Econometric Analysis: Panel Data & IV Regression

I will conduct an econometric analysis using panel data methods or instrumental variables — covering fixed effects vs. random effects model selection with Hausman test, robust standard error estimation (clustered by panel unit), instrumental variable regression with first-stage F-statistic and weak instrument testing, and a results report meeting the standards of an economics or applied econometrics journal submission. Econometric identification is the central challenge in causal inference from observational data; standard OLS applied to panel data with unobserved heterogeneity or endogenous regressors produces biased estimates that support incorrect causal conclusions regardless of how precisely estimated they appear.

The analysis covers panel data structure verification, Hausman test for RE vs. FE, within-group demeaning (FE) or GLS (RE) estimation, clustered or robust standard errors, IV first stage with excluded instrument F-statistic, Sargan-Hansen overidentification test if applicable, coefficient table with robust SEs, and an APA or econometrics journal formatted results section.

Designed for economists, policy researchers, and social scientists conducting causal inference from observational panel or cross-sectional data with endogeneity concerns.