gen avg_account_receivable= (netaccountsreceivable+lag_net_account_receivable)/2
* Example generated by -dataex-. To install: ssc install dataex clear input long stkcd int year float(netaccountsreceivable lag_net_account_receivable avg_account_receivable) 1 1990 . . . 1 1991 . . . 1 1992 . . . 1 1993 . . . 1 1994 244475184 . . 1 1995 309246048 244475184 276860608 1 1996 469556608 309246048 389401344 1 1997 534341664 469556608 501949120 1 1998 516883264 534341664 525612480 1 1999 378508704 516883264 447696000 1 2000 -396003232 378508704 -8747264 1 2001 11202902 -396003232 -192400160 1 2002 -762710976 11202902 -375754048 1 2003 -833153216 -762710976 -797932096 1 2004 -874245760 -833153216 -853699456 1 2005 -763604032 -874245760 -818924928 1 2006 . -763604032 . 1 2007 . . . 1 2008 15109592064 . . 1 2009 35209261056 15109592064 25159426048 1 2010 32229515264 35209261056 33719388160 1 2011 1.84321e+11 32229515264 108275253248 1 2012 99201843200 1.84321e+11 141761413120 1 2013 1.91714e+11 99201843200 145457922048 1 2014 2.56183e+11 1.91714e+11 2.239485e+11 1 2015 3.14259e+11 2.56183e+11 2.85221e+11 1 2016 4.19846e+11 3.14259e+11 3.670525e+11 1 2017 4.25209e+11 4.19846e+11 4.225275e+11 1 2018 . 4.25209e+11 . 2 1991 142333296 . . 2 1992 125544736 142333296 133939016 2 1993 158023472 125544736 141784096 2 1994 386629024 158023472 272326240 2 1995 650885952 386629024 518757504 2 1996 691276416 650885952 671081216 2 1997 775456832 691276416 733366656 2 1998 528862240 775456832 652159552 2 1999 535368512 528862240 532115392 2 2000 516286848 535368512 525827680 2 2001 477500384 516286848 496893632 2 2002 302297120 477500384 389898752 2 2003 365968992 302297120 334133056 2 2004 838037504 365968992 602003264 2 2005 1082277376 838037504 960157440 2 2006 1035615424 1082277376 1058946432 2 2007 864883008 1035615424 950249216 2 2008 922774848 864883008 893828928 2 2009 713191936 922774848 817983360 2 2010 1594024576 713191936 1153608192 2 2011 1514813824 1594024576 1554419200 2 2012 1886548480 1514813824 1700681216 2 2013 3078969856 1886548480 2482759168 2 2014 1894071808 3078969856 2486520832 2 2015 2510653184 1894071808 2202362368 2 2016 2075256832 2510653184 2292955136 2 2017 1432733952 2075256832 1753995392 2 2018 1586180736 1432733952 1509457408 3 1991 96595616 . . 3 1992 183449968 96595616 140022784 3 1993 389976800 183449968 286713376 3 1994 533173248 389976800 461575040 3 1995 652192256 533173248 592682752 3 1996 949415296 652192256 800803776 3 1997 710684608 949415296 830049920 3 1998 566756352 710684608 638720512 3 1999 711459392 566756352 639107840 3 2000 522822464 711459392 617140928 3 2001 344030464 522822464 433426464 4 1991 18389532 . . 4 1992 53118160 18389532 35753848 4 1993 203273392 53118160 128195776 4 1994 191898672 203273392 197586032 4 1995 279380832 191898672 235639744 4 1996 118328432 279380832 198854624 4 1997 126063984 118328432 122196208 4 1998 93838936 126063984 109951456 4 1999 55299972 93838936 74569456 4 2000 222196064 55299972 138748016 4 2001 31434708 222196064 126815384 4 2002 62747196 31434708 47090952 4 2003 88416992 62747196 75582096 4 2004 98330824 88416992 93373904 4 2005 76457512 98330824 87394168 4 2006 62786196 76457512 69621856 4 2007 7229633 62786196 35007916 4 2008 4995476 7229633 6112554 4 2009 6860687 4995476 5928081 4 2010 4296549.5 6860687 5578618 4 2011 4540338 4296549.5 4418444 4 2012 8129105 4540338 6334721 4 2013 3760743 8129105 5944924 4 2014 2742071 3760743 3251407 4 2015 1726513.8 2742071 2234292.5 4 2016 1706211 1726513.8 1716362.5 4 2017 9456606 1706211 5581409 4 2018 27268320 9456606 18362464 5 1992 155349056 . . 5 1993 166755648 155349056 161052352 5 1994 200326880 166755648 183541264 5 1995 127329032 200326880 163827952 end
. net sj 13-1 st0236_2 . net install st0236_2 // INSTALLATION FILES . net get st0236_2 // ANCILLARY FILES, including dlsy_khb.dta and khb.do
. use dlsy_khb.dta
. khb logit univ fses || abil intact boy, disentangle summary verbose
(omitted)
Logistic regression Number of obs = 1,896
LR chi2(4) = 216.87
Prob > chi2 = 0.0000
Log likelihood = -468.31516 Pseudo R2 = 0.1880
------------------------------------------------------------------------------
univ | Coef. Std. Err. z P>|z| [95% Conf. Interval]
-------------+----------------------------------------------------------------
fses | .3817324 .0778061 4.91 0.000 .2292353 .5342295
abil | 1.065516 .106775 9.98 0.000 .8562405 1.274791
intact | 1.08391 .7386558 1.47 0.142 -.3638292 2.531648
boy | .9821406 .1848351 5.31 0.000 .6198704 1.344411
_cons | -4.462997 .7479123 -5.97 0.000 -5.928878 -2.997116
------------------------------------------------------------------------------
(omitted)
Logistic regression Number of obs = 1,896
LR chi2(4) = 216.87
Prob > chi2 = 0.0000
Log likelihood = -468.31516 Pseudo R2 = 0.1880
------------------------------------------------------------------------------
univ | Coef. Std. Err. z P>|z| [95% Conf. Interval]
-------------+----------------------------------------------------------------
fses | .5805281 .0786111 7.38 0.000 .4264531 .7346031
__000001 | 1.065516 .106775 9.98 0.000 .8562405 1.274791
__000002 | 1.08391 .7386558 1.47 0.142 -.3638292 2.531648
__000003 | .9821406 .1848351 5.31 0.000 .6198704 1.344411
_cons | -2.945969 .124697 -23.63 0.000 -3.190371 -2.701568
------------------------------------------------------------------------------
Decomposition using the KHB-Method
Model-Type: logit Number of obs = 1896
Variables of Interest: fses Pseudo R2 = 0.19
Z-variable(s): abil intact boy
------------------------------------------------------------------------------
univ | Coef. Std. Err. z P>|z| [95% Conf. Interval]
-------------+----------------------------------------------------------------
fses |
Reduced | .5805281 .0786111 7.38 0.000 .4264531 .7346031
Full | .3817324 .0778061 4.91 0.000 .2292353 .5342295
Diff | .1987956 .0359394 5.53 0.000 .1283557 .2692355
------------------------------------------------------------------------------
Summary of confounding
Variable | Conf_ratio Conf_Pct Resc_Fact
-------------+-------------------------------------
fses | 1.5207722 34.24 1.1317064
---------------------------------------------------
Components of Difference
Z-Variable | Coef Std_Err P_Diff P_Reduced
-------------+---------------------------------------------
fses |
abil | .1661177 .0301003 83.56 28.61
intact | .020142 .0144611 10.13 3.47
boy | .0125359 .011524 6.31 2.16
-----------------------------------------------------------
gen temp123=1
levelsof temp123, local(123)
foreach id of local 123{
by ticker: egen s2_short_`id' = sd(logret) if estimation_window_short`id'==1
by ticker: egen L_short_`id' = count(logret) if estimation_window_short`id'==1
by ticker: egen aRM_short_`id' = mean(logret) if estimation_window_short`id'==1
by ticker: egen R_short_`id' = max(logret) if eventid==`id' &estimation_window_short`id'==1
}
foreach id of local 123{
by ticker: gen Rsum_short_t_`id' = logret-aRM_short_`id' if estimation_window_short`id'==1
}
foreach id of local 123{
by ticker: egen Rsum_short_`id' = sum(Rsum_short_t_`id'^2) if estimation_window_short`id'==1
}
foreach id of local 123{
drop Rsum_short_t_`id'
}
//3.10.1.2 Part-by-part calculation of statistic
//(Rmt-ARm)^2
foreach id of local 123{
gen part1_s_`id' = R_short_`id'- aRM_short_`id' if estimation_window_short`id'==1
replace part1_s_`id' = part1_s_`id'^2 if estimation_window_short`id'==1
}
//(Rmt-ARm)^2/sum(Rmt-ARm)^2
foreach id of local 123{
gen part2_s_`id' = part1_s_`id'/Rsum_short_`id' if estimation_window_short`id'==1
}
//1+(1/L)+(part2)
foreach id of local 123{
gen part3_s_`id' = 1+(1/L_short_`id')+part2_s_`id' if estimation_window_short`id'==1
}
//s2(part3)^0.5
foreach id of local 123{
gen part4_s_`id' = sqrt(s2_short_`id'*part3_s_`id') if estimation_window_short`id'==1
}
foreach id of local 123{
by ticker: replace part4_s_`id' = part4_s_`id'[_n-1] if missing(part4_s_`id')&event_window_short`id'==1
}
//3.10.1.3 Standardize abnormal returns Patell short
foreach id of local 123{
gen AR_sd_s_pat`id' =. if estimation_window_short`id'==1
}
foreach id of local 123{
replace AR_sd_s_pat`id' = abnormal_return_short`id'/part4_s_`id' if event_window_short`id'==1
}
//3.10.1.4 Drop variables
foreach id of local 123{
drop R_short_`id' aRM_short_`id' L_short_`id' s2_short_`id' part1_s_`id' part2_s_`id' part3_s_`id' part4_s_`id'
}
save temp11.dta, replace
//3.10.2 Cummulate standardized Patell abnormal returns short
use temp11.dta, clear
foreach id of local 123 {
by ticker: egen CAR_pat_t_s`id'= sum(AR_sd_s_pat`id') if event_window_short`id'==1
}
foreach id of local 123 {
by ticker: gen CAR_pat_s`id' = CAR_pat_t_s`id'*(1/(sqrt(3))) if event_window_short`id'==1
}
//3.10.3 Derive Patell Z-statistic
foreach id of local 123 {
egen CAAR_P_s`id'= mean(CAR_pat_s`id') if eventid==`id'
}
foreach id of local 123 {
egen No_CAAR_P_s`id'= count(CAAR_P_s`id')
replace No_CAAR_P_s`id'= sqrt(No_CAAR_P_s`id')
}
foreach id of local 123 {
gen test_P_s`id'= CAAR_P_s`id'* No_CAAR_P_s`id'
}
drop if STORY> 10
foreach id of local temp {
stack cum_abnormal_return_short`id', into(cum_abnormal_return_short)
stack cum_abnormal_return_med`id', into(cum_abnormal_return_med)
stack cum_abnormal_return_long`id', into(cum_abnormal_return_long)
}
year month 2006 Jan 2006 Feb 2006 Mar 2006 Apr 2006 May 2006 Jun 2006 Jul 2006 Aug 2006 Sep 2006 Oct 2006 Nov 2006 Dec 2007 Jan 2007 Feb 2007 Mar 2007 Apr 2007 May 2007 Jun 2007 Jul --------- --------- 2019 Mar 2019 Apr
| id | wave | score |
| 1 | 1 | 3 |
| 1 | 2 | |
| 1 | 3 | |
| 1 | 4 | |
| 2 | 1 | 1 |
| 2 | 2 | |
| 2 | 3 | |
| 2 | 4 | |
| 3 | 1 | 2 |
| 3 | 2 | |
| 3 | 3 | |
| 3 | 4 |
| id | wave | score |
| 1 | 1 | 3 |
| 1 | 2 | 3 |
| 1 | 3 | 3 |
| 1 | 4 | 3 |
| 2 | 1 | 1 |
| 2 | 2 | 1 |
| 2 | 3 | 1 |
| 2 | 4 | 1 |
| 3 | 1 | 2 |
| 3 | 2 | 2 |
| 3 | 3 | 2 |
| 3 | 4 | 2 |
ppml permits_all lgdp_o lgdp_d ldist contig comlang_off colony comcol market_test shortage_list point_system job_offer dFE_ot*, cluster(dist)
ppml permits_all lgdp_o lgdp_d ldist contig comlang_off colony comcol market_test shortage_list point_system job_offer dFE_ot*, cluster(dist)
ppmlhdfe permits_all lgdp_o lgdp_d ldist contig comlang_off colony comcol market_test shortage_list point_system job_offer, a(i.origin#i.year)
* Example generated by -dataex-. To install: ssc install dataex clear input int id str24 institution str17 var1a str36 var2a str17 var1b str36 var2b 43 "hus 1" "1 kvinde" "Bil" "1 kvinde" "Bil" 44 "hus 2" "1 mand" "Bil" "1 kvinde" "Bil" end
| id | institution | var1 | var | |
| 43-1 | hus1 | 1 kvinde | Bil | |
| 43-2 | hus1 | 1 kvinde | Bil | |
| 44-1 | hus2 | 1 mand | Bil | |
| 44-2 | hus2 | 1 kvinde | Bil | |