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Instrumental-Variable Poisson PML with High-Dimensional Fixed Effects

Author

Listed:
  • Ohyun Kwon
  • Mario Larch
  • Jangsu Yoon
  • Yoto V. Yotov

Abstract

We implement an instrumental-variable Poisson pseudo-maximum likelihood estimator with high-dimensional fixed effects (IV-PPML-HDFE). To correct for incidental parameter bias, we use a split-panel jackknife (SPJ) routine with bootstrapped standard errors. Monte Carlo simulations across the three most common fixed-effect structures confirm that SPJ reduces the mean absolute bias by 42% and raises mean bootstrap confidence-interval coverage from 69% to 92%. We provide a robust and user-friendly 'ivppmlhdfe' package, and deploy it in three empirical applications to establish the validity and usefulness of our methods.

Suggested Citation

  • Ohyun Kwon & Mario Larch & Jangsu Yoon & Yoto V. Yotov, 2026. "Instrumental-Variable Poisson PML with High-Dimensional Fixed Effects," CESifo Working Paper Series 12641, CESifo.
    • Handle: RePEc:ces:ceswps:_12641
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    JEL classification:

    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
    • C26 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Instrumental Variables (IV) Estimation
    • F14 - International Economics - - Trade - - - Empirical Studies of Trade

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