### PANEL PMG / ARDL Model Can I ignore non normal distributions of the residuals and cross-section dependence?

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**Sat Aug 18, 2018 7:48 am**I am trying to estimate the impact of economic shocks (captured by a dummy variable in a ECB study) on unemployment rate in EU-28. The thing is PMG is so attractive because have the option - short-run coefficients and I can extract the impact of this dummy for each member state. Anyway, I have two variables non-stationary (stationary at I1): unemployment rate and youth unemployment rate. I used youth only to control unemployment and to make feasible the estimation of the economic shocks impact on unemployment. As fixed regressors (I0) I used percentage change of unit labour cost and the dummy variable mentioned above. I am satisfied about my coefficients results. All are significants and the economic reality is justified. My sample size consist in 1680 observation (60*28 cross sections).

Question 1: Can I ignore the non normal distribution of the residuals (JB test rejects the null) - I have a problem with Kurtosis which is high near 7? Even if I add more variables, the JB prob doesn't change.

Question 2: After extracting the residuals I check the cross dependence test and the result is that in my model exist cross section dependence between residuals. Do you think I should try to quit this method and try another one having in regard that in UE exists a significant level of homogeneity between some countries?

Thank you!

Question 1: Can I ignore the non normal distribution of the residuals (JB test rejects the null) - I have a problem with Kurtosis which is high near 7? Even if I add more variables, the JB prob doesn't change.

Question 2: After extracting the residuals I check the cross dependence test and the result is that in my model exist cross section dependence between residuals. Do you think I should try to quit this method and try another one having in regard that in UE exists a significant level of homogeneity between some countries?

Thank you!