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Bibliographic Details
Main Authors: Botosaru, Irene, Liu, Laura
Format: Preprint
Published: 2026
Subjects:
Online Access:https://arxiv.org/abs/2601.05493
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author Botosaru, Irene
Liu, Laura
author_facet Botosaru, Irene
Liu, Laura
contents Event studies often conflate direct treatment effects with indirect effects operating through endogenous covariate adjustment. We develop a dynamic panel event study framework that separates these effects. The framework allows for persistent outcomes and treatment effects and for covariates that respond to past outcomes and treatment exposure. Under sequential exogeneity and homogeneous feedback, we establish point identification of common parameters governing outcome and treatment effect dynamics, the distribution of heterogeneous treatment effects, and the covariate feedback process. We propose an algorithm for dynamic decomposition that enables researchers to assess the relative importance of each effect in driving treatment effect dynamics.
format Preprint
id arxiv_https___arxiv_org_abs_2601_05493
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle Event Studies with Feedback
Botosaru, Irene
Liu, Laura
Econometrics
Event studies often conflate direct treatment effects with indirect effects operating through endogenous covariate adjustment. We develop a dynamic panel event study framework that separates these effects. The framework allows for persistent outcomes and treatment effects and for covariates that respond to past outcomes and treatment exposure. Under sequential exogeneity and homogeneous feedback, we establish point identification of common parameters governing outcome and treatment effect dynamics, the distribution of heterogeneous treatment effects, and the covariate feedback process. We propose an algorithm for dynamic decomposition that enables researchers to assess the relative importance of each effect in driving treatment effect dynamics.
title Event Studies with Feedback
topic Econometrics
url https://arxiv.org/abs/2601.05493