Introduction to Panel Data and Other Advanced Topics

Professor: Wagner
Units: 0.5
Elective Course (Research Analysis and Design: Empirical Analysis)

This course will introduce you to several methods used to analyze data over time and with multiple levels. We will primarily focus on how these methods can be used to identifying causal effects of interventions and how they help control for unobservable confounding factors. The first 2+ weeks will cover panel data methods including fixed-effects, random-effects, difference-in-differences, event study, and interrupted time-series. In the third week, we will discuss how to analyze data that has multiple levels, which is common in policy analysis (policies are usually not implemented for the individual but for the state, school, employer, etc.). In the last two weeks of the course, we will revisit some quasi-experimental methods you may have already seen, with the goal of improving your ability to apply these methods.