Data Science for Economists

Catalog description

This is an applied econometrics course intended to introduce students to the tools used in contemporary empirical microeconomic research inside and outside of academia. Emphasizing aspects of data sciences that are relevant for economics research, we will cover econometric methodology commonly used to analyze labor markets, issues arising in policy evaluations, and firm-and-consumer behaviors in industrial organization as well as use of computational software packages such as R or Julia. Specifically, students will study how to (1) work with data using modern statistical software (data science), (2) separate correlation from causation (causal inference), and (3) use various identification strategies for making quantitative causal statements using data (econometrics).