This course aims to familiarize students with the process of conducting empirical economic research. Students practice applying statistical methods to real-world data and encounter issues such as outliers, measurement error, and multilevel data structures. Several methods are introduced and applied to broaden student’s econometric toolkit, such as robust methods, the bootstrap, feature extraction/dimension reduction, nonparametric methods. Empirical applications come from growth empirics, political economy, labor, health, and development. We will use both STATA and R, given that both are ubiquitously used in the economics profession.
This course is targeted to students who are interested in conducting empirical data analyses, including but not limited to those writing or planning to write empirical senior undergraduate theses, those applying for Tobin RA positions, and those who plan to apply for “pre-doc” RA positions in economics or quantitative social science more broadly.