I have a panel dataset of 77 variables and approximately 57.000 observations for the years 2014 - 2018. Therefore I use dummy variables for the independent variable company size (klein mittel groß) and industry sector (LuF BB, etc.). Using this, I ran regress to determine the effect on the tax burden (ETR_un) of companies.
I am using xtreg in Stata 15.1.
My problem is that as soon as I add the company size to my regression in addition to the industry dummies, 2 variables are immediately omitted. Therefore, the values of the independent variables are skewed.
I know that to avoid a dummy trap, I can remove one variable from the industry dummies and one from the company size, but the values still remain skewed.
How can I get around this problem?
Code:
xtreg ETR_un LuF BB Verarbeitendes Energieversorg Wasserversorg Baugewerbe Handel Verkehr Gastgewerbe Inform_Kommun Finanz_Versich Grunds
> tücks_Wohnungswesen FreiWissTech_DL wirts_DL ÖV Erziehung_Unterr Gesundheit_Sozialwesen Kunst_Unterhaltung_Erholung sonst_DL klein mittel
> groß i.year, re
note: sonst_DL omitted because of collinearity
note: groß omitted because of collinearity
Random-effects GLS regression Number of obs = 57,217
Group variable: ID Number of groups = 18,389
R-sq: Obs per group:
within = 0.0013 min = 1
between = 0.0589 avg = 3.1
overall = 0.0337 max = 5
Wald chi2(24) = 1163.20
corr(u_i, X) = 0 (assumed) Prob > chi2 = 0.0000
---------------------------------------------------------------------------------------------
ETR_un | Coef. Std. Err. z P>|z| [95% Conf. Interval]
----------------------------+----------------------------------------------------------------
LuF | -2.806153 1.724013 -1.63 0.104 -6.185157 .5728511
BB | 1.223227 1.931906 0.63 0.527 -2.563238 5.009692
Verarbeitendes | 1.156536 .7854209 1.47 0.141 -.3828609 2.695932
Energieversorg | -1.362574 .8817548 -1.55 0.122 -3.090782 .3656336
Wasserversorg | 1.335969 1.015181 1.32 0.188 -.6537506 3.325688
Baugewerbe | .8637391 .8727683 0.99 0.322 -.8468553 2.574333
Handel | 2.5564 .789308 3.24 0.001 1.009385 4.103415
Verkehr | 1.4275 .8937224 1.60 0.110 -.3241637 3.179164
Gastgewerbe | 2.483374 1.282375 1.94 0.053 -.0300348 4.996784
Inform_Kommun | 2.36475 .8876878 2.66 0.008 .6249134 4.104586
Finanz_Versich | 3.360829 .911962 3.69 0.000 1.573416 5.148241
Grundstücks_Wohnungswesen | -6.140547 .9226302 -6.66 0.000 -7.948869 -4.332225
FreiWissTech_DL | 1.915703 .80875 2.37 0.018 .330582 3.500824
wirts_DL | 2.66731 .880347 3.03 0.002 .9418616 4.392758
ÖV | 6.128692 2.154682 2.84 0.004 1.905592 10.35179
Erziehung_Unterr | -7.485594 1.566971 -4.78 0.000 -10.5568 -4.414388
Gesundheit_Sozialwesen | -11.52747 .8984018 -12.83 0.000 -13.28831 -9.766636
Kunst_Unterhaltung_Erholung | 1.190228 1.34611 0.88 0.377 -1.4481 3.828556
sonst_DL | 0 (omitted)
klein | .107322 .3644027 0.29 0.768 -.6068941 .8215381
mittel | -.4489496 .2944976 -1.52 0.127 -1.026154 .1282552
groß | 0 (omitted)
|
year |
15 | .3697264 .1749918 2.11 0.035 .0267489 .712704
16 | -.2524269 .1744287 -1.45 0.148 -.5943008 .0894471
17 | .3338847 .1742833 1.92 0.055 -.0077044 .6754738
18 | .9312448 .2926599 3.18 0.001 .3576419 1.504848
|
_cons | 26.40237 .775345 34.05 0.000 24.88272 27.92202
----------------------------+----------------------------------------------------------------
sigma_u | 9.70098
sigma_e | 12.63551
rho | .37085086 (fraction of variance due to u_i)Code:
tabstat ETR_un, statistics (count mean sd max min range) by(Branche)
Summary for variables: ETR_un
by categories of: Branche (Branche)
Branche | N mean sd max min range
-----------------+------------------------------------------------------------
1. Land- und For | 177 24.83884 12.81619 76.21348 1.072381 75.1411
2. Bergbau und G | 142 28.01898 17.38571 91.96083 1.116526 90.8443
3. Verarbeitende | 16119 28.02748 14.02538 99.6544 1.005321 98.64908
4. Energieversor | 2514 25.49997 15.52516 97.77159 1.019462 96.75213
5. Wasserversorg | 1067 27.8953 15.64467 99.73144 1.119681 98.61176
6. Baugewerbe/Ba | 2725 27.80223 12.44849 98.92137 1.014662 97.90671
7. Handel; Insta | 13455 29.22813 13.67265 99.76919 1.003844 98.76534
8. Verkehr und L | 2173 28.26321 14.86916 99.54535 1.024184 98.52117
9. Gastgewerbe/B | 417 29.41986 15.65624 99.04601 1.067991 97.97802
10. Information | 2270 29.26193 15.2746 97.74427 1.017193 96.72708
11. Erbringung v | 1842 30.01445 18.04395 99.85857 1.026219 98.83235
12. Grundstücks- | 1679 20.97251 16.91162 99.36201 1.012189 98.34982
13. Erbringung v | 6944 28.79622 17.03924 99.88694 1.017734 98.86921
14. Erbringung v | 2441 29.4939 15.703 99.85537 1.02731 98.82806
15. Öffentliche | 108 33.55072 27.06546 98.77544 1.449751 97.32569
16. Erziehung un | 206 20.88952 22.37715 99.39492 1.019612 98.37531
17. Gesundheits- | 1822 15.34987 16.67667 99.662 1.000133 98.66187
18. Kunst, Unter | 366 27.51446 19.84288 97.59387 1.18329 96.41058
19. Erbringung v | 750 27.34199 17.72626 98.51981 1.002463 97.51734
-----------------+------------------------------------------------------------
Total | 57217 27.82532 15.28509 99.88694 1.000133 98.88681
------------------------------------------------------------------------------Code:
tabstat ETR_un, statistics (count mean sd max min range) by(Größe_HP)
Summary for variables: ETR_un
by categories of: Größe_HP
Größe_HP | N mean sd max min range
--------------+------------------------------------------------------------
große KapG | 45881 27.75923 15.2651 99.88694 1.001677 98.88526
kleine KapG | 3250 28.64398 15.4276 99.27302 1.003844 98.26917
mittlere KapG | 8086 27.87132 15.33302 99.73144 1.000133 98.7313
--------------+------------------------------------------------------------
Total | 57217 27.82532 15.28509 99.88694 1.000133 98.88681
---------------------------------------------------------------------------Code:
xtreg ETR_un LuF BB Verarbeitendes Energieversorg Wasserversorg Baugewerbe Handel Verkehr Gastgewerbe Inform_Kommun Finanz_Versich Grunds
> tücks_Wohnungswesen FreiWissTech_DL wirts_DL ÖV Erziehung_Unterr Gesundheit_Sozialwesen Kunst_Unterhaltung_Erholung sonst_DL klein mittel
> , fe
note: LuF omitted because of collinearity
note: BB omitted because of collinearity
note: Verarbeitendes omitted because of collinearity
note: Energieversorg omitted because of collinearity
note: Wasserversorg omitted because of collinearity
note: Baugewerbe omitted because of collinearity
note: Handel omitted because of collinearity
note: Verkehr omitted because of collinearity
note: Gastgewerbe omitted because of collinearity
note: Inform_Kommun omitted because of collinearity
note: Finanz_Versich omitted because of collinearity
note: Grundstücks_Wohnungswesen omitted because of collinearity
note: FreiWissTech_DL omitted because of collinearity
note: wirts_DL omitted because of collinearity
note: ÖV omitted because of collinearity
note: Erziehung_Unterr omitted because of collinearity
note: Gesundheit_Sozialwesen omitted because of collinearity
note: Kunst_Unterhaltung_Erholung omitted because of collinearity
note: sonst_DL omitted because of collinearity
Fixed-effects (within) regression Number of obs = 57,217
Group variable: ID Number of groups = 18,389
R-sq: Obs per group:
within = 0.0007 min = 1
between = 0.0002 avg = 3.1
overall = 0.0001 max = 5
F(2,38826) = 13.26
corr(u_i, Xb) = -0.0121 Prob > F = 0.0000
---------------------------------------------------------------------------------------------
ETR_un | Coef. Std. Err. t P>|t| [95% Conf. Interval]
----------------------------+----------------------------------------------------------------
LuF | 0 (omitted)
BB | 0 (omitted)
Verarbeitendes | 0 (omitted)
Energieversorg | 0 (omitted)
Wasserversorg | 0 (omitted)
Baugewerbe | 0 (omitted)
Handel | 0 (omitted)
Verkehr | 0 (omitted)
Gastgewerbe | 0 (omitted)
Inform_Kommun | 0 (omitted)
Finanz_Versich | 0 (omitted)
Grundstücks_Wohnungswesen | 0 (omitted)
FreiWissTech_DL | 0 (omitted)
wirts_DL | 0 (omitted)
ÖV | 0 (omitted)
Erziehung_Unterr | 0 (omitted)
Gesundheit_Sozialwesen | 0 (omitted)
Kunst_Unterhaltung_Erholung | 0 (omitted)
sonst_DL | 0 (omitted)
klein | 1.206493 .2799578 4.31 0.000 .6577689 1.755217
mittel | .5408651 .1822532 2.97 0.003 .1836443 .898086
_cons | 27.68036 .0611299 452.81 0.000 27.56054 27.80017
----------------------------+----------------------------------------------------------------
sigma_u | 13.079854
sigma_e | 12.638967
rho | .51713756 (fraction of variance due to u_i)
---------------------------------------------------------------------------------------------
F test that all u_i=0: F(18388, 38826) = 2.44 Prob > F = 0.0000Kind regards
Can
0 Response to Panel dataset and omitted dummy variables for regression
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