A Dynamic Hurdle Model for Zero-Inflated Count Data: With an Application to Health Care Utilization
University of Zurich, Department of Economics, Working Paper No. 151
24 Pages Posted: 10 Apr 2014
Date Written: April 2014
Abstract
Excess zeros are encountered in many empirical count data applications. We provide a new explanation of extra zeros, related to the underlying stochastic process that generates events. The process has two rates, a lower rate until the first event, and a higher one thereafter. We derive the corresponding distribution of the number of events during a fixed period and extend it to account for observed and unobserved heterogeneity. An application to the socio-economic determinants of the individual number of doctor visits in Germany illustrates the usefulness of the new approach.
Keywords: excess zeros, Poisson process, exposure, hurdle model
JEL Classification: C25, I10
Suggested Citation: Suggested Citation
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