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.