 Staggered Difference-in-Differences Estimation for Antitrust Analysis: A Review of Literature and Recommendations for Practitioners**Hassan Faghani and Steven VanOmmeren Journal of Competition Law and Economics, 2025, vol. 21, issue 1, 44-80 Abstract: The aim of this paper is twofold: first, we discuss literature developments surrounding difference-in-differences (DiD) methods with staggered treatment mechanisms. Second, we provide a resource for sound DiD analysis in antitrust expert testimony in light of these developments. We review relevant papers and their most important conclusions. We then discuss the antitrust implications of three important topics: parallel trends, the not-yet-treated group, and data with customer entry and exit. We supplement this discussion with Monte Carlo analysis, in which we compare the performance of DiD estimators and quantify certain types of bias. Finally, we discuss the sensitivity and robustness checks that should underlay expert testimony going forward. DiD theory has come a long way in the academic literature since the 2010s, and we distill that knowledge into what we consider to be the standards for robust DiD results going forward. JEL-codes: C18 C52 L40 (search for similar items in EconPapers) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:oup:jcomle:v:21:y:2025:i:1:p:44-80. Access Statistics for this article Journal of Competition Law and Economics is currently edited by Nicholas Economides, Amelia Fletcher, Michal Gal, Damien Geradin, Ioannis Lianos and Tommaso Valletti More articles in Journal of Competition Law and Economics from Oxford University Press |
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