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What belongs where? Variable selection for zero-inflated count models with an application to the demand for health care

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  • Markus Jochmann

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Abstract

This paper develops a Bayesian spike and slab model for zero-inflated count models which are commonly used in health economics. We account for model uncertainty and allow for model averaging in situations with many potential regressors. The proposed techniques are applied to a German data set analyzing the demand for health care. An accompanying package for the free statistical software environment R is provided. Copyright Springer-Verlag Berlin Heidelberg 2013

Suggested Citation

  • Markus Jochmann, 2013. "What belongs where? Variable selection for zero-inflated count models with an application to the demand for health care," Computational Statistics, Springer, vol. 28(5), pages 1947-1964, October.
  • Handle: RePEc:spr:compst:v:28:y:2013:i:5:p:1947-1964
    DOI: 10.1007/s00180-012-0388-z
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    References listed on IDEAS

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    1. Deb, Partha & Munkin, Murat K. & Trivedi, Pravin K., 2006. "Private Insurance, Selection, and Health Care Use: A Bayesian Analysis of a Roy-Type Model," Journal of Business & Economic Statistics, American Statistical Association, vol. 24, pages 403-415, October.
    2. Andreas Million & Regina T. Riphahn & Achim Wambach, 2003. "Incentive effects in the demand for health care: a bivariate panel count data estimation," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 18(4), pages 387-405.
    3. Geweke, John & Keane, Michael, 2007. "Smoothly mixing regressions," Journal of Econometrics, Elsevier, vol. 138(1), pages 252-290, May.
    4. Mullahy, John, 1986. "Specification and testing of some modified count data models," Journal of Econometrics, Elsevier, vol. 33(3), pages 341-365, December.
    5. D. Böhning & E. Dietz & P. Schlattmann & L. Mendonça & U. Kirchner, 1999. "The zero-inflated Poisson model and the decayed, missing and filled teeth index in dental epidemiology," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 162(2), pages 195-209.
    6. Pizer, Steven D. & Prentice, Julia C., 2011. "Time is money: Outpatient waiting times and health insurance choices of elderly veterans in the United States," Journal of Health Economics, Elsevier, vol. 30(4), pages 626-636, July.
    7. Eddelbuettel, Dirk & Francois, Romain, 2011. "Rcpp: Seamless R and C++ Integration," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 40(i08).
    8. Markus Jochmann & Roberto León-González, 2004. "Estimating the demand for health care with panel data: a semiparametric Bayesian approach," Health Economics, John Wiley & Sons, Ltd., vol. 13(10), pages 1003-1014.
    9. Nazmi Sari, 2009. "Physical inactivity and its impact on healthcare utilization," Health Economics, John Wiley & Sons, Ltd., vol. 18(8), pages 885-901.
    10. Gert G. Wagner & Joachim R. Frick & Jürgen Schupp, 2007. "The German Socio-Economic Panel Study (SOEP) – Scope, Evolution and Enhancements," Schmollers Jahrbuch : Journal of Applied Social Science Studies / Zeitschrift für Wirtschafts- und Sozialwissenschaften, Duncker & Humblot, Berlin, vol. 127(1), pages 139-169.
    11. Street, Andrew & Jones, Andrew & Furuta, Aya, 1999. "Cost-sharing and pharmaceutical utilisation and expenditure in Russia," Journal of Health Economics, Elsevier, vol. 18(4), pages 459-472, August.
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    Cited by:

    1. 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

    Bayesian; Spike and slab model; Model uncertainty; Model averaging; Count data; Zero-inflation; Demand for health care; C11; C25; I11;

    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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