Dear all,
I'm trying to implement a staggered diff-in-diff estimation model with time variation of treatment effects.
My dataset is a sample of firms which receive a treatment in different point in time (2009q2; 2010q2; 2011q3). As a result I have three different cohorts.
I try to estimate the average treatment effects across cohort by using the -csdid- command.
where -ESGScore- is my outcome of interest and from -size- to -cur_rat- I have my control variables.
I identified the treatment period of each observation with a variable -first_treat- (i.e. a variable that tells me the first time the firm has been treated. Then I carry backward and forward that identification date value across the panel)
There is the option -notyet- because I don't have firms never treated. Throughout the time, all firms receive the treatment.
The issue is that when I run the -csdid- command as above I have this outcome
I'm wondering why I don't have the ATT for the third cohort?
It's the first time that I implement -csdid- so it might be that I'm missing something.
FernandoRios , I kindly ask your specific help regarding this command. In case you have any advice. Many thanks
Below, an example of my dataset
I'm trying to implement a staggered diff-in-diff estimation model with time variation of treatment effects.
My dataset is a sample of firms which receive a treatment in different point in time (2009q2; 2010q2; 2011q3). As a result I have three different cohorts.
I try to estimate the average treatment effects across cohort by using the -csdid- command.
Code:
csdid ESGScore size lev mtb roa cash divid capex ppeg salesgr cfo cur_rat, ivar(cusip_id) time(calendar_qtr) gvar(first_treat) method(dripw) agg(group) notyet
I identified the treatment period of each observation with a variable -first_treat- (i.e. a variable that tells me the first time the firm has been treated. Then I carry backward and forward that identification date value across the panel)
There is the option -notyet- because I don't have firms never treated. Throughout the time, all firms receive the treatment.
The issue is that when I run the -csdid- command as above I have this outcome
I'm wondering why I don't have the ATT for the third cohort?
It's the first time that I implement -csdid- so it might be that I'm missing something.
FernandoRios , I kindly ask your specific help regarding this command. In case you have any advice. Many thanks
Below, an example of my dataset
Code:
* Example generated by -dataex-. For more info, type help dataex clear input float(cusip_id calendar_qtr first_treat) double ESGScore float(size lev mtb roa cash divid capex ppeg salesgr cfo cur_rat) 1717 162 205 . . . . . . . . . . . . 11056 162 205 . 3.0105224 .4631491 .7113667 .015842067 . 0 .00536193 .33360955 . .04245674 5.506432 1739 162 205 . . . . . . . . . . . . 8859 162 201 . 8.62513 .7456099 1.0718229 .04286504 .004225761 . . .4906725 . . .7566832 12521 162 201 . 8.162637 .619559 1.221232 .015227363 . .03144017 .0002506643 . . .04467605 . 1164 162 201 . 8.13088 .4730813 . .05778094 . 0 .2217634 .4594994 . .18458244 2.0917983 1175 162 205 . 4.173787 .3289204 . .03358446 . 0 .02935383 .3935253 . .06627988 3.96497 9260 162 205 . 2.704042 .5056225 .6171811 .005174821 . 0 .002451231 .14026487 . -.11779526 2.2012725 14174 162 205 . 5.06636 .11009105 . . . . . .015422817 . . 9.636494 14200 162 205 . 3.105349 .6173321 . . . . . . . . 1.1057146 9945 162 205 . 5.855665 .15575 8.135866 .068892 . 0 .1812927 .2055621 . .09153683 4.6512103 587 162 205 . 3.711472 .37979665 3.1304395 .0898808 . .05098499 .0821202 .715369 . .19728632 .8949946 9997 162 201 . 7.866638 .6269057 1.749897 .03871606 . 0 .04337056 .7740817 . .02071698 1.0839332 11513 162 205 . 6.877117 .4362587 .748989 .032063063 . .01945813 .05802334 .3525617 . .07519276 4.0344753 9259 162 205 . 3.795062 .3298037 16.075735 -.03816701 . 0 .07696964 .20312357 . -.08795665 3.764005 8844 162 205 . 2.6732516 .13991855 14.266404 -.21031325 . 0 .04028916 .09953414 . -.4303293 5.281697 12715 162 201 . 7.439071 .5233025 2.997776 .04575763 . 0 .04437522 .5338311 . .09541574 1.867141 46 162 205 . 5.228635 .51341283 .3716462 .014444145 . 0 .02695837 .2155185 . -.04494345 3.3292935 12419 162 201 . 6.66012 .50464934 7.361979 . . 0 .06817951 .11048158 . .09261508 11.602832 34 162 197 . 10.542812 .8917265 . . . .0016093288 .0003650682 .012803463 . .06813737 . 3675 162 205 . 6.848838 1.2323043 -.10860642 .035465416 . 0 .02462749 .4441699 . -.024314225 .440455 2033 162 205 . . . . . . . . . . . . 13699 162 205 . 4.426916 .18440835 2.564921 .06692289 . .04288122 .12341386 .6097121 . .1761591 2.0984213 4058 162 205 . . . . . . . . . . . . 1919 162 201 . 4.7281575 .2575716 1.923916 .04228651 . 0 .0430421 .23365587 . .13199757 3.2869086 6458 162 205 . 4.1067176 .16338256 4.243679 . . 0 . . . . 10.959726 8486 162 205 . 8.215322 .8661453 .5165787 .003758709 . 0 0 . . .031744014 . 10724 162 197 . 8.531191 .6274631 6.006215 .08447158 . .026995275 .011597147 .0897523 . .062948704 1.234882 2581 162 201 . 5.238759 .2012991 . -.0752723 . .036070604 .02975597 .13280527 . -.2649679 6.629703 10648 162 201 . 5.75483 .7425249 5.473234 .025786527 . .014342185 .03682316 .15699776 . .009051853 .8510608 12678 162 205 . 4.434263 .653565 .8863738 .02470279 . .003559141 .3006789 .8259319 . .072833546 1.1629992 1337 162 201 . 9.106756 .9282521 . .007620651 . . . .01440397 . . . 3198 162 201 . 7.757931 .7649482 1.4821112 . . 0 . . . . 2.078471 5834 162 205 . 5.759567 .9768072 11.532588 .06460729 . 0 .13065045 .36967105 . .15164465 1.0966895 5108 162 205 . 4.5645356 .3067758 2.7874644 . . .008321356 0 .13271536 . .025594866 6.60692 13071 162 205 . 12.37916 .13760704 . . . .0024313966 . . . . 2.8421924 11593 162 205 . 6.30232 .45427665 .7767091 .01904036 . 0 .03044014 .08789437 . .031968992 . 9263 162 201 . 6.812297 .8049421 1.7725058 . . 0 .030814227 .16160735 . .033687662 .7496 13395 162 205 . 2.6333985 .6786869 1.2308283 .0003037091 . 0 .020348506 .40089595 . -.07600319 1.350954 9546 162 205 . 6.476024 .4984447 1.1509856 . . .029897565 0 . . .04434728 . 1659 162 205 . 4.7577195 .6188101 .9081094 . . 0 .037056535 .07787094 . .04095136 .9433692 2322 162 205 . 2.643476 .3424833 2.990266 .08122823 . 0 .27025262 .8042973 . .2058653 .7517867 13243 162 205 . 7.73761 .8888881 . .006204254 . . . .023673635 . . . 5188 162 205 . 2.994682 .29210672 1.213931 . . .01271335 .07972 .1431737 . .13642544 2.9362576 3438 162 205 . 6.828034 .3519917 .4338639 .004468592 . .003822936 .010060942 .08432043 . -.012189472 6.9703 9427 162 201 . 6.643393 .6584359 1.2362876 .05746971 . .003998984 .02366424 .15320566 . -.07404339 2.653811 3770 162 201 . 9.0050955 .6633481 .26874313 .01241984 . .0013632543 .019495707 .4431586 . .06189856 2.622879 9581 162 197 . 7.828397 .7530326 26.788557 . . .008894811 . . . . 1.281754 2667 162 205 . 3.6121604 .17224532 1.008657 .02235173 . 0 .15802537 .8907233 . .1531985 .7158753 3932 162 205 . 4.482539 .17989124 11.33462 . . 0 . . . . 9.37874 14037 162 201 . 7.387352 .53192043 . .015370923 . . . .1696113 . -.030758677 2.2761872 974 162 201 . 7.723332 .9060549 1.7971756 .027491193 . .002912656 .0453355 .6345334 . .0559465 .7412569 12524 162 205 . 3.743107 .59336 .52703524 .035620376 . 0 .028795475 .2877444 . .0045577255 1.2576902 2571 162 205 . 6.852143 .9293576 . .005834902 . . . .00934154 . . . 1443 162 205 . 5.951715 .9150001 . .007750934 . . . .00660627 . . . 3408 162 205 . 6.271638 .4457461 2.9025304 -.019497063 . 0 .035430104 .05385209 . -.16560484 .8616663 5957 162 205 . 4.507513 .6776925 .466954 . . .013550763 0 . . .02859717 . 8446 162 205 . 5.285202 .4745585 1.1768849 .037130747 . 0 .00707847 .3081957 . .032699835 2.160521 1141 162 205 . 5.921552 .7912357 .5751466 .007918614 . 0 .0007515415 . . .027165206 . 7544 162 201 . 6.965368 .58405936 1.241557 .05857951 . .003732636 0 .002900473 . -.1058328 . 436 162 201 . 6.88442 .440017 1.44608 .05432484 . .01505832 .04132806 .4961309 . .12363583 2.1880116 4978 162 201 . 8.050263 .7506707 2.076004 .005598946 . .016633265 .029401524 .3834697 . .06047234 1.0191048 13707 162 205 . . . . . . . . . . . . 13675 162 201 . 7.897913 .39870235 3.402879 .012273638 . 0 .009722014 .08291313 . -.0035975776 3.2802854 10964 162 201 . 7.023561 .518668 1.2096968 .02233472 . 0 .04135999 .4675177 . .03544647 4.574239 10093 162 205 . 6.305129 .471418 .782564 . . .00720351 0 . . -.00596372 . 11337 162 205 . 7.410995 .7319922 .7743193 .03777938 . 0 .034622397 .04344322 . .033685092 1.3464807 13249 162 205 . 7.221001 .9125662 . .007194922 . . . .02149165 . . . 4198 162 205 . 3.3755376 .28491792 .3518007 .0043157474 . .006155951 .0011741372 .05137644 . .014533915 4.3837533 732 162 205 . 4.5149827 .397194 1.2969925 . . 0 .010129306 .1952987 . -.014280494 1.5158124 11578 162 201 . 6.385208 .6623705 2.8389156 .03895241 . 0 .013462705 .12511168 . .00923026 1.945245 5893 162 201 . 5.562119 .28088441 2.169961 .05933297 . 0 .09353508 .3205304 . .13554703 3.0176916 13421 162 201 . 6.294731 .4023943 . .04392084 . .008028281 .01283258 .1857562 . .0004599624 7.187948 4223 162 205 . 5.441361 .6495086 .4331991 .02476634 . 0 .008904751 .04206346 . -.01494726 8.289263 6199 162 205 . 4.494149 .5417691 .3893615 -.005367978 . 0 .019780183 .16510597 . -.08183184 1.9310915 13054 162 205 . 7.55017 .4177435 14.46652 . . 0 .0481617 .07594889 . .08158159 12.429214 6569 162 205 . 7.423398 .56440765 .3035601 .001631431 . 0 .016265452 .14221278 . -.05344993 1.9992297 12735 162 201 . 5.091238 .2245635 1.205927 .04541375 . 0 .15754615 .5567563 . .02309992 2.140835 6753 162 197 . 7.870612 .6304586 2.0374057 .02610851 . 0 .04508202 .29051316 . .04256862 1.0186433 316 162 201 . 5.853739 .5563602 5.402216 .0716973 . 0 .07364646 .20568693 . .06756282 2.0663385 4041 162 205 . 4.448259 .5651396 1.0544198 .05695616 . .0140504 .04614978 .3237584 . .09081939 2.964731 5259 162 205 . 2.854399 .2457959 .5927383 . . 0 . . . . 2.2770822 7741 162 201 . 8.571537 .8691546 1.6089678 -.0023134442 . 0 0 . . .004926193 . 7368 162 205 . 4.826985 .3558085 .8512877 .04409377 . .01668616 .01440713 .11592212 . .09514061 1.8995655 10629 162 205 . 3.146477 .07228864 1.5158473 -.05944825 . 0 .02832066 .4630596 . -.1507363 7.144557 12621 162 197 . . . . . . . . . . . . 12696 162 205 . 6.010247 .9454836 . .0005598032 . . . .02612173 . . . 3697 162 205 . . . . . . . . . . . . 11184 162 205 . 7.531128 .9091008 . .006744571 . . . .025511524 . . . 8742 162 197 . 10.93184 .8598354 . . . 0 . . . . .9038271 3661 162 201 . 5.73094 .6185642 2.733001 .10139057 . 0 .209624 .8383147 . .23396015 1.1346033 701 162 205 . . . . . . . . . . . . 11136 162 205 . 4.819103 .08451887 . .005709975 . 0 . .04653144 . -.06785462 10.41054 784 162 205 . 6.15765 .6076004 1.3874477 .012658502 . 0 .02961791 .18544045 . .021340284 . 6453 162 205 . 6.564983 .59213865 .3433312 .04712852 . 0 .0068673 .1147243 . .1561974 1.496805 5902 162 201 . 5.498815 .59454095 .5059047 -.0004755178 . .0247052 .04577359 .6914109 . -.01880493 .55671304 4196 162 205 . 5.700333 .23847783 1.2275796 . . 0 . . . . . 3959 162 205 . 3.382524 .6298523 . . . . . . . . . 10639 162 205 . 1.3467736 .28582576 2.5967884 -.05470175 . 0 .021099245 .167752 . -.14665277 1.8935395 7253 162 205 . . . . . . . . . . . . end format %tq calendar_qtr format %tq first_treat
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