Dear all,

I have an unbalanced panel (xtset id year) of 22 countries for 25 years (with total observations = 286). I am interested in finding the best estimator to run a regression (with max 7-8 regressors). I am also taking into consideration non parametric estimators (npregress kernel), but just as a comparison as I am not sure they perform well in small sample sizes. So far, I understood that OLS with fixed-effect (xtreg, fe) is comparatively better than others (such as FGLS) in small sample sizes.

Two questions:
1) Which estimator is more appropriate? (also several)
2) Another issue concerns the numbers of regressors, are they too many?

Additional informations:
a) Mundlak test to determine whether I should use a Fixed- or Random-effect model: with chi2( 7) = 29.47 and Prob > chi2 = 0.0001, the test suggests to go for a Fixed-effect model.
b) Autocorrelation (xtserial): the null hypothesis of no serial correlation is strongly rejected.
c) Heteroskedasticity (lrtest, xttest3): the null hypothesis of homoskedasticity is strongly rejected.

Thanks for the support,
Alessandro