Hi all
I'm running a pool OLS regression with the command as follows.
xi: reg lnnumber_d_w post soe postsoe ownership asset_w leverage_w cashhold_w i.indu1 i.year1,cluster(stkcd)
When I run the same do-file with same data in STATA14 and STATA15, the result for variable “post"(a dummy variable coding 1 after year 2013) is different while other variables are same.
Morever, _Iyear1_2014 is omitted because of collinearity in STATA 14 while _Iyear1_2015 is omitted because of collinearity in STATA 15.
I just wonder why the results are different in STATA14 and 15. Which result is correct?


Below is the result using STATA14.

i.indu1 _Iindu1_1-17 (_Iindu1_1 for indu1==A omitted)
i.year1 _Iyear1_2009-2015 (naturally coded; _Iyear1_2009 omitted)
note: _Iyear1_2014 omitted because of collinearity

Linear regression Number of obs = 9,217
F(37, 2110) = 9.43
Prob > F = 0.0000
R-squared = 0.0531
Root MSE = .29529

(Std. Err. adjusted for 2,111 clusters in stkcd)
-------------------------------------------------------------------------------
| Robust
lnnumber_d_w | Coef. Std. Err. t P>|t| [95% Conf. Interval]
--------------+----------------------------------------------------------------
post | .0668674 .013085 5.11 0.000 .0412067 .0925282
soe | -.0110271 .0093917 -1.17 0.240 -.0294451 .0073909
postsoe | -.0894927 .0123459 -7.25 0.000 -.1137042 -.0652813
ownership | -.0013779 .0211927 -0.07 0.948 -.0429386 .0401829
asset_w | .006405 .0035147 1.82 0.069 -.0004877 .0132978
leverage_w | .0308835 .0220983 1.40 0.162 -.0124533 .0742203
cashhold_w | .0648878 .0279293 2.32 0.020 .0101159 .1196596
_Iindu1_2 | .0836318 .0283376 2.95 0.003 .0280593 .1392043
_Iindu1_3 | .0384154 .0183909 2.09 0.037 .0023491 .0744817
_Iindu1_4 | .1246017 .0270419 4.61 0.000 .07157 .1776333
_Iindu1_5 | .0585011 .0269362 2.17 0.030 .0056767 .1113255
_Iindu1_6 | .041658 .0221213 1.88 0.060 -.0017239 .0850399
_Iindu1_7 | .0586802 .0252648 2.32 0.020 .0091338 .1082267
_Iindu1_8 | .0196253 .0339283 0.58 0.563 -.0469111 .0861616
_Iindu1_9 | .0792681 .0267385 2.96 0.003 .0268317 .1317046
_Iindu1_10 | .0433499 .0244094 1.78 0.076 -.0045192 .091219
_Iindu1_11 | .0640976 .0376795 1.70 0.089 -.0097953 .1379904
_Iindu1_12 | .0694245 .0631215 1.10 0.272 -.0543623 .1932113
_Iindu1_13 | .064119 .0429139 1.49 0.135 -.020039 .148277
_Iindu1_14 | .0542156 .1049017 0.52 0.605 -.151506 .2599372
_Iindu1_15 | .0503639 .0456947 1.10 0.271 -.0392474 .1399752
_Iindu1_16 | -.0219435 .0351372 -0.62 0.532 -.0908506 .0469636
_Iindu1_17 | .087508 .0390906 2.24 0.025 .0108478 .1641682
_Iyear1_2010 | .0163025 .0112808 1.45 0.149 -.0058202 .0384251
_Iyear1_2011 | .0006867 .0113649 0.06 0.952 -.0216008 .0229743
_Iyear1_2012 | .0056306 .0108877 0.52 0.605 -.0157211 .0269823
_Iyear1_2014 | 0 (omitted)
_Iyear1_2015 | .0566508 .0103356 5.48 0.000 .0363817 .0769199
_cons | .0145059 .0758323 0.19 0.848 -.1342079 .1632198
-------------------------------------------------------------------------------

Here is the result using STATA15.

i.indu1 _Iindu1_1-17 (_Iindu1_1 for indu1==A omitted)
i.year1 _Iyear1_2009-2015 (naturally coded; _Iyear1_2009 omitted)
note: _Iyear1_2015 omitted because of collinearity

Linear regression Number of obs = 9,217
F(37, 2110) = 9.78
Prob > F = 0.0000
R-squared = 0.0547
Root MSE = .29822

(Std. Err. adjusted for 2,111 clusters in stkcd)
------------------------------------------------------------------------------
| Robust
lnnumber_w | Coef. Std. Err. t P>|t| [95% Conf. Interval]
-------------+----------------------------------------------------------------
post | .1268291 .0145373 8.72 0.000 .0983201 .1553382
soe | -.0130607 .009503 -1.37 0.169 -.0316969 .0055755
postsoe | -.092008 .0125001 -7.36 0.000 -.1165218 -.0674942
ownership | .0006562 .0214245 0.03 0.976 -.0413591 .0426715
asset_w | .0072593 .0035555 2.04 0.041 .0002866 .0142319
leverage_w | .0291227 .0222048 1.31 0.190 -.0144228 .0726682
cashhold_w | .0629849 .028271 2.23 0.026 .0075428 .1184269
_Iindu1_2 | .0877501 .029679 2.96 0.003 .029547 .1459532
_Iindu1_3 | .0369433 .0198711 1.86 0.063 -.0020256 .0759122
_Iindu1_4 | .121166 .0280556 4.32 0.000 .0661465 .1761856
_Iindu1_5 | .0596673 .0284525 2.10 0.036 .0038694 .1154652
_Iindu1_6 | .0381356 .0234042 1.63 0.103 -.0077621 .0840333
_Iindu1_7 | .0564075 .0265541 2.12 0.034 .0043325 .1084824
_Iindu1_8 | .0167578 .0344558 0.49 0.627 -.0508132 .0843287
_Iindu1_9 | .075899 .028062 2.70 0.007 .020867 .1309311
_Iindu1_10 | .0395524 .0254455 1.55 0.120 -.0103484 .0894532
_Iindu1_11 | .0604579 .0384397 1.57 0.116 -.0149258 .1358415
_Iindu1_12 | .0650782 .0635301 1.02 0.306 -.05951 .1896665
_Iindu1_13 | .0599678 .0435654 1.38 0.169 -.0254679 .1454035
_Iindu1_14 | .0511799 .1055605 0.48 0.628 -.1558336 .2581934
_Iindu1_15 | .0446924 .0459836 0.97 0.331 -.0454855 .1348703
_Iindu1_16 | -.0268586 .0359398 -0.75 0.455 -.0973397 .0436225
_Iindu1_17 | .083435 .0398149 2.10 0.036 .0053545 .1615155
_Iyear1_2010 | .0162149 .0112807 1.44 0.151 -.0059076 .0383374
_Iyear1_2011 | .0019031 .0114849 0.17 0.868 -.0206197 .024426
_Iyear1_2012 | .0066134 .0109773 0.60 0.547 -.014914 .0281409
_Iyear1_2014 | -.0564731 .010469 -5.39 0.000 -.0770038 -.0359424
_Iyear1_2015 | 0 (omitted)
_cons | .0123937 .0771134 0.16 0.872 -.1388326 .1636199
------------------------------------------------------------------------------