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Doubly robust local projections difference-in-differences

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  • Daniel de Abreu Pereira Uhr
  • Guilherme Valle Moura

Abstract

This paper develops a doubly robust extension of local-projections difference-in-differences (LP-DiD) for staggered absorbing treatments. The resulting estimator, DRLPDID, preserves the LP-DiD local-stack ATT target and is consistent when either the local untreated-outcome regression or the local treatment-probability model is correctly specified. It also delivers influence-function-based inference for post-treatment summaries and multiplier-bootstrap bands for dynamic paths. In Monte Carlo designs with covariate-driven selection, DRLPDID matches regression-adjusted LP-DiD under outcome-model alignment and clearly outperforms the IPT-only variant under propensity-score misspecification. In the no-fault-divorce application, DRLPDID tracks robust staggered-adoption estimators and is less negative than unadjusted LP-DiD.

Suggested Citation

  • Daniel de Abreu Pereira Uhr & Guilherme Valle Moura, 2026. "Doubly robust local projections difference-in-differences," Papers 2604.27035, arXiv.org.
    • Handle: RePEc:arx:papers:2604.27035
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    File URL: http://arxiv.org/pdf/2604.27035
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