I am about to find best specification for my dataset.

To begin with - I am trying to probe the effectivenes of the special economic zones in Poland in the meaning of growth of the economy in three similar panel data models for explained variables: a) registered unemployment rate b) GDP per capita c) gross fixed capital formation per capita.

Data is for NUTS3 sub-regions, explanatory variables are: 0-1 variable for presence of the SEZ in sub-region in year t and a few of the economic variables; yearly frequency, dataset is 2004-2012 for 66 sub-regions.

I have tried fixed and random effects. As for now, I have chosen FE, because of significance and theoretically correct signs. But there are some issues that hold me from taking it as granted:

1. autocorrelation and cross-corelation - how to test it?

2. testing for error term distribution - no idea how to do it in Stata, and furthermore - if it is not normally distributed, should I care about it much?

3. corr. coefficient between explanatory var's and error term - as I have understood from the literature, values near -1 or 1 are not bad as a matter of fact; in my case, its nearly -1 as you can see.

4. what about mixed model? Is it appropriate for my dataset?

I attach outcome for the model explaining unemployment rate.

Code:

```
xtreg st_bezr sse01 wartosc_sr_trw_per_capita zatr_przem_bud podm_gosp_na_10tys_ludn proc_ludn_wiek_prod ludnosc_na_km2, fe
Fixed-effects (within) regression Number of obs = 594
Group variable: id Number of groups = 66
R-sq: within = 0.4427 Obs per group: min = 9
between = 0.3479 avg = 9.0
overall = 0.2365 max = 9
F(6,522) = 69.10
corr(u_i, Xb) = -0.9961 Prob > F = 0.0000
-------------------------------------------------------------------------------------------
st_bezr | Coef. Std. Err. t P>|t| [95% Conf. Interval]
--------------------------+----------------------------------------------------------------
sse01 | -1.406066 .4631984 -3.04 0.003 -2.316028 -.4961045
wartosc_sr_trw_per_capita | -.0000963 .0000166 -5.79 0.000 -.0001289 -.0000636
zatr_przem_bud | -26.11989 4.992198 -5.23 0.000 -35.92716 -16.31263
podm_gosp_na_10tys_ludn | -.0201788 .0030788 -6.55 0.000 -.0262273 -.0141304
proc_ludn_wiek_prod | -229.1996 16.92631 -13.54 0.000 -262.4516 -195.9475
ludnosc_na_km2 | .0790167 .0120865 6.54 0.000 .0552726 .1027609
_cons | 161.9786 10.76989 15.04 0.000 140.821 183.1363
--------------------------+----------------------------------------------------------------
sigma_u | 53.986519
sigma_e | 2.5446248
rho | .99778327 (fraction of variance due to u_i)
-------------------------------------------------------------------------------------------
F test that all u_i=0: F(65, 522) = 27.09 Prob > F = 0.0000
```