The choice of model depends on your assumptions about the individual-specific effects (the "unobserved" factors unique to each entity). Model Type Stata Command Description Fixed Effects (FE) xtreg y x, fe
Ordinary summarize mixes across‑unit and within‑unit variation. xtsum separates them:
: Treats observations as independent, ignoring the panel structure. Use only if you believe there are no entity-specific effects. reg y x1 x2 Use code with caution. Copied to clipboard stata panel data
* Tell Stata the panel identifier (i) and time variable (t) xtset country_id year
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: With few clusters (<20), cluster-robust SEs are too small. Use clustse (user-written) or bootstrap with vce(boot, cluster(id)) .
This assumes that the unobserved unit-specific effects are uncorrelated with the independent variables. It allows you to estimate time-invariant variables. Use only if you believe there are no entity-specific effects
Are entities affected by common shocks (e.g., global financial crisis)?
No serial correlation (p>0.05).
You cannot estimate coefficients for variables that do not change over time (e.g., gender, race, geographic location), as they are subtracted out during the within transformation. 3. Random Effects (RE) Model
To analyze panel data in , you must first ensure the data is in "long" format—where each row represents one observation for a specific entity at a specific time 1. Declaring Panel Data Structure Before using specialized panel commands, you must tell which variable identifies the (e.g., countries, firms) and which identifies (e.g., years). xtset panelvar timevar xtset country year
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