Hi everyone,
I am new to this forum and I'm hoping that someone can help me. I have a sample of firms with secondary listings for which I have data for the years before and after the cross-listing (i.e. in the example below for variable "YEAR", -1 stands for the year before the listing, +1 stands for the year after the listing). I am trying to make a new variable which includes matched-adjusted measures based on control firms that best reflect the cross-listed firms based on pre-listing characteristics at "YEAR" -1. The control firms that I need to match to the cross-listed firms should, at the time of "YEAR" -1 (i.e. prelisting), have the same first two digits of the SIC code, should be in the same home country, and should have total assets of between 80%-120% of the cross-listed firms. The fiscal year ends also need to be similar.
So for example, there is 1 firm that cross-listed in year 2001, and there are 5 firms that meet the characteristics as described above in year 2000. For year 2001 and thereafter, I want to know their mean ROA in order to calculate the difference between the cross-listed firm and similar non-cross-listed firms. Thus, I want to know their mean ROA in 2001, in 2002, in 2003, etc.
I would be really grateful if anyone could tell me how I could solve this. Thank you very much in advance!
I am new to this forum and I'm hoping that someone can help me. I have a sample of firms with secondary listings for which I have data for the years before and after the cross-listing (i.e. in the example below for variable "YEAR", -1 stands for the year before the listing, +1 stands for the year after the listing). I am trying to make a new variable which includes matched-adjusted measures based on control firms that best reflect the cross-listed firms based on pre-listing characteristics at "YEAR" -1. The control firms that I need to match to the cross-listed firms should, at the time of "YEAR" -1 (i.e. prelisting), have the same first two digits of the SIC code, should be in the same home country, and should have total assets of between 80%-120% of the cross-listed firms. The fiscal year ends also need to be similar.
So for example, there is 1 firm that cross-listed in year 2001, and there are 5 firms that meet the characteristics as described above in year 2000. For year 2001 and thereafter, I want to know their mean ROA in order to calculate the difference between the cross-listed firm and similar non-cross-listed firms. Thus, I want to know their mean ROA in 2001, in 2002, in 2003, etc.
I would be really grateful if anyone could tell me how I could solve this. Thank you very much in advance!
Code:
* Example generated by -dataex-. To install: ssc install dataex clear input float(id fy_end) str16 home_country float(list_dt YEAR) str16 host_country int SIC double assets float ROA 1 13148 "UNITED STATES" 14620 -5 "GERMANY" 3443 54342 . 1 13514 "UNITED STATES" 14620 -4 "GERMANY" 3443 64816 . 1 13879 "UNITED STATES" 14620 -3 "GERMANY" 3443 84052 .04358016 1 14244 "UNITED STATES" 14620 -2 "GERMANY" 3443 116790 .06372121 1 14609 "UNITED STATES" 14620 -1 "GERMANY" 3443 178392 .08801964 1 14975 "UNITED STATES" 14620 0 "GERMANY" 3443 279960 .11109801 1 15340 "UNITED STATES" 14620 1 "GERMANY" 3443 376506 .10770877 1 15705 "UNITED STATES" 14620 2 "GERMANY" 3443 460890 .09567142 1 16070 "UNITED STATES" 14620 3 "GERMANY" 3443 515080 .08723305 1 16436 "UNITED STATES" 14620 4 "GERMANY" 3443 592146 .0926562 1 16801 "UNITED STATES" 14620 5 "GERMANY" 3443 704957 .107686 1 17166 "UNITED STATES" 14620 6 "GERMANY" 3443 900030 .1105852 1 17531 "UNITED STATES" 14620 7 "GERMANY" 3443 1028851 .10546523 1 17897 "UNITED STATES" 14620 8 "GERMANY" 3443 1798857 .07963835 1 18262 "UNITED STATES" 14620 9 "GERMANY" 3443 1754039 .06654527 1 18627 "UNITED STATES" 14620 10 "GERMANY" 3443 1716317 .05474105 1 18992 "UNITED STATES" 14620 11 "GERMANY" 3443 1708051 .05764289 1 19358 "UNITED STATES" 14620 12 "GERMANY" 3443 1727560 .05893978 1 19723 "UNITED STATES" 14620 13 "GERMANY" 3443 1677374 .064430475 1 20088 "UNITED STATES" 14620 14 "GERMANY" 3443 2103174 .04909151 1 20453 "UNITED STATES" 14620 15 "GERMANY" 3443 1979222 .06290856 1 20819 "UNITED STATES" 14620 16 "GERMANY" 3443 2004894 .05941611 1 21184 "UNITED STATES" 14620 17 "GERMANY" 3443 2073407 .05437331 1 21549 "UNITED STATES" 14620 18 "GERMANY" 3443 2005064 .06965812 4 13148 "UNITED STATES" . . "" 2086 3418716 .06788923 4 13514 "UNITED STATES" . . "" 2086 4780748 .05249178 4 13879 "UNITED STATES" . . "" 2086 6094975 .05417676 4 14244 "UNITED STATES" . . "" 2086 5165892 .06159072 4 14609 "UNITED STATES" . . "" 2086 5693226 .04699972 4 14975 "UNITED STATES" . . "" 2086 4872353 .05373235 4 15340 "UNITED STATES" . . "" 2086 3228608 .05093681 4 15705 "UNITED STATES" . . "" 2086 3316627 .0506786 4 16070 "UNITED STATES" . . "" 2086 4326118 .05055572 4 16436 "UNITED STATES" . . "" 2086 4589734 .06068325 4 16801 "UNITED STATES" . . "" 2086 3848592 .07949453 4 17166 "UNITED STATES" . . "" 2086 4251210 .08920801 4 17531 "UNITED STATES" . . "" 2086 4066916 .1211793 4 17897 "UNITED STATES" . . "" 2086 3504467 .15714344 4 18262 "UNITED STATES" . . "" 2086 4999753 .12179302 4 18627 "UNITED STATES" . . "" 2086 5389783 .14254451 4 18992 "UNITED STATES" . . "" 2086 6164592 .14513743 4 19358 "UNITED STATES" . . "" 2086 6987519 .13453545 4 19723 "UNITED STATES" . . "" 2086 5895089 .065596804 4 20088 "UNITED STATES" . . "" 2086 4934456 .09805194 4 20453 "UNITED STATES" . . "" 2086 4852534 .1068788 4 20819 "UNITED STATES" . . "" 2086 4670643 .09908614 4 21184 "UNITED STATES" . . "" 2086 4724564 .11761403 4 21549 "UNITED STATES" . . "" 2086 4352829 .11175652 5 20635 "CANADA" 20919 -1 "GERMANY" 7812 2831 -2.854115 5 21000 "CANADA" 20919 0 "GERMANY" 7812 4873 -1.4005746 5 21365 "CANADA" 20919 1 "GERMANY" 7812 5301 -1.3310696 6 13879 "UNITED STATES" 15384 -5 "GERMANY" 8741 52562 .03439747 6 14244 "UNITED STATES" 15384 -4 "GERMANY" 8741 40445 .028582025 6 14609 "UNITED STATES" 15384 -3 "GERMANY" 8741 43150 .035874855 6 14975 "UNITED STATES" 15384 -2 "GERMANY" 8741 39842 .02010441 6 15340 "UNITED STATES" 15384 -1 "GERMANY" 8741 34408 -.09462915 6 15705 "UNITED STATES" 15384 0 "GERMANY" 8741 28139 -.01012829 6 16070 "UNITED STATES" 15384 1 "GERMANY" 8741 20656 .04875097 7 13330 "UNITED STATES" 15029 -5 "GERMANY" 2836 11392 -.5019312 7 13695 "UNITED STATES" 15029 -4 "GERMANY" 2836 4207 -1.848348 7 14060 "UNITED STATES" 15029 -3 "GERMANY" 2836 2133 -1.0656352 7 14425 "UNITED STATES" 15029 -2 "GERMANY" 2836 249 -15.016065 7 14791 "UNITED STATES" 15029 -1 "GERMANY" 2836 8683 -.377289 7 15156 "UNITED STATES" 15029 0 "GERMANY" 2836 11458 .0899808 7 15521 "UNITED STATES" 15029 1 "GERMANY" 2836 7665 -.6067841 7 15886 "UNITED STATES" 15029 2 "GERMANY" 2836 4813 -.5879909 7 16252 "UNITED STATES" 15029 3 "GERMANY" 2836 21384 -.11284138 7 16617 "UNITED STATES" 15029 4 "GERMANY" 2836 17470 -.7624499 7 16982 "UNITED STATES" 15029 5 "GERMANY" 2836 22499 -.7305658 7 17347 "UNITED STATES" 15029 6 "GERMANY" 2836 10921 -1.4285322 7 17713 "UNITED STATES" 15029 7 "GERMANY" 2836 43187 -.386621 7 18078 "UNITED STATES" 15029 8 "GERMANY" 2836 24660 .14939173 7 18443 "UNITED STATES" 15029 9 "GERMANY" 2836 2580 . 8 18262 "UNITED STATES" 20045 -5 "MEXICO" 1422 3239283 .0554064 8 18627 "UNITED STATES" 20045 -4 "MEXICO" 1422 3074743 .06158824 8 18992 "UNITED STATES" 20045 -3 "MEXICO" 1422 3147822 .0579102 8 19358 "UNITED STATES" 20045 -2 "MEXICO" 1422 3160926 .04943583 8 19723 "UNITED STATES" 20045 -1 "MEXICO" 1422 3259826 .06560657 8 20088 "UNITED STATES" 20045 0 "MEXICO" 1422 7464392 .0473066 8 20453 "UNITED STATES" 20045 1 "MEXICO" 1422 6961732 .07008026 8 20819 "UNITED STATES" 20045 2 "MEXICO" 1422 7300905 .09053138 8 21184 "UNITED STATES" 20045 3 "MEXICO" 1422 8992511 .0788455 8 21549 "UNITED STATES" 20045 4 "MEXICO" 1422 9551419 .0718242 9 13179 "UNITED STATES" 15316 -5 "GERMANY" 3552 47751 .2413143 9 13545 "UNITED STATES" 15316 -4 "GERMANY" 3552 83625 .18593723 9 13910 "UNITED STATES" 15316 -3 "GERMANY" 3552 114539 .13377976 9 14275 "UNITED STATES" 15316 -2 "GERMANY" 3552 106302 .014684577 9 14640 "UNITED STATES" 15316 -1 "GERMANY" 3552 21346 -.4457978 9 15006 "UNITED STATES" 15316 0 "GERMANY" 3552 54030 -.1588932 9 15371 "UNITED STATES" 15316 1 "GERMANY" 3552 38279 -.29023746 9 15736 "UNITED STATES" 15316 2 "GERMANY" 3552 36002 -.06505194 9 16101 "UNITED STATES" 15316 3 "GERMANY" 3552 30346 -.11062413 9 16465 "UNITED STATES" 15316 4 "GERMANY" 3552 26626 -.067866 9 16829 "UNITED STATES" 15316 5 "GERMANY" 3552 26354 .02917963 9 17166 "UNITED STATES" 15316 5 "GERMANY" 3552 27188 .08573636 9 17531 "UNITED STATES" 15316 6 "GERMANY" 3552 29300 .06484642 9 17897 "UNITED STATES" 15316 7 "GERMANY" 3552 21030 -.29448408 11 13875 "UNITED STATES" 15652 -5 "GERMANY" 5200 223370 .10552894 11 14239 "UNITED STATES" 15652 -4 "GERMANY" 5200 263223 .10850876 11 14610 "UNITED STATES" 15652 -2 "GERMANY" 5200 301631 .1167486 end format %tddd/nn/CCYY fy_end format %tddd/nn/CCYY LD2 label var id "group(DSCD)" label var fy_end "date of fiscal year end" label var home_country "Country of home market" label var list_dt "cross-listing date" label var host_country "country of first cross-listings" label var SIC "sic code" label var assets "total assets"
