Advanced Topics in Causal Inference

This course builds on 231B to introduce students to the theory and application of cutting-edge methods for observational causal inference, including recent advances on difference-in-differences estimators (e.g. accounting for multiple periods and variation in treatment timing), instrumental variable approaches (e.g. the strengths and weaknesses of shift-share instruments which are widely applied in the migration literature), and regression discontinuity designs (e.g. how to think about politician characteristics’ RDDs). With this course, students will learn the theory behind these methods and will have the opportunity to apply the methods to cases of interest to social scientists, and to their own causal empirical research. The ultimate goal of the course is to stimulate student interest in future independent learning of new advanced techniques.