How Do You Handle Missing Values in Panel Data Analysis? or What Are the Best Practices for Modeling

Ugh, the FE vs. RE debate is eternal! Personally, I default to fixed effects unless I’m *really* pressed for power. Random effects can give you tighter confidence intervals, but if your assumptions are off, you’re screwed.

For Hausman tests, R’s `plm` package makes it easy. Just don’t forget to cluster your standard errors—rookie mistake!

Also, Cameron & Trivedi’s "Microeconometrics" has a solid chapter on panel data. Worth a skim!