Hello everyone,
Was just concerned as I have a set of panel data obvservations, and when running regressions I find that I get the same results for the normal OLS (which i suppose to be Pooled OLS regression) and the Random Effects regression. Is this possible and if so what does it mean? Or am i doing something completely wrong?
Here is my code
**OLS**
reg gincdif1 Immigrationfromforeigncountri RegionalDebtGDP1 UnemploymentRate lnRGDP,
** Fixed Effects**
xtreg gincdif1 Immigrationfromforeigncountri RegionalDebtGDP1 UnemploymentRate lnRGDP, fe
estimates store fixed
** Now we run a Random Effects**
xtreg gincdif1 Immigrationfromforeigncountri RegionalDebtGDP1 UnemploymentRate lnRGDP, re

And here the results
. ** OLS reg **
. reg gincdif1 Immigrationfromforeigncountri RegionalDebtGDP1 UnemploymentRate
> lnRGDP,

Source | SS df MS Number of obs = 68
-------------+---------------------------------- F(4, 63) = 4.33
Model | .416390252 4 .104097563 Prob > F = 0.0037
Residual | 1.51345595 63 .02402311 R-squared = 0.2158
-------------+---------------------------------- Adj R-squared = 0.1660
Total | 1.9298462 67 .028803675 Root MSE = .15499

------------------------------------------------------------------------------
gincdif1 | Coef. Std. Err. t P>|t| [95% Conf. Interval]
-------------+----------------------------------------------------------------
Immigratio~i | .020578 .0072703 2.83 0.006 .0060495 .0351065
RegionalDe~1 | -.5074746 .2396663 -2.12 0.038 -.9864096 -.0285397
Unemployme~e | -1.27616 .4877509 -2.62 0.011 -2.250852 -.3014674
lnRGDP | -.3935338 .1557389 -2.53 0.014 -.7047532 -.0823145
_cons | 6.050379 1.620674 3.73 0.000 2.811721 9.289037
------------------------------------------------------------------------------

.
.
.
. ** Fixed Effects**
. xtreg gincdif1 Immigrationfromforeigncountri RegionalDebtGDP1 UnemploymentRa
> te lnRGDP, fe

Fixed-effects (within) regression Number of obs = 68
Group variable: Region1 Number of groups = 17

R-sq: Obs per group:
within = 0.2074 min = 4
between = 0.0528 avg = 4.0
overall = 0.0723 max = 4

F(4,47) = 3.07
corr(u_i, Xb) = -0.7899 Prob > F = 0.0249

------------------------------------------------------------------------------
gincdif1 | Coef. Std. Err. t P>|t| [95% Conf. Interval]
-------------+----------------------------------------------------------------
Immigratio~i | .0029911 .0303781 0.10 0.922 -.0581217 .0641039
RegionalDe~1 | -1.058942 .7713853 -1.37 0.176 -2.610769 .4928855
Unemployme~e | -1.353692 1.204872 -1.12 0.267 -3.777583 1.070198
lnRGDP | .2214223 .899801 0.25 0.807 -1.588744 2.031588
_cons | .0838402 8.926705 0.01 0.993 -17.87437 18.04205
-------------+----------------------------------------------------------------
sigma_u | .14660047
sigma_e | .16457669
rho | .4424237 (fraction of variance due to u_i)
------------------------------------------------------------------------------
F test that all u_i=0: F(16, 47) = 0.55 Prob > F = 0.9009

. estimates store fixed

. ** Now we run a Random Effects**
. xtreg gincdif1 Immigrationfromforeigncountri RegionalDebtGDP1 UnemploymentRa
> te lnRGDP, re

Random-effects GLS regression Number of obs = 68
Group variable: Region1 Number of groups = 17

R-sq: Obs per group:
within = 0.1955 min = 4
between = 0.3172 avg = 4.0
overall = 0.2158 max = 4

Wald chi2(4) = 17.33
corr(u_i, X) = 0 (assumed) Prob > chi2 = 0.0017

------------------------------------------------------------------------------
gincdif1 | Coef. Std. Err. z P>|z| [95% Conf. Interval]
-------------+----------------------------------------------------------------
Immigratio~i | .020578 .0072703 2.83 0.005 .0063285 .0348275
RegionalDe~1 | -.5074746 .2396663 -2.12 0.034 -.977212 -.0377373
Unemployme~e | -1.27616 .4877509 -2.62 0.009 -2.232134 -.3201856
lnRGDP | -.3935338 .1557389 -2.53 0.012 -.6987764 -.0882912
_cons | 6.050379 1.620674 3.73 0.000 2.873917 9.226841
-------------+----------------------------------------------------------------
sigma_u | 0
sigma_e | .16457669
rho | 0 (fraction of variance due to

Many thanks
Pepito