Consistent Estimation Of Zero‐Inflated Count Models
AbstractApplications 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 paper 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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Bibliographic InfoArticle provided by John Wiley & Sons, Ltd. in its journal Health Economics.
Volume (Year): 22 (2013)
Issue (Month): 6 (06)
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Web page: http://www3.interscience.wiley.com/cgi-bin/jhome/5749
Other versions of this item:
- Kevin E. Staub & Rainer Winkelmann, 2009. "Consistent estimation of zero-inflated count models," SOI - Working Papers 0908, Socioeconomic Institute - University of Zurich, revised Aug 2011.
- I12 - Health, Education, and Welfare - - Health - - - Health Production
- C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
- C25 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions
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