Pre-Event Trends in the Panel Event-Study Design

By S. Freyaldenhoven, Christian Hansen, Jesse M. Shapiro. The American Economic Review, 2019

368 citations recorded by the source corpus.

We consider a linear panel event-study design in which unobserved confounds may be related both to the outcome and to the policy variable of interest. We provide sufficient conditions to identify the causal effect of the policy by exploiting covariates related to the policy only through the confounds. Our model implies a set of moment equations that are linear in parameters. The effect of the policy can be estimated by 2SLS, and causal inference is valid even when endogeneity leads to pre-event trends (“pre-trends”) in the outcome. Alternative approaches perform poorly in our simulations. (JEL C23, C26)

Subfields: Economics and Econometrics, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/ea609aa252f4f50cd9085603d8d3079b713c3f31

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Citations in the corpus

How Are SNAP Benefits Spent? Evidence from a Retail Panel (2018, methodology): “We argue that trends in food spending prior to adoption suggest a small role for confounding changes in circumstances, and use the instrumental variables approach proposed in Freyaldenhoven et al. (2018) to account directly for such confounds.”
Two-Way Fixed Effects and Differences-in-Differences with Heterogeneous Treatment Effects: A Survey (2021, background): “Similarly, recent papers have proposed relaxations of the parallel trends assumption (see, e.g., Manski and Pepper, 2018; Rambachan and Roth, 2019; Freyaldenhoven et al., 2019).”
What’s trending in difference-in-differences? A synthesis of the recent econometrics literature (2022, positive): “Finally, Freyaldenhoven et al. (2019) propose a GMM-based estimation strategy that allows for parallel trends to be violated when there exists a covariate assumed to be affected by the same confounds as the outcome but not by the treatment itself.”
How Much Should We Trust Staggered Difference-In-Differences Estimates? (2021, methodology): “Simultaneous confidence intervals for event study designs have been advocated by both Freyaldenhoven, Hansen, and Shapiro (2019) and Callaway and Sant’Anna (2020), and are generated by their estimator.”
Tax Policy and Local Labor Market Behavior (2019, methodology): “Appendix F presents details on the implementation of the estimator of Freyaldenhoven et al. (2018).”