The seminar introduces principles of causal inference for randomized experiments and observational studies. We discuss the potential outcomes framework and, through its lens, give an overview of modern quasi-experimental methods, including regression and matching. We end with a brief literature review.
Audience: Harvard Faculty, Students, and Staff are all welcome. (Priority is given to HBS faculty, doctoral students, and RAs).
Prerequisites: Familiarity with fundamental statistical concepts, including probability, distribution, and linear regression is recommended.
Software requirements: None
Link to slides (HBS affiliates): Principles of Causal Inference (04-15-2020)
Link to slides (Harvard affiliates): Principles of Causal Inference (04-15-2020)