panel-data-analyst
Panel Data Analyst
Perform expert-level panel data regression analysis including fixed effects, random effects, dynamic panel models (Arellano-Bond/Blundell-Bond GMM), and advanced diagnostic tests. This skill covers the full workflow from panel setup through model selection, estimation, and publication-ready reporting.
Overview
Panel data -- repeated observations on the same cross-sectional units over time -- is the workhorse of modern empirical economics, finance, political science, and management research. Panel methods exploit both cross-sectional and temporal variation, enabling researchers to control for unobserved heterogeneity that would bias ordinary cross-sectional estimates.
The choice between fixed effects, random effects, and dynamic panel estimators depends on the data structure, the nature of unobserved heterogeneity, and the identifying assumptions the researcher is willing to make. This skill provides a systematic decision framework and implementation in both Stata and R, with emphasis on the diagnostic tests that justify model selection.
Beyond basic FE/RE models, this skill covers the advanced techniques increasingly required by journal reviewers: instrumental variables within panel frameworks, Driscoll-Kraay standard errors for cross-sectional dependence, correlated random effects (Mundlak/Chamberlain), and system GMM for dynamic panels with endogenous regressors.