The course provides an introduction into panel data analysis. After a discussion of the advantages (and disadvantages) of repeated measurements of the same units (“panel data”), the course introduces the fixed and random effects estimators and discusses their underlying assumptions. The second part of the course focuses explicitly on causal analysis using panel data. The canonical difference-in-differences approach is presented together with recent extensions, including the method of synthetic controls and the case of staggered treatment timings. The lecture will be accompanied by a hands-on-sessions, in which students will learn how to implement the discussed panel data methods and estimators in statistical software.

Structure

Block A: Traditional panel data analysis

1. Introduction
2. What is panel data
3. Fixed effects estimation
4. Random effects estimation
5. Panel data analysis with categorical outcomes

Block B: Causality and panel data

1. Causality and the counterfactual framework
2. The difference-in-differences approach for panel data
3. The synthetic control methods
4. The new Diff-in-Diff: Difference-in-differences with staggered treatment timing

Recommended readings

Abadie, A. (2021). Using synthetic controls: Feasibility, data requirements, and methodological aspects. Journal of Economic Literature, 59(2), 391-425.

Baker, A. C., Larcker, D. F., & Wang, C. C. (2022). How much should we trust staggered difference-in-differences estimates?. Journal of Financial Economics, 144(2), 370-395.

Cunningham, S. (2021). Causal inference: The mixtape. Yale University Press. https://mixtape.scunning.com/

Wooldridge, J. M. (2010). Econometric analysis of cross section and panel data. MIT press (2nd edition).

Wooldridge, J. M. (2015). Introductory econometrics: A modern approach. Cengage learning (6th edition).

 

Examination: Written examination (120 minutes) at the end of the course