A beginner-friendly tour of seven panel-data estimators, from pooled OLS to correlated random effects (Mundlak), applied to a two-period worker wage panel. Predict-first checks, two short proofs, an interactive lab, and worked exercises show why the within estimators nearly triple the union wage premium.
How persistent is firm employment? Pooled OLS, fixed effects, Anderson-Hsiao IV, Arellano-Bond difference GMM, and Blundell-Bond system GMM on the classic 140-firm UK panel — and how the AR(2), Hansen, and instrument-collapse diagnostics separate the one defensible estimate from four seductive wrong ones.
Estimate the within-country dynamic effect of war on log GDP per capita using Arellano-Bond GMM in Stata, reproducing Thies and Baum (2020) on a 1955-2015 panel of 160 countries.
Identify latent group structures in panel data using the Classifier-LASSO method (Su, Shi, Phillips 2016), revealing that the pooled democracy-growth effect of +1.055 masks a +2.151 effect in 57 countries and a -0.936 effect in 41 countries.
Comparing standard error estimators in panel data regressions using Python and linearmodels --- from conventional to clustered, Driscoll-Kraay, and fixed effects