Dear all,
When running the following regression Stata omits the F-test results.
I suspect this is caused by the singleton dummy problem and check for indicator variables that are nonzero for only one observation or cluster and, amonst other things, indentified that the POST variable (1 if fyears 2003-2005; 0 if 2000-2002) in combination with the sic_COMP_2d variable (which indicates the industry group; 2-digit SIC codes) might cause the problems; in particular the industry groups 1, 22, 78, 83, and 99:
If I exclude these industry groups from the regression the F-statistic appears and the problem seems resolved – especially since I would just loose a couple of observations. There are minor changes in magnitude but statistical significance of all the regressors remains unchanged with the constant being the only exeption (it looses its statistical significance).
What made me curious though is that if I include sic_Comp_2d!=1 the F-statistic increases dramatically.
I have been taught that the important aspect is the significance of the F-test and thus I always just check if -Prob > F- is acceptable, more or less ignoring the F-test statistic. I found this odd, however, and wonder whether this translates into any implications regarding the model's regressions results?
Thank you very much in advance for soothing my inquisitiveness!
Kind regards,
Roman
When running the following regression Stata omits the F-test results.
HTML Code:
reg D_ROE_lead1_win c.UCOMP##i.POST D_RET_win D_ROE_win D_logSALES_by2002_win i.sic_Comp_2d i.fyear, vce(cl gvkey) notab note: 2005.fyear omitted because of collinearity Linear regression Number of obs = 4,387 F(65, 945) = . Prob > F = . R-squared = 0.1559 Root MSE = .18604 .
HTML Code:
. tab sic_Comp_2d fyear sic_Comp_2 | Fiscal Year d | 2000 2001 2002 2003 2004 2005 | Total -----------+------------------------------------------------------------------+---------- 1 | 1 0 0 0 0 1 | 2 10 | 3 2 2 3 2 2 | 14 13 | 23 23 20 25 26 25 | 142 14 | 2 2 2 2 2 2 | 12 15 | 7 8 8 8 7 8 | 46 16 | 3 3 3 3 1 1 | 14 20 | 22 21 21 29 29 25 | 147 21 | 2 2 1 1 2 2 | 10 22 | 3 0 0 3 3 3 | 12 23 | 7 7 6 6 7 8 | 41 24 | 5 6 6 6 6 5 | 34 25 | 7 6 7 7 6 8 | 41 26 | 13 11 15 16 14 13 | 82 27 | 11 11 11 13 12 10 | 68 28 | 57 51 49 57 59 55 | 328 29 | 4 3 5 6 5 5 | 28 30 | 7 8 8 7 8 7 | 45 31 | 2 3 5 5 5 5 | 25 32 | 5 5 5 5 4 4 | 28 33 | 13 12 13 14 13 14 | 79 34 | 12 9 10 13 12 12 | 68 35 | 45 43 51 54 50 46 | 289 36 | 59 57 55 58 55 51 | 335 37 | 21 26 26 21 22 21 | 137 38 | 23 28 34 31 30 32 | 178 39 | 5 4 5 4 4 5 | 27 40 | 5 3 3 4 4 5 | 24 42 | 7 7 8 8 6 6 | 42 44 | 4 5 4 4 3 4 | 24 45 | 4 4 4 4 4 4 | 24 47 | 3 3 2 2 3 2 | 15 48 | 14 14 14 11 15 15 | 83 49 | 64 67 65 63 59 57 | 375 50 | 14 14 17 18 18 16 | 97 51 | 5 5 7 6 6 6 | 35 52 | 4 3 3 3 3 3 | 19 53 | 8 9 11 10 9 9 | 56 54 | 7 6 6 6 6 6 | 37 55 | 3 2 2 2 2 2 | 13 56 | 14 14 13 10 11 13 | 75 57 | 3 4 4 3 4 5 | 23 58 | 15 15 17 17 16 11 | 91 59 | 10 10 10 10 13 12 | 65 60 | 44 39 41 44 44 45 | 257 61 | 5 4 5 7 6 5 | 32 62 | 15 14 13 11 11 13 | 77 63 | 23 28 34 33 31 31 | 180 64 | 4 4 5 4 4 3 | 24 67 | 1 2 1 1 2 2 | 9 70 | 2 3 3 3 3 2 | 16 72 | 4 3 3 5 3 2 | 20 73 | 48 51 50 54 61 57 | 321 75 | 3 2 2 2 3 3 | 15 78 | 1 1 1 1 1 1 | 6 79 | 2 2 1 1 2 3 | 11 80 | 11 8 8 10 9 10 | 56 82 | 2 2 3 3 2 2 | 14 83 | 1 1 1 1 1 1 | 6 87 | 7 7 8 9 8 5 | 44 99 | 1 1 0 0 1 1 | 4 -----------+------------------------------------------------------------------+---------- Total | 720 708 737 767 758 732 | 4,422 .
HTML Code:
. reg D_ROE_lead1_win c.UCOMP##i.POST D_RET_win D_ROE_win D_logSALES_by2002_win i.sic_Comp_2d i.fyear if sic_Comp_2d!=1 & sic_Comp_2d!=22 & sic_Comp_2d!=99 & sic_Comp_2d!=78 & sic_Comp_2d!=83, vce(cl gvkey) notab note: 2005.fyear omitted because of collinearity Linear regression Number of obs = 4,357 F(64, 938) = 6.35 Prob > F = 0.0000 R-squared = 0.1555 Root MSE = .18645 .
HTML Code:
. reg D_ROE_lead1_win c.UCOMP##i.POST D_RET_win D_ROE_win D_logSALES_by2002_win i.sic_Comp_2d i.fyear if sic_Comp_2d!=22 & sic_Comp_2d!=99 & sic_Comp_2d!=78 & sic_Comp_2d!=83, vce(cl gvkey) notab note: 2005.fyear omitted because of collinearity Linear regression Number of obs = 4,359 F(65, 939) = 2516.96 Prob > F = 0.0000 R-squared = 0.1561 Root MSE = .18643 .
Thank you very much in advance for soothing my inquisitiveness!
Kind regards,
Roman
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