Instrumental-Variable Poisson PML with High-Dimensional Fixed Effects

Ohyun Kwon, Mario Larch, Jangsu Yoon and Yoto Yotov

No 202611, Working Papers from Center for Global Policy Analysis, LeBow College of Business, Drexel University

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.

Keywords: Poisson pseudo-maximum likelihood; instrumental variables; high-dimensional fixed effects; incidental parameter problem; gravity model; split-panel jackknife. (search for similar items in EconPapers)
JEL-codes: C13 C23 C26 F14 (search for similar items in EconPapers)
Pages: 56
Date: 2026-04
New Economics Papers: this item is included in nep-dcm
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