Political Science 797CA - ST- Causal Inference

The nature of causality and techniques for making valid causal inferences have been the subject of intense recent discussion in the social sciences. These topics are also increasingly relevant in government, business, and non-profit sectors amid the growing popularity of evidence-based approaches. Rooted in the potential outcomes framework, this course will discuss various conceptualizations of causality, explore the statistics of causal inference and provide deep coverage of methods for design- and model-based causal inference with experimental and observational data. Students will learn about designing, implementing and analyzing survey, lab, field and natural experiments, and about analytic techniques such as matching and regression-discontinuity design.

Open to Graduate students only.