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 = 0.0000
Kind regards
Can
0 Response to Panel dataset and omitted dummy variables for regression
Post a Comment