currently, I am trying to decide whether my data is normally distributed or not using the Jarque-Bera test. The test runs fine, however, after reading the manual, looking at other posts (most of which are unanswered), and watching youtube videos, I have not found a way how to interpret the results for panel data. I would be very grateful if somebody could please help me with this.
Code:
xtsktest resid (running _xtsktest_calculations on estimation sample) Bootstrap replications (50) ----+--- 1 ---+--- 2 ---+--- 3 ---+--- 4 ---+--- 5 .................................................. 50 Tests for skewness and kurtosis Number of obs = 3,683 Replications = 50 (Replications based on 559 clusters in firm) ------------------------------------------------------------------------------ | Observed Bootstrap Normal-based | coefficient std. err. z P>|z| [95% conf. interval] -------------+---------------------------------------------------------------- Skewness_e | -.0002604 .0001401 -1.86 0.063 -.000535 .0000142 Kurtosis_e | .0003008 .0001085 2.77 0.006 .0000882 .0005134 Skewness_u | .0001761 .000113 1.56 0.119 -.0000454 .0003976 Kurtosis_u | -7.41e-06 .0000286 -0.26 0.795 -.0000634 .0000486 ------------------------------------------------------------------------------ Joint test for Normality on e: chi2(2) = 11.14 Prob > chi2 = 0.0038 Joint test for Normality on u: chi2(2) = 2.49 Prob > chi2 = 0.2873 ------------------------------------------------------------------------------ . jb resid Jarque-Bera normality test: 2878 Chi(2) 0 Jarque-Bera test for Ho: normality:
Best,
Robin
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