A historically structured survey of panel data econometrics

A historically structured survey of panel data econometrics is provided, tracing its evolution from the error components models of the 1960s to the modern integration of causal inference, machine learning, and high-dimensional methods. The survey emphasizes the conceptual breakthroughs that shaped the field, including approaches to unobserved heterogeneity, the development of dynamic panel GMM estimators, nonlinear and limited dependent variable models, cross-sectional dependence, nonstationary panels, and recent advances in causal inference and policy evaluation.