Dear members
I would like to regress a dependent variable (annual_report) that is binary over the independent variable (DID treatment) using either the logit or probit model while controlling for firm FE, industryxyear FE, and clustering at the firm_id.
Here is an example of my data:
input float(annual_report treatedxmandate log_assets profit_assets leverage pay_dividends firm_id indyear)
0 0 21.902086 .010306734 .2206007 1 1 107
0 0 21.82287 .023236906 .18649498 1 1 108
0 0 21.74963 -.07548836 .18513305 0 1 109
0 0 21.98201 .0443056 .25447315 0 2 71
0 0 22.00753 .034606867 .22314507 0 2 72
0 0 22.087317 .03733062 .2349182 0 2 73
0 0 22.049013 -.023373174 .2260292 0 2 74
0 0 22.05352 .02194606 .2065045 1 2 75
0 0 21.87605 -.05904642 .13072309 1 2 76
0 0 21.88704 .04903185 .142411 1 2 77
0 0 23.599426 .12391525 .24721064 1 3 63
0 0 23.833174 .16548464 .26696107 1 3 64
0 0 24.04246 .18731457 .19777484 1 3 65
0 0 24.1709 .17173678 .1683602 1 3 66
0 0 24.22247 .09537913 .16561395 1 3 67
0 0 24.67002 .08242703 .156451 1 3 68
0 0 24.73425 .08653829 .17979747 1 3 69
0 0 24.84307 .08874518 .1889613 1 3 70
0 0 24.92945 .10032787 .19636364 1 3 71
1 0 24.926525 .08128064 .1992407 1 3 72
1 0 24.942846 .03046835 .2793765 1 3 73
1 0 25.07941 -.02164041 .2516291 1 3 74
1 0 24.99975 -.01985081 .25280952 1 3 75
1 0 24.97898 .03032323 .22765115 1 3 76
1 0 24.754173 -.18001492 .271594 1 3 77
0 0 20.86467 .0745382 .14186156 1 4 345
0 0 20.912657 .1161205 .1727725 1 4 346
0 0 20.627867 .08729772 .1882192 1 4 347
0 0 20.56115 .13791901 .0772841 1 4 348
0 0 20.440073 .16702846 .28794026 1 4 349
0 0 21.13426 .10510793 .29772565 1 4 350
1 0 14.44674 .07748583 .28516528 1 5 784
1 0 14.627494 .07080033 .02303519 1 5 785
1 0 13.5533 .17989874 .10921659 1 5 786
1 0 13.5533 -.05727171 .0774895 1 5 787
I would like to regress a dependent variable (annual_report) that is binary over the independent variable (DID treatment) using either the logit or probit model while controlling for firm FE, industryxyear FE, and clustering at the firm_id.
Here is an example of my data:
input float(annual_report treatedxmandate log_assets profit_assets leverage pay_dividends firm_id indyear)
0 0 21.902086 .010306734 .2206007 1 1 107
0 0 21.82287 .023236906 .18649498 1 1 108
0 0 21.74963 -.07548836 .18513305 0 1 109
0 0 21.98201 .0443056 .25447315 0 2 71
0 0 22.00753 .034606867 .22314507 0 2 72
0 0 22.087317 .03733062 .2349182 0 2 73
0 0 22.049013 -.023373174 .2260292 0 2 74
0 0 22.05352 .02194606 .2065045 1 2 75
0 0 21.87605 -.05904642 .13072309 1 2 76
0 0 21.88704 .04903185 .142411 1 2 77
0 0 23.599426 .12391525 .24721064 1 3 63
0 0 23.833174 .16548464 .26696107 1 3 64
0 0 24.04246 .18731457 .19777484 1 3 65
0 0 24.1709 .17173678 .1683602 1 3 66
0 0 24.22247 .09537913 .16561395 1 3 67
0 0 24.67002 .08242703 .156451 1 3 68
0 0 24.73425 .08653829 .17979747 1 3 69
0 0 24.84307 .08874518 .1889613 1 3 70
0 0 24.92945 .10032787 .19636364 1 3 71
1 0 24.926525 .08128064 .1992407 1 3 72
1 0 24.942846 .03046835 .2793765 1 3 73
1 0 25.07941 -.02164041 .2516291 1 3 74
1 0 24.99975 -.01985081 .25280952 1 3 75
1 0 24.97898 .03032323 .22765115 1 3 76
1 0 24.754173 -.18001492 .271594 1 3 77
0 0 20.86467 .0745382 .14186156 1 4 345
0 0 20.912657 .1161205 .1727725 1 4 346
0 0 20.627867 .08729772 .1882192 1 4 347
0 0 20.56115 .13791901 .0772841 1 4 348
0 0 20.440073 .16702846 .28794026 1 4 349
0 0 21.13426 .10510793 .29772565 1 4 350
1 0 14.44674 .07748583 .28516528 1 5 784
1 0 14.627494 .07080033 .02303519 1 5 785
1 0 13.5533 .17989874 .10921659 1 5 786
1 0 13.5533 -.05727171 .0774895 1 5 787
