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Consistent estimation of zero-inflated count models


Staub, Kevin E; Winkelmann, Rainer (2013). Consistent estimation of zero-inflated count models. Health Economics, 22(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.

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.

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11 citations in Web of Science®
13 citations in Scopus®
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Additional indexing

Item Type:Journal Article, refereed, original work
Communities & Collections:03 Faculty of Economics > Department of Economics
Dewey Decimal Classification:330 Economics
Language:English
Date:24 June 2013
Deposited On:13 Jun 2012 09:50
Last Modified:05 Apr 2016 15:52
Publisher:Wiley-Blackwell
ISSN:1057-9230
Free access at:Related URL. An embargo period may apply.
Publisher DOI:https://doi.org/10.1002/hec.2844

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