Hello to everyone can see my post,

I am running a panel model for balanced data with N = 14 and T= 21, but I have many missing observations, ending with 162 instead of 294 (only 55% of the data). I tried to interpolate some of the controlled variables but it changed the results in significance and sign. I tried multiple imputation but it turned that it is not benefitable in post estimation to choose between pooled, fixed, and random. Anyway, I proceeded with abit less variables as much as I can with the same162 observation and run Hausman (testing random vs fixed) and Breush-Bagan (testing ols vs random). It turned that random effect is the appropriate model.

I tested for serial and found it does exist. However, I could not find a command in random effect model for testing hetero. However, I run restricted and unrestricted xtgls model (restricted for homo and unrestricted for heteo) and run LR test, yielding there is hetero. So, what is the solution for the serial correlation and possible hetero in my random effect model.

When I add option robust, vce(cluster), cluster(country), vce(bootstrap), or vce(jackknife), it gives me so inflated std errors, ruining the significance of my explanatory variables. I noticed that the random effect model is estimated by Generalized Least Squares. Can I consider that GLS is already corrected the heteroscedastic std errors of my random effect model. However, what about the serial correlation.

I appreciate any help of anyone can see my question.
Also, if anyone has an idea to increase my sample size, will be very generous