Hello everybody!

For my master dissertation, I'm dealing with panel data. In addition, I detected heteroskedasticity and autocorrelation in my dataset.
Until now, I only checked for heteroskedasticity as I had never heard of autocorrelation before. Therefore, I used White robust standard errors for all my models (until now).
(White robust standard errors = heteroskedasticity vs vce(cluster) = heteroskedasticity + autocorrelation)

The approach I use is OLS regression. In the first model, I run the standard regression. In the second model, I check for year dummies as well. According to someone in the literature, I avoid autocorrelation when checking for year dummy variables. Thus, in the second model I should only use White robust standard errors, in contrast to the first model. Do you agree?
However, if I use vce(cluster) in model 1, I observe big differences in the t-statistics compared to my second model (where I use White robust standard errors).

What should I do?

Thanks in advance!