Instrumental-Variable Poisson PML with High-Dimensional Fixed Effects

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.