Hello everyone,
I apologize in advance in case this is a silly questions but I could not find enlightening clues neither on Stata forum nor on internet. I have a panel data consisting of 59 cross-sectional units (countries) and 10 time-units (year) and I am trying to assess whether my residuals are normally distributed. This is the code I run:

Code:
. jb residuals
Jarque-Bera normality test:  1.377 Chi(2)  .5022
Jarque-Bera test for Ho: normality:

. 
. xtsktest, reps(500) seed(123)
(running _xtsktest_calculations on estimation sample)


Tests for skewness and kurtosis                 Number of obs     =        465
                                                Replications      =        479

                                (Replications based on 59 clusters in country)
------------------------------------------------------------------------------
             |   Observed   Bootstrap                         Normal-based
             |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
  Skewness_e |   2.276566   11.81486     0.19   0.847    -20.88013    25.43326
  Kurtosis_e |   353.2939   232.8903     1.52   0.129    -103.1627    809.7504
  Skewness_u |   355.1194   112.5327     3.16   0.002     134.5594    575.6794
  Kurtosis_u |   3539.433    1691.43     2.09   0.036     224.2903    6854.576
------------------------------------------------------------------------------
Note: One or more parameters could not be estimated in 21 bootstrap replicates;
      standard-error estimates include only complete replications.
Joint test for Normality on e:        chi2(2) =   2.34    Prob > chi2 = 0.3106
Joint test for Normality on u:        chi2(2) =  14.34    Prob > chi2 = 0.0008
If I am not wrong, the JB test does not reject the H0 of normality, while the second test reject the join test for normality in the country-specific components. How should I interpret that? Does this mean that the results are conflicting?
Thank you in advance for your time
Best regards