Details

Autor(en) / Beteiligte

• Baker, Andrew C.
• Larcker, David F.
• Wang, Charles C.Y.

Titel

How much should we trust staggered difference-in-differences estimates?

Ist Teil von

• Journal of financial economics, 2022-05, Vol.144 (2), p.370-395

Ort / Verlag

Amsterdam: Elsevier B.V

Erscheinungsjahr

2022

Quelle

Elsevier ScienceDirect Journals

Beschreibungen/Notizen

• We 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.