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Consistent estimation of zero-inflated count models

Author

Listed:
  • Kevin E. Staub

    (Department of Economics, University of Zurich)

  • Rainer Winkelmann

    (Department of Economics, University of Zurich)

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 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.

Suggested Citation

  • 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.
    • Handle: RePEc:soz:wpaper:0908
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    References listed on IDEAS

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    More about this item

    Keywords

    Excess zeros; Poisson; logit; unobserved heterogeneity; misspecification;
    All these keywords.

    JEL classification:

    • I12 - Health, Education, and Welfare - - Health - - - Health Behavior
    • 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; Probabilities

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