Causal Analysis
I teach this course jointly with Prof. Michael Gerfin.
Course description
In this course, we study econometric methods for identifying and estimating causal effects. We first present the potential outcomes approach as a general framework to examine such effects. We discuss randomized experiments as the predominant way for establishing causality, and then move on to observational studies and explore various types of assumptions that allow for credible causal inference. Examples from the literature and step-by-step tutorials o¤er hands-on experiences in utilizing the methods. Course language is English.
Slides for the 2nd part of the course
IV with heterogeneous potential outcomes
Sharp regression discontinuity design
Fuzzy regression discontinuity design
Quantile regression and related methods
Lecture notes
IV with heterogeneous potential outcomes
Past exams