xtserial wage experience union Random effects assumes the unobserved panel effects are uncorrelated with your regressors. This is a strong assumption but allows inclusion of time-invariant variables.
asdoc xtreg wage experience union i.year, fe Question : Does joining a labor union increase wages, controlling for individual ability? stata panel data
merge 1:1 id year using another_panel.dta 1:1 because each combination is unique. Learning Stata panel data commands is easy, but avoiding mistakes separates novices from experts. Pitfall 1: Forgetting to xtset Without xtset , commands like L.wage produce nonsense. Solution: Always xtset immediately after loading data. Pitfall 2: Ignoring Missing Data Patterns xtdescribe, patterns Shows which periods are missing for which panels. If missingness correlates with outcomes, you have attrition bias. Pitfall 3: Overlooking Time Fixed Effects Not including year dummies can make your FE model pick up economy-wide trends and claim them as treatment effects. Solution: Always include i.year or use xtreg, fe with time dummies. Pitfall 4: Using FE with Low Within Variation If experience barely changes for any worker, FE estimates will be imprecise. Check within variation via xtsum . Pitfall 5: Misinterpreting Hausman Test The Hausman test assumes homoskedasticity. Use hausman fe re, sigmamore for robust version. Part 8: Reporting Stata Panel Data Results Creating Regression Tables Using estout or outreg2 : xtserial wage experience union Random effects assumes the
Use pooled OLS as a baseline, but rarely as a final model. Fixed effects removes all time-invariant unobserved heterogeneity by de-meaning the data. It answers: Within a worker, how does changing union status affect wage? merge 1:1 id year using another_panel
Why does this matter? Because panel data allows you to control for unobserved heterogeneity—the "invisible" variables that differ across entities but remain constant over time. For example, when studying the impact of education policy on test scores, panel data can control for inherent differences in school quality or regional culture that you cannot measure directly.
xtreg wage experience union i.year, fe Already done above via i.year . This removes time trends common to all panels. When lagged dependent variables matter (e.g., wage depends on prior wage), standard FE is biased. Use Arellano-Bond GMM:
After FE, test for serial correlation: