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Heterogeneous Treatment Effect Event Study Design/Evidence
Method evidence record

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.

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Source record

Citations copied verbatim from the method’s source record. No claim-level verification is inferred from them.

Heterogeneous Treatment Effect Event Study Design
Taxonomic method record · regression-model / causal-inference
  • 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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Related methods

Generated from the method graph and shown as machine-suggested relations — no evidence claim is inferred.

Same method familyDifference-in-Differencesmachine-suggested · Relational suggestion, not evidence.Taxonomic bucketDynamic Difference-in-Differencesmachine-suggested · Relational suggestion, not evidence.Taxonomic bucketPanel Event Studymachine-suggested · Relational suggestion, not evidence.

Evidence status

Sources recorded, not reviewed

Bibliographic sources are present. Claim-level evidence review has not been performed.

Sources

2 recorded citations, copied from the method source record.

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