlying gap in GDP per worker. In a development accounting framework, this finding implies that switching countries accounts for 40% of cross-country income differences, while human capital accounts for 60%. Wage gains decline with education, consistent with imperfect substitution between skill types. We augment our analysis to allow for this possibility and bound the human capital share in development accounting to between one-half and two-thirds. We also provide results on the importance of premigration sector of employment, assimilation, and skill transfer.
This study uses discontinuities in U.S. strategies employed during the Vietnam War to estimate their causal impacts. It identifies the effects of bombing by exploiting rounding thresholds in an algorithm used to target air strikes. Bombing increased the military and political activities of the communist insurgency, weakened local governance, and reduced noncommunist civic engagement. The study also exploits a spatial discontinuity across neighboring military regions that pursued different counterinsurgency strategies. A strategy emphasizing overwhelming firepower plausibly increased insurgent attacks and worsened attitudes toward the U.S. and South Vietnamese government, relative to a more hearts-and-minds-oriented approach.
Job-testing technologies enable firms to rely less on human judgment when making hiring decisions. Placing more weight on test scores may improve hiring decisions by reducing the influence of human bias or mistakes but may also lead firms to forgo the potentially valuable private information of their managers. We study the introduction of job testing across 15 firms employing low-skilled service sector workers. When faced with similar applicant pools, we find that managers who appear to hire against test recommendations end up with worse average hires. This suggests that managers often overrule test recommendations because they are biased or mistaken, not only because they have superior private information.
How does transparency, a key feature of central bank design, affect monetary policy makers’ deliberations? Theory predicts a positive discipline effect and negative conformity effect. We empirically explore these effects using a natural experiment in the Federal Open Market Committee in 1993 and computational linguistics algorithms. We first find large changes in communication patterns after transparency. We then propose a difference-in-differences approach inspired by the career concerns literature, and find evidence for both effects. Finally, we construct an influence measure that suggests the discipline effect dominates.
This article studies how a recommender system may incentivize users to learn about a product collaboratively. To improve the incentives for early exploration, the optimal design trades off fully transparent disclosure by selectively overrecommending the product (or “spamming”) to a fraction of users. Under the optimal scheme, the designer spams very little on a product immediately after its release but gradually increases its frequency; she stops it altogether when she becomes sufficiently pessimistic about the product. The recommender’s product research and intrinsic/naive users “seed” incentives for user exploration and determine the speed and trajectory of social learning. Potential applications for various Internet recommendation platforms and implications for review/ratings inflation are discussed.
We show that World War I and the subsequent boycott against Central scientists severely interrupted international scientific cooperation. After 1914, citations to recent research from abroad decreased and paper titles became less similar (evaluated by latent semantic analysis), suggesting a reduction in international knowledge flows. Reduced international scientific cooperation led to a decline in the production of basic science and its application in new technology. Specifically, we compare productivity changes for scientists who relied on frontier research from abroad, to changes for scientists who relied on frontier research from home. After 1914, scientists who relied on frontier research from abroad published fewer papers in top scientific journals, produced less Nobel Prize–nominated research, introduced fewer novel scientific words, and introduced fewer novel words that appeared in the text of subsequent patent grants. The productivity of scientists who relied on top 1% research declined twice as much as the productivity of scientists who relied on top 3% research. Furthermore, highly prolific scientists experienced the starkest absolute productivity declines. This suggests that access to the very best research is key for scientific and technological progress.
How does a large unconditional increase in salary affect the performance of incumbent employees in the public sector? We present experimental evidence on this question in the context of a policy change in Indonesia that led to a permanent doubling of teacher base salaries. Using a large-scale randomized experiment across a representative sample of Indonesian schools that accelerated this pay increase for teachers in treated schools, we find that the large pay increase significantly improved teachers' satisfaction with their income, reduced the incidence of teachers holding outside jobs, and reduced self-reported financial stress. Nevertheless, after two and three years, the increase in pay led to no improvement in student learning outcomes. The effects are precisely estimated, and we can rule out even modest positive impacts on test scores. Our results suggest that unconditional pay increases are unlikely to be an effective policy option for improving the effort and productivity of incumbent employees in public-sector settings.
An influential thesis often associated with de Tocqueville views social mobility as a bulwark of democracy: when members of a social group expect to join the ranks of other social groups in the near future, they should have less reason to exclude these other groups from the political process. In this article, we investigate this hypothesis using a dynamic model of political economy. As well as formalizing this argument, our model demonstrates its limits, elucidating a robust theoretical force making democracy less stable in societies with high social mobility: when the median voter expects to move up (respectively down), she would prefer to give less voice to poorer (respectively richer) social groups. Our theoretical analysis shows that in the presence of social mobility, the political preferences of an individual depend on the potentially conflicting preferences of her “future selves,” and that the evolution of institutions is determined through the implicit interaction between occupants of the same social niche at different points in time.
We show that the neighborhoods in which children grow up shape their earnings, college attendance rates, and fertility and marriage patterns by studying more than 7 million families who move across commuting zones and counties in the United States. Exploiting variation in the age of children when families move, we find that neighborhoods have significant childhood exposure effects: the outcomes of children whose families move to a better neighborhood—as measured by the outcomes of children already living there—improve linearly in proportion to the amount of time they spend growing up in that area, at a rate of approximately 4% per year of exposure. We distinguish the causal effects of neighborhoods from confounding factors by comparing the outcomes of siblings within families, studying moves triggered by displacement shocks, and exploiting sharp variation in predicted place effects across birth cohorts, genders, and quantiles to implement overidentification tests. The findings show that neighborhoods affect intergenerational mobility primarily through childhood exposure, helping reconcile conflicting results in the prior literature.
We estimate the causal effect of each county in the United States on children’s incomes in adulthood. We first estimate a fixed effects model that is identified by analyzing families who move across counties with children of different ages. We then use these fixed effect estimates to (i) quantify how much places matter for intergenerational mobility, (ii) construct forecasts of the causal effect of growing up in each county that can be used to guide families seeking to move to opportunity, and (iii) characterize which types of areas produce better outcomes. For children growing up in low-income families, each year of childhood exposure to a one standard deviation (std. dev.) better county increases income in adulthood by 0.5%. There is substantial variation in counties’ causal effects even within metro areas. Counties with less concentrated poverty, less income inequality, better schools, a larger share of two-parent families, and lower crime rates tend to produce better outcomes for children in poor families. Boys’ outcomes vary more across areas than girls’ outcomes, and boys have especially negative outcomes in highly segregated areas. Areas that generate better outcomes have higher house prices on average, but our approach uncovers many “opportunity bargains”—places that generate good outcomes but are not very expensive.
We organized business associations for the owner-managers of young Chinese firms to study the effect of business networks on firm performance. We randomized 2,820 firms into small groups whose managers held monthly meetings for one year, and into a “no-meetings” control group. We find the following. (i) The meetings increased firm revenue by 8.1%, and also significantly increased profit, factors, inputs, the number of partners, borrowing, and a management score. (ii) These effects persisted one year after the conclusion of the meetings. (iii) Firms randomized to have better peers exhibited higher growth. We exploit additional interventions to document concrete channels. (iv) Managers shared exogenous business-relevant information, particularly when they were not competitors, showing that the meetings facilitated learning from peers. (v) Managers created more business partnerships in the regular than in other one-time meetings, showing that the meetings improved supplier-client matching.
We present estimates of monetary non-neutrality based on evidence from high-frequency responses of real interest rates, expected inflation, and expected output growth. Our identifying assumption is that unexpected changes in interest rates in a 30-minute window surrounding scheduled Federal Reserve announcements arise from news about monetary policy. In response to an interest rate hike, nominal and real interest rates increase roughly one-for-one, several years out into the term structure, while the response of expected inflation is small. At the same time, forecasts about output growth also increase—the opposite of what standard models imply about a monetary tightening. To explain these facts, we build a model in which Fed announcements affect beliefs not only about monetary policy but also about other economic fundamentals. Our model implies that these information effects play an important role in the overall causal effect of monetary policy shocks on output.
This article estimates workers’ preferences for firms by studying the structure of employer-to-employer transitions in U.S. administrative data. The article uses a tool from numerical linear algebra to measure the central tendency of worker flows, which is closely related to the ranking of firms revealed by workers’ choices. There is evidence for compensating differentials when workers systematically move to lower-paying firms in a way that cannot be accounted for by layoffs or differences in recruiting intensity. The estimates suggest that compensating differentials account for over half of the firm component of the variance of earnings.
We study the impact of international long-distance flights on the global spatial allocation of economic activity. To identify causal effects, we exploit variation due to regulatory and technological constraints, which gives rise to a discontinuity in connectedness between cities at a distance of 6,000 miles. We show that improving an airport’s position in the network of air links has a positive effect on local economic activity, as captured by satellite-measured night lights. We find that air links increase business links, showing that the movement of people fosters the movement of capital. In particular, this is driven mostly by capital flowing from high-income to middle-income (but not low-income) countries. Taken together, the results suggest that increasing interconnectedness induces links between businesses and generates economic activity at the local level but also gives rise to increased spatial inequality locally, and potentially globally.
We present new evidence on the evolution of black–white earnings differences among all men, including both workers and nonworkers. We study two measures: (i) the level earnings gap—the racial earnings difference at a given quantile; and (ii) the earnings rank gap—the difference between a black man's percentile in the black earnings distribution and the position he would hold in the white earnings distribution. After narrowing from 1940 to the mid-1970s, the median black–white level earnings gap has since grown as large as it was in 1950. At the same time, the median black man's relative position in the earnings distribution has remained essentially constant since 1940, so that the improvement then worsening of median relative earnings have come mainly from the stretching and narrowing of the overall earnings distribution. Black men at higher percentiles have experienced significant advances in relative earnings since 1940, due mainly to strong positional gains among those with college educations. Large relative schooling gains by blacks at the median and below have been more than counteracted by rising return to skill in the labor market, which has increasingly penalized remaining racial differences in schooling at the bottom of the distribution.
We document the portfolio activity of federal housing agencies and provide evidence on its impact on mortgage markets and the economy. Through a narrative analysis, we identify historical policy changes leading to expansions or contractions in agency mortgage holdings. Based on those regulatory events that we classify as unrelated to short-run cyclical or credit market shocks, we find that an increase in mortgage purchases by the agencies boosts mortgage lending, in particular refinancing, and lowers mortgage rates. Agency purchases also influence prices in other asset markets, stimulate residential investment, and expand homeownership. We compare these effects to those of conventional monetary policy shocks, and we provide evidence on the interactions between housing credit and monetary policies.
This article provides field-experimental evidence on status goods. We work with an Indonesian bank that markets platinum credit cards to high-income customers. In a first experiment, we show that demand for the platinum card exceeds demand for a nondescript control product with identical benefits, suggesting demand for the pure status aspect of the card. Transaction data reveal that platinum cards are more likely to be used in social contexts, implying social image motivations. In a second experiment, we provide evidence of positional externalities from the consumption of these status goods. A final experiment provides suggestive evidence that increasing self-esteem causally reduces demand for status goods, indicating that social image might be a substitute for self-image.
A growing number of policies and programs aim to increase investment in energy efficiency, because conventional wisdom suggests that people fail to take up these investments even though they have positive private returns and generate environmental benefits. Many explanations for this energy efficiency gap have been put forward, but there has been surprisingly little field testing of whether the conventional wisdom is correct. This article reports on the results of an experimental evaluation of the nation’s largest residential energy efficiency program—the Weatherization Assistance Program—conducted on a sample of approximately 30,000 households in Michigan. The findings suggest that the upfront investment costs are about twice the actual energy savings. Furthermore, the model-projected savings are more than three times the actual savings. Although this might be attributed to the “rebound” effect—when demand for energy end uses increases as a result of greater efficiency—the article fails to find evidence of significantly higher indoor temperatures at weatherized homes. Even when accounting for the broader societal benefits derived from emissions reductions, the costs still substantially outweigh the benefits; the average rate of return is approximately −7.8% annually.
This article studies the global variation in economic preferences. For this purpose, we present the Global Preference Survey (GPS), an experimentally validated survey data set of time preference, risk preference, positive and negative reciprocity, altruism, and trust from 80,000 people in 76 countries. The data reveal substantial heterogeneity in preferences across countries, but even larger within-country heterogeneity. Across individuals, preferences vary with age, gender, and cognitive ability, yet these relationships appear partly country specific. At the country level, the data reveal correlations between preferences and biogeographic and cultural variables, such as agricultural suitability, language structure, and religion. Variation in preferences is also correlated with economic outcomes and behaviors. Within countries and subnational regions, preferences are linked to individual savings decisions, labor market choices, and prosocial behaviors. Across countries, preferences vary with aggregate outcomes ranging from per capita income, to entrepreneurial activities, to the frequency of armed conflicts.
Using new transaction data, I find considerable deviations from consumption smoothing in response to large, regular, predetermined, and salient payments from the Alaska Permanent Fund. On average, the marginal propensity to consume (MPC) is 25% for nondurables and services within one quarter of the payments. The MPC is heterogeneous, monotonically increasing with income, and the average is largely driven by high-income households with substantial amounts of liquid assets, who have MPCs above 50%. The account-level data and the properties of the payments rule out most previous explanations of excess sensitivity, including buffer stock models and rational inattention. How big are these “mistakes?” Using a sufficient statistics approach, I show that the welfare loss from excess sensitivity depends on the MPC and the relative payment size as a fraction of income. Since the lump-sum payments do not depend on income, the two statistics are negatively correlated such that the welfare losses are similar across households and small (less than 0.1% of wealth), despite the large MPCs.
Much of the variation in international trade volume is driven by firms’ extensive margin decisions of whether to participate in export markets. We evaluate how the information potential exporters possess influences their decisions. We estimate a model of export participation in which firms weigh the fixed costs of exporting against the forecasted profits from serving a foreign market. We adopt a moment inequality approach, placing weak assumptions on firms’ expectations. The framework allows us to test whether firms differ in the information they have about foreign markets. We find that larger firms possess better knowledge of market conditions in foreign countries, even when those firms have not exported in the past. Quantifying the value of information, we show that, in a typical destination, total exports rise while the number of exporters falls when firms have access to better information to forecast export revenues.
Using new narrative measures of exogenous variation in marginal tax rates associated with postwar tax reforms in the United States, this study estimates short-run tax elasticities of reported income of around 1.2 based on time series from 1946 to 2012. Estimated elasticities are larger in the top 1% of the income distribution but are also positive and statistically significant for other income groups. Previous time series studies of tax returns data have found little evidence for income responses to taxes outside the top of the income distribution. The different results in this article arise because of additional efforts to account for dynamics, expectations, and especially the endogeneity of tax policy decisions. Marginal rate cuts lead to increases in real GDP and declines in unemployment. There is also evidence that the responses are to marginal tax rates rather than average tax rates. Counterfactual tax cuts targeting the top 1% alone are estimated to have short-run positive effects on economic activity and incomes outside of the top 1%, but to increase inequality in pretax incomes. Cuts for taxpayers outside of the top 1% also lead to increases in incomes and economic activity, but with a longer delay.
This article develops a new test for identifying racial bias in the context of bail decisions—a high-stakes setting with large disparities between white and black defendants. We motivate our analysis using Becker’s model of racial bias, which predicts that rates of pretrial misconduct will be identical for marginal white and marginal black defendants if bail judges are racially unbiased. In contrast, marginal white defendants will have higher rates of misconduct than marginal black defendants if bail judges are racially biased, whether that bias is driven by racial animus, inaccurate racial stereotypes, or any other form of bias. To test the model, we use the release tendencies of quasi-randomly assigned bail judges to identify the relevant race-specific misconduct rates. Estimates from Miami and Philadelphia show that bail judges are racially biased against black defendants, with substantially more racial bias among both inexperienced and part-time judges. We find suggestive evidence that this racial bias is driven by bail judges relying on inaccurate stereotypes that exaggerate the relative danger of releasing black defendants.
A key policy question is: how high an inflation rate should central banks target? This depends crucially on the costs of inflation. An important concern is that high inflation will lead to inefficient price dispersion. Workhorse New Keynesian models imply that this cost of inflation is very large. An increase in steady-state inflation from 0% to 10% yields a welfare loss that is an order of magnitude greater than the welfare loss from business cycle fluctuations in output in these models. We assess this prediction empirically using a new data set on price behavior during the Great Inflation of the late 1970s and early 1980s in the United States. If price dispersion increases rapidly with inflation, we should see the absolute size of price changes increasing with inflation: price changes should become larger as prices drift further from their optimal level at higher inflation rates. We find no evidence that the absolute size of price changes rose during the Great Inflation. This suggests that the standard New Keynesian analysis of the welfare costs of inflation is wrong and its implications for the optimal inflation rate need to be reassessed. We also find that (nonsale) prices have not become more flexible over the past 40 years.
We study the persuasive effects of political advertising. Our empirical strategy exploits FCC regulations that result in plausibly exogenous variation in the number of impressions across the borders of neighboring counties. Applying this approach to detailed data on television advertisement broadcasts and viewership patterns during the 2004–12 presidential campaigns, our results indicate that total political advertising has almost no impact on aggregate turnout. By contrast, we find a positive and economically meaningful effect of advertising on candidates’ vote shares. Taken at face value, our estimates imply that a one standard deviation increase in the partisan difference in advertising raises the partisan difference in vote shares by about 0.5 percentage points. Evidence from a regression discontinuity design suggests that advertising affects election results by altering the partisan composition of the electorate.
Using novel microdata, we document an important, unintended consequence of the Protestant Reformation: a reallocation of resources from religious to secular purposes. To understand this process, we propose a conceptual framework in which the introduction of religious competition shifts political markets where religious authorities provide legitimacy to rulers in exchange for control over resources. Consistent with our framework, religious competition changed the balance of power between secular and religious elites: secular authorities acquired enormous amounts of wealth from monasteries closed during the Reformation, particularly in Protestant regions. This transfer of resources had significant consequences. First, it shifted the allocation of upper-tail human capital. Graduates of Protestant universities increasingly took secular, especially administrative, occupations. Protestant university students increasingly studied secular subjects, especially degrees that prepared students for public sector jobs, rather than church sector specific theology. Second, it affected the sectoral composition of fixed investment. Particularly in Protestant regions, new construction shifted from religious toward secular purposes, especially the building of palaces and administrative buildings, which reflected the increased wealth and power of secular lords. Reallocation was not driven by preexisting economic or cultural differences. Our findings indicate that the Reformation played an important causal role in the secularization of the West.
Firms often sell a basic good as well as ancillary ones. Hold-up concerns have led to ancillary good regulations, such as transparency and price caps. The hold-up narrative, however, runs counter to evidence in many retail settings where ancillary good prices are set below cost (e.g., free shipping or limited card surcharging in countries where the “no-surcharge rule” was lifted). We argue that the key to unifying these conflicting narratives is that the seller may absorb partly or fully the ancillary good’s cost so as not to miss sales on the basic good. A supplier with market power on the ancillary good market then takes advantage of cost absorption and jacks up its wholesale price. Hold-ups occur only when consumers are initially uninformed or naive about the drip price and shopping costs are high. The price of the basic good then acts as a signal of the drip price, since a high markup on the basic good makes the firm more wary of missed sales. Regardless of whether consumers are informed, uninformed but rational, or naive, mandating price transparency and banning loss-making on the ancillary good leads to (i) an efficient consumption of the ancillary good, and (ii) a reduction of its wholesale price, generating strict welfare gains.
To answer the question in the title, this article characterizes the socially efficient organization of the market with search frictions. The efficient organization depends on the relative elasticity in the supply between the two sides of the market, the costs of participating in the market and organizing trade, and the (a)symmetry in matching. We also show that the social optimum can be implemented by a realistic market equilibrium where the organizers set up trading sites to direct the other side’s search. The results provide a unified explanation for why trade has often been organized by sellers in the goods market, by buyers (firms) in the labor market, and by both sides in the asset market. The analysis also sheds light on how the efficient market organization can change with innovations such as e-commerce and just-in-time production.
We use a massive, matched employer-employee database for the United States to analyze the contribution of firms to the rise in earnings inequality from 1978 to 2013. We find that one-third of the rise in the variance of (log) earnings occurred within firms, whereas two-thirds of the rise occurred due to a rise in the dispersion of average earnings between firms. However, this rising between-firm variance is not accounted for by the firms themselves but by a widening gap between firms in the composition of their workers. This compositional change can be split into two roughly equal parts: high-wage workers became increasingly likely to work in high-wage firms (i.e., sorting increased), and high-wage workers became increasingly likely to work with each other (i.e., segregation rose). In contrast, we do not find a rise in the variance of firm-specific pay once we control for the worker composition in firms. Finally, we find that two-thirds of the rise in the within-firm variance of earnings occurred within mega (10,000+ employee) firms, which saw a particularly large increase in the variance of earnings compared with smaller firms.
We use insurance claims data covering 28% of individuals with employer-sponsored health insurance in the United States to study the variation in health spending on the privately insured, examine the structure of insurer-hospital contracts, and analyze the variation in hospital prices across the nation. Health spending per privately insured beneficiary differs by a factor of three across geographic areas and has a very low correlation with Medicare spending. For the privately insured, half of the spending variation is driven by price variation across regions, and half is driven by quantity variation. Prices vary substantially across regions, across hospitals within regions, and even within hospitals. For example, even for a nearly homogeneous service such as lower-limb magnetic resonance imaging, about a fifth of the total case-level price variation occurs within a hospital in the cross section. Hospital market structure is strongly associated with price levels and contract structure. Prices at monopoly hospitals are 12% higher than those in markets with four or more rivals. Monopoly hospitals also have contracts that load more risk on insurers (e.g., they have more cases with prices set as a share of their charges). In concentrated insurer markets the opposite occurs—hospitals have lower prices and bear more financial risk. Examining the 366 mergers and acquisitions that occurred between 2007 and 2011, we find that prices increased by over 6% when the merging hospitals were geographically close (e.g., 5 miles or less apart), but not when the hospitals were geographically distant (e.g., over 25 miles apart).
We argue that the time-varying regional distribution of housing equity influences the aggregate consequences of monetary policy through its effects on mortgage refinancing. Using detailed loan-level data, we show that regional differences in housing equity affect refinancing and spending responses to interest rate cuts, but these effects vary over time with changes in the regional distribution of house price growth. We build a heterogeneous household model of refinancing with mortgage borrowers and lenders and use it to explore the monetary policy implications arising from our regional evidence. We find that the 2008 equity distribution made spending in depressed regions less responsive to interest rate cuts, thus dampening aggregate stimulus and increasing regional consumption inequality, whereas the opposite occurred in some earlier recessions. Taken together, our results strongly suggest that monetary policy makers should track the regional distribution of equity over time.
Using data on over a million land transactions during 2004–2016 where local governments are the sole seller, we find that firms linked to members of China's supreme political elites—the Politburo—obtained a price discount ranging from 55.4% to 59.9% compared with those without the same connections. These firms also purchased slightly more land. In return, the provincial party secretaries who provided the discount to these “princeling” firms are 23.4% more likely to be promoted to positions of national leadership. To curb corruption, President Xi Jinping stepped up investigations and strengthened personnel control at the province level. Using a spatially matched sample (e.g., within a 500-meter radius), we find a reduction in corruption of between 42.6% and 31.5% in the provinces either targeted by the central inspection teams or whose party secretary was replaced by one appointed by Xi. Accordingly, this crackdown on corruption has also significantly reduced the promotional prospects of those local officials who rely on supplying a discount to get ahead.
By how much does an extension of unemployment benefits affect macroeconomic outcomes such as unemployment? Answering this question is challenging because U.S. law extends benefits for states experiencing high unemployment. We use data revisions to decompose the variation in the duration of benefits into the part coming from actual differences in economic conditions and the part coming from measurement error in the real-time data used to determine benefit extensions. Using only the variation coming from measurement error, we find that benefit extensions have a limited influence on state-level macroeconomic outcomes. We apply our estimates to the increase in the duration of benefits during the Great Recession and find that they increased the unemployment rate by at most 0.3 percentage point.
Agricultural productivity is particularly low in developing countries. Output-sharing rules that make farmers less-than-full residual claimants are seen as a potentially important driver of low agricultural productivity. We report results from a field experiment designed to estimate and understand the effects of sharecropping contracts on agricultural input choices, risk-taking, and output. The experiment induced variation in the terms of sharecropping contracts. After agreeing to pay 50% of their output to the landlord, tenants were randomized into three groups: (i) some kept 50% of their output; (ii) others kept 75%; (iii) others kept 50% of output and received a lump-sum payment at the end of their contract, either fixed or stochastic. We find that tenants with higher output shares used more inputs, cultivated riskier crops, and produced 60% more output relative to control. Income or risk exposure have at most a small effect on farm output; the increase in output should be interpreted as an incentive effect of the output-sharing rule.
Since the 1972 U.S. Clean Water Act, government and industry have invested over |${\$}$|1 trillion to abate water pollution, or |${\$}$|100 per person-year. Over half of U.S. stream and river miles, however, still violate pollution standards. We use the most comprehensive set of files ever compiled on water pollution and its determinants, including 50 million pollution readings from 240,000 monitoring sites and a network model of all U.S. rivers, to study water pollution’s trends, causes, and welfare consequences. We have three main findings. First, water pollution concentrations have fallen substantially. Between 1972 and 2001, for example, the share of waters safe for fishing grew by 12 percentage points. Second, the Clean Water Act’s grants to municipal wastewater treatment plants, which account for |${\$}$|650 billion in expenditure, caused some of these declines. Through these grants, it cost around |${\$}$|1.5 million (2014 dollars) to make one river-mile fishable for a year. We find little displacement of municipal expenditure due to a federal grant. Third, the grants’ estimated effects on housing values are smaller than the grants’ costs; we carefully discuss welfare implications.
Separate literatures study violations of uncovered interest parity (UIP) using regression-based and portfolio-based methods. We propose a decomposition of these violations into a cross-currency, a between-time-and-currency, and a cross-time component that allows us to analytically relate regression-based and portfolio-based facts and to estimate the joint restrictions they put on models of currency returns. Subject to standard assumptions on investors’ information sets, we find that the forward premium puzzle (FPP) and the “dollar trade” anomaly are intimately linked: both are driven almost exclusively by the cross-time component. By contrast, the “carry trade” anomaly is driven largely by cross-sectional violations of UIP. The simplest model that the data do not reject features a cross-sectional asymmetry that makes some currencies pay permanently higher expected returns than others, and larger time series variation in expected returns on the U.S. dollar than on other currencies. Importantly, conventional estimates of the FPP are not directly informative about expected returns because they do not correct for uncertainty about future mean interest rates. Once we correct for this uncertainty, we never reject the null that investors expect high-interest-rate currencies to depreciate, not appreciate.
In this article, we analyze how inflation affects firms’ price-setting behavior. For a class of menu cost models, we derive several predictions about how price-setting changes with inflation at very high and at near-zero inflation rates. Then, we present evidence supporting these predictions using product-level data underlying Argentina’s consumer price index from 1988 to 1997—a unique experience where monthly inflation ranged from almost 200% to less than zero. For low inflation rates, we find that (i) the frequency and absolute size of price changes as well as the dispersion of relative prices do not change with inflation, (ii) the frequency and size of price increases and decreases are symmetric around zero inflation, and (iii) aggregate inflation changes are mostly driven by changes in the frequency of price increases and decreases, as opposed to the size of price changes. For high inflation rates, we find that (iv) the elasticity of the frequency of price changes with respect to inflation is close to two-thirds, (v) the frequency of price changes across different products becomes similar, and (vi) the elasticity of the dispersion of relative prices with respect to inflation is one-third. Our findings confirm and extend available evidence for countries that experienced either very high or near-zero inflation. We conclude by showing that a hyperinflation of 500% a year is associated with a cost of approximately 8.5% of aggregate output a year as a result of inefficient price dispersion alone.
This article examines the long-term consequences of a historical human capital intervention. The Jesuit order founded religious missions in 1609 among the Guaraní, in modern-day Argentina, Brazil, and Paraguay. Before their expulsion in 1767, missionaries instructed indigenous inhabitants in reading, writing, and various crafts. Using archival records, as well as data at the individual and municipal level, I show that in areas of former Jesuit presence—within the Guaraní area—educational attainment was higher and remains so (by 10%–15%) 250 years later. These educational differences have also translated into incomes that are 10% higher today. The identification of the positive effect of the Guaraní Jesuit missions emerges after comparing them with abandoned Jesuit missions and neighboring Franciscan Guaraní missions. The enduring effects observed are consistent with transmission mechanisms of structural transformation, occupational specialization, and technology adoption in agriculture.
I follow R. A. Fisher's,The Design of Experiments (1935), using randomization statistical inference to test the null hypothesis of no treatment effects in a comprehensive sample of 53 experimental papers drawn from the journals of the American Economic Association. In the average paper, randomization tests of the significance of individual treatment effects find 13% to 22% fewer significant results than are found using authors’ methods. In joint tests of multiple treatment effects appearing together in tables, randomization tests yield 33% to 49% fewer statistically significant results than conventional tests. Bootstrap and jackknife methods support and confirm the randomization results.
This article provides a comprehensive history of anchor or reference currencies, exchange rate arrangements, and a new measure of foreign exchange restrictions for 194 countries and territories over 1946–2016. We find that the often cited post–Bretton Woods transition from fixed to flexible arrangements is overstated; regimes with limited flexibility remain in the majority. Even if central bankers’ communications jargon has evolved considerably in recent decades, it is apparent that many still place a large implicit weight on the exchange rate. The U.S. dollar scores as the world's dominant anchor currency by a very large margin. By some metrics, its use is far wider today than 70 years ago. In contrast, the global role of the euro appears to have stalled. We argue that in addition to the usual safe assets story, the record accumulation of reserves since 2002 may also have to do with many countries’ desire to stabilize exchange rates in an environment of markedly reduced exchange rate restrictions or, more broadly, capital controls: an important amendment to the conventional portrayal of the macroeconomic trilemma.
This article examines how product innovations led to inflation inequality in the United States from 2004 to 2015. Using scanner data from the retail sector, I find that annual inflation for retail products was 0.661 (std. err. 0.0535) percentage points higher for the bottom income quintile relative to the top income quintile. When including changes in product variety over time, this difference increases to 0.8846 (std. err. 0.0739) percentage points a year. In CEX-CPI data covering the full consumption basket, the annual inflation difference is 0.368 (std. err. 0.0502) percentage points. I investigate the following hypothesis: (i) the relative demand for products consumed by high-income households increased because of growth and rising inequality; (ii) in response, firms introduced more new products catering to such households; (iii) as a result, the prices of continuing products in these market segments fell due to increased competitive pressure. Using a shift-share research design, I find causal evidence that increasing relative demand leads to increasing product variety and lower inflation for continuing products. A calibration indicates that the hypothesized channel accounts for a large fraction (over 50%) of observed inflation inequality.
Large and regular seasonal price fluctuations in local grain markets appear to offer African farmers substantial intertemporal arbitrage opportunities, but these opportunities remain largely unexploited. Small-scale farmers are commonly observed to “sell low and buy high,” rather than the reverse. In a field experiment in Kenya, we show that credit market imperfections limit farmers’ abilities to move grain intertemporally. Providing timely access to credit allows farmers to buy at lower prices and sell at higher prices, increasing farm revenues and generating a return on investment of 29%. To understand general equilibrium (GE) effects of these changes in behavior, we vary the density of loan offers across locations. We document significant effects of the credit intervention on seasonal price fluctuations in local grain markets, and show that these GE effects shape individual-level profitability estimates. In contrast to existing experimental work, the results indicate a setting in which microcredit can improve firm profitability, and suggest that GE effects can substantially shape microcredit’s effectiveness. In particular, failure to consider these GE effects could lead to underestimates of the social welfare benefits of microcredit interventions.
The home-market effect, first hypothesized by Linder (1961) and later formalized by Krugman (1980), is the idea that countries with larger demand for some products at home tend to have larger sales of the same products abroad. In this article, we develop a simple test of the home-market effect using detailed drug sales data from the global pharmaceutical industry. The core of our empirical strategy is the observation that a country’s exogenous demographic composition can be used as a predictor of the diseases that its inhabitants are most likely to die from and, in turn, the drugs they are most likely to demand. We find that the correlation between predicted home demand and sales abroad is positive and greater than the correlation between predicted home demand and purchases from abroad. In short, countries tend to be net sellers of the drugs they demand the most, as predicted by Linder (1961) and Krugman (1980).
This article studies strategic default on forward sale contracts in the international coffee market. To test for strategic default, we construct contract-specific measures of unanticipated changes in market conditions by comparing spot prices at maturity with the relevant futures prices at the contracting date. Unanticipated rises in market prices increase defaults on fixed-price contracts but not on price-indexed ones. We isolate strategic default by focusing on unanticipated rises at the time of delivery after production decisions are sunk and suppliers have been paid. Estimates suggest that roughly half of the observed defaults are strategic. We model how strategic default introduces a trade-off between insurance and counterparty risk: relative to indexed contracts, fixed-price contracts insure against price swings but create incentives to default when market conditions change. A model calibration suggests that the possibility of strategic default causes 15.8% average losses in output, significant dispersion in the marginal product of capital, and sizable negative externalities on supplying farmers.
Across the social sciences, a key question is how societies manage to enforce cooperative behavior in social dilemmas such as public goods provision or bilateral trade. According to an influential body of theories in psychology, anthropology, and evolutionary biology, the answer is that humans have evolved moral systems: packages of functional psychological and biological mechanisms that regulate economic behavior, including a belief in moralizing gods; moral values; negative reciprocity; and emotions of shame, guilt, and disgust. Based on a stylized model, this article empirically studies the structure and evolution of these moral traits as a function of historical heterogeneity in extended kinship relationships. The evidence shows that societies with a historically tightly knit kinship structure regulate behavior through communal moral values, revenge taking, emotions of external shame, and notions of purity and disgust. In loose kinship societies, on the other hand, cooperation appears to be enforced through universal moral values, internalized guilt, altruistic punishment, and an apparent rise and fall of moralizing religions. These patterns point to the presence of internally consistent but culturally variable functional moral systems. Consistent with the model, the relationship between kinship ties, economic development, and the structure of the mediating moral systems amplified over time.
Social scientists have long viewed the decision to protest as strategic, with an individual's participation a function of their beliefs about others’ turnout. We conduct a framed field experiment that recalibrates individuals’ beliefs about others’ protest participation, in the context of Hong Kong's ongoing antiauthoritarian movement. We elicit subjects’ planned participation in an upcoming protest and their prior beliefs about others’ participation, in an incentivized manner. One day before the protest, we randomly provide a subset of subjects with truthful information about others’ protest plans and elicit posterior beliefs about protest turnout, again in an incentivized manner. After the protest, we elicit subjects’ actual participation. This allows us to identify the causal effects of positively and negatively updated beliefs about others’ protest participation on subjects’ own turnout. In contrast with the assumptions of many recent models of protest participation, we consistently find evidence of strategic substitutability. We provide guidance regarding plausible sources of strategic substitutability that can be incorporated into theoretical models of protests.
Using the Consumption Activities Mail Survey (CAMS) module in the HRS, we document how individual time allocations change when one or more household members transitions from full-time work to not working. We find that the ratio of home production to leisure time is approximately constant for both family members. Using a model of household labor supply to understand the implications of this finding, we conclude that the elasticity of substitution between the leisure of the two members is quite large. This elasticity plays a key role in models of household labor supply and is important for understanding how changes in relative wages and taxes affect household labor supply.
We show that grit, a skill that has been shown to be highly predictive of achievement, is malleable in childhood and can be fostered in the classroom environment. We evaluate a randomized educational intervention implemented in two independent elementary school samples. Outcomes are measured via a novel incentivized real-effort task and performance in standardized tests. We find that treated students are more likely to exert effort to accumulate task-specific ability and hence more likely to succeed. In a follow up 2.5 years after the intervention, we estimate an effect of about 0.2 standard deviations on a standardized math test.
I study whether exposure to teacher stereotypes, as measured by the Gender-Science Implicit Association Test, affects student achievement. I provide evidence that the gender gap in math performance, defined as the score of boys minus the score of girls in standardized tests, substantially increases when students are assigned to math teachers with stronger gender stereotypes. Teacher stereotypes induce girls to underperform in math and self-select into less demanding high schools, following the track recommendation of their teachers. These effects are at least partially driven by lower self-confidence on math ability of girls exposed to gender-biased teachers. Stereotypes impair the test performance of girls, who end up failing to achieve their full potential. I do not detect statistically significant effects on student outcomes of literature teacher stereotypes.
What is the aggregate real rate of return in the economy? Is it higher than the growth rate of the economy and, if so, by how much? Is there a tendency for returns to fall in the long run? Which particular assets have the highest long-run returns? We answer these questions on the basis of a new and comprehensive data set for all major asset classes, including housing. The annual data on total returns for equity, housing, bonds, and bills cover 16 advanced economies from 1870 to 2015, and our new evidence reveals many new findings and puzzles.
In setting prices for physician services, Medicare solicits input from a committee that evaluates proposals from industry. The committee itself comprises members from industry; we investigate whether this arrangement leads to regulatory capture with prices biased toward industry interests. We find that increasing a measure of affiliation between the committee and proposers by one standard deviation increases prices by 10%. We then evaluate whether employing a biased committee as an intermediary may nonetheless be desirable, if greater affiliation allows the committee to extract information needed for regulation. We find industry proposers more affiliated with the committee produce less hard evidence in their proposals. However, on soft information, we find evidence of a trade-off: private insurers set prices that more closely track Medicare prices generated under higher affiliation.
This article analyzes how patent-induced shocks to labor productivity propagate into worker compensation using a new linkage of U.S. patent applications to U.S. business and worker tax records. We infer the causal effects of patent allowances by comparing firms whose patent applications were initially allowed to those whose patent applications were initially rejected. To identify patents that are ex ante valuable, we extrapolate the excess stock return estimates of Kogan et al. (2017) to the full set of accepted and rejected patent applications based on predetermined firm and patent application characteristics. An initial allowance of an ex ante valuable patent generates substantial increases in firm productivity and worker compensation. By contrast, initial allowances of lower ex ante value patents yield no detectable effects on firm outcomes. Patent allowances lead firms to increase employment, but entry wages and workforce composition are insensitive to patent decisions. On average, workers capture roughly 30 cents of every dollar of patent-induced surplus in higher earnings. This share is roughly twice as high among workers present since the year of application. These earnings effects are concentrated among men and workers in the top half of the earnings distribution and are paired with corresponding improvements in worker retention among these groups. We interpret these earnings responses as reflecting the capture of economic rents by senior workers, who are most costly for innovative firms to replace.
We estimate the effect of minimum wages on low-wage jobs using 138 prominent state-level minimum wage changes between 1979 and 2016 in the United States using a difference-in-differences approach. We first estimate the effect of the minimum wage increase on employment changes by wage bins throughout the hourly wage distribution. We then focus on the bottom part of the wage distribution and compare the number of excess jobs paying at or slightly above the new minimum wage to the missing jobs paying below it to infer the employment effect. We find that the overall number of low-wage jobs remained essentially unchanged over the five years following the increase. At the same time, the direct effect of the minimum wage on average earnings was amplified by modest wage spillovers at the bottom of the wage distribution. Our estimates by detailed demographic groups show that the lack of job loss is not explained by labor-labor substitution at the bottom of the wage distribution. We also find no evidence of disemployment when we consider higher levels of minimum wages. However, we do find some evidence of reduced employment in tradeable sectors. We also show how decomposing the overall employment effect by wage bins allows a transparent way of assessing the plausibility of estimates.
We analyze a large data set of commercial records produced by Assyrian merchants in the nineteenth century BCE. Using the information from these records, we estimate a structural gravity model of long-distance trade in the Bronze Age. We use our structural gravity model to locate lost ancient cities. In many cases, our estimates confirm the conjectures of historians who follow different methodologies. In some instances, our estimates confirm one conjecture against others. We also structurally estimate ancient city sizes and offer evidence in support of the hypothesis that large cities tend to emerge at the intersections of natural transport routes, as dictated by topography. Finally, we document persistent patterns in the distribution of city sizes across four millennia, find a distance elasticity of trade in the Bronze Age close to modern estimates, and show suggestive evidence that the distribution of ancient city sizes, inferred from trade data, is well approximated by Zipf’s law.
We develop a framework for welfare analysis of interventions designed to increase take-up of social safety net programs in the presence of potential behavioral biases. We calibrate the key parameters using a randomized field experiment in which 30,000 elderly individuals not enrolled in—but likely eligible for—the Supplemental Nutrition Assistance Program (SNAP) are either provided with information that they are likely eligible, provided with this information and offered assistance in applying, or are in a “status quo” control group. Only 6% of the control group enrolls in SNAP over the next nine months, compared to 11% of the Information Only group and 18% of the Information Plus Assistance group. The individuals who apply or enroll in response to either intervention have higher net income and are less sick than the average enrollee in the control group. We present evidence consistent with the existence of optimization frictions that are greater for needier individuals, which suggests that the poor targeting properties of the interventions reduce their welfare benefits.
A common objection to “sin taxes”—corrective taxes on goods that are thought to be overconsumed, such as cigarettes, alcohol, and sugary drinks—is that they often fall disproportionately on low-income consumers. This paper studies the interaction between corrective and redistributive motives in a general optimal taxation framework and delivers empirically implementable formulas for sufficient statistics for the optimal commodity tax. The optimal sin tax is increasing in the price elasticity of demand, increasing in the degree to which lower-income consumers are more biased or more elastic to the tax, decreasing in the extent to which consumption is concentrated among the poor, and decreasing in income effects, because income effects imply that commodity taxes create labor supply distortions. Contrary to common intuitions, stronger preferences for redistribution can increase the optimal sin tax, if lower-income consumers are more responsive to taxes or are more biased. As an application, we estimate the optimal nationwide tax on sugar-sweetened beverages, using Nielsen Homescan data and a specially designed survey measuring nutrition knowledge and self-control. Holding federal income tax rates constant, our estimates imply an optimal federal sugar-sweetened beverage tax of 1 to 2.1 cents per ounce, although optimal city-level taxes could be as much as 60% lower due to cross-border shopping.
We present results from a large-scale randomized experiment across 350 schools in Tanzania that studied the impact of providing schools with (i) unconditional grants, (ii) teacher incentives based on student performance, and (iii) both of the above. After two years, we find (i) no impact on student test scores from providing school grants, (ii) some evidence of positive effects from teacher incentives, and (iii) significant positive effects from providing both programs. Most important, we find strong evidence of complementarities between the programs, with the effect of joint provision being significantly greater than the sum of the individual effects. Our results suggest that combining spending on school inputs (the default policy) with improved teacher incentives could substantially increase the cost-effectiveness of public spending on education.
How important is human capital at the top of the U.S. income distribution? A primary source of top income is private “pass-through” business profit, which can include entrepreneurial labor income for tax reasons. This article asks whether top pass-through profit mostly reflects human capital, defined as all inalienable factors embodied in business owners, rather than financial capital. Tax data linking 11 million firms to their owners show that top pass-through profit accrues to working-age owners of closely held mid-market firms in skill-intensive industries. Pass-through profit falls by three-quarters after owner retirement or premature death. Classifying three-quarters of pass-through profit as human capital income, we find that the typical top earner derives most of her income from human capital, not financial capital. Growth in pass-through profit is explained by both rising productivity and a rising share of value added accruing to owners.
Workplace wellness programs cover over 50 million U.S. workers and are intended to reduce medical spending, increase productivity, and improve well-being. Yet limited evidence exists to support these claims. We designed and implemented a comprehensive workplace wellness program for a large employer and randomly assigned program eligibility and financial incentives at the individual level for nearly 5,000 employees. We find strong patterns of selection: during the year prior to the intervention, program participants had lower medical expenditures and healthier behaviors than nonparticipants. The program persistently increased health screening rates, but we do not find significant causal effects of treatment on total medical expenditures, other health behaviors, employee productivity, or self-reported health status after more than two years. Our 95% confidence intervals rule out 84% of previous estimates on medical spending and absenteeism.
We study the causes of “nutritional inequality”: why the wealthy eat more healthfully than the poor in the United States. Exploiting supermarket entry and household moves to healthier neighborhoods, we reject that neighborhood environments contribute meaningfully to nutritional inequality. We then estimate a structural model of grocery demand, using a new instrument exploiting the combination of grocery retail chains’ differing presence across geographic markets with their differing comparative advantages across product groups. Counterfactual simulations show that exposing low-income households to the same products and prices available to high-income households reduces nutritional inequality by only about 10%, while the remaining 90% is driven by differences in demand. These findings counter the argument that policies to increase the supply of healthy groceries could play an important role in reducing nutritional inequality.
We examine the within- and across-firm shipment decisions of tens of thousands of goods-producing and goods-distributing establishments. This allows us to quantify the normally unobservable forces that determine firm boundaries, that is, which transactions are mediated by ownership control, as opposed to contracts or markets. We find firm boundaries to be an economically significant barrier to trade: having an additional vertically integrated establishment in a given destination ZIP code has the same effect on shipment volumes as a 40% reduction in distance. These effects are larger for high value-to-weight products, faraway destinations, differentiated products, and IT-intensive industries.
Many developing economies adopt industrial policies favoring selected sectors. Is there an economic logic to this type of intervention? I analyze industrial policy when economic sectors form a production network via input-output linkages. Market imperfections generate distortionary effects that compound through backward demand linkages, causing upstream sectors to become the sink for imperfections and have the greatest size distortions. My key finding is that the distortion in sectoral size is a sufficient statistic for the social value of promoting that sector; thus, there is an incentive for a well-meaning government to subsidize upstream sectors. Furthermore, sectoral interventions’ aggregate effects can be simply summarized, to first order, by the cross-sector covariance between my sufficient statistic and subsidy spending. My sufficient statistic predicts sectoral policies in South Korea in the 1970s and modern-day China, suggesting that sectoral interventions might have generated positive aggregate effects in these economies.
We study inference in shift-share regression designs, such as when a regional outcome is regressed on a weighted average of sectoral shocks, using regional sector shares as weights. We conduct a placebo exercise in which we estimate the effect of a shift-share regressor constructed with randomly generated sectoral shocks on actual labor market outcomes across U.S. commuting zones. Tests based on commonly used standard errors with 5% nominal significance level reject the null of no effect in up to 55% of the placebo samples. We use a stylized economic model to show that this overrejection problem arises because regression residuals are correlated across regions with similar sectoral shares, independent of their geographic location. We derive novel inference methods that are valid under arbitrary cross-regional correlation in the regression residuals. We show using popular applications of shift-share designs that our methods may lead to substantially wider confidence intervals in practice.
We show that most U.S. food, drugstore, and mass-merchandise chains charge nearly uniform prices across stores, despite wide variation in consumer demographics and competition. Demand estimates reveal substantial within-chain variation in price elasticities and suggest that the median chain sacrifices |${\$}$|16 million of annual profit relative to a benchmark of optimal prices. In contrast, differences in average prices between chains are broadly consistent with the optimal benchmark. We discuss a range of explanations for nearly uniform pricing, highlighting managerial inertia and brand image concerns as mechanisms frequently mentioned by industry participants. Relative to our optimal benchmark, uniform pricing may significantly increase the prices paid by poorer households relative to the rich, dampen the response of prices to local economic shocks, alter the analysis of mergers in antitrust, and shift the incidence of intranational trade costs.
The best worker is not always the best candidate for manager. In these cases, do firms promote the best potential manager or the best worker in their current job? Using microdata on the performance of sales workers at 131 firms, we find evidence consistent with the Peter Principle, which proposes that firms prioritize current job performance in promotion decisions at the expense of other observable characteristics that better predict managerial performance. We estimate that the costs of promoting workers with lower managerial potential are high, suggesting either that firms are making inefficient promotion decisions or that the benefits of promotion-based incentives are great enough to justify the costs of managerial mismatch. We find that firms manage the costs of the Peter Principle by placing less weight on sales performance in promotion decisions when managerial roles entail greater responsibility and when frontline workers are incentivized by strong pay for performance.
We adapt simple tools from computational linguistics to construct a new measure of political risk faced by individual U.S. firms: the share of their quarterly earnings conference calls that they devote to political risks. We validate our measure by showing that it correctly identifies calls containing extensive conversations on risks that are political in nature, that it varies intuitively over time and across sectors, and that it correlates with the firm’s actions and stock market volatility in a manner that is highly indicative of political risk. Firms exposed to political risk retrench hiring and investment and actively lobby and donate to politicians. These results continue to hold after controlling for news about the mean (as opposed to the variance) of political shocks. Interestingly, the vast majority of the variation in our measure is at the firm level rather than at the aggregate or sector level, in the sense that it is captured neither by the interaction of sector and time fixed effects nor by heterogeneous exposure of individual firms to aggregate political risk. The dispersion of this firm-level political risk increases significantly at times with high aggregate political risk. Decomposing our measure of political risk by topic, we find that firms that devote more time to discussing risks associated with a given political topic tend to increase lobbying on that topic, but not on other topics, in the following quarter.
Can access to a few hundred dollars of liquidity affect the career choice of a recent college graduate? In a three-year field experiment with Teach For America (TFA), a prestigious teacher placement program, we randomly increase the financial packages offered to nearly 7,300 potential teachers who requested support for the transition into teaching. The first two years of the experiment reveal that although most applicants do not respond to a marginal $600 of grants or loans, those in the worst financial position respond by joining TFA at higher rates. We continue the experiment into the third year and self-replicate our results. For the highest-need applicants, an extra $600 in loans, $600 in grants, and $1,200 in grants increase the likelihood of joining TFA by 12.2, 11.4, and 17.1 percentage points (or 20.0%, 18.7%, and 28.1%), respectively. Additional grant and loan dollars are equally effective, suggesting a liquidity mechanism. A follow-up survey bolsters the liquidity story and also shows that those drawn into teaching would have otherwise worked in private-sector firms.
After decades of supporting free trade, in 2018 the United States raised import tariffs and major trade partners retaliated. We analyze the short-run impact of this return to protectionism on the U.S. economy. Import and retaliatory tariffs caused large declines in imports and exports. Prices of imports targeted by tariffs did not fall, implying complete pass-through of tariffs to duty-inclusive prices. The resulting losses to U.S. consumers and firms that buy imports was $51 billion, or 0.27% of GDP. We embed the estimated trade elasticities in a general-equilibrium model of the U.S. economy. After accounting for tariff revenue and gains to domestic producers, the aggregate real income loss was $7.2 billion, or 0.04% of GDP. Import tariffs favored sectors concentrated in politically competitive counties, and the model implies that tradeable-sector workers in heavily Republican counties were the most negatively affected due to the retaliatory tariffs. JEL Code: F1.
We analyze a unique episode in the history of monetary economics, the 2016 Indian “demonetization.” This policy made 86% of cash in circulation illegal tender overnight, with new notes gradually introduced over the next several months. We present a model of demonetization where agents hold cash both to satisfy a cash-in-advance constraint and for tax evasion purposes. We test the predictions of the model in the cross-section of Indian districts using several novel data sets including: the geographic distribution of demonetized and new notes for causal inference; night light activity and employment surveys to measure economic activity including in the informal sector; debit/credit cards and e-wallet transactions data; and banking data on deposit and credit growth. Districts experiencing more severe demonetization had relative reductions in economic activity, faster adoption of alternative payment technologies, and lower bank credit growth. The cross-sectional responses cumulate to a contraction in aggregate employment and night lights–based output due to the the cash shortage of at least 2 percentage points and of bank credit of 2 percentage points in 2016Q4 relative to their counterfactual paths, effects that dissipate over the next few months. Our analysis rejects monetary neutrality using a large-scale natural experiment, something that is still rare in the vast literature on the effects of monetary policy.
This paper develops a general theory of aggregation in inefficient economies. We provide nonparametric formulas for aggregating microeconomic shocks in economies with distortions such as taxes, markups, frictions to resource reallocation, financial frictions, and nominal rigidities. We allow for arbitrary elasticities of substitution, returns to scale, factor mobility, and input-output network linkages. We show how to separately measure changes in technical and allocative efficiency. We also show how to compute the social cost of distortions. We pursue applications focusing on firm-level markups in the United States. We find that improvement in allocative efficiency, due to the reallocation over time of market share to high-markup firms, accounts for about half of aggregate TFP growth over the period 1997–2015. We also find that eliminating the misallocation resulting from the large and dispersed markups estimated in the data would raise aggregate TFP by about 15%, increasing the economy-wide cost of monopoly distortions by two orders of magnitude compared with the famous 0.1% estimate by Harberger (1954). These exact numbers should be interpreted with care because the data are imperfect and require substantial imputation.
We use a unique design feature of a survey of Italian firms to study the causal effect of inflation expectations on firms’ economic decisions. In the survey, a randomly chosen subset of firms is repeatedly treated with information about recent inflation whereas other firms are not. This information treatment generates exogenous variation in inflation expectations. We find that higher inflation expectations on the part of firms leads them to raise their prices, increase demand for credit, and reduce their employment and capital. However, when policy rates are constrained by the effective lower bound, demand effects are stronger, leading firms to raise their prices more and no longer reduce their employment.
Many industries have become increasingly concentrated through mergers and acquisitions, which in health care may have important consequences for spending and outcomes. Using a rich panel of Medicare claims data for nearly one million dialysis patients, we advance the literature on the effects of mergers and acquisitions by studying the precise ways providers change their behavior following an acquisition. We base our empirical analysis on more than 1,200 acquisitions of independent dialysis facilities by large chains over a 12-year period and find that chains transfer several prominent strategies to the facilities they acquire. Most notably, acquired facilities converge to the behavior of their new parent companies by increasing patients’ doses of highly reimbursed drugs, replacing high-skill nurses with less-skilled technicians, and waitlisting fewer patients for kidney transplants. We then show that patients fare worse as a result of these changes: outcomes such as hospitalizations and mortality deteriorate, with our long panel allowing us to identify these effects from within-facility or within-patient variation around the acquisitions. Because overall Medicare spending increases at acquired facilities, mostly as a result of higher drug reimbursements, this decline in quality corresponds to a decline in value for payers. We conclude the article by considering the channels through which acquisitions produce such large changes in provider behavior and outcomes, finding that increased market power cannot explain the decline in quality. Rather, the adoption of the acquiring firm’s strategies and practices drives our main results, with greater economies of scale for drug purchasing responsible for more than half of the change in profits following an acquisition.
We study the role of gender in the evaluation of economic research using submissions to four leading journals. We find that referee gender has no effect on the relative assessment of female- versus male-authored papers, suggesting that any differential biases of male referees are negligible. To determine whether referees as a whole impose different standards for female authors, we compare citations for female- and male-authored papers, holding constant referee evaluations and other characteristics. We find that female-authored papers receive about 25% more citations than observably similar male-authored papers. Editors largely follow the referees, resulting in a 1.7 percentage point lower probability of a revise and resubmit verdict for papers with female authors relative to a citation-maximizing benchmark. In their desk rejection decisions, editors treat female authors more favorably, though they still impose a higher bar than would be implied by citation maximization. We find no differences in the informativeness of female versus male referees or in the weight that editors place on the recommendations of female versus male referees. We also find no differences in editorial delays for female- versus male-authored papers.
Using administrative wealth records from Denmark, we study the effects of wealth taxes on wealth accumulation. Denmark used to impose one of the world’s highest marginal tax rates on wealth, but this tax was greatly reduced starting in 1989 and later abolished. Due to the specific design of the wealth tax, the 1989 reform provides a compelling quasi-experiment for understanding behavioral responses among the wealthiest segments of the population. We find clear reduced-form effects of wealth taxes in the short and medium run, with larger effects on the very wealthy than on the moderately wealthy. We develop a simple life cycle model with utility of residual wealth (bequests) allowing us to interpret the evidence in terms of structural primitives. We calibrate the model to the quasi-experimental moments and simulate the model forward to estimate the long-run effect of wealth taxes on wealth accumulation. Our simulations show that the long-run elasticity of taxable wealth with respect to the net-of-tax return is sizable at the top of the distribution.
We develop a model of social learning from complementary information: short-lived agents sequentially choose from a large set of flexibly correlated information sources for prediction of an unknown state, and information is passed down across periods. Will the community collectively acquire the best kinds of information? Long-run outcomes fall into one of two cases: (i) efficient information aggregation, where the community eventually learns as fast as possible; (ii) “learning traps,” where the community gets stuck observing suboptimal sources and information aggregation is inefficient. Our main results identify a simple property of the underlying informational complementarities that determines which occurs. In both regimes, we characterize which sources are observed in the long run and how often.
A widely held view is that openness to international trade leads to higher income volatility, as trade increases specialization and hence exposure to sector-specific shocks. Contrary to this common wisdom, we argue that when country-wide shocks are important, openness to international trade can lower income volatility by reducing exposure to domestic shocks and allowing countries to diversify the sources of demand and supply across countries. Using a quantitative model of trade, we assess the importance of the two mechanisms (sectoral specialization and cross-country diversification) and show that in recent decades international trade has reduced economic volatility for most countries.
We develop an approach to measuring the cost of living for CES preferences that treats demand shocks as taste shocks that are equivalent to price shocks. In the presence of relative taste shocks, the Sato-Vartia price index is upward biased because an increase in the relative consumer taste for a variety lowers its taste-adjusted price and raises its expenditure share. By failing to allow for this association, the Sato-Vartia index underweights drops in taste-adjusted prices and overweights increases in taste-adjusted prices, leading to what we call a “taste-shock bias.” We show that this bias generalizes to other invertible demand systems.
We document the evolution of market power based on firm-level data for the U.S. economy since 1955. We measure both markups and profitability. In 1980, aggregate markups start to rise from 21% above marginal cost to 61% now. The increase is driven mainly by the upper tail of the markup distribution: the upper percentiles have increased sharply. Quite strikingly, the median is unchanged. In addition to the fattening upper tail of the markup distribution, there is reallocation of market share from low- to high-markup firms. This rise occurs mostly within industry. We also find an increase in the average profit rate from 1% to 8%. Although there is also an increase in overhead costs, the markup increase is in excess of overhead. We discuss the macroeconomic implications of an increase in average market power, which can account for a number of secular trends in the past four decades, most notably the declining labor and capital shares as well as the decrease in labor market dynamism.
The fall of labor’s share of GDP in the United States and many other countries in recent decades is well documented but its causes remain uncertain. Existing empirical assessments typically rely on industry or macro data, obscuring heterogeneity among firms. In this article, we analyze micro panel data from the U.S. Economic Census since 1982 and document empirical patterns to assess a new interpretation of the fall in the labor share based on the rise of “superstar firms.” If globalization or technological changes push sales toward the most productive firms in each industry, product market concentration will rise as industries become increasingly dominated by superstar firms, which have high markups and a low labor share of value added. We empirically assess seven predictions of this hypothesis: (i) industry sales will increasingly concentrate in a small number of firms; (ii) industries where concentration rises most will have the largest declines in the labor share; (iii) the fall in the labor share will be driven largely by reallocation rather than a fall in the unweighted mean labor share across all firms; (iv) the between-firm reallocation component of the fall in the labor share will be greatest in the sectors with the largest increases in market concentration; (v) the industries that are becoming more concentrated will exhibit faster growth of productivity; (vi) the aggregate markup will rise more than the typical firm’s markup; and (vii) these patterns should be observed not only in U.S. firms but also internationally. We find support for all of these predictions.
We study the sources of racial disparities in income using anonymized longitudinal data covering nearly the entire U.S. population from 1989 to 2015. We document three results. First, black Americans and American Indians have much lower rates of upward mobility and higher rates of downward mobility than whites, leading to persistent disparities across generations. Conditional on parent income, the black-white income gap is driven by differences in wages and employment rates between black and white men; there are no such differences between black and white women. Hispanic Americans have rates of intergenerational mobility more similar to whites than blacks, leading the Hispanic-white income gap to shrink across generations. Second, differences in parental marital status, education, and wealth explain little of the black-white income gap conditional on parent income. Third, the black-white gap persists even among boys who grow up in the same neighborhood. Controlling for parental income, black boys have lower incomes in adulthood than white boys in 99% of Census tracts. The few areas with small black-white gaps tend to be low-poverty neighborhoods with low levels of racial bias among whites and high rates of father presence among blacks. Black males who move to such neighborhoods earlier in childhood have significantly better outcomes. However, less than 5% of black children grow up in such areas. Our findings suggest that reducing the black-white income gap will require efforts whose impacts cross neighborhood and class lines and increase upward mobility specifically for black men.
In medicine, the reasons for variation in treatment rates across hospitals serving similar patients are not well understood. Some interpret this variation as unwarranted and push standardization of care as a way of reducing allocative inefficiency. An alternative interpretation is that hospitals with greater expertise in a treatment use it more because of their comparative advantage, suggesting that standardization is misguided. A simple economic model provides an empirical framework to separate these explanations. Estimating this model with data for heart attack patients, we find evidence of substantial variation across hospitals in allocative inefficiency and comparative advantage, with most hospitals overusing treatment in part because of incorrect beliefs about their comparative advantage. A stylized welfare calculation suggests that eliminating allocative inefficiency would increase the total benefits from the treatment that we study by 44%.
This article explores the foundations of religious influence in politics and society. We show that an important Islamic institution fostered the entrenchment of Islamism at a critical juncture in Indonesia, the world’s largest Muslim country. In the early 1960s, rural elites transferred large amounts of land into waqf—inalienable charitable trusts in Islamic law—to avoid expropriation by the state. Regions facing a greater threat of expropriation exhibit more prevalent waqf land and Islamic institutions endowed as such, including mosques and religious schools. These endowments provided conservative forces with the capital needed to promote Islamist ideology and mobilize against the secular state. We identify lasting effects of the transfers on the size of the religious sector, electoral support for Islamist parties, and the adoption of local sharia laws. These effects are shaped by greater demand for religion in government but not by greater piety among the electorate. Waqf assets also impose costs on the local economy, particularly in agriculture, where these endowments are associated with lower productivity. Overall, our findings shed new light on the origins and consequences of Islamism.
We estimate the benefit of life-extending medical treatments to life insurance companies. Our main insight is that life insurance companies have a direct benefit from such treatments because they lower the insurer’s liabilities by pushing the death benefit further into the future and raising future premium income. We apply this insight to immunotherapy, treatments associated with durable gains in survival rates for a growing number of cancer patients. We estimate that the life insurance sector’s aggregate benefit from FDA-approved immunotherapies is $9.8 billion a year. Such life-extending treatments are often prohibitively expensive for patients and governments alike. Exploiting this value creation, we explore various ways life insurers could improve stress-free access to treatment. We discuss potential barriers to integration and the long-run implications for the industrial organization of life and health insurance markets, as well as the broader implications for medical innovation and long-term care insurance markets.
We study optimal spatial policies in a quantitative trade and geography framework with spillovers and spatial sorting of heterogeneous workers. We characterize the spatial transfers that must hold in efficient allocations, as well as labor subsidies that can implement them. There exists scope for welfare-enhancing spatial policies even when spillovers are common across locations. Using data on U.S. cities and existing estimates of the spillover elasticities, we find that the U.S. economy would benefit from a reallocation of workers to currently low-wage cities. The optimal allocation features a greater share of high-skill workers in smaller cities relative to the observed allocation. Inefficient sorting may lead to substantial welfare costs.
Several scholars argue that high agricultural productivity can retard industrial development because it draws resources toward the comparative advantage sector, agriculture. However, agricultural productivity growth can increase savings and the supply of capital, generating an expansion of the capital-intensive sector, manufacturing. We highlight this mechanism in a simple model and test its predictions in the context of a large and exogenous increase in agricultural productivity due to the adoption of genetically engineered soy in Brazil. We find that agricultural productivity growth generated an increase in savings, but these were not reinvested locally. Instead, there were capital outflows from rural areas. Capital reallocated toward urban regions, where it was invested in the industrial and service sectors. The degree of financial integration affected the speed of structural transformation. Regions that were more financially integrated with soy-producing areas through bank branch networks experienced faster growth in nonagricultural lending. Within these regions, firms with preexisting relationships with banks receiving funds from the soy area experienced faster growth in borrowing and employment.
Using a randomized controlled trial, we study whether a negotiation skills training can improve girls’ educational outcomes in a low-resource environment. We find that a negotiation training given to eighth-grade Zambian girls significantly improved educational outcomes over the next three years, and these effects did not fade out. To better understand mechanisms, we estimate the effects of two alternative treatments. Negotiation had much stronger effects than an informational treatment, which had no effect. A treatment designed to have more traditional girls’ empowerment effects had directionally positive but insignificant educational effects. Relative to this treatment, negotiation increased enrollment in higher-quality schooling and had larger effects for high-ability girls. These findings are consistent with a model in which negotiation allows girls to resolve incomplete contracting problems with their parents, yielding increased educational investment for those who experience sufficiently high returns. We provide evidence for this channel through a lab-in-the-field game and follow-up survey with girls and their guardians.
We develop a theory of how an agent makes basic multiproduct consumption decisions in the presence of taste, consumption opportunity, and price shocks that are costly to attend to. We establish that the agent often simplifies her choices by restricting attention to a few important considerations, which depend on the decision at hand and affect her consumption patterns in specific ways. If the agent’s problem is to choose the consumption levels of many goods with different degrees of substitutability, then she may create mental budgets for more substitutable products (e.g., entertainment). In some situations, it is optimal to specify budgets in terms of consumption quantities, but when most products have an abundance of substitutes, specifying budgets in terms of nominal spending tends to be optimal. If the goods are complements, in contrast, then the agent may—consistent with naive diversification—choose a fixed, unconsidered mix of products. And if the agent’s problem is to choose one of multiple products to fulfill a given consumption need (e.g., for gasoline or a bed), then it is often optimal for her to allocate a fixed sum for the need.
We conduct a comparative welfare analysis of 133 historical policy changes over the past half-century in the United States, focusing on policies in social insurance, education and job training, taxes and cash transfers, and in-kind transfers. For each policy, we use existing causal estimates to calculate the benefit that each policy provides its recipients (measured as their willingness to pay) and the policy’s net cost, inclusive of long-term effects on the government’s budget. We divide the willingness to pay by the net cost to the government to form each policy’s Marginal Value of Public Funds, or its ``MVPF''. Comparing MVPFs across policies provides a unified method of assessing their effect on social welfare. Our results suggest that direct investments in low-income children’s health and education have historically had the highest MVPFs, on average exceeding 5. Many such policies have paid for themselves as the government recouped the cost of their initial expenditures through additional taxes collected and reduced transfers. We find large MVPFs for education and health policies among children of all ages, rather than observing diminishing marginal returns throughout childhood. We find smaller MVPFs for policies targeting adults, generally between 0.5 and 2. Expenditures on adults have exceeded this MVPF range in particular if they induced large spillovers on children. We relate our estimates to existing theories of optimal government policy, and we discuss how the MVPF provides lessons for the design of future research.
We study patterns of behavior in bilateral bargaining situations using a rich new data set describing back-and-forth sequential bargaining occurring in over 25 million listings from eBay’s Best Offer platform. We compare observed behavior to predictions from the large theoretical bargaining literature. One-third of bargaining interactions end in immediate agreement, as predicted by complete-information models. The majority of sequences play out differently, ending in disagreement or delayed agreement, which have been rationalized by incomplete information models. We find that stronger bargaining power and better outside options improve agents’ outcomes. Robust empirical findings that existing models cannot rationalize include reciprocal (and gradual) concession behavior and delayed disagreement. Another robust pattern at odds with existing theory is that players exhibit a preference for making and accepting offers that split the difference between the two most recent offers. These observations suggest that behavioral norms, which are neither incorporated nor explained by existing theories, play an important role in the success of bargaining outcomes.
News reports and communication are inherently constrained by space, time, and attention. As a result, news sources often condition the decision of whether to share a piece of information on the similarity between the signal and the prior belief of the audience, which generates a sample selection problem. This article experimentally studies how people form beliefs in these contexts, in particular the mechanisms behind errors in statistical reasoning. I document that a substantial fraction of experimental participants follows a simple “what you see is all there is” heuristic, according to which participants exclusively consider information that is right in front of them, and directly use the sample mean to estimate the population mean. A series of treatments aimed at identifying mechanisms suggests that for many participants, unobserved signals do not even come to mind. I provide causal evidence that the frequency of such incorrect mental models is a function of the computational complexity of the decision problem. These results point to the context dependence of what comes to mind and the resulting errors in belief updating.
Building on a textbook description of associative memory (Kahana 2012), we present a model of choice in which a choice option cues recall of similar past experiences. Memory shapes valuation and decisions in two ways. First, recalled experiences form a norm, which serves as an initial anchor for valuation. Second, salient quality and price surprises relative to the norm lead to large adjustments in valuation. The model unifies many well-documented choice puzzles, including the attribution and projection biases, inattention to hidden attributes, background contrast effects, and context-dependent willingness to pay. Unifying these puzzles on the basis of selective memory and attention to surprise yields multiple new predictions.
We provide evidence that financial market risk perceptions are important drivers of economic fluctuations. We introduce a novel measure of risk perceptions: the price of volatile stocks (PVSt), defined as the book-to-market ratio of low-volatility stocks minus the book-to-market ratio of high-volatility stocks. PVSt is high when perceived risk directly measured from surveys and option prices is low. Using our measure, we show that high perceived risk is associated with low risk-free interest rates, a high cost of capital for risky firms, and future declines in output and real investment. Perceived risk as measured by PVSt falls after positive macroeconomic news. These declines are predictably followed by upward revisions in perceived risk, indicating that fluctuations in investor risk perceptions are not fully rational.
We provide a continuous-time “risk-centric” representation of the New Keynesian model, which we use to analyze the interactions between asset prices, financial speculation, and macroeconomic outcomes when output is determined by aggregate demand. In principle, interest rate policy is highly effective in dealing with shocks to asset valuations. However, in practice monetary policy faces a wide range of constraints. If these constraints are severe, a decline in risky asset valuations generates a demand recession. This reduces earnings and generates a negative feedback loop between asset prices and aggregate demand. In the recession phase, average beliefs matter because they not only affect asset valuations but also determine the strength of the amplification mechanism. In the ex ante boom phase, belief disagreements (or heterogeneous asset valuations) matter because they induce investors to speculate. This speculation exacerbates the crash by reducing high-valuation investors’ wealth when the economy transitions to recession, which depresses (wealth-weighted) average beliefs. Macroprudential policy that restricts speculation in the boom can Pareto improve welfare by increasing asset prices and aggregate demand in the recession.
We conducted a field experiment in a sales firm to test whether improving knowledge flows between coworkers affects productivity. Our design allows us to compare different management practices and isolate whether frictions to knowledge transmission primarily reside with knowledge seekers, knowledge providers, or both. We find large productivity gains from treatments that reduced frictions for knowledge seekers. Workers who were encouraged to seek advice from a randomly chosen partner during structured meetings had average sales gains exceeding 15%. These effects lasted at least 20 weeks after the experiment ended. Treatments intended to change knowledge providers’ willingness to share information, in the form of incentives tied to partners’ joint output, led to positive—but transitory—sales gains. Directing coworkers to share knowledge raised average productivity and reduced output dispersion between workers, highlighting the role that management practices play in generating spillovers inside the firm.
We introduce a simple method of recovering attention costs from choice data. Our method rests on a precise analogy with production theory. Costs of attention determine consumer demand and consumer welfare, just as a competitive firm’s technology determines its supply curve and profits. We implement our recovery method experimentally, outline applications, and link our work to the broader literature on inattention and mistaken decisions.
We construct a dynamic model of election campaigns. In the model, opportunities for candidates to refine/clarify their policy positions are limited and arrive stochastically along the course of the campaign until the predetermined election date. We show that this simple friction leads to rich and subtle campaign dynamics. We first demonstrate these effects in a series of canonical static models of elections that we extend to dynamic settings, including models with valence and a multidimensional policy space. We then present general principles that underlie the results from those models. In particular, we establish that candidates spend a long time using ambiguous language during the election campaign in equilibrium.
This article provides experimental support for the hypothesis that insurance can be a motive for religious donations. We randomize enrollment of members of a Pentecostal church in Ghana into a commercial funeral insurance policy. Then church members allocate money between themselves and a set of religious goods in a series of dictator games with significant stakes. Members enrolled in insurance give significantly less money to their own church compared with members who only receive information about the insurance. Enrollment also reduces giving toward other spiritual goods. We set up a model exploring different channels of religiously based insurance. The implications of the model and the results from the dictator games suggest that adherents perceive the church as a source of insurance and that this insurance is derived from beliefs in an interventionist God. Survey results suggest that material insurance from the church community is also important and we hypothesize that these two insurance channels exist in parallel.
This article provides evidence from a fragile state that citizens demand more of a voice in the government when it tries to tax them. I examine a field experiment randomizing property tax collection across 356 neighborhoods of a large Congolese city. The tax campaign was the first time most citizens had been registered by the state or asked to pay formal taxes. It raised property tax compliance from 0.1% in control to 11.6% in treatment. It also increased political participation by about 5 percentage points (31%): citizens in taxed neighborhoods were more likely to attend town hall meetings hosted by the government or submit evaluations of its performance. To participate in these ways, the average citizen incurred costs equal to their daily household income, and treated citizens spent 43% more than control. Treated citizens also positively updated about the provincial government, perceiving more revenue, less leakage, and a greater responsibility to provide public goods. The results suggest that broadening the tax base has a “participation dividend,” a key idea in historical accounts of the emergence of inclusive governance in early modern Europe and a common justification for donor support of tax programs in weak states.
Nonemployment is often posited as a worker’s outside option in wage-setting models such as bargaining and wage posting. The value of nonemployment is therefore a key determinant of wages. We measure the wage effect of changes in the value of nonemployment among initially employed workers. Our quasi-experimental variation in the value of nonemployment arises from four large reforms of unemployment insurance (UI) benefit levels in Austria. We document that wages are insensitive to UI benefit changes: point estimates imply a wage response of less than $0.01 per $1.00 UI benefit increase, and we can reject sensitivities larger than $0.03. The insensitivity holds even among workers with low wages and high predicted unemployment duration, and among job switchers hired out of unemployment. The insensitivity of wages to the nonemployment value presents a puzzle to the widely used Nash bargaining model, which predicts a sensitivity of $0.24–$0.48. Our evidence supports wage-setting models that insulate wages from the value of nonemployment.
This article studies the impact of changing job skills on career earnings dynamics for college graduates. We measure changes in the skill content of occupations between 2007 and 2019 using detailed job descriptions from a near universe of online job postings. We then develop a simple model where the returns to work experience are a race between on-the-job learning and skill obsolescence. Obsolescence lowers the return to experience, flattening the age-earnings profile in faster-changing careers. We show that the earnings premium for college graduates majoring in technology-intensive subjects such as computer science, engineering, and business declines rapidly, and that these graduates sort out of faster-changing occupations as they gain experience.
The strength of contract enforcement determines how firms source inputs and organize production. Using microdata on Indian manufacturing plants, we show that production and sourcing decisions appear systematically distorted in states with weaker enforcement. Specifically, we document that in industries that tend to rely more heavily on relationship-specific intermediate inputs, plants in states with more-congested courts shift their expenditures away from intermediate inputs and have a greater vertical span of production. To quantify the effect of these distortions on aggregate productivity, we construct a model in which plants have several ways of producing, each with different bundles of inputs. Weak enforcement exacerbates a holdup problem that arises when using inputs that require customization, distorting both the intensive and extensive margins of input use. The equilibrium organization of production and the network structure of input-output linkages arise endogenously from the producers’ simultaneous cost-minimization decisions. We identify the structural parameters that govern enforcement frictions from cross-state variation in the first moments of producers’ cost shares. A set of counterfactuals show that enforcement frictions lower aggregate productivity to an extent that is relevant on the macro scale.
Using newly constructed spatially disaggregated data for London from 1801 to 1921, we show that the invention of the steam railway led to the first large-scale separation of workplace and residence. We show that a class of quantitative urban models is remarkably successful in explaining this reorganization of economic activity. We structurally estimate one of the models in this class and find substantial agglomeration forces in both production and residence. In counterfactuals, we find that removing the whole railway network reduces the population and the value of land and buildings in London by up to 51.5% and 53.3% respectively, and decreases net commuting into the historical center of London by more than 300,000 workers.
This article estimates the effect of environmental regulation on firm productivity using a spatial regression discontinuity design implicit in China's water quality monitoring system. Because water quality readings are important for political evaluations and the monitoring stations only capture emissions from their upstream regions, local government officials are incentivized to enforce tighter environmental standards on firms immediately upstream of a monitoring station, rather than those immediately downstream. Exploiting this discontinuity in regulation stringency with novel firm-level geocoded emission and production data sets, we find that immediate upstream polluters face a more than 24% reduction in total factor productivity (TFP), and a more than 57% reduction in chemical oxygen demand emissions, as compared with their immediate downstream counterparts. We find that the discontinuity in TFP does not exist in nonpolluting industries, only emerged after the government explicitly linked political promotion to water quality readings, and was predominantly driven by prefectural cities with career-driven leaders. Linking the TFP estimate with the emission estimate, a back-of-the-envelope calculation indicates that China's water regulation efforts between 2000 and 2007 were associated with an economic cost of more than 800 billion Chinese yuan.
How does an economy’s production structure determine its macroeconomic response to sectoral distortions? We study a static, multisector framework in which production is organized in an input-output network and production decisions are distorted. Sectoral distortions manifest at the aggregate level via two channels: total factor productivity (TFP) and the labor wedge. We show that near efficiency, distortions have zero first-order effects on TFP and nonzero first-order effects on the labor wedge, and that a sufficient statistic for the latter are the Domar weights. We thereby provide a Hulten-like theorem for the aggregate effects of sectoral distortions. A quantitative application of the model to the 2008–09 financial crisis suggests that the U.S. input-output structure amplified financial distortions by roughly a factor of two during the crisis.
Despite decades of research, the consistent estimation of structural forward-looking macroeconomic equations remains a formidable empirical challenge because of pervasive endogeneity issues. Prominent cases—the estimation of Phillips curves, Euler equations, or monetary policy rules—have typically relied on using predetermined variables as instruments, with mixed success. In this work, we propose a new approach that consists in using sequences of independently identified structural shocks as instrumental variables. Our approach is robust to weak instruments and is valid regardless of the shocks’ variance contribution. We estimate a Phillips curve using monetary shocks as instruments and find that conventional methods substantially underestimate the slope of the Phillips curve.
Equilibria and optima generally differ in imperfectly competitive markets. Although this is well understood theoretically, it is unclear how large the welfare distortions are in the aggregate economy. Do they matter quantitatively? To answer this question, we develop a multisector monopolistic competition model with endogenous firm entry and selection, productivity, and markups. Using French and UK data, we quantify the gap between the equilibrium and optimal allocations. We find that inefficiencies in the labor allocation and entry between sectors, as well as inefficient selection and output per firm within sectors, generate welfare losses of about 6%–10% of GDP.
We evaluate a randomized outreach study in which the IRS sent informational letters to 3.9 million households that paid a tax penalty for lacking health insurance coverage under the Affordable Care Act. Drawing on administrative data, we study the effect of this intervention on taxpayers’ subsequent health insurance enrollment and mortality. We find the intervention led to increased coverage during the subsequent two years and reduced mortality among middle-aged adults over the same time period. The results provide experimental evidence that health insurance coverage can reduce mortality in the United States.
We examine historical banking crises through the lens of bank equity declines, which cover a broad sample of episodes of banking distress with and without banking panics. To do this, we construct a new data set on bank equity returns and narrative information on banking panics for 46 countries over the period of 1870 to 2016. We find that even in the absence of panics, large bank equity declines are associated with substantial credit contractions and output gaps. Although panics are an important amplification mechanism, our results indicate that panics are not necessary for banking crises to have severe economic consequences. Furthermore, panics tend to be preceded by large bank equity declines, suggesting that panics are the result, rather than the cause, of earlier bank losses. We use bank equity returns to uncover a number of forgotten historical banking crises and create a banking crisis chronology that distinguishes between bank equity losses and panics.
Nearly 1,000 officer-involved killings occur each year in the United States. This article documents the large, racially disparate effects of these events on the educational and psychological well-being of Los Angeles public high school students. Exploiting hyperlocal variation in how close students live to a killing, I find that exposure to police violence leads to persistent decreases in GPA, increased incidence of emotional disturbance, and lower rates of high school completion and college enrollment. These effects are driven entirely by black and Hispanic students in response to police killings of other minorities and are largest for incidents involving unarmed individuals.
The earnings difference between white and black workers fell dramatically in the United States in the late 1960s and early 1970s. This article shows that the expansion of the minimum wage played a critical role in this decline. The 1966 Fair Labor Standards Act extended federal minimum wage coverage to agriculture, restaurants, nursing homes, and other services that were previously uncovered and where nearly a third of black workers were employed. We digitize over 1,000 hourly wage distributions from Bureau of Labor Statistics industry wage reports and use CPS microdata to investigate the effects of this reform on wages, employment, and racial inequality. Using a cross-industry difference-in-differences design, we show that earnings rose sharply for workers in the newly covered industries. The impact was nearly twice as large for black workers as for white workers. Within treated industries, the racial gap adjusted for observables fell from 25 log points prereform to 0 afterward. We can rule out significant disemployment effects for black workers. Using a bunching design, we find no aggregate effect of the reform on employment. The 1967 extension of the minimum wage can explain more than 20% of the reduction in the racial earnings and income gap during the civil rights era. Our findings shed new light on the dynamics of labor market inequality in the United States and suggest that minimum wage policy can play a critical role in reducing racial economic disparities.
Macro-finance analyses commonly link firms’ borrowing constraints to the liquidation value of physical assets. For U.S. nonfinancial firms, we show that 20% of debt by value is based on such assets (asset-based lending in creditor parlance), whereas 80% is based predominantly on cash flows from firms’ operations (cash flow–based lending). A standard borrowing constraint restricts total debt as a function of cash flows measured using operating earnings (earnings-based borrowing constraints). These features shape firm outcomes on the margin: first, cash flows in the form of operating earnings can directly relax borrowing constraints; second, firms are less vulnerable to collateral damage from asset price declines, and fire sale amplification may be mitigated. Taken together, our findings point to new venues for modeling firms’ borrowing constraints in macro-finance studies.
We study the causal impact of religiosity through a randomized evaluation of an evangelical Protestant Christian values and theology education program delivered to thousands of ultrapoor Filipino households. Six months after the program ended, treated households have higher religiosity and income; no statistically significant differences in total labor supply, consumption, food security, or life satisfaction; and lower perceived relative economic status. Exploratory analysis suggests that the income treatment effect may operate through increasing grit. Thirty months after the program ended, significant differences in the intensity of religiosity disappear, but those in the treatment group are less likely to be Catholic and more likely to be Protestant, and there is some mixed evidence that their consumption and perceived relative economic status are higher.
We relate gender differences in willingness to commute to the gender wage gap. Using French administrative data on job search criteria, we first document that unemployed women have a lower reservation wage and a shorter maximum acceptable commute than their male counterparts. We identify indifference curves between wage and commute using the joint distributions of reservation job attributes and accepted job bundles. Indifference curves are steeper for women, who value commute around 20% more than men. Controlling in particular for the previous job, newly hired women are paid after unemployment 4% less per hour and have a 12% shorter commute than men. Through the lens of a job search model where commuting matters, we estimate that gender differences in commute valuation can account for a 0.5 log point hourly wage deficit for women, that is, 14% of the residualized gender wage gap. Finally, we use job application data to test the robustness of our results and to show that female workers do not receive less demand from far-away employers, confirming that most of the gender gap in commute is supply-side driven.
We examine the impact of criminalizing sex work, exploiting an event in which local officials unexpectedly criminalized sex work in one district in East Java, Indonesia, but not in neighboring districts. We collect data from female sex workers and their clients before and after the change. We find that criminalization increases sexually transmitted infections among female sex workers by 58 percent, measured by biological tests. This is driven by decreased condom access and use. We also find evidence that criminalization decreases earnings among women who left sex work due to criminalization and decreases their ability to meet their children’s school expenses while increasing the likelihood that children begin working to supplement household income. Although criminalization has the potential to improve population STI outcomes if the market shrinks permanently, we show that five years postcriminalization the market has rebounded and the probability of STI transmission in the general population is likely to have increased.
Communication facilitates cooperation by ensuring that deviators are collectively punished. We explore how players might misuse communication to threaten one another, and we identify ways that organizations can deter misuse and restore cooperation. In our model, a principal plays trust games with a sequence of short-run agents who communicate with each other. An agent can shirk and then extort pay by threatening to report that the principal deviated. We show that these threats can completely undermine cooperation. Investigations of agents’ efforts, or dyadic relationships between the principal and each agent, can deter extortion and restore some cooperation. Investigations of the principal’s action, on the other hand, typically do not help. Our analysis suggests that collective punishments are vulnerable to misuse unless they are designed with an eye toward discouraging it.
This article argues that accounting for capital-embodied technology greatly increases the importance of capital in explaining cross-country differences in agricultural labor productivity. To do so, we draw on a novel data set of agricultural capital prices. We document that new capital is more expensive in richer countries, both in absolute terms and relative to old capital. A model of endogenous adoption of capital of different quality links these price differences to the path of capital-embodied technology. In particular, our model recovers the level of embodied technology from the price of new capital and the growth rate of embodied technology from the price of new capital relative to old capital. We then measure the stocks of quality-adjusted capital in agriculture for a sample of 16 countries at different stages of development. We find that adjusting for differences in quality almost doubles the importance of capital in accounting for cross-country differences in agricultural labor productivity: from 21% to 37%. In addition, improvements in capital quality have been an important source of agricultural labor productivity growth over the past 25 years, accounting for 21% and 35% of the productivity growth in poor and rich countries, respectively.
I study how a credit crunch affects output price dynamics. I build a unique micro-level data set that combines scanner-level prices and quantities with producer information, including the producer’s banking relationships, inventory, and cash holdings. I exploit the Lehman Brothers failure as a quasi-experiment and find that the firms facing a negative credit supply shock decrease their output prices approximately 15% more than their unaffected counterparts. I hypothesize that such firms reduce prices to liquidate inventory and generate additional cash flow from the product market. I find strong empirical support for this hypothesis: (i) the firms that face a negative bank shock temporarily decrease their prices and inventory and increase their market share and cash holdings relative to their counterparts, and (ii) this effect is stronger for the firms and sectors with a high initial inventory or small initial cash holdings.
We study how long-lived rational agents learn from repeatedly observing a private signal and each others’ actions. With normal signals, a group of any size learns more slowly than just four agents who directly observe each others’ private signals in each period. Similar results apply to general signal structures. We identify rational groupthink—in which agents ignore their private signals and choose the same action for long periods of time—as the cause of this failure of information aggregation.
We estimate the wage effects of shared governance, or codetermination, in the form of a mandate of one-third of corporate board seats going to worker representatives. We study a reform in Germany that abruptly abolished this mandate for stock corporations incorporated after August 1994, while it locked the mandate for the slightly older cohorts. Our research design compares firm cohorts incorporated before the reform and after; in a robustness check we draw on the analogous difference in unaffected firm types (LLCs). We find no effects of board-level codetermination on wages and the wage structure, even in firms with particularly flexible wages. The degree of rent sharing and the labor share are also unaffected. We reject that disinvestment could have offset wage effects through the canonical hold-up channel, as shared governance, if anything, increases capital formation.
We develop a theory of sweat equity—the value of business owners’ time and expenses to build customer bases, client lists, and other intangible assets. We discipline the theory using data from U.S. national accounts, business censuses, and brokered sales to estimate a value for sweat equity in the private business sector equal to 1.2 times U.S. GDP, which is about the same magnitude as the value of fixed assets in use in these businesses. For a typical owner, 26% of the sweat equity is transferable through inheritance or sale. The equity values are positively correlated with business incomes and standard measures of markups based on accounting data, but not with owners’ financial assets or standard measures of business total factor productivity. We use our theory to show that abstracting from sweat activity leads to a significant understatement of the effects of lowering business income tax rates on private business activity for both the extensive and intensive margins. Despite finding larger responses, our model’s implied tax elasticities of establishments and owner hours are in line with empirical estimates in the public finance literature. Allowing for financial constraints and superstar firms does not overturn our main findings.
We explore the interplay between trade-invoicing patterns and the pricing of safe assets in different currencies. Our theory highlights the following points: (i) a currency’s role as a unit of account for invoicing decisions is complementary to its role as a safe store of value; (ii) this complementarity can lead to the emergence of a single dominant currency in trade invoicing and global banking, even when multiple large candidate countries share similar economic fundamentals; (iii) firms in emerging-market countries endogenously take on currency mismatches by borrowing in the dominant currency; and (iv) the expected return on dominant-currency safe assets is lower than that on similarly safe assets denominated in other currencies, thereby bestowing an “exorbitant privilege” on the dominant currency. The theory thus provides a unified explanation for why a dominant currency is so heavily used in both trade invoicing and in global finance.
This article describes a new fact, then analyzes its causes and consequences: in most countries, import tariffs and nontariff barriers are substantially lower on dirty than on clean industries, where an industry’s “dirtiness” is defined as its carbon dioxide (CO2) emissions per dollar of output. This difference in trade policy creates a global implicit subsidy to CO2 emissions in internationally traded goods and contributes to climate change. This global implicit subsidy to CO2 emissions totals several hundred billion dollars annually. The greater protection of downstream industries, which are relatively clean, substantially accounts for this pattern. The downstream pattern can be explained by theories where industries lobby for low tariffs on their inputs but final consumers are poorly organized. A quantitative general equilibrium model suggests that if countries applied similar trade policies to clean and dirty goods, global CO2 emissions would decrease and global real income would change little.
How does unemployment insurance (UI) affect unemployed workers’ search behavior? Search models predict that until benefit exhaustion, UI depresses job search effort and increases reservation wages. Over an unemployment spell, search effort should increase up to benefit exhaustion and stay high thereafter. Meanwhile, reservation wages should decrease up to benefit exhaustion and stay low thereafter. To test these predictions, we link administrative registers to data on job search behavior from a major online job search platform in France. We follow over 400,000 workers, as long as they remain unemployed. We analyze the changes in search behavior around benefits exhaustion and take two steps to isolate the individual response to unemployment benefits. First, our longitudinal data allows us to correct for changes in sample composition over the spell. Second, we exploit data on workers eligible for 12–24 months of UI as well as workers ineligible for UI, to control for behavior changes over the unemployment spell that are independent of UI. Our results confirm the predictions of search models. We find that search effort (the number of job applications) increases by at least 50% during the year preceding benefits exhaustion and remains high thereafter. The target monthly wage decreases by at least 2.4% during the year preceding benefits exhaustion and remains low thereafter. In addition, we provide evidence for duration dependence: workers decrease the wage they target by 1.5% over each year of unemployment, irrespective of their UI status.
When a Bayesian learns new information and changes her beliefs, she must on average become concomitantly more certain about the state of the world. Consequently, it is rare for a Bayesian to frequently shift beliefs substantially while remaining relatively uncertain, or, conversely, become very confident with relatively little belief movement. We formalize this intuition by developing specific measures of movement and uncertainty reduction given a Bayesian’s changing beliefs over time, showing that these measures are equal in expectation and creating consequent statistical tests for Bayesianess. We then show connections between these two core concepts and four common psychological biases, suggesting that the test might be particularly good at detecting these biases. We provide support for this conclusion by simulating the performance of our test and other martingale tests. Finally, we apply our test to data sets of individual, algorithmic, and market beliefs.
We examine whether integrating men and women in a traditionally male-dominated environment can change men's attitudes about mixed-gender productivity, gender roles, and gender identity. Our context is the military in Norway, where we randomly assigned female recruits to some squads but not others during boot camp. We find that living and working with women for eight weeks causes men to have more egalitarian attitudes. There is a 14 percentage point higher fraction of men who think mixed-gender teams perform as well or better than same-gender teams, an 8 percentage point increase in men who think household work should be shared equally, and a 14 percentage point increase in men who do not completely disavow feminine traits. Moreover, men in mixed-gender teams are more likely to choose military occupations immediately after boot camp that have a higher fraction of women in them. But these effects do not persist once treatment stops. Treated men’s attitudes converge to those of the controls in a six-month follow-up survey, and there is no long-term effect on choosing fields of study, occupations, or workplaces with a higher fraction of women after military service ends. Contrary to the predictions of many policy makers, we do not find that integrating women into squads hurt male recruits’ performance or satisfaction with service, either during boot camp or their subsequent military assignment. These findings provide evidence that even in a highly gender-skewed environment, gender stereotypes are malleable and can be altered by integrating members of the opposite sex. But they also suggest that without continuing intensive exposure, effects are unlikely to persist.
The labor share in U.S. manufacturing declined from 61% in 1967 to 41% in 2012. The labor share of the typical U.S. manufacturing establishment, in contrast, rose by over 3 percentage points during the same period. Using micro-level data, we document five salient facts: (i) since the 1980s, there has been a dramatic reallocation of value added toward the lower end of the labor share distribution; (ii) this aggregate reallocation is not due to entry/exit, to “superstars” growing faster, or to large establishments lowering their labor shares, but is instead due to units whose labor share fell as they grew in size; (iii) low labor share (LL) establishments benefit from high revenue labor productivity, not low wages; (iv) they also enjoy a product price premium relative to their peers; and (v) they have only temporarily lower labor shares that rebound after five to eight years. This transient pattern has become more pronounced over time, and the dynamics of value added and employment are increasingly disconnected. Taken together, we interpret these facts as pointing to a significant role for demand-side forces.
How does competition affect market outcomes when formal contracts are not enforceable and parties resort to relational contracts? Difficulties with measuring relational contracts and dealing with the endogeneity of competition have frustrated attempts to answer this question. We make progress by studying relational contracts between upstream farmers and downstream mills in Rwanda’s coffee industry. First, we identify salient dimensions of their relational contracts and measure them through an original survey of mills and farmers. Second, we take advantage of an engineering model for the optimal placement of mills to construct an instrument that isolates geographically determined variation in competition. Conditional on the suitability for mills’ placement in the catchment area, we find that mills surrounded by more suitable areas (i) face more competition from other mills, (ii) use fewer relational contracts with farmers, and (iii) exhibit worse performance. An additional competing mill also (iv) reduces the aggregate quantity of coffee supplied to mills by farmers and (v) makes farmers worse off. Competition hampers relational contracts directly by increasing farmers’ temptation to default on the relational contract and indirectly by reducing mills’ profits.
Skepticism about the quality of health systems and their consequent underuse are thought to contribute to high rates of mortality in the developing world. The perceived quality of health services may be especially critical during epidemics, when people choose whether to cooperate with response efforts and frontline health workers. Can improving the perceived quality of health care promote community health and ultimately help to contain epidemics? We leverage a field experiment in Sierra Leone to answer this question in the context of the 2014 West African Ebola crisis. Two years before the outbreak, we randomly assigned two interventions to government-run health clinics—one focused on community monitoring, and the other conferred nonfinancial awards to clinic staff. Prior to the Ebola crisis, both interventions increased clinic utilization and patient satisfaction. Community monitoring additionally improved child health, leading to 38% fewer deaths of children under age five. Later, during the crisis, the interventions also increased reporting of Ebola cases by 62%, and community monitoring significantly reduced Ebola-related deaths. Evidence on mechanisms suggests that both interventions improved the perceived quality of health care, encouraging patients to report Ebola symptoms and receive medical care. Improvements in health outcomes under community monitoring suggest that these changes partly reflect a rise in the underlying quality of administered care. Overall, our results indicate that promoting accountability not only has the power to improve health systems during normal times, but can also make them more resilient to emergent crises.
Most convicted offenders serve their sentences under “community supervision” at home instead of in prison. Under supervision, however, a technical rule violation, such as not paying fees, can result in incarceration. Rule violations account for 25% of prison admissions nationally and are significantly more common among black offenders. I test whether technical rules are effective tools for identifying likely reoffenders and deterring crime and examine their disparate racial impacts using administrative data from North Carolina. Analysis of a 2011 reform reducing prison punishments for technical violations on probation reveals that 40% of rule breakers would go on to commit crimes if spared harsh punishment. The same reform also closed a 33% black-white gap in incarceration rates without substantially increasing the black-white reoffending gap. These effects combined imply that technical rules target riskier probationers overall but disproportionately affect low-risk black offenders. To justify black probationers’ higher violation rate on efficiency grounds, their crimes must be roughly twice as socially costly as that of white probationers. Exploiting the repeat spell nature of the North Carolina data, I estimate a semiparametric competing risks model that allows me to distinguish the effects of particular types of technical rules from unobserved probationer heterogeneity. Rules related to the payment of fees and fines, which are common in many states, are ineffective in tagging likely reoffenders and drive differential effects by race. These findings illustrate the potentially large influence of ostensibly race-neutral policies on racial disparities in the justice system.
Exploiting the exogenous and regional nature of the Great East Japan Earthquake of 2011, this article provides a quantification of the role of input-output linkages as a mechanism for the propagation and amplification of shocks. We document that the disruption caused by the disaster propagated upstream and downstream along supply chains, affecting the direct and indirect suppliers and customers of disaster-stricken firms. Using a general equilibrium model of production networks, we then obtain an estimate for the overall macroeconomic impact of the disaster by taking these propagation effects into account. We find that the earthquake and its aftermaths resulted in a 0.47 percentage point decline in Japan’s real GDP growth in the year following the disaster.
U.S. income inequality has varied inversely with union density over the past 100 years. But moving beyond this aggregate relationship has proven difficult, in part because of limited microdata on union membership prior to 1973. We develop a new source of microdata on union membership dating back to 1936, survey data primarily from Gallup (N ≈ 980,000), to examine the long-run relationship between unions and inequality. We document dramatic changes in the demographics of union members: when density was at its mid-century peak, union households were much less educated and more nonwhite than other households, whereas pre-World War II and today they are more similar to nonunion households on these dimensions. However, despite large changes in composition and density since 1936, the household union premium holds relatively steady between 10 and 20 log points. We use our data to examine the effect of unions on income inequality. Using distributional decompositions, time series regressions, state-year regressions, as well as a new instrumental-variable strategy based on the 1935 legalization of unions and the World War II–era War Labor Board, we find consistent evidence that unions reduce inequality, explaining a significant share of the dramatic fall in inequality between the mid-1930s and late 1940s.
We implement a new survey of firms, focusing on their higher-order macroeconomic expectations. The survey provides a novel set of stylized facts regarding the relationship between first-order and higher-order expectations of economic agents, including how they adjust their beliefs in response to a variety of information treatments. We show how these facts can be used to calibrate key parameters of noisy-information models with infinite regress as well as to test predictions made by this class of models. We also consider a range of extensions to the basic noisy-information model that can potentially better reconcile theory and empirics. Although some extensions like level-k thinking are unsuccessful, incorporating heterogeneous long-run priors can address the empirical shortcomings of the basic noisy-information model.
In October 2010, the state government of Andhra Pradesh, India, issued an emergency ordinance, bringing microfinance activities in the state to a complete halt and causing a nationwide shock to the liquidity of lenders, especially those with loans in the affected state. We use this massive dislocation in the microfinance market to identify the causal impacts of a reduction in credit supply on consumption, earnings, and employment in general equilibrium in rural labor markets. Using a proprietary district-level data set from 25 separate, for-profit microlenders matched with household data from the National Sample Survey, we find that district-level reductions in credit supply are associated with significant decreases in casual daily wages, household wage earnings, and consumption. We find a substantial consumption multiplier from credit that is likely driven by two channels—aggregate demand and business investment. We calibrate a simple two-period, two-sector model of the rural economy that incorporates both channels and show that the magnitude of our wage results is consistent with the model’s predictions.
Global firms finance themselves through foreign subsidiaries, often shell companies in tax havens, which obscures their true economic location in official statistics. We associate the universe of traded securities issued by firms in tax havens with their issuer's ultimate parent and restate bilateral investment positions to better reflect the financial linkages connecting countries around the world. Bilateral portfolio investment from developed countries to firms in large emerging markets is dramatically larger than previously thought. The national accounts of the United States, for example, understate the U.S. position in Chinese firms by nearly $600 billion. Further, we demonstrate how offshore issuance in tax havens affects our understanding of the currency composition of external portfolio liabilities and the nature of foreign direct investment. Finally, we provide additional restatements of bilateral investment positions, including one based on the geographic distribution of sales.
Competition in health insurance markets may fail to improve health outcomes if consumers are not able to identify high-quality plans. We develop and apply a novel instrumental variables framework to quantify the variation in causal mortality effects across plans and measure how much consumers attend to this variation. We first document large differences in the observed mortality rates of Medicare Advantage plans in local markets. We then show that when plans with high mortality rates exit these markets, enrollees tend to switch to more typical plans and subsequently experience lower mortality. We derive and validate a novel “fallback condition” governing the subsequent choices of those affected by plan exits. When the fallback condition is satisfied, plan terminations can be used to estimate the relationship between observed plan mortality rates and causal mortality effects. Applying the framework, we find that mortality rates unbiasedly predict causal mortality effects. We then extend our framework to study other predictors of plan mortality effects and estimate consumer willingness to pay. Higher-spending plans tend to reduce enrollee mortality, but existing quality ratings are uncorrelated with plan mortality effects. Consumers place little weight on mortality effects when choosing plans. Good insurance plans dramatically reduce mortality, and redirecting consumers to such plans could improve beneficiary health.
Consideration set models generalize discrete-choice models by relaxing the assumption that consumers consider all available options. Determining which options were considered has previously required either survey data or restrictions on how attributes affect consideration or utility. We provide an alternative route. In full-consideration models, choice probabilities satisfy a symmetry property analogous to Slutsky symmetry in continuous-choice models. This symmetry breaks down in consideration set models when changes in characteristics perturb consideration. We show that consideration probabilities are constructively identified from the resulting asymmetries. We validate our approach in a lab experiment where consideration sets are known and then apply our framework to study a “smart default” policy in Medicare Part D, wherein consumers are automatically reassigned to lower-cost prescription drug plans with the option of opting out. Full-consideration models imply that such a policy will be ineffective because consumers will opt out to avoid switching costs. Allowing for inattention, we find that defaulting all consumers to lower-cost options produces negligible welfare benefits on average, but defaulting only consumers who would save at least $300 produces large benefits.
We examine how owning a good affects learning and beliefs about its quality. We show that people have more extreme reactions to information about a good they own compared with the same information about a nonowned good: ownership causes more optimistic beliefs after receiving a positive signal and more pessimistic beliefs after receiving a negative signal. Comparing learning to normative benchmarks reveals that people overextrapolate from signals about goods they own, which leads to an overreaction to information; in contrast, learning is close to Bayesian for nonowned goods. We provide direct evidence that this effect is driven by ownership channeling greater attention toward associated information, which leads people to overweight recent signals when forming beliefs. The relationship between ownership and beliefs has testable implications for trade and market expectations. In line with these predictions, we show that the endowment effect doubles in response to positive information and disappears with negative information, and demonstrate a significant relationship between ownership and overextrapolation in survey data about stock market expectations.
Long-term nominal interest rates are surprisingly sensitive to high-frequency (daily or monthly) movements in short-term rates. Since 2000, this high-frequency sensitivity has grown even stronger in U.S. data. By contrast, the association between low-frequency changes (at 6- or 12-month horizons) in long- and short-term rates, which was also strong before 2000, has weakened substantially. This puzzling post-2000 pattern arises because increases in short rates temporarily raise the term premium component of long-term yields, leading long rates to temporarily overreact to changes in short rates. The frequency-dependent excess sensitivity of long-term rates that we observe in recent years is best understood using a model in which (i) declines in short rates trigger “rate-amplifying” shifts in investor demand for long-term bonds, and (ii) the arbitrage response to these demand shifts is both limited and slow. We study, theoretically and empirically, how such rate-amplifying demand can be traced to mortgage-refinancing activity, investors who extrapolate recent changes in short rates, and investors who “reach for yield” when short rates fall. We discuss the implications of our findings for the validity of event study methodologies and the transmission of monetary policy.
We use large-scale federal survey data linked to administrative death records to investigate the relationship between Medicaid enrollment and mortality. Our analysis compares changes in mortality for near-elderly adults in states with and without Affordable Care Act Medicaid expansions. We identify adults most likely to benefit using survey information on socioeconomic status, citizenship status, and public program participation. We find that prior to the ACA expansions, mortality rates across expansion and nonexpansion states trended similarly, but beginning in the first year of the policy, there were significant reductions in mortality in states that opted to expand relative to nonexpanders. Individuals in expansion states experienced a 0.132 percentage point decline in annual mortality, a 9.4% reduction over the sample mean, as a result of the Medicaid expansions. The effect is driven by a reduction in disease-related deaths and grows over time. A variety of alternative specifications, methods of inference, placebo tests, and sample definitions confirm our main result.
Family and social networks are widely believed to influence important life decisions, but causal identification of those effects is notoriously challenging. Using data from Chile, Croatia, Sweden, and the United States, we study within-family spillovers in college and major choice across a variety of national contexts. Exploiting college-specific admissions thresholds that directly affect older but not younger siblings’ college options, we show that in all four countries a meaningful portion of younger siblings follow their older sibling to the same college or college-major combination. Older siblings are followed regardless of whether their target and counterfactual options have large, small, or even negative differences in quality. Spillover effects disappear, however, if the older sibling drops out of college, suggesting that older siblings’ college experiences matter. That siblings influence important human capital investment decisions across such varied contexts suggests that our findings are not an artifact of particular institutional detail but a more generalizable description of human behavior. Causal links between the postsecondary paths of close peers may partly explain persistent college enrollment inequalities between social groups, and this suggests that interventions to improve college access may have multiplier effects.
The urban poor in developing countries face challenging living environments, which may interfere with good sleep. Using actigraphy to measure sleep objectively, we find that low-income adults in Chennai, India, sleep only 5.5 hours a night on average despite spending 8 hours in bed. Their sleep is highly interrupted, with sleep efficiency—sleep per time in bed—comparable to those with disorders such as sleep apnea or insomnia. A randomized three-week treatment providing information, encouragement, and improvements to home sleep environments increased sleep duration by 27 minutes a night by inducing more time in bed. Contrary to expert predictions and a large body of sleep research, increased nighttime sleep had no detectable effects on cognition, productivity, decision making, or well being, and led to small decreases in labor supply. In contrast, short afternoon naps at the workplace improved an overall index of outcomes by 0.12 standard deviations, with significant increases in productivity, psychological well-being, and cognition, but a decrease in work time.
Governments go to great lengths to attract foreign multinationals because they are thought to raise the wages paid to their employees (direct effects) and to improve outcomes at local domestic firms (indirect effects). We construct the first U.S. employer-employee data set with foreign ownership information from tax records to measure these direct and indirect effects. We find the average direct effect of a foreign multinational firm on its U.S. workers is a 7% increase in wages. This premium is larger for higher-skilled workers and for the employees of firms from high GDP per capita countries. We find evidence that it is membership in a multinational production network—instead of foreignness—that generates the foreign-firm premium. We leverage the past spatial clustering of foreign-owned firms by country of ownership to identify the indirect effects. An expansion in the foreign-multinational share of commuting-zone employment substantially increases the employment, value added, and—for higher-earning workers—wages at local domestic-owned firms. Per job created by a foreign multinational, our estimates suggest annual gains of US$13,400 to the aggregate wages of local incumbents, two-thirds of which are from indirect effects. Our estimates suggest that—via mega-deals for subsidies from local governments—foreign multinationals are able to extract a sizable fraction of the local surplus they generate.
Folklore is the collection of traditional beliefs, customs, and stories of a community passed through the generations by word of mouth. We introduce to economics a unique catalog of oral traditions spanning approximately 1,000 societies. After validating the catalog’s content by showing that the groups’ motifs reflect known geographic and social attributes, we present two sets of applications. First, we illustrate how to fill in the gaps and expand upon a group’s ethnographic record, focusing on political complexity, high gods, and trade. Second, we discuss how machine learning and human classification methods can help shed light on cultural traits, using gender roles, attitudes toward risk, and trust as examples. Societies with tales portraying men as dominant and women as submissive tend to relegate their women to subordinate positions in their communities, both historically and today. More risk-averse and less entrepreneurial people grew up listening to stories wherein competitions and challenges are more likely to be harmful than beneficial. Communities with low tolerance toward antisocial behavior, captured by the prevalence of tricksters being punished, are more trusting and prosperous today. These patterns hold across groups, countries, and second-generation immigrants. Overall, the results highlight the significance of folklore in cultural economics, calling for additional applications.
All colonial powers granted concessions to private companies to extract natural resources during the colonial era. In Africa, these concessions were characterized by indirect rule and violence. We use the arbitrarily defined borders of rubber concessions granted in the north of the Congo Free State to examine the causal effects of this form of economic organization on development. We find that historical exposure to the concessions causes significantly worse education, wealth, and health outcomes. To examine mechanisms, we collect survey and experimental data from individuals near a former concession boundary. We find that village chiefs inside the former concessions provide fewer public goods, are less likely to be elected, and are more likely to be hereditary. However, individuals in the concessions are more trusting, more cohesive, and more supportive of sharing income. We interpret our results as reflecting how institutions and culture may act as substitutes in the context of the widespread colonial concession system.
We use the effect of the Dissolution of the English Monasteries after 1535 to test the commercialization hypothesis about the roots of long-run English economic development. Before the Dissolution, monastic lands were relatively unencumbered by inefficient feudal land tenure but could not be sold. The Dissolution created a market for formerly monastic lands, which could now be more effectively commercialized relative to nonmonastic lands, where feudal tenure persisted until the twentieth century. We show that parishes affected by the Dissolution subsequently experienced a rise of the gentry and had more innovation and higher yield in agriculture, a greater share of the population working outside of agriculture, and ultimately higher levels of industrialization. Our results are consistent with explanations of the Agricultural and Industrial Revolutions which emphasize the commercialization of society as a key precondition for taking advantage of technological change and new economic opportunities.
We evaluate the effect of an educational program that aims to build social cohesion in ethnically mixed schools by developing perspective-taking ability in children. The program is implemented in Turkish elementary schools affected by a large influx of Syrian refugee children. We measure a comprehensive set of outcomes that characterize a cohesive school environment, including peer violence incidents, the prevalence of interethnic social ties, and prosocial behavior. Using randomized variation in program implementation, we find that the program significantly lowers peer violence and victimization on school grounds. The program also reduces the likelihood of social exclusion and increases interethnic social ties in the classroom. We find that the program significantly improves prosocial behavior, measured by incentivized tasks: treated students exhibit significantly higher trust, reciprocity, and altruism toward each other as well as toward anonymous out-school peers. We show that this enhanced prosociality is welfare improving from the ex post payoff perspective. We investigate multiple channels that could explain the results, including ethnic bias, impulsivity, empathetic concern, emotional intelligence, behavioral norms, and perspective taking. Children’s increased effort to take others’ perspectives emerges as the most robust mechanism to explain our results.
We design a field experiment to study how the allocation of authority between frontline procurement officers and their monitors affects performance both directly and through the response to incentives. In collaboration with the government of Punjab, Pakistan, we shift authority from monitors to procurement officers and introduce financial incentives in a sample of 600 procurement officers in 26 districts. We find that autonomy alone reduces prices by 9% without reducing quality and that the effect is stronger when the monitor tends to delay approvals for purchases until the end of the fiscal year. In contrast, the effect of performance pay is muted, except when agents face a monitor who does not delay approvals. Time use data reveal agents’ responses vary along the same margin: autonomy increases the time devoted to procurement, and this leads to lower prices only when monitors cause delays. By contrast, incentives work when monitors do not cause delays. The results illustrate that organizational design and anti-corruption policies must balance agency issues at different levels of the hierarchy.
We propose a theory of indebted demand, capturing the idea that large debt burdens lower aggregate demand, and thus the natural rate of interest. At the core of the theory is the simple yet underappreciated observation that borrowers and savers differ in their marginal propensities to save out of permanent income. Embedding this insight in a two-agent perpetual-youth model, we find that recent trends in income inequality and financial deregulation lead to indebted household demand, pushing down the natural rate of interest. Moreover, popular expansionary policies—such as accommodative monetary policy—generate a debt-financed short-run boom at the expense of indebted demand in the future. When demand is sufficiently indebted, the economy gets stuck in a debt-driven liquidity trap, or debt trap. Escaping a debt trap requires consideration of less conventional macroeconomic policies, such as those focused on redistribution or those reducing the structural sources of high inequality.
I study how people understand, reason, and learn about two major tax policies: income taxation and estate taxation. Using large-scale social economics surveys issued to representative U.S. samples and associated experiments, I elicit respondents’ factual knowledge about tax policy and the income or wealth distributions. Most important, I study their understanding of the mechanisms of tax policy and the reasoning that underlies their policy views. In decomposing policy views, I find that support for income and estate taxes is most strongly correlated with social preferences, that is, the perceived benefits of redistribution and concerns around the fairness of inequality and taxation, as well as with broader views of the government. Efficiency concerns play a more minor role. These correlational patterns are confirmed by the experimental approach, which shows people instructional videos that explain the workings and consequences of one of the aspects of tax policy (the Redistribution and the Efficiency treatments) or that bring the two together and focus on the trade-off (the Economist treatment). The Redistribution and Economist treatments significantly increase support for more progressive income or estate taxes, while the Efficiency treatment has no effect. There are large partisan gaps in both the final policy views and at every step of the reasoning about the underlying mechanisms of taxes. Democrats’ and Republicans’ divergences in tax policy views can ultimately be traced back to different normative criteria (social preferences) and views of the government, rather than to different perceptions of the efficiency implications of taxation.
We present a theory of identity politics that builds on two ideas. First, when policy conflict renders a certain social divide—economic or cultural—salient, a voter identifies with her economic or cultural group. Second, the voter slants her beliefs toward the stereotype of the group she identifies with. We obtain three implications. First, voters’ beliefs are polarized along the distinctive features of salient groups. Second, if the salience of cultural policies increases, cultural conflict rises, redistributive conflict falls, and polarization becomes more correlated across issues. Third, economic shocks hurting conservative voters may trigger a switch to cultural identity, causing these voters to demand less redistribution. We discuss U.S. survey evidence in light of these implications.
Information is central to designing effective policy, and policy makers often rely on competing interests to separate useful from biased information. We show how this logic of virtuous competition can break down, using a new and comprehensive data set on U.S. federal regulatory rulemaking for 2003–2016. For-profit corporations and nonprofit entities are active in the rulemaking process and are arguably expected to provide independent viewpoints. Policy makers, however, may not be fully aware of the financial ties between some firms and nonprofits—grants that are legal and tax-exempt but hard to trace. We document three patterns that suggest that these grants may distort policy. First, we show that shortly after a firm donates to a nonprofit, the nonprofit is more likely to comment on rules on which the firm has also commented. Second, when a firm comments on a rule, the comments by nonprofits that recently received grants from the firm’s foundation are systematically closer in content to the firm’s own comments, relative to comments submitted by other nonprofits. Third, the final rule’s discussion by a regulator is more similar to the firm’s comments on that rule when the firm’s recent grantees also commented on it.
Should policy communications aim at anchoring expectations of the policy instrument (“keep interest rates at zero until date τ”) or of the targeted outcome (“do whatever it takes to bring unemployment down to |$y\%$|”)? We study how the optimal approach depends on a departure from rational expectations. People have limited depth of knowledge and rationality, or form otherwise distorted beliefs about the behavior of others and the general equilibrium (GE) effects of policy. The bite of this distortion on implementability and welfare is minimized by target-based guidance if and only if GE feedback is strong enough. This offers a rationale for why central banks should shine the spotlight on unemployment when faced with a prolonged liquidity trap, a steep Keynesian cross, or a large financial accelerator.
How does mobile broadband internet affect approval of government? Using Gallup World Poll surveys of 840,537 individuals from 2,232 subnational regions in 116 countries from 2008 to 2017 and the global expansion of 3G mobile networks, we show that on average, an increase in mobile broadband internet access reduces government approval. This effect is present only when the internet is not censored, and it is stronger when the traditional media are censored. 3G helps expose actual corruption in government: revelations of the Panama Papers and other corruption incidents translate into higher perceptions of corruption in regions covered by 3G networks. Voter disillusionment had electoral implications. In Europe, 3G expansion led to lower vote shares for incumbent parties and higher vote shares for the antiestablishment populist opposition. Vote shares for nonpopulist opposition parties were unaffected by 3G expansion.
U.S. states increasingly require identification to vote—an ostensible attempt to deter fraud that prompts complaints of selective disenfranchisement. Using a difference-in-differences design on a panel data set with 1.6 billion observations, 2008–2018, we find that the laws have no negative effect on registration or turnout, overall or for any group defined by race, gender, age, or party affiliation. These results hold through a large number of specifications. Our most demanding specification controls for state, year, and voter fixed effects, along with state and voter time-varying controls. Based on this specification, we obtain point estimates of −0.1 percentage points for effects both on overall registration and turnout (with 95% confidence intervals of [−2.3; 2.1 percentage points] and [−3.0; 2.8 percentage points], respectively), and +1.4 percentage points for the effect on the turnout of nonwhite voters relative to whites (with a 95% confidence interval of [−0.5; 3.2 percentage points]). The lack of negative impact on voter turnout cannot be attributed to voters’ reaction against the laws, measured by campaign contributions and self-reported political engagement. However, the likelihood that nonwhite voters were contacted by a campaign increases by 4.7 percentage points, suggesting that parties’ mobilization might have offset modest effects of the laws on the participation of ethnic minorities. Finally, strict ID requirements have no effect on fraud, actual or perceived. Overall, our findings suggest that efforts to improve elections may be better directed at other reforms.
This article sheds new light on the long-run evolution of political cleavages in 21 Western democracies. We exploit a new database on the socioeconomic determinants of the vote, covering more than 300 elections held between 1948 and 2020. In the 1950s and 1960s, the vote for social democratic, socialist, and affiliated parties was associated with lower-educated and low-income voters. It has gradually become associated with higher-educated voters, giving rise in the 2010s to a disconnection between the effects of income and education on the vote: higher-educated voters now vote for the “left,” while high-income voters continue to vote for the “right.” This transition has been accelerated by the rise of green and anti-immigration movements, whose distinctive feature is to concentrate the votes of the higher-educated and lower-educated electorates. Combining our database with historical data on political parties’ programs, we provide evidence that the reversal of the education cleavage is strongly linked to the emergence of a new “sociocultural” axis of political conflict.
During traffic stops, police search black and Hispanic motorists more than twice as often as white motorists, yet those searches are no more likely to yield contraband. We ask whether equalizing search rates by motorist race would reduce contraband yield. We use unique administrative data from Texas to isolate variation in search behavior across and within highway patrol troopers and find that search rates are unrelated to the proportion of searches that yield contraband. We find that troopers can equalize search rates across racial groups, maintain the status quo search rate, and increase contraband yield. Troopers appear to be limited in their ability to discern between motorists who are more or less likely to carry contraband.
Proposition 209 banned race-based affirmative action at California public universities in 1998. Using a difference-in-differences research design and a newly constructed longitudinal database linking all 1994–2002 University of California applicants to their educational experiences and wages, I show that ending affirmative action caused underrepresented minority (URM) freshman applicants to cascade into lower-quality colleges. The “mismatch hypothesis” implies that this cascade would provide net educational benefits to URM applicants, but their degree attainment declined overall and in STEM fields, especially among less academically qualified applicants. URM applicants’ average wages in their twenties and thirties subsequently declined, driven by declines among Hispanic applicants. These declines are not explained by URM students' performance or persistence in STEM course sequences, which were unchanged after Prop 209. Ending affirmative action also deterred thousands of qualified URM students from applying to any UC campus. Complementary regression discontinuity and institutional value-added analyses suggest that affirmative action’s net educational and wage benefits for URM applicants exceed its net costs for on-the-margin white and Asian applicants.
We experimentally test a theory of risky choice in which the perception of a lottery payoff is noisy due to information processing constraints in the brain. We model perception using the principle of efficient coding, which implies that perception is most accurate for those payoffs that occur most frequently. Across two preregistered laboratory experiments, we manipulate the distribution from which payoffs in the choice set are drawn. In our first experiment, we find that risk taking is more sensitive to payoffs that are presented more frequently. In a follow-up task, we incentivize subjects to classify which of two symbolic numbers is larger. Subjects exhibit higher accuracy and faster response times for numbers they have observed more frequently. In our second experiment, we manipulate the payoff distribution so that efficient coding modulates the strength of valuation biases. As we experimentally increase the frequency of large payoffs, we find that subjects perceive the upside of a risky lottery more accurately and take greater risk. Together, our experimental results suggest that risk taking depends systematically on the payoff distribution to which the decision maker’s perceptual system has recently adapted. More broadly, our findings highlight the importance of imprecise and efficient coding in economic decision making.
Does flexible pay increase the gender wage gap? To answer this question, we analyze the wages of public school teachers in Wisconsin, where a 2011 reform allowed school districts to set teachers’ pay more flexibly and engage in individual negotiations. Using quasi-exogenous variation in the timing of the introduction of flexible pay, driven by the expiration of preexisting collective-bargaining agreements, we show that flexible pay lowered the salaries of women compared with men with the same credentials. This gap is larger for younger teachers and smaller for teachers working under a female principal or superintendent. Survey evidence suggests that the gap is partly driven by women engaging less frequently in negotiations over pay, especially when the counterpart is a man. The gap is unlikely to be driven by observable gender differences in job mobility or teacher ability, although the threat of moving and a high demand for male teachers could exacerbate it. Our results suggest that pay discretion and wage bargaining are important determinants of the gender wage gap and that institutions, such as unions, might help narrow this gap.
We investigate the wage, employment, and reallocation effects of the introduction of a nationwide minimum wage in Germany that affected 15% of all employees. Based on identification designs that exploit variation in exposure across individuals and local areas, we find that the minimum wage raised wages but did not lower employment. It also led to the reallocation of low-wage workers from smaller to larger, from lower- to higher-paying, and from less to more productive establishments. This worker upgrading accounts for up to 17% of the wage increase induced by the minimum wage. Moreover, at the regional level, average establishment quality increased in more affected areas in the years following the introduction of the minimum wage.
This article studies the effect of corporate and personal taxes on innovation in the United States over the twentieth century. We build a panel of the universe of inventors who patented since 1920, and a historical state-level corporate tax database with corporate tax rates and tax base information, which we link to existing data on state-level personal income taxes and other economic outcomes. Our analysis focuses on the effect of personal and corporate income taxes on individual inventors (the micro level) and on states (the macro level), considering the quantity and quality of innovation, its location, and the share produced by the corporate rather than the noncorporate sector. We propose several identification strategies, all of which yield consistent results. We find that higher taxes negatively affect the quantity and the location of innovation, but not average innovation quality. The state-level elasticities to taxes are large and consistent with the aggregation of the individual-level responses of innovation produced and cross-state mobility. Corporate taxes tend to especially affect corporate inventors’ innovation production and cross-state mobility. Personal income taxes significantly affect the quantity of innovation overall and the mobility of inventors.
We argue that the network of investment production and purchases across sectors is an important propagation mechanism for understanding business cycles. Empirically, we show that the majority of investment goods are produced by a few “investment hubs,” which are more cyclical than other sectors. We embed this investment network into a multisector business cycle model and show that sector-specific shocks to the investment hubs and their key suppliers have large effects on aggregate employment and drive down labor productivity. Quantitatively, we find that sector-specific shocks to hubs and their suppliers account for an increasing share of aggregate fluctuations over time, generating the declining cyclicality of labor productivity and other changes in business cycle patterns since the 1980s.
This article shows that the inability to use monetary policy for macroeconomic stabilization leaves a government more vulnerable to a rollover crisis. We study a sovereign default model with self-fulfilling rollover crises, foreign currency debt, and nominal rigidities. When the government lacks monetary independence, lenders anticipate that the government would face a severe recession in the event of a liquidity crisis and are therefore more prone to run on government bonds. In a quantitative application to the Eurozone debt crisis, we find that the lack of monetary autonomy played a central role in making Spain vulnerable to a rollover crisis. Finally, we argue that a lender of last resort can go a long way toward reducing the costs of giving up monetary independence.
We use stock exchange message data to quantify the negative aspect of high-frequency trading, known as “latency arbitrage.” The key difference between message data and widely familiar limit order book data is that message data contain attempts to trade or cancel that fail. This allows the researcher to observe both winners and losers in a race, whereas in limit order book data you cannot see the losers, so you cannot directly see the races. We find that latency arbitrage races are very frequent (about one per minute per symbol for FTSE 100 stocks), extremely fast (the modal race lasts 5–10 millionths of a second), and account for a remarkably large portion of overall trading volume (about 20%). Race participation is concentrated, with the top six firms accounting for over 80% of all race wins and losses. The average race is worth just a small amount (about half a price tick), but because of the large volumes the stakes add up. Our main estimates suggest that races constitute roughly one-third of price impact and the effective spread (key microstructure measures of the cost of liquidity), that latency arbitrage imposes a roughly 0.5 basis point tax on trading, that market designs that eliminate latency arbitrage would reduce the market’s cost of liquidity by 17%, and that the total sums at stake are on the order of $5 billion per year in global equity markets alone.
Government programs are often offered on an optional basis to market participants. We explore the economics of such voluntary regulation in the context of a Medicare payment reform, in which one medical provider receives a single, predetermined payment for a sequence of related healthcare services, instead of separate service-specific payments. This “bundled payment” program was originally implemented as a five-year randomized trial, with mandatory participation by hospitals assigned to the new payment model; however, after two years, participation was made voluntary for half of these hospitals. Using detailed claim-level data, we document that voluntary participation is more likely for hospitals that can increase revenue without changing behavior (“selection on levels”) and for hospitals that had large changes in behavior when participation was mandatory (“selection on slopes”). To assess outcomes under counterfactual regimes, we estimate a stylized model of responsiveness to and selection into the program. We find that the current voluntary regime generates inefficient transfers to hospitals, and that alternative (feasible) designs could reduce these inefficient transfers and raise welfare. Our analysis highlights key design elements to consider under voluntary regulation.
The seller of an asset has the option to buy hard information about the value of the asset from an intermediary. The seller can then disclose this information before selling the asset in a competitive market. We study how the intermediary designs and sells hard information to robustly maximize the intermediary's revenue across all equilibria. Even though the intermediary could use an accurate test that reveals the asset’s value, we show that robust revenue maximization leads to a noisy test with a continuum of possible scores. In addition, the intermediary always charges the seller for disclosing the test score to the market, but not necessarily for running the test. This enables the intermediary to robustly appropriate a significant share of the surplus resulting from the asset sale.
We use machine learning as a tool to study decision making, focusing specifically on how physicians diagnose heart attack. An algorithmic model of a patient’s probability of heart attack allows us to identify cases where physicians' testing decisions deviate from predicted risk. We then use actual health outcomes to evaluate whether those deviations represent mistakes or physicians’ superior knowledge. This approach reveals two inefficiencies. Physicians overtest: predictably low-risk patients are tested, but do not benefit. At the same time, physicians undertest: predictably high-risk patients are left untested, and then go on to suffer adverse health events including death. A natural experiment using shift-to-shift testing variation confirms these findings. Simultaneous over- and undertesting cannot easily be explained by incentives alone, and instead point to systematic errors in judgment. We provide suggestive evidence on the psychology underlying these errors. First, physicians use too simple a model of risk. Second, they overweight factors that are salient or representative of heart attack, such as chest pain. We argue health care models must incorporate physician error, and illustrate how policies focused solely on incentive problems can produce large inefficiencies.
Physicians, judges, teachers, and agents in many other settings differ systematically in the decisions they make when faced with similar cases. Standard approaches to interpreting and exploiting such differences assume they arise solely from variation in preferences. We develop an alternative framework that allows variation in preferences and diagnostic skill and show that both dimensions may be partially identified in standard settings under quasi-random assignment. We apply this framework to study pneumonia diagnoses by radiologists. Diagnosis rates vary widely among radiologists, and descriptive evidence suggests that a large component of this variation is due to differences in diagnostic skill. Our estimated model suggests that radiologists view failing to diagnose a patient with pneumonia as more costly than incorrectly diagnosing one without, and that this leads less skilled radiologists to optimally choose lower diagnostic thresholds. Variation in skill can explain 39% of the variation in diagnostic decisions, and policies that improve skill perform better than uniform decision guidelines. Failing to account for skill variation can lead to highly misleading results in research designs that use agent assignments as instruments.
There are two broad views as to why people stay poor. One emphasizes differences in fundamentals, such as ability, talent, or motivation. The poverty traps view emphasizes differences in opportunities that stem from access to wealth. To test these views, we exploit a large-scale, randomized asset transfer and an 11-year panel of 6,000 households who begin in extreme poverty. The setting is rural Bangladesh, and the assets are cows. The data support the poverty traps view—we identify a threshold level of initial assets above which households accumulate assets, take on better occupations (from casual labor in agriculture or domestic services to running small livestock businesses), and grow out of poverty. The reverse happens for those below the threshold. Structural estimation of an occupational choice model reveals that almost all beneficiaries are misallocated in the work they do at baseline and that the gains arising from eliminating misallocation would far exceed the program costs. Our findings imply that large transfers, which create better jobs for the poor, are an effective means of getting people out of poverty traps and reducing global poverty.
We give a full analytic characterization of a large class of sticky-price models where the firm’s price-setting behavior is described by a generalized hazard function. Such a function allows for a vast variety of empirical hazards to be fitted. This setup is microfounded by random adjustment costs, as in Caballero and Engel (1999), or by information frictions, as in Woodford (2009). We establish two main results. First, we show how to identify all the primitives of the model, including the distribution of the fundamental adjustment costs and the implied generalized hazard function, using the distribution of price changes. Second, we derive a sufficient statistic for the aggregate effect of a monetary shock: given an arbitrary generalized hazard function, the cumulative impulse response of output to a once-and-for-all monetary shock is proportional to the ratio of the kurtosis of the steady-state distribution of price changes over the frequency of price adjustment. We prove that Calvo’s model yields the upper bound and Golosov and Lucas’s model the lower bound on this measure in the class of random menu cost models.
Financial aid from the Susan Thompson Buffett Foundation (STBF) provides comprehensive support to a student population similar to that served by a host of state aid programs. In conjunction with STBF, we randomly assigned aid awards to thousands of Nebraska high school graduates from low-income, minority, and first-generation college households. Randomly assigned STBF awards boost bachelor’s (BA) degree completion for students targeting four-year schools by about 8 points. Degree gains are concentrated among four-year college applicants who would otherwise have been unlikely to pursue a four-year program. Degree effects are mediated by award-induced increases in credits earned toward a BA in the first year of college. The extent of initial four-year college engagement explains differences in impact by target campus and across covariate subgroups. The projected lifetime earnings effect of awards exceeds marginal educational spending for all of the subgroups examined in the study. Projected earnings gains exceed funder costs for urban students and for students with relatively weak academic preparation.
We show theoretically and empirically that the managerial organization of multiestablishment firms is interdependent across establishments. To derive our result, we study the effect of geographic frictions on firm organization. In our model, we assume that a CEO’s time is a resource in limited supply, shared across headquarters and establishments. Geographic frictions increase the costs of accessing the CEO. Hiring middle managers at one establishment substitutes for CEO time, which is reallocated across all establishments. Consequently, geographic frictions between the headquarters and one establishment affect the organization of all establishments of a firm. Our model is consistent with novel facts about multiestablishment firm organization that we document using administrative data from Germany. We exploit the opening of high-speed railway routes to show that not only the establishments directly affected by faster travel times but also the other establishments of the firm adjust their organization. Our findings imply that local conditions propagate across space through firm organization.
Overdose deaths involving opioids have increased dramatically since the 1990s, leading to the worst drug overdose epidemic in U.S. history, but there is limited empirical evidence about the initial causes. In this article, we examine the role of the 1996 introduction and marketing of OxyContin as a potential leading cause of the opioid crisis. We leverage cross-state variation in exposure to OxyContin's introduction due to a state policy that substantially limited the drug's early entry and marketing in select states. Recently unsealed court documents involving Purdue Pharma show that state-based triplicate prescription programs posed a major obstacle to sales of OxyContin and suggest that less marketing was targeted to states with these programs. We find that OxyContin distribution was more than 50% lower in “triplicate states” in the years after the drug's launch. Although triplicate states had higher rates of overdose deaths prior to 1996, this relationship flipped shortly after the launch and triplicate states saw substantially slower growth in overdose deaths, continuing even 20 years after OxyContin's introduction. Our results show that the introduction and marketing of OxyContin explain a substantial share of overdose deaths over the past two decades.