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What Belongs Where? Variable Selection for Zero-Inflated Count Models with an Application to the Demand for Health Care

Author

Listed:
  • Markus Jochmann

    (Department of Economics, University of Strathclyde)

Abstract

This paper develops stochastic search variable selection (SSVS) for zero-inflated count models which are commonly used in health economics. This allows for either model averaging or model selection in situations with many potential regressors. The proposed techniques are applied to a data set from Germany considering the demand for health care. A package for the free statistical software environment R is provided.

Suggested Citation

  • Markus Jochmann, 2009. "What Belongs Where? Variable Selection for Zero-Inflated Count Models with an Application to the Demand for Health Care," Working Paper series 45_09, Rimini Centre for Economic Analysis.
    • Handle: RePEc:rim:rimwps:45_09
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    Cited by:

    1. is not listed on IDEAS
    2. John Haslett & Andrew C. Parnell & John Hinde & Rafael de Andrade Moral, 2022. "Modelling Excess Zeros in Count Data: A New Perspective on Modelling Approaches," International Statistical Review, International Statistical Institute, vol. 90(2), pages 216-236, August.
    3. Antonio J. Sáez-Castillo & Antonio Conde-Sánchez, 2017. "Detecting over- and under-dispersion in zero inflated data with the hyper-Poisson regression model," Statistical Papers, Springer, vol. 58(1), pages 19-33, March.

    More about this item

    Keywords

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    JEL classification:

    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
    • C25 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions; Probabilities
    • I11 - Health, Education, and Welfare - - Health - - - Analysis of Health Care Markets

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