I have these regressions. I would like to know what is the better options.
The test xtoverid show that I can chose the randon effects, but I dont understand very much.
reg vm capgir lnat roe, vce (cluster cod)
xtreg capgir lnat roe, fe vce (cluster cod)
xtreg capgir lnat roe, re vce (cluster cod)
xtoverid
The test xtoverid show that I can chose the randon effects, but I dont understand very much.
reg vm capgir lnat roe, vce (cluster cod)
Linear regression Number of obs = 749 F( 3, 184) = 42.83 Prob > F = 0.0000 R-squared = 0.4751 Root MSE = 3.9e+06 (Std. Err. adjusted for 185 clusters in cod) ------------------------------------------------------------------------------ | Robust vm | Coef. Std. Err. t P>|t| [95% Conf. Interval] -------------+---------------------------------------------------------------- capgir | 1.685738 .3949142 4.27 0.000 .9065955 2.46488 lnat | 1996273 248645.1 8.03 0.000 1505711 2486835 roe | 15454.81 4703.384 3.29 0.001 6175.314 24734.31 _cons | -2.58e+07 3436346 -7.51 0.000 -3.26e+07 -1.90e+07 ------------------------------------------------------------------------------ |
Fixed-effects (within) regression Number of obs = 749 Group variable: cod Number of groups = 185 R-sq: within = 0.0948 Obs per group: min = 1 between = 0.5134 avg = 4.0 overall = 0.4505 max = 5 F(3,184) = 13.15 corr(u_i, Xb) = 0.0115 Prob > F = 0.0000 (Std. Err. adjusted for 185 clusters in cod) ------------------------------------------------------------------------------ | Robust vm | Coef. Std. Err. t P>|t| [95% Conf. Interval] -------------+---------------------------------------------------------------- capgir | .8108888 .4202563 1.93 0.055 -.018252 1.640029 lnat | 2214233 587288.4 3.77 0.000 1055548 3372919 roe | 2707.187 2423.25 1.12 0.265 -2073.742 7488.115 _cons | -2.87e+07 8491240 -3.38 0.001 -4.54e+07 -1.19e+07 -------------+---------------------------------------------------------------- sigma_u | 3939428.2 sigma_e | 1879713.3 rho | .8145473 (fraction of variance due to u_i) ------------------------------------------------------------------------------ |
Random-effects GLS regression Number of obs = 749 Group variable: cod Number of groups = 185 R-sq: within = 0.0927 Obs per group: min = 1 between = 0.5321 avg = 4.0 overall = 0.4617 max = 5 Wald chi2(3) = 124.72 corr(u_i, X) = 0 (assumed) Prob > chi2 = 0.0000 (Std. Err. adjusted for 185 clusters in cod) ------------------------------------------------------------------------------ | Robust vm | Coef. Std. Err. z P>|z| [95% Conf. Interval] -------------+---------------------------------------------------------------- capgir | 1.106154 .3818139 2.90 0.004 .357812 1.854495 lnat | 2143280 245806.2 8.72 0.000 1661509 2625051 roe | 4136.752 2380.596 1.74 0.082 -529.1303 8802.635 _cons | -2.75e+07 3377511 -8.13 0.000 -3.41e+07 -2.08e+07 -------------+---------------------------------------------------------------- sigma_u | 3579910.2 sigma_e | 1879713.3 rho | .7838825 (fraction of variance due to u_i) ------------------------------------------------------------------------------ |
xtoverid
Test of overidentifying restrictions: fixed vs random effects Cross-section time-series model: xtreg re robust cluster(cod) Sargan-Hansen statistic 7.262 Chi-sq(3) P-value = 0.0640 |
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