I m currently doing some social science research using panel data to determine the impact of budget cuts on financial vulnerability. I have decided to use a fixed effects model to determine this association. When I use raw data, however, my results are insignificant (there are major outliers in my data). In order to reduce the impact of these outliers I have scaled the data using min-max scaler and this results in significant results.
However, I have seen some posts which advise against scaling panel datasets and I would like to confirm if sclaing for fixed effects regression is good practice?