Behavioral Policymaking and Impact Evaluation

This is a graduate-level course on figuring out whether a policy actually worked, with a behavioral economics lens on the kinds of interventions worth testing in the first place. You'll spend most of the semester in Stata, working through five labs that build up the causal-inference toolkit—regression diagnostics, difference-in-differences, panel methods, and RCT design—before applying it to a hands-on research project where you evaluate a real program's impact. It assumes you're already comfortable with multivariate regression and inference, and it's where that econometrics background gets pointed at concrete questions like how to reduce inequality or alleviate poverty without fooling yourself about selection bias.