Causal inference and policy evaluation

Aims: to introduce ex-post policy impact evaluation using the counterfactual approach
Learning outcomes: to acquire the basics of ex-post impact evaluation and to gain an in-depth understanding of some quasi-experimental methods from an applied perspective.

Course content

• the Rubin causal model and the fundamental problem of causal inference
• selection processes (random assignment, selection on observables, selection on unobservables) and identification strategies
• statistical methods for counterfactual analysis (e.g. matching methods, Regression Discontinuity Designs, Difference-in-Differences, Synthetic Control Methods)