---------------------------------------------------------------------------------------------------------------------------------------
      name:  <unnamed>
       log:  /home/damian/investigacion/2013/genderMMR/replicationJEEA//log/IndiaEvent.txt
  log type:  text
 opened on:  14 Oct 2022, 15:20:06

. 
. 
. *--------------------------------------------------------------------------------
. *--- (2) Data import and generation
. *--------------------------------------------------------------------------------    
. insheet using "$DAT/IndiaStateMMRQuotas.csv", clear
(8 vars, 135 obs)

. 
. gen lnMMR  = log(mmr)

. egen sID   = group(state)

. gen quotaRound     = 2 if quotayr>1986&quotayr<=1997
(27 missing values generated)

. replace quotaRound = 3 if quotayr ==2001|quotayr==2002
(18 real changes made)

. replace quotaRound = 5 if quotayr ==2006
(9 real changes made)

. gen timeToQuota = round - quotaRound

. gen Quota = timeToQuota>=0

. 
. 
. *--------------------------------------------------------------------------------
. *--- (3) Two-way FE model
. *--------------------------------------------------------------------------------    
. eststo: reg lnMMR i.sID i.year quota [aw=censuspop], cluster(sID)
(sum of wgt is 9,011,096,327)

Linear regression                               Number of obs     =        135
                                                F(8, 14)          =          .
                                                Prob > F          =          .
                                                R-squared         =     0.9499
                                                Root MSE          =     .16036

                                   (Std. Err. adjusted for 15 clusters in sID)
------------------------------------------------------------------------------
             |               Robust
       lnMMR |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         sID |
          2  |   1.015823   .0078647   129.16   0.000     .9989553    1.032691
          3  |   .7184266   .0081843    87.78   0.000     .7008729    .7359803
          4  |  -.0783999   .0013329   -58.82   0.000    -.0812586   -.0755412
          5  |   .0963416   .0019796    48.67   0.000     .0920957    .1005875
          6  |   .2612274   .0006294   415.02   0.000     .2598774    .2625774
          7  |  -.4537161   .0009731  -466.26   0.000    -.4558032   -.4516289
          8  |   .7095697   .0014555   487.49   0.000     .7064479    .7126916
          9  |  -.2050918   .0011201  -183.11   0.000     -.207494   -.2026895
         10  |   .7233762   .0003892  1858.66   0.000     .7225415     .724211
         11  |   .1493163   .0007266   205.51   0.000     .1477579    .1508746
         12  |   .8600678   .0019592   438.98   0.000     .8558657      .86427
         13  |  -.2446939   .0001789 -1368.02   0.000    -.2450775   -.2443103
         14  |   .9553505   .0253225    37.73   0.000     .9010391    1.009662
         15  |   .1418951   .0005367   264.40   0.000     .1407441    .1430462
             |
        year |
       1998  |   -.543821   .0939169    -5.79   0.000    -.7452527   -.3423893
       2001  |  -.5128084   .0958294    -5.35   0.000    -.7183421   -.3072748
       2003  |  -.6153634   .0950952    -6.47   0.000    -.8193223   -.4114046
       2006  |  -.7401208   .1141542    -6.48   0.000    -.9849572   -.4952843
       2009  |  -.9023753   .1093052    -8.26   0.000    -1.136812   -.6679389
       2012  |   -1.07901   .1118167    -9.65   0.000    -1.318833   -.8391871
       2013  |  -1.164278   .1215103    -9.58   0.000    -1.424892   -.9036647
       2016  |  -1.387203   .1165459   -11.90   0.000    -1.637169   -1.137237
             |
       quota |   -.141973    .079886    -1.78   0.097    -.3133115    .0293655
       _cons |   5.936967   .0722714    82.15   0.000     5.781961    6.091974
------------------------------------------------------------------------------
(est1 stored)

. eststo: reg lnMMR i.sID i.year quota, cluster(sID)

Linear regression                               Number of obs     =        135
                                                F(8, 14)          =          .
                                                Prob > F          =          .
                                                R-squared         =     0.9237
                                                Root MSE          =     .19757

                                   (Std. Err. adjusted for 15 clusters in sID)
------------------------------------------------------------------------------
             |               Robust
       lnMMR |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         sID |
          2  |   1.001083   .0128216    78.08   0.000     .9735836    1.028583
          3  |   .7146309   .0128216    55.74   0.000     .6871312    .7421305
          4  |  -.1195068   4.01e-15 -3.0e+13   0.000    -.1195068   -.1195068
          5  |   .0761179   3.96e-15  1.9e+13   0.000     .0761179    .0761179
          6  |   .2551845   3.97e-15  6.4e+13   0.000     .2551845    .2551845
          7  |  -.4539291   3.97e-15 -1.1e+14   0.000    -.4539291   -.4539291
          8  |   .6972192   3.93e-15  1.8e+14   0.000     .6972192    .6972192
          9  |  -.1943069   4.03e-15 -4.8e+13   0.000    -.1943069   -.1943069
         10  |   .7166069   3.93e-15  1.8e+14   0.000     .7166069    .7166069
         11  |   .1265921   3.95e-15  3.2e+13   0.000     .1265921    .1265921
         12  |   .8503993   3.93e-15  2.2e+14   0.000     .8503993    .8503993
         13  |  -.2482478   3.97e-15 -6.3e+13   0.000    -.2482478   -.2482478
         14  |   .9301765   .0384649    24.18   0.000     .8476774    1.012676
         15  |   .1487416   3.93e-15  3.8e+13   0.000     .1487416    .1487416
             |
        year |
       1998  |  -.5169049   .1085727    -4.76   0.000    -.7497702   -.2840396
       2001  |  -.4397168   .1224111    -3.59   0.003    -.7022626    -.177171
       2003  |  -.5428505   .1204276    -4.51   0.000    -.8011421   -.2845589
       2006  |  -.6449232   .1389855    -4.64   0.000    -.9430175   -.3468289
       2009  |  -.8022585   .1385061    -5.79   0.000    -1.099325   -.5051926
       2012  |  -.9657321   .1424222    -6.78   0.000    -1.271197    -.660267
       2013  |  -1.057335   .1455965    -7.26   0.000    -1.369608   -.7450614
       2016  |  -1.268353   .1454859    -8.72   0.000    -1.580389   -.9563165
             |
       quota |  -.2042534   .1153948    -1.77   0.098    -.4517506    .0432439
       _cons |   5.917712   .0813266    72.76   0.000     5.743284     6.09214
------------------------------------------------------------------------------
(est2 stored)

. eststo: reg mmr   i.sID i.year quota [aw=censuspop], cluster(sID)
(sum of wgt is 9,011,096,327)

Linear regression                               Number of obs     =        135
                                                F(8, 14)          =          .
                                                Prob > F          =          .
                                                R-squared         =     0.9078
                                                Root MSE          =     60.526

                                   (Std. Err. adjusted for 15 clusters in sID)
------------------------------------------------------------------------------
             |               Robust
         mmr |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         sID |
          2  |   276.5299    1.96377   140.82   0.000      272.318    280.7417
          3  |   168.1258   2.375687    70.77   0.000     163.0305    173.2211
          4  |  -9.573393   .7269794   -13.17   0.000    -11.13261   -8.014177
          5  |   15.82694    1.07013    14.79   0.000     13.53174    18.12214
          6  |     42.975   .3497217   122.88   0.000     42.22492    43.72508
          7  |  -62.83708   .5450716  -115.28   0.000    -64.00614   -61.66802
          8  |   152.8561   .8015135   190.71   0.000      151.137    154.5752
          9  |  -21.62921   .5904416   -36.63   0.000    -22.89558   -20.36284
         10  |   171.9029   .2160021   795.84   0.000     171.4396    172.3662
         11  |   10.87662   .3773268    28.83   0.000     10.06734    11.68591
         12  |   207.2214     1.0538   196.64   0.000     204.9612    209.4816
         13  |  -34.44482   .1006867  -342.10   0.000    -34.66077   -34.22887
         14  |   240.9915   6.033397    39.94   0.000     228.0511    253.9318
         15  |   32.38108   .2834097   114.26   0.000     31.77323    32.98894
             |
        year |
       1998  |  -171.3545   44.39437    -3.86   0.002    -266.5709   -76.13802
       2001  |  -182.0556   56.52171    -3.22   0.006    -303.2826   -60.82863
       2003  |  -207.8225   55.19586    -3.77   0.002    -326.2058    -89.4391
       2006  |  -230.0787   50.03387    -4.60   0.000    -337.3907   -122.7667
       2009  |  -272.6587    57.6941    -4.73   0.000    -396.4003   -148.9172
       2012  |  -309.8886   64.31006    -4.82   0.000      -447.82   -171.9573
       2013  |  -321.2857   63.45344    -5.06   0.000    -457.3798   -185.1916
       2016  |  -359.2516   73.08769    -4.92   0.000    -516.0091   -202.4941
             |
       quota |  -107.8389   18.04183    -5.98   0.000    -146.5347   -69.14297
       _cons |   501.4741   46.84126    10.71   0.000     401.0096    601.9387
------------------------------------------------------------------------------
(est3 stored)

. eststo: reg mmr   i.sID i.year quota, cluster(sID)

Linear regression                               Number of obs     =        135
                                                F(8, 14)          =          .
                                                Prob > F          =          .
                                                R-squared         =     0.8758
                                                Root MSE          =     70.033

                                   (Std. Err. adjusted for 15 clusters in sID)
------------------------------------------------------------------------------
             |               Robust
         mmr |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         sID |
          2  |   287.1004   2.549283   112.62   0.000     281.6327    292.5681
          3  |   178.3226   2.549283    69.95   0.000      172.855    183.7903
          4  |        -16   3.85e-13 -4.2e+13   0.000          -16         -16
          5  |   12.33333   3.84e-13  3.2e+13   0.000     12.33333    12.33333
          6  |   42.66667   3.81e-13  1.1e+14   0.000     42.66667    42.66667
          7  |  -62.77778   4.02e-13 -1.6e+14   0.000    -62.77778   -62.77778
          8  |   154.6667   3.84e-13  4.0e+14   0.000     154.6667    154.6667
          9  |  -21.88889   3.87e-13 -5.6e+13   0.000    -21.88889   -21.88889
         10  |   177.7778   3.89e-13  4.6e+14   0.000     177.7778    177.7778
         11  |          6   3.86e-13  1.6e+13   0.000            6           6
         12  |   212.7778   3.82e-13  5.6e+14   0.000     212.7778    212.7778
         13  |  -35.88889   3.82e-13 -9.4e+13   0.000    -35.88889   -35.88889
         14  |   252.6346   7.647848    33.03   0.000     236.2316    269.0376
         15  |   35.88889   3.84e-13  9.3e+13   0.000     35.88889    35.88889
             |
        year |
       1998  |  -159.3229   48.50282    -3.28   0.005    -263.3511   -55.29474
       2001  |  -161.3768   53.39378    -3.02   0.009     -275.895   -46.85849
       2003  |  -183.4434   48.27561    -3.80   0.002    -286.9843   -79.90254
       2006  |  -205.9037   49.85708    -4.13   0.001    -312.8365   -98.97087
       2009  |  -244.1037   55.30487    -4.41   0.001    -362.7208   -125.4865
       2012  |  -275.5037   59.42518    -4.64   0.000     -402.958   -148.0493
       2013  |  -288.1703   59.89202    -4.81   0.000    -416.6259   -159.7147
       2016  |   -320.237   64.72741    -4.95   0.000    -459.0635   -181.4105
             |
       quota |  -105.0963   22.94354    -4.58   0.000    -154.3053   -55.88732
       _cons |   472.0925   44.30445    10.66   0.000     377.0689    567.1161
------------------------------------------------------------------------------
(est4 stored)

. 
. esttab est1 est2 est3 est4, keep(quota)

----------------------------------------------------------------------------
                      (1)             (2)             (3)             (4)   
                    lnMMR           lnMMR             mmr             mmr   
----------------------------------------------------------------------------
quota              -0.142          -0.204          -107.8***       -105.1***
                  (-1.78)         (-1.77)         (-5.98)         (-4.58)   
----------------------------------------------------------------------------
N                     135             135             135             135   
----------------------------------------------------------------------------
t statistics in parentheses
* p<0.05, ** p<0.01, *** p<0.001

. lab var quota "Reserved Seats for Women"

. #delimit ;
delimiter now ;
. esttab est1 est2 est3 est4 using "$OUT/DD_India_baseline.tex",
> b(%-9.3f) se(%-9.3f) noobs keep(quota) nonotes nogaps
> mlabels(, none) nonumbers style(tex) fragment replace noline
> label starlevel ("*" 0.10 "**" 0.05 "***" 0.01)
> stats(N r2, fmt(%14.0gc %5.2f)
>       label("\\ Observations" "R-Squared"));
(note: file /home/damian/investigacion/2013/genderMMR/replicationJEEA//results/appendix/India/DD_India_baseline.tex not found)
(output written to ~/investigacion/2013/genderMMR/replicationJEEA//results/appendix/India/DD_India_baseline.tex)

. #delimit cr
delimiter now cr
. estimates clear

. 
. 
. 
. *--------------------------------------------------------------------------------
. *--- (4) Event studies
. *--------------------------------------------------------------------------------    
. xtset sID round
       panel variable:  sID (strongly balanced)
        time variable:  round, 1 to 9
                delta:  1 unit

. 
. graph set eps fontface "Times New Roman"

. set seed 2727

. set scheme s1mono

. 
. #delimit ;
delimiter now ;
. eventdd lnMMR i.sID i.year, ci(rarea, color(gs12%70))
> timevar(timeToQuota) lags(5) leads(3) accum wboot level(95)
> robust graph_op(ytitle("ln(MMR)") xlabel(-3(1)5)
>                 xtitle("Periods to State Gender Quota"))
> wboot_op(seed(12012017)) coef_op(msymbol(Oh) mcolor(gs2))
> endpoints_op(msymbol(Oh) mcolor(gs2));

Linear regression                               Number of obs     =        135
                                                F(30, 104)        =     253.40
                                                Prob > F          =     0.0000
                                                R-squared         =     0.9250
                                                Root MSE          =     .20238

------------------------------------------------------------------------------
             |               Robust
       lnMMR |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         sID |
          2  |    .987663   .0532603    18.54   0.000     .8820458     1.09328
          3  |   .7012106   .0530073    13.23   0.000     .5960952     .806326
          4  |  -.1195068   .1706052    -0.70   0.485    -.4578234    .2188098
          5  |   .0761179   .0766586     0.99   0.323     -.075899    .2281349
          6  |   .2551845   .0385106     6.63   0.000     .1788165    .3315524
          7  |  -.4539291   .0614006    -7.39   0.000    -.5756887   -.3321695
          8  |   .6972192   .0663009    10.52   0.000      .565742    .8286964
          9  |  -.1943069   .0715466    -2.72   0.008    -.3361864   -.0524273
         10  |   .7166069   .0407919    17.57   0.000     .6357149    .7974988
         11  |   .1265921   .1186187     1.07   0.288    -.1086332    .3618174
         12  |   .8503993   .0613017    13.87   0.000     .7288358    .9719628
         13  |  -.2482478   .0522814    -4.75   0.000    -.3519238   -.1445718
         14  |   .8890925    .108806     8.17   0.000     .6733261    1.104859
         15  |   .1487416   .0797404     1.87   0.065    -.0093866    .3068698
             |
        year |
       1998  |  -.4720017   .0947284    -4.98   0.000    -.6598517   -.2841518
       2001  |  -.4904675   .1264119    -3.88   0.000     -.741147    -.239788
       2003  |  -.5478742    .134956    -4.06   0.000    -.8154971   -.2802514
       2006  |  -.5862677   .1681947    -3.49   0.001    -.9198041   -.2527313
       2009  |  -.7344577   .1873243    -3.92   0.000    -1.105929   -.3629866
       2012  |  -.8874979   .2208382    -4.02   0.000    -1.325428   -.4495675
       2013  |  -.9742405   .2434673    -4.00   0.000    -1.457045   -.4914357
       2016  |  -1.184487   .2491248    -4.75   0.000     -1.67851   -.6904629
             |
       lead3 |    .049751   .1141795     0.44   0.664    -.1766712    .2761732
       lead2 |   .0460463   .0861669     0.53   0.594    -.1248258    .2169184
        lag0 |  -.2527079   .1195257    -2.11   0.037    -.4897319   -.0156839
        lag1 |  -.1247561   .1233533    -1.01   0.314    -.3693703     .119858
        lag2 |  -.1994029   .1324673    -1.51   0.135    -.4620906    .0632848
        lag3 |   -.262523   .1672527    -1.57   0.120    -.5941913    .0691453
        lag4 |  -.2740973   .1884527    -1.45   0.149    -.6478061    .0996115
        lag5 |  -.2789894   .2331596    -1.20   0.234    -.7413536    .1833749
       _cons |   5.912784   .0917635    64.44   0.000     5.730814    6.094755
------------------------------------------------------------------------------

. translate @Graph "$OUT/eventIndia.pdf", name(Graph) replace;
(file /home/damian/investigacion/2013/genderMMR/replicationJEEA//results/appendix/India/eventIndia.pdf written in PDF format)

. eventdd lnMMR i.sID i.year [aw=censuspop], ci(rarea, color(gs12%70))
> timevar(timeToQuota) leads(3) lags(5) accum wboot level(95) robust
> graph_op(ytitle("ln(MMR)") xtitle("Periods to State Gender Quota")
>          xlabel(-3(1)5)) wboot_op(seed(120117))
> coef_op(msymbol(Oh) mcolor(gs2)) endpoints_op(msymbol(Oh) mcolor(gs2));
(sum of wgt is 9,011,096,327)

Linear regression                               Number of obs     =        135
                                                F(30, 104)        =     216.35
                                                Prob > F          =     0.0000
                                                R-squared         =     0.9509
                                                Root MSE          =     .16399

------------------------------------------------------------------------------
             |               Robust
       lnMMR |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         sID |
          2  |   .9987504   .0546127    18.29   0.000     .8904514    1.107049
          3  |   .7016461   .0415701    16.88   0.000      .619211    .7840811
          4  |  -.0784604   .1480855    -0.53   0.597    -.3721196    .2151987
          5  |   .0962579   .0737569     1.31   0.195    -.0500048    .2425206
          6  |   .2611947   .0330137     7.91   0.000     .1957273     .326662
          7  |  -.4536625    .049314    -9.20   0.000    -.5514539    -.355871
          8  |   .7094988    .055945    12.68   0.000     .5985576    .8204399
          9  |  -.2051298   .0579384    -3.54   0.001    -.3200237   -.0902358
         10  |   .7233562   .0353768    20.45   0.000     .6532027    .7935096
         11  |    .149295   .1102507     1.35   0.179    -.0693361    .3679262
         12  |   .8599883   .0497913    17.27   0.000     .7612503    .9587263
         13  |  -.2447237   .0431409    -5.67   0.000    -.3302737   -.1591737
         14  |    .891811   .0845074    10.55   0.000     .7242297    1.059392
         15  |   .1418766   .0638282     2.22   0.028      .015303    .2684503
             |
        year |
       1998  |  -.4961808   .0837209    -5.93   0.000    -.6622025   -.3301592
       2001  |  -.4886331   .0926348    -5.27   0.000    -.6723315   -.3049348
       2003  |   -.557357   .1066682    -5.23   0.000     -.768884     -.34583
       2006  |  -.6278872   .1377012    -4.56   0.000    -.9009537   -.3548206
       2009  |  -.7702967   .1442364    -5.34   0.000    -1.056323   -.4842705
       2012  |   -.916207   .1721593    -5.32   0.000    -1.257605   -.5748086
       2013  |  -.9900041    .194658    -5.09   0.000    -1.376018   -.6039901
       2016  |  -1.206547    .194877    -6.19   0.000    -1.592995   -.8200986
             |
       lead3 |   .0228259    .102649     0.22   0.824    -.1807309    .2263828
       lead2 |  -.0212498   .0802722    -0.26   0.792    -.1804326    .1379329
        lag0 |  -.2146804   .0997768    -2.15   0.034    -.4125415   -.0168193
        lag1 |  -.1547353   .0896583    -1.73   0.087    -.3325311    .0230605
        lag2 |  -.2220279   .1020069    -2.18   0.032    -.4243113   -.0197445
        lag3 |  -.2687769   .1360206    -1.98   0.051    -.5385108     .000957
        lag4 |  -.3039339   .1441866    -2.11   0.037    -.5898613   -.0180065
        lag5 |  -.3244622   .1825806    -1.78   0.078    -.6865264     .037602
       _cons |    5.94908   .0853852    69.67   0.000     5.779758    6.118402
------------------------------------------------------------------------------

. translate @Graph "$OUT/eventIndiaWeighted.pdf", name(Graph) replace;
(file /home/damian/investigacion/2013/genderMMR/replicationJEEA//results/appendix/India/eventIndiaWeighted.pdf written in PDF format)

. *trends
> eventdd lnMMR i.sID i.year i.sID#c.round, ci(rarea, color(gs12%70))
> timevar(timeToQuota) leads(3) lags(5) accum level(95) robust
> graph_op(ytitle("ln(MMR)") xtitle("Periods to State Gender Quota")
>          xlabel(-3(1)5)) coef_op(msymbol(Oh) mcolor(gs2))
> endpoints_op(msymbol(Oh) mcolor(gs2)) wboot_op(seed(130319));
. translate @Graph "$OUT/eventIndiaTrends.pdf", name(Graph) replace;
(file /home/damian/investigacion/2013/genderMMR/replicationJEEA//results/appendix/India/eventIndiaTrends.pdf written in PDF format)

. eventdd lnMMR i.sID i.year i.sID#c.round [aw=censuspop], accum 
> ci(rarea, color(gs12%70)) timevar(timeToQuota) lags(5) leads(3) 
> graph_op(ytitle("ln(MMR)") xtitle("Periods to State Gender Quota")
>          xlabel(-3(1)5)) coef_op(msymbol(Oh) mcolor(gs2))
> endpoints_op(msymbol(Oh) mcolor(gs2)) wboot_op(seed(120117))
> level(95) robust;
(sum of wgt is 9,011,096,327)
note: 15.sID#c.round omitted because of collinearity

Linear regression                               Number of obs     =        135
                                                F(44, 90)         =    1424.81
                                                Prob > F          =     0.0000
                                                R-squared         =     0.9663
                                                Root MSE          =     .14615

------------------------------------------------------------------------------
             |               Robust
       lnMMR |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         sID |
          2  |   .6920012   .1399863     4.94   0.000      .413894    .9701084
          3  |    .585842   .1212579     4.83   0.000     .3449419     .826742
          4  |  -.6323043   .4874787    -1.30   0.198    -1.600766    .3361573
          5  |  -.2531837   .2124053    -1.19   0.236    -.6751639    .1687964
          6  |   .1037185   .0709738     1.46   0.147    -.0372834    .2447204
          7  |   -.407633   .1030241    -3.96   0.000    -.6123083   -.2029578
          8  |     .46666   .1971445     2.37   0.020     .0749981    .8583219
          9  |   -.081448   .0966709    -0.84   0.402    -.2735015    .1106056
         10  |    .564576   .0773733     7.30   0.000     .4108604    .7182916
         11  |  -.3986421   .3069262    -1.30   0.197    -1.008405    .2111202
         12  |   .6756493   .1810575     3.73   0.000      .315947    1.035352
         13  |  -.3212749   .1204125    -2.67   0.009    -.5604952   -.0820545
         14  |   .4865547   .3095487     1.57   0.120    -.1284178    1.101527
         15  |   .1673217   .1530666     1.09   0.277    -.1367719    .4714152
             |
        year |
       1998  |  -.4936452   .0403034   -12.25   0.000    -.5737149   -.4135754
       2001  |  -.4479124   .1274887    -3.51   0.001    -.7011909   -.1946339
       2003  |  -.5132736   .1710716    -3.00   0.003    -.8531372     -.17341
       2006  |  -.5923612   .2247808    -2.64   0.010    -1.038928   -.1457949
       2009  |  -.7455148   .2598391    -2.87   0.005     -1.26173   -.2292992
       2012  |  -.9306531   .2907332    -3.20   0.002    -1.508245   -.3530608
       2013  |  -1.038196   .3090191    -3.36   0.001    -1.652116   -.4242752
       2016  |  -1.287131   .3283501    -3.92   0.000    -1.939456   -.6348064
             |
 sID#c.round |
          1  |   .0046546   .0241922     0.19   0.848    -.0434074    .0527166
          2  |   .0591265    .027955     2.12   0.037     .0035891     .114664
          3  |   .0232818   .0261047     0.89   0.375    -.0285798    .0751433
          4  |   .1091019   .0714439     1.53   0.130    -.0328338    .2510377
          5  |   .0703052   .0376223     1.87   0.065    -.0044381    .1450485
          6  |   .0348003   .0244529     1.42   0.158    -.0137795    .0833802
          7  |  -.0047551   .0265123    -0.18   0.858    -.0574264    .0479162
          8  |   .0506727   .0360773     1.40   0.164    -.0210011    .1223465
          9  |   -.018289    .027164    -0.67   0.502     -.072255     .035677
         10  |   .0350814   .0248467     1.41   0.161     -.014281    .0844437
         11  |    .108946   .0492445     2.21   0.029     .0111132    .2067788
         12  |   .0396387    .034187     1.16   0.249    -.0282797     .107557
         13  |   .0193886   .0283243     0.68   0.495    -.0368825    .0756598
         14  |   .0640077   .0395599     1.62   0.109    -.0145849    .1426003
         15  |          0  (omitted)
             |
       lead3 |   .2359593    .227796     1.04   0.303    -.2165973    .6885159
       lead2 |   .0379755   .0762063     0.50   0.619    -.1134215    .1893726
        lag0 |  -.2560626   .1076488    -2.38   0.019    -.4699258   -.0421994
        lag1 |  -.2532376   .1542315    -1.64   0.104    -.5596455    .0531703
        lag2 |  -.3492443   .1952481    -1.79   0.077    -.7371387    .0386501
        lag3 |  -.4176899   .2399793    -1.74   0.085    -.8944506    .0590708
        lag4 |    -.46867    .267027    -1.76   0.083    -.9991658    .0618257
        lag5 |  -.4725623   .2881769    -1.64   0.105    -1.045076    .0999514
       _cons |   6.043924   .0828725    72.93   0.000     5.879283    6.208565
------------------------------------------------------------------------------

. translate @Graph "$OUT/eventIndiaWeightedTrends.pdf", name(Graph)  replace;
(file /home/damian/investigacion/2013/genderMMR/replicationJEEA//results/appendix/India/eventIndiaWeightedTrends.pdf written in PDF for
> mat)

. #delimit cr
delimiter now cr
. 
. 
. *--------------------------------------------------------------------------------
. *--- (5) Event studies -- Leave-one-out
. *--------------------------------------------------------------------------------    
. local k=1

. levelsof state, local(snames)
`"Andhra Pradesh"' `"Assam"' `"Bihar/Jharkhand"' `"Gujarat"' `"Haryana"' `"Karnataka"' `"Kerala"' `"Madhya Pradesh/ Chhattisgarh"' `"Ma
> harashtra"' `"Odisha"' `"Punjab"' `"Rajasthan"' `"Tamil Nadu"' `"Uttar Pradesh/Uttarakhand"' `"West Bengal"'

. local Mgraphs

. foreach st of local snames {
  2.     preserve
  3.     local lag=5
  4.     local lead=3
  5.     local se robust wboot
  6.     if `"`st'"'=="Bihar/Jharkhand" {
  7.         local lag=4
  8.         local lead=4
  9.         local se cluster(sID)
 10.     }
 11.     if `"`st'"'=="Uttar Pradesh/Uttarakhand" {
 12.         local lag=5
 13.         local lead=2
 14.         local se cluster(sID)
 15.     }
 16. 
.     *set seed 2727
.     dis "`st'"
 17.     drop if state==`"`st'"'
 18.     sum lnMMR
 19.     local N  = r(N)
 20.     local mu = string(r(mean), "%5.2f")
 21.     #delimit ;
delimiter now ;
.     eventdd lnMMR i.sID i.year [aw=censuspop], ci(rarea, color(gs12%70))
>     timevar(timeToQuota) lags(`lag') leads(`lead') accum
>     graph_op(ytitle("ln(MMR)") xtitle("Periods to State Gender Quota")
>              xlabel(-`lead'(1)`lag') name(m`k', replace) legend(off)
>              note("Observations = `N'.  Mean ln(MMR) = `mu'.") title("No `st'"))
>     wboot_op(seed(2727)) coef_op(msymbol(Oh) mcolor(gs2))
>     endpoints_op(msymbol(Oh) mcolor(gs2)) level(95) `se';
 22.     local Mgraphs `Mgraphs' m`k';
 23.     #delimit cr
delimiter now cr
.     restore
 24.     local ++k
 25. }
Andhra Pradesh
(9 observations deleted)

    Variable |        Obs        Mean    Std. Dev.       Min        Max
-------------+---------------------------------------------------------
       lnMMR |        126    5.372623    .6560162   3.828641   6.973543
(sum of wgt is 8,321,424,056)

Linear regression                               Number of obs     =        126
                                                F(29, 96)         =     221.07
                                                Prob > F          =     0.0000
                                                R-squared         =     0.9484
                                                Root MSE          =     .16963

------------------------------------------------------------------------------
             |               Robust
       lnMMR |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         sID |
          3  |  -.2972128    .043682    -6.80   0.000    -.3839209   -.2105047
          4  |  -1.069034   .1459413    -7.33   0.000    -1.358725   -.7793428
          5  |   -.894432   .0779288   -11.48   0.000    -1.049119   -.7397445
          6  |  -.7292433    .046868   -15.56   0.000    -.8222756    -.636211
          7  |  -1.443709   .0617585   -23.38   0.000    -1.566299    -1.32112
          8  |  -.2811185   .0646102    -4.35   0.000    -.4093686   -.1528684
          9  |  -1.195612   .0729607   -16.39   0.000    -1.340438   -1.050786
         10  |  -.2670242   .0479217    -5.57   0.000    -.3621479   -.1719004
         11  |  -.8411067   .1143136    -7.36   0.000    -1.068017   -.6141959
         12  |  -.1306855   .0596428    -2.19   0.031    -.2490756   -.0122954
         13  |  -1.235122   .0543407   -22.73   0.000    -1.342987   -1.127256
         14  |  -.1272379   .0727972    -1.75   0.084    -.2717393    .0172634
         15  |  -.8485058   .0704458   -12.04   0.000    -.9883396    -.708672
             |
        year |
       1998  |  -.4879872   .0894787    -5.45   0.000    -.6656011   -.3103733
       2001  |  -.4707648   .0995081    -4.73   0.000    -.6682868   -.2732427
       2003  |  -.5264573   .1134156    -4.64   0.000    -.7515856   -.3013291
       2006  |  -.5791299   .1453606    -3.98   0.000    -.8676685   -.2905913
       2009  |  -.7151076   .1512242    -4.73   0.000    -1.015285   -.4149299
       2012  |  -.8470615   .1796911    -4.71   0.000    -1.203746   -.4903775
       2013  |  -.9098956   .2053664    -4.43   0.000    -1.317545   -.5022466
       2016  |  -1.124437   .2036403    -5.52   0.000     -1.52866   -.7202148
             |
       lead3 |   .0501284   .1083796     0.46   0.645    -.1650035    .2652602
       lead2 |   -.008619   .0853333    -0.10   0.920    -.1780042    .1607662
        lag0 |  -.2265678   .1089961    -2.08   0.040    -.4429234   -.0102122
        lag1 |  -.1795256   .0963689    -1.86   0.066    -.3708163    .0117652
        lag2 |  -.2619584   .1082951    -2.42   0.017    -.4769225   -.0469943
        lag3 |  -.3138026   .1443873    -2.17   0.032    -.6004091   -.0271961
        lag4 |  -.3586994   .1516169    -2.37   0.020    -.6596566   -.0577423
        lag5 |  -.3899221   .1933102    -2.02   0.046    -.7736398   -.0062044
       _cons |    6.93673   .1007141    68.88   0.000     6.736814    7.136646
------------------------------------------------------------------------------
Assam
(9 observations deleted)

    Variable |        Obs        Mean    Std. Dev.       Min        Max
-------------+---------------------------------------------------------
       lnMMR |        126    5.299496    .6344427   3.828641   6.824374
(sum of wgt is 8,766,205,471)

Linear regression                               Number of obs     =        126
                                                F(29, 96)         =     203.07
                                                Prob > F          =     0.0000
                                                R-squared         =     0.9499
                                                Root MSE          =     .16584

------------------------------------------------------------------------------
             |               Robust
       lnMMR |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         sID |
          3  |   .6993966   .0412694    16.95   0.000     .6174775    .7813156
          4  |  -.0783942   .1493354    -0.52   0.601    -.3748226    .2180343
          5  |   .0963554   .0746482     1.29   0.200    -.0518201    .2445309
          6  |   .2612265   .0329047     7.94   0.000     .1959112    .3265418
          7  |  -.4537121   .0486736    -9.32   0.000    -.5503283   -.3570958
          8  |   .7095718   .0561239    12.64   0.000     .5981667    .8209769
          9  |   -.205076   .0577265    -3.55   0.001    -.3196623   -.0904898
         10  |   .7233758   .0352822    20.50   0.000     .6533413    .7934104
         11  |   .1493294   .1110574     1.34   0.182    -.0711179    .3697766
         12  |   .8600843   .0497516    17.29   0.000     .7613283    .9588404
         13  |  -.2447168    .042951    -5.70   0.000    -.3299739   -.1594597
         14  |   .8805318   .0841064    10.47   0.000      .713582    1.047482
         15  |   .1419024   .0634635     2.24   0.028     .0159284    .2678765
             |
        year |
       1998  |  -.4950659   .0860299    -5.75   0.000    -.6658338    -.324298
       2001  |   -.459763   .0910061    -5.05   0.000    -.6404087   -.2791172
       2003  |  -.5357524   .1080148    -4.96   0.000      -.75016   -.3213447
       2006  |  -.6127772   .1377003    -4.45   0.000    -.8861101   -.3394444
       2009  |   -.743641   .1409275    -5.28   0.000     -1.02338   -.4639022
       2012  |  -.8860273   .1710864    -5.18   0.000    -1.225631   -.5464236
       2013  |  -.9601213   .1930989    -4.97   0.000     -1.34342    -.576823
       2016  |  -1.174415   .1940472    -6.05   0.000    -1.559596   -.7892344
             |
       lead3 |   .0326624    .105497     0.31   0.758    -.1767475    .2420724
       lead2 |  -.0371923   .0906281    -0.41   0.682    -.2170875     .142703
        lag0 |  -.2124597   .1022305    -2.08   0.040    -.4153856   -.0095338
        lag1 |  -.1798004   .0883739    -2.03   0.045    -.3552212   -.0043796
        lag2 |  -.2450432   .1020988    -2.40   0.018    -.4477077   -.0423787
        lag3 |  -.2881164   .1361896    -2.12   0.037    -.5584506   -.0177823
        lag4 |  -.3324782    .140529    -2.37   0.020     -.611426   -.0535305
        lag5 |  -.3573627   .1816975    -1.97   0.052    -.7180293    .0033039
       _cons |   5.949966   .0865453    68.75   0.000     5.778175    6.121757
------------------------------------------------------------------------------
Bihar/Jharkhand
(9 observations deleted)

    Variable |        Obs        Mean    Std. Dev.       Min        Max
-------------+---------------------------------------------------------
       lnMMR |        126    5.319956     .651035   3.828641   6.973543
(sum of wgt is 7,988,662,615)

Linear regression                               Number of obs     =        126
                                                F(8, 13)          =          .
                                                Prob > F          =          .
                                                R-squared         =     0.9478
                                                Root MSE          =     .17273

                                   (Std. Err. adjusted for 14 clusters in sID)
------------------------------------------------------------------------------
             |               Robust
       lnMMR |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         sID |
          2  |   1.009403   .0102855    98.14   0.000     .9871821    1.031623
          4  |  -.0786518   .0017537   -44.85   0.000    -.0824403   -.0748632
          5  |   .0959626   .0026093    36.78   0.000     .0903256    .1015995
          6  |    .261112   .0008252   316.41   0.000     .2593292    .2628949
          7  |  -.4535403   .0012739  -356.02   0.000    -.4562925   -.4507882
          8  |   .7092988   .0019116   371.06   0.000     .7051692    .7134285
          9  |  -.2053133   .0014838  -138.37   0.000     -.208519   -.2021077
         10  |   .7233048   .0005104  1417.22   0.000     .7222022    .7244074
         11  |   .1491701   .0009656   154.49   0.000     .1470841    .1512561
         12  |   .8596901    .002585   332.57   0.000     .8541056    .8652745
         13  |  -.2446836   .0002532  -966.50   0.000    -.2452305   -.2441367
         14  |   .9219132   .0471921    19.54   0.000     .8199609    1.023866
         15  |   .1417892   .0007107   199.51   0.000     .1402538    .1433246
             |
        year |
       1998  |  -.6395618   .1694369    -3.77   0.002    -1.005608   -.2735156
       2001  |  -.5637141   .1115374    -5.05   0.000    -.8046759   -.3227522
       2003  |  -.6216319   .1218635    -5.10   0.000    -.8849019   -.3583618
       2006  |  -.7414207   .1426441    -5.20   0.000    -1.049585   -.4332569
       2009  |  -.8664286   .1411152    -6.14   0.000    -1.171289   -.5615679
       2012  |  -1.028191   .1461542    -7.03   0.000    -1.343938   -.7124435
       2013  |  -1.116165   .1680805    -6.64   0.000    -1.479281   -.7530494
       2016  |   -1.32778   .1577772    -8.42   0.000    -1.668637   -.9869232
             |
       lead4 |  -.0448014   .1256532    -0.36   0.727    -.3162587     .226656
       lead3 |   .1772666   .1645898     1.08   0.301    -.1783081    .5328412
       lead2 |  -.0120326   .0559524    -0.22   0.833    -.1329104    .1088453
        lag0 |  -.0921657   .1134185    -0.81   0.431    -.3371914    .1528601
        lag1 |  -.0773896   .0725816    -1.07   0.306    -.2341925    .0794134
        lag2 |  -.1436336   .0640517    -2.24   0.043    -.2820089   -.0052583
        lag3 |  -.1524965   .0721346    -2.11   0.054    -.3083338    .0033408
        lag4 |  -.2017684   .0866382    -2.33   0.037    -.3889389   -.0145978
       _cons |   5.947262   .1018814    58.37   0.000     5.727161    6.167363
------------------------------------------------------------------------------
Gujarat
(9 observations deleted)

    Variable |        Obs        Mean    Std. Dev.       Min        Max
-------------+---------------------------------------------------------
       lnMMR |        126    5.381159    .6472134   3.828641   6.973543
(sum of wgt is 8,544,937,483)

Linear regression                               Number of obs     =        126
                                                F(29, 96)         =     348.75
                                                Prob > F          =     0.0000
                                                R-squared         =     0.9722
                                                Root MSE          =     .12351

------------------------------------------------------------------------------
             |               Robust
       lnMMR |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         sID |
          2  |   1.005902   .0560119    17.96   0.000     .8947189    1.117084
          3  |   .7093439   .0370522    19.14   0.000     .6357958     .782892
          5  |   .0976667   .0806467     1.21   0.229    -.0624158    .2577492
          6  |   .2616304   .0340068     7.69   0.000     .1941275    .3291334
          7  |  -.4543297   .0425307   -10.68   0.000    -.5387525   -.3699069
          8  |   .7105163   .0543557    13.07   0.000     .6026212    .8184115
          9  |  -.2043168   .0555101    -3.68   0.000    -.3145034   -.0941302
         10  |   .7236259   .0399144    18.13   0.000     .6443965    .8028554
         11  |   .1498277   .1098758     1.36   0.176     -.068274    .3679293
         12  |   .8613886     .04786    18.00   0.000     .7663873    .9563899
         13  |  -.2447311   .0467712    -5.23   0.000    -.3375713    -.151891
         14  |   .9250936   .0738421    12.53   0.000     .7785183    1.071669
         15  |   .1422657   .0575288     2.47   0.015     .0280719    .2564594
             |
        year |
       1998  |  -.4660878   .0710159    -6.56   0.000    -.6070532   -.3251223
       2001  |  -.5432183   .0750519    -7.24   0.000    -.6921951   -.3942414
       2003  |  -.6081531   .0932386    -6.52   0.000    -.7932303    -.423076
       2006  |  -.7051928   .1116794    -6.31   0.000    -.9268747   -.4835109
       2009  |  -.8513039   .1222202    -6.97   0.000    -1.093909   -.6086988
       2012  |  -1.004018   .1449282    -6.93   0.000    -1.291698    -.716338
       2013  |  -1.081986   .1654771    -6.54   0.000    -1.410456   -.7535169
       2016  |  -1.298759   .1641502    -7.91   0.000    -1.624595   -.9729239
             |
       lead3 |  -.0212702    .089339    -0.24   0.812    -.1986067    .1560663
       lead2 |  -.0068063   .0726588    -0.09   0.926    -.1510328    .1374203
        lag0 |  -.1466913   .0662352    -2.21   0.029    -.2781673   -.0152154
        lag1 |  -.1036309   .0728505    -1.42   0.158    -.2482381    .0409763
        lag2 |  -.1667995   .0835694    -2.00   0.049    -.3326835   -.0009155
        lag3 |  -.1974724   .1120488    -1.76   0.081    -.4198875    .0249428
        lag4 |  -.2339916   .1244969    -1.88   0.063    -.4811159    .0131328
        lag5 |  -.2431873   .1552653    -1.57   0.121    -.5513864    .0650118
       _cons |   5.944847   .0900014    66.05   0.000     5.766196    6.123499
------------------------------------------------------------------------------
Haryana
(9 observations deleted)

    Variable |        Obs        Mean    Std. Dev.       Min        Max
-------------+---------------------------------------------------------
       lnMMR |        126    5.367186    .6612951   3.828641   6.973543
(sum of wgt is 8,816,572,284)

Linear regression                               Number of obs     =        126
                                                F(29, 96)         =     226.22
                                                Prob > F          =     0.0000
                                                R-squared         =     0.9521
                                                Root MSE          =     .16357

------------------------------------------------------------------------------
             |               Robust
       lnMMR |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         sID |
          2  |   1.000183   .0549262    18.21   0.000     .8911552     1.10921
          3  |   .7031527   .0408045    17.23   0.000     .6221565     .784149
          4  |  -.0783043   .1500566    -0.52   0.603    -.3761644    .2195557
          6  |   .2612741   .0319501     8.18   0.000     .1978535    .3246946
          7  |  -.4537892   .0473837    -9.58   0.000    -.5478452   -.3597333
          8  |   .7096759   .0551053    12.88   0.000     .6002929     .819059
          9  |  -.2050163   .0571223    -3.59   0.001    -.3184032   -.0916294
         10  |    .723405   .0352416    20.53   0.000      .653451    .7933591
         11  |   .1493638    .110816     1.35   0.181    -.0706041    .3693318
         12  |   .8602048   .0485478    17.72   0.000     .7638382    .9565715
         13  |  -.2446794   .0430767    -5.68   0.000    -.3301861   -.1591728
         14  |   .8973083   .0850613    10.55   0.000     .7284629    1.066154
         15  |   .1419314   .0629477     2.25   0.026     .0169812    .2668816
             |
        year |
       1998  |   -.491214   .0845884    -5.81   0.000    -.6591207   -.3233074
       2001  |  -.4913552   .0940208    -5.23   0.000    -.6779851   -.3047254
       2003  |  -.5628149    .108186    -5.20   0.000    -.7775623   -.3480674
       2006  |    -.64057   .1397558    -4.58   0.000     -.917983   -.3631569
       2009  |  -.7839319   .1467619    -5.34   0.000    -1.075252   -.4926119
       2012  |  -.9330128   .1740226    -5.36   0.000    -1.278445   -.5875808
       2013  |  -1.005079   .1970359    -5.10   0.000    -1.396192   -.6139658
       2016  |  -1.221623   .1973047    -6.19   0.000     -1.61327    -.829976
             |
       lead3 |   .0188722   .1037771     0.18   0.856    -.1871237    .2248682
       lead2 |  -.0195051    .081737    -0.24   0.812    -.1817517    .1427415
        lag0 |  -.2041199   .1013407    -2.01   0.047    -.4052797   -.0029601
        lag1 |  -.1417973   .0909054    -1.56   0.122    -.3222432    .0386486
        lag2 |     -.2068   .1030482    -2.01   0.048    -.4113491   -.0022509
        lag3 |  -.2544857   .1380441    -1.84   0.068     -.528501    .0195297
        lag4 |  -.2880996   .1471003    -1.96   0.053    -.5800914    .0038921
        lag5 |  -.3090355   .1848194    -1.67   0.098    -.6758991    .0578281
       _cons |   5.945053   .0875624    67.90   0.000     5.771243    6.118863
------------------------------------------------------------------------------
Karnataka
(9 observations deleted)

    Variable |        Obs        Mean    Std. Dev.       Min        Max
-------------+---------------------------------------------------------
       lnMMR |        126    5.354395    .6652042   3.828641   6.973543
(sum of wgt is 8,526,809,871)

Linear regression                               Number of obs     =        126
                                                F(29, 96)         =     207.79
                                                Prob > F          =     0.0000
                                                R-squared         =     0.9501
                                                Root MSE          =     .16905

------------------------------------------------------------------------------
             |               Robust
       lnMMR |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         sID |
          2  |   .9986562   .0555844    17.97   0.000     .8883219     1.10899
          3  |   .7016001   .0423886    16.55   0.000     .6174593    .7857409
          4  |  -.0783985   .1490494    -0.53   0.600    -.3742591    .2174622
          5  |   .0963554   .0740522     1.30   0.196     -.050637    .2433478
          7  |  -.4536992   .0495417    -9.16   0.000    -.5520386   -.3553597
          8  |    .709562   .0571033    12.43   0.000     .5962128    .8229112
          9  |  -.2050665   .0577443    -3.55   0.001     -.319688    -.090445
         10  |   .7233721   .0352486    20.52   0.000     .6534041      .79334
         11  |    .149339   .1116316     1.34   0.184     -.072248    .3709261
         12  |   .8600877   .0508723    16.91   0.000      .759107    .9610684
         13  |  -.2447448    .042676    -5.73   0.000    -.3294559   -.1600337
         14  |   .8913965   .0885667    10.06   0.000     .7155929      1.0672
         15  |   .1419067   .0635381     2.23   0.028     .0157844    .2680289
             |
        year |
       1998  |  -.5023226   .0876634    -5.73   0.000    -.6763331    -.328312
       2001  |  -.4942494    .098117    -5.04   0.000    -.6890101   -.2994887
       2003  |  -.5634015   .1133707    -4.97   0.000    -.7884406   -.3383624
       2006  |  -.6344742   .1464493    -4.33   0.000    -.9251737   -.3437747
       2009  |  -.7754459   .1535941    -5.05   0.000    -1.080328   -.4705641
       2012  |  -.9193501   .1824727    -5.04   0.000    -1.281555   -.5571447
       2013  |  -.9924385   .2075933    -4.78   0.000    -1.404508   -.5803691
       2016  |  -1.209255   .2080419    -5.81   0.000    -1.622215   -.7962951
             |
       lead3 |   .0170316   .1083046     0.16   0.875    -.1979513    .2320146
       lead2 |  -.0267929   .0825634    -0.32   0.746    -.1906799    .1370941
        lag0 |  -.2178377   .1061093    -2.05   0.043     -.428463   -.0072123
        lag1 |  -.1593057   .0952009    -1.67   0.098    -.3482781    .0296666
        lag2 |  -.2256599   .1088588    -2.07   0.041    -.4417429   -.0095769
        lag3 |  -.2751145   .1449223    -1.90   0.061     -.562783    .0125541
        lag4 |  -.3112699   .1538505    -2.02   0.046    -.6166607    -.005879
        lag5 |  -.3309739   .1945179    -1.70   0.092    -.7170888    .0551411
       _cons |    5.95836    .090733    65.67   0.000     5.778256    6.138464
------------------------------------------------------------------------------
Kerala
(9 observations deleted)

    Variable |        Obs        Mean    Std. Dev.       Min        Max
-------------+---------------------------------------------------------
       lnMMR |        126    5.405046    .6258482   3.828641   6.973543
(sum of wgt is 8,725,380,250)

Linear regression                               Number of obs     =        126
                                                F(29, 96)         =     198.15
                                                Prob > F          =     0.0000
                                                R-squared         =     0.9481
                                                Root MSE          =     .16605

------------------------------------------------------------------------------
             |               Robust
       lnMMR |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         sID |
          2  |   .9961717   .0553839    17.99   0.000     .8862355    1.106108
          3  |   .6989881    .043629    16.02   0.000     .6123853    .7855909
          4  |  -.0786358   .1479022    -0.53   0.596    -.3722194    .2149479
          5  |   .0960023   .0733459     1.31   0.194    -.0495882    .2415928
          6  |   .2611087   .0343033     7.61   0.000     .1930172    .3292001
          8  |   .7093035   .0569889    12.45   0.000     .5961814    .8224256
          9  |   -.205267   .0596765    -3.44   0.001     -.323724     -.08681
         10  |   .7233031   .0361247    20.02   0.000     .6515962    .7950101
         11  |   .1492089   .1106843     1.35   0.181    -.0704976    .3689154
         12  |   .8597379   .0511145    16.82   0.000     .7582765    .9611993
         13  |  -.2447528   .0441409    -5.54   0.000    -.3323718   -.1571338
         14  |   .8823518   .0876481    10.07   0.000     .7083717    1.056332
         15  |   .1418106    .065525     2.16   0.033     .0117445    .2718768
             |
        year |
       1998  |  -.4979501   .0874092    -5.70   0.000     -.671456   -.3244442
       2001  |  -.4815278   .0964583    -4.99   0.000     -.672996   -.2900597
       2003  |  -.5431846   .1111774    -4.89   0.000      -.76387   -.3224991
       2006  |  -.6096252   .1429856    -4.26   0.000    -.8934493    -.325801
       2009  |  -.7491536    .149379    -5.02   0.000    -1.045669   -.4526386
       2012  |  -.8921005   .1783323    -5.00   0.000    -1.246087   -.5381138
       2013  |  -.9650185   .2022086    -4.77   0.000    -1.366399   -.5636377
       2016  |  -1.178956   .2019553    -5.84   0.000    -1.579834    -.778078
             |
       lead3 |   .0340134   .1067566     0.32   0.751    -.1778969    .2459236
       lead2 |  -.0179419   .0833543    -0.22   0.830    -.1833989    .1475152
        lag0 |   -.222969   .1046158    -2.13   0.036    -.4306298   -.0153083
        lag1 |  -.1674949   .0935574    -1.79   0.077    -.3532049    .0182151
        lag2 |  -.2350811   .1065882    -2.21   0.030    -.4466571   -.0235051
        lag3 |  -.2841192    .141596    -2.01   0.048     -.565185   -.0030534
        lag4 |  -.3227543   .1495266    -2.16   0.033    -.6195623   -.0259463
        lag5 |  -.3453053    .189732    -1.82   0.072    -.7219204    .0313098
       _cons |   5.948237   .0898633    66.19   0.000      5.76986    6.126614
------------------------------------------------------------------------------
Madhya Pradesh/ Chhattisgarh
(9 observations deleted)

    Variable |        Obs        Mean    Std. Dev.       Min        Max
-------------+---------------------------------------------------------
       lnMMR |        126    5.322821    .6588088   3.828641   6.973543
(sum of wgt is 8,259,439,764)

Linear regression                               Number of obs     =        126
                                                F(29, 96)         =     216.99
                                                Prob > F          =     0.0000
                                                R-squared         =     0.9531
                                                Root MSE          =     .16462

------------------------------------------------------------------------------
             |               Robust
       lnMMR |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         sID |
          2  |   .9986139   .0562981    17.74   0.000     .8868631    1.110365
          3  |   .7017329   .0424228    16.54   0.000     .6175243    .7859415
          4  |  -.0781368   .1477809    -0.53   0.598    -.3714795     .215206
          5  |   .0967446   .0728949     1.33   0.188    -.0479505    .2414398
          6  |   .2613432   .0359231     7.28   0.000     .1900364      .33265
          7  |  -.4538889   .0502046    -9.04   0.000    -.5535444   -.3542335
          9  |  -.2048459   .0551893    -3.71   0.000    -.3143958    -.095296
         10  |   .7234482   .0344423    21.00   0.000     .6550807    .7918157
         11  |   .1494821   .1155887     1.29   0.199    -.0799596    .3789239
         12  |   .8604732   .0543887    15.82   0.000     .7525125    .9684339
         13  |  -.2447352   .0398085    -6.15   0.000    -.3237544   -.1657159
         14  |   .8890716    .091552     9.71   0.000     .7073422    1.070801
         15  |   .1420124   .0628195     2.26   0.026     .0173166    .2667081
             |
        year |
       1998  |  -.5318932   .0835571    -6.37   0.000    -.6977527   -.3660336
       2001  |  -.5070753   .0977593    -5.19   0.000    -.7011261   -.3130246
       2003  |  -.5899176   .1137391    -5.19   0.000    -.8156879   -.3641472
       2006  |  -.6499837    .151654    -4.29   0.000    -.9510145   -.3489528
       2009  |  -.7882796   .1600626    -4.92   0.000    -1.106001   -.4705579
       2012  |  -.9322811   .1916262    -4.87   0.000    -1.312656   -.5519061
       2013  |  -1.007176   .2175452    -4.63   0.000       -1.439   -.5753526
       2016  |  -1.221123   .2188868    -5.58   0.000     -1.65561   -.7866357
             |
       lead3 |  -.0058082    .109013    -0.05   0.958    -.2221973    .2105808
       lead2 |  -.0574467   .0732776    -0.78   0.435    -.2029016    .0880083
        lag0 |  -.2451432   .1065858    -2.30   0.024    -.4567142   -.0335721
        lag1 |   -.182479   .0955342    -1.91   0.059    -.3721128    .0071548
        lag2 |   -.248492   .1133442    -2.19   0.031    -.4734786   -.0235055
        lag3 |  -.3016516   .1497725    -2.01   0.047    -.5989476   -.0043556
        lag4 |  -.3366403   .1591982    -2.11   0.037    -.6526462   -.0206343
        lag5 |  -.3620494   .2022216    -1.79   0.077    -.7634562    .0393574
       _cons |    5.99831   .0752694    79.69   0.000     5.848901    6.147719
------------------------------------------------------------------------------
Maharashtra
(9 observations deleted)

    Variable |        Obs        Mean    Std. Dev.       Min        Max
-------------+---------------------------------------------------------
       lnMMR |        126    5.386502    .6419349   3.828641   6.973543
(sum of wgt is 8,129,093,031)

Linear regression                               Number of obs     =        126
                                                F(29, 96)         =     294.59
                                                Prob > F          =     0.0000
                                                R-squared         =     0.9472
                                                Root MSE          =     .16475

------------------------------------------------------------------------------
             |               Robust
       lnMMR |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         sID |
          2  |   .9877567    .057721    17.11   0.000     .8731814    1.102332
          3  |   .6901539   .0481783    14.33   0.000     .5945209     .785787
          4  |  -.0793035   .1480662    -0.54   0.593    -.3732127    .2146056
          5  |   .0950257    .074734     1.27   0.207    -.0533201    .2433714
          6  |   .2607833   .0370204     7.04   0.000     .1872985    .3342681
          7  |  -.4530175   .0561359    -8.07   0.000    -.5644464   -.3415885
          8  |   .7085623   .0556976    12.72   0.000     .5980035    .8191211
         10  |   .7231023   .0400201    18.07   0.000      .643663    .8025416
         11  |   .1488752   .1070111     1.39   0.167    -.0635402    .3612905
         12  |   .8587798   .0511957    16.77   0.000     .7571572    .9604024
         13  |  -.2448504   .0499608    -4.90   0.000    -.3440218    -.145679
         14  |   .8543397   .0903554     9.46   0.000     .6749857    1.033694
         15  |   .1415565   .0697317     2.03   0.045     .0031401    .2799729
             |
        year |
       1998  |  -.4614769   .0857544    -5.38   0.000    -.6316979   -.2912558
       2001  |  -.4361218   .0965546    -4.52   0.000    -.6277812   -.2444625
       2003  |  -.4830611   .1048799    -4.61   0.000    -.6912461   -.2748762
       2006  |   -.539536   .1386587    -3.89   0.000    -.8147713   -.2643007
       2009  |  -.6717828   .1436184    -4.68   0.000    -.9568631   -.3867025
       2012  |  -.8043811   .1725757    -4.66   0.000    -1.146941    -.461821
       2013  |  -.8548814   .1914823    -4.46   0.000    -1.234971    -.474792
       2016  |   -1.08282   .1958978    -5.53   0.000    -1.471674   -.6939656
             |
       lead3 |   .0893537   .1025275     0.87   0.386    -.1141619    .2928692
       lead2 |   .0202665   .0865079     0.23   0.815    -.1514502    .1919833
        lag0 |  -.2151846   .1097833    -1.96   0.053    -.4331026    .0027335
        lag1 |  -.1670329   .0932804    -1.79   0.077    -.3521931    .0181273
        lag2 |  -.2541784   .1040216    -2.44   0.016    -.4606597   -.0476971
        lag3 |  -.3144992   .1374757    -2.29   0.024    -.5873863   -.0416122
        lag4 |  -.3508147   .1439702    -2.44   0.017    -.6365933   -.0650361
        lag5 |  -.3835588   .1857313    -2.07   0.042    -.7522325   -.0148851
       _cons |   5.902672   .0846374    69.74   0.000     5.734668    6.070676
------------------------------------------------------------------------------
Odisha
(9 observations deleted)

    Variable |        Obs        Mean    Std. Dev.       Min        Max
-------------+---------------------------------------------------------
       lnMMR |        126    5.321436    .6542644   3.828641   6.973543
(sum of wgt is 8,675,103,173)

Linear regression                               Number of obs     =        126
                                                F(29, 96)         =     215.61
                                                Prob > F          =     0.0000
                                                R-squared         =     0.9499
                                                Root MSE          =     .16757

------------------------------------------------------------------------------
             |               Robust
       lnMMR |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         sID |
          2  |   1.000011   .0549869    18.19   0.000     .8908633     1.10916
          3  |   .7029411   .0417585    16.83   0.000     .6200512    .7858311
          4  |  -.0783887   .1495195    -0.52   0.601    -.3751826    .2184052
          5  |   .0963594    .074531     1.29   0.199    -.0515834    .2443023
          6  |    .261232   .0325162     8.03   0.000     .1966879    .3257761
          7  |  -.4537226   .0488345    -9.29   0.000    -.5506583   -.3567868
          8  |   .7095811   .0556083    12.76   0.000     .5991995    .8199628
          9  |  -.2050801   .0578439    -3.55   0.001    -.3198992   -.0902609
         11  |   .1493244   .1104754     1.35   0.180    -.0699676    .3686165
         12  |    .860086   .0493429    17.43   0.000     .7621411     .958031
         13  |  -.2446982   .0436781    -5.60   0.000    -.3313986   -.1579978
         14  |   .8967988   .0871829    10.29   0.000     .7237421    1.069856
         15  |   .1419007   .0639338     2.22   0.029     .0149931    .2688083
             |
        year |
       1998  |  -.4927359   .0862469    -5.71   0.000    -.6639347   -.3215371
       2001  |  -.4924591    .096349    -5.11   0.000    -.6837103   -.3012079
       2003  |  -.5609061   .1108481    -5.06   0.000    -.7809379   -.3408744
       2006  |  -.6335203   .1428402    -4.44   0.000    -.9170557   -.3499848
       2009  |    -.77804   .1502632    -5.18   0.000     -1.07631   -.4797698
       2012  |   -.927722   .1783833    -5.20   0.000     -1.28181    -.573634
       2013  |  -1.002953   .2024338    -4.95   0.000    -1.404781   -.6011254
       2016  |  -1.220013   .2027227    -6.02   0.000    -1.622415    -.817612
             |
       lead3 |   .0196351    .106158     0.18   0.854    -.1910868     .230357
       lead2 |  -.0189407   .0829096    -0.23   0.820     -.183515    .1456336
        lag0 |  -.2084904   .1038139    -2.01   0.047    -.4145594   -.0024214
        lag1 |  -.1486463   .0932958    -1.59   0.114     -.333837    .0365444
        lag2 |  -.2137691   .1060925    -2.01   0.047     -.424361   -.0031772
        lag3 |  -.2567132   .1414022    -1.82   0.073    -.5373943    .0239679
        lag4 |  -.2904895   .1505732    -1.93   0.057    -.5893749    .0083959
        lag5 |  -.3104799   .1900828    -1.63   0.106    -.6877912    .0668315
       _cons |   5.945561    .089766    66.23   0.000     5.767377    6.123745
------------------------------------------------------------------------------
Punjab
(9 observations deleted)

    Variable |        Obs        Mean    Std. Dev.       Min        Max
-------------+---------------------------------------------------------
       lnMMR |        126     5.36358    .6693411   3.828641   6.973543
(sum of wgt is 8,790,263,157)

Linear regression                               Number of obs     =        126
                                                F(29, 96)         =     213.38
                                                Prob > F          =     0.0000
                                                R-squared         =     0.9558
                                                Root MSE          =     .15784

------------------------------------------------------------------------------
             |               Robust
       lnMMR |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         sID |
          2  |   1.001114   .0545386    18.36   0.000     .8928556    1.109372
          3  |   .7041745   .0403108    17.47   0.000     .6241581    .7841908
          4  |  -.0781794   .1482959    -0.53   0.599    -.3725444    .2161856
          5  |   .0966647   .0741803     1.30   0.196    -.0505819    .2439114
          6  |   .2613345   .0330928     7.90   0.000     .1956459    .3270232
          7  |  -.4538837   .0479158    -9.47   0.000    -.5489957   -.3587716
          8  |   .7098141   .0579512    12.25   0.000     .5947819    .8248464
          9  |  -.2049161   .0551082    -3.72   0.000    -.3143049   -.0955272
         10  |   .7234424   .0338384    21.38   0.000     .6562736    .7906111
         12  |   .8603851    .051002    16.87   0.000     .7591469    .9616233
         13  |   -.244664   .0403807    -6.06   0.000     -.324819    -.164509
         14  |   .8981916   .0841258    10.68   0.000     .7312033     1.06518
         15  |   .1419796   .0628835     2.26   0.026     .0171567    .2668024
             |
        year |
       1998  |  -.5166509   .0847796    -6.09   0.000    -.6849371   -.3483647
       2001  |  -.5003029   .0942194    -5.31   0.000    -.6873269   -.3132789
       2003  |  -.5817307   .1090215    -5.34   0.000    -.7981367   -.3653248
       2006  |  -.6529192   .1419279    -4.60   0.000    -.9346438   -.3711947
       2009  |  -.7995518   .1477021    -5.41   0.000    -1.092738   -.5063655
       2012  |  -.9473723   .1758441    -5.39   0.000     -1.29642   -.5983247
       2013  |  -1.019727   .1984846    -5.14   0.000    -1.413715   -.6257379
       2016  |  -1.238389   .1982168    -6.25   0.000    -1.631846   -.8449319
             |
       lead3 |   .0018275   .1049516     0.02   0.986    -.2064998    .2101548
       lead2 |  -.0438021   .0782237    -0.56   0.577     -.199075    .1114707
        lag0 |  -.2272131   .1024644    -2.22   0.029    -.4306032   -.0238229
        lag1 |  -.1574477   .0911957    -1.73   0.087    -.3384698    .0235744
        lag2 |  -.2194201   .1049912    -2.09   0.039    -.4278261   -.0110142
        lag3 |  -.2701917   .1395463    -1.94   0.056     -.547189    .0068055
        lag4 |  -.3034385   .1473113    -2.06   0.042    -.5958491   -.0110279
        lag5 |  -.3251875   .1856608    -1.75   0.083    -.6937213    .0433462
       _cons |   5.973933    .083225    71.78   0.000     5.808733    6.139133
------------------------------------------------------------------------------
Rajasthan
(9 observations deleted)

    Variable |        Obs        Mean    Std. Dev.       Min        Max
-------------+---------------------------------------------------------
       lnMMR |        126     5.31188    .6493337   3.828641   6.973543
(sum of wgt is 8,491,328,111)

Linear regression                               Number of obs     =        126
                                                F(29, 96)         =     214.79
                                                Prob > F          =     0.0000
                                                R-squared         =     0.9506
                                                Root MSE          =     .16622

------------------------------------------------------------------------------
             |               Robust
       lnMMR |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         sID |
          2  |   .9986626    .055762    17.91   0.000     .8879758    1.109349
          3  |   .7016446   .0426321    16.46   0.000     .6170206    .7862686
          4  |  -.0783555   .1481925    -0.53   0.598    -.3725153    .2158043
          5  |   .0964245   .0729857     1.32   0.190    -.0484509    .2412999
          6  |   .2612368   .0351066     7.44   0.000     .1915507    .3309229
          7  |  -.4537223   .0505864    -8.97   0.000    -.5541354   -.3533092
          8  |   .7096047   .0591406    12.00   0.000     .5922114    .8269979
          9  |  -.2050196   .0572058    -3.58   0.001    -.3185722    -.091467
         10  |   .7233825   .0350678    20.63   0.000     .6537734    .7929916
         11  |   .1493723   .1131297     1.32   0.190    -.0751883     .373933
         13  |   -.244766   .0416921    -5.87   0.000    -.3275241   -.1620078
         14  |   .8905343    .089307     9.97   0.000     .7132614    1.067807
         15  |   .1419289   .0636737     2.23   0.028     .0155376    .2683202
             |
        year |
       1998  |  -.5160804   .0862732    -5.98   0.000    -.6873314   -.3448294
       2001  |  -.5005661   .0976489    -5.13   0.000    -.6943975   -.3067346
       2003  |   -.574131   .1134576    -5.06   0.000    -.7993426   -.3489194
       2006  |  -.6385111   .1476426    -4.32   0.000    -.9315794   -.3454428
       2009  |  -.7787912    .155022    -5.02   0.000    -1.086507    -.471075
       2012  |  -.9216873   .1852245    -4.98   0.000    -1.289355   -.5540196
       2013  |  -.9969008   .2105329    -4.74   0.000    -1.414805   -.5789963
       2016  |  -1.214166   .2110856    -5.75   0.000    -1.633168   -.7951645
             |
       lead3 |   .0072792   .1085634     0.07   0.947    -.2082176    .2227759
       lead2 |  -.0398781   .0791031    -0.50   0.615    -.1968966    .1171403
        lag0 |  -.2315837   .1054777    -2.20   0.031    -.4409553   -.0222122
        lag1 |  -.1724122   .0949561    -1.82   0.073    -.3608985    .0160741
        lag2 |  -.2391483   .1101544    -2.17   0.032    -.4578031   -.0204936
        lag3 |   -.288657   .1460208    -1.98   0.051    -.5785059     .001192
        lag4 |  -.3242197   .1547275    -2.10   0.039    -.6313514    -.017088
        lag5 |  -.3442745   .1965245    -1.75   0.083    -.7343725    .0458236
       _cons |   5.975854   .0859646    69.52   0.000     5.805215    6.146492
------------------------------------------------------------------------------
Tamil Nadu
(9 observations deleted)

    Variable |        Obs        Mean    Std. Dev.       Min        Max
-------------+---------------------------------------------------------
       lnMMR |        126    5.390355    .6432011   3.828641   6.973543
(sum of wgt is 8,434,515,293)

Linear regression                               Number of obs     =        126
                                                F(29, 96)         =     221.96
                                                Prob > F          =     0.0000
                                                R-squared         =     0.9470
                                                Root MSE          =     .16816

------------------------------------------------------------------------------
             |               Robust
       lnMMR |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         sID |
          2  |   .9985175   .0553144    18.05   0.000     .8887194    1.108316
          3  |   .7013831   .0429261    16.34   0.000     .6161754    .7865907
          4  |  -.0784974   .1500822    -0.52   0.602    -.3764081    .2194133
          5  |   .0961948   .0751326     1.28   0.204    -.0529423    .2453319
          6  |   .2611829   .0323364     8.08   0.000     .1969956    .3253702
          7  |  -.4536483   .0495207    -9.16   0.000    -.5519461   -.3553505
          8  |    .709465   .0542954    13.07   0.000     .6016895    .8172406
          9  |  -.2051778   .0595048    -3.45   0.001    -.3232939   -.0870617
         10  |   .7233487   .0371259    19.48   0.000     .6496543     .797043
         11  |   .1492594   .1088838     1.37   0.174    -.0668732     .365392
         12  |   .8599214   .0483305    17.79   0.000     .7639862    .9558566
         14  |   .8926705   .0894184     9.98   0.000     .7151763    1.070165
         15  |    .141854   .0649823     2.18   0.031     .0128651    .2708429
             |
        year |
       1998  |   -.478946   .0870617    -5.50   0.000    -.6517622   -.3061299
       2001  |  -.4844732   .0981226    -4.94   0.000     -.679245   -.2897014
       2003  |  -.5443721   .1121637    -4.85   0.000    -.7670152    -.321729
       2006  |  -.6168288    .144709    -4.26   0.000    -.9040739   -.3295838
       2009  |  -.7625287   .1529109    -4.99   0.000    -1.066055   -.4590029
       2012  |  -.9133494   .1811202    -5.04   0.000     -1.27287   -.5538287
       2013  |  -.9841052    .206745    -4.76   0.000    -1.394491   -.5737196
       2016  |  -1.203208   .2069771    -5.81   0.000    -1.614054   -.7923616
             |
       lead3 |   .0338757   .1072534     0.32   0.753    -.1790206    .2467721
       lead2 |  -.0037167   .0851523    -0.04   0.965    -.1727427    .1653093
        lag0 |  -.1999415   .1063698    -1.88   0.063    -.4110839     .011201
        lag1 |  -.1443253   .0950457    -1.52   0.132    -.3329896    .0443389
        lag2 |   -.210351   .1078657    -1.95   0.054    -.4244627    .0037606
        lag3 |  -.2514451   .1437574    -1.75   0.083    -.5368012     .033911
        lag4 |  -.2860236    .153578    -1.86   0.066    -.5908735    .0188262
        lag5 |  -.3089282   .1937367    -1.59   0.114    -.6934926    .0756361
       _cons |   5.928554   .0914887    64.80   0.000      5.74695    6.110157
------------------------------------------------------------------------------
Uttar Pradesh/Uttarakhand
(9 observations deleted)

    Variable |        Obs        Mean    Std. Dev.       Min        Max
-------------+---------------------------------------------------------
       lnMMR |        126    5.301318    .6353666   3.828641   6.973543
(sum of wgt is 7,405,602,040)

Linear regression                               Number of obs     =        126
                                                F(8, 13)          =          .
                                                Prob > F          =          .
                                                R-squared         =     0.9363
                                                Root MSE          =      .1777

                                   (Std. Err. adjusted for 14 clusters in sID)
------------------------------------------------------------------------------
             |               Robust
       lnMMR |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         sID |
          2  |   1.011289   .0406689    24.87   0.000     .9234295    1.099149
          3  |   .7150908   .0402765    17.75   0.000     .6280788    .8021028
          4  |  -.0786197   .0017839   -44.07   0.000    -.0824735   -.0747658
          5  |   .0960034    .002656    36.15   0.000     .0902655    .1017412
          6  |    .261132   .0008382   311.53   0.000     .2593211    .2629428
          7  |  -.4535745   .0012931  -350.77   0.000     -.456368    -.450781
          8  |   .7093395   .0019431   365.06   0.000     .7051418    .7135373
          9  |  -.2053007   .0015129  -135.70   0.000    -.2085691   -.2020323
         10  |   .7233169   .0005185  1395.15   0.000     .7221969     .724437
         11  |   .1491744   .0009853   151.40   0.000     .1470457    .1513031
         12  |   .8597267   .0026321   326.63   0.000     .8540403     .865413
         13  |  -.2446516    .000252  -970.67   0.000    -.2451961   -.2441071
         15  |   .1417956   .0007245   195.70   0.000     .1402303    .1433609
             |
        year |
       1998  |   -.433571   .1506748    -2.88   0.013    -.7590841    -.108058
       2001  |  -.4305167   .2832828    -1.52   0.153    -1.042512    .1814787
       2003  |   -.552528   .3230768    -1.71   0.111    -1.250493     .145437
       2006  |  -.6827071   .3421897    -2.00   0.067    -1.421963    .0565487
       2009  |  -.8486208   .3581309    -2.37   0.034    -1.622316   -.0749259
       2012  |  -1.043517   .3720883    -2.80   0.015    -1.847365    -.239669
       2013  |  -1.146971   .3929307    -2.92   0.012    -1.995846   -.2980955
       2016  |  -1.341892   .3836294    -3.50   0.004    -2.170673   -.5131111
             |
       lead2 |    .034728   .1301349     0.27   0.794    -.2464114    .3158674
        lag0 |  -.2980015   .1705735    -1.75   0.104    -.6665031       .0705
        lag1 |  -.1959675   .2479157    -0.79   0.443    -.7315569    .3396219
        lag2 |  -.2092028   .2878147    -0.73   0.480    -.8309887     .412583
        lag3 |  -.2274636    .296775    -0.77   0.457     -.868607    .4136798
        lag4 |  -.2086018   .3066257    -0.68   0.508    -.8710264    .4538227
        lag5 |   -.182396   .3152022    -0.58   0.573     -.863349    .4985569
       _cons |   5.946094     .10397    57.19   0.000     5.721481    6.170708
------------------------------------------------------------------------------
West Bengal
(9 observations deleted)

    Variable |        Obs        Mean    Std. Dev.       Min        Max
-------------+---------------------------------------------------------
       lnMMR |        126    5.361998    .6577307   3.828641   6.973543
(sum of wgt is 8,280,011,979)

Linear regression                               Number of obs     =        126
                                                F(29, 96)         =     203.85
                                                Prob > F          =     0.0000
                                                R-squared         =     0.9534
                                                Root MSE          =      .1624

------------------------------------------------------------------------------
             |               Robust
       lnMMR |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         sID |
          2  |   1.002723   .0543248    18.46   0.000     .8948887    1.110556
          3  |   .7052621   .0450593    15.65   0.000       .61582    .7947042
          4  |  -.0790092   .1448935    -0.55   0.587    -.3666205    .2086022
          5  |   .0954132   .0727842     1.31   0.193    -.0490624    .2398887
          6  |   .2609563   .0331636     7.87   0.000     .1951272    .3267854
          7  |   -.453309   .0536562    -8.45   0.000    -.5598157   -.3468022
          8  |   .7089238   .0556568    12.74   0.000      .598446    .8194016
          9  |  -.2056517   .0616419    -3.34   0.001    -.3280099   -.0832936
         10  |    .723208   .0372285    19.43   0.000       .64931     .797106
         11  |   .1489407   .1101124     1.35   0.179    -.0696307    .3675121
         12  |   .8591363   .0498761    17.23   0.000      .760133    .9581395
         13  |   -.244618   .0460967    -5.31   0.000    -.3361193   -.1531167
         14  |   .9020079   .0890211    10.13   0.000     .7253025    1.078713
             |
        year |
       1998  |   -.494744   .0903016    -5.48   0.000    -.6739913   -.3154967
       2001  |  -.4638229   .0990972    -4.68   0.000    -.6605292   -.2671166
       2003  |  -.5378025   .1133222    -4.75   0.000    -.7627453   -.3128597
       2006  |  -.5989987   .1448746    -4.13   0.000    -.8865726   -.3114248
       2009  |   -.768282   .1512848    -5.08   0.000     -1.06858    -.467984
       2012  |  -.9162814   .1821921    -5.03   0.000     -1.27793    -.554633
       2013  |  -.9982078   .2068058    -4.83   0.000    -1.408714   -.5877015
       2016  |  -1.223991   .2065623    -5.93   0.000    -1.634014   -.8139685
             |
       lead3 |   .0399673   .1103138     0.36   0.718    -.1790039    .2589385
       lead2 |  -.0161754   .0917069    -0.18   0.860     -.198212    .1658613
        lag0 |  -.2287623   .1072662    -2.13   0.036     -.441684   -.0158405
        lag1 |  -.1429669   .0954177    -1.50   0.137    -.3323696    .0464357
        lag2 |  -.2093496   .1093942    -1.91   0.059    -.4264953    .0077962
        lag3 |  -.2389355   .1429996    -1.67   0.098    -.5227875    .0449165
        lag4 |  -.2726369   .1513339    -1.80   0.075    -.5730324    .0277586
        lag5 |  -.2843215   .1930827    -1.47   0.144    -.6675876    .0989447
       _cons |   5.921024   .0913911    64.79   0.000     5.739614    6.102434
------------------------------------------------------------------------------

. graph combine `Mgraphs', scheme(s1mono) rows(3)

. graph display, xsize(9)

. translate @Graph "$OUT/events_all.pdf", name(Graph)  replace
(file /home/damian/investigacion/2013/genderMMR/replicationJEEA//results/appendix/India/events_all.pdf written in PDF format)

. 
end of do-file

. exit,clear
