Description

This Master Prompt focuses on transforming the complete panel-data workflow into an integrated, transparent and defensible research account rather than presenting data preparation, estimator selection, diagnostics, robustness tests and empirical findings as disconnected statistical exercises. It guides researchers in reconnecting the research problem and theoretical framework with the actual panel structure; variable definitions and transformations; within-, between- and temporal variation; baseline model; estimator assumptions; diagnostic evidence; endogeneity strategy; cross-sectional dependence; dynamics; spatial interaction; latent factors; heterogeneity; nonlinear or semiparametric structures; structural instability; missingness; outliers; and robustness analysis. The final interpretation must show not only what was estimated, but why the estimator was appropriate, what assumptions support the result, what evidence challenges those assumptions, which findings survive alternative specifications, and what conclusions remain justified after the complete validation process.