Stata Panel — Data Exclusive //top\\

xtreg y x1 x2, pa

xtreg y x1 x2, fe

xtunitroot llc y // Levin-Lin-Chu xtunitroot ips y // Im-Pesaran-Shin xtunitroot fisher y // Fisher-type

reshape long y x, i(id) j(year)

Stata's panel data capabilities shine in modern causal inference.

There is no unconditional fixed effects probit model in Stata due to the "incidental parameters problem," which yields inconsistent estimates. Stick to xtlogit, fe when you need to control for fixed effects with a binary outcome. Panel Count Data (Poisson and Negative Binomial)

Stata provides several estimators for panel data, primarily through the Panel Data 4: Fixed Effects vs Random Effects Models stata panel data exclusive

xtreg y x1 x2, fe vce(cluster id)

Step 2: Check dependence xtscc y x1 x2, fe lag(3)

// Unit-specific means bysort id: egen mean_y = mean(y) bysort id: egen mean_x = mean(x) xtreg y x1 x2, pa xtreg y x1

Tests cov(u_i, X) = 0. Null favors RE.

This command automatically handles spatial and temporal dependence. Most Stata users never touch this because it requires understanding of the lag structure. Exclusive users test the lag length via autocorrelation plots before applying it.

xtreg y x1, fe vce(cluster id) // Clusters standard errors at unit level Use code with caution. 5. Summary Checklist for Panel Data in Stata Set Panel Structure xtset id year Check Data Balance xtdes Explore Variance xtsum var Run Fixed Effects xtreg y x, fe Run Random Effects xtreg y x, re Select Model hausman fixed random Account for Clustering vce(cluster id) Conclusion Panel Count Data (Poisson and Negative Binomial) Stata