Do files for "Methods Matter: p-Hacking and Publication Bias in Causal Analysis in Economics: Comment"

1
*** this script creates caliper tables using our adjustment procedure using different significant thresholds (Tables 2, A5 and A6 in our comment)
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clear

. clear

. 
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set more off

. set more off

. 
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* specify directories where data are located and where results should be stored
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global dir_main : pwd

. global dir_main : pwd

. 
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global dir_data "$dir_main/Data"
global dir_data "/home/rstudio/repbox/projects_ejd/aer_112_9_9/mod/Scripts/Data"

. global dir_data "$dir_main/Data"

. 
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global dir_results "$dir_main/Results"
global dir_results "/home/rstudio/repbox/projects_ejd/aer_112_9_9/mod/Scripts/Results"

. global dir_results "$dir_main/Results"

. 
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** Table 2: 5% significance treshold
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* read in the data
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cd "$dir_data" 
cd "/home/rstudio/repbox/projects_ejd/aer_112_9_9/mod/Scripts/Data"

. cd "${repbox_path}/Data"
/home/rstudio/repbox/projects_ejd/aer_112_9_9/mod/Data

. 
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capture use "MM_new.dta", clear 

. capture use "MM_new.dta", clear

. 
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* determine folder to store results
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cd "$dir_results" 
cd "/home/rstudio/repbox/projects_ejd/aer_112_9_9/mod/Scripts/Results"

. cd "${repbox_path}/Results"
/home/rstudio/repbox/projects_ejd/aer_112_9_9/mod/Results

. 
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* drop obs with small significand
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keep if keep_obs==1

. keep if keep_obs==1
(8,233 observations deleted)

. 
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* first: 5% threshold
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	local depvar "sign_5pct"

. local depvar "sign_5pct"

. 
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	local threshold 1.96

. local threshold 1.96

. 
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	local weight1 "pw="

. local weight1 "pw="

. 
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	local weight2 "aw"

. local weight2 "aw"

. 
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eststo clear

. eststo clear

. 
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probit `depvar' DID IV RDD if t>(`threshold'-0.5) & t<(`threshold'+0.5) [`weight1'`weight2'], cluster(journal_article_cluster)
probit sign_5pct DID IV RDD if t>(1.96-0.5) & t<(1.96+0.5) [pw=aw], cluster(journal_article_cluster)

. probit `depvar' DID IV RDD if t>(`threshold'-0.5) & t<(`th
> reshold'+0.5) [`weight1'`weight2'], cluster(journal_article_cluster)

Iteration 0:   log pseudolikelihood = -787128.03  
Iteration 1:   log pseudolikelihood = -783790.82  
Iteration 2:   log pseudolikelihood =  -783790.8  

Probit regression                                       Number of obs =  3,558
                                                        Wald chi2(3)  =   9.30
                                                        Prob > chi2   = 0.0256
Log pseudolikelihood = -783790.8                        Pseudo R2     = 0.0042

              (Std. err. adjusted for 464 clusters in journal_article_cluster)
------------------------------------------------------------------------------
             |               Robust
   sign_5pct | Coefficient  std. err.      z    P>|z|     [95% conf. interval]
-------------+----------------------------------------------------------------
         DID |   .1417897   .0981744     1.44   0.149    -.0506287     .334208
          IV |   .2585744   .0882504     2.93   0.003     .0856068     .431542
         RDD |   .2395807   .1623999     1.48   0.140    -.0787172    .5578786
       _cons |  -.0147018    .058181    -0.25   0.801    -.1287345    .0993309
------------------------------------------------------------------------------

. 
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eststo : margins, dydx(*) post

. eststo : margins, dydx(*) post

Average marginal effects                                 Number of obs = 3,558
Model VCE: Robust

Expression: Pr(sign_5pct), predict()
dy/dx wrt:  DID IV RDD

------------------------------------------------------------------------------
             |            Delta-method
             |      dy/dx   std. err.      z    P>|z|     [95% conf. interval]
-------------+----------------------------------------------------------------
         DID |   .0555643   .0383468     1.45   0.147     -.019594    .1307227
          IV |   .1013297   .0340454     2.98   0.003     .0346019    .1680575
         RDD |   .0938865   .0633513     1.48   0.138    -.0302798    .2180528
------------------------------------------------------------------------------
(est1 stored)

. 
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estadd local Window "[`threshold'$\pm$0.50]"
estadd local Window "[1.96$\pm$0.50]"

. estadd local Window "[`threshold'$\pm$0.50]"

added macro:
             e(Window) : "[1.96$\pm$0.50]"

. 
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sum `depvar' if t>(`threshold'-0.5) & t<(`threshold'+0.5) & method=="RCT"
sum sign_5pct if t>(1.96-0.5) & t<(1.96+0.5) & method=="RCT"

. sum `depvar' if t>(`threshold'-0.5) & t<(`threshold'+0.5) 
> & method=="RCT"

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
   sign_5pct |      1,135    .4696035    .4992952          0          1

. 
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estadd local rct_sign = round(r(mean), 0.01)

. estadd local rct_sign = round(r(mean), 0.01)

added macro:
           e(rct_sign) : ".47"

. 
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probit `depvar' DID IV RDD top5 i.year experience_avg experience_avg_sq share_top_authors share_top_phd i.ireport authored_solo share_female_authors editor_present if t>(`threshold'-0.5) & t<(`threshold'+0.5) [`weight1'`weight2'], cluster(journal_article_cluster)
probit sign_5pct DID IV RDD top5 i.year experience_avg experience_avg_sq share_top_authors share_top_phd i.ireport authored_solo share_female_authors editor_present if t>(1.96-0.5) & t<(1.96+0.5) [pw=aw], cluster(journal_article_cluster)

. probit `depvar' DID IV RDD top5 i.year experience_avg expe
> rience_avg_sq share_top_authors share_top_phd i.ireport authored_solo share_f
> emale_authors editor_present if t>(`threshold'-0.5) & t<(`threshold'+0.5) [`w
> eight1'`weight2'], cluster(journal_article_cluster)

Iteration 0:   log pseudolikelihood = -787128.03  
Iteration 1:   log pseudolikelihood = -779397.93  
Iteration 2:   log pseudolikelihood = -779397.22  
Iteration 3:   log pseudolikelihood = -779397.22  

Probit regression                                       Number of obs =  3,558
                                                        Wald chi2(15) =  17.30
                                                        Prob > chi2   = 0.3015
Log pseudolikelihood = -779397.22                       Pseudo R2     = 0.0098

              (Std. err. adjusted for 464 clusters in journal_article_cluster)
------------------------------------------------------------------------------
             |               Robust
   sign_5pct | Coefficient  std. err.      z    P>|z|     [95% conf. interval]
-------------+----------------------------------------------------------------
         DID |   .1165539   .1006179     1.16   0.247    -.0806535    .3137613
          IV |   .2561537   .0955064     2.68   0.007     .0689646    .4433428
         RDD |   .2115284   .1575675     1.34   0.179    -.0972981    .5203549
        top5 |  -.0722586   .1376952    -0.52   0.600    -.3421362     .197619
             |
        year |
       2018  |   .0158176    .084099     0.19   0.851    -.1490134    .1806487
             |
experience~g |  -.0195206    .021143    -0.92   0.356    -.0609601    .0219188
experience~q |   .0058338   .0547813     0.11   0.915    -.1015356    .1132032
share_top_~s |  -.0035355   .1397164    -0.03   0.980    -.2773747    .2703037
share_top_~d |   .0370752   .1147796     0.32   0.747    -.1878887    .2620391
             |
     ireport |
          2  |  -.1032901   .3110685    -0.33   0.740    -.7129732    .5063929
          3  |  -.1859905   .2622382    -0.71   0.478    -.6999679    .3279869
          4  |  -.1515877   .2895918    -0.52   0.601    -.7191771    .4160017
             |
authored_s~o |  -.2043409   .1288895    -1.59   0.113    -.4569596    .0482778
share_fema~s |  -.0633343   .1384035    -0.46   0.647    -.3346001    .2079316
editor_pre~t |   .0592437   .1213527     0.49   0.625    -.1786032    .2970906
       _cons |   .3775107   .3603338     1.05   0.295    -.3287307    1.083752
------------------------------------------------------------------------------

. 
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eststo : margins, dydx(*) post

. eststo : margins, dydx(*) post

Average marginal effects                                 Number of obs = 3,558
Model VCE: Robust

Expression: Pr(sign_5pct), predict()
dy/dx wrt:  DID IV RDD top5 2018.year experience_avg experience_avg_sq
            share_top_authors share_top_phd 2.ireport 3.ireport 4.ireport
            authored_solo share_female_authors editor_present

------------------------------------------------------------------------------
             |            Delta-method
             |      dy/dx   std. err.      z    P>|z|     [95% conf. interval]
-------------+----------------------------------------------------------------
         DID |   .0453942   .0390883     1.16   0.246    -.0312175    .1220059
          IV |    .099764   .0366758     2.72   0.007     .0278807    .1716474
         RDD |   .0823838   .0611258     1.35   0.178    -.0374206    .2021883
        top5 |  -.0281425    .053614    -0.52   0.600    -.1332241     .076939
             |
        year |
       2018  |   .0061621   .0327656     0.19   0.851    -.0580573    .0703814
             |
experience~g |  -.0076027   .0082208    -0.92   0.355    -.0237152    .0085098
experience~q |   .0022721   .0213344     0.11   0.915    -.0395426    .0440867
share_top_~s |   -.001377   .0544148    -0.03   0.980    -.1080279     .105274
share_top_~d |   .0144396    .044689     0.32   0.747    -.0731492    .1020284
             |
     ireport |
          2  |   -.039136   .1171979    -0.33   0.738    -.2688396    .1905677
          3  |  -.0711716   .0979541    -0.73   0.467    -.2631582    .1208149
          4  |  -.0577843   .1090707    -0.53   0.596    -.2715589    .1559903
             |
authored_s~o |  -.0795845   .0499084    -1.59   0.111    -.1774031     .018234
share_fema~s |  -.0246668   .0539276    -0.46   0.647     -.130363    .0810295
editor_pre~t |   .0230736   .0472585     0.49   0.625    -.0695513    .1156985
------------------------------------------------------------------------------
Note: dy/dx for factor levels is the discrete change from the base level.
(est2 stored)

. 
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estadd local Window "[`threshold'$\pm$0.50]"
estadd local Window "[1.96$\pm$0.50]"

. estadd local Window "[`threshold'$\pm$0.50]"

added macro:
             e(Window) : "[1.96$\pm$0.50]"

. 
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sum `depvar' if t>(`threshold'-0.5) & t<(`threshold'+0.5) & method=="RCT"
sum sign_5pct if t>(1.96-0.5) & t<(1.96+0.5) & method=="RCT"

. sum `depvar' if t>(`threshold'-0.5) & t<(`threshold'+0.5) 
> & method=="RCT"

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
   sign_5pct |      1,135    .4696035    .4992952          0          1

. 
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estadd local rct_sign = round(r(mean), 0.01)

. estadd local rct_sign = round(r(mean), 0.01)

added macro:
           e(rct_sign) : ".47"

. 
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probit `depvar' DID IV RDD top5 i.year FINANCE MACRO_GROWTH GEN_INT EXP DEV LABOR PUB URB experience_avg experience_avg_sq share_top_authors share_top_phd i.ireport authored_solo share_female_authors editor_present if t>(`threshold'-0.5) & t<(`threshold'+0.5) [`weight1'`weight2'], cluster(journal_article_cluster)
probit sign_5pct DID IV RDD top5 i.year FINANCE MACRO_GROWTH GEN_INT EXP DEV LABOR PUB URB experience_avg experience_avg_sq share_top_authors share_top_phd i.ireport authored_solo share_female_authors editor_present if t>(1.96-0.5) & t<(1.96+0.5) [pw=aw], cluster(journal_article_cluster)

. probit `depvar' DID IV RDD top5 i.year FINANCE MACRO_GROWT
> H GEN_INT EXP DEV LABOR PUB URB experience_avg experience_avg_sq share_top_au
> thors share_top_phd i.ireport authored_solo share_female_authors editor_prese
> nt if t>(`threshold'-0.5) & t<(`threshold'+0.5) [`weight1'`weight2'], cluster
> (journal_article_cluster)

Iteration 0:   log pseudolikelihood = -787128.03  
Iteration 1:   log pseudolikelihood = -771481.98  
Iteration 2:   log pseudolikelihood = -771472.86  
Iteration 3:   log pseudolikelihood = -771472.86  

Probit regression                                       Number of obs =  3,558
                                                        Wald chi2(23) =  28.71
                                                        Prob > chi2   = 0.1901
Log pseudolikelihood = -771472.86                       Pseudo R2     = 0.0199

              (Std. err. adjusted for 464 clusters in journal_article_cluster)
------------------------------------------------------------------------------
             |               Robust
   sign_5pct | Coefficient  std. err.      z    P>|z|     [95% conf. interval]
-------------+----------------------------------------------------------------
         DID |   .0757119   .1041663     0.73   0.467    -.1284502     .279874
          IV |   .2051944    .099425     2.06   0.039      .010325    .4000639
         RDD |   .1788154   .1514817     1.18   0.238    -.1180833     .475714
        top5 |  -.0536747   .2860662    -0.19   0.851    -.6143542    .5070048
             |
        year |
       2018  |   .0326287   .0860954     0.38   0.705    -.1361151    .2013725
             |
     FINANCE |   .2836399   .2923781     0.97   0.332    -.2894106    .8566905
MACRO_GROWTH |   .1591018    .305504     0.52   0.603     -.439675    .7578786
     GEN_INT |   .0357906   .2600287     0.14   0.891    -.4738562    .5454374
         EXP |  -.1864556    .297199    -0.63   0.530    -.7689549    .3960438
         DEV |  -.1670997   .2850511    -0.59   0.558    -.7257896    .3915902
       LABOR |  -.0488808    .306058    -0.16   0.873    -.6487433    .5509818
         PUB |   -.111524   .2683149    -0.42   0.678    -.6374116    .4143635
         URB |  -.3861322   .3149989    -1.23   0.220    -1.003519    .2312543
experience~g |  -.0346788   .0220463    -1.57   0.116    -.0778888    .0085311
experience~q |   .0451448   .0575547     0.78   0.433    -.0676603    .1579499
share_top_~s |   .0068984    .136691     0.05   0.960    -.2610111    .2748078
share_top_~d |  -.0349392   .1161714    -0.30   0.764    -.2626309    .1927525
             |
     ireport |
          2  |  -.2030917   .3086295    -0.66   0.511    -.8079945     .401811
          3  |  -.1921778   .2649042    -0.73   0.468    -.7113804    .3270249
          4  |  -.3767746   .3121362    -1.21   0.227    -.9885502     .235001
             |
authored_s~o |  -.2774233   .1325264    -2.09   0.036    -.5371703   -.0176764
share_fema~s |  -.0409916   .1291988    -0.32   0.751    -.2942166    .2122335
editor_pre~t |    .059749   .1226511     0.49   0.626    -.1806428    .3001408
       _cons |   .5575802   .4590339     1.21   0.224    -.3421097     1.45727
------------------------------------------------------------------------------

. 
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eststo : margins, dydx(*) post

. eststo : margins, dydx(*) post

Average marginal effects                                 Number of obs = 3,558
Model VCE: Robust

Expression: Pr(sign_5pct), predict()
dy/dx wrt:  DID IV RDD top5 2018.year FINANCE MACRO_GROWTH GEN_INT EXP DEV
            LABOR PUB URB experience_avg experience_avg_sq share_top_authors
            share_top_phd 2.ireport 3.ireport 4.ireport authored_solo
            share_female_authors editor_present

------------------------------------------------------------------------------
             |            Delta-method
             |      dy/dx   std. err.      z    P>|z|     [95% conf. interval]
-------------+----------------------------------------------------------------
         DID |   .0291632   .0401224     0.73   0.467    -.0494752    .1078016
          IV |   .0790381   .0379999     2.08   0.038     .0045596    .1535166
         RDD |   .0688772   .0581974     1.18   0.237    -.0451876    .1829421
        top5 |  -.0206748   .1101918    -0.19   0.851    -.2366467    .1952972
             |
        year |
       2018  |   .0125738   .0331962     0.38   0.705    -.0524896    .0776371
             |
     FINANCE |   .1092542   .1122214     0.97   0.330    -.1106957    .3292042
MACRO_GROWTH |   .0612838   .1176928     0.52   0.603    -.1693897    .2919574
     GEN_INT |    .013786   .1001594     0.14   0.891    -.1825227    .2100948
         EXP |  -.0718201    .114333    -0.63   0.530    -.2959087    .1522685
         DEV |  -.0643645   .1097413    -0.59   0.558    -.2794535    .1507245
       LABOR |  -.0188282   .1178808    -0.16   0.873    -.2498704     .212214
         PUB |  -.0429575   .1033144    -0.42   0.678    -.2454501     .159535
         URB |  -.1487329   .1210878    -1.23   0.219    -.3860606    .0885949
experience~g |  -.0133578   .0084511    -1.58   0.114    -.0299217    .0032061
experience~q |   .0173892   .0221389     0.79   0.432    -.0260022    .0607805
share_top_~s |   .0026572   .0526548     0.05   0.960    -.1005443    .1058586
share_top_~d |  -.0134581   .0447383    -0.30   0.764    -.1011436    .0742274
             |
     ireport |
          2  |  -.0760581   .1138294    -0.67   0.504    -.2991597    .1470435
          3  |  -.0718773   .0963194    -0.75   0.456    -.2606598    .1169051
          4  |  -.1433133   .1151492    -1.24   0.213    -.3690015     .082375
             |
authored_s~o |  -.1068597   .0504076    -2.12   0.034    -.2056569   -.0080625
share_fema~s |  -.0157894   .0497791    -0.32   0.751    -.1133546    .0817758
editor_pre~t |   .0230145   .0472671     0.49   0.626    -.0696273    .1156563
------------------------------------------------------------------------------
Note: dy/dx for factor levels is the discrete change from the base level.
(est3 stored)

. 
48
estadd local Window "[`threshold'$\pm$0.50]"
estadd local Window "[1.96$\pm$0.50]"

. estadd local Window "[`threshold'$\pm$0.50]"

added macro:
             e(Window) : "[1.96$\pm$0.50]"

. 
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sum `depvar' if t>(`threshold'-0.5) & t<(`threshold'+0.5) & method=="RCT"
sum sign_5pct if t>(1.96-0.5) & t<(1.96+0.5) & method=="RCT"

. sum `depvar' if t>(`threshold'-0.5) & t<(`threshold'+0.5) 
> & method=="RCT"

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
   sign_5pct |      1,135    .4696035    .4992952          0          1

. 
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estadd local rct_sign = round(r(mean), 0.01)

. estadd local rct_sign = round(r(mean), 0.01)

added macro:
           e(rct_sign) : ".47"

. 
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probit `depvar' DID IV RDD i.year i.unique_j experience_avg experience_avg_sq share_top_authors share_top_phd i.ireport authored_solo share_female_authors editor_present if t>(`threshold'-0.5) & t<(`threshold'+0.5) [`weight1'`weight2'], cluster(journal_article_cluster)
probit sign_5pct DID IV RDD i.year i.unique_j experience_avg experience_avg_sq share_top_authors share_top_phd i.ireport authored_solo share_female_authors editor_present if t>(1.96-0.5) & t<(1.96+0.5) [pw=aw], cluster(journal_article_cluster)

. probit `depvar' DID IV RDD i.year i.unique_j experience_av
> g experience_avg_sq share_top_authors share_top_phd i.ireport authored_solo s
> hare_female_authors editor_present if t>(`threshold'-0.5) & t<(`threshold'+0.
> 5) [`weight1'`weight2'], cluster(journal_article_cluster)

Iteration 0:   log pseudolikelihood = -787128.03  
Iteration 1:   log pseudolikelihood = -766548.66  
Iteration 2:   log pseudolikelihood = -766512.36  
Iteration 3:   log pseudolikelihood = -766512.36  

Probit regression                                       Number of obs =  3,558
                                                        Wald chi2(38) =  46.69
                                                        Prob > chi2   = 0.1574
Log pseudolikelihood = -766512.36                       Pseudo R2     = 0.0262

              (Std. err. adjusted for 464 clusters in journal_article_cluster)
------------------------------------------------------------------------------
             |               Robust
   sign_5pct | Coefficient  std. err.      z    P>|z|     [95% conf. interval]
-------------+----------------------------------------------------------------
         DID |   .0736408   .1062244     0.69   0.488    -.1345553    .2818368
          IV |   .2198465   .0995092     2.21   0.027      .024812    .4148809
         RDD |   .1801098   .1524099     1.18   0.237     -.118608    .4788277
             |
        year |
       2018  |   .0566411   .0896519     0.63   0.528    -.1190734    .2323557
             |
    unique_j |
          2  |  -.2516936   .2134245    -1.18   0.238    -.6699979    .1666107
          3  |   .0785309   .3926721     0.20   0.841    -.6910922     .848154
          4  |   .2345425   .2341113     1.00   0.316    -.2243073    .6933923
          5  |   .0482819   .3622297     0.13   0.894    -.6616753    .7582392
          6  |   .5010829   .6140697     0.82   0.414    -.7024715    1.704637
          7  |   .1438332   .2350388     0.61   0.541    -.3168343    .6045007
          8  |   .1433989   .2249147     0.64   0.524    -.2974259    .5842237
          9  |   .0323671   .2624939     0.12   0.902    -.4821115    .5468457
         10  |  -.0738271   .2192112    -0.34   0.736    -.5034732     .355819
         11  |   .0311221   .1876327     0.17   0.868    -.3366312    .3988753
         12  |   .5293393   .2383176     2.22   0.026     .0622454    .9964331
         13  |   .4821917   .2814032     1.71   0.087    -.0693484    1.033732
         14  |   .0384885   .2951909     0.13   0.896     -.540075    .6170519
         15  |  -.0118614   .2480466    -0.05   0.962    -.4980239    .4743011
         16  |   .2766264   .2430563     1.14   0.255    -.1997553     .753008
         17  |  -.1370631   .2146993    -0.64   0.523    -.5578661    .2837398
         18  |  -.1239927   .1897303    -0.65   0.513    -.4958572    .2478718
         19  |   .0051459   .2340717     0.02   0.982    -.4536262     .463918
         20  |  -.1338312   .3528399    -0.38   0.704    -.8253847    .5577223
         21  |   .3127046   .5474384     0.57   0.568    -.7602549    1.385664
         22  |  -.1507644   .2243116    -0.67   0.502    -.5904071    .2888783
         23  |   .0338202   .2392322     0.14   0.888    -.4350662    .5027067
         24  |  -.3245505   .2433748    -1.33   0.182    -.8015562    .1524553
         25  |  -.0880728   .1809318    -0.49   0.626    -.4426925    .2665469
             |
experience~g |  -.0345579   .0220377    -1.57   0.117    -.0777511    .0086353
experience~q |   .0516204    .057724     0.89   0.371    -.0615166    .1647575
share_top_~s |   .0046775   .1347783     0.03   0.972    -.2594831    .2688381
share_top_~d |  -.0335067   .1192466    -0.28   0.779    -.2672257    .2002124
             |
     ireport |
          2  |   .0220078   .5879276     0.04   0.970    -1.130309    1.174325
          3  |   .0415578   .5676137     0.07   0.942    -1.070945     1.15406
          4  |  -.1325214   .5967744    -0.22   0.824    -1.302178    1.037135
             |
authored_s~o |  -.2185934   .1364597    -1.60   0.109    -.4860496    .0488627
share_fema~s |  -.0108071   .1256119    -0.09   0.931    -.2570019    .2353877
editor_pre~t |   .0925139   .1263826     0.73   0.464    -.1551914    .3402192
       _cons |   .2000555   .6305136     0.32   0.751    -1.035729    1.435839
------------------------------------------------------------------------------

. 
53
eststo : margins, dydx(*) post

. eststo : margins, dydx(*) post

Average marginal effects                                 Number of obs = 3,558
Model VCE: Robust

Expression: Pr(sign_5pct), predict()
dy/dx wrt:  DID IV RDD 2018.year 2.unique_j 3.unique_j 4.unique_j 5.unique_j
            6.unique_j 7.unique_j 8.unique_j 9.unique_j 10.unique_j
            11.unique_j 12.unique_j 13.unique_j 14.unique_j 15.unique_j
            16.unique_j 17.unique_j 18.unique_j 19.unique_j 20.unique_j
            21.unique_j 22.unique_j 23.unique_j 24.unique_j 25.unique_j
            experience_avg experience_avg_sq share_top_authors share_top_phd
            2.ireport 3.ireport 4.ireport authored_solo share_female_authors
            editor_present

------------------------------------------------------------------------------
             |            Delta-method
             |      dy/dx   std. err.      z    P>|z|     [95% conf. interval]
-------------+----------------------------------------------------------------
         DID |   .0281719   .0406646     0.69   0.488    -.0515293     .107873
          IV |    .084104   .0377267     2.23   0.026      .010161     .158047
         RDD |   .0689024   .0582121     1.18   0.237    -.0451912     .182996
             |
        year |
       2018  |   .0216803   .0343569     0.63   0.528     -.045658    .0890186
             |
    unique_j |
          2  |  -.0989098   .0835062    -1.18   0.236     -.262579    .0647593
          3  |   .0306391   .1525348     0.20   0.841    -.2683236    .3296017
          4  |   .0900873   .0891744     1.01   0.312    -.0846912    .2648658
          5  |   .0188776   .1413106     0.13   0.894     -.258086    .2958412
          6  |   .1841719   .2051616     0.90   0.369    -.2179374    .5862812
          7  |   .0558032   .0909217     0.61   0.539    -.1224001    .2340066
          8  |   .0556371   .0870941     0.64   0.523    -.1150643    .2263384
          9  |   .0126678   .1026468     0.12   0.902    -.1885162    .2138519
         10  |  -.0290274    .086141    -0.34   0.736    -.1978607    .1398058
         11  |   .0121814   .0734644     0.17   0.868    -.1318061    .1561689
         12  |   .1934162     .08424     2.30   0.022     .0283088    .3585236
         13  |   .1779048   .0991036     1.80   0.073    -.0163348    .3721443
         14  |   .0150579    .115359     0.13   0.896    -.2110416    .2411574
         15  |  -.0046533   .0973201    -0.05   0.962    -.1953972    .1860906
         16  |   .1056657   .0917448     1.15   0.249    -.0741509    .2854823
         17  |  -.0539442   .0843527    -0.64   0.522    -.2192724     .111384
         18  |  -.0487952   .0745362    -0.65   0.513    -.1948835     .097293
         19  |   .0020171    .091746     0.02   0.982    -.1778017    .1818359
         20  |  -.0526712   .1389144    -0.38   0.705    -.3249384     .219596
         21  |   .1188302   .1996676     0.60   0.552    -.2725111    .5101716
         22  |  -.0593392   .0881722    -0.67   0.501    -.2321536    .1134751
         23  |   .0132354   .0935735     0.14   0.888    -.1701653     .196636
         24  |  -.1271377   .0943687    -1.35   0.178    -.3120969    .0578216
         25  |  -.0346403   .0710473    -0.49   0.626    -.1738903    .1046098
             |
experience~g |  -.0132204   .0083953    -1.57   0.115    -.0296749    .0032341
experience~q |   .0197478   .0220502     0.90   0.370    -.0234697    .0629653
share_top_~s |   .0017894   .0515635     0.03   0.972    -.0992733    .1028521
share_top_~d |  -.0128182   .0456253    -0.28   0.779    -.1022421    .0766057
             |
     ireport |
          2  |   .0084063   .2248797     0.04   0.970    -.4323497    .4491624
          3  |   .0158495   .2171473     0.07   0.942    -.4097514    .4414505
          4  |   -.051024   .2284281    -0.22   0.823    -.4987348    .3966868
             |
authored_s~o |  -.0836246   .0517545    -1.62   0.106    -.1850616    .0178124
share_fema~s |  -.0041344   .0480566    -0.09   0.931    -.0983236    .0900549
editor_pre~t |   .0353919   .0484033     0.73   0.465    -.0594769    .1302607
------------------------------------------------------------------------------
Note: dy/dx for factor levels is the discrete change from the base level.
(est4 stored)

. 
54
estadd local Window "[`threshold'$\pm$0.50]"
estadd local Window "[1.96$\pm$0.50]"

. estadd local Window "[`threshold'$\pm$0.50]"

added macro:
             e(Window) : "[1.96$\pm$0.50]"

. 
55
sum `depvar' if t>(`threshold'-0.5) & t<(`threshold'+0.5) & method=="RCT"
sum sign_5pct if t>(1.96-0.5) & t<(1.96+0.5) & method=="RCT"

. sum `depvar' if t>(`threshold'-0.5) & t<(`threshold'+0.5) 
> & method=="RCT"

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
   sign_5pct |      1,135    .4696035    .4992952          0          1

. 
56
estadd local rct_sign = round(r(mean), 0.01)

. estadd local rct_sign = round(r(mean), 0.01)

added macro:
           e(rct_sign) : ".47"

. 
57
58
probit `depvar' DID IV RDD i.year i.unique_j experience_avg experience_avg_sq share_top_authors share_top_phd i.ireport authored_solo share_female_authors editor_present if t>(`threshold'-0.35) & t<(`threshold'+0.35) [`weight1'`weight2'], cluster(journal_article_cluster)
probit sign_5pct DID IV RDD i.year i.unique_j experience_avg experience_avg_sq share_top_authors share_top_phd i.ireport authored_solo share_female_authors editor_present if t>(1.96-0.35) & t<(1.96+0.35) [pw=aw], cluster(journal_article_cluster)

. probit `depvar' DID IV RDD i.year i.unique_j experience_av
> g experience_avg_sq share_top_authors share_top_phd i.ireport authored_solo s
> hare_female_authors editor_present if t>(`threshold'-0.35) & t<(`threshold'+0
> .35) [`weight1'`weight2'], cluster(journal_article_cluster)

note: 6.unique_j != 0 predicts success perfectly;
      6.unique_j omitted and 2 obs not used.

Iteration 0:   log pseudolikelihood = -591666.24  
Iteration 1:   log pseudolikelihood = -574775.18  
Iteration 2:   log pseudolikelihood = -574730.73  
Iteration 3:   log pseudolikelihood = -574730.72  

Probit regression                                       Number of obs =  2,626
                                                        Wald chi2(37) =  50.33
                                                        Prob > chi2   = 0.0707
Log pseudolikelihood = -574730.72                       Pseudo R2     = 0.0286

              (Std. err. adjusted for 433 clusters in journal_article_cluster)
------------------------------------------------------------------------------
             |               Robust
   sign_5pct | Coefficient  std. err.      z    P>|z|     [95% conf. interval]
-------------+----------------------------------------------------------------
         DID |   .0633271    .118004     0.54   0.592    -.1679564    .2946106
          IV |   .2543622   .1094703     2.32   0.020     .0398044      .46892
         RDD |   .1921999   .1575691     1.22   0.223    -.1166298    .5010297
             |
        year |
       2018  |  -.0104169   .0969474    -0.11   0.914    -.2004303    .1795966
             |
    unique_j |
          2  |  -.0266616   .2970691    -0.09   0.928    -.6089064    .5555832
          3  |   .2681497   .4806622     0.56   0.577    -.6739309     1.21023
          4  |   .0025828   .3186021     0.01   0.994    -.6218658    .6270314
          5  |    .160241   .4015092     0.40   0.690    -.6267025    .9471846
          7  |   .1514289   .2809237     0.54   0.590    -.3991713    .7020291
          8  |   .2737456   .2835051     0.97   0.334    -.2819141    .8294053
          9  |   .1358753   .3272474     0.42   0.678    -.5055179    .7772684
         10  |  -.0917075   .2500014    -0.37   0.714    -.5817011    .3982862
         11  |   .1614007   .2497478     0.65   0.518    -.3280961    .6508974
         12  |   .6870897   .3070947     2.24   0.025     .0851951    1.288984
         13  |   .5541148    .302435     1.83   0.067    -.0386469    1.146877
         14  |   .1863834   .3771267     0.49   0.621    -.5527713    .9255381
         15  |   .3124553   .3026538     1.03   0.302    -.2807351    .9056458
         16  |    .025289   .3274312     0.08   0.938    -.6164644    .6670424
         17  |  -.2197718   .2748699    -0.80   0.424    -.7585068    .3189632
         18  |   .1824681   .2524869     0.72   0.470    -.3123971    .6773332
         19  |   .1042038   .2800405     0.37   0.710    -.4446655    .6530732
         20  |  -.1810595   .4365845    -0.41   0.678     -1.03675    .6746305
         21  |   .9323148   .5237417     1.78   0.075    -.0942001     1.95883
         22  |  -.0170097   .2992592    -0.06   0.955     -.603547    .5695275
         23  |   .0793226   .3102112     0.26   0.798    -.5286802    .6873254
         24  |  -.1313301   .3273032    -0.40   0.688    -.7728327    .5101724
         25  |   .0436462    .250565     0.17   0.862    -.4474522    .5347445
             |
experience~g |  -.0274967   .0252185    -1.09   0.276     -.076924    .0219307
experience~q |   .0513463   .0677197     0.76   0.448    -.0813819    .1840746
share_top_~s |  -.1034644   .1545477    -0.67   0.503    -.4063724    .1994436
share_top_~d |    .151753   .1320918     1.15   0.251    -.1071422    .4106482
             |
     ireport |
          2  |   .4059452   .5446588     0.75   0.456    -.6615664    1.473457
          3  |    .407311   .5162205     0.79   0.430    -.6044627    1.419085
          4  |   .5783056   .5491737     1.05   0.292    -.4980551    1.654666
             |
authored_s~o |  -.2579011   .1374657    -1.88   0.061    -.5273288    .0115266
share_fema~s |  -.0167991   .1323454    -0.13   0.899    -.2761913     .242593
editor_pre~t |   .0464266   .1229163     0.38   0.706    -.1944849    .2873382
       _cons |  -.3689419   .5905684    -0.62   0.532    -1.526435     .788551
------------------------------------------------------------------------------

. 
59
eststo : margins, dydx(*) post

. eststo : margins, dydx(*) post

Average marginal effects                                 Number of obs = 2,626
Model VCE: Robust

Expression: Pr(sign_5pct), predict()
dy/dx wrt:  DID IV RDD 2018.year 2.unique_j 3.unique_j 4.unique_j 5.unique_j
            7.unique_j 8.unique_j 9.unique_j 10.unique_j 11.unique_j
            12.unique_j 13.unique_j 14.unique_j 15.unique_j 16.unique_j
            17.unique_j 18.unique_j 19.unique_j 20.unique_j 21.unique_j
            22.unique_j 23.unique_j 24.unique_j 25.unique_j experience_avg
            experience_avg_sq share_top_authors share_top_phd 2.ireport
            3.ireport 4.ireport authored_solo share_female_authors
            editor_present

------------------------------------------------------------------------------
             |            Delta-method
             |      dy/dx   std. err.      z    P>|z|     [95% conf. interval]
-------------+----------------------------------------------------------------
         DID |   .0242441   .0451488     0.54   0.591    -.0642459    .1127341
          IV |   .0973798   .0413972     2.35   0.019     .0162428    .1785168
         RDD |   .0735816   .0601929     1.22   0.222    -.0443944    .1915577
             |
        year |
       2018  |  -.0039875   .0371007    -0.11   0.914    -.0767035    .0687285
             |
    unique_j |
          2  |  -.0104825   .1167964    -0.09   0.928    -.2393993    .2184343
          3  |   .1044124   .1844381     0.57   0.571    -.2570797    .4659045
          4  |   .0010158   .1253027     0.01   0.994    -.2445729    .2466044
          5  |   .0628198   .1567737     0.40   0.689    -.2444511    .3700906
          7  |   .0593883   .1102345     0.54   0.590    -.1566674     .275444
          8  |   .1065431   .1102239     0.97   0.334    -.1094919     .322578
          9  |   .0533218   .1281341     0.42   0.677    -.1978165    .3044601
         10  |  -.0359973   .0982164    -0.37   0.714    -.2284979    .1565032
         11  |    .063271   .0979908     0.65   0.518    -.1287875    .2553295
         12  |   .2519214   .1102311     2.29   0.022     .0358724    .4679704
         13  |     .20824   .1126418     1.85   0.065    -.0125339    .4290139
         14  |   .0729733   .1469962     0.50   0.620    -.2151341    .3610806
         15  |    .121196   .1168873     1.04   0.300    -.1078989    .3502909
         16  |   .0099462   .1287847     0.08   0.938    -.2424671    .2623594
         17  |  -.0856451    .107071    -0.80   0.424    -.2955004    .1242102
         18  |   .0714553   .0989787     0.72   0.470    -.1225393    .2654499
         19  |   .0409353   .1099623     0.37   0.710    -.1745868    .2564574
         20  |  -.0707522   .1694953    -0.42   0.676    -.4029569    .2614525
         21  |   .3226878   .1499695     2.15   0.031      .028753    .6166226
         22  |  -.0066886   .1176768    -0.06   0.955    -.2373309    .2239538
         23  |   .0311793   .1218641     0.26   0.798      -.20767    .2700286
         24  |  -.0514641   .1280655    -0.40   0.688    -.3024678    .1995397
         25  |   .0171644   .0985253     0.17   0.862    -.1759415    .2102704
             |
experience~g |  -.0105268   .0096251    -1.09   0.274    -.0293916     .008338
experience~q |   .0196574   .0258859     0.76   0.448    -.0310781    .0703928
share_top_~s |  -.0396102   .0590569    -0.67   0.502    -.1553596    .0761392
share_top_~d |    .058097   .0503718     1.15   0.249      -.04063     .156824
             |
     ireport |
          2  |   .1555973    .203309     0.77   0.444     -.242881    .5540757
          3  |   .1561221   .1920849     0.81   0.416    -.2203574    .5326016
          4  |   .2208672   .2041461     1.08   0.279    -.1792518    .6209861
             |
authored_s~o |  -.0987346   .0523303    -1.89   0.059    -.2013002     .003831
share_fema~s |  -.0064314   .0506837    -0.13   0.899    -.1057695    .0929068
editor_pre~t |   .0177739   .0470249     0.38   0.705    -.0743933    .1099411
------------------------------------------------------------------------------
Note: dy/dx for factor levels is the discrete change from the base level.
(est5 stored)

. 
60
estadd local Window "[`threshold'$\pm$0.35]"
estadd local Window "[1.96$\pm$0.35]"

. estadd local Window "[`threshold'$\pm$0.35]"

added macro:
             e(Window) : "[1.96$\pm$0.35]"

. 
61
sum `depvar' if t>(`threshold'-0.35) & t<(`threshold'+0.35) & method=="RCT"
sum sign_5pct if t>(1.96-0.35) & t<(1.96+0.35) & method=="RCT"

. sum `depvar' if t>(`threshold'-0.35) & t<(`threshold'+0.35
> ) & method=="RCT"

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
   sign_5pct |        829    .4788902    .4998558          0          1

. 
62
estadd local rct_sign = round(r(mean), 0.01)

. estadd local rct_sign = round(r(mean), 0.01)

added macro:
           e(rct_sign) : ".48"

. 
63
64
probit `depvar' DID IV RDD i.year i.unique_j experience_avg experience_avg_sq share_top_authors share_top_phd i.ireport authored_solo share_female_authors editor_present if t>(`threshold'-0.2) & t<(`threshold'+0.2) [`weight1'`weight2'], cluster(journal_article_cluster)
probit sign_5pct DID IV RDD i.year i.unique_j experience_avg experience_avg_sq share_top_authors share_top_phd i.ireport authored_solo share_female_authors editor_present if t>(1.96-0.2) & t<(1.96+0.2) [pw=aw], cluster(journal_article_cluster)

. probit `depvar' DID IV RDD i.year i.unique_j experience_av
> g experience_avg_sq share_top_authors share_top_phd i.ireport authored_solo s
> hare_female_authors editor_present if t>(`threshold'-0.2) & t<(`threshold'+0.
> 2) [`weight1'`weight2'], cluster(journal_article_cluster)

note: 1.ireport != 0 predicts success perfectly;
      1.ireport omitted and 2 obs not used.

note: 4.ireport omitted because of collinearity.
Iteration 0:   log pseudolikelihood = -355463.65  
Iteration 1:   log pseudolikelihood = -339163.89  
Iteration 2:   log pseudolikelihood = -339074.16  
Iteration 3:   log pseudolikelihood = -339074.15  

Probit regression                                       Number of obs =  1,585
                                                        Wald chi2(35) =  39.48
                                                        Prob > chi2   = 0.2764
Log pseudolikelihood = -339074.15                       Pseudo R2     = 0.0461

              (Std. err. adjusted for 382 clusters in journal_article_cluster)
------------------------------------------------------------------------------
             |               Robust
   sign_5pct | Coefficient  std. err.      z    P>|z|     [95% conf. interval]
-------------+----------------------------------------------------------------
         DID |  -.0964881   .1567822    -0.62   0.538    -.4037756    .2107994
          IV |   .2509065   .1353012     1.85   0.064    -.0142791    .5160921
         RDD |   .1044717   .1944235     0.54   0.591    -.2765913    .4855346
             |
        year |
       2018  |   .0628803   .1083788     0.58   0.562    -.1495382    .2752989
             |
    unique_j |
          2  |   .4421289   .4739418     0.93   0.351    -.4867799    1.371038
          3  |   .7663616   .5749897     1.33   0.183    -.3605975    1.893321
          4  |   .1554897   .3627346     0.43   0.668    -.5554571    .8664365
          5  |  -.2566929   .3436636    -0.75   0.455    -.9302612    .4168754
          7  |   .4169843   .3798307     1.10   0.272    -.3274701    1.161439
          8  |   .2814138   .3223887     0.87   0.383    -.3504565    .9132841
          9  |   .5996322   .3628387     1.65   0.098    -.1115185    1.310783
         10  |  -.1096609   .3375951    -0.32   0.745    -.7713352    .5520134
         11  |   .1573383   .3404936     0.46   0.644     -.510017    .8246935
         12  |   .6283063   .3999799     1.57   0.116    -.1556398    1.412253
         13  |   .7346479   .3554657     2.07   0.039     .0379479    1.431348
         14  |   .6212516   .4990812     1.24   0.213    -.3569297    1.599433
         15  |   .3771099   .3620881     1.04   0.298    -.3325698     1.08679
         16  |    .348219   .3378403     1.03   0.303    -.3139358    1.010374
         17  |  -1.332629   .8223676    -1.62   0.105     -2.94444    .2791815
         18  |    .283486   .3003785     0.94   0.345    -.3052451    .8722171
         19  |   .4831164   .3747499     1.29   0.197    -.2513799    1.217613
         20  |   .1832293   .5441272     0.34   0.736    -.8832405    1.249699
         21  |   .1381565     .32404     0.43   0.670    -.4969502    .7732632
         22  |    .030599   .3645257     0.08   0.933    -.6838582    .7450562
         23  |   .2263885   .3299362     0.69   0.493    -.4202745    .8730515
         24  |   .1596085   .3719585     0.43   0.668    -.5694168    .8886338
         25  |   .1191819   .3098103     0.38   0.700    -.4880351    .7263989
             |
experience~g |  -.0005587   .0296723    -0.02   0.985    -.0587152    .0575979
experience~q |  -.0114865   .0853756    -0.13   0.893    -.1788197    .1558466
share_top_~s |  -.2123991   .1831683    -1.16   0.246    -.5714024    .1466041
share_top_~d |   .3849395   .1648651     2.33   0.020     .0618099    .7080692
             |
     ireport |
          3  |   .1116569   .1444979     0.77   0.440    -.1715539    .3948676
          4  |          0  (omitted)
             |
authored_s~o |  -.1546806   .1687515    -0.92   0.359    -.4854274    .1760662
share_fema~s |  -.0163136   .1540992    -0.11   0.916    -.3183424    .2857153
editor_pre~t |  -.0630015    .154652    -0.41   0.684    -.3661138    .2401108
       _cons |  -.3815988   .3556943    -1.07   0.283    -1.078747    .3155493
------------------------------------------------------------------------------

. 
65
eststo : margins, dydx(*) post

. eststo : margins, dydx(*) post

Average marginal effects                                 Number of obs = 1,585
Model VCE: Robust

Expression: Pr(sign_5pct), predict()
dy/dx wrt:  DID IV RDD 2018.year 2.unique_j 3.unique_j 4.unique_j 5.unique_j
            7.unique_j 8.unique_j 9.unique_j 10.unique_j 11.unique_j
            12.unique_j 13.unique_j 14.unique_j 15.unique_j 16.unique_j
            17.unique_j 18.unique_j 19.unique_j 20.unique_j 21.unique_j
            22.unique_j 23.unique_j 24.unique_j 25.unique_j experience_avg
            experience_avg_sq share_top_authors share_top_phd 3.ireport
            4.ireport authored_solo share_female_authors editor_present

------------------------------------------------------------------------------
             |            Delta-method
             |      dy/dx   std. err.      z    P>|z|     [95% conf. interval]
-------------+----------------------------------------------------------------
         DID |  -.0363211   .0589632    -0.62   0.538    -.1518869    .0792446
          IV |    .094449   .0502584     1.88   0.060    -.0040556    .1929537
         RDD |   .0393264   .0731264     0.54   0.591    -.1039988    .1826516
             |
        year |
       2018  |          .  (not estimable)
             |
    unique_j |
          2  |          .  (not estimable)
          3  |          .  (not estimable)
          4  |          .  (not estimable)
          5  |          .  (not estimable)
          7  |          .  (not estimable)
          8  |          .  (not estimable)
          9  |          .  (not estimable)
         10  |          .  (not estimable)
         11  |          .  (not estimable)
         12  |          .  (not estimable)
         13  |          .  (not estimable)
         14  |          .  (not estimable)
         15  |          .  (not estimable)
         16  |          .  (not estimable)
         17  |          .  (not estimable)
         18  |          .  (not estimable)
         19  |          .  (not estimable)
         20  |          .  (not estimable)
         21  |          .  (not estimable)
         22  |          .  (not estimable)
         23  |          .  (not estimable)
         24  |          .  (not estimable)
         25  |          .  (not estimable)
             |
experience~g |  -.0002103   .0111699    -0.02   0.985    -.0221028    .0216822
experience~q |  -.0043239   .0321318    -0.13   0.893     -.067301    .0586532
share_top_~s |  -.0799536   .0686192    -1.17   0.244    -.2144448    .0545376
share_top_~d |   .1449032   .0613735     2.36   0.018     .0246134     .265193
             |
     ireport |
          3  |          .  (not estimable)
          4  |          .  (not estimable)
             |
authored_s~o |  -.0582266   .0634362    -0.92   0.359    -.1825593    .0661061
share_fema~s |  -.0061409   .0580097    -0.11   0.916    -.1198379    .1075561
editor_pre~t |  -.0237157    .058194    -0.41   0.684     -.137774    .0903425
------------------------------------------------------------------------------
Note: dy/dx for factor levels is the discrete change from the base level.
(est6 stored)

. 
66
estadd local Window "[`threshold'$\pm$0.20]"
estadd local Window "[1.96$\pm$0.20]"

. estadd local Window "[`threshold'$\pm$0.20]"

added macro:
             e(Window) : "[1.96$\pm$0.20]"

. 
67
sum `depvar' if t>(`threshold'-0.2) & t<(`threshold'+0.2) & method=="RCT"
sum sign_5pct if t>(1.96-0.2) & t<(1.96+0.2) & method=="RCT"

. sum `depvar' if t>(`threshold'-0.2) & t<(`threshold'+0.2) 
> & method=="RCT"

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
   sign_5pct |        501    .4870259    .5003312          0          1

. 
68
estadd local rct_sign = round(r(mean), 0.01)

. estadd local rct_sign = round(r(mean), 0.01)

added macro:
           e(rct_sign) : ".49"

. 
69
70
esttab, margin ///
esttab, margin keep(DID IV RDD top5 2018.year experience_avg experience_avg_sq share_top_authors share_top_phd ) label stats(N Window rct_sign, fmt(%9.0fc) labels("Observations" "Window" "RCT sig rate"))

. esttab, margin keep(DID IV RDD top5 2018.year experience_a
> vg experience_avg_sq share_top_authors share_top_phd ) label stats(N Window r
> ct_sign, fmt(%9.0fc) labels("Observations" "Window" "RCT sig rate"))

-------------------------------------------------------------------------------
> -------------------------------------
                              (1)             (2)             (3)             (
> 4)             (5)             (6)   
                                                                               
>                                      
-------------------------------------------------------------------------------
> -------------------------------------
DID                        0.0556          0.0454          0.0292          0.02
> 82          0.0242         -0.0363   
                           (1.45)          (1.16)          (0.73)          (0.6
> 9)          (0.54)         (-0.62)   

IV                          0.101**        0.0998**        0.0790*         0.08
> 41*         0.0974*         0.0944   
                           (2.98)          (2.72)          (2.08)          (2.2
> 3)          (2.35)          (1.88)   

RDD                        0.0939          0.0824          0.0689          0.06
> 89          0.0736          0.0393   
                           (1.48)          (1.35)          (1.18)          (1.1
> 8)          (1.22)          (0.54)   

Top 5                                     -0.0281         -0.0207              
>                                      
                                          (-0.52)         (-0.19)              
>                                      

Year=2018                                 0.00616          0.0126          0.02
> 17        -0.00399               0   
                                           (0.19)          (0.38)          (0.6
> 3)         (-0.11)             (.)   

Experience                               -0.00760         -0.0134         -0.01
> 32         -0.0105       -0.000210   
                                          (-0.92)         (-1.58)         (-1.5
> 7)         (-1.09)         (-0.02)   

Experience squared                        0.00227          0.0174          0.01
> 97          0.0197        -0.00432   
                                           (0.11)          (0.79)          (0.9
> 0)          (0.76)         (-0.13)   

Top institution                          -0.00138         0.00266         0.001
> 79         -0.0396         -0.0800   
                                          (-0.03)          (0.05)          (0.0
> 3)         (-0.67)         (-1.17)   

Top PhD institution                        0.0144         -0.0135         -0.01
> 28          0.0581           0.145*  
                                           (0.32)         (-0.30)         (-0.2
> 8)          (1.15)          (2.36)   
-------------------------------------------------------------------------------
> -------------------------------------
Observations                3,558           3,558           3,558           3,5
> 58           2,626           1,585   
Window               [1.96$\pm$0.50]    [1.96$\pm$0.50]    [1.96$\pm$0.50]    [
> 1.96$\pm$0.50]    [1.96$\pm$0.35]    [1.96$\pm$0.20]   
RCT sig rate                  .47             .47             .47             .
> 47             .48             .49   
-------------------------------------------------------------------------------
> -------------------------------------
Marginal effects; t statistics in parentheses
 (d) for discrete change of dummy variable from 0 to 1
* p<0.05, ** p<0.01, *** p<0.001

. 
71
keep(DID IV RDD top5 2018.year experience_avg experience_avg_sq share_top_authors share_top_phd ) label stats(N Window rct_sign, fmt(%9.0fc) labels("Observations" "Window" "RCT sig rate"))
72
73
esttab using table_2_caliper_`depvar'.tex, margin ///
esttab using table_2_caliper_sign_5pct.tex, margin keep(DID IV RDD top5 2018.year experience_avg experience_avg_sq share_top_authors share_top_phd) label  stats(N Window rct_sign, fmt(%9.0fc) labels("Observations" "Window" "RCT sig rate")) mtitles() nomtitles nostar compress se(3) b(3) replace nogaps noomitted indicate( "Reporting Method = *ireport" "Solo Authored = authored_solo" "Share Female Authors = share_female_authors" "Editor = editor_present" "Field FE = FINANCE" "Journal FE = *unique_j" , labels("Y" " ")) nonotes

. esttab using "table_2_caliper_sign_5pct.tex", margin keep(DID IV 
> RDD top5 2018.year experience_avg experience_avg_sq share_top_authors share_t
> op_phd) label  stats(N Window rct_sign, fmt(%9.0fc) labels("Observations" "Wi
> ndow" "RCT sig rate")) mtitles() nomtitles nostar compress se(3) b(3) replace
>  nogaps noomitted indicate( "Reporting Method = *ireport" "Solo Authored = au
> thored_solo" "Share Female Authors = share_female_authors" "Editor = editor_p
> resent" "Field FE = FINANCE" "Journal FE = *unique_j" , labels("Y" " ")) nono
> tes
(output written to table_2_caliper_sign_5pct.tex)

. 
74
keep(DID IV RDD top5 2018.year experience_avg experience_avg_sq share_top_authors share_top_phd) label  stats(N Window rct_sign, fmt(%9.0fc) labels("Observations" "Window" "RCT sig rate")) ///
75
mtitles() nomtitles nostar ///
76
 compress se(3) b(3) replace nogaps noomitted ///
77
indicate( ///
78
"Reporting Method = *ireport" ///
79
"Solo Authored = authored_solo" ///
80
"Share Female Authors = share_female_authors" ///
81
"Editor = editor_present" ///
82
"Field FE = FINANCE" ///
83
"Journal FE = *unique_j" ///
84
, labels("Y" " ")) ///
85
nonotes
86
87
88
89
** Table A5: 5% significance treshold
90
91
* read in the data
92
cd "$dir_data" 
cd "/home/rstudio/repbox/projects_ejd/aer_112_9_9/mod/Scripts/Data"

. cd "${repbox_path}/Data"
/home/rstudio/repbox/projects_ejd/aer_112_9_9/mod/Data

. 
93
capture use "MM_new.dta", clear 

. capture use "MM_new.dta", clear

. 
94
95
* determine folder to store results
96
cd "$dir_results" 
cd "/home/rstudio/repbox/projects_ejd/aer_112_9_9/mod/Scripts/Results"

. cd "${repbox_path}/Results"
/home/rstudio/repbox/projects_ejd/aer_112_9_9/mod/Results

. 
97
98
99
* drop obs with small significand
100
keep if keep_obs==1

. keep if keep_obs==1
(8,233 observations deleted)

. 
101
102
* first: 5% threshold
103
104
	local depvar "sign_10pct"

. local depvar "sign_10pct"

. 
105
	local threshold 1.65

. local threshold 1.65

. 
106
	local weight1 "pw="

. local weight1 "pw="

. 
107
	local weight2 "aw"

. local weight2 "aw"

. 
108
109
110
eststo clear

. eststo clear

. 
111
112
probit `depvar' DID IV RDD if t>(`threshold'-0.5) & t<(`threshold'+0.5) [`weight1'`weight2'], cluster(journal_article_cluster)
probit sign_10pct DID IV RDD if t>(1.65-0.5) & t<(1.65+0.5) [pw=aw], cluster(journal_article_cluster)

. probit `depvar' DID IV RDD if t>(`threshold'-0.5) & t<(`th
> reshold'+0.5) [`weight1'`weight2'], cluster(journal_article_cluster)

Iteration 0:   log pseudolikelihood = -658201.09  
Iteration 1:   log pseudolikelihood = -653009.87  
Iteration 2:   log pseudolikelihood =  -653009.5  
Iteration 3:   log pseudolikelihood =  -653009.5  

Probit regression                                       Number of obs =  3,470
                                                        Wald chi2(3)  =  12.36
                                                        Prob > chi2   = 0.0062
Log pseudolikelihood = -653009.5                        Pseudo R2     = 0.0079

              (Std. err. adjusted for 446 clusters in journal_article_cluster)
------------------------------------------------------------------------------
             |               Robust
  sign_10pct | Coefficient  std. err.      z    P>|z|     [95% conf. interval]
-------------+----------------------------------------------------------------
         DID |   .2674024   .1183662     2.26   0.024     .0354088    .4993959
          IV |   .3088297   .0997324     3.10   0.002     .1133578    .5043016
         RDD |   .0401727   .1131901     0.35   0.723    -.1816758    .2620213
       _cons |   .1222091   .0587997     2.08   0.038     .0069638    .2374544
------------------------------------------------------------------------------

. 
113
eststo : margins, dydx(*) post

. eststo : margins, dydx(*) post

Average marginal effects                                 Number of obs = 3,470
Model VCE: Robust

Expression: Pr(sign_10pct), predict()
dy/dx wrt:  DID IV RDD

------------------------------------------------------------------------------
             |            Delta-method
             |      dy/dx   std. err.      z    P>|z|     [95% conf. interval]
-------------+----------------------------------------------------------------
         DID |   .1001962   .0435242     2.30   0.021     .0148903     .185502
          IV |    .115719   .0361463     3.20   0.001     .0448736    .1865645
         RDD |   .0150528   .0424067     0.35   0.723    -.0680628    .0981684
------------------------------------------------------------------------------
(est1 stored)

. 
114
estadd local Window "[`threshold'$\pm$0.50]"
estadd local Window "[1.65$\pm$0.50]"

. estadd local Window "[`threshold'$\pm$0.50]"

added macro:
             e(Window) : "[1.65$\pm$0.50]"

. 
115
sum `depvar' if t>(`threshold'-0.5) & t<(`threshold'+0.5) & method=="RCT"
sum sign_10pct if t>(1.65-0.5) & t<(1.65+0.5) & method=="RCT"

. sum `depvar' if t>(`threshold'-0.5) & t<(`threshold'+0.5) 
> & method=="RCT"

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
  sign_10pct |      1,216    .5164474     .499935          0          1

. 
116
estadd local rct_sign = round(r(mean), 0.01)

. estadd local rct_sign = round(r(mean), 0.01)

added macro:
           e(rct_sign) : ".52"

. 
117
118
probit `depvar' DID IV RDD top5 i.year experience_avg experience_avg_sq share_top_authors share_top_phd i.ireport authored_solo share_female_authors editor_present if t>(`threshold'-0.5) & t<(`threshold'+0.5) [`weight1'`weight2'], cluster(journal_article_cluster)
probit sign_10pct DID IV RDD top5 i.year experience_avg experience_avg_sq share_top_authors share_top_phd i.ireport authored_solo share_female_authors editor_present if t>(1.65-0.5) & t<(1.65+0.5) [pw=aw], cluster(journal_article_cluster)

. probit `depvar' DID IV RDD top5 i.year experience_avg expe
> rience_avg_sq share_top_authors share_top_phd i.ireport authored_solo share_f
> emale_authors editor_present if t>(`threshold'-0.5) & t<(`threshold'+0.5) [`w
> eight1'`weight2'], cluster(journal_article_cluster)

Iteration 0:   log pseudolikelihood = -658201.09  
Iteration 1:   log pseudolikelihood = -646729.81  
Iteration 2:   log pseudolikelihood =  -646713.3  
Iteration 3:   log pseudolikelihood = -646713.29  

Probit regression                                       Number of obs =  3,470
                                                        Wald chi2(15) =  24.53
                                                        Prob > chi2   = 0.0566
Log pseudolikelihood = -646713.29                       Pseudo R2     = 0.0175

              (Std. err. adjusted for 446 clusters in journal_article_cluster)
------------------------------------------------------------------------------
             |               Robust
  sign_10pct | Coefficient  std. err.      z    P>|z|     [95% conf. interval]
-------------+----------------------------------------------------------------
         DID |   .3054278   .1103157     2.77   0.006     .0892129    .5216426
          IV |    .340464   .1044438     3.26   0.001     .1357579    .5451702
         RDD |   .0232021   .1105085     0.21   0.834    -.1933906    .2397947
        top5 |   .1614665   .1314808     1.23   0.219    -.0962312    .4191643
             |
        year |
       2018  |   .0084053   .0934317     0.09   0.928    -.1747174     .191528
             |
experience~g |  -.0049399   .0238661    -0.21   0.836    -.0517165    .0418367
experience~q |  -.0087031   .0724233    -0.12   0.904    -.1506502    .1332441
share_top_~s |   -.154885   .1321336    -1.17   0.241     -.413862     .104092
share_top_~d |   -.043656   .1226124    -0.36   0.722    -.2839718    .1966599
             |
     ireport |
          2  |  -.3662434   .7540036    -0.49   0.627    -1.844063    1.111577
          3  |  -.5069767   .7335503    -0.69   0.489    -1.944709    .9307555
          4  |  -.7354124    .757664    -0.97   0.332    -2.220407    .7495818
             |
authored_s~o |   .0978376   .1332095     0.73   0.463    -.1632481    .3589233
share_fema~s |   .1324691   .1483577     0.89   0.372    -.1583066    .4232448
editor_pre~t |   .0293531    .125409     0.23   0.815    -.2164439    .2751501
       _cons |   .6414197   .7700302     0.83   0.405    -.8678117    2.150651
------------------------------------------------------------------------------

. 
119
eststo : margins, dydx(*) post

. eststo : margins, dydx(*) post

Average marginal effects                                 Number of obs = 3,470
Model VCE: Robust

Expression: Pr(sign_10pct), predict()
dy/dx wrt:  DID IV RDD top5 2018.year experience_avg experience_avg_sq
            share_top_authors share_top_phd 2.ireport 3.ireport 4.ireport
            authored_solo share_female_authors editor_present

------------------------------------------------------------------------------
             |            Delta-method
             |      dy/dx   std. err.      z    P>|z|     [95% conf. interval]
-------------+----------------------------------------------------------------
         DID |   .1132788   .0401968     2.82   0.005     .0344945    .1920632
          IV |   .1262733   .0375258     3.36   0.001     .0527242    .1998224
         RDD |   .0086053   .0409854     0.21   0.834    -.0717246    .0889352
        top5 |   .0598857    .048525     1.23   0.217    -.0352215    .1549928
             |
        year |
       2018  |   .0031182   .0346647     0.09   0.928    -.0648232    .0710597
             |
experience~g |  -.0018321   .0088484    -0.21   0.836    -.0191746    .0155104
experience~q |  -.0032278   .0268643    -0.12   0.904    -.0558809    .0494252
share_top_~s |  -.0574446   .0487798    -1.18   0.239    -.1530512    .0381619
share_top_~d |  -.0161914   .0454562    -0.36   0.722    -.1052839    .0729012
             |
     ireport |
          2  |  -.1152325   .2114157    -0.55   0.586    -.5295997    .2991347
          3  |  -.1659906   .2026644    -0.82   0.413    -.5632055    .2312242
          4  |  -.2532284   .2159417    -1.17   0.241    -.6764663    .1700094
             |
authored_s~o |   .0362866   .0493765     0.73   0.462    -.0604895    .1330627
share_fema~s |   .0491309   .0549052     0.89   0.371    -.0584813    .1567432
editor_pre~t |   .0108866   .0464877     0.23   0.815    -.0802276    .1020008
------------------------------------------------------------------------------
Note: dy/dx for factor levels is the discrete change from the base level.
(est2 stored)

. 
120
estadd local Window "[`threshold'$\pm$0.50]"
estadd local Window "[1.65$\pm$0.50]"

. estadd local Window "[`threshold'$\pm$0.50]"

added macro:
             e(Window) : "[1.65$\pm$0.50]"

. 
121
sum `depvar' if t>(`threshold'-0.5) & t<(`threshold'+0.5) & method=="RCT"
sum sign_10pct if t>(1.65-0.5) & t<(1.65+0.5) & method=="RCT"

. sum `depvar' if t>(`threshold'-0.5) & t<(`threshold'+0.5) 
> & method=="RCT"

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
  sign_10pct |      1,216    .5164474     .499935          0          1

. 
122
estadd local rct_sign = round(r(mean), 0.01)

. estadd local rct_sign = round(r(mean), 0.01)

added macro:
           e(rct_sign) : ".52"

. 
123
124
probit `depvar' DID IV RDD top5 i.year FINANCE MACRO_GROWTH GEN_INT EXP DEV LABOR PUB URB experience_avg experience_avg_sq share_top_authors share_top_phd i.ireport authored_solo share_female_authors editor_present if t>(`threshold'-0.5) & t<(`threshold'+0.5) [`weight1'`weight2'], cluster(journal_article_cluster)
probit sign_10pct DID IV RDD top5 i.year FINANCE MACRO_GROWTH GEN_INT EXP DEV LABOR PUB URB experience_avg experience_avg_sq share_top_authors share_top_phd i.ireport authored_solo share_female_authors editor_present if t>(1.65-0.5) & t<(1.65+0.5) [pw=aw], cluster(journal_article_cluster)

. probit `depvar' DID IV RDD top5 i.year FINANCE MACRO_GROWT
> H GEN_INT EXP DEV LABOR PUB URB experience_avg experience_avg_sq share_top_au
> thors share_top_phd i.ireport authored_solo share_female_authors editor_prese
> nt if t>(`threshold'-0.5) & t<(`threshold'+0.5) [`weight1'`weight2'], cluster
> (journal_article_cluster)

Iteration 0:   log pseudolikelihood = -658201.09  
Iteration 1:   log pseudolikelihood = -640456.59  
Iteration 2:   log pseudolikelihood = -640307.62  
Iteration 3:   log pseudolikelihood = -640306.84  
Iteration 4:   log pseudolikelihood = -640306.84  

Probit regression                                       Number of obs =  3,470
                                                        Wald chi2(23) =  43.62
                                                        Prob > chi2   = 0.0058
Log pseudolikelihood = -640306.84                       Pseudo R2     = 0.0272

              (Std. err. adjusted for 446 clusters in journal_article_cluster)
------------------------------------------------------------------------------
             |               Robust
  sign_10pct | Coefficient  std. err.      z    P>|z|     [95% conf. interval]
-------------+----------------------------------------------------------------
         DID |   .2942549   .1133104     2.60   0.009     .0721707    .5163391
          IV |   .2744547   .1118847     2.45   0.014     .0551647    .4937447
         RDD |   .0122454   .1194844     0.10   0.918    -.2219398    .2464306
        top5 |  -.1289498   .2771565    -0.47   0.642    -.6721665    .4142669
             |
        year |
       2018  |   .0278961   .0924776     0.30   0.763    -.1533567    .2091489
             |
     FINANCE |  -.1095336   .2731278    -0.40   0.688    -.6448544    .4257871
MACRO_GROWTH |   .3437249   .5542687     0.62   0.535    -.7426217    1.430072
     GEN_INT |  -.2988225   .2516392    -1.19   0.235    -.7920262    .1943812
         EXP |   .9774686   .5401224     1.81   0.070    -.0811518    2.036089
         DEV |   -.410228   .2848745    -1.44   0.150    -.9685718    .1481158
       LABOR |  -.2500453   .3250758    -0.77   0.442    -.8871821    .3870915
         PUB |  -.3855273   .2648781    -1.46   0.146    -.9046789    .1336242
         URB |  -.5564295   .2934216    -1.90   0.058    -1.131525    .0186662
experience~g |  -.0150776   .0233984    -0.64   0.519    -.0609377    .0307825
experience~q |   .0214136   .0705808     0.30   0.762    -.1169223    .1597496
share_top_~s |   -.120671   .1339409    -0.90   0.368    -.3831903    .1418482
share_top_~d |  -.0882738   .1217286    -0.73   0.468    -.3268574    .1503098
             |
     ireport |
          2  |  -.4416945   .7565664    -0.58   0.559    -1.924537    1.041148
          3  |  -.5465874   .7397134    -0.74   0.460    -1.996399    .9032242
          4  |  -.9035389   .7719247    -1.17   0.242    -2.416483    .6094056
             |
authored_s~o |   .0506023   .1361734     0.37   0.710    -.2162927    .3174973
share_fema~s |    .125262   .1374177     0.91   0.362    -.1440718    .3945958
editor_pre~t |   .0017211   .1270381     0.01   0.989    -.2472689    .2507112
       _cons |   1.100199   .8282919     1.33   0.184    -.5232229    2.723622
------------------------------------------------------------------------------

. 
125
eststo : margins, dydx(*) post

. eststo : margins, dydx(*) post

Average marginal effects                                 Number of obs = 3,470
Model VCE: Robust

Expression: Pr(sign_10pct), predict()
dy/dx wrt:  DID IV RDD top5 2018.year FINANCE MACRO_GROWTH GEN_INT EXP DEV
            LABOR PUB URB experience_avg experience_avg_sq share_top_authors
            share_top_phd 2.ireport 3.ireport 4.ireport authored_solo
            share_female_authors editor_present

------------------------------------------------------------------------------
             |            Delta-method
             |      dy/dx   std. err.      z    P>|z|     [95% conf. interval]
-------------+----------------------------------------------------------------
         DID |   .1080061    .041033     2.63   0.008     .0275828    .1884294
          IV |   .1007385   .0401824     2.51   0.012     .0219824    .1794946
         RDD |   .0044947   .0438523     0.10   0.918    -.0814542    .0904435
        top5 |   -.047331   .1018554    -0.46   0.642     -.246964     .152302
             |
        year |
       2018  |   .0102479   .0339954     0.30   0.763    -.0563819    .0768777
             |
     FINANCE |  -.0402043   .1003217    -0.40   0.689    -.2368311    .1564226
MACRO_GROWTH |   .1261641   .2031288     0.62   0.535     -.271961    .5242891
     GEN_INT |  -.1096827   .0924311    -1.19   0.235    -.2908443     .071479
         EXP |   .3587794    .198456     1.81   0.071    -.0301873     .747746
         DEV |   -.150574   .1047323    -1.44   0.151    -.3558456    .0546976
       LABOR |   -.091779   .1193533    -0.77   0.442    -.3257071    .1421491
         PUB |  -.1415076   .0972772    -1.45   0.146    -.3321674    .0491522
         URB |  -.2042372   .1074175    -1.90   0.057    -.4147717    .0062973
experience~g |  -.0055342   .0085814    -0.64   0.519    -.0223534    .0112849
experience~q |   .0078599   .0259021     0.30   0.762    -.0429074    .0586271
share_top_~s |  -.0442922   .0490166    -0.90   0.366     -.140363    .0517786
share_top_~d |  -.0324008   .0446365    -0.73   0.468    -.1198867     .055085
             |
     ireport |
          2  |  -.1360979   .2015814    -0.68   0.500    -.5311902    .2589944
          3  |  -.1735551    .194067    -0.89   0.371    -.5539195    .2068093
          4  |  -.3091124   .2109962    -1.47   0.143    -.7226574    .1044325
             |
authored_s~o |   .0185736   .0499735     0.37   0.710    -.0793726    .1165198
share_fema~s |   .0459774      .0504     0.91   0.362    -.0528048    .1447595
editor_pre~t |   .0006317   .0466283     0.01   0.989    -.0907581    .0920216
------------------------------------------------------------------------------
Note: dy/dx for factor levels is the discrete change from the base level.
(est3 stored)

. 
126
estadd local Window "[`threshold'$\pm$0.50]"
estadd local Window "[1.65$\pm$0.50]"

. estadd local Window "[`threshold'$\pm$0.50]"

added macro:
             e(Window) : "[1.65$\pm$0.50]"

. 
127
sum `depvar' if t>(`threshold'-0.5) & t<(`threshold'+0.5) & method=="RCT"
sum sign_10pct if t>(1.65-0.5) & t<(1.65+0.5) & method=="RCT"

. sum `depvar' if t>(`threshold'-0.5) & t<(`threshold'+0.5) 
> & method=="RCT"

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
  sign_10pct |      1,216    .5164474     .499935          0          1

. 
128
estadd local rct_sign = round(r(mean), 0.01)

. estadd local rct_sign = round(r(mean), 0.01)

added macro:
           e(rct_sign) : ".52"

. 
129
130
probit `depvar' DID IV RDD i.year i.unique_j experience_avg experience_avg_sq share_top_authors share_top_phd i.ireport authored_solo share_female_authors editor_present if t>(`threshold'-0.5) & t<(`threshold'+0.5) [`weight1'`weight2'], cluster(journal_article_cluster)
probit sign_10pct DID IV RDD i.year i.unique_j experience_avg experience_avg_sq share_top_authors share_top_phd i.ireport authored_solo share_female_authors editor_present if t>(1.65-0.5) & t<(1.65+0.5) [pw=aw], cluster(journal_article_cluster)

. probit `depvar' DID IV RDD i.year i.unique_j experience_av
> g experience_avg_sq share_top_authors share_top_phd i.ireport authored_solo s
> hare_female_authors editor_present if t>(`threshold'-0.5) & t<(`threshold'+0.
> 5) [`weight1'`weight2'], cluster(journal_article_cluster)

note: 6.unique_j != 0 predicts failure perfectly;
      6.unique_j omitted and 1 obs not used.

Iteration 0:   log pseudolikelihood = -657374.36  
Iteration 1:   log pseudolikelihood = -629017.21  
Iteration 2:   log pseudolikelihood = -628721.33  
Iteration 3:   log pseudolikelihood = -628720.44  
Iteration 4:   log pseudolikelihood = -628720.44  

Probit regression                                       Number of obs =  3,469
                                                        Wald chi2(37) =  75.75
                                                        Prob > chi2   = 0.0002
Log pseudolikelihood = -628720.44                       Pseudo R2     = 0.0436

              (Std. err. adjusted for 445 clusters in journal_article_cluster)
------------------------------------------------------------------------------
             |               Robust
  sign_10pct | Coefficient  std. err.      z    P>|z|     [95% conf. interval]
-------------+----------------------------------------------------------------
         DID |   .3067344   .1165659     2.63   0.009     .0782694    .5351995
          IV |   .3094702   .1156761     2.68   0.007     .0827491    .5361912
         RDD |   .0141679    .124399     0.11   0.909    -.2296496    .2579855
             |
        year |
       2018  |   .0545419   .0956883     0.57   0.569    -.1330038    .2420876
             |
    unique_j |
          2  |  -.3307762   .3816209    -0.87   0.386    -1.078739     .417187
          3  |   .0219097   .3516636     0.06   0.950    -.6673382    .7111576
          4  |   -.027792   .2757375    -0.10   0.920    -.5682277    .5126436
          5  |   -.268534   .3742118    -0.72   0.473    -1.001976    .4649077
          7  |   .5594341   .6126629     0.91   0.361    -.6413631    1.760231
          8  |  -.3459349   .2533849    -1.37   0.172    -.8425602    .1506904
          9  |  -.1214621   .2733101    -0.44   0.657    -.6571401    .4142159
         10  |   .3881216   .3654681     1.06   0.288    -.3281827    1.104426
         11  |  -.2545579   .2253984    -1.13   0.259    -.6963307    .1872149
         12  |   .0324593   .2896925     0.11   0.911    -.5353276    .6002462
         13  |  -.3054428   .2736658    -1.12   0.264    -.8418178    .2309323
         14  |  -.0343718   .3058782    -0.11   0.911     -.633882    .5651384
         15  |  -.6641387   .2789404    -2.38   0.017    -1.210852   -.1174255
         16  |   .0130772   .2929312     0.04   0.964    -.5610574    .5872117
         17  |   .9674764    .525976     1.84   0.066    -.0634176     1.99837
         18  |  -.4258668   .2305086    -1.85   0.065    -.8776553    .0259217
         19  |  -.2479698   .2987351    -0.83   0.407    -.8334798    .3375402
         20  |    .601708   .3685704     1.63   0.103    -.1206767    1.324093
         21  |   .6619555    .940323     0.70   0.481    -1.181044    2.504955
         22  |  -.4065839    .268071    -1.52   0.129    -.9319934    .1188256
         23  |  -.0403292   .2361529    -0.17   0.864    -.5031804     .422522
         24  |  -.5686039    .254211    -2.24   0.025    -1.066848   -.0703595
         25  |  -.4890831   .2333259    -2.10   0.036    -.9463934   -.0317727
             |
experience~g |  -.0182684   .0228858    -0.80   0.425    -.0631238    .0265871
experience~q |   .0242088   .0671281     0.36   0.718    -.1073599    .1557775
share_top_~s |  -.1080948   .1346331    -0.80   0.422    -.3719709    .1557813
share_top_~d |  -.1238134   .1205535    -1.03   0.304    -.3600939     .112467
             |
     ireport |
          2  |   .2282544    .861652     0.26   0.791    -1.460552    1.917061
          3  |   .1490447   .8503858     0.18   0.861    -1.517681     1.81577
          4  |  -.2435608   .8794555    -0.28   0.782    -1.967262     1.48014
             |
authored_s~o |   .0647148   .1372601     0.47   0.637    -.2043102    .3337397
share_fema~s |   .1430325   .1369329     1.04   0.296    -.1253511    .4114161
editor_pre~t |   .0236931   .1276777     0.19   0.853    -.2265505    .2739367
       _cons |    .398202   .8670902     0.46   0.646    -1.301263    2.097667
------------------------------------------------------------------------------

. 
131
eststo : margins, dydx(*) post

. eststo : margins, dydx(*) post

Average marginal effects                                 Number of obs = 3,469
Model VCE: Robust

Expression: Pr(sign_10pct), predict()
dy/dx wrt:  DID IV RDD 2018.year 2.unique_j 3.unique_j 4.unique_j 5.unique_j
            7.unique_j 8.unique_j 9.unique_j 10.unique_j 11.unique_j
            12.unique_j 13.unique_j 14.unique_j 15.unique_j 16.unique_j
            17.unique_j 18.unique_j 19.unique_j 20.unique_j 21.unique_j
            22.unique_j 23.unique_j 24.unique_j 25.unique_j experience_avg
            experience_avg_sq share_top_authors share_top_phd 2.ireport
            3.ireport 4.ireport authored_solo share_female_authors
            editor_present

------------------------------------------------------------------------------
             |            Delta-method
             |      dy/dx   std. err.      z    P>|z|     [95% conf. interval]
-------------+----------------------------------------------------------------
         DID |   .1105029   .0414564     2.67   0.008     .0292499    .1917559
          IV |   .1114885   .0407369     2.74   0.006     .0316456    .1913313
         RDD |   .0051041   .0448056     0.11   0.909    -.0827133    .0929215
             |
        year |
       2018  |   .0196757   .0345658     0.57   0.569    -.0480721    .0874236
             |
    unique_j |
          2  |  -.1179246   .1403233    -0.84   0.401    -.3929533    .1571041
          3  |   .0071871   .1150011     0.06   0.950     -.218211    .2325852
          4  |  -.0092454   .0917467    -0.10   0.920    -.1890658    .1705749
          5  |  -.0946056    .135259    -0.70   0.484    -.3597084    .1704971
          7  |   .1513191   .1368665     1.11   0.269    -.1169344    .4195725
          8  |  -.1236623   .0894426    -1.38   0.167    -.2989666     .051642
          9  |  -.0414059   .0933564    -0.44   0.657    -.2243811    .1415693
         10  |   .1124645   .0997144     1.13   0.259    -.0829721    .3079012
         11  |  -.0894279   .0772883    -1.16   0.247    -.2409102    .0620544
         12  |    .010615   .0946358     0.11   0.911    -.1748678    .1960979
         13  |  -.1083848   .0966677    -1.12   0.262    -.2978501    .0810805
         14  |  -.0114549    .102104    -0.11   0.911    -.2115751    .1886652
         15  |  -.2469285   .1007434    -2.45   0.014    -.4443819    -.049475
         16  |   .0043007   .0963072     0.04   0.964    -.1844579    .1930592
         17  |   .2178429   .0867576     2.51   0.012     .0478012    .3878847
         18  |   -.154228   .0806022    -1.91   0.056    -.3122053    .0037494
         19  |  -.0869952   .1056579    -0.82   0.410    -.2940809    .1200904
         20  |   .1598717   .0889608     1.80   0.072    -.0144884    .3342317
         21  |   .1713664   .1784299     0.96   0.337    -.1783498    .5210827
         22  |  -.1468116   .0959282    -1.53   0.126    -.3348274    .0412042
         23  |  -.0134621   .0785457    -0.17   0.864     -.167409    .1404847
         24  |  -.2096611   .0909498    -2.31   0.021    -.3879193   -.0314028
         25  |  -.1786875   .0820988    -2.18   0.030    -.3395982   -.0177768
             |
experience~g |  -.0065813   .0082354    -0.80   0.424    -.0227224    .0095598
experience~q |   .0087214   .0241772     0.36   0.718    -.0386652    .0561079
share_top_~s |  -.0389418   .0483934    -0.80   0.421     -.133791    .0559074
share_top_~d |  -.0446045   .0433913    -1.03   0.304    -.1296499    .0404409
             |
     ireport |
          2  |   .0819634   .3183557     0.26   0.797    -.5420022     .705929
          3  |   .0541999   .3148587     0.17   0.863    -.5629119    .6713116
          4  |  -.0917247   .3265767    -0.28   0.779    -.7318034    .5483539
             |
authored_s~o |   .0233139   .0494329     0.47   0.637    -.0735729    .1202007
share_fema~s |   .0515283   .0492539     1.05   0.295    -.0450075    .1480641
editor_pre~t |   .0085356   .0459791     0.19   0.853    -.0815819     .098653
------------------------------------------------------------------------------
Note: dy/dx for factor levels is the discrete change from the base level.
(est4 stored)

. 
132
estadd local Window "[`threshold'$\pm$0.50]"
estadd local Window "[1.65$\pm$0.50]"

. estadd local Window "[`threshold'$\pm$0.50]"

added macro:
             e(Window) : "[1.65$\pm$0.50]"

. 
133
sum `depvar' if t>(`threshold'-0.5) & t<(`threshold'+0.5) & method=="RCT"
sum sign_10pct if t>(1.65-0.5) & t<(1.65+0.5) & method=="RCT"

. sum `depvar' if t>(`threshold'-0.5) & t<(`threshold'+0.5) 
> & method=="RCT"

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
  sign_10pct |      1,216    .5164474     .499935          0          1

. 
134
estadd local rct_sign = round(r(mean), 0.01)

. estadd local rct_sign = round(r(mean), 0.01)

added macro:
           e(rct_sign) : ".52"

. 
135
136
probit `depvar' DID IV RDD i.year i.unique_j experience_avg experience_avg_sq share_top_authors share_top_phd i.ireport authored_solo share_female_authors editor_present if t>(`threshold'-0.35) & t<(`threshold'+0.35) [`weight1'`weight2'], cluster(journal_article_cluster)
probit sign_10pct DID IV RDD i.year i.unique_j experience_avg experience_avg_sq share_top_authors share_top_phd i.ireport authored_solo share_female_authors editor_present if t>(1.65-0.35) & t<(1.65+0.35) [pw=aw], cluster(journal_article_cluster)

. probit `depvar' DID IV RDD i.year i.unique_j experience_av
> g experience_avg_sq share_top_authors share_top_phd i.ireport authored_solo s
> hare_female_authors editor_present if t>(`threshold'-0.35) & t<(`threshold'+0
> .35) [`weight1'`weight2'], cluster(journal_article_cluster)

note: 6.unique_j != 0 predicts failure perfectly;
      6.unique_j omitted and 1 obs not used.

Iteration 0:   log pseudolikelihood = -442242.94  
Iteration 1:   log pseudolikelihood = -419798.28  
Iteration 2:   log pseudolikelihood = -419521.18  
Iteration 3:   log pseudolikelihood = -419520.09  
Iteration 4:   log pseudolikelihood = -419520.09  

Probit regression                                       Number of obs =  2,377
                                                        Wald chi2(37) =  73.56
                                                        Prob > chi2   = 0.0003
Log pseudolikelihood = -419520.09                       Pseudo R2     = 0.0514

              (Std. err. adjusted for 413 clusters in journal_article_cluster)
------------------------------------------------------------------------------
             |               Robust
  sign_10pct | Coefficient  std. err.      z    P>|z|     [95% conf. interval]
-------------+----------------------------------------------------------------
         DID |   .2845893   .1320785     2.15   0.031     .0257202    .5434584
          IV |   .1813196   .1183084     1.53   0.125    -.0505606    .4131997
         RDD |  -.0659786   .1537339    -0.43   0.668    -.3672915    .2353343
             |
        year |
       2018  |   .0655507   .1013908     0.65   0.518    -.1331717    .2642731
             |
    unique_j |
          2  |  -.3064238   .3553262    -0.86   0.388     -1.00285    .3900027
          3  |  -.1776791    .296197    -0.60   0.549    -.7582146    .4028565
          4  |   .3306152   .3077883     1.07   0.283    -.2726388    .9338692
          5  |   .2399634   .3200833     0.75   0.453    -.3873883    .8673151
          7  |    .326602   .5400965     0.60   0.545    -.7319678    1.385172
          8  |  -.1492463   .2678324    -0.56   0.577    -.6741881    .3756956
          9  |  -.0330916   .2461022    -0.13   0.893     -.515443    .4492597
         10  |   .9365125   .4985731     1.88   0.060    -.0406728    1.913698
         11  |  -.0711041    .228183    -0.31   0.755    -.5183345    .3761263
         12  |   -.031446   .3248993    -0.10   0.923    -.6682368    .6053448
         13  |  -.2473589   .2865312    -0.86   0.388    -.8089497    .3142319
         14  |   .0302252   .3637233     0.08   0.934    -.6826593    .7431098
         15  |  -.6346342   .2836079    -2.24   0.025    -1.190496   -.0787729
         16  |   .3910687   .3206352     1.22   0.223    -.2373649    1.019502
         17  |   1.104191   .5536038     1.99   0.046     .0191477    2.189235
         18  |  -.4406852    .242953    -1.81   0.070    -.9168644     .035494
         19  |   -.175174   .2868864    -0.61   0.541     -.737461    .3871131
         20  |   1.107661   .3902658     2.84   0.005     .3427538    1.872567
         21  |   .1031202   .7545757     0.14   0.891    -1.375821    1.582061
         22  |  -.1074449   .3105217    -0.35   0.729    -.7160564    .5011665
         23  |   .1275117   .2587629     0.49   0.622    -.3796542    .6346776
         24  |   -.402911   .2785259    -1.45   0.148    -.9488118    .1429898
         25  |  -.3036968   .2574991    -1.18   0.238    -.8083858    .2009922
             |
experience~g |  -.0426977    .021873    -1.95   0.051    -.0855681    .0001726
experience~q |   .0873579   .0644875     1.35   0.176    -.0390353    .2137511
share_top_~s |  -.0162223   .1422882    -0.11   0.909     -.295102    .2626574
share_top_~d |  -.1635343   .1350543    -1.21   0.226    -.4282359    .1011674
             |
     ireport |
          2  |  -.3889376   .7540907    -0.52   0.606    -1.866928    1.089053
          3  |  -.3847109   .7420405    -0.52   0.604    -1.839084    1.069662
          4  |  -.7913694   .7810919    -1.01   0.311    -2.322281    .7395427
             |
authored_s~o |   .0360235   .1480467     0.24   0.808    -.2541426    .3261896
share_fema~s |   .2660892   .1530786     1.74   0.082    -.0339394    .5661178
editor_pre~t |   .0597911   .1333152     0.45   0.654     -.201502    .3210841
       _cons |   .9238401   .7695609     1.20   0.230    -.5844716    2.432152
------------------------------------------------------------------------------

. 
137
eststo : margins, dydx(*) post

. eststo : margins, dydx(*) post

Average marginal effects                                 Number of obs = 2,377
Model VCE: Robust

Expression: Pr(sign_10pct), predict()
dy/dx wrt:  DID IV RDD 2018.year 2.unique_j 3.unique_j 4.unique_j 5.unique_j
            7.unique_j 8.unique_j 9.unique_j 10.unique_j 11.unique_j
            12.unique_j 13.unique_j 14.unique_j 15.unique_j 16.unique_j
            17.unique_j 18.unique_j 19.unique_j 20.unique_j 21.unique_j
            22.unique_j 23.unique_j 24.unique_j 25.unique_j experience_avg
            experience_avg_sq share_top_authors share_top_phd 2.ireport
            3.ireport 4.ireport authored_solo share_female_authors
            editor_present

------------------------------------------------------------------------------
             |            Delta-method
             |      dy/dx   std. err.      z    P>|z|     [95% conf. interval]
-------------+----------------------------------------------------------------
         DID |   .1034587   .0474987     2.18   0.029     .0103629    .1965545
          IV |   .0659163    .042702     1.54   0.123     -.017778    .1496107
         RDD |  -.0239856   .0558904    -0.43   0.668    -.1335288    .0855575
             |
        year |
       2018  |   .0238433   .0369025     0.65   0.518    -.0484843    .0961709
             |
    unique_j |
          2  |  -.1153011   .1350907    -0.85   0.393    -.3800741    .1494718
          3  |  -.0658718   .1103924    -0.60   0.551    -.2822369    .1504933
          4  |   .1100003    .100454     1.10   0.274    -.0868859    .3068865
          5  |   .0818409   .1070803     0.76   0.445    -.1280326    .2917144
          7  |   .1087893   .1680519     0.65   0.517    -.2205863    .4381649
          8  |  -.0551105   .0987842    -0.56   0.577     -.248724    .1385031
          9  |  -.0119902    .089054    -0.13   0.893    -.1865328    .1625524
         10  |    .251628   .1041688     2.42   0.016     .0474609    .4557951
         11  |  -.0259355   .0827795    -0.31   0.754    -.1881804    .1363093
         12  |  -.0113906   .1178705    -0.10   0.923    -.2424124    .2196313
         13  |  -.0925052   .1068431    -0.87   0.387    -.3019138    .1169035
         14  |   .0108202    .129917     0.08   0.934    -.2438124    .2654529
         15  |  -.2421215   .1046443    -2.31   0.021    -.4472205   -.0370225
         16  |   .1278294   .1022588     1.25   0.211    -.0725942     .328253
         17  |   .2766271   .0979856     2.82   0.005     .0845788    .4686754
         18  |  -.1674576   .0897594    -1.87   0.062    -.3433828    .0084675
         19  |  -.0649209    .106382    -0.61   0.542    -.2734257    .1435839
         20  |   .2770859   .0844697     3.28   0.001     .1115285    .4426434
         21  |   .0363519   .2605529     0.14   0.889    -.4743223    .5470262
         22  |  -.0394247   .1143492    -0.34   0.730     -.263545    .1846956
         23  |   .0447039   .0910096     0.49   0.623    -.1336716    .2230794
         24  |  -.1527707   .1044384    -1.46   0.144    -.3574662    .0519248
         25  |  -.1142454   .0956978    -1.19   0.233    -.3018097    .0733189
             |
experience~g |  -.0155222    .007917    -1.96   0.050    -.0310393   -5.11e-06
experience~q |   .0317578   .0233854     1.36   0.174    -.0140768    .0775924
share_top_~s |  -.0058974   .0517172    -0.11   0.909    -.1072613    .0954665
share_top_~d |  -.0594507   .0491035    -1.21   0.226    -.1556918    .0367904
             |
     ireport |
          2  |   -.129471   .2284283    -0.57   0.571    -.5771822    .3182402
          3  |  -.1279519   .2232618    -0.57   0.567     -.565537    .3096332
          4  |   -.279108   .2401934    -1.16   0.245    -.7498784    .1916625
             |
authored_s~o |   .0130959    .053803     0.24   0.808    -.0923561    .1185478
share_fema~s |   .0967332   .0554889     1.74   0.081    -.0120229    .2054894
editor_pre~t |   .0217363   .0484371     0.45   0.654    -.0731987    .1166712
------------------------------------------------------------------------------
Note: dy/dx for factor levels is the discrete change from the base level.
(est5 stored)

. 
138
estadd local Window "[`threshold'$\pm$0.35]"
estadd local Window "[1.65$\pm$0.35]"

. estadd local Window "[`threshold'$\pm$0.35]"

added macro:
             e(Window) : "[1.65$\pm$0.35]"

. 
139
sum `depvar' if t>(`threshold'-0.35) & t<(`threshold'+0.35) & method=="RCT"
sum sign_10pct if t>(1.65-0.35) & t<(1.65+0.35) & method=="RCT"

. sum `depvar' if t>(`threshold'-0.35) & t<(`threshold'+0.35
> ) & method=="RCT"

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
  sign_10pct |        823    .5261239    .4996207          0          1

. 
140
estadd local rct_sign = round(r(mean), 0.01)

. estadd local rct_sign = round(r(mean), 0.01)

added macro:
           e(rct_sign) : ".53"

. 
141
142
probit `depvar' DID IV RDD i.year i.unique_j experience_avg experience_avg_sq share_top_authors share_top_phd i.ireport authored_solo share_female_authors editor_present if t>(`threshold'-0.2) & t<(`threshold'+0.2) [`weight1'`weight2'], cluster(journal_article_cluster)
probit sign_10pct DID IV RDD i.year i.unique_j experience_avg experience_avg_sq share_top_authors share_top_phd i.ireport authored_solo share_female_authors editor_present if t>(1.65-0.2) & t<(1.65+0.2) [pw=aw], cluster(journal_article_cluster)

. probit `depvar' DID IV RDD i.year i.unique_j experience_av
> g experience_avg_sq share_top_authors share_top_phd i.ireport authored_solo s
> hare_female_authors editor_present if t>(`threshold'-0.2) & t<(`threshold'+0.
> 2) [`weight1'`weight2'], cluster(journal_article_cluster)

note: 6.unique_j != 0 predicts failure perfectly;
      6.unique_j omitted and 1 obs not used.

note: 17.unique_j != 0 predicts success perfectly;
      17.unique_j omitted and 2 obs not used.

note: 1.ireport != 0 predicts success perfectly;
      1.ireport omitted and 2 obs not used.

note: 4.ireport omitted because of collinearity.
Iteration 0:   log pseudolikelihood = -255287.43  
Iteration 1:   log pseudolikelihood = -238015.26  
Iteration 2:   log pseudolikelihood = -237925.37  
Iteration 3:   log pseudolikelihood = -237925.33  
Iteration 4:   log pseudolikelihood = -237925.33  

Probit regression                                       Number of obs =  1,363
                                                        Wald chi2(34) =  63.92
                                                        Prob > chi2   = 0.0014
Log pseudolikelihood = -237925.33                       Pseudo R2     = 0.0680

              (Std. err. adjusted for 352 clusters in journal_article_cluster)
------------------------------------------------------------------------------
             |               Robust
  sign_10pct | Coefficient  std. err.      z    P>|z|     [95% conf. interval]
-------------+----------------------------------------------------------------
         DID |    .246094   .1684007     1.46   0.144    -.0839653    .5761534
          IV |   .0568339   .1503284     0.38   0.705    -.2378044    .3514722
         RDD |  -.2245795    .175924    -1.28   0.202    -.5693841    .1202251
             |
        year |
       2018  |   .2549064   .1168868     2.18   0.029     .0258124    .4840003
             |
    unique_j |
          2  |   -.282745   .5654319    -0.50   0.617    -1.390971    .8254811
          3  |  -.5659022   .5163728    -1.10   0.273    -1.577974      .44617
          4  |    .627347   .3888874     1.61   0.107    -.1348582    1.389552
          5  |   .4721226    .488829     0.97   0.334    -.4859647     1.43021
          7  |   .0798365    .629183     0.13   0.899     -1.15334    1.313012
          8  |  -.2707945   .3183011    -0.85   0.395    -.8946533    .3530642
          9  |   .1015442   .3452403     0.29   0.769    -.5751144    .7782028
         10  |   .6397329   .4441426     1.44   0.150    -.2307707    1.510236
         11  |  -.1072324   .3103702    -0.35   0.730    -.7155469    .5010821
         12  |  -.0684838   .4560902    -0.15   0.881    -.9624041    .8254366
         13  |  -.5364663   .3582739    -1.50   0.134     -1.23867    .1657376
         14  |  -.4103014    .525207    -0.78   0.435    -1.439688    .6190854
         15  |   -.916741   .4016627    -2.28   0.022    -1.703985   -.1294966
         16  |   .5137234    .445626     1.15   0.249    -.3596875    1.387134
         18  |  -.5921128   .3337154    -1.77   0.076    -1.246183    .0619574
         19  |  -.3325689   .4205156    -0.79   0.429    -1.156764    .4916266
         20  |    .988769   .4289826     2.30   0.021     .1479785    1.829559
         21  |  -.8001148    .549299    -1.46   0.145    -1.876721    .2764915
         22  |  -.3410793   .3984938    -0.86   0.392    -1.122113    .4399543
         23  |  -.0378115    .337763    -0.11   0.911    -.6998148    .6241918
         24  |  -.2184652   .3381983    -0.65   0.518    -.8813217    .4443912
         25  |  -.3351321   .3293585    -1.02   0.309     -.980663    .3103987
             |
experience~g |    -.02985   .0260438    -1.15   0.252     -.080895     .021195
experience~q |   .0638069   .0716646     0.89   0.373    -.0766531     .204267
share_top_~s |  -.0275563    .178107    -0.15   0.877    -.3766395     .321527
share_top_~d |   -.420389   .1733485    -2.43   0.015    -.7601458   -.0806322
             |
     ireport |
          3  |   .5736708   .1927511     2.98   0.003     .1958855    .9514561
          4  |          0  (omitted)
             |
authored_s~o |    .177324   .1657397     1.07   0.285    -.1475199    .5021679
share_fema~s |   .2084027   .1835765     1.14   0.256    -.1514007     .568206
editor_pre~t |   .0338833   .1570289     0.22   0.829    -.2738876    .3416542
       _cons |   .0413152   .4068878     0.10   0.919    -.7561702    .8388005
------------------------------------------------------------------------------

. 
143
eststo : margins, dydx(*) post

. eststo : margins, dydx(*) post

Average marginal effects                                 Number of obs = 1,363
Model VCE: Robust

Expression: Pr(sign_10pct), predict()
dy/dx wrt:  DID IV RDD 2018.year 2.unique_j 3.unique_j 4.unique_j 5.unique_j
            7.unique_j 8.unique_j 9.unique_j 10.unique_j 11.unique_j
            12.unique_j 13.unique_j 14.unique_j 15.unique_j 16.unique_j
            18.unique_j 19.unique_j 20.unique_j 21.unique_j 22.unique_j
            23.unique_j 24.unique_j 25.unique_j experience_avg
            experience_avg_sq share_top_authors share_top_phd 3.ireport
            4.ireport authored_solo share_female_authors editor_present

------------------------------------------------------------------------------
             |            Delta-method
             |      dy/dx   std. err.      z    P>|z|     [95% conf. interval]
-------------+----------------------------------------------------------------
         DID |    .088472   .0600876     1.47   0.141    -.0292975    .2062416
          IV |   .0204321   .0540049     0.38   0.705    -.0854157    .1262798
         RDD |  -.0807374   .0629968    -1.28   0.200    -.2042089     .042734
             |
        year |
       2018  |          .  (not estimable)
             |
    unique_j |
          2  |          .  (not estimable)
          3  |          .  (not estimable)
          4  |          .  (not estimable)
          5  |          .  (not estimable)
          7  |          .  (not estimable)
          8  |          .  (not estimable)
          9  |          .  (not estimable)
         10  |          .  (not estimable)
         11  |          .  (not estimable)
         12  |          .  (not estimable)
         13  |          .  (not estimable)
         14  |          .  (not estimable)
         15  |          .  (not estimable)
         16  |          .  (not estimable)
         18  |          .  (not estimable)
         19  |          .  (not estimable)
         20  |          .  (not estimable)
         21  |          .  (not estimable)
         22  |          .  (not estimable)
         23  |          .  (not estimable)
         24  |          .  (not estimable)
         25  |          .  (not estimable)
             |
experience~g |  -.0107312   .0093345    -1.15   0.250    -.0290266    .0075641
experience~q |   .0229389   .0257002     0.89   0.372    -.0274325    .0733103
share_top_~s |  -.0099066   .0639981    -0.15   0.877    -.1353405    .1155273
share_top_~d |  -.1511319   .0615993    -2.45   0.014    -.2718643   -.0303995
             |
     ireport |
          3  |          .  (not estimable)
          4  |          .  (not estimable)
             |
authored_s~o |   .0637489   .0592532     1.08   0.282    -.0523853     .179883
share_fema~s |   .0749218   .0661596     1.13   0.257    -.0547485    .2045921
editor_pre~t |   .0121812   .0564288     0.22   0.829    -.0984173    .1227797
------------------------------------------------------------------------------
Note: dy/dx for factor levels is the discrete change from the base level.
(est6 stored)

. 
144
estadd local Window "[`threshold'$\pm$0.20]"
estadd local Window "[1.65$\pm$0.20]"

. estadd local Window "[`threshold'$\pm$0.20]"

added macro:
             e(Window) : "[1.65$\pm$0.20]"

. 
145
sum `depvar' if t>(`threshold'-0.2) & t<(`threshold'+0.2) & method=="RCT"
sum sign_10pct if t>(1.65-0.2) & t<(1.65+0.2) & method=="RCT"

. sum `depvar' if t>(`threshold'-0.2) & t<(`threshold'+0.2) 
> & method=="RCT"

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
  sign_10pct |        484    .5392562    .4989723          0          1

. 
146
estadd local rct_sign = round(r(mean), 0.01)

. estadd local rct_sign = round(r(mean), 0.01)

added macro:
           e(rct_sign) : ".54"

. 
147
148
esttab, margin ///
esttab, margin keep(DID IV RDD top5 2018.year experience_avg experience_avg_sq share_top_authors share_top_phd ) label stats(N Window rct_sign, fmt(%9.0fc) labels("Observations" "Window" "RCT sig rate"))

. esttab, margin keep(DID IV RDD top5 2018.year experience_a
> vg experience_avg_sq share_top_authors share_top_phd ) label stats(N Window r
> ct_sign, fmt(%9.0fc) labels("Observations" "Window" "RCT sig rate"))

-------------------------------------------------------------------------------
> -------------------------------------
                              (1)             (2)             (3)             (
> 4)             (5)             (6)   
                                                                               
>                                      
-------------------------------------------------------------------------------
> -------------------------------------
DID                         0.100*          0.113**         0.108**         0.1
> 11**         0.103*         0.0885   
                           (2.30)          (2.82)          (2.63)          (2.6
> 7)          (2.18)          (1.47)   

IV                          0.116**         0.126***        0.101*          0.1
> 11**        0.0659          0.0204   
                           (3.20)          (3.36)          (2.51)          (2.7
> 4)          (1.54)          (0.38)   

RDD                        0.0151         0.00861         0.00449         0.005
> 10         -0.0240         -0.0807   
                           (0.35)          (0.21)          (0.10)          (0.1
> 1)         (-0.43)         (-1.28)   

Top 5                                      0.0599         -0.0473              
>                                      
                                           (1.23)         (-0.46)              
>                                      

Year=2018                                 0.00312          0.0102          0.01
> 97          0.0238               0   
                                           (0.09)          (0.30)          (0.5
> 7)          (0.65)             (.)   

Experience                               -0.00183        -0.00553        -0.006
> 58         -0.0155*        -0.0107   
                                          (-0.21)         (-0.64)         (-0.8
> 0)         (-1.96)         (-1.15)   

Experience squared                       -0.00323         0.00786         0.008
> 72          0.0318          0.0229   
                                          (-0.12)          (0.30)          (0.3
> 6)          (1.36)          (0.89)   

Top institution                           -0.0574         -0.0443         -0.03
> 89        -0.00590        -0.00991   
                                          (-1.18)         (-0.90)         (-0.8
> 0)         (-0.11)         (-0.15)   

Top PhD institution                       -0.0162         -0.0324         -0.04
> 46         -0.0595          -0.151*  
                                          (-0.36)         (-0.73)         (-1.0
> 3)         (-1.21)         (-2.45)   
-------------------------------------------------------------------------------
> -------------------------------------
Observations                3,470           3,470           3,470           3,4
> 69           2,377           1,363   
Window               [1.65$\pm$0.50]    [1.65$\pm$0.50]    [1.65$\pm$0.50]    [
> 1.65$\pm$0.50]    [1.65$\pm$0.35]    [1.65$\pm$0.20]   
RCT sig rate                  .52             .52             .52             .
> 52             .53             .54   
-------------------------------------------------------------------------------
> -------------------------------------
Marginal effects; t statistics in parentheses
 (d) for discrete change of dummy variable from 0 to 1
* p<0.05, ** p<0.01, *** p<0.001

. 
149
keep(DID IV RDD top5 2018.year experience_avg experience_avg_sq share_top_authors share_top_phd ) label stats(N Window rct_sign, fmt(%9.0fc) labels("Observations" "Window" "RCT sig rate"))
150
151
esttab using table_A5_caliper_`depvar'.tex, margin ///
esttab using table_A5_caliper_sign_10pct.tex, margin keep(DID IV RDD top5 2018.year experience_avg experience_avg_sq share_top_authors share_top_phd) label  stats(N Window rct_sign, fmt(%9.0fc) labels("Observations" "Window" "RCT sig rate")) mtitles() nomtitles nostar compress se(3) b(3) replace nogaps noomitted indicate( "Reporting Method = *ireport" "Solo Authored = authored_solo" "Share Female Authors = share_female_authors" "Editor = editor_present" "Field FE = FINANCE" "Journal FE = *unique_j" , labels("Y" " ")) nonotes

. esttab using "table_A5_caliper_sign_10pct.tex", margin keep(DID IV 
> RDD top5 2018.year experience_avg experience_avg_sq share_top_authors share_t
> op_phd) label  stats(N Window rct_sign, fmt(%9.0fc) labels("Observations" "Wi
> ndow" "RCT sig rate")) mtitles() nomtitles nostar compress se(3) b(3) replace
>  nogaps noomitted indicate( "Reporting Method = *ireport" "Solo Authored = au
> thored_solo" "Share Female Authors = share_female_authors" "Editor = editor_p
> resent" "Field FE = FINANCE" "Journal FE = *unique_j" , labels("Y" " ")) nono
> tes
(output written to table_A5_caliper_sign_10pct.tex)

. 
152
keep(DID IV RDD top5 2018.year experience_avg experience_avg_sq share_top_authors share_top_phd) label  stats(N Window rct_sign, fmt(%9.0fc) labels("Observations" "Window" "RCT sig rate")) ///
153
mtitles() nomtitles nostar ///
154
 compress se(3) b(3) replace nogaps noomitted ///
155
indicate( ///
156
"Reporting Method = *ireport" ///
157
"Solo Authored = authored_solo" ///
158
"Share Female Authors = share_female_authors" ///
159
"Editor = editor_present" ///
160
"Field FE = FINANCE" ///
161
"Journal FE = *unique_j" ///
162
, labels("Y" " ")) ///
163
nonotes
164
165
166
167
** Table A6: 1% significance treshold
168
169
* read in the data
170
cd "$dir_data" 
cd "/home/rstudio/repbox/projects_ejd/aer_112_9_9/mod/Scripts/Data"

. cd "${repbox_path}/Data"
/home/rstudio/repbox/projects_ejd/aer_112_9_9/mod/Data

. 
171
capture use "MM_new.dta", clear 

. capture use "MM_new.dta", clear

. 
172
173
* determine folder to store results
174
cd "$dir_results" 
cd "/home/rstudio/repbox/projects_ejd/aer_112_9_9/mod/Scripts/Results"

. cd "${repbox_path}/Results"
/home/rstudio/repbox/projects_ejd/aer_112_9_9/mod/Results

. 
175
176
177
* drop obs with small significand
178
keep if keep_obs==1

. keep if keep_obs==1
(8,233 observations deleted)

. 
179
180
181
	local depvar "sign_1pct"

. local depvar "sign_1pct"

. 
182
	local threshold 2.58

. local threshold 2.58

. 
183
	local weight1 "pw="

. local weight1 "pw="

. 
184
	local weight2 "aw"

. local weight2 "aw"

. 
185
186
187
eststo clear

. eststo clear

. 
188
189
probit `depvar' DID IV RDD if t>(`threshold'-0.5) & t<(`threshold'+0.5) [`weight1'`weight2'], cluster(journal_article_cluster)
probit sign_1pct DID IV RDD if t>(2.58-0.5) & t<(2.58+0.5) [pw=aw], cluster(journal_article_cluster)

. probit `depvar' DID IV RDD if t>(`threshold'-0.5) & t<(`th
> reshold'+0.5) [`weight1'`weight2'], cluster(journal_article_cluster)

Iteration 0:   log pseudolikelihood =  -669750.1  
Iteration 1:   log pseudolikelihood = -667247.48  
Iteration 2:   log pseudolikelihood = -667246.54  
Iteration 3:   log pseudolikelihood = -667246.54  

Probit regression                                       Number of obs =  2,689
                                                        Wald chi2(3)  =   3.44
                                                        Prob > chi2   = 0.3286
Log pseudolikelihood = -667246.54                       Pseudo R2     = 0.0037

              (Std. err. adjusted for 461 clusters in journal_article_cluster)
------------------------------------------------------------------------------
             |               Robust
   sign_1pct | Coefficient  std. err.      z    P>|z|     [95% conf. interval]
-------------+----------------------------------------------------------------
         DID |   .1289408   .1248527     1.03   0.302     -.115766    .3736476
          IV |   .0500791   .1090326     0.46   0.646    -.1636209     .263779
         RDD |  -.2116945   .1757407    -1.20   0.228      -.55614    .1327509
       _cons |  -.2623067   .0748966    -3.50   0.000    -.4091014   -.1155121
------------------------------------------------------------------------------

. 
190
eststo : margins, dydx(*) post

. eststo : margins, dydx(*) post

Average marginal effects                                 Number of obs = 2,689
Model VCE: Robust

Expression: Pr(sign_1pct), predict()
dy/dx wrt:  DID IV RDD

------------------------------------------------------------------------------
             |            Delta-method
             |      dy/dx   std. err.      z    P>|z|     [95% conf. interval]
-------------+----------------------------------------------------------------
         DID |   .0500332   .0485232     1.03   0.302    -.0450705    .1451368
          IV |   .0194323   .0423733     0.46   0.647    -.0636178    .1024824
         RDD |  -.0821443   .0678584    -1.21   0.226    -.2151443    .0508557
------------------------------------------------------------------------------
(est1 stored)

. 
191
estadd local Window "[`threshold'$\pm$0.50]"
estadd local Window "[2.58$\pm$0.50]"

. estadd local Window "[`threshold'$\pm$0.50]"

added macro:
             e(Window) : "[2.58$\pm$0.50]"

. 
192
sum `depvar' if t>(`threshold'-0.5) & t<(`threshold'+0.5) & method=="RCT"
sum sign_1pct if t>(2.58-0.5) & t<(2.58+0.5) & method=="RCT"

. sum `depvar' if t>(`threshold'-0.5) & t<(`threshold'+0.5) 
> & method=="RCT"

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
   sign_1pct |        741    .3711201    .4834308          0          1

. 
193
estadd local rct_sign = round(r(mean), 0.01)

. estadd local rct_sign = round(r(mean), 0.01)

added macro:
           e(rct_sign) : ".37"

. 
194
195
probit `depvar' DID IV RDD top5 i.year experience_avg experience_avg_sq share_top_authors share_top_phd i.ireport authored_solo share_female_authors editor_present if t>(`threshold'-0.5) & t<(`threshold'+0.5) [`weight1'`weight2'], cluster(journal_article_cluster)
probit sign_1pct DID IV RDD top5 i.year experience_avg experience_avg_sq share_top_authors share_top_phd i.ireport authored_solo share_female_authors editor_present if t>(2.58-0.5) & t<(2.58+0.5) [pw=aw], cluster(journal_article_cluster)

. probit `depvar' DID IV RDD top5 i.year experience_avg expe
> rience_avg_sq share_top_authors share_top_phd i.ireport authored_solo share_f
> emale_authors editor_present if t>(`threshold'-0.5) & t<(`threshold'+0.5) [`w
> eight1'`weight2'], cluster(journal_article_cluster)

Iteration 0:   log pseudolikelihood =  -669750.1  
Iteration 1:   log pseudolikelihood = -659017.59  
Iteration 2:   log pseudolikelihood = -659006.41  
Iteration 3:   log pseudolikelihood = -659006.41  

Probit regression                                       Number of obs =  2,689
                                                        Wald chi2(15) =  19.56
                                                        Prob > chi2   = 0.1894
Log pseudolikelihood = -659006.41                       Pseudo R2     = 0.0160

              (Std. err. adjusted for 461 clusters in journal_article_cluster)
------------------------------------------------------------------------------
             |               Robust
   sign_1pct | Coefficient  std. err.      z    P>|z|     [95% conf. interval]
-------------+----------------------------------------------------------------
         DID |   .1049754   .1180157     0.89   0.374    -.1263311    .3362819
          IV |   .0227496   .1027472     0.22   0.825    -.1786313    .2241305
         RDD |   -.215545   .1626261    -1.33   0.185    -.5342862    .1031962
        top5 |   .0749811   .1456956     0.51   0.607     -.210577    .3605392
             |
        year |
       2018  |   .0267661   .1063027     0.25   0.801    -.1815833    .2351156
             |
experience~g |   .0469408   .0246645     1.90   0.057    -.0014006    .0952823
experience~q |  -.1289768   .0790245    -1.63   0.103     -.283862    .0259084
share_top_~s |   .0083037   .1623162     0.05   0.959    -.3098302    .3264376
share_top_~d |  -.1335537   .1391907    -0.96   0.337    -.4063625    .1392551
             |
     ireport |
          2  |    .118627    .768349     0.15   0.877    -1.387309    1.624563
          3  |   .2407662   .7534585     0.32   0.749    -1.235985    1.717518
          4  |   .0756213   .7685389     0.10   0.922    -1.430687     1.58193
             |
authored_s~o |   .1635069   .1340453     1.22   0.223    -.0992172    .4262309
share_fema~s |  -.3373093   .1435892    -2.35   0.019     -.618739   -.0558796
editor_pre~t |  -.0011926   .1313088    -0.01   0.993    -.2585531     .256168
       _cons |  -.7068931   .7791257    -0.91   0.364    -2.233951    .8201652
------------------------------------------------------------------------------

. 
196
eststo : margins, dydx(*) post

. eststo : margins, dydx(*) post

Average marginal effects                                 Number of obs = 2,689
Model VCE: Robust

Expression: Pr(sign_1pct), predict()
dy/dx wrt:  DID IV RDD top5 2018.year experience_avg experience_avg_sq
            share_top_authors share_top_phd 2.ireport 3.ireport 4.ireport
            authored_solo share_female_authors editor_present

------------------------------------------------------------------------------
             |            Delta-method
             |      dy/dx   std. err.      z    P>|z|     [95% conf. interval]
-------------+----------------------------------------------------------------
         DID |   .0401893   .0453022     0.89   0.375    -.0486014      .12898
          IV |   .0087096   .0393635     0.22   0.825    -.0684414    .0858606
         RDD |  -.0825202   .0618957    -1.33   0.182    -.2038335     .038793
        top5 |   .0287061   .0557322     0.52   0.607    -.0805269    .1379392
             |
        year |
       2018  |   .0102445    .040671     0.25   0.801    -.0694692    .0899583
             |
experience~g |    .017971   .0093974     1.91   0.056    -.0004476    .0363897
experience~q |  -.0493781   .0301451    -1.64   0.101    -.1084614    .0097053
share_top_~s |    .003179   .0621443     0.05   0.959    -.1186215    .1249796
share_top_~d |  -.0511303   .0532617    -0.96   0.337    -.1555213    .0532606
             |
     ireport |
          2  |    .043468    .275852     0.16   0.875     -.497192    .5841281
          3  |   .0898759   .2700094     0.33   0.739    -.4393328    .6190846
          4  |   .0274979   .2757206     0.10   0.921    -.5129046    .5679003
             |
authored_s~o |   .0625977   .0511927     1.22   0.221    -.0377381    .1629336
share_fema~s |   -.129137   .0543453    -2.38   0.017    -.2356519   -.0226222
editor_pre~t |  -.0004566   .0502704    -0.01   0.993    -.0989847    .0980716
------------------------------------------------------------------------------
Note: dy/dx for factor levels is the discrete change from the base level.
(est2 stored)

. 
197
estadd local Window "[`threshold'$\pm$0.50]"
estadd local Window "[2.58$\pm$0.50]"

. estadd local Window "[`threshold'$\pm$0.50]"

added macro:
             e(Window) : "[2.58$\pm$0.50]"

. 
198
sum `depvar' if t>(`threshold'-0.5) & t<(`threshold'+0.5) & method=="RCT"
sum sign_1pct if t>(2.58-0.5) & t<(2.58+0.5) & method=="RCT"

. sum `depvar' if t>(`threshold'-0.5) & t<(`threshold'+0.5) 
> & method=="RCT"

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
   sign_1pct |        741    .3711201    .4834308          0          1

. 
199
estadd local rct_sign = round(r(mean), 0.01)

. estadd local rct_sign = round(r(mean), 0.01)

added macro:
           e(rct_sign) : ".37"

. 
200
201
probit `depvar' DID IV RDD top5 i.year FINANCE MACRO_GROWTH GEN_INT EXP DEV LABOR PUB URB experience_avg experience_avg_sq share_top_authors share_top_phd i.ireport authored_solo share_female_authors editor_present if t>(`threshold'-0.5) & t<(`threshold'+0.5) [`weight1'`weight2'], cluster(journal_article_cluster)
probit sign_1pct DID IV RDD top5 i.year FINANCE MACRO_GROWTH GEN_INT EXP DEV LABOR PUB URB experience_avg experience_avg_sq share_top_authors share_top_phd i.ireport authored_solo share_female_authors editor_present if t>(2.58-0.5) & t<(2.58+0.5) [pw=aw], cluster(journal_article_cluster)

. probit `depvar' DID IV RDD top5 i.year FINANCE MACRO_GROWT
> H GEN_INT EXP DEV LABOR PUB URB experience_avg experience_avg_sq share_top_au
> thors share_top_phd i.ireport authored_solo share_female_authors editor_prese
> nt if t>(`threshold'-0.5) & t<(`threshold'+0.5) [`weight1'`weight2'], cluster
> (journal_article_cluster)

Iteration 0:   log pseudolikelihood =  -669750.1  
Iteration 1:   log pseudolikelihood = -656965.52  
Iteration 2:   log pseudolikelihood =  -656953.8  
Iteration 3:   log pseudolikelihood =  -656953.8  

Probit regression                                       Number of obs =  2,689
                                                        Wald chi2(23) =  26.71
                                                        Prob > chi2   = 0.2687
Log pseudolikelihood = -656953.8                        Pseudo R2     = 0.0191

              (Std. err. adjusted for 461 clusters in journal_article_cluster)
------------------------------------------------------------------------------
             |               Robust
   sign_1pct | Coefficient  std. err.      z    P>|z|     [95% conf. interval]
-------------+----------------------------------------------------------------
         DID |   .0561092   .1253168     0.45   0.654    -.1895072    .3017255
          IV |  -.0455817   .1054459    -0.43   0.666    -.2522519    .1610885
         RDD |  -.2450737   .1638788    -1.50   0.135    -.5662703    .0761229
        top5 |  -.2633865   .2643093    -1.00   0.319    -.7814233    .2546502
             |
        year |
       2018  |   .0221047   .1080531     0.20   0.838    -.1896755    .2338848
             |
     FINANCE |  -.2517506   .2609974    -0.96   0.335    -.7632962    .2597949
MACRO_GROWTH |  -.1471067   .4009632    -0.37   0.714    -.9329802    .6387667
     GEN_INT |  -.3894207   .2388287    -1.63   0.103    -.8575165     .078675
         EXP |  -.2147162   .2502937    -0.86   0.391    -.7052828    .2758504
         DEV |  -.4519424   .2827011    -1.60   0.110    -1.006026    .1021416
       LABOR |  -.4441472   .2614634    -1.70   0.089    -.9566061    .0683117
         PUB |  -.4125309   .2626777    -1.57   0.116    -.9273697    .1023079
         URB |  -.2745804   .3170516    -0.87   0.386    -.8959902    .3468294
experience~g |   .0421548   .0238079     1.77   0.077    -.0045079    .0888174
experience~q |  -.1146504   .0760567    -1.51   0.132    -.2637189    .0344181
share_top_~s |   .0168047   .1645871     0.10   0.919      -.30578    .3393894
share_top_~d |  -.1379511   .1406996    -0.98   0.327    -.4137172    .1378151
             |
     ireport |
          2  |   .0414204   .7575666     0.05   0.956    -1.443383    1.526224
          3  |   .1976292   .7418961     0.27   0.790     -1.25646    1.651719
          4  |  -.0405008   .7634453    -0.05   0.958    -1.536826    1.455825
             |
authored_s~o |    .139048   .1340644     1.04   0.300    -.1237134    .4018094
share_fema~s |  -.3471497   .1417911    -2.45   0.014    -.6250551   -.0692442
editor_pre~t |   -.032286   .1341003    -0.24   0.810    -.2951178    .2305457
       _cons |   -.212291   .8107186    -0.26   0.793     -1.80127    1.376688
------------------------------------------------------------------------------

. 
202
eststo : margins, dydx(*) post

. eststo : margins, dydx(*) post

Average marginal effects                                 Number of obs = 2,689
Model VCE: Robust

Expression: Pr(sign_1pct), predict()
dy/dx wrt:  DID IV RDD top5 2018.year FINANCE MACRO_GROWTH GEN_INT EXP DEV
            LABOR PUB URB experience_avg experience_avg_sq share_top_authors
            share_top_phd 2.ireport 3.ireport 4.ireport authored_solo
            share_female_authors editor_present

------------------------------------------------------------------------------
             |            Delta-method
             |      dy/dx   std. err.      z    P>|z|     [95% conf. interval]
-------------+----------------------------------------------------------------
         DID |   .0214101   .0478951     0.45   0.655    -.0724626    .1152828
          IV |  -.0173931   .0401725    -0.43   0.665    -.0961298    .0613437
         RDD |  -.0935152   .0620886    -1.51   0.132    -.2152066    .0281763
        top5 |   -.100503   .1006628    -1.00   0.318    -.2977985    .0967925
             |
        year |
       2018  |    .008433   .0412074     0.20   0.838    -.0723321    .0891981
             |
     FINANCE |   -.096063   .0993545    -0.97   0.334    -.2907943    .0986684
MACRO_GROWTH |   -.056133   .1529368    -0.37   0.714    -.3558836    .2436177
     GEN_INT |  -.1485951   .0907006    -1.64   0.101     -.326365    .0291749
         EXP |  -.0819314   .0954957    -0.86   0.391    -.2690994    .1052367
         DEV |  -.1724521    .107272    -1.61   0.108    -.3827012    .0377971
       LABOR |  -.1694776   .0994083    -1.70   0.088    -.3643143    .0253591
         PUB |  -.1574135    .099665    -1.58   0.114    -.3527533    .0379264
         URB |  -.1047743   .1207954    -0.87   0.386     -.341529    .1319804
experience~g |   .0160854   .0090547     1.78   0.076    -.0016615    .0338323
experience~q |  -.0437483   .0289627    -1.51   0.131    -.1005141    .0130175
share_top_~s |   .0064123    .062806     0.10   0.919    -.1166851    .1295097
share_top_~d |  -.0526393   .0536604    -0.98   0.327    -.1578118    .0525331
             |
     ireport |
          2  |   .0152065     .27631     0.06   0.956    -.5263512    .5567641
          3  |   .0742071   .2704563     0.27   0.784    -.4558775    .6042917
          4  |  -.0146494   .2779867    -0.05   0.958    -.5594934    .5301946
             |
authored_s~o |   .0530579   .0510538     1.04   0.299    -.0470057    .1531215
share_fema~s |  -.1324653   .0533958    -2.48   0.013    -.2371192   -.0278114
editor_pre~t |  -.0123197    .051149    -0.24   0.810    -.1125699    .0879305
------------------------------------------------------------------------------
Note: dy/dx for factor levels is the discrete change from the base level.
(est3 stored)

. 
203
estadd local Window "[`threshold'$\pm$0.50]"
estadd local Window "[2.58$\pm$0.50]"

. estadd local Window "[`threshold'$\pm$0.50]"

added macro:
             e(Window) : "[2.58$\pm$0.50]"

. 
204
sum `depvar' if t>(`threshold'-0.5) & t<(`threshold'+0.5) & method=="RCT"
sum sign_1pct if t>(2.58-0.5) & t<(2.58+0.5) & method=="RCT"

. sum `depvar' if t>(`threshold'-0.5) & t<(`threshold'+0.5) 
> & method=="RCT"

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
   sign_1pct |        741    .3711201    .4834308          0          1

. 
205
estadd local rct_sign = round(r(mean), 0.01)

. estadd local rct_sign = round(r(mean), 0.01)

added macro:
           e(rct_sign) : ".37"

. 
206
207
probit `depvar' DID IV RDD i.year i.unique_j experience_avg experience_avg_sq share_top_authors share_top_phd i.ireport authored_solo share_female_authors editor_present if t>(`threshold'-0.5) & t<(`threshold'+0.5) [`weight1'`weight2'], cluster(journal_article_cluster)
probit sign_1pct DID IV RDD i.year i.unique_j experience_avg experience_avg_sq share_top_authors share_top_phd i.ireport authored_solo share_female_authors editor_present if t>(2.58-0.5) & t<(2.58+0.5) [pw=aw], cluster(journal_article_cluster)

. probit `depvar' DID IV RDD i.year i.unique_j experience_av
> g experience_avg_sq share_top_authors share_top_phd i.ireport authored_solo s
> hare_female_authors editor_present if t>(`threshold'-0.5) & t<(`threshold'+0.
> 5) [`weight1'`weight2'], cluster(journal_article_cluster)

Iteration 0:   log pseudolikelihood =  -669750.1  
Iteration 1:   log pseudolikelihood = -641856.54  
Iteration 2:   log pseudolikelihood = -641691.24  
Iteration 3:   log pseudolikelihood = -641690.99  
Iteration 4:   log pseudolikelihood = -641690.99  

Probit regression                                       Number of obs =  2,689
                                                        Wald chi2(38) =  54.12
                                                        Prob > chi2   = 0.0434
Log pseudolikelihood = -641690.99                       Pseudo R2     = 0.0419

              (Std. err. adjusted for 461 clusters in journal_article_cluster)
------------------------------------------------------------------------------
             |               Robust
   sign_1pct | Coefficient  std. err.      z    P>|z|     [95% conf. interval]
-------------+----------------------------------------------------------------
         DID |   .0257111   .1301481     0.20   0.843    -.2293744    .2807967
          IV |  -.1059543    .112491    -0.94   0.346    -.3264326     .114524
         RDD |  -.2465012   .1743136    -1.41   0.157    -.5881497    .0951472
             |
        year |
       2018  |   .0589941   .1116136     0.53   0.597    -.1597646    .2777528
             |
    unique_j |
          2  |   .2956642   .4679035     0.63   0.527    -.6214099    1.212738
          3  |   .5506824   .3473928     1.59   0.113     -.130195     1.23156
          4  |    .026867    .253102     0.11   0.915    -.4692039    .5229379
          5  |   .2489778   .3416742     0.73   0.466    -.4206913    .9186469
          6  |  -.4094304   .5102086    -0.80   0.422    -1.409421      .59056
          7  |   .5991428   .4718049     1.27   0.204    -.3255779    1.523863
          8  |   .1029652   .2790941     0.37   0.712    -.4440491    .6499795
          9  |   .1646734   .2721574     0.61   0.545    -.3687453    .6980922
         10  |   .1995355   .2126906     0.94   0.348    -.2173305    .6164014
         11  |   .1079337   .2305514     0.47   0.640    -.3439387    .5598062
         12  |  -.2598078    .274835    -0.95   0.344    -.7984745    .2788589
         13  |  -.0620644   .2642471    -0.23   0.814    -.5799792    .4558503
         14  |   .4792887   .2840772     1.69   0.092    -.0774924     1.03607
         15  |   .1370836    .261072     0.53   0.600    -.3746082    .6487753
         16  |   .2360148   .2591621     0.91   0.362    -.2719336    .7439633
         17  |   .2279155   .2247168     1.01   0.310    -.2125213    .6683524
         18  |  -.0419797   .2487263    -0.17   0.866    -.5294743    .4455149
         19  |   .0138106    .238701     0.06   0.954    -.4540347    .4816559
         20  |   1.273893   .4055921     3.14   0.002      .478947    2.068839
         21  |  -1.526916   .8057508    -1.90   0.058    -3.106158    .0523268
         22  |   .0904133   .2350773     0.38   0.701    -.3703297    .5511564
         23  |   -.102508    .306142    -0.33   0.738    -.7025354    .4975193
         24  |   .1905859   .2934376     0.65   0.516    -.3845413     .765713
         25  |   .0710025   .2508327     0.28   0.777    -.4206205    .5626254
             |
experience~g |   .0352558   .0239867     1.47   0.142    -.0117572    .0822688
experience~q |  -.1005329   .0758881    -1.32   0.185    -.2492709    .0482051
share_top_~s |   .0167082   .1652389     0.10   0.919    -.3071541    .3405705
share_top_~d |  -.1018654   .1500139    -0.68   0.497    -.3958872    .1921565
             |
     ireport |
          2  |  -.7766744   .5102179    -1.52   0.128    -1.776683    .2233343
          3  |  -.5604131   .4816508    -1.16   0.245    -1.504431    .3836052
          4  |  -.7461254   .5136793    -1.45   0.146    -1.752918    .2606676
             |
authored_s~o |   .1368841   .1411598     0.97   0.332    -.1397841    .4135523
share_fema~s |  -.3152116    .131669    -2.39   0.017     -.573278   -.0571451
editor_pre~t |  -.0606189   .1388297    -0.44   0.662    -.3327202    .2114824
       _cons |   .1723919   .5047188     0.34   0.733    -.8168388    1.161622
------------------------------------------------------------------------------

. 
208
eststo : margins, dydx(*) post

. eststo : margins, dydx(*) post

Average marginal effects                                 Number of obs = 2,689
Model VCE: Robust

Expression: Pr(sign_1pct), predict()
dy/dx wrt:  DID IV RDD 2018.year 2.unique_j 3.unique_j 4.unique_j 5.unique_j
            6.unique_j 7.unique_j 8.unique_j 9.unique_j 10.unique_j
            11.unique_j 12.unique_j 13.unique_j 14.unique_j 15.unique_j
            16.unique_j 17.unique_j 18.unique_j 19.unique_j 20.unique_j
            21.unique_j 22.unique_j 23.unique_j 24.unique_j 25.unique_j
            experience_avg experience_avg_sq share_top_authors share_top_phd
            2.ireport 3.ireport 4.ireport authored_solo share_female_authors
            editor_present

------------------------------------------------------------------------------
             |            Delta-method
             |      dy/dx   std. err.      z    P>|z|     [95% conf. interval]
-------------+----------------------------------------------------------------
         DID |   .0095712   .0484743     0.20   0.843    -.0854368    .1045791
          IV |  -.0394422   .0417182    -0.95   0.344    -.1212083    .0423239
         RDD |  -.0917618   .0645585    -1.42   0.155    -.2182941    .0347705
             |
        year |
       2018  |   .0219448   .0414626     0.53   0.597    -.0593204    .1032099
             |
    unique_j |
          2  |   .1137101   .1822399     0.62   0.533    -.2434735    .4708937
          3  |   .2132205   .1323746     1.61   0.107     -.046229    .4726699
          4  |   .0100275   .0944197     0.11   0.915    -.1750317    .1950867
          5  |   .0954176   .1318662     0.72   0.469    -.1630355    .3538707
          6  |  -.1387854   .1581679    -0.88   0.380    -.4487887    .1712179
          7  |    .231731   .1786678     1.30   0.195    -.1184514    .5819134
          8  |   .0388489   .1054654     0.37   0.713    -.1678595    .2455573
          9  |   .0625955   .1036011     0.60   0.546     -.140459      .26565
         10  |   .0761252   .0801135     0.95   0.342    -.0808943    .2331448
         11  |   .0407498   .0866792     0.47   0.638    -.1291382    .2106378
         12  |  -.0915933   .0959825    -0.95   0.340    -.2797154    .0965289
         13  |  -.0228191   .0971173    -0.23   0.814    -.2131655    .1675273
         14  |   .1856215   .1084807     1.71   0.087    -.0269968    .3982399
         15  |   .0519429   .0988254     0.53   0.599    -.1417514    .2456372
         16  |   .0903498   .0988365     0.91   0.361    -.1033663    .2840658
         17  |   .0871866   .0850802     1.02   0.305    -.0795676    .2539407
         18  |  -.0154903   .0918156    -0.17   0.866    -.1954456    .1644649
         19  |   .0051439   .0888756     0.06   0.954     -.169049    .1793369
         20  |   .4516789   .1150449     3.93   0.000      .226195    .6771628
         21  |  -.3366742   .0843757    -3.99   0.000    -.5020475   -.1713008
         22  |   .0340564    .088233     0.39   0.700     -.138877    .2069898
         23  |  -.0374022    .110967    -0.34   0.736    -.2548935    .1800891
         24  |   .0726453   .1122336     0.65   0.517    -.1473284    .2926191
         25  |   .0266734   .0941321     0.28   0.777    -.1578221    .2111689
             |
experience~g |   .0131242   .0089164     1.47   0.141    -.0043516       .0306
experience~q |  -.0374241    .028219    -1.33   0.185    -.0927323    .0178842
share_top_~s |   .0062197   .0615088     0.10   0.919    -.1143353    .1267748
share_top_~d |  -.0379201   .0557846    -0.68   0.497    -.1472558    .0714157
             |
     ireport |
          2  |  -.2896501   .1825896    -1.59   0.113    -.6475192    .0682189
          3  |  -.2107436   .1729875    -1.22   0.223    -.5497929    .1283056
          4  |  -.2788188   .1841608    -1.51   0.130    -.6397672    .0821297
             |
authored_s~o |   .0509561   .0524771     0.97   0.332    -.0518972    .1538093
share_fema~s |  -.1173397   .0485035    -2.42   0.016    -.2124047   -.0222747
editor_pre~t |  -.0225658   .0516462    -0.44   0.662    -.1237904    .0786588
------------------------------------------------------------------------------
Note: dy/dx for factor levels is the discrete change from the base level.
(est4 stored)

. 
209
estadd local Window "[`threshold'$\pm$0.50]"
estadd local Window "[2.58$\pm$0.50]"

. estadd local Window "[`threshold'$\pm$0.50]"

added macro:
             e(Window) : "[2.58$\pm$0.50]"

. 
210
sum `depvar' if t>(`threshold'-0.5) & t<(`threshold'+0.5) & method=="RCT"
sum sign_1pct if t>(2.58-0.5) & t<(2.58+0.5) & method=="RCT"

. sum `depvar' if t>(`threshold'-0.5) & t<(`threshold'+0.5) 
> & method=="RCT"

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
   sign_1pct |        741    .3711201    .4834308          0          1

. 
211
estadd local rct_sign = round(r(mean), 0.01)

. estadd local rct_sign = round(r(mean), 0.01)

added macro:
           e(rct_sign) : ".37"

. 
212
213
probit `depvar' DID IV RDD i.year i.unique_j experience_avg experience_avg_sq share_top_authors share_top_phd i.ireport authored_solo share_female_authors editor_present if t>(`threshold'-0.35) & t<(`threshold'+0.35) [`weight1'`weight2'], cluster(journal_article_cluster)
probit sign_1pct DID IV RDD i.year i.unique_j experience_avg experience_avg_sq share_top_authors share_top_phd i.ireport authored_solo share_female_authors editor_present if t>(2.58-0.35) & t<(2.58+0.35) [pw=aw], cluster(journal_article_cluster)

. probit `depvar' DID IV RDD i.year i.unique_j experience_av
> g experience_avg_sq share_top_authors share_top_phd i.ireport authored_solo s
> hare_female_authors editor_present if t>(`threshold'-0.35) & t<(`threshold'+0
> .35) [`weight1'`weight2'], cluster(journal_article_cluster)

note: 1.ireport != 0 predicts failure perfectly;
      1.ireport omitted and 1 obs not used.

note: 4.ireport omitted because of collinearity.
Iteration 0:   log pseudolikelihood = -447631.12  
Iteration 1:   log pseudolikelihood = -430154.08  
Iteration 2:   log pseudolikelihood = -430104.52  
Iteration 3:   log pseudolikelihood = -430104.51  

Probit regression                                       Number of obs =  1,850
                                                        Wald chi2(36) =  64.68
                                                        Prob > chi2   = 0.0023
Log pseudolikelihood = -430104.51                       Pseudo R2     = 0.0392

              (Std. err. adjusted for 411 clusters in journal_article_cluster)
------------------------------------------------------------------------------
             |               Robust
   sign_1pct | Coefficient  std. err.      z    P>|z|     [95% conf. interval]
-------------+----------------------------------------------------------------
         DID |   .0694135   .1441847     0.48   0.630    -.2131833    .3520104
          IV |  -.0486364   .1217521    -0.40   0.690    -.2872661    .1899933
         RDD |  -.2004576   .1899846    -1.06   0.291    -.5728206    .1719054
             |
        year |
       2018  |   .0373967   .1137537     0.33   0.742    -.1855564    .2603498
             |
    unique_j |
          2  |   .3211505   .6069604     0.53   0.597    -.8684701    1.510771
          3  |   .9409668   .2810071     3.35   0.001     .3902029    1.491731
          4  |    .001558    .271082     0.01   0.995    -.5297529     .532869
          5  |   .9615514   .6286406     1.53   0.126    -.2705615    2.193664
          6  |  -.5400524   .7262664    -0.74   0.457    -1.963508    .8834035
          7  |   .0320907   .2486539     0.13   0.897    -.4552621    .5194434
          8  |   .1020781   .2800466     0.36   0.715    -.4468031    .6509594
          9  |   .4289812   .2343286     1.83   0.067    -.0302945    .8882568
         10  |   .2512324   .2017984     1.24   0.213    -.1442851      .64675
         11  |   .2129032   .2487633     0.86   0.392    -.2746639    .7004702
         12  |   .0279251   .3249122     0.09   0.932    -.6088911    .6647413
         13  |   .0192811   .2711351     0.07   0.943    -.5121339    .5506961
         14  |   .5804223   .2902839     2.00   0.046     .0114764    1.149368
         15  |   .0268399   .2832367     0.09   0.925    -.5282938    .5819736
         16  |    .345085   .2720131     1.27   0.205    -.1880509     .878221
         17  |  -.1002304      .5408    -0.19   0.853    -1.160179     .959718
         18  |    .243329   .2607562     0.93   0.351    -.2677438    .7544019
         19  |  -.0282034   .2315294    -0.12   0.903    -.4819926    .4255858
         20  |   .9469508   .4077359     2.32   0.020     .1478031    1.746099
         21  |  -.3966219   .6417485    -0.62   0.537    -1.654426    .8611821
         22  |   .2167314   .2335249     0.93   0.353     -.240969    .6744318
         23  |  -.1683029   .2905126    -0.58   0.562    -.7376971    .4010914
         24  |    .534512   .2960957     1.81   0.071    -.0458249    1.114849
         25  |   .2822675   .2642241     1.07   0.285    -.2356022    .8001373
             |
experience~g |   .0368621   .0278063     1.33   0.185    -.0176373    .0913616
experience~q |  -.1124292   .1037008    -1.08   0.278     -.315679    .0908207
share_top_~s |   .0015571   .1809837     0.01   0.993    -.3531645    .3562787
share_top_~d |   .0675872   .1692833     0.40   0.690     -.264202    .3993764
             |
     ireport |
          3  |   .1120985   .1484976     0.75   0.450    -.1789515    .4031485
          4  |          0  (omitted)
             |
authored_s~o |   .1781958   .1495602     1.19   0.233    -.1149369    .4713284
share_fema~s |  -.2586775    .142706    -1.81   0.070    -.5383761    .0210212
editor_pre~t |  -.0302245   .1400717    -0.22   0.829    -.3047601     .244311
       _cons |  -.6583336   .3390612    -1.94   0.052    -1.322881    .0062141
------------------------------------------------------------------------------

. 
214
eststo : margins, dydx(*) post

. eststo : margins, dydx(*) post

Average marginal effects                                 Number of obs = 1,850
Model VCE: Robust

Expression: Pr(sign_1pct), predict()
dy/dx wrt:  DID IV RDD 2018.year 2.unique_j 3.unique_j 4.unique_j 5.unique_j
            6.unique_j 7.unique_j 8.unique_j 9.unique_j 10.unique_j
            11.unique_j 12.unique_j 13.unique_j 14.unique_j 15.unique_j
            16.unique_j 17.unique_j 18.unique_j 19.unique_j 20.unique_j
            21.unique_j 22.unique_j 23.unique_j 24.unique_j 25.unique_j
            experience_avg experience_avg_sq share_top_authors share_top_phd
            3.ireport 4.ireport authored_solo share_female_authors
            editor_present

------------------------------------------------------------------------------
             |            Delta-method
             |      dy/dx   std. err.      z    P>|z|     [95% conf. interval]
-------------+----------------------------------------------------------------
         DID |   .0263101   .0546511     0.48   0.630    -.0808041    .1334244
          IV |  -.0184349   .0461199    -0.40   0.689    -.1088283    .0719585
         RDD |  -.0759804   .0717566    -1.06   0.290    -.2166207    .0646599
             |
        year |
       2018  |          .  (not estimable)
             |
    unique_j |
          2  |          .  (not estimable)
          3  |          .  (not estimable)
          4  |          .  (not estimable)
          5  |          .  (not estimable)
          6  |          .  (not estimable)
          7  |          .  (not estimable)
          8  |          .  (not estimable)
          9  |          .  (not estimable)
         10  |          .  (not estimable)
         11  |          .  (not estimable)
         12  |          .  (not estimable)
         13  |          .  (not estimable)
         14  |          .  (not estimable)
         15  |          .  (not estimable)
         16  |          .  (not estimable)
         17  |          .  (not estimable)
         18  |          .  (not estimable)
         19  |          .  (not estimable)
         20  |          .  (not estimable)
         21  |          .  (not estimable)
         22  |          .  (not estimable)
         23  |          .  (not estimable)
         24  |          .  (not estimable)
         25  |          .  (not estimable)
             |
experience~g |    .013972   .0105024     1.33   0.183    -.0066124    .0345564
experience~q |  -.0426146   .0392336    -1.09   0.277     -.119511    .0342818
share_top_~s |   .0005902   .0686002     0.01   0.993    -.1338636    .1350441
share_top_~d |   .0256179   .0641246     0.40   0.690    -.1000639    .1512998
             |
     ireport |
          3  |          .  (not estimable)
          4  |          .  (not estimable)
             |
authored_s~o |   .0675424    .056457     1.20   0.232    -.0431114    .1781962
share_fema~s |  -.0980478   .0536235    -1.83   0.067    -.2031478    .0070523
editor_pre~t |  -.0114561   .0530783    -0.22   0.829    -.1154878    .0925755
------------------------------------------------------------------------------
Note: dy/dx for factor levels is the discrete change from the base level.
(est5 stored)

. 
215
estadd local Window "[`threshold'$\pm$0.35]"
estadd local Window "[2.58$\pm$0.35]"

. estadd local Window "[`threshold'$\pm$0.35]"

added macro:
             e(Window) : "[2.58$\pm$0.35]"

. 
216
sum `depvar' if t>(`threshold'-0.35) & t<(`threshold'+0.35) & method=="RCT"
sum sign_1pct if t>(2.58-0.35) & t<(2.58+0.35) & method=="RCT"

. sum `depvar' if t>(`threshold'-0.35) & t<(`threshold'+0.35
> ) & method=="RCT"

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
   sign_1pct |        520    .4153846    .4932627          0          1

. 
217
estadd local rct_sign = round(r(mean), 0.01)

. estadd local rct_sign = round(r(mean), 0.01)

added macro:
           e(rct_sign) : ".42"

. 
218
219
probit `depvar' DID IV RDD i.year i.unique_j experience_avg experience_avg_sq share_top_authors share_top_phd i.ireport authored_solo share_female_authors editor_present if t>(`threshold'-0.2) & t<(`threshold'+0.2) [`weight1'`weight2'], cluster(journal_article_cluster)
probit sign_1pct DID IV RDD i.year i.unique_j experience_avg experience_avg_sq share_top_authors share_top_phd i.ireport authored_solo share_female_authors editor_present if t>(2.58-0.2) & t<(2.58+0.2) [pw=aw], cluster(journal_article_cluster)

. probit `depvar' DID IV RDD i.year i.unique_j experience_av
> g experience_avg_sq share_top_authors share_top_phd i.ireport authored_solo s
> hare_female_authors editor_present if t>(`threshold'-0.2) & t<(`threshold'+0.
> 2) [`weight1'`weight2'], cluster(journal_article_cluster)

note: 21.unique_j != 0 predicts failure perfectly;
      21.unique_j omitted and 1 obs not used.

note: 1.ireport != 0 predicts failure perfectly;
      1.ireport omitted and 1 obs not used.

note: 4.ireport omitted because of collinearity.
Iteration 0:   log pseudolikelihood = -256050.16  
Iteration 1:   log pseudolikelihood =  -240145.8  
Iteration 2:   log pseudolikelihood = -240053.29  
Iteration 3:   log pseudolikelihood = -240053.25  
Iteration 4:   log pseudolikelihood = -240053.25  

Probit regression                                       Number of obs =  1,079
                                                        Wald chi2(34) =      .
                                                        Prob > chi2   =      .
Log pseudolikelihood = -240053.25                       Pseudo R2     = 0.0625

              (Std. err. adjusted for 344 clusters in journal_article_cluster)
------------------------------------------------------------------------------
             |               Robust
   sign_1pct | Coefficient  std. err.      z    P>|z|     [95% conf. interval]
-------------+----------------------------------------------------------------
         DID |  -.1706136   .1700649    -1.00   0.316    -.5039347    .1627075
          IV |  -.0328247   .1618584    -0.20   0.839    -.3500613    .2844118
         RDD |  -.3499436   .2648305    -1.32   0.186     -.869002    .1691147
             |
        year |
       2018  |   .0213381    .126176     0.17   0.866    -.2259623    .2686384
             |
    unique_j |
          2  |   .0173573   .6029519     0.03   0.977    -1.164407    1.199121
          3  |   1.251681   .7346801     1.70   0.088    -.1882652    2.691628
          4  |   .0527726   .3628033     0.15   0.884    -.6583088    .7638539
          5  |   1.740364   .7273633     2.39   0.017     .3147587     3.16597
          6  |  -.0393111   .9667391    -0.04   0.968    -1.934085    1.855463
          7  |  -.2597284    .422492    -0.61   0.539    -1.087797    .5683407
          8  |   .2464017   .3753992     0.66   0.512    -.4893672    .9821706
          9  |   .4398809   .3360071     1.31   0.190    -.2186809    1.098443
         10  |   .3974267   .3894363     1.02   0.307    -.3658545    1.160708
         11  |   .7988205   .3706174     2.16   0.031     .0724237    1.525217
         12  |  -.0046464   .4289148    -0.01   0.991    -.8453041    .8360112
         13  |   .4774205   .3502264     1.36   0.173    -.2090105    1.163852
         14  |   .5561059   .3787608     1.47   0.142    -.1862516    1.298463
         15  |   .3864028   .3752701     1.03   0.303    -.3491131    1.121919
         16  |   .7829345   .4034111     1.94   0.052    -.0077367    1.573606
         17  |   1.117616   .3288304     3.40   0.001     .4731205    1.762112
         18  |   .6331085   .3601299     1.76   0.079    -.0727332     1.33895
         19  |   .0715211   .3686188     0.19   0.846    -.6509584    .7940006
         20  |   .8428357   .5836691     1.44   0.149    -.3011347    1.986806
         22  |   .6743445   .3491103     1.93   0.053     -.009899    1.358588
         23  |  -.0854744   .4047588    -0.21   0.833    -.8787871    .7078383
         24  |   .3523933   .3844433     0.92   0.359    -.4011018    1.105888
         25  |   .4547123   .3595614     1.26   0.206    -.2500151     1.15944
             |
experience~g |   .0149618   .0331977     0.45   0.652    -.0501045     .080028
experience~q |  -.0633345   .1244869    -0.51   0.611    -.3073244    .1806553
share_top_~s |   .1885915   .1982024     0.95   0.341    -.1998779     .577061
share_top_~d |   .0203048    .186255     0.11   0.913    -.3447482    .3853579
             |
     ireport |
          3  |   .2571571   .1830048     1.41   0.160    -.1015257    .6158398
          4  |          0  (omitted)
             |
authored_s~o |    .128888    .175336     0.74   0.462    -.2147643    .4725402
share_fema~s |  -.4534533   .1798909    -2.52   0.012    -.8060329   -.1008737
editor_pre~t |   .0492618   .1660957     0.30   0.767    -.2762799    .3748034
       _cons |  -.6916964    .440737    -1.57   0.117    -1.555525    .1721324
------------------------------------------------------------------------------

. 
220
eststo : margins, dydx(*) post

. eststo : margins, dydx(*) post

Average marginal effects                                 Number of obs = 1,079
Model VCE: Robust

Expression: Pr(sign_1pct), predict()
dy/dx wrt:  DID IV RDD 2018.year 2.unique_j 3.unique_j 4.unique_j 5.unique_j
            6.unique_j 7.unique_j 8.unique_j 9.unique_j 10.unique_j
            11.unique_j 12.unique_j 13.unique_j 14.unique_j 15.unique_j
            16.unique_j 17.unique_j 18.unique_j 19.unique_j 20.unique_j
            22.unique_j 23.unique_j 24.unique_j 25.unique_j experience_avg
            experience_avg_sq share_top_authors share_top_phd 3.ireport
            4.ireport authored_solo share_female_authors editor_present

------------------------------------------------------------------------------
             |            Delta-method
             |      dy/dx   std. err.      z    P>|z|     [95% conf. interval]
-------------+----------------------------------------------------------------
         DID |  -.0633719   .0630006    -1.01   0.314    -.1868508    .0601071
          IV |  -.0121923   .0601269    -0.20   0.839    -.1300389    .1056544
         RDD |  -.1299814   .0976794    -1.33   0.183    -.3214294    .0614667
             |
        year |
       2018  |          .  (not estimable)
             |
    unique_j |
          2  |          .  (not estimable)
          3  |          .  (not estimable)
          4  |          .  (not estimable)
          5  |          .  (not estimable)
          6  |          .  (not estimable)
          7  |          .  (not estimable)
          8  |          .  (not estimable)
          9  |          .  (not estimable)
         10  |          .  (not estimable)
         11  |          .  (not estimable)
         12  |          .  (not estimable)
         13  |          .  (not estimable)
         14  |          .  (not estimable)
         15  |          .  (not estimable)
         16  |          .  (not estimable)
         17  |          .  (not estimable)
         18  |          .  (not estimable)
         19  |          .  (not estimable)
         20  |          .  (not estimable)
         22  |          .  (not estimable)
         23  |          .  (not estimable)
         24  |          .  (not estimable)
         25  |          .  (not estimable)
             |
experience~g |   .0055573   .0123209     0.45   0.652    -.0185912    .0297059
experience~q |  -.0235247   .0462179    -0.51   0.611      -.11411    .0670607
share_top_~s |   .0700495   .0736536     0.95   0.342    -.0743089     .214408
share_top_~d |   .0075419   .0691589     0.11   0.913     -.128007    .1430909
             |
     ireport |
          3  |          .  (not estimable)
          4  |          .  (not estimable)
             |
authored_s~o |   .0478735   .0649058     0.74   0.461    -.0793395    .1750866
share_fema~s |  -.1684285   .0656553    -2.57   0.010    -.2971105   -.0397464
editor_pre~t |   .0182975   .0616811     0.30   0.767    -.1025951    .1391902
------------------------------------------------------------------------------
Note: dy/dx for factor levels is the discrete change from the base level.
(est6 stored)

. 
221
estadd local Window "[`threshold'$\pm$0.20]"
estadd local Window "[2.58$\pm$0.20]"

. estadd local Window "[`threshold'$\pm$0.20]"

added macro:
             e(Window) : "[2.58$\pm$0.20]"

. 
222
sum `depvar' if t>(`threshold'-0.2) & t<(`threshold'+0.2) & method=="RCT"
sum sign_1pct if t>(2.58-0.2) & t<(2.58+0.2) & method=="RCT"

. sum `depvar' if t>(`threshold'-0.2) & t<(`threshold'+0.2) 
> & method=="RCT"

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
   sign_1pct |        301     .461794    .4993684          0          1

. 
223
estadd local rct_sign = round(r(mean), 0.01)

. estadd local rct_sign = round(r(mean), 0.01)

added macro:
           e(rct_sign) : ".46"

. 
224
225
esttab, margin ///
esttab, margin keep(DID IV RDD top5 2018.year experience_avg experience_avg_sq share_top_authors share_top_phd ) label stats(N Window rct_sign, fmt(%9.0fc) labels("Observations" "Window" "RCT sig rate"))

. esttab, margin keep(DID IV RDD top5 2018.year experience_a
> vg experience_avg_sq share_top_authors share_top_phd ) label stats(N Window r
> ct_sign, fmt(%9.0fc) labels("Observations" "Window" "RCT sig rate"))

-------------------------------------------------------------------------------
> -------------------------------------
                              (1)             (2)             (3)             (
> 4)             (5)             (6)   
                                                                               
>                                      
-------------------------------------------------------------------------------
> -------------------------------------
DID                        0.0500          0.0402          0.0214         0.009
> 57          0.0263         -0.0634   
                           (1.03)          (0.89)          (0.45)          (0.2
> 0)          (0.48)         (-1.01)   

IV                         0.0194         0.00871         -0.0174         -0.03
> 94         -0.0184         -0.0122   
                           (0.46)          (0.22)         (-0.43)         (-0.9
> 5)         (-0.40)         (-0.20)   

RDD                       -0.0821         -0.0825         -0.0935         -0.09
> 18         -0.0760          -0.130   
                          (-1.21)         (-1.33)         (-1.51)         (-1.4
> 2)         (-1.06)         (-1.33)   

Top 5                                      0.0287          -0.101              
>                                      
                                           (0.52)         (-1.00)              
>                                      

Year=2018                                  0.0102         0.00843          0.02
> 19               0               0   
                                           (0.25)          (0.20)          (0.5
> 3)             (.)             (.)   

Experience                                 0.0180          0.0161          0.01
> 31          0.0140         0.00556   
                                           (1.91)          (1.78)          (1.4
> 7)          (1.33)          (0.45)   

Experience squared                        -0.0494         -0.0437         -0.03
> 74         -0.0426         -0.0235   
                                          (-1.64)         (-1.51)         (-1.3
> 3)         (-1.09)         (-0.51)   

Top institution                           0.00318         0.00641         0.006
> 22        0.000590          0.0700   
                                           (0.05)          (0.10)          (0.1
> 0)          (0.01)          (0.95)   

Top PhD institution                       -0.0511         -0.0526         -0.03
> 79          0.0256         0.00754   
                                          (-0.96)         (-0.98)         (-0.6
> 8)          (0.40)          (0.11)   
-------------------------------------------------------------------------------
> -------------------------------------
Observations                2,689           2,689           2,689           2,6
> 89           1,850           1,079   
Window               [2.58$\pm$0.50]    [2.58$\pm$0.50]    [2.58$\pm$0.50]    [
> 2.58$\pm$0.50]    [2.58$\pm$0.35]    [2.58$\pm$0.20]   
RCT sig rate                  .37             .37             .37             .
> 37             .42             .46   
-------------------------------------------------------------------------------
> -------------------------------------
Marginal effects; t statistics in parentheses
 (d) for discrete change of dummy variable from 0 to 1
* p<0.05, ** p<0.01, *** p<0.001

. 
226
keep(DID IV RDD top5 2018.year experience_avg experience_avg_sq share_top_authors share_top_phd ) label stats(N Window rct_sign, fmt(%9.0fc) labels("Observations" "Window" "RCT sig rate"))
227
228
esttab using table_A6_caliper_`depvar'.tex, margin ///
esttab using table_A6_caliper_sign_1pct.tex, margin keep(DID IV RDD top5 2018.year experience_avg experience_avg_sq share_top_authors share_top_phd) label  stats(N Window rct_sign, fmt(%9.0fc) labels("Observations" "Window" "RCT sig rate")) mtitles() nomtitles nostar compress se(3) b(3) replace nogaps noomitted indicate( "Reporting Method = *ireport" "Solo Authored = authored_solo" "Share Female Authors = share_female_authors" "Editor = editor_present" "Field FE = FINANCE" "Journal FE = *unique_j" , labels("Y" " ")) nonotes

. esttab using "table_A6_caliper_sign_1pct.tex", margin keep(DID IV 
> RDD top5 2018.year experience_avg experience_avg_sq share_top_authors share_t
> op_phd) label  stats(N Window rct_sign, fmt(%9.0fc) labels("Observations" "Wi
> ndow" "RCT sig rate")) mtitles() nomtitles nostar compress se(3) b(3) replace
>  nogaps noomitted indicate( "Reporting Method = *ireport" "Solo Authored = au
> thored_solo" "Share Female Authors = share_female_authors" "Editor = editor_p
> resent" "Field FE = FINANCE" "Journal FE = *unique_j" , labels("Y" " ")) nono
> tes
(output written to table_A6_caliper_sign_1pct.tex)

. 
229
keep(DID IV RDD top5 2018.year experience_avg experience_avg_sq share_top_authors share_top_phd) label  stats(N Window rct_sign, fmt(%9.0fc) labels("Observations" "Window" "RCT sig rate")) ///
230
mtitles() nomtitles nostar ///
231
 compress se(3) b(3) replace nogaps noomitted ///
232
indicate( ///
233
"Reporting Method = *ireport" ///
234
"Solo Authored = authored_solo" ///
235
"Share Female Authors = share_female_authors" ///
236
"Editor = editor_present" ///
237
"Field FE = FINANCE" ///
238
"Journal FE = *unique_j" ///
239
, labels("Y" " ")) ///
240
nonotes
241
242
243
244
1
/* This file was run to create the ado folder, but does not need to be run given the ado folder exists */
2
/* setup.do */
3
sysdir

. sysdir
   STATA:  /usr/local/stata/
    BASE:  /usr/local/stata/ado/base/
    SITE:  /usr/local/ado/
    PLUS:  ~/ado/plus/
PERSONAL:  ~/ado/personal/
OLDPLACE:  ~/ado/

. 
4
5
/* add packages to the macro */
6
7
* *** Add required packages from SSC to this list ***
8
    local ssc_packages "estout egenmore"

. local ssc_packages "estout egenmore"

. 
9
10
    // local ssc_packages "estout boottest"
11
    
12
    if !missing("`ssc_packages'") {
13
        foreach pkg in `ssc_packages' {
foreach pkg in estout egenmore {
14
            dis "Installing `pkg'"
dis "Installing estout"
Installing estout
dis "Installing egenmore"
Installing egenmore
15
            ssc install `pkg', replace
16
        }
17
    }
18
19
    * Install packages using net
20
    *  net install yaml, from("https://raw.githubusercontent.com/gslab-econ/stata-misc/master/")
21
    
22
/* other commands */
23
24
/* after installing all packages, it may be necessary to issue the mata mlib index command */
25
	mata: mata mlib index

. mata: mata mlib index
.mlib libraries to be searched are now
    lmatabase;lmatamcmc;lmatafc;lmatapss;lmatasem;lmatasp;lmatabma;lmatasvy;lma
> tacollect;lmataerm;lmatatab;lmatami;lmatalasso;lmataado;lmatamixlog;lmataopt;
> lmatagsem;lmatameta;lmatapostest;lmatanumlib;lmatapath;lnwspgr;lintegrate;lxt
> spj;lout;lsplagvar;lmetapreg;lepimodels;lcureregr_lf;lusexmlex;lfieldarea;lst
> ns;lmultistate;lxtabond2;lgo;ltolong;lplssem;lspwmatrix;lxtbreak;lskolenik;ls
> qbm;lasdoc;ltestcase;lcmc;lsomersd;lgeochart;lxtdpdqml;lstjm;ltoxl_v13;lasreg
> ;lstpm2;lmcmclinear;lmoremata;lratetable;lasgen;linorm;leefanalytics;licio;lq
> env9;lboottest;lnearstat;lmargdistfit;lcem;lpoparms;lhetsar;lsynth_mata_subr;
> lsetpoisson;lcolrspace;ligencox;librecycle;lsmwoodbury;lirand;ltihtest11;lghk
> 2;lalogit;lkinkyreg;lkhb;lelabel;lasrol;lstandsurv;lqenv10;lsfpanel;lpanelhet
> ero;lmoremata11;ltoxl_v14;lquaidsce;lparallel;lasn;lpsweight;lextreme;lrcl;ls
> kolenik10;lmmtxttool;lxtdpdgmm;lspmat;libjson;lfrcount;lgetsymbols;lmetadta;l
> kdens;lmhtreg;lsq;lstaft;lmatrixtools;lbasetable;ltihtest13;lmetan;lftools;lr
> pn;lsbmeff;lgtools;lsae_povmap;lstmt;lsfcross;llog2markup;lsavespss;lfreduse;
> ltihtest12;ludiff;lmerlin;lxtseqreg;lcmp;lportheory;lmoremata10;l_cfrmt;lpetp
> oisson;lstrcs;livreg2;lguttmanl;lmhtexp;lsls;lsmclpres;lmoremata14;lxtivdfreg
> ;lflexmat;lxsmle;larimaauto;luse13

. 
26
27
28
set more off, perm

. set more off, perm
(set more preference recorded)

. 
29
30
1
*** This script generates Figures 3,4,5, A1 and A2 in our comment which are replications of BCH's Figures 1,2,3,5 and 6 (BCH's Figure 4 is replicated using R)
2
3
clear

. clear

. 
4
set more off

. set more off

. 
5
6
* specify directories where data are located and where results should be stored
7
global dir_main  : pwd

. global dir_main  : pwd

. 
8
global dir_data "$dir_main/Data"
global dir_data "/home/rstudio/repbox/projects_ejd/aer_112_9_9/mod/Scripts/Data"

. global dir_data "$dir_main/Data"

. 
9
global dir_results "$dir_main/Results"
global dir_results "/home/rstudio/repbox/projects_ejd/aer_112_9_9/mod/Scripts/Results"

. global dir_results "$dir_main/Results"

. 
10
11
* read in the data
12
cd "$dir_data" 
cd "/home/rstudio/repbox/projects_ejd/aer_112_9_9/mod/Scripts/Data"

. cd "${repbox_path}/Data"
/home/rstudio/repbox/projects_ejd/aer_112_9_9/mod/Data

. 
13
capture use "MM_new.dta", clear 

. capture use "MM_new.dta", clear

. 
14
15
* set folder to store results
16
cd "$dir_results" 
cd "/home/rstudio/repbox/projects_ejd/aer_112_9_9/mod/Scripts/Results"

. cd "${repbox_path}/Results"
/home/rstudio/repbox/projects_ejd/aer_112_9_9/mod/Results

. 
17
18
*** Figure 3 in our comment
19
histogram t if t <= 10 & keep_obs==1, saving(temp1, replace) title() width(0.1) start(0) fcolor(gs10) lcolor(gs10) kdensity kdenopts(width(0.1)) xtitle(z-statistic, size(large)) ytitle(Density, size(large)) xline(1.65 1.96 2.58, lwidth(thin))  xlabel(0(1)10, labels labsize(large)) ylabel(, labels labsize(large)) legend(off) scheme(s1mono) addplot((kdensity t if t <= 10, bwidth(0.1) lpattern(vshortdash) lcolor(black) ))
histogram t if t <= 10 & keep_obs==1, saving(temp1, replace) title() width(0.1) start(0) fcolor(gs10) lcolor(gs10) kdensity kdenopts(width(0.1)) xtitle(z-statistic, size(large)) ytitle(Density, size(large)) xline(1.65 1.96 2.58, lwidth(thin))  xlabel(0(1)10, labels labsize(large)) ylabel(, labels labsize(large)) legend(off) scheme(s1mono) addplot((kdensity t if t <= 10, bwidth(0.1) lpattern(vshortdash) lcolor(black) ))

. histogram t if t <= 10 & keep_obs==1, saving("`r(repbox_fo
> und_file)'", replace) title() width(0.1) start(0) fcolor(gs10) lcolor(gs10) k
> density kdenopts(width(0.1)) xtitle(z-statistic, size(large)) ytitle(Density,
>  size(large)) xline(1.65 1.96 2.58, lwidth(thin))  xlabel(0(1)10, labels labs
> ize(large)) ylabel(, labels labsize(large)) legend(off) scheme(s1mono) addplo
> t((kdensity t if t <= 10, bwidth(0.1) lpattern(vshortdash) lcolor(black) ))
(bin=100, start=0, width=.1)
(file temp1.gph not found)
file temp1.gph saved

. 
20
graph export figure_3a.pdf, replace 
graph export figure_3a.pdf, replace

. graph export "figure_3a.pdf", replace
file figure_3a.pdf saved as PDF format

. 
21
22
histogram t if t <= 10 & top5==1 & keep_obs==1, title("Top 5") saving(temp2, replace) width(0.1) start(0) fcolor(gs10) lcolor(gs10) kdensity kdenopts(width(0.1)) xtitle(z-statistic, size(large)) ytitle(Density, size(large)) xline(1.65 1.96 2.58, lwidth(thin))  xlabel(0(1)10, labels labsize(large)) ylabel(, labels labsize(large)) legend(off) scheme(s1mono) addplot((kdensity t if t <= 10 & top5==1 , bwidth(0.1) lpattern(vshortdash) lcolor(black) ))
histogram t if t <= 10 & top5==1 & keep_obs==1, title("Top 5") saving(temp2, replace) width(0.1) start(0) fcolor(gs10) lcolor(gs10) kdensity kdenopts(width(0.1)) xtitle(z-statistic, size(large)) ytitle(Density, size(large)) xline(1.65 1.96 2.58, lwidth(thin))  xlabel(0(1)10, labels labsize(large)) ylabel(, labels labsize(large)) legend(off) scheme(s1mono) addplot((kdensity t if t <= 10 & top5==1 , bwidth(0.1) lpattern(vshortdash) lcolor(black) ))

. histogram t if t <= 10 & top5==1 & keep_obs==1, title("Top
>  5") saving("temp2", replace) width(0.1) start(0) fcolor(gs1
> 0) lcolor(gs10) kdensity kdenopts(width(0.1)) xtitle(z-statistic, size(large)
> ) ytitle(Density, size(large)) xline(1.65 1.96 2.58, lwidth(thin))  xlabel(0(
> 1)10, labels labsize(large)) ylabel(, labels labsize(large)) legend(off) sche
> me(s1mono) addplot((kdensity t if t <= 10 & top5==1 , bwidth(0.1) lpattern(vs
> hortdash) lcolor(black) ))
(bin=100, start=0, width=.1)
(file temp2.gph not found)
file temp2.gph saved

. 
23
graph export figure_3b.pdf, replace
graph export figure_3b.pdf, replace

. graph export "figure_3b.pdf", replace
file figure_3b.pdf saved as PDF format

. 
24
25
histogram t if t <= 10 & top5==0 & keep_obs==1, title("Non-Top 5") saving(temp3, replace) width(0.1) start(0) fcolor(gs10) lcolor(gs10) kdensity kdenopts(width(0.1)) xtitle(z-statistic, size(large)) ytitle(Density, size(large)) xline(1.65 1.96 2.58, lwidth(thin))  xlabel(0(1)10, labels labsize(large)) ylabel(, labels labsize(large)) legend(off) scheme(s1mono) addplot((kdensity t if t <= 10 & top5==0, bwidth(0.1) lpattern(vshortdash) lcolor(black) ))
histogram t if t <= 10 & top5==0 & keep_obs==1, title("Non-Top 5") saving(temp3, replace) width(0.1) start(0) fcolor(gs10) lcolor(gs10) kdensity kdenopts(width(0.1)) xtitle(z-statistic, size(large)) ytitle(Density, size(large)) xline(1.65 1.96 2.58, lwidth(thin))  xlabel(0(1)10, labels labsize(large)) ylabel(, labels labsize(large)) legend(off) scheme(s1mono) addplot((kdensity t if t <= 10 & top5==0, bwidth(0.1) lpattern(vshortdash) lcolor(black) ))

. histogram t if t <= 10 & top5==0 & keep_obs==1, title("Non
> -Top 5") saving("temp3", replace) width(0.1) start(0) fcolor
> (gs10) lcolor(gs10) kdensity kdenopts(width(0.1)) xtitle(z-statistic, size(la
> rge)) ytitle(Density, size(large)) xline(1.65 1.96 2.58, lwidth(thin))  xlabe
> l(0(1)10, labels labsize(large)) ylabel(, labels labsize(large)) legend(off) 
> scheme(s1mono) addplot((kdensity t if t <= 10 & top5==0, bwidth(0.1) lpattern
> (vshortdash) lcolor(black) ))
(bin=100, start=0, width=.1)
(file temp3.gph not found)
file temp3.gph saved

. 
26
graph export figure_3c.pdf, replace
graph export figure_3c.pdf, replace

. graph export "figure_3c.pdf", replace
file figure_3c.pdf saved as PDF format

. 
27
28
29
*** Figure 4 in our comment
30
31
histogram t if t <= 10 & method=="DID" & keep_obs==1 , title("DID") saving(temp1, replace) width(0.1) start(0) fcolor(gs10) lcolor(gs10) kdensity kdenopts(width(0.1)) xtitle(z-statistic, size(large)) ytitle(Density, size(large)) xline(1.65 1.96 2.58, lwidth(thin)) xlabel(0(1)10, labels labsize(large)) ylabel(, labels labsize(large)) legend(off) scheme(s1mono) addplot((kdensity t if t <= 10 & method=="DID", bwidth(0.1) lpattern(vshortdash) lcolor(black) ))
histogram t if t <= 10 & method=="DID" & keep_obs==1 , title("DID") saving(temp1, replace) width(0.1) start(0) fcolor(gs10) lcolor(gs10) kdensity kdenopts(width(0.1)) xtitle(z-statistic, size(large)) ytitle(Density, size(large)) xline(1.65 1.96 2.58, lwidth(thin)) xlabel(0(1)10, labels labsize(large)) ylabel(, labels labsize(large)) legend(off) scheme(s1mono) addplot((kdensity t if t <= 10 & method=="DID", bwidth(0.1) lpattern(vshortdash) lcolor(black) ))

. histogram t if t <= 10 & method=="DID" & keep_obs==1 , tit
> le("DID") saving("temp1", replace) width(0.1) start(0) fcolo
> r(gs10) lcolor(gs10) kdensity kdenopts(width(0.1)) xtitle(z-statistic, size(l
> arge)) ytitle(Density, size(large)) xline(1.65 1.96 2.58, lwidth(thin)) xlabe
> l(0(1)10, labels labsize(large)) ylabel(, labels labsize(large)) legend(off) 
> scheme(s1mono) addplot((kdensity t if t <= 10 & method=="DID", bwidth(0.1) lp
> attern(vshortdash) lcolor(black) ))
(bin=100, start=0, width=.1)
file temp1.gph saved

. 
32
graph export figure_4_did.pdf, replace
graph export figure_4_did.pdf, replace

. graph export "figure_4_did.pdf", replace
file figure_4_did.pdf saved as PDF format

. 
33
histogram t if t <= 10 & method=="IV" & keep_obs==1 , title("IV") saving(temp1, replace) width(0.1) start(0) fcolor(gs10) lcolor(gs10) kdensity kdenopts(width(0.1)) xtitle(z-statistic, size(large)) ytitle(Density, size(large)) xline(1.65 1.96 2.58, lwidth(thin)) xlabel(0(1)10, labels labsize(large)) ylabel(, labels labsize(large)) legend(off) scheme(s1mono) addplot((kdensity t if t <= 10 & method=="IV", bwidth(0.1) lpattern(vshortdash) lcolor(black) ))
histogram t if t <= 10 & method=="IV" & keep_obs==1 , title("IV") saving(temp1, replace) width(0.1) start(0) fcolor(gs10) lcolor(gs10) kdensity kdenopts(width(0.1)) xtitle(z-statistic, size(large)) ytitle(Density, size(large)) xline(1.65 1.96 2.58, lwidth(thin)) xlabel(0(1)10, labels labsize(large)) ylabel(, labels labsize(large)) legend(off) scheme(s1mono) addplot((kdensity t if t <= 10 & method=="IV", bwidth(0.1) lpattern(vshortdash) lcolor(black) ))

. histogram t if t <= 10 & method=="IV" & keep_obs==1 , titl
> e("IV") saving("temp1", replace) width(0.1) start(0) fcolor(
> gs10) lcolor(gs10) kdensity kdenopts(width(0.1)) xtitle(z-statistic, size(lar
> ge)) ytitle(Density, size(large)) xline(1.65 1.96 2.58, lwidth(thin)) xlabel(
> 0(1)10, labels labsize(large)) ylabel(, labels labsize(large)) legend(off) sc
> heme(s1mono) addplot((kdensity t if t <= 10 & method=="IV", bwidth(0.1) lpatt
> ern(vshortdash) lcolor(black) ))
(bin=100, start=0, width=.1)
file temp1.gph saved

. 
34
graph export figure_4_iv.pdf, replace
graph export figure_4_iv.pdf, replace

. graph export "figure_4_iv.pdf", replace
file figure_4_iv.pdf saved as PDF format

. 
35
histogram t if t <= 10 & method=="RCT" & keep_obs==1 , title("RCT") saving(temp1, replace) width(0.1) start(0) fcolor(gs10) lcolor(gs10) kdensity kdenopts(width(0.1)) xtitle(z-statistic, size(large)) ytitle(Density, size(large)) xline(1.65 1.96 2.58, lwidth(thin)) xlabel(0(1)10, labels labsize(large)) ylabel(, labels labsize(large)) legend(off) scheme(s1mono) addplot((kdensity t if t <= 10 & method=="RCT", bwidth(0.1) lpattern(vshortdash) lcolor(black) ))
histogram t if t <= 10 & method=="RCT" & keep_obs==1 , title("RCT") saving(temp1, replace) width(0.1) start(0) fcolor(gs10) lcolor(gs10) kdensity kdenopts(width(0.1)) xtitle(z-statistic, size(large)) ytitle(Density, size(large)) xline(1.65 1.96 2.58, lwidth(thin)) xlabel(0(1)10, labels labsize(large)) ylabel(, labels labsize(large)) legend(off) scheme(s1mono) addplot((kdensity t if t <= 10 & method=="RCT", bwidth(0.1) lpattern(vshortdash) lcolor(black) ))

. histogram t if t <= 10 & method=="RCT" & keep_obs==1 , tit
> le("RCT") saving("temp1", replace) width(0.1) start(0) fcolo
> r(gs10) lcolor(gs10) kdensity kdenopts(width(0.1)) xtitle(z-statistic, size(l
> arge)) ytitle(Density, size(large)) xline(1.65 1.96 2.58, lwidth(thin)) xlabe
> l(0(1)10, labels labsize(large)) ylabel(, labels labsize(large)) legend(off) 
> scheme(s1mono) addplot((kdensity t if t <= 10 & method=="RCT", bwidth(0.1) lp
> attern(vshortdash) lcolor(black) ))
(bin=100, start=0, width=.1)
file temp1.gph saved

. 
36
graph export figure_4_rct.pdf, replace
graph export figure_4_rct.pdf, replace

. graph export "figure_4_rct.pdf", replace
file figure_4_rct.pdf saved as PDF format

. 
37
histogram t if t <= 10 & method=="RDD" & keep_obs==1 , title("RDD") saving(temp1, replace) width(0.1) start(0) fcolor(gs10) lcolor(gs10) kdensity kdenopts(width(0.1)) xtitle(z-statistic, size(large)) ytitle(Density, size(large)) xline(1.65 1.96 2.58, lwidth(thin)) xlabel(0(1)10, labels labsize(large)) ylabel(, labels labsize(large)) legend(off) scheme(s1mono) addplot((kdensity t if t <= 10 & method=="RDD", bwidth(0.1) lpattern(vshortdash) lcolor(black) ))
histogram t if t <= 10 & method=="RDD" & keep_obs==1 , title("RDD") saving(temp1, replace) width(0.1) start(0) fcolor(gs10) lcolor(gs10) kdensity kdenopts(width(0.1)) xtitle(z-statistic, size(large)) ytitle(Density, size(large)) xline(1.65 1.96 2.58, lwidth(thin)) xlabel(0(1)10, labels labsize(large)) ylabel(, labels labsize(large)) legend(off) scheme(s1mono) addplot((kdensity t if t <= 10 & method=="RDD", bwidth(0.1) lpattern(vshortdash) lcolor(black) ))

. histogram t if t <= 10 & method=="RDD" & keep_obs==1 , tit
> le("RDD") saving("temp1", replace) width(0.1) start(0) fcolo
> r(gs10) lcolor(gs10) kdensity kdenopts(width(0.1)) xtitle(z-statistic, size(l
> arge)) ytitle(Density, size(large)) xline(1.65 1.96 2.58, lwidth(thin)) xlabe
> l(0(1)10, labels labsize(large)) ylabel(, labels labsize(large)) legend(off) 
> scheme(s1mono) addplot((kdensity t if t <= 10 & method=="RDD", bwidth(0.1) lp
> attern(vshortdash) lcolor(black) ))
(bin=99, start=0, width=.1)
file temp1.gph saved

. 
38
graph export figure_4_rdd.pdf, replace
graph export figure_4_rdd.pdf, replace

. graph export "figure_4_rdd.pdf", replace
file figure_4_rdd.pdf saved as PDF format

. 
39
40
41
*** Figure 5 in our comment
42
*** Note that we used an approximate merging procedure to get the standard errors for the
43
*** Star Wars data 
44
45
clear all

. clear all

. 
46
set more off

. set more off

. 
47
* read in the data
48
cd "$dir_data" 
cd "/home/rstudio/repbox/projects_ejd/aer_112_9_9/mod/Scripts/Data"

. cd "${repbox_path}/Data"
/home/rstudio/repbox/projects_ejd/aer_112_9_9/mod/Data

. 
49
50
use "starwars_bch_pk.dta", clear

. use "starwars_bch_pk.dta", clear

. 
51
rename journal journal_name

. rename journal journal_name

. 
52
53
append using "MM_new.dta", force

. append using "MM_new.dta", force
(variable journal_name was str30, now str44 to accommodate using data's
       values)
(variable mu_str was str12, now str19 to accommodate using data's values)

. 
54
55
* determine folder to store results
56
cd "$dir_results" 
cd "/home/rstudio/repbox/projects_ejd/aer_112_9_9/mod/Scripts/Results"

. cd "${repbox_path}/Results"
/home/rstudio/repbox/projects_ejd/aer_112_9_9/mod/Results

. 
57
58
capture drop top3

. capture drop top3

. 
59
60
gen top3 = 0

. gen top3 = 0

. 
61
replace top3 = 1 if strpos(journal_name,"Quarterly Journal of Economics")
replace top3 = 1 if strpos(journal_name,"Quarterly Journal of Economics")

. replace top3 = 1 if strpos(journal_name,"Quarterly Journal
>  of Economics")
(7,920 real changes made)

. 
62
replace top3 = 1 if strpos(journal_name,"Journal of Political Economy")
replace top3 = 1 if strpos(journal_name,"Journal of Political Economy")

. replace top3 = 1 if strpos(journal_name,"Journal of Politi
> cal Economy")
(3,480 real changes made)

. 
63
replace top3 = 1 if strpos(journal_name,"American Economic Review")
replace top3 = 1 if strpos(journal_name,"American Economic Review")

. replace top3 = 1 if strpos(journal_name,"American Economic
>  Review")
(9,824 real changes made)

. 
64
65
histogram t if keep_obs==1 & t <= 10 & year<2015 & top3==1 , title("2005-2011") saving(temp1, replace) width(0.1) start(0) fcolor(gs10) lcolor(gs10) kdensity kdenopts(width(0.1)) xtitle(z-statistic, size(large)) ytitle(Density, size(large)) xline(1.65 1.96 2.58, lwidth(thin)) xlabel(0(1)10, labels labsize(large)) ylabel(, labels labsize(large)) legend(off) scheme(s1mono) addplot((kdensity t if t <= 10 & year<2015 & top3==1, bwidth(0.1) lpattern(vshortdash) lcolor(black) ))
histogram t if keep_obs==1 & t <= 10 & year<2015 & top3==1 , title("2005-2011") saving(temp1, replace) width(0.1) start(0) fcolor(gs10) lcolor(gs10) kdensity kdenopts(width(0.1)) xtitle(z-statistic, size(large)) ytitle(Density, size(large)) xline(1.65 1.96 2.58, lwidth(thin)) xlabel(0(1)10, labels labsize(large)) ylabel(, labels labsize(large)) legend(off) scheme(s1mono) addplot((kdensity t if t <= 10 & year<2015 & top3==1, bwidth(0.1) lpattern(vshortdash) lcolor(black) ))

. histogram t if keep_obs==1 & t <= 10 & year<2015 & top3==1
>  , title("2005-2011") saving("temp1", replace) width(0.1) st
> art(0) fcolor(gs10) lcolor(gs10) kdensity kdenopts(width(0.1)) xtitle(z-stati
> stic, size(large)) ytitle(Density, size(large)) xline(1.65 1.96 2.58, lwidth(
> thin)) xlabel(0(1)10, labels labsize(large)) ylabel(, labels labsize(large)) 
> legend(off) scheme(s1mono) addplot((kdensity t if t <= 10 & year<2015 & top3=
> =1, bwidth(0.1) lpattern(vshortdash) lcolor(black) ))
(bin=100, start=0, width=.1)
file temp1.gph saved

. 
66
graph export figure_5a.pdf, replace
graph export figure_5a.pdf, replace

. graph export "figure_5a.pdf", replace
file figure_5a.pdf saved as PDF format

. 
67
histogram t if keep_obs==1 &  t <= 10 & year>=2015 & top3==1 , title("2015 & 2018") saving(temp2, replace) width(0.1) start(0) fcolor(gs10) lcolor(gs10) kdensity kdenopts(width(0.1)) xtitle(z-statistic, size(large)) ytitle(Density, size(large)) xline(1.65 1.96 2.58, lwidth(thin)) xlabel(0(1)10, labels labsize(large)) ylabel(, labels labsize(large)) legend(off) scheme(s1mono) addplot((kdensity t if t <= 10 & year>=2015 & top3==1, bwidth(0.1) lpattern(vshortdash) lcolor(black) ))
histogram t if keep_obs==1 &  t <= 10 & year>=2015 & top3==1 , title("2015 & 2018") saving(temp2, replace) width(0.1) start(0) fcolor(gs10) lcolor(gs10) kdensity kdenopts(width(0.1)) xtitle(z-statistic, size(large)) ytitle(Density, size(large)) xline(1.65 1.96 2.58, lwidth(thin)) xlabel(0(1)10, labels labsize(large)) ylabel(, labels labsize(large)) legend(off) scheme(s1mono) addplot((kdensity t if t <= 10 & year>=2015 & top3==1, bwidth(0.1) lpattern(vshortdash) lcolor(black) ))

. histogram t if keep_obs==1 &  t <= 10 & year>=2015 & top3=
> =1 , title("2015 & 2018") saving("temp2", replace) width(0.1
> ) start(0) fcolor(gs10) lcolor(gs10) kdensity kdenopts(width(0.1)) xtitle(z-s
> tatistic, size(large)) ytitle(Density, size(large)) xline(1.65 1.96 2.58, lwi
> dth(thin)) xlabel(0(1)10, labels labsize(large)) ylabel(, labels labsize(larg
> e)) legend(off) scheme(s1mono) addplot((kdensity t if t <= 10 & year>=2015 & 
> top3==1, bwidth(0.1) lpattern(vshortdash) lcolor(black) ))
(bin=100, start=0, width=.1)
file temp2.gph saved

. 
68
graph export figure_5b.pdf, replace
graph export figure_5b.pdf, replace

. graph export "figure_5b.pdf", replace
file figure_5b.pdf saved as PDF format

. 
69
70
* read in the data
71
cd "$dir_data" 
cd "/home/rstudio/repbox/projects_ejd/aer_112_9_9/mod/Scripts/Data"

. cd "${repbox_path}/Data"
/home/rstudio/repbox/projects_ejd/aer_112_9_9/mod/Data

. 
72
capture use "MM_new.dta", clear 

. capture use "MM_new.dta", clear

. 
73
74
* determine folder to store results
75
cd "$dir_results" 
cd "/home/rstudio/repbox/projects_ejd/aer_112_9_9/mod/Scripts/Results"

. cd "${repbox_path}/Results"
/home/rstudio/repbox/projects_ejd/aer_112_9_9/mod/Results

. 
76
77
histogram t if keep_obs==1 & t <= 10 & year==2015 , title("2015") saving(temp3, replace) width(0.1) start(0) fcolor(gs10) lcolor(gs10) kdensity kdenopts(width(0.1)) xtitle(z-statistic, size(large)) ytitle(Density, size(large)) xline(1.65 1.96 2.58, lwidth(thin)) xlabel(0(1)10, labels labsize(large)) ylabel(, labels labsize(large)) legend(off) scheme(s1mono) addplot((kdensity t if t <= 10 & year==2015 , bwidth(0.1) lpattern(vshortdash) lcolor(black) ))
histogram t if keep_obs==1 & t <= 10 & year==2015 , title("2015") saving(temp3, replace) width(0.1) start(0) fcolor(gs10) lcolor(gs10) kdensity kdenopts(width(0.1)) xtitle(z-statistic, size(large)) ytitle(Density, size(large)) xline(1.65 1.96 2.58, lwidth(thin)) xlabel(0(1)10, labels labsize(large)) ylabel(, labels labsize(large)) legend(off) scheme(s1mono) addplot((kdensity t if t <= 10 & year==2015 , bwidth(0.1) lpattern(vshortdash) lcolor(black) ))

. histogram t if keep_obs==1 & t <= 10 & year==2015 , title(
> "2015") saving("temp3", replace) width(0.1) start(0) fcolor(
> gs10) lcolor(gs10) kdensity kdenopts(width(0.1)) xtitle(z-statistic, size(lar
> ge)) ytitle(Density, size(large)) xline(1.65 1.96 2.58, lwidth(thin)) xlabel(
> 0(1)10, labels labsize(large)) ylabel(, labels labsize(large)) legend(off) sc
> heme(s1mono) addplot((kdensity t if t <= 10 & year==2015 , bwidth(0.1) lpatte
> rn(vshortdash) lcolor(black) ))
(bin=100, start=0, width=.1)
file temp3.gph saved

. 
78
graph export figure_5c.pdf, replace
graph export figure_5c.pdf, replace

. graph export "figure_5c.pdf", replace
file figure_5c.pdf saved as PDF format

. 
79
histogram t if keep_obs==1 & t <= 10 & year==2018 , title("2018") saving(temp4, replace) width(0.1) start(0) fcolor(gs10) lcolor(gs10) kdensity kdenopts(width(0.1)) xtitle(z-statistic, size(large)) ytitle(Density, size(large)) xline(1.65 1.96 2.58, lwidth(thin)) xlabel(0(1)10, labels labsize(large)) ylabel(, labels labsize(large)) legend(off) scheme(s1mono) addplot((kdensity t if t <= 10 & year==2018 , bwidth(0.1) lpattern(vshortdash) lcolor(black) ))
histogram t if keep_obs==1 & t <= 10 & year==2018 , title("2018") saving(temp4, replace) width(0.1) start(0) fcolor(gs10) lcolor(gs10) kdensity kdenopts(width(0.1)) xtitle(z-statistic, size(large)) ytitle(Density, size(large)) xline(1.65 1.96 2.58, lwidth(thin)) xlabel(0(1)10, labels labsize(large)) ylabel(, labels labsize(large)) legend(off) scheme(s1mono) addplot((kdensity t if t <= 10 & year==2018 , bwidth(0.1) lpattern(vshortdash) lcolor(black) ))

. histogram t if keep_obs==1 & t <= 10 & year==2018 , title(
> "2018") saving("temp4", replace) width(0.1) start(0) fcolor(
> gs10) lcolor(gs10) kdensity kdenopts(width(0.1)) xtitle(z-statistic, size(lar
> ge)) ytitle(Density, size(large)) xline(1.65 1.96 2.58, lwidth(thin)) xlabel(
> 0(1)10, labels labsize(large)) ylabel(, labels labsize(large)) legend(off) sc
> heme(s1mono) addplot((kdensity t if t <= 10 & year==2018 , bwidth(0.1) lpatte
> rn(vshortdash) lcolor(black) ))
(bin=99, start=0, width=.1)
(file temp4.gph not found)
file temp4.gph saved

. 
80
graph export figure_5d.pdf, replace
graph export figure_5d.pdf, replace

. graph export "figure_5d.pdf", replace
file figure_5d.pdf saved as PDF format

. 
81
82
83
*** Figure A1 in our comment
84
* drop obs with small significand
85
keep if keep_obs==1

. keep if keep_obs==1
(8,233 observations deleted)

. 
86
capture destring fstat, replace force

. capture destring fstat, replace force

. 
87
88
histogram fstat if fstat <= 50 , title() width(2) start(0) fcolor(gs10) lcolor(gs10) kdensity kdenopts() xtitle(F-statistic, size(large)) ytitle(Density, size(large)) xline(10, lwidth(thin)) xlabel(0 10 20 30 40 50, labels labsize(large)) ylabel(, labels labsize(large)) legend(off) scheme(s1mono)
histogram fstat if fstat <= 50 , title() width(2) start(0) fcolor(gs10) lcolor(gs10) kdensity kdenopts() xtitle(F-statistic, size(large)) ytitle(Density, size(large)) xline(10, lwidth(thin)) xlabel(0 10 20 30 40 50, labels labsize(large)) ylabel(, labels labsize(large)) legend(off) scheme(s1mono)

. histogram fstat if fstat <= 50 , title() width(2) start(0)
>  fcolor(gs10) lcolor(gs10) kdensity kdenopts() xtitle(F-statistic, size(large
> )) ytitle(Density, size(large)) xline(10, lwidth(thin)) xlabel(0 10 20 30 40 
> 50, labels labsize(large)) ylabel(, labels labsize(large)) legend(off) scheme
> (s1mono)
(bin=25, start=0, width=2)

. 
89
graph export figure_A1a.pdf, replace 
graph export figure_A1a.pdf, replace

. graph export "figure_A1a.pdf", replace
file figure_A1a.pdf saved as PDF format

. 
90
91
92
capture destring fstat, replace force

. capture destring fstat, replace force

. 
93
94
histogram t if t <= 10 & method=="IV" & fstat< 30 , title("F less than 30") saving(temp1, replace) width(0.1) start(0) fcolor(gs10) lcolor(gs10) kdensity kdenopts(width(0.1)) ytitle(Density, size(large)) xtitle(z-statistic, size(large)) xline(1.65 1.96 2.58, lwidth(thin)) xlabel(0 1 1.65 "*" 1.96 "**" 2.58 "***" 3 4 5 6 7 8 9 10, labels labsize(large)) ylabel(, labels labsize(large)) legend(off) scheme(s1mono)
histogram t if t <= 10 & method=="IV" & fstat< 30 , title("F less than 30") saving(temp1, replace) width(0.1) start(0) fcolor(gs10) lcolor(gs10) kdensity kdenopts(width(0.1)) ytitle(Density, size(large)) xtitle(z-statistic, size(large)) xline(1.65 1.96 2.58, lwidth(thin)) xlabel(0 1 1.65 "*" 1.96 "**" 2.58 "***" 3 4 5 6 7 8 9 10, labels labsize(large)) ylabel(, labels labsize(large)) legend(off) scheme(s1mono)

. histogram t if t <= 10 & method=="IV" & fstat< 30 , title(
> "F less than 30") saving("temp1", replace) width(0.1) start(
> 0) fcolor(gs10) lcolor(gs10) kdensity kdenopts(width(0.1)) ytitle(Density, si
> ze(large)) xtitle(z-statistic, size(large)) xline(1.65 1.96 2.58, lwidth(thin
> )) xlabel(0 1 1.65 "*" 1.96 "**" 2.58 "***" 3 4 5 6 7 8 9 10, labels labsize(
> large)) ylabel(, labels labsize(large)) legend(off) scheme(s1mono)
(bin=90, start=0, width=.1)
file temp1.gph saved

. 
95
graph export figure_A1b.pdf, replace 
graph export figure_A1b.pdf, replace

. graph export "figure_A1b.pdf", replace
file figure_A1b.pdf saved as PDF format

. 
96
97
histogram t if t <= 10 & method=="IV" & fstat>= 30 , title("F greater than or equal to 30") saving(temp2, replace) width(0.1) start(0) fcolor(gs10) lcolor(gs10) kdensity kdenopts(width(0.1)) ytitle(Density, size(large)) xtitle(z-statistic, size(large)) xline(1.65 1.96 2.58, lwidth(thin)) xlabel(0 1 1.65 "*" 1.96 "**" 2.58 "***" 3 4 5 6 7 8 9 10, labels labsize(large)) ylabel(, labels labsize(large)) legend(off) scheme(s1mono)
histogram t if t <= 10 & method=="IV" & fstat>= 30 , title("F greater than or equal to 30") saving(temp2, replace) width(0.1) start(0) fcolor(gs10) lcolor(gs10) kdensity kdenopts(width(0.1)) ytitle(Density, size(large)) xtitle(z-statistic, size(large)) xline(1.65 1.96 2.58, lwidth(thin)) xlabel(0 1 1.65 "*" 1.96 "**" 2.58 "***" 3 4 5 6 7 8 9 10, labels labsize(large)) ylabel(, labels labsize(large)) legend(off) scheme(s1mono)

. histogram t if t <= 10 & method=="IV" & fstat>= 30 , title
> ("F greater than or equal to 30") saving("temp2", replace) w
> idth(0.1) start(0) fcolor(gs10) lcolor(gs10) kdensity kdenopts(width(0.1)) yt
> itle(Density, size(large)) xtitle(z-statistic, size(large)) xline(1.65 1.96 2
> .58, lwidth(thin)) xlabel(0 1 1.65 "*" 1.96 "**" 2.58 "***" 3 4 5 6 7 8 9 10,
>  labels labsize(large)) ylabel(, labels labsize(large)) legend(off) scheme(s1
> mono)
(bin=100, start=0, width=.1)
file temp2.gph saved

. 
98
graph export figure_A1c.pdf, replace 
graph export figure_A1c.pdf, replace

. graph export "figure_A1c.pdf", replace
file figure_A1c.pdf saved as PDF format

. 
99
100
101
*** Figure A2 in our comment
102
103
* read in the data
104
cd "$dir_data" 
cd "/home/rstudio/repbox/projects_ejd/aer_112_9_9/mod/Scripts/Data"

. cd "${repbox_path}/Data"
/home/rstudio/repbox/projects_ejd/aer_112_9_9/mod/Data

. 
105
capture use "MM Data with WP ready.dta", clear 

. capture use "MM Data with WP ready.dta", clear

. 
106
107
* determine folder to store results
108
cd "$dir_results" 
cd "/home/rstudio/repbox/projects_ejd/aer_112_9_9/mod/Scripts/Results"

. cd "${repbox_path}/Results"
/home/rstudio/repbox/projects_ejd/aer_112_9_9/mod/Results

. 
109
110
* drop obs with small significand
111
keep if keep_obs==1

. keep if keep_obs==1
(5,626 observations deleted)

. 
112
113
histogram t if t <= 10 & WP==0, title("Published") saving(temp1, replace) width(0.1) start(0) fcolor(gs10) lcolor(gs10) kdensity kdenopts(width(0.1)) ytitle(Density, size(large)) xtitle(z-statistic, size(large)) xline(1.65 1.96 2.58, lwidth(thin)) xlabel(0 1 1.65 "*" 1.96 "**" 2.58 "***" 3 4 5 6 7 8 9 10, labels labsize(large)) ylabel(, labels labsize(large)) legend(off) scheme(s1mono)
histogram t if t <= 10 & WP==0, title("Published") saving(temp1, replace) width(0.1) start(0) fcolor(gs10) lcolor(gs10) kdensity kdenopts(width(0.1)) ytitle(Density, size(large)) xtitle(z-statistic, size(large)) xline(1.65 1.96 2.58, lwidth(thin)) xlabel(0 1 1.65 "*" 1.96 "**" 2.58 "***" 3 4 5 6 7 8 9 10, labels labsize(large)) ylabel(, labels labsize(large)) legend(off) scheme(s1mono)

. histogram t if t <= 10 & WP==0, title("Published") saving(
> "temp1", replace) width(0.1) start(0) fcolor(gs10) lcolor(gs
> 10) kdensity kdenopts(width(0.1)) ytitle(Density, size(large)) xtitle(z-stati
> stic, size(large)) xline(1.65 1.96 2.58, lwidth(thin)) xlabel(0 1 1.65 "*" 1.
> 96 "**" 2.58 "***" 3 4 5 6 7 8 9 10, labels labsize(large)) ylabel(, labels l
> absize(large)) legend(off) scheme(s1mono)
(bin=100, start=0, width=.1)
file temp1.gph saved

. 
114
graph export figure_A2a.pdf, replace 
graph export figure_A2a.pdf, replace

. graph export "figure_A2a.pdf", replace
file figure_A2a.pdf saved as PDF format

. 
115
histogram t if t <= 10 & WP==1, title("Working Paper") saving(temp2, replace) width(0.1) start(0) fcolor(gs10) lcolor(gs10) kdensity kdenopts(width(0.1)) ytitle(Density, size(large)) xtitle(z-statistic, size(large)) xline(1.65 1.96 2.58, lwidth(thin)) xlabel(0 1 1.65 "*" 1.96 "**" 2.58 "***" 3 4 5 6 7 8 9 10, labels labsize(large)) ylabel(, labels labsize(large)) legend(off) scheme(s1mono)
histogram t if t <= 10 & WP==1, title("Working Paper") saving(temp2, replace) width(0.1) start(0) fcolor(gs10) lcolor(gs10) kdensity kdenopts(width(0.1)) ytitle(Density, size(large)) xtitle(z-statistic, size(large)) xline(1.65 1.96 2.58, lwidth(thin)) xlabel(0 1 1.65 "*" 1.96 "**" 2.58 "***" 3 4 5 6 7 8 9 10, labels labsize(large)) ylabel(, labels labsize(large)) legend(off) scheme(s1mono)

. histogram t if t <= 10 & WP==1, title("Working Paper") sav
> ing("temp2", replace) width(0.1) start(0) fcolor(gs10) lcolo
> r(gs10) kdensity kdenopts(width(0.1)) ytitle(Density, size(large)) xtitle(z-s
> tatistic, size(large)) xline(1.65 1.96 2.58, lwidth(thin)) xlabel(0 1 1.65 "*
> " 1.96 "**" 2.58 "***" 3 4 5 6 7 8 9 10, labels labsize(large)) ylabel(, labe
> ls labsize(large)) legend(off) scheme(s1mono)
(bin=99, start=0, width=.1)
file temp2.gph saved

. 
116
graph export figure_A2b.pdf, replace 
graph export figure_A2b.pdf, replace

. graph export "figure_A2b.pdf", replace
file figure_A2b.pdf saved as PDF format

. 
117
1
* this sctipt is borrowed from Brodeur et al. (2020) and executes some variable manipulation, labels variables and drops variables not needed any more
2
3
clear all

. clear all

. 
4
set more off

. set more off

. 
5
6
* specify directories where data are located and where results should be stored
7
global dir_main : pwd

. global dir_main : pwd

. 
8
global dir_data "$dir_main/Data"
global dir_data "/home/rstudio/repbox/projects_ejd/aer_112_9_9/mod/Scripts/Data"

. global dir_data "$dir_main/Data"

. 
9
global dir_results "$dir_main/Results"
global dir_results "/home/rstudio/repbox/projects_ejd/aer_112_9_9/mod/Scripts/Results"

. global dir_results "$dir_main/Results"

. 
10
11
12
cd "$dir_data"
cd "/home/rstudio/repbox/projects_ejd/aer_112_9_9/mod/Scripts/Data"

. cd "${repbox_path}/Data"
/home/rstudio/repbox/projects_ejd/aer_112_9_9/mod/Data

. 
13
* read in the data
14
use "MM Data.dta" , clear

. use "MM Data.dta" , clear

. 
15
16
* journals
17
rename journal journal_name

. rename journal journal_name

. 
18
gen journal=.

. gen journal=.
(21,740 missing values generated)

. 
19
replace journal=1 if journal_name=="Quarterly Journal of Economics"
replace journal=1 if journal_name=="Quarterly Journal of Economics"

. replace journal=1 if journal_name=="Quarterly Journal of E
> conomics"
(840 real changes made)

. 
20
replace journal=3 if journal_name=="Journal of Political Economy"
replace journal=3 if journal_name=="Journal of Political Economy"

. replace journal=3 if journal_name=="Journal of Political E
> conomy"
(761 real changes made)

. 
21
replace journal=4 if journal_name=="Econometrica"

. replace journal=4 if journal_name=="Econometrica"
(307 real changes made)

. 
22
replace journal=5 if journal_name=="Journal of Finance" // old one, has no effect

. replace journal=5 if journal_name=="Journal of Finance" 
(1,135 real changes made)

. 
23
replace journal=5 if journal_name=="Journal of Finance" 

. replace journal=5 if journal_name=="Journal of Finance"
(0 real changes made)

. 
24
replace journal=6 if journal_name=="Review of Economic Studies" // old one, has no effect
replace journal=6 if journal_name=="Review of Economic Studies"

. replace journal=6 if journal_name=="Review of Economic Stu
> dies" 
(306 real changes made)

. 
25
replace journal=6 if journal_name=="Review of Economic Studies" 
replace journal=6 if journal_name=="Review of Economic Studies"

. replace journal=6 if journal_name=="Review of Economic Stu
> dies"
(0 real changes made)

. 
26
replace journal=7 if journal_name=="AEJ: Macroeconomics" // old

. replace journal=7 if journal_name=="AEJ: Macroeconomics" 
(54 real changes made)

. 
27
replace journal=7 if journal_name=="American Economic Journal: Macroeconomics"
replace journal=7 if journal_name=="American Economic Journal: Macroeconomics"

. replace journal=7 if journal_name=="American Economic Jour
> nal: Macroeconomics"
(0 real changes made)

. 
28
replace journal=8 if journal_name=="Journal of Economic Growth"
replace journal=8 if journal_name=="Journal of Economic Growth"

. replace journal=8 if journal_name=="Journal of Economic Gr
> owth"
(100 real changes made)

. 
29
replace journal=9 if journal_name=="Review of Economics and Statistics"
replace journal=9 if journal_name=="Review of Economics and Statistics"

. replace journal=9 if journal_name=="Review of Economics an
> d Statistics"
(1,484 real changes made)

. 
30
replace journal=11 if journal_name=="American Economic Review"
replace journal=11 if journal_name=="American Economic Review"

. replace journal=11 if journal_name=="American Economic Rev
> iew"
(1,740 real changes made)

. 
31
replace journal=12 if journal_name=="Economic Policy"

. replace journal=12 if journal_name=="Economic Policy"
(80 real changes made)

. 
32
replace journal=15 if journal_name=="AEJ: Applied Economics" // OLD
replace journal=15 if journal_name=="AEJ: Applied Economics"

. replace journal=15 if journal_name=="AEJ: Applied Economic
> s" 
(2,242 real changes made)

. 
33
replace journal=15 if journal_name=="American Economic Journal: Applied Economics"
replace journal=15 if journal_name=="American Economic Journal: Applied Economics"

. replace journal=15 if journal_name=="American Economic Jou
> rnal: Applied Economics"
(0 real changes made)

. 
34
replace journal=16 if journal_name=="Journal of the European Economic Association"
replace journal=16 if journal_name=="Journal of the European Economic Association"

. replace journal=16 if journal_name=="Journal of the Europe
> an Economic Association"
(491 real changes made)

. 
35
replace journal=17 if journal_name=="Review of Financial Studies"
replace journal=17 if journal_name=="Review of Financial Studies"

. replace journal=17 if journal_name=="Review of Financial S
> tudies"
(963 real changes made)

. 
36
replace journal=18 if journal_name=="Journal of International Economics"
replace journal=18 if journal_name=="Journal of International Economics"

. replace journal=18 if journal_name=="Journal of Internatio
> nal Economics"
(510 real changes made)

. 
37
replace journal=19 if journal_name=="Economic Journal" // OLD

. replace journal=19 if journal_name=="Economic Journal" 
(891 real changes made)

. 
38
replace journal=19 if journal_name=="Economic Journal"

. replace journal=19 if journal_name=="Economic Journal"
(0 real changes made)

. 
39
replace journal=20 if journal_name=="Review of Financial Economics" // OLD
replace journal=20 if journal_name=="Review of Financial Economics"

. replace journal=20 if journal_name=="Review of Financial E
> conomics" 
(0 real changes made)

. 
40
replace journal=20 if journal_name=="Journal of Financial Economics"
replace journal=20 if journal_name=="Journal of Financial Economics"

. replace journal=20 if journal_name=="Journal of Financial 
> Economics"
(635 real changes made)

. 
41
replace journal=21 if journal_name=="Experimental Economics"
replace journal=21 if journal_name=="Experimental Economics"

. replace journal=21 if journal_name=="Experimental Economic
> s"
(79 real changes made)

. 
42
replace journal=22 if journal_name=="Journal of Development Economics"
replace journal=22 if journal_name=="Journal of Development Economics"

. replace journal=22 if journal_name=="Journal of Developmen
> t Economics"
(2,818 real changes made)

. 
43
replace journal=23 if journal_name=="Journal of Labor Economics"
replace journal=23 if journal_name=="Journal of Labor Economics"

. replace journal=23 if journal_name=="Journal of Labor Econ
> omics"
(653 real changes made)

. 
44
replace journal=24 if journal_name=="Journal of Financial Intermediation"
replace journal=24 if journal_name=="Journal of Financial Intermediation"

. replace journal=24 if journal_name=="Journal of Financial 
> Intermediation"
(285 real changes made)

. 
45
replace journal=25 if journal_name=="Journal of Applied Econometrics"
replace journal=25 if journal_name=="Journal of Applied Econometrics"

. replace journal=25 if journal_name=="Journal of Applied Ec
> onometrics"
(86 real changes made)

. 
46
replace journal=26 if journal_name=="Journal of Human Resources"
replace journal=26 if journal_name=="Journal of Human Resources"

. replace journal=26 if journal_name=="Journal of Human Reso
> urces"
(752 real changes made)

. 
47
replace journal=27 if journal_name=="AEJ: Economic Policy" // OLD

. replace journal=27 if journal_name=="AEJ: Economic Policy"
>  
(1,263 real changes made)

. 
48
replace journal=27 if journal_name=="American Economic Journal: Economic Policy"
replace journal=27 if journal_name=="American Economic Journal: Economic Policy"

. replace journal=27 if journal_name=="American Economic Jou
> rnal: Economic Policy"
(0 real changes made)

. 
49
replace journal=31 if journal_name=="Journal of Urban Economics"
replace journal=31 if journal_name=="Journal of Urban Economics"

. replace journal=31 if journal_name=="Journal of Urban Econ
> omics"
(660 real changes made)

. 
50
replace journal=32 if journal_name=="Journal of Public Economics"
replace journal=32 if journal_name=="Journal of Public Economics"

. replace journal=32 if journal_name=="Journal of Public Eco
> nomics"
(2,605 real changes made)

. 
51
52
gen top5=0 if journal!=.

. gen top5=0 if journal!=.

. 
53
replace top5=1 if journal==1

. replace top5=1 if journal==1
(840 real changes made)

. 
54
replace top5=1 if journal==3

. replace top5=1 if journal==3
(761 real changes made)

. 
55
replace top5=1 if journal==4

. replace top5=1 if journal==4
(307 real changes made)

. 
56
replace top5=1 if journal==6

. replace top5=1 if journal==6
(306 real changes made)

. 
57
replace top5=1 if journal==11

. replace top5=1 if journal==11
(1,740 real changes made)

. 
58
59
gen FINANCE=0 if journal!=.

. gen FINANCE=0 if journal!=.

. 
60
replace FINANCE=1 if journal==5

. replace FINANCE=1 if journal==5
(1,135 real changes made)

. 
61
replace FINANCE=1 if journal==17

. replace FINANCE=1 if journal==17
(963 real changes made)

. 
62
replace FINANCE=1 if journal==20

. replace FINANCE=1 if journal==20
(635 real changes made)

. 
63
replace FINANCE=1 if journal==24

. replace FINANCE=1 if journal==24
(285 real changes made)

. 
64
65
gen MACRO_GROWTH=0 if journal!=.

. gen MACRO_GROWTH=0 if journal!=.

. 
66
replace MACRO_GROWTH=1 if journal==7

. replace MACRO_GROWTH=1 if journal==7
(54 real changes made)

. 
67
replace MACRO_GROWTH=1 if journal==8

. replace MACRO_GROWTH=1 if journal==8
(100 real changes made)

. 
68
69
gen GEN_INT=0 if journal!=.

. gen GEN_INT=0 if journal!=.

. 
70
replace GEN_INT=1 if journal==9

. replace GEN_INT=1 if journal==9
(1,484 real changes made)

. 
71
replace GEN_INT=1 if journal==12

. replace GEN_INT=1 if journal==12
(80 real changes made)

. 
72
replace GEN_INT=1 if journal==14

. replace GEN_INT=1 if journal==14
(0 real changes made)

. 
73
replace GEN_INT=1 if journal==15

. replace GEN_INT=1 if journal==15
(2,242 real changes made)

. 
74
replace GEN_INT=1 if journal==16

. replace GEN_INT=1 if journal==16
(491 real changes made)

. 
75
replace GEN_INT=1 if journal==19

. replace GEN_INT=1 if journal==19
(891 real changes made)

. 
76
replace GEN_INT=1 if journal==25

. replace GEN_INT=1 if journal==25
(86 real changes made)

. 
77
replace GEN_INT=1 if journal==26

. replace GEN_INT=1 if journal==26
(752 real changes made)

. 
78
79
gen EXP=0 if journal!=.

. gen EXP=0 if journal!=.

. 
80
replace EXP=1 if journal==21

. replace EXP=1 if journal==21
(79 real changes made)

. 
81
82
gen DEV=0 if journal!=.

. gen DEV=0 if journal!=.

. 
83
replace DEV=1 if journal==22

. replace DEV=1 if journal==22
(2,818 real changes made)

. 
84
85
gen LABOR=0 if journal!=.

. gen LABOR=0 if journal!=.

. 
86
replace LABOR=1 if journal==23

. replace LABOR=1 if journal==23
(653 real changes made)

. 
87
88
gen PUB=0 if journal!=.

. gen PUB=0 if journal!=.

. 
89
replace PUB=1 if journal==27

. replace PUB=1 if journal==27
(1,263 real changes made)

. 
90
replace PUB=1 if journal==32

. replace PUB=1 if journal==32
(2,605 real changes made)

. 
91
92
gen URB=0 if journal!=.

. gen URB=0 if journal!=.

. 
93
replace URB=1 if journal==31

. replace URB=1 if journal==31
(660 real changes made)

. 
94
95
* how reported
96
gen p_value=1 if report=="p"

. gen p_value=1 if report=="p"
(20,726 missing values generated)

. 
97
gen z_stat=1 if report=="s"

. gen z_stat=1 if report=="s"
(2,009 missing values generated)

. 
98
gen t_stat=1 if report=="t"

. gen t_stat=1 if report=="t"
(20,768 missing values generated)

. 
99
100
replace p_value=0 if report=="s"

. replace p_value=0 if report=="s"
(19,731 real changes made)

. 
101
replace p_value=0 if report=="t"

. replace p_value=0 if report=="t"
(972 real changes made)

. 
102
replace z_stat=0 if report=="p"

. replace z_stat=0 if report=="p"
(1,014 real changes made)

. 
103
replace z_stat=0 if report=="t"

. replace z_stat=0 if report=="t"
(972 real changes made)

. 
104
replace t_stat=0 if report=="p"

. replace t_stat=0 if report=="p"
(1,014 real changes made)

. 
105
replace t_stat=0 if report=="s"

. replace t_stat=0 if report=="s"
(19,731 real changes made)

. 
106
107
encode report, gen(ireport)

. encode report, gen(ireport)

. 
108
109
* unique identifiers
110
capture egen unique_j = group(journal)

. capture egen unique_j = group(journal)

. 
111
capture egen unique_ja = group(journal article)

. capture egen unique_ja = group(journal article)

. 
112
capture egen unique_jat = group(journal article table)

. capture egen unique_jat = group(journal article table)

. 
113
114
* weights
115
gen journal_cluster=journal*10000

. gen journal_cluster=journal*10000

. 
116
117
egen journal_article_cluster=concat(journal_cluster article)
egen journal_article_cluster=concat(journal_cluster article)

. egen journal_article_cluster=concat(journal_cluster articl
> e)

. 
118
destring journal_article_cluster, replace

. destring journal_article_cluster, replace
journal_article_cluster: all characters numeric; replaced as long

. 
119
120
egen journal_article=concat(journal article)

. egen journal_article=concat(journal article)

. 
121
destring journal_article, replace

. destring journal_article, replace
journal_article: all characters numeric; replaced as int

. 
122
123
egen article_table=concat(journal_article_cluster table)

. egen article_table=concat(journal_article_cluster table)

. 
124
destring article_table, replace

. destring article_table, replace
article_table: contains nonnumeric characters; no replace

. 
125
126
bysort journal_article_cluster: gen test_count = _N

. bysort journal_article_cluster: gen test_count = _N

. 
127
gen aw_d=1/test_count

. gen aw_d=1/test_count

. 
128
gen aw=aw_d*10000

. gen aw=aw_d*10000

. 
129
130
bysort article_table: gen test_count_1 = _N

. bysort article_table: gen test_count_1 = _N

. 
131
gen aw_tab_d=1/test_count_1

. gen aw_tab_d=1/test_count_1

. 
132
gen aw_tab=aw_tab_d*10000

. gen aw_tab=aw_tab_d*10000

. 
133
134
135
136
* method identifiers
137
gen RCT=.

. gen RCT=.
(21,740 missing values generated)

. 
138
replace RCT=1 if method=="RCT"

. replace RCT=1 if method=="RCT"
(7,569 real changes made)

. 
139
replace RCT=0 if method!="RCT"

. replace RCT=0 if method!="RCT"
(14,171 real changes made)

. 
140
141
gen DID=.

. gen DID=.
(21,740 missing values generated)

. 
142
replace DID=1 if method=="DID"

. replace DID=1 if method=="DID"
(5,853 real changes made)

. 
143
replace DID=0 if method!="DID"

. replace DID=0 if method!="DID"
(15,887 real changes made)

. 
144
145
gen IV=.

. gen IV=.
(21,740 missing values generated)

. 
146
replace IV=1 if method=="IV"

. replace IV=1 if method=="IV"
(5,170 real changes made)

. 
147
replace IV=0 if method!="IV"

. replace IV=0 if method!="IV"
(16,570 real changes made)

. 
148
149
gen RDD=.

. gen RDD=.
(21,740 missing values generated)

. 
150
replace RDD=1 if method=="RDD"

. replace RDD=1 if method=="RDD"
(3,148 real changes made)

. 
151
replace RDD=0 if method!="RDD"

. replace RDD=0 if method!="RDD"
(18,592 real changes made)

. 
152
153
* statistical threshold identifiers
154
gen sign_1pct=.

. gen sign_1pct=.
(21,740 missing values generated)

. 
155
replace sign_1pct=1 if t!=. & t>2.58

. replace sign_1pct=1 if t!=. & t>2.58
(7,362 real changes made)

. 
156
replace sign_1pct=0 if t!=. & t<=2.58

. replace sign_1pct=0 if t!=. & t<=2.58
(14,378 real changes made)

. 
157
158
gen sign_5pct=.

. gen sign_5pct=.
(21,740 missing values generated)

. 
159
replace sign_5pct=1 if t!=. & t>1.96

. replace sign_5pct=1 if t!=. & t>1.96
(10,559 real changes made)

. 
160
replace sign_5pct=0 if t!=. & t<=1.96

. replace sign_5pct=0 if t!=. & t<=1.96
(11,181 real changes made)

. 
161
162
gen sign_10pct=.

. gen sign_10pct=.
(21,740 missing values generated)

. 
163
replace sign_10pct=1 if t!=. & t>1.65

. replace sign_10pct=1 if t!=. & t>1.65
(12,252 real changes made)

. 
164
replace sign_10pct=0 if t!=. & t<=1.65

. replace sign_10pct=0 if t!=. & t<=1.65
(9,488 real changes made)

. 
165
166
* num authors
167
168
capture drop num_authors

. capture drop num_authors

. 
169
egen num_authors = rownonmiss(Author*), strok

. egen num_authors = rownonmiss(Author*), strok

. 
170
replace num_authors = 11 if title=="Giving kids a head start: The impact and mechanisms of early commitment of financial aid on poor students in rural China" 
replace num_authors = 11 if title=="Giving kids a head start: The impact and mechanisms of early commitment of financial aid on poor students in rural China"

. replace num_authors = 11 if title=="Giving kids a head sta
> rt: The impact and mechanisms of early commitment of financial aid on poor st
> udents in rural China"
(34 real changes made)

. 
171
172
capture drop authored_solo

. capture drop authored_solo

. 
173
gen authored_solo = 0

. gen authored_solo = 0

. 
174
replace authored_solo = 1 if num_authors==1

. replace authored_solo = 1 if num_authors==1
(4,360 real changes made)

. 
175
176
177
* genders
178
* ssc inst egenmore // may be necessary 
179
180
capture drop authors_gender_string

. capture drop authors_gender_string

. 
181
gen authors_gender_string=""

. gen authors_gender_string=""
(21,740 missing values generated)

. 
182
replace authors_gender_string=Gender1+Gender2+Gender3+Gender4+Gender5+Gender6+Gender7+Gender8+Gender9+Gender10+Gender11
replace authors_gender_string=Gender1+Gender2+Gender3+Gender4+Gender5+Gender6+Gender7+Gender8+Gender9+Gender10+Gender11

. replace authors_gender_string=Gender1+Gender2+Gender3+Gend
> er4+Gender5+Gender6+Gender7+Gender8+Gender9+Gender10+Gender11
variable authors_gender_string was str1 now str11
(21,740 real changes made)

. 
183
184
capture drop num_male_authors

. capture drop num_male_authors

. 
185
egen num_male_authors = nss(authors_gender_string) , find(m)
egen num_male_authors = nss(authors_gender_string) , find(m)

. egen num_male_authors = nss(authors_gender_string) , find(
> m)

. 
186
187
capture drop num_female_authors

. capture drop num_female_authors

. 
188
egen num_female_authors = nss(authors_gender_string) , find(f)
egen num_female_authors = nss(authors_gender_string) , find(f)

. egen num_female_authors = nss(authors_gender_string) , fin
> d(f)

. 
189
190
capture drop share_male_authors

. capture drop share_male_authors

. 
191
gen share_male_authors = num_male_authors / num_authors

. gen share_male_authors = num_male_authors / num_authors

. 
192
193
capture drop share_female_authors

. capture drop share_female_authors

. 
194
gen share_female_authors = num_female_authors / num_authors
gen share_female_authors = num_female_authors / num_authors

. gen share_female_authors = num_female_authors / num_author
> s

. 
195
196
197
198
* experience
199
replace PhDYear1 = "1989" if PhDYear1=="2989"

. replace PhDYear1 = "1989" if PhDYear1=="2989"
(2 real changes made)

. 
200
201
forval i = 1(1)11 {
forval i = 1(1)11 {
202
capture drop PhDYear`i'sieve
capture drop PhDYear1sieve
capture drop PhDYear2sieve
capture drop PhDYear3sieve
capture drop PhDYear4sieve
capture drop PhDYear5sieve
capture drop PhDYear6sieve
capture drop PhDYear7sieve
capture drop PhDYear8sieve
capture drop PhDYear9sieve
capture drop PhDYear10sieve
capture drop PhDYear11sieve
203
egen PhDYear`i'sieve = sieve(PhDYear`i'), keep(numeric)
egen PhDYear1sieve = sieve(PhDYear1), keep(numeric)
(536 missing values generated)
egen PhDYear2sieve = sieve(PhDYear2), keep(numeric)
(4,982 missing values generated)
egen PhDYear3sieve = sieve(PhDYear3), keep(numeric)
(10,559 missing values generated)
egen PhDYear4sieve = sieve(PhDYear4), keep(numeric)
(17,980 missing values generated)
egen PhDYear5sieve = sieve(PhDYear5), keep(numeric)
(20,534 missing values generated)
egen PhDYear6sieve = sieve(PhDYear6), keep(numeric)
(21,693 missing values generated)
egen PhDYear7sieve = sieve(PhDYear7), keep(numeric)
(21,740 missing values generated)
egen PhDYear8sieve = sieve(PhDYear8), keep(numeric)
(21,706 missing values generated)
egen PhDYear9sieve = sieve(PhDYear9), keep(numeric)
(21,706 missing values generated)
egen PhDYear10sieve = sieve(PhDYear10), keep(numeric)
(21,740 missing values generated)
egen PhDYear11sieve = sieve(PhDYear11), keep(numeric)
(21,706 missing values generated)
204
destring PhDYear`i'sieve, replace
destring PhDYear1sieve, replace
PhDYear1sieve: all characters numeric; replaced as int
(536 missing values generated)
destring PhDYear2sieve, replace
PhDYear2sieve: all characters numeric; replaced as int
(4982 missing values generated)
destring PhDYear3sieve, replace
PhDYear3sieve: all characters numeric; replaced as int
(10559 missing values generated)
destring PhDYear4sieve, replace
PhDYear4sieve: all characters numeric; replaced as int
(17980 missing values generated)
destring PhDYear5sieve, replace
PhDYear5sieve: all characters numeric; replaced as int
(20534 missing values generated)
destring PhDYear6sieve, replace
PhDYear6sieve: all characters numeric; replaced as int
(21693 missing values generated)
destring PhDYear7sieve, replace
PhDYear7sieve: all characters numeric; replaced as byte
(21740 missing values generated)
destring PhDYear8sieve, replace
PhDYear8sieve: all characters numeric; replaced as int
(21706 missing values generated)
destring PhDYear9sieve, replace
PhDYear9sieve: all characters numeric; replaced as int
(21706 missing values generated)
destring PhDYear10sieve, replace
PhDYear10sieve: all characters numeric; replaced as byte
(21740 missing values generated)
destring PhDYear11sieve, replace
PhDYear11sieve: all characters numeric; replaced as int
(21706 missing values generated)
205
replace PhDYear`i'sieve = . if PhDYear`i'sieve==0
replace PhDYear1sieve = . if PhDYear1sieve==0
(0 real changes made)
replace PhDYear2sieve = . if PhDYear2sieve==0
(0 real changes made)
replace PhDYear3sieve = . if PhDYear3sieve==0
(0 real changes made)
replace PhDYear4sieve = . if PhDYear4sieve==0
(0 real changes made)
replace PhDYear5sieve = . if PhDYear5sieve==0
(12 real changes made, 12 to missing)
replace PhDYear6sieve = . if PhDYear6sieve==0
(0 real changes made)
replace PhDYear7sieve = . if PhDYear7sieve==0
(0 real changes made)
replace PhDYear8sieve = . if PhDYear8sieve==0
(0 real changes made)
replace PhDYear9sieve = . if PhDYear9sieve==0
(0 real changes made)
replace PhDYear10sieve = . if PhDYear10sieve==0
(0 real changes made)
replace PhDYear11sieve = . if PhDYear11sieve==0
(0 real changes made)
206
replace PhDYear`i'sieve = . if PhDYear`i'sieve==9999
replace PhDYear1sieve = . if PhDYear1sieve==9999
(0 real changes made)
replace PhDYear2sieve = . if PhDYear2sieve==9999
(0 real changes made)
replace PhDYear3sieve = . if PhDYear3sieve==9999
(0 real changes made)
replace PhDYear4sieve = . if PhDYear4sieve==9999
(0 real changes made)
replace PhDYear5sieve = . if PhDYear5sieve==9999
(0 real changes made)
replace PhDYear6sieve = . if PhDYear6sieve==9999
(0 real changes made)
replace PhDYear7sieve = . if PhDYear7sieve==9999
(0 real changes made)
replace PhDYear8sieve = . if PhDYear8sieve==9999
(0 real changes made)
replace PhDYear9sieve = . if PhDYear9sieve==9999
(0 real changes made)
replace PhDYear10sieve = . if PhDYear10sieve==9999
(0 real changes made)
replace PhDYear11sieve = . if PhDYear11sieve==9999
(0 real changes made)
207
capture drop experience`i'
capture drop experience1
capture drop experience2
capture drop experience3
capture drop experience4
capture drop experience5
capture drop experience6
capture drop experience7
capture drop experience8
capture drop experience9
capture drop experience10
capture drop experience11
208
gen experience`i' = year-PhDYear`i'sieve
gen experience1 = year-PhDYear1sieve
(536 missing values generated)
gen experience2 = year-PhDYear2sieve
(4,982 missing values generated)
gen experience3 = year-PhDYear3sieve
(10,559 missing values generated)
gen experience4 = year-PhDYear4sieve
(17,980 missing values generated)
gen experience5 = year-PhDYear5sieve
(20,546 missing values generated)
gen experience6 = year-PhDYear6sieve
(21,693 missing values generated)
gen experience7 = year-PhDYear7sieve
(21,740 missing values generated)
gen experience8 = year-PhDYear8sieve
(21,706 missing values generated)
gen experience9 = year-PhDYear9sieve
(21,706 missing values generated)
gen experience10 = year-PhDYear10sieve
(21,740 missing values generated)
gen experience11 = year-PhDYear11sieve
(21,706 missing values generated)
209
replace experience`i' = . if experience`i'<0
replace experience1 = . if experience1<0
(157 real changes made, 157 to missing)
replace experience2 = . if experience2<0
(330 real changes made, 330 to missing)
replace experience3 = . if experience3<0
(156 real changes made, 156 to missing)
replace experience4 = . if experience4<0
(102 real changes made, 102 to missing)
replace experience5 = . if experience5<0
(0 real changes made)
replace experience6 = . if experience6<0
(0 real changes made)
replace experience7 = . if experience7<0
(0 real changes made)
replace experience8 = . if experience8<0
(0 real changes made)
replace experience9 = . if experience9<0
(0 real changes made)
replace experience10 = . if experience10<0
(0 real changes made)
replace experience11 = . if experience11<0
(0 real changes made)
210
replace experience`i' = . if experience`i' == .
replace experience1 = . if experience1 == .
(0 real changes made)
replace experience2 = . if experience2 == .
(0 real changes made)
replace experience3 = . if experience3 == .
(0 real changes made)
replace experience4 = . if experience4 == .
(0 real changes made)
replace experience5 = . if experience5 == .
(0 real changes made)
replace experience6 = . if experience6 == .
(0 real changes made)
replace experience7 = . if experience7 == .
(0 real changes made)
replace experience8 = . if experience8 == .
(0 real changes made)
replace experience9 = . if experience9 == .
(0 real changes made)
replace experience10 = . if experience10 == .
(0 real changes made)
replace experience11 = . if experience11 == .
(0 real changes made)
211
}
212
213
sum PhDYear*

. sum PhDYear*

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
    PhDYear1 |          0
    PhDYear2 |          0
    PhDYear3 |          0
    PhDYear4 |          0
    PhDYear5 |          0
-------------+---------------------------------------------------------
    PhDYear6 |          0
    PhDYear7 |          0
    PhDYear8 |          0
    PhDYear9 |          0
   PhDYear10 |          0
-------------+---------------------------------------------------------
   PhDYear11 |          0
PhDYear1si~e |     21,204    2005.547    8.602276       1959       2020
PhDYear2si~e |     16,758    2005.605    7.854448       1966       2021
PhDYear3si~e |     11,181    2003.636    9.216486       1972       2020
PhDYear4si~e |      3,760    2003.947    10.33362       1967       2019
-------------+---------------------------------------------------------
PhDYear5si~e |      1,194    2002.482     6.53587       1990       2016
PhDYear6si~e |         47        1987           0       1987       1987
PhDYear7si~e |          0
PhDYear8si~e |         34        2002           0       2002       2002
PhDYear9si~e |         34        2009           0       2009       2009
-------------+---------------------------------------------------------
PhDYear10s~e |          0
PhDYear11s~e |         34        1991           0       1991       1991

. 
214
215
sum experience*

. sum experience*

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
 experience1 |     21,047    10.99587     8.45535          0         59
 experience2 |     16,428    11.14305     7.52349          0         49
 experience3 |     11,025    13.04599     8.78391          0         43
 experience4 |      3,658     13.0205    9.917178          1         48
 experience5 |      1,194    14.75963    6.739682          2         28
-------------+---------------------------------------------------------
 experience6 |         47          28           0         28         28
 experience7 |          0
 experience8 |         34          13           0         13         13
 experience9 |         34           6           0          6          6
experience10 |          0
-------------+---------------------------------------------------------
experience11 |         34          24           0         24         24

. 
216
217
capture drop experience_avg

. capture drop experience_avg

. 
218
capture drop experience_avg_sq

. capture drop experience_avg_sq

. 
219
220
egen experience_avg = rowmean(experience*)

. egen experience_avg = rowmean(experience*)
(71 missing values generated)

. 
221
replace experience_avg = 0 if experience_avg==.

. replace experience_avg = 0 if experience_avg==.
(71 real changes made)

. 
222
gen experience_avg_sq = (experience_avg^2)/100

. gen experience_avg_sq = (experience_avg^2)/100

. 
223
224
sum experience*

. sum experience*

    Variable |        Obs        Mean    Std. dev.       Min        Max
-------------+---------------------------------------------------------
 experience1 |     21,047    10.99587     8.45535          0         59
 experience2 |     16,428    11.14305     7.52349          0         49
 experience3 |     11,025    13.04599     8.78391          0         43
 experience4 |      3,658     13.0205    9.917178          1         48
 experience5 |      1,194    14.75963    6.739682          2         28
-------------+---------------------------------------------------------
 experience6 |         47          28           0         28         28
 experience7 |          0
 experience8 |         34          13           0         13         13
 experience9 |         34           6           0          6          6
experience10 |          0
-------------+---------------------------------------------------------
experience11 |         34          24           0         24         24
experience~g |     21,740    10.73031    5.816504          0         38
experience~q |     21,740    1.489696    1.672511          0      14.44

. 
225
226
227
* editor_present
228
229
forval i = 1(1)11 {
forval i = 1(1)11 {
230
destring Editor`i', replace force
destring Editor1, replace force
Editor1: contains nonnumeric characters; replaced as byte
(303 missing values generated)
destring Editor2, replace force
Editor2: contains nonnumeric characters; replaced as byte
(4468 missing values generated)
destring Editor3, replace force
Editor3: contains nonnumeric characters; replaced as byte
(10451 missing values generated)
destring Editor4, replace force
Editor4: contains nonnumeric characters; replaced as byte
(17890 missing values generated)
destring Editor5, replace force
Editor5: contains nonnumeric characters; replaced as byte
(20482 missing values generated)
destring Editor6, replace force
Editor6: contains nonnumeric characters; replaced as byte
(21437 missing values generated)
destring Editor7, replace force
Editor7: contains nonnumeric characters; replaced as byte
(21740 missing values generated)
destring Editor8, replace force
Editor8: all characters numeric; replaced as byte
(21706 missing values generated)
destring Editor9, replace force
Editor9: all characters numeric; replaced as byte
(21706 missing values generated)
destring Editor10, replace force
Editor10: all characters numeric; replaced as byte
(21706 missing values generated)
destring Editor11, replace force
Editor11: all characters numeric; replaced as byte
(21706 missing values generated)
231
replace Editor`i' = 0 if Editor`i'==. 
replace Editor1 = 0 if Editor1==.
(303 real changes made)
replace Editor2 = 0 if Editor2==.
(4,468 real changes made)
replace Editor3 = 0 if Editor3==.
(10,451 real changes made)
replace Editor4 = 0 if Editor4==.
(17,890 real changes made)
replace Editor5 = 0 if Editor5==.
(20,482 real changes made)
replace Editor6 = 0 if Editor6==.
(21,437 real changes made)
replace Editor7 = 0 if Editor7==.
(21,740 real changes made)
replace Editor8 = 0 if Editor8==.
(21,706 real changes made)
replace Editor9 = 0 if Editor9==.
(21,706 real changes made)
replace Editor10 = 0 if Editor10==.
(21,706 real changes made)
replace Editor11 = 0 if Editor11==.
(21,706 real changes made)
232
}
233
234
capture drop editor_present

. capture drop editor_present

. 
235
egen editor_present = rowmax(Editor*)

. egen editor_present = rowmax(Editor*)

. 
236
237
* share_top_authors
238
239
forval i = 1(1)11 {
forval i = 1(1)11 {
240
capture drop top_author`i'
capture drop top_author1
capture drop top_author2
capture drop top_author3
capture drop top_author4
capture drop top_author5
capture drop top_author6
capture drop top_author7
capture drop top_author8
capture drop top_author9
capture drop top_author10
capture drop top_author11
241
gen top_author`i'=0
gen top_author1=0
gen top_author2=0
gen top_author3=0
gen top_author4=0
gen top_author5=0
gen top_author6=0
gen top_author7=0
gen top_author8=0
gen top_author9=0
gen top_author10=0
gen top_author11=0
242
replace top_author`i'=. if Author`i'==""
replace top_author1=. if Author1==""
(0 real changes made)
replace top_author2=. if Author2==""
(4,394 real changes made, 4,394 to missing)
replace top_author3=. if Author3==""
(10,395 real changes made, 10,395 to missing)
replace top_author4=. if Author4==""
(17,884 real changes made, 17,884 to missing)
replace top_author5=. if Author5==""
(20,482 real changes made, 20,482 to missing)
replace top_author6=. if Author6==""
(21,437 real changes made, 21,437 to missing)
replace top_author7=. if Author7==""
(21,693 real changes made, 21,693 to missing)
replace top_author8=. if Author8==""
(21,740 real changes made, 21,740 to missing)
replace top_author9=. if Author9==""
(21,740 real changes made, 21,740 to missing)
replace top_author10=. if Author10==""
(21,740 real changes made, 21,740 to missing)
replace top_author11=. if Author11==""
(21,740 real changes made, 21,740 to missing)
243
replace top_author`i'=1 if strpos(AF`i', "Harvard")
replace top_author1=1 if strpos(AF1, "Harvard")
(1,233 real changes made)
replace top_author2=1 if strpos(AF2, "Harvard")
(747 real changes made)
replace top_author3=1 if strpos(AF3, "Harvard")
(573 real changes made)
replace top_author4=1 if strpos(AF4, "Harvard")
(116 real changes made)
replace top_author5=1 if strpos(AF5, "Harvard")
(22 real changes made)
replace top_author6=1 if strpos(AF6, "Harvard")
(0 real changes made)
replace top_author7=1 if strpos(AF7, "Harvard")
(0 real changes made)
replace top_author8=1 if strpos(AF8, "Harvard")
(0 real changes made)
replace top_author9=1 if strpos(AF9, "Harvard")
(0 real changes made)
replace top_author10=1 if strpos(AF10, "Harvard")
(0 real changes made)
replace top_author11=1 if strpos(AF11, "Harvard")
(0 real changes made)
244
replace top_author`i'=1 if strpos(AF`i', "Massachusetts Institute of Technology") | strpos(AF`i', "MIT")
replace top_author1=1 if strpos(AF1, "Massachusetts Institute of Technology") | strpos(AF1, "MIT")
(1,092 real changes made)
replace top_author2=1 if strpos(AF2, "Massachusetts Institute of Technology") | strpos(AF2, "MIT")
(226 real changes made)
replace top_author3=1 if strpos(AF3, "Massachusetts Institute of Technology") | strpos(AF3, "MIT")
(640 real changes made)
replace top_author4=1 if strpos(AF4, "Massachusetts Institute of Technology") | strpos(AF4, "MIT")
(135 real changes made)
replace top_author5=1 if strpos(AF5, "Massachusetts Institute of Technology") | strpos(AF5, "MIT")
(0 real changes made)
replace top_author6=1 if strpos(AF6, "Massachusetts Institute of Technology") | strpos(AF6, "MIT")
(0 real changes made)
replace top_author7=1 if strpos(AF7, "Massachusetts Institute of Technology") | strpos(AF7, "MIT")
(0 real changes made)
replace top_author8=1 if strpos(AF8, "Massachusetts Institute of Technology") | strpos(AF8, "MIT")
(0 real changes made)
replace top_author9=1 if strpos(AF9, "Massachusetts Institute of Technology") | strpos(AF9, "MIT")
(0 real changes made)
replace top_author10=1 if strpos(AF10, "Massachusetts Institute of Technology") | strpos(AF10, "MIT")
(0 real changes made)
replace top_author11=1 if strpos(AF11, "Massachusetts Institute of Technology") | strpos(AF11, "MIT")
(0 real changes made)
245
replace top_author`i'=1 if strpos(AF`i', "Berkeley")
replace top_author1=1 if strpos(AF1, "Berkeley")
(290 real changes made)
replace top_author2=1 if strpos(AF2, "Berkeley")
(683 real changes made)
replace top_author3=1 if strpos(AF3, "Berkeley")
(460 real changes made)
replace top_author4=1 if strpos(AF4, "Berkeley")
(6 real changes made)
replace top_author5=1 if strpos(AF5, "Berkeley")
(0 real changes made)
replace top_author6=1 if strpos(AF6, "Berkeley")
(0 real changes made)
replace top_author7=1 if strpos(AF7, "Berkeley")
(0 real changes made)
replace top_author8=1 if strpos(AF8, "Berkeley")
(0 real changes made)
replace top_author9=1 if strpos(AF9, "Berkeley")
(0 real changes made)
replace top_author10=1 if strpos(AF10, "Berkeley")
(0 real changes made)
replace top_author11=1 if strpos(AF11, "Berkeley")
(0 real changes made)
246
replace top_author`i'=1 if strpos(AF`i', "University of Chicago")
replace top_author1=1 if strpos(AF1, "University of Chicago")
(594 real changes made)
replace top_author2=1 if strpos(AF2, "University of Chicago")
(395 real changes made)
replace top_author3=1 if strpos(AF3, "University of Chicago")
(724 real changes made)
replace top_author4=1 if strpos(AF4, "University of Chicago")
(69 real changes made)
replace top_author5=1 if strpos(AF5, "University of Chicago")
(0 real changes made)
replace top_author6=1 if strpos(AF6, "University of Chicago")
(0 real changes made)
replace top_author7=1 if strpos(AF7, "University of Chicago")
(0 real changes made)
replace top_author8=1 if strpos(AF8, "University of Chicago")
(0 real changes made)
replace top_author9=1 if strpos(AF9, "University of Chicago")
(0 real changes made)
replace top_author10=1 if strpos(AF10, "University of Chicago")
(0 real changes made)
replace top_author11=1 if strpos(AF11, "University of Chicago")
(0 real changes made)
247
replace top_author`i'=1 if strpos(AF`i', "Paris School of Economics") | strpos(AF`i', "PSE")
replace top_author1=1 if strpos(AF1, "Paris School of Economics") | strpos(AF1, "PSE")
(174 real changes made)
replace top_author2=1 if strpos(AF2, "Paris School of Economics") | strpos(AF2, "PSE")
(361 real changes made)
replace top_author3=1 if strpos(AF3, "Paris School of Economics") | strpos(AF3, "PSE")
(189 real changes made)
replace top_author4=1 if strpos(AF4, "Paris School of Economics") | strpos(AF4, "PSE")
(0 real changes made)
replace top_author5=1 if strpos(AF5, "Paris School of Economics") | strpos(AF5, "PSE")
(55 real changes made)
replace top_author6=1 if strpos(AF6, "Paris School of Economics") | strpos(AF6, "PSE")
(0 real changes made)
replace top_author7=1 if strpos(AF7, "Paris School of Economics") | strpos(AF7, "PSE")
(0 real changes made)
replace top_author8=1 if strpos(AF8, "Paris School of Economics") | strpos(AF8, "PSE")
(0 real changes made)
replace top_author9=1 if strpos(AF9, "Paris School of Economics") | strpos(AF9, "PSE")
(0 real changes made)
replace top_author10=1 if strpos(AF10, "Paris School of Economics") | strpos(AF10, "PSE")
(0 real changes made)
replace top_author11=1 if strpos(AF11, "Paris School of Economics") | strpos(AF11, "PSE")
(0 real changes made)
248
replace top_author`i'=1 if strpos(AF`i', "Princeton University")
replace top_author1=1 if strpos(AF1, "Princeton University")
(497 real changes made)
replace top_author2=1 if strpos(AF2, "Princeton University")
(163 real changes made)
replace top_author3=1 if strpos(AF3, "Princeton University")
(18 real changes made)
replace top_author4=1 if strpos(AF4, "Princeton University")
(0 real changes made)
replace top_author5=1 if strpos(AF5, "Princeton University")
(0 real changes made)
replace top_author6=1 if strpos(AF6, "Princeton University")
(0 real changes made)
replace top_author7=1 if strpos(AF7, "Princeton University")
(0 real changes made)
replace top_author8=1 if strpos(AF8, "Princeton University")
(0 real changes made)
replace top_author9=1 if strpos(AF9, "Princeton University")
(0 real changes made)
replace top_author10=1 if strpos(AF10, "Princeton University")
(0 real changes made)
replace top_author11=1 if strpos(AF11, "Princeton University")
(0 real changes made)
249
replace top_author`i'=1 if strpos(AF`i', "Stanford University")
replace top_author1=1 if strpos(AF1, "Stanford University")
(425 real changes made)
replace top_author2=1 if strpos(AF2, "Stanford University")
(363 real changes made)
replace top_author3=1 if strpos(AF3, "Stanford University")
(18 real changes made)
replace top_author4=1 if strpos(AF4, "Stanford University")
(15 real changes made)
replace top_author5=1 if strpos(AF5, "Stanford University")
(0 real changes made)
replace top_author6=1 if strpos(AF6, "Stanford University")
(0 real changes made)
replace top_author7=1 if strpos(AF7, "Stanford University")
(0 real changes made)
replace top_author8=1 if strpos(AF8, "Stanford University")
(0 real changes made)
replace top_author9=1 if strpos(AF9, "Stanford University")
(34 real changes made)
replace top_author10=1 if strpos(AF10, "Stanford University")
(34 real changes made)
replace top_author11=1 if strpos(AF11, "Stanford University")
(34 real changes made)
250
replace top_author`i'=1 if strpos(AF`i', "Oxford University")
replace top_author1=1 if strpos(AF1, "Oxford University")
(7 real changes made)
replace top_author2=1 if strpos(AF2, "Oxford University")
(0 real changes made)
replace top_author3=1 if strpos(AF3, "Oxford University")
(12 real changes made)
replace top_author4=1 if strpos(AF4, "Oxford University")
(0 real changes made)
replace top_author5=1 if strpos(AF5, "Oxford University")
(0 real changes made)
replace top_author6=1 if strpos(AF6, "Oxford University")
(0 real changes made)
replace top_author7=1 if strpos(AF7, "Oxford University")
(0 real changes made)
replace top_author8=1 if strpos(AF8, "Oxford University")
(0 real changes made)
replace top_author9=1 if strpos(AF9, "Oxford University")
(0 real changes made)
replace top_author10=1 if strpos(AF10, "Oxford University")
(0 real changes made)
replace top_author11=1 if strpos(AF11, "Oxford University")
(0 real changes made)
251
replace top_author`i'=1 if strpos(AF`i', "Toulouse School of Economics") | strpos(AF`i', "TSE")
replace top_author1=1 if strpos(AF1, "Toulouse School of Economics") | strpos(AF1, "TSE")
(0 real changes made)
replace top_author2=1 if strpos(AF2, "Toulouse School of Economics") | strpos(AF2, "TSE")
(0 real changes made)
replace top_author3=1 if strpos(AF3, "Toulouse School of Economics") | strpos(AF3, "TSE")
(0 real changes made)
replace top_author4=1 if strpos(AF4, "Toulouse School of Economics") | strpos(AF4, "TSE")
(0 real changes made)
replace top_author5=1 if strpos(AF5, "Toulouse School of Economics") | strpos(AF5, "TSE")
(0 real changes made)
replace top_author6=1 if strpos(AF6, "Toulouse School of Economics") | strpos(AF6, "TSE")
(0 real changes made)
replace top_author7=1 if strpos(AF7, "Toulouse School of Economics") | strpos(AF7, "TSE")
(0 real changes made)
replace top_author8=1 if strpos(AF8, "Toulouse School of Economics") | strpos(AF8, "TSE")
(0 real changes made)
replace top_author9=1 if strpos(AF9, "Toulouse School of Economics") | strpos(AF9, "TSE")
(0 real changes made)
replace top_author10=1 if strpos(AF10, "Toulouse School of Economics") | strpos(AF10, "TSE")
(0 real changes made)
replace top_author11=1 if strpos(AF11, "Toulouse School of Economics") | strpos(AF11, "TSE")
(0 real changes made)
252
replace top_author`i'=1 if strpos(AF`i', "Columbia University")
replace top_author1=1 if strpos(AF1, "Columbia University")
(220 real changes made)
replace top_author2=1 if strpos(AF2, "Columbia University")
(355 real changes made)
replace top_author3=1 if strpos(AF3, "Columbia University")
(42 real changes made)
replace top_author4=1 if strpos(AF4, "Columbia University")
(0 real changes made)
replace top_author5=1 if strpos(AF5, "Columbia University")
(0 real changes made)
replace top_author6=1 if strpos(AF6, "Columbia University")
(0 real changes made)
replace top_author7=1 if strpos(AF7, "Columbia University")
(0 real changes made)
replace top_author8=1 if strpos(AF8, "Columbia University")
(0 real changes made)
replace top_author9=1 if strpos(AF9, "Columbia University")
(0 real changes made)
replace top_author10=1 if strpos(AF10, "Columbia University")
(0 real changes made)
replace top_author11=1 if strpos(AF11, "Columbia University")
(0 real changes made)
253
replace top_author`i'=1 if strpos(AF`i', "New York University") | strpos(AF`i', "NYU")
replace top_author1=1 if strpos(AF1, "New York University") | strpos(AF1, "NYU")
(137 real changes made)
replace top_author2=1 if strpos(AF2, "New York University") | strpos(AF2, "NYU")
(258 real changes made)
replace top_author3=1 if strpos(AF3, "New York University") | strpos(AF3, "NYU")
(163 real changes made)
replace top_author4=1 if strpos(AF4, "New York University") | strpos(AF4, "NYU")
(103 real changes made)
replace top_author5=1 if strpos(AF5, "New York University") | strpos(AF5, "NYU")
(0 real changes made)
replace top_author6=1 if strpos(AF6, "New York University") | strpos(AF6, "NYU")
(0 real changes made)
replace top_author7=1 if strpos(AF7, "New York University") | strpos(AF7, "NYU")
(0 real changes made)
replace top_author8=1 if strpos(AF8, "New York University") | strpos(AF8, "NYU")
(0 real changes made)
replace top_author9=1 if strpos(AF9, "New York University") | strpos(AF9, "NYU")
(0 real changes made)
replace top_author10=1 if strpos(AF10, "New York University") | strpos(AF10, "NYU")
(0 real changes made)
replace top_author11=1 if strpos(AF11, "New York University") | strpos(AF11, "NYU")
(0 real changes made)
254
replace top_author`i'=1 if strpos(AF`i', "Yale University")
replace top_author1=1 if strpos(AF1, "Yale University")
(71 real changes made)
replace top_author2=1 if strpos(AF2, "Yale University")
(227 real changes made)
replace top_author3=1 if strpos(AF3, "Yale University")
(32 real changes made)
replace top_author4=1 if strpos(AF4, "Yale University")
(68 real changes made)
replace top_author5=1 if strpos(AF5, "Yale University")
(0 real changes made)
replace top_author6=1 if strpos(AF6, "Yale University")
(256 real changes made)
replace top_author7=1 if strpos(AF7, "Yale University")
(0 real changes made)
replace top_author8=1 if strpos(AF8, "Yale University")
(0 real changes made)
replace top_author9=1 if strpos(AF9, "Yale University")
(0 real changes made)
replace top_author10=1 if strpos(AF10, "Yale University")
(0 real changes made)
replace top_author11=1 if strpos(AF11, "Yale University")
(0 real changes made)
255
replace top_author`i'=1 if strpos(AF`i', "Boston University")
replace top_author1=1 if strpos(AF1, "Boston University")
(37 real changes made)
replace top_author2=1 if strpos(AF2, "Boston University")
(67 real changes made)
replace top_author3=1 if strpos(AF3, "Boston University")
(4 real changes made)
replace top_author4=1 if strpos(AF4, "Boston University")
(0 real changes made)
replace top_author5=1 if strpos(AF5, "Boston University")
(0 real changes made)
replace top_author6=1 if strpos(AF6, "Boston University")
(0 real changes made)
replace top_author7=1 if strpos(AF7, "Boston University")
(0 real changes made)
replace top_author8=1 if strpos(AF8, "Boston University")
(0 real changes made)
replace top_author9=1 if strpos(AF9, "Boston University")
(0 real changes made)
replace top_author10=1 if strpos(AF10, "Boston University")
(0 real changes made)
replace top_author11=1 if strpos(AF11, "Boston University")
(0 real changes made)
256
replace top_author`i'=1 if strpos(AF`i', "Barcelona Graduate School of Economics") | strpos(AF`i', "Barcelona GSE")
replace top_author1=1 if strpos(AF1, "Barcelona Graduate School of Economics") | strpos(AF1, "Barcelona GSE")
(92 real changes made)
replace top_author2=1 if strpos(AF2, "Barcelona Graduate School of Economics") | strpos(AF2, "Barcelona GSE")
(84 real changes made)
replace top_author3=1 if strpos(AF3, "Barcelona Graduate School of Economics") | strpos(AF3, "Barcelona GSE")
(20 real changes made)
replace top_author4=1 if strpos(AF4, "Barcelona Graduate School of Economics") | strpos(AF4, "Barcelona GSE")
(0 real changes made)
replace top_author5=1 if strpos(AF5, "Barcelona Graduate School of Economics") | strpos(AF5, "Barcelona GSE")
(0 real changes made)
replace top_author6=1 if strpos(AF6, "Barcelona Graduate School of Economics") | strpos(AF6, "Barcelona GSE")
(0 real changes made)
replace top_author7=1 if strpos(AF7, "Barcelona Graduate School of Economics") | strpos(AF7, "Barcelona GSE")
(0 real changes made)
replace top_author8=1 if strpos(AF8, "Barcelona Graduate School of Economics") | strpos(AF8, "Barcelona GSE")
(0 real changes made)
replace top_author9=1 if strpos(AF9, "Barcelona Graduate School of Economics") | strpos(AF9, "Barcelona GSE")
(0 real changes made)
replace top_author10=1 if strpos(AF10, "Barcelona Graduate School of Economics") | strpos(AF10, "Barcelona GSE")
(0 real changes made)
replace top_author11=1 if strpos(AF11, "Barcelona Graduate School of Economics") | strpos(AF11, "Barcelona GSE")
(0 real changes made)
257
replace top_author`i'=1 if strpos(AF`i', "University of California-San Diego") | strpos(AF`i', "UCSD")
replace top_author1=1 if strpos(AF1, "University of California-San Diego") | strpos(AF1, "UCSD")
(0 real changes made)
replace top_author2=1 if strpos(AF2, "University of California-San Diego") | strpos(AF2, "UCSD")
(0 real changes made)
replace top_author3=1 if strpos(AF3, "University of California-San Diego") | strpos(AF3, "UCSD")
(0 real changes made)
replace top_author4=1 if strpos(AF4, "University of California-San Diego") | strpos(AF4, "UCSD")
(0 real changes made)
replace top_author5=1 if strpos(AF5, "University of California-San Diego") | strpos(AF5, "UCSD")
(0 real changes made)
replace top_author6=1 if strpos(AF6, "University of California-San Diego") | strpos(AF6, "UCSD")
(0 real changes made)
replace top_author7=1 if strpos(AF7, "University of California-San Diego") | strpos(AF7, "UCSD")
(0 real changes made)
replace top_author8=1 if strpos(AF8, "University of California-San Diego") | strpos(AF8, "UCSD")
(0 real changes made)
replace top_author9=1 if strpos(AF9, "University of California-San Diego") | strpos(AF9, "UCSD")
(0 real changes made)
replace top_author10=1 if strpos(AF10, "University of California-San Diego") | strpos(AF10, "UCSD")
(0 real changes made)
replace top_author11=1 if strpos(AF11, "University of California-San Diego") | strpos(AF11, "UCSD")
(0 real changes made)
258
replace top_author`i'=1 if strpos(AF`i', "Dartmouth College")
replace top_author1=1 if strpos(AF1, "Dartmouth College")
(60 real changes made)
replace top_author2=1 if strpos(AF2, "Dartmouth College")
(65 real changes made)
replace top_author3=1 if strpos(AF3, "Dartmouth College")
(89 real changes made)
replace top_author4=1 if strpos(AF4, "Dartmouth College")
(55 real changes made)
replace top_author5=1 if strpos(AF5, "Dartmouth College")
(0 real changes made)
replace top_author6=1 if strpos(AF6, "Dartmouth College")
(0 real changes made)
replace top_author7=1 if strpos(AF7, "Dartmouth College")
(0 real changes made)
replace top_author8=1 if strpos(AF8, "Dartmouth College")
(0 real changes made)
replace top_author9=1 if strpos(AF9, "Dartmouth College")
(0 real changes made)
replace top_author10=1 if strpos(AF10, "Dartmouth College")
(0 real changes made)
replace top_author11=1 if strpos(AF11, "Dartmouth College")
(0 real changes made)
259
replace top_author`i'=1 if strpos(AF`i', "University of Pennsylvania")
replace top_author1=1 if strpos(AF1, "University of Pennsylvania")
(237 real changes made)
replace top_author2=1 if strpos(AF2, "University of Pennsylvania")
(229 real changes made)
replace top_author3=1 if strpos(AF3, "University of Pennsylvania")
(280 real changes made)
replace top_author4=1 if strpos(AF4, "University of Pennsylvania")
(135 real changes made)
replace top_author5=1 if strpos(AF5, "University of Pennsylvania")
(296 real changes made)
replace top_author6=1 if strpos(AF6, "University of Pennsylvania")
(0 real changes made)
replace top_author7=1 if strpos(AF7, "University of Pennsylvania")
(0 real changes made)
replace top_author8=1 if strpos(AF8, "University of Pennsylvania")
(0 real changes made)
replace top_author9=1 if strpos(AF9, "University of Pennsylvania")
(0 real changes made)
replace top_author10=1 if strpos(AF10, "University of Pennsylvania")
(0 real changes made)
replace top_author11=1 if strpos(AF11, "University of Pennsylvania")
(0 real changes made)
260
replace top_author`i'=1 if strpos(AF`i', "University College London")  | strpos(AF`i', "UCL")
replace top_author1=1 if strpos(AF1, "University College London")  | strpos(AF1, "UCL")
(304 real changes made)
replace top_author2=1 if strpos(AF2, "University College London")  | strpos(AF2, "UCL")
(18 real changes made)
replace top_author3=1 if strpos(AF3, "University College London")  | strpos(AF3, "UCL")
(52 real changes made)
replace top_author4=1 if strpos(AF4, "University College London")  | strpos(AF4, "UCL")
(12 real changes made)
replace top_author5=1 if strpos(AF5, "University College London")  | strpos(AF5, "UCL")
(12 real changes made)
replace top_author6=1 if strpos(AF6, "University College London")  | strpos(AF6, "UCL")
(0 real changes made)
replace top_author7=1 if strpos(AF7, "University College London")  | strpos(AF7, "UCL")
(0 real changes made)
replace top_author8=1 if strpos(AF8, "University College London")  | strpos(AF8, "UCL")
(0 real changes made)
replace top_author9=1 if strpos(AF9, "University College London")  | strpos(AF9, "UCL")
(0 real changes made)
replace top_author10=1 if strpos(AF10, "University College London")  | strpos(AF10, "UCL")
(0 real changes made)
replace top_author11=1 if strpos(AF11, "University College London")  | strpos(AF11, "UCL")
(0 real changes made)
261
replace top_author`i'=1 if strpos(AF`i', "Northwestern University")
replace top_author1=1 if strpos(AF1, "Northwestern University")
(327 real changes made)
replace top_author2=1 if strpos(AF2, "Northwestern University")
(463 real changes made)
replace top_author3=1 if strpos(AF3, "Northwestern University")
(93 real changes made)
replace top_author4=1 if strpos(AF4, "Northwestern University")
(129 real changes made)
replace top_author5=1 if strpos(AF5, "Northwestern University")
(0 real changes made)
replace top_author6=1 if strpos(AF6, "Northwestern University")
(0 real changes made)
replace top_author7=1 if strpos(AF7, "Northwestern University")
(0 real changes made)
replace top_author8=1 if strpos(AF8, "Northwestern University")
(0 real changes made)
replace top_author9=1 if strpos(AF9, "Northwestern University")
(0 real changes made)
replace top_author10=1 if strpos(AF10, "Northwestern University")
(0 real changes made)
replace top_author11=1 if strpos(AF11, "Northwestern University")
(0 real changes made)
262
replace top_author`i'=1 if strpos(AF`i', "Columbia University")
replace top_author1=1 if strpos(AF1, "Columbia University")
(0 real changes made)
replace top_author2=1 if strpos(AF2, "Columbia University")
(0 real changes made)
replace top_author3=1 if strpos(AF3, "Columbia University")
(0 real changes made)
replace top_author4=1 if strpos(AF4, "Columbia University")
(0 real changes made)
replace top_author5=1 if strpos(AF5, "Columbia University")
(0 real changes made)
replace top_author6=1 if strpos(AF6, "Columbia University")
(0 real changes made)
replace top_author7=1 if strpos(AF7, "Columbia University")
(0 real changes made)
replace top_author8=1 if strpos(AF8, "Columbia University")
(0 real changes made)
replace top_author9=1 if strpos(AF9, "Columbia University")
(0 real changes made)
replace top_author10=1 if strpos(AF10, "Columbia University")
(0 real changes made)
replace top_author11=1 if strpos(AF11, "Columbia University")
(0 real changes made)
263
replace top_author`i'=1 if strpos(AF`i', "University of California-Los Angeles ") | strpos(AF`i', "UCLA")
replace top_author1=1 if strpos(AF1, "University of California-Los Angeles ") | strpos(AF1, "UCLA")
(0 real changes made)
replace top_author2=1 if strpos(AF2, "University of California-Los Angeles ") | strpos(AF2, "UCLA")
(0 real changes made)
replace top_author3=1 if strpos(AF3, "University of California-Los Angeles ") | strpos(AF3, "UCLA")
(0 real changes made)
replace top_author4=1 if strpos(AF4, "University of California-Los Angeles ") | strpos(AF4, "UCLA")
(0 real changes made)
replace top_author5=1 if strpos(AF5, "University of California-Los Angeles ") | strpos(AF5, "UCLA")
(0 real changes made)
replace top_author6=1 if strpos(AF6, "University of California-Los Angeles ") | strpos(AF6, "UCLA")
(0 real changes made)
replace top_author7=1 if strpos(AF7, "University of California-Los Angeles ") | strpos(AF7, "UCLA")
(0 real changes made)
replace top_author8=1 if strpos(AF8, "University of California-Los Angeles ") | strpos(AF8, "UCLA")
(0 real changes made)
replace top_author9=1 if strpos(AF9, "University of California-Los Angeles ") | strpos(AF9, "UCLA")
(0 real changes made)
replace top_author10=1 if strpos(AF10, "University of California-Los Angeles ") | strpos(AF10, "UCLA")
(0 real changes made)
replace top_author11=1 if strpos(AF11, "University of California-Los Angeles ") | strpos(AF11, "UCLA")
(0 real changes made)
264
replace top_author`i'=1 if strpos(AF`i', "London School of Economics") | strpos(AF`i', "LSE")
replace top_author1=1 if strpos(AF1, "London School of Economics") | strpos(AF1, "LSE")
(528 real changes made)
replace top_author2=1 if strpos(AF2, "London School of Economics") | strpos(AF2, "LSE")
(267 real changes made)
replace top_author3=1 if strpos(AF3, "London School of Economics") | strpos(AF3, "LSE")
(167 real changes made)
replace top_author4=1 if strpos(AF4, "London School of Economics") | strpos(AF4, "LSE")
(120 real changes made)
replace top_author5=1 if strpos(AF5, "London School of Economics") | strpos(AF5, "LSE")
(0 real changes made)
replace top_author6=1 if strpos(AF6, "London School of Economics") | strpos(AF6, "LSE")
(0 real changes made)
replace top_author7=1 if strpos(AF7, "London School of Economics") | strpos(AF7, "LSE")
(0 real changes made)
replace top_author8=1 if strpos(AF8, "London School of Economics") | strpos(AF8, "LSE")
(0 real changes made)
replace top_author9=1 if strpos(AF9, "London School of Economics") | strpos(AF9, "LSE")
(0 real changes made)
replace top_author10=1 if strpos(AF10, "London School of Economics") | strpos(AF10, "LSE")
(0 real changes made)
replace top_author11=1 if strpos(AF11, "London School of Economics") | strpos(AF11, "LSE")
(0 real changes made)
265
replace top_author`i'=1 if strpos(AF`i', "University of Wisconsin-Madison")
replace top_author1=1 if strpos(AF1, "University of Wisconsin-Madison")
(2 real changes made)
replace top_author2=1 if strpos(AF2, "University of Wisconsin-Madison")
(0 real changes made)
replace top_author3=1 if strpos(AF3, "University of Wisconsin-Madison")
(0 real changes made)
replace top_author4=1 if strpos(AF4, "University of Wisconsin-Madison")
(0 real changes made)
replace top_author5=1 if strpos(AF5, "University of Wisconsin-Madison")
(0 real changes made)
replace top_author6=1 if strpos(AF6, "University of Wisconsin-Madison")
(0 real changes made)
replace top_author7=1 if strpos(AF7, "University of Wisconsin-Madison")
(0 real changes made)
replace top_author8=1 if strpos(AF8, "University of Wisconsin-Madison")
(0 real changes made)
replace top_author9=1 if strpos(AF9, "University of Wisconsin-Madison")
(0 real changes made)
replace top_author10=1 if strpos(AF10, "University of Wisconsin-Madison")
(0 real changes made)
replace top_author11=1 if strpos(AF11, "University of Wisconsin-Madison")
(0 real changes made)
266
replace top_author`i'=1 if strpos(AF`i', "University of Michigan")
replace top_author1=1 if strpos(AF1, "University of Michigan")
(368 real changes made)
replace top_author2=1 if strpos(AF2, "University of Michigan")
(80 real changes made)
replace top_author3=1 if strpos(AF3, "University of Michigan")
(169 real changes made)
replace top_author4=1 if strpos(AF4, "University of Michigan")
(182 real changes made)
replace top_author5=1 if strpos(AF5, "University of Michigan")
(0 real changes made)
replace top_author6=1 if strpos(AF6, "University of Michigan")
(0 real changes made)
replace top_author7=1 if strpos(AF7, "University of Michigan")
(0 real changes made)
replace top_author8=1 if strpos(AF8, "University of Michigan")
(0 real changes made)
replace top_author9=1 if strpos(AF9, "University of Michigan")
(0 real changes made)
replace top_author10=1 if strpos(AF10, "University of Michigan")
(0 real changes made)
replace top_author11=1 if strpos(AF11, "University of Michigan")
(0 real changes made)
267
}
268
269
capture drop share_top_authors

. capture drop share_top_authors

. 
270
egen share_top_authors = rowmean(top_author`i'*)
egen share_top_authors = rowmean(top_author*)

. egen share_top_authors = rowmean(top_author`i'*)

. 
271
272
* share_top_phd
273
274
forval i = 1(1)11 {
forval i = 1(1)11 {
275
capture drop top_phd`i'
capture drop top_phd1
capture drop top_phd2
capture drop top_phd3
capture drop top_phd4
capture drop top_phd5
capture drop top_phd6
capture drop top_phd7
capture drop top_phd8
capture drop top_phd9
capture drop top_phd10
capture drop top_phd11
276
gen top_phd`i'=0
gen top_phd1=0
gen top_phd2=0
gen top_phd3=0
gen top_phd4=0
gen top_phd5=0
gen top_phd6=0
gen top_phd7=0
gen top_phd8=0
gen top_phd9=0
gen top_phd10=0
gen top_phd11=0
277
replace top_phd`i'=. if Author`i'==""
replace top_phd1=. if Author1==""
(0 real changes made)
replace top_phd2=. if Author2==""
(4,394 real changes made, 4,394 to missing)
replace top_phd3=. if Author3==""
(10,395 real changes made, 10,395 to missing)
replace top_phd4=. if Author4==""
(17,884 real changes made, 17,884 to missing)
replace top_phd5=. if Author5==""
(20,482 real changes made, 20,482 to missing)
replace top_phd6=. if Author6==""
(21,437 real changes made, 21,437 to missing)
replace top_phd7=. if Author7==""
(21,693 real changes made, 21,693 to missing)
replace top_phd8=. if Author8==""
(21,740 real changes made, 21,740 to missing)
replace top_phd9=. if Author9==""
(21,740 real changes made, 21,740 to missing)
replace top_phd10=. if Author10==""
(21,740 real changes made, 21,740 to missing)
replace top_phd11=. if Author11==""
(21,740 real changes made, 21,740 to missing)
278
replace top_phd`i'=1 if strpos(PhDInstitution`i', "Harvard")
replace top_phd1=1 if strpos(PhDInstitution1, "Harvard")
(2,389 real changes made)
replace top_phd2=1 if strpos(PhDInstitution2, "Harvard")
(1,758 real changes made)
replace top_phd3=1 if strpos(PhDInstitution3, "Harvard")
(968 real changes made)
replace top_phd4=1 if strpos(PhDInstitution4, "Harvard")
(483 real changes made)
replace top_phd5=1 if strpos(PhDInstitution5, "Harvard")
(43 real changes made)
replace top_phd6=1 if strpos(PhDInstitution6, "Harvard")
(0 real changes made)
replace top_phd7=1 if strpos(PhDInstitution7, "Harvard")
(0 real changes made)
replace top_phd8=1 if strpos(PhDInstitution8, "Harvard")
(0 real changes made)
replace top_phd9=1 if strpos(PhDInstitution9, "Harvard")
(0 real changes made)
replace top_phd10=1 if strpos(PhDInstitution10, "Harvard")
(0 real changes made)
replace top_phd11=1 if strpos(PhDInstitution11, "Harvard")
(0 real changes made)
279
replace top_phd`i'=1 if strpos(PhDInstitution`i', "Massachusetts Institute of Technology") | strpos(PhDInstitution`i', "MIT")
replace top_phd1=1 if strpos(PhDInstitution1, "Massachusetts Institute of Technology") | strpos(PhDInstitution1, "MIT")
(2,279 real changes made)
replace top_phd2=1 if strpos(PhDInstitution2, "Massachusetts Institute of Technology") | strpos(PhDInstitution2, "MIT")
(1,427 real changes made)
replace top_phd3=1 if strpos(PhDInstitution3, "Massachusetts Institute of Technology") | strpos(PhDInstitution3, "MIT")
(1,199 real changes made)
replace top_phd4=1 if strpos(PhDInstitution4, "Massachusetts Institute of Technology") | strpos(PhDInstitution4, "MIT")
(316 real changes made)
replace top_phd5=1 if strpos(PhDInstitution5, "Massachusetts Institute of Technology") | strpos(PhDInstitution5, "MIT")
(0 real changes made)
replace top_phd6=1 if strpos(PhDInstitution6, "Massachusetts Institute of Technology") | strpos(PhDInstitution6, "MIT")
(0 real changes made)
replace top_phd7=1 if strpos(PhDInstitution7, "Massachusetts Institute of Technology") | strpos(PhDInstitution7, "MIT")
(0 real changes made)
replace top_phd8=1 if strpos(PhDInstitution8, "Massachusetts Institute of Technology") | strpos(PhDInstitution8, "MIT")
(0 real changes made)
replace top_phd9=1 if strpos(PhDInstitution9, "Massachusetts Institute of Technology") | strpos(PhDInstitution9, "MIT")
(0 real changes made)
replace top_phd10=1 if strpos(PhDInstitution10, "Massachusetts Institute of Technology") | strpos(PhDInstitution10, "MIT")
(0 real changes made)
replace top_phd11=1 if strpos(PhDInstitution11, "Massachusetts Institute of Technology") | strpos(PhDInstitution11, "MIT")
(0 real changes made)
280
replace top_phd`i'=1 if strpos(PhDInstitution`i', "Berkeley")
replace top_phd1=1 if strpos(PhDInstitution1, "Berkeley")
(1,139 real changes made)
replace top_phd2=1 if strpos(PhDInstitution2, "Berkeley")
(896 real changes made)
replace top_phd3=1 if strpos(PhDInstitution3, "Berkeley")
(549 real changes made)
replace top_phd4=1 if strpos(PhDInstitution4, "Berkeley")
(94 real changes made)
replace top_phd5=1 if strpos(PhDInstitution5, "Berkeley")
(292 real changes made)
replace top_phd6=1 if strpos(PhDInstitution6, "Berkeley")
(0 real changes made)
replace top_phd7=1 if strpos(PhDInstitution7, "Berkeley")
(0 real changes made)
replace top_phd8=1 if strpos(PhDInstitution8, "Berkeley")
(0 real changes made)
replace top_phd9=1 if strpos(PhDInstitution9, "Berkeley")
(0 real changes made)
replace top_phd10=1 if strpos(PhDInstitution10, "Berkeley")
(0 real changes made)
replace top_phd11=1 if strpos(PhDInstitution11, "Berkeley")
(0 real changes made)
281
replace top_phd`i'=1 if strpos(PhDInstitution`i', "University of Chicago")
replace top_phd1=1 if strpos(PhDInstitution1, "University of Chicago")
(560 real changes made)
replace top_phd2=1 if strpos(PhDInstitution2, "University of Chicago")
(306 real changes made)
replace top_phd3=1 if strpos(PhDInstitution3, "University of Chicago")
(71 real changes made)
replace top_phd4=1 if strpos(PhDInstitution4, "University of Chicago")
(0 real changes made)
replace top_phd5=1 if strpos(PhDInstitution5, "University of Chicago")
(0 real changes made)
replace top_phd6=1 if strpos(PhDInstitution6, "University of Chicago")
(0 real changes made)
replace top_phd7=1 if strpos(PhDInstitution7, "University of Chicago")
(0 real changes made)
replace top_phd8=1 if strpos(PhDInstitution8, "University of Chicago")
(0 real changes made)
replace top_phd9=1 if strpos(PhDInstitution9, "University of Chicago")
(0 real changes made)
replace top_phd10=1 if strpos(PhDInstitution10, "University of Chicago")
(0 real changes made)
replace top_phd11=1 if strpos(PhDInstitution11, "University of Chicago")
(0 real changes made)
282
replace top_phd`i'=1 if strpos(PhDInstitution`i', "Paris School of Economics") | strpos(PhDInstitution`i', "PSE")
replace top_phd1=1 if strpos(PhDInstitution1, "Paris School of Economics") | strpos(PhDInstitution1, "PSE")
(376 real changes made)
replace top_phd2=1 if strpos(PhDInstitution2, "Paris School of Economics") | strpos(PhDInstitution2, "PSE")
(564 real changes made)
replace top_phd3=1 if strpos(PhDInstitution3, "Paris School of Economics") | strpos(PhDInstitution3, "PSE")
(105 real changes made)
replace top_phd4=1 if strpos(PhDInstitution4, "Paris School of Economics") | strpos(PhDInstitution4, "PSE")
(52 real changes made)
replace top_phd5=1 if strpos(PhDInstitution5, "Paris School of Economics") | strpos(PhDInstitution5, "PSE")
(52 real changes made)
replace top_phd6=1 if strpos(PhDInstitution6, "Paris School of Economics") | strpos(PhDInstitution6, "PSE")
(0 real changes made)
replace top_phd7=1 if strpos(PhDInstitution7, "Paris School of Economics") | strpos(PhDInstitution7, "PSE")
(0 real changes made)
replace top_phd8=1 if strpos(PhDInstitution8, "Paris School of Economics") | strpos(PhDInstitution8, "PSE")
(0 real changes made)
replace top_phd9=1 if strpos(PhDInstitution9, "Paris School of Economics") | strpos(PhDInstitution9, "PSE")
(0 real changes made)
replace top_phd10=1 if strpos(PhDInstitution10, "Paris School of Economics") | strpos(PhDInstitution10, "PSE")
(0 real changes made)
replace top_phd11=1 if strpos(PhDInstitution11, "Paris School of Economics") | strpos(PhDInstitution11, "PSE")
(0 real changes made)
283
replace top_phd`i'=1 if strpos(PhDInstitution`i', "Princeton University")
replace top_phd1=1 if strpos(PhDInstitution1, "Princeton University")
(32 real changes made)
replace top_phd2=1 if strpos(PhDInstitution2, "Princeton University")
(219 real changes made)
replace top_phd3=1 if strpos(PhDInstitution3, "Princeton University")
(227 real changes made)
replace top_phd4=1 if strpos(PhDInstitution4, "Princeton University")
(6 real changes made)
replace top_phd5=1 if strpos(PhDInstitution5, "Princeton University")
(0 real changes made)
replace top_phd6=1 if strpos(PhDInstitution6, "Princeton University")
(0 real changes made)
replace top_phd7=1 if strpos(PhDInstitution7, "Princeton University")
(0 real changes made)
replace top_phd8=1 if strpos(PhDInstitution8, "Princeton University")
(0 real changes made)
replace top_phd9=1 if strpos(PhDInstitution9, "Princeton University")
(0 real changes made)
replace top_phd10=1 if strpos(PhDInstitution10, "Princeton University")
(0 real changes made)
replace top_phd11=1 if strpos(PhDInstitution11, "Princeton University")
(0 real changes made)
284
replace top_phd`i'=1 if strpos(PhDInstitution`i', "Stanford University")
replace top_phd1=1 if strpos(PhDInstitution1, "Stanford University")
(310 real changes made)
replace top_phd2=1 if strpos(PhDInstitution2, "Stanford University")
(163 real changes made)
replace top_phd3=1 if strpos(PhDInstitution3, "Stanford University")
(127 real changes made)
replace top_phd4=1 if strpos(PhDInstitution4, "Stanford University")
(36 real changes made)
replace top_phd5=1 if strpos(PhDInstitution5, "Stanford University")
(0 real changes made)
replace top_phd6=1 if strpos(PhDInstitution6, "Stanford University")
(0 real changes made)
replace top_phd7=1 if strpos(PhDInstitution7, "Stanford University")
(0 real changes made)
replace top_phd8=1 if strpos(PhDInstitution8, "Stanford University")
(0 real changes made)
replace top_phd9=1 if strpos(PhDInstitution9, "Stanford University")
(0 real changes made)
replace top_phd10=1 if strpos(PhDInstitution10, "Stanford University")
(0 real changes made)
replace top_phd11=1 if strpos(PhDInstitution11, "Stanford University")
(0 real changes made)
285
replace top_phd`i'=1 if strpos(PhDInstitution`i', "Oxford University")
replace top_phd1=1 if strpos(PhDInstitution1, "Oxford University")
(79 real changes made)
replace top_phd2=1 if strpos(PhDInstitution2, "Oxford University")
(135 real changes made)
replace top_phd3=1 if strpos(PhDInstitution3, "Oxford University")
(0 real changes made)
replace top_phd4=1 if strpos(PhDInstitution4, "Oxford University")
(59 real changes made)
replace top_phd5=1 if strpos(PhDInstitution5, "Oxford University")
(67 real changes made)
replace top_phd6=1 if strpos(PhDInstitution6, "Oxford University")
(0 real changes made)
replace top_phd7=1 if strpos(PhDInstitution7, "Oxford University")
(0 real changes made)
replace top_phd8=1 if strpos(PhDInstitution8, "Oxford University")
(0 real changes made)
replace top_phd9=1 if strpos(PhDInstitution9, "Oxford University")
(0 real changes made)
replace top_phd10=1 if strpos(PhDInstitution10, "Oxford University")
(0 real changes made)
replace top_phd11=1 if strpos(PhDInstitution11, "Oxford University")
(0 real changes made)
286
replace top_phd`i'=1 if strpos(PhDInstitution`i', "Toulouse School of Economics") | strpos(PhDInstitution`i', "TSE")
replace top_phd1=1 if strpos(PhDInstitution1, "Toulouse School of Economics") | strpos(PhDInstitution1, "TSE")
(35 real changes made)
replace top_phd2=1 if strpos(PhDInstitution2, "Toulouse School of Economics") | strpos(PhDInstitution2, "TSE")
(0 real changes made)
replace top_phd3=1 if strpos(PhDInstitution3, "Toulouse School of Economics") | strpos(PhDInstitution3, "TSE")
(0 real changes made)
replace top_phd4=1 if strpos(PhDInstitution4, "Toulouse School of Economics") | strpos(PhDInstitution4, "TSE")
(18 real changes made)
replace top_phd5=1 if strpos(PhDInstitution5, "Toulouse School of Economics") | strpos(PhDInstitution5, "TSE")
(0 real changes made)
replace top_phd6=1 if strpos(PhDInstitution6, "Toulouse School of Economics") | strpos(PhDInstitution6, "TSE")
(0 real changes made)
replace top_phd7=1 if strpos(PhDInstitution7, "Toulouse School of Economics") | strpos(PhDInstitution7, "TSE")
(0 real changes made)
replace top_phd8=1 if strpos(PhDInstitution8, "Toulouse School of Economics") | strpos(PhDInstitution8, "TSE")
(0 real changes made)
replace top_phd9=1 if strpos(PhDInstitution9, "Toulouse School of Economics") | strpos(PhDInstitution9, "TSE")
(0 real changes made)
replace top_phd10=1 if strpos(PhDInstitution10, "Toulouse School of Economics") | strpos(PhDInstitution10, "TSE")
(0 real changes made)
replace top_phd11=1 if strpos(PhDInstitution11, "Toulouse School of Economics") | strpos(PhDInstitution11, "TSE")
(0 real changes made)
287
replace top_phd`i'=1 if strpos(PhDInstitution`i', "Columbia University")
replace top_phd1=1 if strpos(PhDInstitution1, "Columbia University")
(163 real changes made)
replace top_phd2=1 if strpos(PhDInstitution2, "Columbia University")
(97 real changes made)
replace top_phd3=1 if strpos(PhDInstitution3, "Columbia University")
(272 real changes made)
replace top_phd4=1 if strpos(PhDInstitution4, "Columbia University")
(113 real changes made)
replace top_phd5=1 if strpos(PhDInstitution5, "Columbia University")
(256 real changes made)
replace top_phd6=1 if strpos(PhDInstitution6, "Columbia University")
(0 real changes made)
replace top_phd7=1 if strpos(PhDInstitution7, "Columbia University")
(0 real changes made)
replace top_phd8=1 if strpos(PhDInstitution8, "Columbia University")
(0 real changes made)
replace top_phd9=1 if strpos(PhDInstitution9, "Columbia University")
(0 real changes made)
replace top_phd10=1 if strpos(PhDInstitution10, "Columbia University")
(0 real changes made)
replace top_phd11=1 if strpos(PhDInstitution11, "Columbia University")
(0 real changes made)
288
replace top_phd`i'=1 if strpos(PhDInstitution`i', "New York University") | strpos(PhDInstitution`i', "NYU")
replace top_phd1=1 if strpos(PhDInstitution1, "New York University") | strpos(PhDInstitution1, "NYU")
(233 real changes made)
replace top_phd2=1 if strpos(PhDInstitution2, "New York University") | strpos(PhDInstitution2, "NYU")
(50 real changes made)
replace top_phd3=1 if strpos(PhDInstitution3, "New York University") | strpos(PhDInstitution3, "NYU")
(358 real changes made)
replace top_phd4=1 if strpos(PhDInstitution4, "New York University") | strpos(PhDInstitution4, "NYU")
(1 real change made)
replace top_phd5=1 if strpos(PhDInstitution5, "New York University") | strpos(PhDInstitution5, "NYU")
(6 real changes made)
replace top_phd6=1 if strpos(PhDInstitution6, "New York University") | strpos(PhDInstitution6, "NYU")
(0 real changes made)
replace top_phd7=1 if strpos(PhDInstitution7, "New York University") | strpos(PhDInstitution7, "NYU")
(0 real changes made)
replace top_phd8=1 if strpos(PhDInstitution8, "New York University") | strpos(PhDInstitution8, "NYU")
(0 real changes made)
replace top_phd9=1 if strpos(PhDInstitution9, "New York University") | strpos(PhDInstitution9, "NYU")
(0 real changes made)
replace top_phd10=1 if strpos(PhDInstitution10, "New York University") | strpos(PhDInstitution10, "NYU")
(0 real changes made)
replace top_phd11=1 if strpos(PhDInstitution11, "New York University") | strpos(PhDInstitution11, "NYU")
(0 real changes made)
289
replace top_phd`i'=1 if strpos(PhDInstitution`i', "Yale University")
replace top_phd1=1 if strpos(PhDInstitution1, "Yale University")
(217 real changes made)
replace top_phd2=1 if strpos(PhDInstitution2, "Yale University")
(309 real changes made)
replace top_phd3=1 if strpos(PhDInstitution3, "Yale University")
(58 real changes made)
replace top_phd4=1 if strpos(PhDInstitution4, "Yale University")
(8 real changes made)
replace top_phd5=1 if strpos(PhDInstitution5, "Yale University")
(0 real changes made)
replace top_phd6=1 if strpos(PhDInstitution6, "Yale University")
(0 real changes made)
replace top_phd7=1 if strpos(PhDInstitution7, "Yale University")
(0 real changes made)
replace top_phd8=1 if strpos(PhDInstitution8, "Yale University")
(0 real changes made)
replace top_phd9=1 if strpos(PhDInstitution9, "Yale University")
(0 real changes made)
replace top_phd10=1 if strpos(PhDInstitution10, "Yale University")
(0 real changes made)
replace top_phd11=1 if strpos(PhDInstitution11, "Yale University")
(0 real changes made)
290
replace top_phd`i'=1 if strpos(PhDInstitution`i', "Boston University")
replace top_phd1=1 if strpos(PhDInstitution1, "Boston University")
(82 real changes made)
replace top_phd2=1 if strpos(PhDInstitution2, "Boston University")
(144 real changes made)
replace top_phd3=1 if strpos(PhDInstitution3, "Boston University")
(67 real changes made)
replace top_phd4=1 if strpos(PhDInstitution4, "Boston University")
(20 real changes made)
replace top_phd5=1 if strpos(PhDInstitution5, "Boston University")
(0 real changes made)
replace top_phd6=1 if strpos(PhDInstitution6, "Boston University")
(0 real changes made)
replace top_phd7=1 if strpos(PhDInstitution7, "Boston University")
(0 real changes made)
replace top_phd8=1 if strpos(PhDInstitution8, "Boston University")
(0 real changes made)
replace top_phd9=1 if strpos(PhDInstitution9, "Boston University")
(0 real changes made)
replace top_phd10=1 if strpos(PhDInstitution10, "Boston University")
(0 real changes made)
replace top_phd11=1 if strpos(PhDInstitution11, "Boston University")
(0 real changes made)
291
replace top_phd`i'=1 if strpos(PhDInstitution`i', "Barcelona Graduate School of Economics") | strpos(PhDInstitution`i', "Barcelona GSE")
replace top_phd1=1 if strpos(PhDInstitution1, "Barcelona Graduate School of Economics") | strpos(PhDInstitution1, "Barcelona GSE")
(0 real changes made)
replace top_phd2=1 if strpos(PhDInstitution2, "Barcelona Graduate School of Economics") | strpos(PhDInstitution2, "Barcelona GSE")
(0 real changes made)
replace top_phd3=1 if strpos(PhDInstitution3, "Barcelona Graduate School of Economics") | strpos(PhDInstitution3, "Barcelona GSE")
(0 real changes made)
replace top_phd4=1 if strpos(PhDInstitution4, "Barcelona Graduate School of Economics") | strpos(PhDInstitution4, "Barcelona GSE")
(0 real changes made)
replace top_phd5=1 if strpos(PhDInstitution5, "Barcelona Graduate School of Economics") | strpos(PhDInstitution5, "Barcelona GSE")
(0 real changes made)
replace top_phd6=1 if strpos(PhDInstitution6, "Barcelona Graduate School of Economics") | strpos(PhDInstitution6, "Barcelona GSE")
(0 real changes made)
replace top_phd7=1 if strpos(PhDInstitution7, "Barcelona Graduate School of Economics") | strpos(PhDInstitution7, "Barcelona GSE")
(0 real changes made)
replace top_phd8=1 if strpos(PhDInstitution8, "Barcelona Graduate School of Economics") | strpos(PhDInstitution8, "Barcelona GSE")
(0 real changes made)
replace top_phd9=1 if strpos(PhDInstitution9, "Barcelona Graduate School of Economics") | strpos(PhDInstitution9, "Barcelona GSE")
(0 real changes made)
replace top_phd10=1 if strpos(PhDInstitution10, "Barcelona Graduate School of Economics") | strpos(PhDInstitution10, "Barcelona GSE")
(0 real changes made)
replace top_phd11=1 if strpos(PhDInstitution11, "Barcelona Graduate School of Economics") | strpos(PhDInstitution11, "Barcelona GSE")
(0 real changes made)
292
replace top_phd`i'=1 if strpos(PhDInstitution`i', "University of California-San Diego") | strpos(PhDInstitution`i', "UCSD")
replace top_phd1=1 if strpos(PhDInstitution1, "University of California-San Diego") | strpos(PhDInstitution1, "UCSD")
(140 real changes made)
replace top_phd2=1 if strpos(PhDInstitution2, "University of California-San Diego") | strpos(PhDInstitution2, "UCSD")
(6 real changes made)
replace top_phd3=1 if strpos(PhDInstitution3, "University of California-San Diego") | strpos(PhDInstitution3, "UCSD")
(51 real changes made)
replace top_phd4=1 if strpos(PhDInstitution4, "University of California-San Diego") | strpos(PhDInstitution4, "UCSD")
(0 real changes made)
replace top_phd5=1 if strpos(PhDInstitution5, "University of California-San Diego") | strpos(PhDInstitution5, "UCSD")
(0 real changes made)
replace top_phd6=1 if strpos(PhDInstitution6, "University of California-San Diego") | strpos(PhDInstitution6, "UCSD")
(0 real changes made)
replace top_phd7=1 if strpos(PhDInstitution7, "University of California-San Diego") | strpos(PhDInstitution7, "UCSD")
(0 real changes made)
replace top_phd8=1 if strpos(PhDInstitution8, "University of California-San Diego") | strpos(PhDInstitution8, "UCSD")
(0 real changes made)
replace top_phd9=1 if strpos(PhDInstitution9, "University of California-San Diego") | strpos(PhDInstitution9, "UCSD")
(0 real changes made)
replace top_phd10=1 if strpos(PhDInstitution10, "University of California-San Diego") | strpos(PhDInstitution10, "UCSD")
(0 real changes made)
replace top_phd11=1 if strpos(PhDInstitution11, "University of California-San Diego") | strpos(PhDInstitution11, "UCSD")
(0 real changes made)
293
replace top_phd`i'=1 if strpos(PhDInstitution`i', "Dartmouth College")
replace top_phd1=1 if strpos(PhDInstitution1, "Dartmouth College")
(0 real changes made)
replace top_phd2=1 if strpos(PhDInstitution2, "Dartmouth College")
(0 real changes made)
replace top_phd3=1 if strpos(PhDInstitution3, "Dartmouth College")
(0 real changes made)
replace top_phd4=1 if strpos(PhDInstitution4, "Dartmouth College")
(0 real changes made)
replace top_phd5=1 if strpos(PhDInstitution5, "Dartmouth College")
(0 real changes made)
replace top_phd6=1 if strpos(PhDInstitution6, "Dartmouth College")
(0 real changes made)
replace top_phd7=1 if strpos(PhDInstitution7, "Dartmouth College")
(0 real changes made)
replace top_phd8=1 if strpos(PhDInstitution8, "Dartmouth College")
(0 real changes made)
replace top_phd9=1 if strpos(PhDInstitution9, "Dartmouth College")
(0 real changes made)
replace top_phd10=1 if strpos(PhDInstitution10, "Dartmouth College")
(0 real changes made)
replace top_phd11=1 if strpos(PhDInstitution11, "Dartmouth College")
(0 real changes made)
294
replace top_phd`i'=1 if strpos(PhDInstitution`i', "University of Pennsylvania")
replace top_phd1=1 if strpos(PhDInstitution1, "University of Pennsylvania")
(165 real changes made)
replace top_phd2=1 if strpos(PhDInstitution2, "University of Pennsylvania")
(5 real changes made)
replace top_phd3=1 if strpos(PhDInstitution3, "University of Pennsylvania")
(192 real changes made)
replace top_phd4=1 if strpos(PhDInstitution4, "University of Pennsylvania")
(0 real changes made)
replace top_phd5=1 if strpos(PhDInstitution5, "University of Pennsylvania")
(0 real changes made)
replace top_phd6=1 if strpos(PhDInstitution6, "University of Pennsylvania")
(0 real changes made)
replace top_phd7=1 if strpos(PhDInstitution7, "University of Pennsylvania")
(0 real changes made)
replace top_phd8=1 if strpos(PhDInstitution8, "University of Pennsylvania")
(0 real changes made)
replace top_phd9=1 if strpos(PhDInstitution9, "University of Pennsylvania")
(0 real changes made)
replace top_phd10=1 if strpos(PhDInstitution10, "University of Pennsylvania")
(0 real changes made)
replace top_phd11=1 if strpos(PhDInstitution11, "University of Pennsylvania")
(0 real changes made)
295
replace top_phd`i'=1 if strpos(PhDInstitution`i', "University College London")  | strpos(PhDInstitution`i', "UCL")
replace top_phd1=1 if strpos(PhDInstitution1, "University College London")  | strpos(PhDInstitution1, "UCL")
(293 real changes made)
replace top_phd2=1 if strpos(PhDInstitution2, "University College London")  | strpos(PhDInstitution2, "UCL")
(265 real changes made)
replace top_phd3=1 if strpos(PhDInstitution3, "University College London")  | strpos(PhDInstitution3, "UCL")
(104 real changes made)
replace top_phd4=1 if strpos(PhDInstitution4, "University College London")  | strpos(PhDInstitution4, "UCL")
(77 real changes made)
replace top_phd5=1 if strpos(PhDInstitution5, "University College London")  | strpos(PhDInstitution5, "UCL")
(71 real changes made)
replace top_phd6=1 if strpos(PhDInstitution6, "University College London")  | strpos(PhDInstitution6, "UCL")
(0 real changes made)
replace top_phd7=1 if strpos(PhDInstitution7, "University College London")  | strpos(PhDInstitution7, "UCL")
(0 real changes made)
replace top_phd8=1 if strpos(PhDInstitution8, "University College London")  | strpos(PhDInstitution8, "UCL")
(0 real changes made)
replace top_phd9=1 if strpos(PhDInstitution9, "University College London")  | strpos(PhDInstitution9, "UCL")
(0 real changes made)
replace top_phd10=1 if strpos(PhDInstitution10, "University College London")  | strpos(PhDInstitution10, "UCL")
(0 real changes made)
replace top_phd11=1 if strpos(PhDInstitution11, "University College London")  | strpos(PhDInstitution11, "UCL")
(0 real changes made)
296
replace top_phd`i'=1 if strpos(PhDInstitution`i', "Northwestern University")
replace top_phd1=1 if strpos(PhDInstitution1, "Northwestern University")
(0 real changes made)
replace top_phd2=1 if strpos(PhDInstitution2, "Northwestern University")
(72 real changes made)
replace top_phd3=1 if strpos(PhDInstitution3, "Northwestern University")
(12 real changes made)
replace top_phd4=1 if strpos(PhDInstitution4, "Northwestern University")
(12 real changes made)
replace top_phd5=1 if strpos(PhDInstitution5, "Northwestern University")
(0 real changes made)
replace top_phd6=1 if strpos(PhDInstitution6, "Northwestern University")
(0 real changes made)
replace top_phd7=1 if strpos(PhDInstitution7, "Northwestern University")
(0 real changes made)
replace top_phd8=1 if strpos(PhDInstitution8, "Northwestern University")
(0 real changes made)
replace top_phd9=1 if strpos(PhDInstitution9, "Northwestern University")
(0 real changes made)
replace top_phd10=1 if strpos(PhDInstitution10, "Northwestern University")
(0 real changes made)
replace top_phd11=1 if strpos(PhDInstitution11, "Northwestern University")
(0 real changes made)
297
replace top_phd`i'=1 if strpos(PhDInstitution`i', "Columbia University")
replace top_phd1=1 if strpos(PhDInstitution1, "Columbia University")
(0 real changes made)
replace top_phd2=1 if strpos(PhDInstitution2, "Columbia University")
(0 real changes made)
replace top_phd3=1 if strpos(PhDInstitution3, "Columbia University")
(0 real changes made)
replace top_phd4=1 if strpos(PhDInstitution4, "Columbia University")
(0 real changes made)
replace top_phd5=1 if strpos(PhDInstitution5, "Columbia University")
(0 real changes made)
replace top_phd6=1 if strpos(PhDInstitution6, "Columbia University")
(0 real changes made)
replace top_phd7=1 if strpos(PhDInstitution7, "Columbia University")
(0 real changes made)
replace top_phd8=1 if strpos(PhDInstitution8, "Columbia University")
(0 real changes made)
replace top_phd9=1 if strpos(PhDInstitution9, "Columbia University")
(0 real changes made)
replace top_phd10=1 if strpos(PhDInstitution10, "Columbia University")
(0 real changes made)
replace top_phd11=1 if strpos(PhDInstitution11, "Columbia University")
(0 real changes made)
298
replace top_phd`i'=1 if strpos(PhDInstitution`i', "University of California-Los Angeles ") | strpos(PhDInstitution`i', "UCLA")
replace top_phd1=1 if strpos(PhDInstitution1, "University of California-Los Angeles ") | strpos(PhDInstitution1, "UCLA")
(0 real changes made)
replace top_phd2=1 if strpos(PhDInstitution2, "University of California-Los Angeles ") | strpos(PhDInstitution2, "UCLA")
(0 real changes made)
replace top_phd3=1 if strpos(PhDInstitution3, "University of California-Los Angeles ") | strpos(PhDInstitution3, "UCLA")
(0 real changes made)
replace top_phd4=1 if strpos(PhDInstitution4, "University of California-Los Angeles ") | strpos(PhDInstitution4, "UCLA")
(0 real changes made)
replace top_phd5=1 if strpos(PhDInstitution5, "University of California-Los Angeles ") | strpos(PhDInstitution5, "UCLA")
(0 real changes made)
replace top_phd6=1 if strpos(PhDInstitution6, "University of California-Los Angeles ") | strpos(PhDInstitution6, "UCLA")
(0 real changes made)
replace top_phd7=1 if strpos(PhDInstitution7, "University of California-Los Angeles ") | strpos(PhDInstitution7, "UCLA")
(0 real changes made)
replace top_phd8=1 if strpos(PhDInstitution8, "University of California-Los Angeles ") | strpos(PhDInstitution8, "UCLA")
(0 real changes made)
replace top_phd9=1 if strpos(PhDInstitution9, "University of California-Los Angeles ") | strpos(PhDInstitution9, "UCLA")
(0 real changes made)
replace top_phd10=1 if strpos(PhDInstitution10, "University of California-Los Angeles ") | strpos(PhDInstitution10, "UCLA")
(0 real changes made)
replace top_phd11=1 if strpos(PhDInstitution11, "University of California-Los Angeles ") | strpos(PhDInstitution11, "UCLA")
(0 real changes made)
299
replace top_phd`i'=1 if strpos(PhDInstitution`i', "London School of Economics") | strpos(PhDInstitution`i', "LSE")
replace top_phd1=1 if strpos(PhDInstitution1, "London School of Economics") | strpos(PhDInstitution1, "LSE")
(715 real changes made)
replace top_phd2=1 if strpos(PhDInstitution2, "London School of Economics") | strpos(PhDInstitution2, "LSE")
(147 real changes made)
replace top_phd3=1 if strpos(PhDInstitution3, "London School of Economics") | strpos(PhDInstitution3, "LSE")
(289 real changes made)
replace top_phd4=1 if strpos(PhDInstitution4, "London School of Economics") | strpos(PhDInstitution4, "LSE")
(56 real changes made)
replace top_phd5=1 if strpos(PhDInstitution5, "London School of Economics") | strpos(PhDInstitution5, "LSE")
(0 real changes made)
replace top_phd6=1 if strpos(PhDInstitution6, "London School of Economics") | strpos(PhDInstitution6, "LSE")
(0 real changes made)
replace top_phd7=1 if strpos(PhDInstitution7, "London School of Economics") | strpos(PhDInstitution7, "LSE")
(0 real changes made)
replace top_phd8=1 if strpos(PhDInstitution8, "London School of Economics") | strpos(PhDInstitution8, "LSE")
(0 real changes made)
replace top_phd9=1 if strpos(PhDInstitution9, "London School of Economics") | strpos(PhDInstitution9, "LSE")
(0 real changes made)
replace top_phd10=1 if strpos(PhDInstitution10, "London School of Economics") | strpos(PhDInstitution10, "LSE")
(0 real changes made)
replace top_phd11=1 if strpos(PhDInstitution11, "London School of Economics") | strpos(PhDInstitution11, "LSE")
(0 real changes made)
300
replace top_phd`i'=1 if strpos(PhDInstitution`i', "University of Wisconsin-Madison")
replace top_phd1=1 if strpos(PhDInstitution1, "University of Wisconsin-Madison")
(97 real changes made)
replace top_phd2=1 if strpos(PhDInstitution2, "University of Wisconsin-Madison")
(60 real changes made)
replace top_phd3=1 if strpos(PhDInstitution3, "University of Wisconsin-Madison")
(5 real changes made)
replace top_phd4=1 if strpos(PhDInstitution4, "University of Wisconsin-Madison")
(0 real changes made)
replace top_phd5=1 if strpos(PhDInstitution5, "University of Wisconsin-Madison")
(0 real changes made)
replace top_phd6=1 if strpos(PhDInstitution6, "University of Wisconsin-Madison")
(0 real changes made)
replace top_phd7=1 if strpos(PhDInstitution7, "University of Wisconsin-Madison")
(0 real changes made)
replace top_phd8=1 if strpos(PhDInstitution8, "University of Wisconsin-Madison")
(0 real changes made)
replace top_phd9=1 if strpos(PhDInstitution9, "University of Wisconsin-Madison")
(0 real changes made)
replace top_phd10=1 if strpos(PhDInstitution10, "University of Wisconsin-Madison")
(0 real changes made)
replace top_phd11=1 if strpos(PhDInstitution11, "University of Wisconsin-Madison")
(0 real changes made)
301
replace top_phd`i'=1 if strpos(PhDInstitution`i', "University of Michigan")
replace top_phd1=1 if strpos(PhDInstitution1, "University of Michigan")
(227 real changes made)
replace top_phd2=1 if strpos(PhDInstitution2, "University of Michigan")
(201 real changes made)
replace top_phd3=1 if strpos(PhDInstitution3, "University of Michigan")
(57 real changes made)
replace top_phd4=1 if strpos(PhDInstitution4, "University of Michigan")
(6 real changes made)
replace top_phd5=1 if strpos(PhDInstitution5, "University of Michigan")
(0 real changes made)
replace top_phd6=1 if strpos(PhDInstitution6, "University of Michigan")
(0 real changes made)
replace top_phd7=1 if strpos(PhDInstitution7, "University of Michigan")
(0 real changes made)
replace top_phd8=1 if strpos(PhDInstitution8, "University of Michigan")
(0 real changes made)
replace top_phd9=1 if strpos(PhDInstitution9, "University of Michigan")
(0 real changes made)
replace top_phd10=1 if strpos(PhDInstitution10, "University of Michigan")
(0 real changes made)
replace top_phd11=1 if strpos(PhDInstitution11, "University of Michigan")
(0 real changes made)
302
}
303
304
capture drop share_top_phd

. capture drop share_top_phd

. 
305
egen share_top_phd = rowmean(top_phd`i'*)
egen share_top_phd = rowmean(top_phd*)

. egen share_top_phd = rowmean(top_phd`i'*)

. 
306
307
capture drop min_table

. capture drop min_table

. 
308
capture drop main_table

. capture drop main_table

. 
309
egen min_table = min(table), by(journal_article_cluster)

. egen min_table = min(table), by(journal_article_cluster)

. 
310
gen main_table = .

. gen main_table = .
(21,740 missing values generated)

. 
311
replace main_table = 1 if min_table == table

. replace main_table = 1 if min_table == table
(7,049 real changes made)

. 
312
313
gen rct_registered=0 if RCT!=.

. gen rct_registered=0 if RCT!=.

. 
314
replace rct_registered=1 if rct_pre_registered==1

. replace rct_registered=1 if rct_pre_registered==1
(280 real changes made)

. 
315
destring registered, replace

. destring registered, replace
registered: all characters numeric; replaced as byte
(17574 missing values generated)

. 
316
replace rct_registered=1 if registered==1

. replace rct_registered=1 if registered==1
(1,012 real changes made)

. 
317
318
gen DID_graph=DID

. gen DID_graph=DID

. 
319
replace DID_graph=0 if graph_did==0

. replace DID_graph=0 if graph_did==0
(914 real changes made)

. 
320
321
gen ambiguous=0 if sign_5pct!=.

. gen ambiguous=0 if sign_5pct!=.

. 
322
replace ambiguous=1 if journal_name=="Journal of Urban Economics" & table==7 & article==7 & year==2018
replace ambiguous=1 if journal_name=="Journal of Urban Economics" & table==7 & article==7 & year==2018

. replace ambiguous=1 if journal_name=="Journal of Urban Eco
> nomics" & table==7 & article==7 & year==2018
(8 real changes made)

. 
323
replace ambiguous=1 if Not_sure_shouldbe_included=="1"

. replace ambiguous=1 if Not_sure_shouldbe_included=="1"
(160 real changes made)

. 
324
replace ambiguous=1 if ambig==1

. replace ambiguous=1 if ambig==1
(128 real changes made)

. 
325
replace ambiguous=1 if abelcomments=="This is an RCT, I  would code differently"
replace ambiguous=1 if abelcomments=="This is an RCT, I  would code differently"

. replace ambiguous=1 if abelcomments=="This is an RCT, I  w
> ould code differently"
(33 real changes made)

. 
326
replace ambiguous=1 if abelcomments=="not sure which tables to select here"
replace ambiguous=1 if abelcomments=="not sure which tables to select here"

. replace ambiguous=1 if abelcomments=="not sure which table
> s to select here"
(6 real changes made)

. 
327
replace ambiguous=1 if drop==1

. replace ambiguous=1 if drop==1
(80 real changes made)

. 
328
329
* keep only variables that are needed for further analyses
330
keep t t_orig t_new t_new_string mu_orig mu_new mu_new_string sd_new sd_new_string sd_orig RCT DID IV RDD year unique_j experience_avg experience_avg_sq share_top_authors share_top_phd ireport authored_solo share_female_authors editor_present journal_article_cluster FINANCE MACRO_GROWTH GEN_INT EXP DEV LABOR PUB URB sign_5pct aw sign_10pct sign_1pct fstat journal title table method report article journal_name top5
keep t t_orig t_new t_new_string mu_orig mu_new mu_new_string sd_new sd_new_string sd_orig RCT DID IV RDD year unique_j experience_avg experience_avg_sq share_top_authors share_top_phd ireport authored_solo share_female_authors editor_present journal_article_cluster FINANCE MACRO_GROWTH GEN_INT EXP DEV LABOR PUB URB sign_5pct aw sign_10pct sign_1pct fstat journal title table method report article journal_name top5

. keep t t_orig t_new t_new_string mu_orig mu_new mu_new_str
> ing sd_new sd_new_string sd_orig RCT DID IV RDD year unique_j experience_avg 
> experience_avg_sq share_top_authors share_top_phd ireport authored_solo share
> _female_authors editor_present journal_article_cluster FINANCE MACRO_GROWTH G
> EN_INT EXP DEV LABOR PUB URB sign_5pct aw sign_10pct sign_1pct fstat journal 
> title table method report article journal_name top5

. 
331
332
* label variables that have no label
333
label variable year "Year"

. label variable year "Year"

. 
334
label variable top5 "Published in Top 5 journal"

. label variable top5 "Published in Top 5 journal"

. 
335
label variable sign_5pct "significant at 5% level"

. label variable sign_5pct "significant at 5% level"

. 
336
label variable sign_1pct "significant at 1% level"

. label variable sign_1pct "significant at 1% level"

. 
337
label variable sign_10pct "significant at 10% level"

. label variable sign_10pct "significant at 10% level"

. 
338
label variable share_top_authors "share of authors share of authors affiliated with top institutions"
label variable share_top_authors "share of authors share of authors affiliated with top institutions"

. label variable share_top_authors "share of authors share o
> f authors affiliated with top institutions"

. 
339
label variable share_top_phd "share of authors who completed a PhD at a top institution"
label variable share_top_phd "share of authors who completed a PhD at a top institution"

. label variable share_top_phd "share of authors who complet
> ed a PhD at a top institution"

. 
340
label variable share_female_authors "share of female authors"
label variable share_female_authors "share of female authors"

. label variable share_female_authors "share of female autho
> rs"

. 
341
label variable journal "Journal"

. label variable journal "Journal"

. 
342
label variable journal_article_cluster "Article ID"

. label variable journal_article_cluster "Article ID"

. 
343
label variable experience_avg "Average experience since authors' phds in years"
label variable experience_avg "Average experience since authors' phds in years"

. label variable experience_avg "Average experience since au
> thors' phds in years"

. 
344
label variable experience_avg_sq "Average experience since authors' phds in years (squared)"
label variable experience_avg_sq "Average experience since authors' phds in years (squared)"

. label variable experience_avg_sq "Average experience since
>  authors' phds in years (squared)"

. 
345
label variable editor_present "Editor of an economic journal among authors"
label variable editor_present "Editor of an economic journal among authors"

. label variable editor_present "Editor of an economic journ
> al among authors"

. 
346
label variable aw "Weights mapping the inverse number of tests per article"
label variable aw "Weights mapping the inverse number of tests per article"

. label variable aw "Weights mapping the inverse number of t
> ests per article"

. 
347
label variable authored_solo "Solo authorship"

. label variable authored_solo "Solo authorship"

. 
348
label variable DEV "Field: Development Economics"

. label variable DEV "Field: Development Economics"

. 
349
label variable URB "Field: Urban Economics"

. label variable URB "Field: Urban Economics"

. 
350
label variable FINANCE "Field: Finance"

. label variable FINANCE "Field: Finance"

. 
351
label variable LABOR "Field: Labor Economics"

. label variable LABOR "Field: Labor Economics"

. 
352
label variable PUB "Field: Public Economics"

. label variable PUB "Field: Public Economics"

. 
353
label variable MACRO_GROWTH "Field: Macroeconomics "

. label variable MACRO_GROWTH "Field: Macroeconomics "

. 
354
label variable GEN_INT "Field: General Interest"

. label variable GEN_INT "Field: General Interest"

. 
355
label variable EXP "Field: Experimental Economics"

. label variable EXP "Field: Experimental Economics"

. 
356
label variable DID "Method: Difference-in-Differences"

. label variable DID "Method: Difference-in-Differences"

. 
357
label variable IV "Method: Instrumental Variables"

. label variable IV "Method: Instrumental Variables"

. 
358
label variable RDD "Method: Regression Discontinuity Design"
label variable RDD "Method: Regression Discontinuity Design"

. label variable RDD "Method: Regression Discontinuity Desig
> n"

. 
359
label variable RCT "Method: Randomized Control Trial"

. label variable RCT "Method: Randomized Control Trial"

. 
360
label variable report "Which statistics reported"

. label variable report "Which statistics reported"

. 
361
label variable ireport "Which statistics reported"

. label variable ireport "Which statistics reported"

. 
362
363
saveold mm_data_ready, replace

. saveold mm_data_ready, replace
(saving in Stata 13 format)
(FYI, saveold has options version(12) and version(11) that write files in
      older Stata formats)
file mm_data_ready.dta saved

.