Heterogeneous Treatment Effect Event Study Design
Heterogeneous Treatment Effect Event Study Design is a causal-inference framework that uses event study regression to estimate how treatment effects vary across groups, cohorts, or time relative to a treatment event. Unlike classical two-way fixed-effects event studies — which assume a homogeneous effect — this approach explicitly models and recovers group-time average treatment effects (ATTs), addressing the contamination bias that arises when effects differ across treated units.
Source record
Citations copied verbatim from the method’s source record. No claim-level verification is inferred from them.
- Sun, L., & Abraham, S. (2021). Estimating dynamic treatment effects in event studies with heterogeneous treatment effects. Journal of Econometrics, 225(2), 175-199. · DOI 10.1016/j.jeconom.2020.09.006
- Callaway, B., & Sant'Anna, P. H. C. (2021). Difference-in-Differences with multiple time periods. Journal of Econometrics, 225(2), 200-230. · DOI 10.1016/j.jeconom.2020.12.001
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