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Estimating effects of staggered intervention with count and binary outcomes: a simulation study

Author

Listed:
  • Yadav, Anil

    (Central Bank of Ireland)

  • McHale, John

    (University of Galway)

  • Harold, Jason

    (University of Galway)

  • O'Neill, Stephen

    (London School of Hygiene & Tropical Medicine)

Abstract

Difference-in-Differences and Event-study methods with staggered intervention may provide biased estimates when these approaches are implemented using a two-way fixed effect (TWFE) estimator in the presence of heterogeneous effects. Recent literature proposed alternative estimators that are unbiased, however to date, attention has primarily focused on linear outcome models. This study addresses this gap by extending five of these alternative estimators to count and binary outcomes and assessing their accuracy against the TWFE estimator in Monte Carlo simulations. While unbiased for linear models, some of the estimators yield biased estimates for nonlinear outcomes. An application revisits the statistical association between citations and star coauthorship.

Suggested Citation

  • Yadav, Anil & McHale, John & Harold, Jason & O'Neill, Stephen, 2024. "Estimating effects of staggered intervention with count and binary outcomes: a simulation study," Research Technical Papers 4/RT/24, Central Bank of Ireland.
    • Handle: RePEc:cbi:wpaper:4/rt/24
    as

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    File URL: https://www.centralbank.ie/docs/default-source/publications/research-technical-papers/estimating-effects-of-staggered-intervention-with-count-and-binary-outcomes.pdf?sfvrsn=f937611a_7
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    References listed on IDEAS

    as
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    More about this item

    Keywords

    Nonlinear difference-in-differences and Event-study; Staggered intervention; Count and Binary outcomes; Treatment effect heterogeneity.;
    All these keywords.

    JEL classification:

    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C18 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Methodolical Issues: General
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
    • C35 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions

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