Statistical Panel Models: Differences-in-differences and fixed-effects models

This course provides a gentle introduction to difference-in-differences (DiD) analysis, including various extensions and recent developments. DiD is a straightforward research design that involves comparing the same units over time, along with a suitable control group, to estimate causal effects. It is widely used in fields such as economics, policy evaluation, marketing, political sciences and social sciences to uncover causal relationships. In recent years, researchers have critiqued previous methods of estimating DiD effects and increased our conceptual understanding of DiD analysis. This course aims to introduce the fundamentals of DiD, its basic assumptions, and its recent extensions. It will establish the connection between the DiD research design and fixed-effects estimation. In addition to understanding major concepts, we will engage in hands-on data exercises. By the end of this course, students will have a solid understanding of DiD that allows them to critically evaluate existing research that uses this method. Furthermore, it provides students with a set of techniques to conduct their own DiD analysis.