This is the third graduate-level course in the quantitative political methodology sequence at the Political Science Department at UCSD. The goal of course is to provide a survey of most commonly used empirical tools for political science and public policy research. Our focus is design-based causal inference, that is, to use statistical methods to answer research questions that concern the impact of some cause on certain outcomes. We cover a variety of causal inference designs and methods, including experiments, matching, regression, fixed effects models, difference-in-differences, synthetic control methods, instrumental variable estimation, and regression discontinuity designs.
The class is open to qualified students from other departments and undergraduates, but priority will be given to graduate students in the Political Science Department.