Causal Inference

Graduate credit

Causal inference with potential outcomes, for students with advanced statistical training: finite- and superpopulation causal estimands; randomization inference; propensity scores, including matching and weighting; directed acyclic graphs for covariate selection; doubly robust estimation; omitted variable sensitivity analysis; quasi-experimental devices including instrumental variables, discontinuities and differences-in-differences; additional topics at instructor discretion. Course deliverables will include biweekly homework assignments and a final project. Students enrolled in 571 will be allowed to complete the final project in teams.