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A split-treatment design

Author

Listed:
  • Jean-Baptiste Bonnier

    (CRESE - Centre de REcherches sur les Stratégies Economiques (UR 3190) - UFC - Université de Franche-Comté - UBFC - Université Bourgogne Franche-Comté [COMUE])

Abstract

I devise a difference-in-differences design that accounts for the possibility that some treatment effect is split in the reactions to two or more events. At the intersection of settings with a single treatment and with multiple treatments, regression-based methods for this split-treatment design can be subject both to negative weights and contamination bias. I propose a simple solution, a first-difference regression with sample constraints in the spirit of Dube et al.'s (2023) LP-DiD, that allows to identify and estimate sensible causal parameters of interest. This estimator is efficient under random walk errors and unrestricted heterogeneity across groups and events.

Suggested Citation

  • Jean-Baptiste Bonnier, 2024. "A split-treatment design," Working Papers hal-04532056, HAL.
    • Handle: RePEc:hal:wpaper:hal-04532056
    Note: View the original document on HAL open archive server: https://hal.science/hal-04532056
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