Hello,
I am trying to run an event study with the user-created command eventdd. This command has an option to use regdhfe as the method. However, whereas I get the same point estimates and p-values for my controls, I get different point estimates and p-values for my year dummies and leads/lags. I've been playing around a bit with changing the number of leads/lags included in eventdd to see if I can isolate a reason there, but I haven't found it yet.
The code and dataex below should replicate the problem. Please let me know if you spot what I'm missing. Thank you in advance!
I am trying to run an event study with the user-created command eventdd. This command has an option to use regdhfe as the method. However, whereas I get the same point estimates and p-values for my controls, I get different point estimates and p-values for my year dummies and leads/lags. I've been playing around a bit with changing the number of leads/lags included in eventdd to see if I can isolate a reason there, but I haven't found it yet.
The code and dataex below should replicate the problem. Please let me know if you spot what I'm missing. Thank you in advance!
Code:
* Set as panel
xtset year uninumbr
gen timeToTreat = year - 2016
* Reghdfe
reghdfe log_depsumbr_r12 ///
persinc_r12 quest_hofri topcorp top_esttax top_incrate log_pop i.year, absorb(stnumbr) vce(cluster stnumbr#year)
coefplot, drop(_cons log_depsumbr_r12 persinc_r12 quest_hofri topcorp top_esttax top_incrate log_pop) vertical yline(0) levels(95)
*eventdd
eventdd log_depsumbr_r12 ///
persinc_r12 quest_hofri topcorp top_esttax top_incrate log_pop, ///
timevar(timeToTreat) graph_op(ytitle("Log Branch Level Deposits") ///
xlabel(-4(1)3)) method(hdfe, absorb(stnumbr) vce(cluster stnumbr#year)) inrange leads(4) lags(3)
Code:
* Example generated by -dataex-. For more info, type help dataex
clear
input float(log_depsumbr_r12 persinc_r12 quest_hofri) double(topcorp top_esttax) float(top_incrate log_pop) byte stnumbr float year long uninumbr
11.198833 1827194368 10.25 .0884 0 43.64 17.451637 6 2012 197317
10.399082 237812624 13.583333 .06968 0 37.82 15.695944 4 2012 277602
10.346488 254474448 15.416667 .065 9.5 34.98 15.680482 47 2012 357338
11.09252 236762640 7.25 .0463 0 38.010002 15.46295 8 2012 363833
11.845684 1049173952 9.916666 .071 16 40.73 16.789732 36 2012 428606
11.005934 66540872 15.416666 .08500000089406967 0 43.4 14.098637 33 2013 11263
13.620537 245227328 8.25 .046300001442432404 0 47.21 15.477688 8 2013 195938
11.35375 789184704 13.416667 .054999999701976776 0 43.39 16.788572 12 2013 289371
9.676985 369927904 13.75 .0689999982714653 0 48.97 16.102648 37 2013 357541
8.791045 188208320 8.166667 .07999999821186066 0 46.58 15.347212 22 2013 423308
9.850019 386817120 12.75 .05999999865889549 0 46.99 16.109539 26 2013 518633
9.033786 470860448 13.75 0 0 47.66 16.264763 39 2013 531789
. 481333152 13.75 0 0 47.6 16.267082 39 2014 211936
10.265052 65379020 11.583333 .06499999761581421 0 48.27 14.431004 54 2014 212159
11.297485 193243440 8.166667 .07999999821186066 0 46.58 15.351503 22 2014 231815
10.334745 396551648 12.75 .05999999865889549 0 46.99 16.111277 26 2014 233175
10.888033 396551648 12.75 .05999999865889549 0 46.99 16.111277 26 2014 237790
12.009887 311088160 11.916666 .08250000327825546 26 47.84 15.600592 24 2014 267964
10.55259 176396816 13.083333 .05000000074505806 0 48.55 15.389707 45 2014 290407
8.818259 1911013632 10.25 .08839999884366989 0 52.12 17.468418 6 2014 428753
11.353657 1229768832 10.416667 0 0 43.39 17.10998 48 2014 430934
10.611972 637068352 10 .0775 16 46.71 16.3696 17 2015 11753
. 1242254592 11.083334 0 0 43.39 17.128551 48 2015 360004
8.866914 258684528 13.583333 .06 0 47.12 15.737247 4 2015 447303
8.219564 192343504 8.166667 .08 0 46.58 15.356027 22 2015 534244
10.784465 1129725184 9.916666 .065 16 49.58 16.792894 36 2016 183481
11.33099 409154080 13.75 .04 0 47.84 16.134146 37 2016 185869
10.253937 1226140288 11.083334 0 0 43.39 17.144642 48 2016 188013
9.679642 425424576 13.75 .06 0 47.84 15.945842 51 2016 227407
8.341726 1226140288 11.083334 0 0 43.39 17.144642 48 2016 249058
9.552864 522099872 13.083333 .09 32 49.67 15.99859 34 2016 426505
10.974532 2098095360 10.25 .0884 0 52.13 17.482891 6 2016 445687
11.70103 949614336 13.416667 .055 0 43.39 16.858942 12 2017 14120
8.56325 161720288 11.75 .06 0 47.42 15.185066 40 2017 17416
9.608523 282592448 13.583333 .098 16 50.61 15.532777 27 2017 221983
11.602762 1181438976 9.916666 .065 16 49.58 16.790726 36 2017 261419
10.629284 1181438976 9.916666 .065 16 49.58 16.790726 36 2017 430915
10.433756 949614336 13.416667 .055 0 43.39 16.858942 12 2017 432420
9.417186 184696912 12.583333 .076 16 49.88 15.237967 41 2017 462027
11.052255 643511872 10 .0775 16 47.05 16.363384 17 2017 470543
12.17712 337389248 11.916666 .0825 26 46.55 15.61427 24 2018 11953
12.820665 1344420992 11.083334 0 0 40.8 17.169775 48 2018 16042
. 1344420992 11.083334 0 0 40.8 17.169775 48 2018 16254
10.05606 439585824 14.75 .06 0 46.55 15.95686 51 2018 212391
10.974466 2204399616 11.25 .0884 0 54.1 17.490227 6 2018 481362
12.493505 2265766656 . .0884 0 54.1 17.49023 6 2019 16963
10.904416 1375026560 . 0 0 40.8 17.18235 48 2019 33140
10.496861 666853632 . .095 16 45.75 16.354511 17 2019 422903
11.041176 551308544 . .115 16 49.77 16.00058 34 2019 481647
10.43661 197755072 . .08 0 44.58 15.354157 22 2019 570213
end
