Estimation of hurdle models for overdispersed count data

Helmut Farbmacher

Stata Journal, 2011, vol. 11, issue 1, 82-94

Abstract: Hurdle models based on the zero-truncated Poisson-lognormal distribution are rarely used in applied work, although they incorporate some advantages compared with their negative binomial alternatives. I present a command that enables Stata users to estimate Poisson-lognormal hurdle models. I use adaptive Gauss–Hermite quadrature to approximate the likelihood function, and I evaluate the performance of the estimator in Monte Carlo experiments. The model is applied to the number of doctor visits in a sample of the U.S. Medical Expenditure Panel Survey. Copyright 2011 by StataCorp LP.

Keywords: ztpnm; count-data analysis; hurdle models; overdispersion; Poisson-lognormal hurdle models (search for similar items in EconPapers)
Date: 2011
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