Assess graduate students' ability to apply causal inference and regression methods to estimate and interpret the effects of public policies using observational data, including selecting identification strategies (difference-in-differences, instrumental variables, regression discontinuity, propensity score methods), specifying and estimating regression models, testing key assumptions (parallel trends, instrument validity, unconfoundedness), performing robustness and sensitivity analyses, addressing clustering and covariate adjustment, and interpreting heterogeneous effects and limitations for policy conclusions.