I am analysing a panel data with n=19 (ID/panel variable i.e. countries) and T=44 (time variable) to understand the drivers of equity flows to emerging markets. Before estimating the model, I run following diagnostic tests:

1. Using -xttest3-, I find presence of Heteroskedasticity.
2. Using -xtserial-, no autocorrelation is found.
3. Using -xttest2-, I find presence of cross sectional dependence.

Moving on, based on these, I compute Robust Hausman Test using -xtoverid- after running -xtreg, re(robust)-. Robust Hausman Test suggests using FE model.

Now, I have to decide between -xtgls- & -xtscc-.

By using help xtscc, I find this:

-xtscc, fe- performs fixed-effects (within) regression with Driscoll-Kraay standard errors. These standard errors are robust to very general forms of cross-sectional ("spatial") and temporal dependence (provided that T is sufficiently large). If the residuals are assumed to be heteroscedastic only: use xtreg, fe robust.

On the other hand, -xtgls- fits panel-data linear models by using feasible generalized least squares. This command allows estimation in the presence of AR(1) autocorrelation within panels and cross-sectional correlation and heteroskedasticity across panels.

So, I have to choose between the following two commands:

1. xtscc depvar indepvars, fe
2. xtgls depvar indepvars, panels(correlated) corr(independent)

Which one should I choose?

Thanks.