Stata Panel Data May 2026

xtline wage, overlay

use union_panel.dta xtset id year xtsum wage union experience stata panel data

bysort id (year): keep if _n == 1 Merging two panel datasets requires both dimensions: xtline wage, overlay use union_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. merge 1:1 id year using another_panel

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 :

After FE, test for serial correlation:

xtdescribe To fill in gaps with missing values (use cautiously):