Correlated random effects (if time-invariant variables needed) xtreg y x1 x2 x3_timeinvariant, cre
Crucially, Stata's CRE implementation works for , thanks to Wooldridge's extension of Mundlak's original result.
The standard summarize command lumps all observations together. xtsum decomposes the total variance into between-entity and within-entity components. xtsum wage experience education Use code with caution.
). It relies purely on within-unit variation, effectively wiping out time-invariant characteristics.\beginequation Y_it = \beta X_it + \alpha_i + u_it \endequation xtreg y x1 x2 x3, fe Use code with caution. Random Effects (RE) Model The Random Effects model assumes αialpha sub i is purely random and completely uncorrelated with Xitcap X sub i t end-sub xtreg y x1 x2 x3, re Use code with caution. Selection via the Classic Hausman Test
Mastering Panel Data in Stata: An Exclusive Guide to Advanced Econometric Workflows stata panel data exclusive
Reverse:
Before any panel data analysis, you must formally tell Stata about the structure of your data using the xtset command. This command declares which variable identifies the panels (e.g., individuals, firms, countries) and, optionally, which variable identifies the time periods. Once set, Stata remembers this structure, and you won't need to declare it again if you save your dataset.
xtmlogit restaurant age, covariance(unstructured) // RE xtmlogit restaurant age, fe // Conditional FE
* Im-Pesaran-Shin test for panel stationarity xtunitroot ips gdp Use code with caution. Summary Checklist for a Flawless Panel Data Workflow xtsum wage experience education Use code with caution
Obtain clustered standard errors xtreg y x1 x2, fe vce(cluster country_id)
Once executed, Stata will report whether your panel is (every entity is observed for every time period) or unbalanced (some entities have missing time periods). Stata natively handles unbalanced panels for almost all estimators, but identifying the structure early helps flag data collection errors. Leveraging Time-Series Operators
xtvar grants revenues expenditures, lags(2)
If the null hypothesis of no cointegration is rejected, you can proceed to estimate long-run relationships using advanced estimators like Panel Dynamic OLS (DOLS) or Fully Modified OLS (FMOLS) using user-developed commands such as xtpedroni . 6. Advanced Stata Code Template for Applied Panel Analysis Random Effects (RE) Model The Random Effects model
This article is current as of Stata 19 (April 2025) and includes features from StataNow™ updates.
To tailor this workflow to your research design, could you share: The of your panel (the number of entities vs. time periods
xtreg y x1 x2, fd