I am trying to figure out why there is one variable omitted in xtgls regression but not in reg regression.
any advice is highly appreciated!
any advice is highly appreciated!
Code:
. xtgls lnsale_w lnit_stock_w lncogs_w lnsga2_w i.fyear i.sic_2 , force i(gvkey) t(fyear) p(h) c(p)
(note: 83 observations dropped because only 1 obs in group)
Cross-sectional time-series FGLS regression
Coefficients: generalized least squares
Panels: heteroskedastic
Correlation: panel-specific AR(1)
Estimated covariances = 864 Number of obs = 6,140
Estimated autocorrelations = 864 Number of groups = 864
Estimated coefficients = 28 Obs per group:
min = 2
avg = 7.106481
max = 9
Wald chi2(28) = 6.65e+15
Prob > chi2 = 0.0000
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lnsale_w | Coefficient Std. err. z P>|z| [95% conf. interval]
-------------+----------------------------------------------------------------
lnit_stock_w | -.0627259 .0006983 -89.83 0.000 -.0640946 -.0613573
lncogs_w | 1.07105 .0002252 4755.05 0.000 1.070608 1.071491
lnsga2_w | 0 (omitted)
|
fyear |
2011 | -.0087647 .0004499 -19.48 0.000 -.0096465 -.0078829
2012 | .0222538 .0009953 22.36 0.000 .0203031 .0242046
2013 | .0547922 .0012749 42.98 0.000 .0522934 .057291
2014 | .0570109 .0015397 37.03 0.000 .0539932 .0600286
2015 | .0754605 .0017639 42.78 0.000 .0720033 .0789178
2016 | .1378157 .0021297 64.71 0.000 .1336416 .1419899
2017 | .1647435 .002498 65.95 0.000 .1598475 .1696395
2018 | .1741515 .0027955 62.30 0.000 .1686724 .1796305
|
sic_2 |
21 | .3397569 .0382942 8.87 0.000 .2647017 .4148122
22 | .1858502 .0120713 15.40 0.000 .162191 .2095094
23 | .2686389 .0055983 47.99 0.000 .2576664 .2796113
24 | .2066785 .0100844 20.49 0.000 .1869134 .2264436
25 | .3223446 .0083365 38.67 0.000 .3060054 .3386838
26 | -.1115616 .0094189 -11.84 0.000 -.1300223 -.093101
27 | .0898889 .0143198 6.28 0.000 .0618227 .1179552
28 | 1.941361 .0046328 419.04 0.000 1.93228 1.950441
29 | -.1352792 .0373032 -3.63 0.000 -.2083921 -.0621664
30 | .0343942 .0064241 5.35 0.000 .0218031 .0469853
31 | .1707927 .0312966 5.46 0.000 .1094525 .2321329
32 | .0448271 .0116934 3.83 0.000 .0219085 .0677457
33 | -.1197643 .008942 -13.39 0.000 -.1372904 -.1022383
34 | .1057662 .0071131 14.87 0.000 .0918247 .1197077
35 | .1533331 .0038878 39.44 0.000 .1457132 .160953
36 | .1390721 .0029855 46.58 0.000 .1332206 .1449236
37 | -.0769828 .0050326 -15.30 0.000 -.0868465 -.067119
38 | .3605061 .0049591 72.70 0.000 .3507864 .3702258
39 | 0 (omitted)
|
_cons | 0 (omitted)
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. reg lnsale_w lnit_stock_w lncogs_w lnsga2_w i.fyear i.sic_2
Source | SS df MS Number of obs = 6,223
-------------+---------------------------------- F(30, 6192) = 12475.16
Model | 19514.6432 30 650.488105 Prob > F = 0.0000
Residual | 322.867399 6,192 .052142668 R-squared = 0.9837
-------------+---------------------------------- Adj R-squared = 0.9836
Total | 19837.5106 6,222 3.18828521 Root MSE = .22835
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lnsale_w | Coefficient Std. err. t P>|t| [95% conf. interval]
-------------+----------------------------------------------------------------
lnit_stock_w | .0381838 .0038393 9.95 0.000 .0306574 .0457102
lncogs_w | .6876295 .0038201 180.00 0.000 .6801409 .6951182
lnsga2_w | .3107006 .0031863 97.51 0.000 .3044543 .3169468
|
fyear |
2011 | -.0054058 .0119152 -0.45 0.650 -.0287637 .017952
2012 | -.0047566 .0119508 -0.40 0.691 -.0281844 .0186711
2013 | -.0075589 .0119924 -0.63 0.529 -.0310681 .0159503
2014 | -.0067479 .0121654 -0.55 0.579 -.0305964 .0171005
2015 | -.0153265 .0125101 -1.23 0.221 -.0398506 .0091976
2016 | .0015709 .0139521 0.11 0.910 -.02578 .0289218
2017 | .0239516 .0150229 1.59 0.111 -.0054985 .0534017
2018 | .0184825 .0155345 1.19 0.234 -.0119706 .0489355
|
sic_2 |
21 | .1991205 .0513183 3.88 0.000 .0985188 .2997221
22 | -.0301966 .0301257 -1.00 0.316 -.0892534 .0288603
23 | -.1131618 .0229568 -4.93 0.000 -.158165 -.0681585
24 | .0122045 .0245732 0.50 0.619 -.0359675 .0603766
25 | -.0908516 .0227095 -4.00 0.000 -.1353701 -.0463331
26 | .0453891 .022114 2.05 0.040 .0020379 .0887403
27 | .0509572 .0260054 1.96 0.050 -.0000225 .1019369
28 | .1912057 .0147924 12.93 0.000 .1622075 .2202039
29 | .251608 .0290935 8.65 0.000 .1945746 .3086414
30 | -.0348874 .0229905 -1.52 0.129 -.0799566 .0101819
31 | -.0611215 .0314201 -1.95 0.052 -.1227158 .0004728
32 | .0364904 .0278588 1.31 0.190 -.0181224 .0911033
33 | .0872981 .020296 4.30 0.000 .0475109 .1270854
34 | -.0171009 .0189186 -0.90 0.366 -.0541879 .0199861
35 | -.0638843 .014574 -4.38 0.000 -.0924544 -.0353142
36 | -.0396236 .0145074 -2.73 0.006 -.0680632 -.011184
37 | .0314182 .0162489 1.93 0.053 -.0004353 .0632717
38 | .0056201 .0153525 0.37 0.714 -.0244763 .0357164
39 | -.0488434 .0248894 -1.96 0.050 -.0976352 -.0000515
|
_cons | .7995171 .0223239 35.81 0.000 .7557544 .8432797
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