arXiv 9 Jan 2026 · Econometrics · publishedAEA Papers and Proceedings (2026)
arXiv:2601.05493 · PDF · DOI · OpenAlex · Extracted main text
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.
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The works this paper leans on most, across its whole bibliography — not restricted to papers in our corpus. Ranked by composite intensity, which combines how often a work is mentioned, how many sections mention it, and how much of that falls in the main text rather than the appendix.
| Reference | Intensity | Mentions | Sections | Main text | |
|---|---|---|---|---|---|
| 1 | Botosaru, Irene and Liu, Laura (2025) Time-Varying Heterogeneous Treatment Effects in Event Studies self | 0.950 | 7 | 5 | 86% |
| 2 | Bonhomme, Stéphane (2025) Back to Feedback: Dynamics and Heterogeneity in Panel Data | 0.405 | 1 | 1 | 100% |
Showing the top 2 of 2 scored citations.