Modeling Event Studies with Heterogeneous Treatment Effects
September 07, 2023
Summary
The authors of this working paper develop a simple approach to overcome the shortcomings of using a standard, single treatment–effect event study to assess the ability of an empirical model to measure heterogeneous treatment effects.
View PaperWorking Paper 2023-11a
Abstract: In this paper, we develop a new event-study approach that has the ability to capture model misspecifications in the presence of heterogeneous treatment effects. It is less prone to false rejections of the null hypothesis of no event-time variations than an event study that assumes a single treatment effect in the presence of heterogenous effects. We also introduce an alternative approach to calculating the standard errors for this event-study model to better assess the underlying trends in the model specification. These features contribute to a more precise understanding of the impacts of policy changes on outcomes and behaviors.
JEL classification: C22, C23
Key words: event studies, heterogeneous treatment effects
Digital Object Identifier: https://doi.org/10.29338/wp2023-11
The views expressed here are those of the authors and not necessarily those of the Federal Reserve Bank of Atlanta or the Federal Reserve System. Any remaining errors are the authors' responsibility. The authors report there are no competing interests to declare.
Please address questions regarding content to Laura M. Argys, College of Liberal Arts and Sciences, CB 181, University of Colorado, Denver, PO Box 173364, Denver, CO 80217-3364, laura.argys@ucdenver.edu; Thomas A. Mroz, Georgia State University, Department of Economics, PO Box 3992, Atlanta, GA 30302-3992, tmroz@gsu.edu; or M. Melinda Pitts, Federal Reserve Bank of Atlanta, Research Department, 1000 Peachtree Street NE, Atlanta, GA 30309-4470, 404-498-7009, melinda.pitts@atl.frb.org.
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