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Proportional Treatment Effects in Staggered Settings: An Approach for Poisson Pseudo-Maximum Likelihood

Author

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  • Ninon Moreau-Kastler

    (EU Tax Observatory, Paris School of Economics)

Abstract

I propose a counterfactual approach to measure proportional treatment effects for staggered multiplicative difference-in-differences (DiD) models with Poisson Pseudo-Maximum Likelihood (PPML). Two-way fixed effect (TWFE) linear estimators do not recover DiD estimates in the presence of a staggered treatment. I show that the wrong comparisons problem extends to TWFE PPML. I provide evidence that robust estimators for the linear case do not naturally extend to PPML, as aggregation of lower-level effects is challenging in the non-linear case. In these settings, my proposed estimator recovers a quantity analogous to that in the canonical 2-by-2 TWFE PPML model: the percent change of the average.

Suggested Citation

  • Ninon Moreau-Kastler, 2025. "Proportional Treatment Effects in Staggered Settings: An Approach for Poisson Pseudo-Maximum Likelihood," Working Papers 031, EU Tax Observatory.
    • Handle: RePEc:dbp:wpaper:031
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    More about this item

    Keywords

    PPML; difference-in-differences; ratio-of-ratios; staggered treatment;
    All these keywords.

    JEL classification:

    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
    • F14 - International Economics - - Trade - - - Empirical Studies of Trade
    • H26 - Public Economics - - Taxation, Subsidies, and Revenue - - - Tax Evasion and Avoidance

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