Hope all is well.
Context: I am in the process of regressing director-turnover on the board of a company (identified as dummy variable = 1 if turnover event happens in that year), on a number of independent variables including company's stock return performance over 1, 2 and 3 years.
Data: My data has director-firm-year observations (1 observation for each director, in each company, for each year). Sample is below:
Code:
input int year double permno int(fyear meetingdate) long our_director_id int age byte female float(left_early ind_adj_ret) 1996 78791 1995 13285 38111000 73 . 1 13.151268 1996 14702 1995 13222 33878000 66 . 0 12.2449 1996 11404 1995 13289 4346 43 . 0 -15.231146 1996 90721 1995 13272 31963000 51 . 0 8.038734 1996 20183 1995 13285 40459000 53 . 0 -5.435533 1996 41355 1996 13445 39443000 69 . 0 -2.2939062 1996 53065 1995 13289 4744 55 . 0 -16.172775 1996 49744 1995 13285 34949000 65 . 0 .9351444 1996 58755 1995 13273 4007 71 . 0 -11.683067 1996 34841 1995 13292 38002000 84 . 0 -11.037954 1996 67176 1996 13460 5666 72 . 0 2.3997774 1996 27051 1995 13263 36200000 57 . 0 -14.071634 1996 78975 1995 13165 2426 44 . 0 54.14909 1996 75489 1995 13292 201534000 45 . 1 43.11556 1996 13688 1995 13256 428 66 . 0 -26.11026 1996 65817 1995 13273 201523000 57 . 0 -20.604166 1996 55597 1995 13276 754 56 . 0 -12.89924 1996 27633 1995 13272 2686 54 . 0 -10.729064 1996 35051 1996 13472 5137 81 . 0 -8.403617 1996 49429 1995 13287 200327000 53 . 1 20.802996 1996 68494 1995 13473 200552000 46 . 0 -13.40749 1996 30680 1995 13173 5474 55 . 0 -6.006222 1996 27633 1995 13272 36104000 65 . 0 -10.729064 1996 56266 1995 13282 3653 64 . 0 3.263151 1996 48523 1996 13471 33717000 66 . 0 21.90117 1996 25320 1996 13415 200211000 57 . 1 58.16761 1996 74230 1995 13236 34285000 71 . 0 -7.106485 1996 43553 1995 13255 31590000 67 . 0 15.526155 1996 27780 1995 13269 3966 47 . 0 89.00487 1996 38578 1995 13270 3788 61 . 0 -13.84472 1996 70308 1995 13366 201385000 69 . 1 59.21646 1996 75654 1995 13251 36850000 66 . 0 61.75616 1996 76492 1995 13263 35608000 68 . 0 9.414017 1996 58246 1995 13255 318 62 . 0 42.52085 1996 11607 1995 13242 34448000 61 . 0 23.50525 1996 77637 1996 13471 38673000 73 . 0 2.746721 1996 75819 1995 13284 2703 48 . 0 -32.38974 1996 26710 1995 13283 37598000 83 . 0 -1.0945435 1996 87127 1995 13270 864 49 . 0 -37.093536 1996 24985 1995 13209 34514000 66 . 0 2.196209 1996 22293 1995 13264 2216 57 . 0 -5.990883 1996 11403 1995 13272 1457 48 . 0 142.31427 1996 10460 1995 13262 1207 54 . 0 -6.083118 1996 78946 1995 13258 34774000 70 . 1 17.288269 1996 78928 1995 13297 38621000 62 . 0 33.46526 1996 78928 1995 13297 38622000 67 . 0 33.46526 1996 75241 1995 13278 32815000 43 . 0 6.72043 1996 75654 1995 13251 201412000 51 . 1 61.75616 1996 80072 1995 13241 34417000 55 . 0 -6.115255 1996 51369 1995 13292 32725000 56 . 0 -47.30177 1996 24360 1995 13278 2454 61 . 0 .987216 1996 18016 1995 13264 36074000 64 . 0 12.724827 1996 78916 1995 13279 4645 53 . 0 -51.63638 1996 48506 1995 13255 3012 66 . 0 -16.384653 1996 50905 1995 13265 173 57 . 0 -14.914303 1996 21282 1995 13264 36315000 78 . 0 26.61349 1996 50024 1995 13255 32084000 64 . 0 18.354536 1996 39917 1995 13255 2897 53 . 0 8.930243 1996 52476 1995 13270 2264 62 . 0 15.83344 1996 56143 1995 13269 36391000 70 . 0 -24.86207 1996 13936 1995 13318 1842 57 . 0 -20.055765 1996 59459 1995 13276 36425000 45 . 0 -14.52517 1996 75615 1995 13292 40926000 67 . 0 29.82071 1996 35211 1995 13278 4157 60 . 0 -30.684635 1996 62519 1995 13290 4742 37 . 0 64.42719 1996 48961 1995 13276 4122 68 . 0 -31.7728 1996 65074 1995 13298 38332000 68 . 0 95.01543 1996 34833 1995 13265 3068 65 . 0 -6.114417 1996 63483 1995 13297 200804000 70 . 1 -26.318604 1996 50876 1995 13254 34008000 67 . 0 -2.1853828 1996 20183 1995 13285 37654000 57 . 0 -5.435533 1996 21338 1995 13263 36155000 62 . 0 -6.882256 1996 18374 1995 13255 2910 57 . 0 1.6626244 1996 48389 1995 13283 37711000 66 . 0 -21.129177 1996 43350 1995 13256 34335000 70 . 1 41.83089 1996 11127 1995 13269 201492000 59 . 0 -63.20605 1996 11850 1995 13263 37798000 69 . 1 4.774702 1996 80694 1995 13292 201737000 69 . 0 -.19219208 1996 35175 1995 13257 4013 62 . 1 12.587743 1996 78180 1995 13304 38599000 48 . 0 -63.20605 1996 40483 1995 13285 2915 56 . 0 -12.20704 1996 24184 1995 13276 36551000 68 . 0 -56.84167 1996 80654 1995 13244 2592 60 . 0 -13.19672 1996 76091 1996 13465 32427000 66 . 0 38.057514 1996 34746 1995 13227 2370 55 . 0 54.4802 1996 53401 1995 13461 200271000 63 . 0 -19.353674 1996 44599 1995 13289 37724000 65 . 0 -26.374424 1996 78859 1995 13283 36966000 49 . 0 0 1996 25129 1995 13256 1080 45 . 0 14.3304 1996 24467 1995 13284 200924000 45 . 0 2.5272436 1996 26112 1996 13446 40843000 69 . 1 4.103896 1996 75655 1995 13318 38871000 63 . 0 -63.20605 1996 43721 1995 13261 945 53 . 0 -25.42431 1996 12062 1995 13473 5328 45 . 0 -63.20605 1996 11976 1995 13380 5256 59 . 0 84.78006 1996 60695 1995 13262 36112000 77 . 0 43.0281 1996 78859 1995 13283 201689000 42 . 0 0 1996 62463 1995 13269 32002000 54 . 0 -6.447252 1996 64486 1995 13275 31625000 64 . 0 32.173347 1996 10225 1995 13270 2904 63 . 0 -26.909966 end format %td meetingdate
- Firstly, the industry-induced component of stock returns is estimated as the fitted value from cross-sectional regressions using one-year lagged returns of the sample firms on the corresponding median industry return
- Secondly, Idiosyncratic stock returns are then estimated as the residual from this fitted value.
Thank you!
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