Advanced Empirical Methods for Policy Analysis
The goal of this course is to provide students with an introduction to advanced empirical methods. We begin by discussing a framework for causal inference and how randomized controlled trials provide a simple and powerful template for thinking about causal questions. We then develop a sequence of advanced empirical methods as alternatives to randomized trials, in settings where experiments are infeasible or not desirable. In particular we discuss regression discontinuity, matching methods, difference-in-differences and panel data, and instrumental variables. We will discuss applications from a variety of domestic and international policy settings, and learn how to apply these methods to real-world data sets. Skills students will acquire in this course include: the capacity to reason causally and empirically, the ability critically to assess empirical work, knowledge of advanced quantitative tools, and expertise in applying these methods to policy problems.
The course video provides more information.