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Design-Robust Event-Study Estimation under Staggered Adoption Diagnostics, Sensitivity, and Orthogonalisation

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  • Craig S Wright

Abstract

This paper develops a design-first econometric framework for event-study and difference-in-differences estimands under staggered adoption with heterogeneous effects, emphasising (i) exact probability limits for conventional two-way fixed effects event-study regressions, (ii) computable design diagnostics that quantify contamination and negative-weight risk, and (iii) sensitivity-robust inference that remains uniformly valid under restricted violations of parallel trends. The approach is accompanied by orthogonal score constructions that reduce bias from high-dimensional nuisance estimation when conditioning on covariates. Theoretical results and Monte Carlo experiments jointly deliver a self-contained methodology paper suitable for finance and econometrics applications where timing variation is intrinsic to policy, regulation, and market-structure changes.

Suggested Citation

  • Craig S Wright, 2026. "Design-Robust Event-Study Estimation under Staggered Adoption Diagnostics, Sensitivity, and Orthogonalisation," Papers 2601.18801, arXiv.org.
    • Handle: RePEc:arx:papers:2601.18801
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    References listed on IDEAS

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