Dear Applied Statistics Workshop Community,
Our next meeting will be on Wednesday, March 20 (12:00 EST). Anton Strezhnev presents "A Guide to Dynamic Difference-in-Differences Regressions for Political Scientists."
<When>
March 20, 12:00 to 1:30 PM, EST
Lunch will be available for pick-up inside CGIS K354.
<Where>
In-person: CGIS K354
Zoom:
https://harvard.zoom.us/j/93217566507?pwd=elBwYjRJcWhlVE5teE1VNDZoUXdjQT09
<Abstract>
Difference-in-differences (DiD) designs for estimating causal effects have grown in popularity throughout political science. Many DiD papers present their central results through an "event study" plot - a visualization that combines estimated dynamic average treatment effects for multiple post-treatment time periods alongside placebo tests of the main identifying assumption: parallel trends. Despite their ubiquity, the methods used in practice for the creation of these plots are not standardized and in many cases the approaches adopted by researchers can result in misleading inferences about both the treatment effects and the placebo tests. Building on and synthesizing recent contributions in the econometric literature on differences-in-differences designs, this paper illustrates some common pitfalls through a replication of three recently published papers in major political science journals. We identify three notable problems related to the incorrect specification of the baseline comparison time, incorrect inclusion of "always-treated" units, and sensitivity to effect homogeneity assumptions. We help provide researchers with additional intuition for the problems that arise due to effect heterogeneity and for the "contamination bias" result of Sun and Abraham (2021) through a novel decomposition of the dynamic event study regression in the style of Goodman-Bacon (2021) that allows researchers to recover the weights placed on each 2x2 comparison used to construct the effect estimates and placebos. These weights allow researchers to gauge the sensitivity of each estimate to potential effect heterogeneity.
<2023-2024 Schedule>
GOV 3009 Website:
https://projects.iq.harvard.edu/applied.stats.workshop-gov3009
Calendar:
Best,
Jialu