夏目贵志 发表于 2016-9-4 09:39 
可能有不同原因。请把你用的命令和得到的结果完整贴出来一下。
这里是我的ordered logistic regression 结果
. ologit ReputationLoss33_D board_size board_size_2 indep_board_pct2 busy_board_to_bsize ceo_female2 fe
> male_pct2 chair_female2 ceo_duality2 eindex age_coeff_var tenure_coeff_var $control i.Year, vce(clust
> er parent_permno) or
note: chair_female2 omitted because of collinearity
Iteration 0: log pseudolikelihood = -81.306667
Iteration 1: log pseudolikelihood = -66.573737
Iteration 2: log pseudolikelihood = -65.393626
Iteration 3: log pseudolikelihood = -64.139933
Iteration 4: log pseudolikelihood = -64.132341
Iteration 5: log pseudolikelihood = -64.132339
Ordered logistic regression Number of obs = 75
Wald chi2(30) = .
Prob > chi2 = .
Log pseudolikelihood = -64.132339 Pseudo R2 = 0.2112
(Std. Err. adjusted for 41 clusters in parent_permno)
Robust
ReputationLoss33_D Odds Ratio Std. Err. z P>z [95% Conf. Interval]
board_size 2.94e+28 8.49e+29 2.27 0.023 8341.997 1.04e+53
board_size_2 2.61e-06 .000015 -2.24 0.025 3.44e-11 .1988302
indep_board_pct2 .8043907 2.352055 -0.07 0.941 .0026094 247.9694
busy_board_to_bsize 2.23e+08 3.86e+09 1.11 0.267 4.19e-07 1.19e+23
ceo_female2 .395341 1.076197 -0.34 0.733 .0019047 82.05647
female_pct2 3.484172 20.92799 0.21 0.835 .0000269 451768.9
chair_female2 1 (omitted)
ceo_duality2 .9611527 .7639472 -0.05 0.960 .2024124 4.564023
eindex .9378608 .3594737 -0.17 0.867 .4424665 1.987908
age_coeff_var 1.14e+07 2.09e+08 0.89 0.375 2.89e-09 4.52e+22
tenure_coeff_var 10.97532 19.1539 1.37 0.170 .3588538 335.6731
bank_size .8063505 .2888253 -0.60 0.548 .3996073 1.6271
bank_profit_to_ta 21142.11 3809977 0.06 0.956 8.5e-150 5.2e+157
tot_debt_to_tot_eqy 1.004536 .0062173 0.73 0.465 .9924236 1.016796
px_to_book_ratio 1.197372 .9933716 0.22 0.828 .2355321 6.087072
sum_fines_to_mkcap 0 0 -3.42 0.001 0 5.5e-143
Second .4354927 .4565425 -0.79 0.428 .0558002 3.398801
Third .3790452 .381475 -0.96 0.335 .052727 2.724889
BHC .1273312 .2340451 -1.12 0.262 .0034702 4.672104
SUB .0035968 .0069705 -2.90 0.004 .0000806 .160516
Year
2003 1.6976 4.504134 0.20 0.842 .0093626 307.8036
2004 2.435938 6.90861 0.31 0.754 .0093877 632.0849
2005 29.45174 90.14475 1.11 0.269 .0730779 11869.59
2006 4.442411 16.3307 0.41 0.685 .0033001 5980.136
2007 51.75818 246.2206 0.83 0.407 .0046206 579773.9
2008 16.85842 73.55116 0.65 0.517 .0032594 87196.93
2009 301.0185 997.1045 1.72 0.085 .4560821 198675.1
2010 27.20021 112.911 0.80 0.426 .0079642 92896.75
2011 32.73926 120.439 0.95 0.343 .024195 44300.84
2012 53.10278 200.6844 1.05 0.293 .0322316 87488.74
2013 2.336194 9.535015 0.21 0.835 .0007841 6960.313
2014 352.392 1404.225 1.47 0.141 .142931 868811.7
/cut1 81.24252 36.61494 9.478557 153.0065
/cut2 83.6875 36.68889 11.77859 155.5964
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