I am running a regression with Log stock returns on 1st quarter of 2020 as my dependent variable;
Code:
Ln (Stock price on 31-03-2020/ Stock price on 01-01-2020)
Code:
reg quart_ret i.ff48,vce(cluster ff48)
Code:
. reg quart_ret i.ff48,vce(cluster ff48) Linear regression Number of obs = 1924 F( 0, 29) = . Prob > F = . R-squared = 0.0586 Root MSE = .30878 (Std. Err. adjusted for 30 clusters in ff48) ------------------------------------------------------------------------------ | Robust quart_ret | Coef. Std. Err. t P>|t| [95% Conf. Interval] -------------+---------------------------------------------------------------- ff48 | 5 | -.0006924 1.29e-15 -5.4e+11 0.000 -.0006924 -.0006924 7 | .0184726 1.29e-15 1.4e+13 0.000 .0184726 .0184726 8 | -.0564544 1.29e-15 -4.4e+13 0.000 -.0564544 -.0564544 9 | -.0447615 1.29e-15 -3.5e+13 0.000 -.0447615 -.0447615 10 | .1450836 1.29e-15 1.1e+14 0.000 .1450836 .1450836 11 | .1361723 1.29e-15 1.1e+14 0.000 .1361723 .1361723 13 | .1527319 1.43e-15 1.1e+14 0.000 .1527319 .1527319 14 | .0309398 1.30e-15 2.4e+13 0.000 .0309398 .0309398 16 | .0442209 1.29e-15 3.4e+13 0.000 .0442209 .0442209
As the results indicate all my standard errors are very big, bizarre (+ve &-ve) and F statistic is missing. My intention of clustering by industries is to account for correlation among firms in the same industry but I know that during this period correlation can exist amongst industries also. Hence I tried the following command by clustering at the company level and my results are attached
Code:
reg quart_ret i.ff48,vce(cluster companyname) Linear regression Number of obs = 1924 F( 29, 1923) = 4.70 Prob > F = 0.0000 R-squared = 0.0586 Root MSE = .30878 (Std. Err. adjusted for 1924 clusters in companyname) ------------------------------------------------------------------------------ | Robust quart_ret | Coef. Std. Err. t P>|t| [95% Conf. Interval] -------------+---------------------------------------------------------------- ff48 | 5 | -.0006924 .0914865 -0.01 0.994 -.1801155 .1787308 7 | .0184726 .0776587 0.24 0.812 -.1338315 .1707766 8 | -.0564544 .0526913 -1.07 0.284 -.1597924 .0468836 9 | -.0447615 .0512153 -0.87 0.382 -.1452049 .0556818 10 | .1450836 .0650334 2.23 0.026 .0175402 .2726271 11 | .1361723 .0814712 1.67 0.095 -.0236089 .2959536 13 | .1527319 .0408991 3.73 0.000 .0725207 .2329432 14 | .0309398 .0304394 1.02 0.310 -.0287578 .0906375 16 | .0442209 .0357533 1.24 0.216 -.0258985 .1143403 17 | -.0232826 .0417664 -0.56 0.577 -.1051948 .0586297 18 | -.1212549 .0403227 -3.01 0.003 -.2003357 -.042174 19 | -.0859658 .036367 -2.36 0.018 -.1572888 -.0146428 21 | -.0131784 .0371308 -0.35 0.723 -.0859993 .059642
Thanks in advance
0 Response to Clustering Standard errors at industry versus company level
Post a Comment