Paneldata

Panel data, or longitudinal data, is a data set that follows the same units over multiple time periods. It combines the cross-sectional dimension with a time dimension, allowing researchers to analyze dynamics, timing, and causal relationships while controlling for unobserved heterogeneity that is constant over time. Panel data can improve the precision of estimates and help address omitted-variable bias that plagues pure cross-sectional or time-series analyses.

The typical structure includes a set of entities, such as individuals, households, firms, or countries, observed at multiple points in time. A balanced panel has the same number of observations for every unit; an unbalanced panel has some units observed for fewer periods due to missing data or attrition.

Econometric methods used with panel data include fixed effects (within estimator), which controls for all time-invariant characteristics of the units; random effects, which model the unobserved effects as part of the error term under a specific assumption; and pooled methods, such as pooled OLS, sometimes with robust standard errors. The choice between fixed and random effects is typically guided by the Hausman test. First-difference and system GMM are used for dynamic panels when lagged dependent variables are present.

Panel data offers advantages such as controlling for unobserved heterogeneity, exploiting temporal variation to study dynamics, and improving parameter efficiency. Its drawbacks include attrition and missing data, measurement error, nonstationarity and unit roots, and potential cross-sectional dependence.

Panel data are widely used in economics, finance, public health, sociology, and political science, drawing on panel surveys and administrative records from national statistics offices and international organizations.