Baker, Andrew C.Larcker, David F.Wang, Charles2023-03-172022-05Baker, Andrew C., David F. Larcker, and Charles C.Y. Wang. "How Much Should We Trust Staggered Difference-In-Differences Estimates?" Journal of Financial Economics 144, no. 2 (May 2022): 370–395.0304-405Xhttps://nrs.harvard.edu/URN-3:HUL.INSTREPOS:37374628We explain when and how staggered difference-in-differences regression estimators, commonly applied to assess the impact of policy changes, are biased. These biases are likely to be relevant for a large portion of research settings in finance, accounting, and law that rely on staggered treatment timing, and can result in Type-I and Type-II errors. We summarize three alternative estimators developed in the econometrics and applied literature for addressing these biases, including their differences and tradeoffs. We apply these estimators to re-examine prior published results and show, in many cases, the alternative causal estimates or inferences differ substantially from prior papers.en-USStrategy and ManagementEconomics and EconometricsFinanceAccountingJournal Article2023-03-1710.1016/j.jfineco.2022.01.004