CONSISTENT ESTIMATION OF ZERO‐INFLATED COUNT MODELS

Kevin Staub and Rainer Winkelmann

Health Economics, 2013, vol. 22, issue 6, 673-686

Abstract: Applications of zero‐inflated count data models have proliferated in health economics. However, zero‐inflated Poisson or zero‐inflated negative binomial maximum likelihood estimators are not robust to misspecification. This article proposes Poisson quasi‐likelihood estimators as an alternative. These estimators are consistent in the presence of excess zeros without having to specify the full distribution. The advantages of the Poisson quasi‐likelihood approach are illustrated in a series of Monte Carlo simulations and in an application to the demand for health services. Copyright © 2012 John Wiley & Sons, Ltd.

Date: 2013
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https://doi.org/10.1002/hec.2844

Related works:
Working Paper: Consistent estimation of zero-inflated count models (2011)
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Persistent link: https://EconPapers.repec.org/RePEc:wly:hlthec:v:22:y:2013:i:6:p:673-686

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