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Multi-episode count data estimation for health care demand

Author

Listed:
  • Hiroaki Masuhara

    (Faculty of Economics and Law, Shinshu University)

Abstract

This study proposes new multi-episode count data models for health care analysis. Using the Pólya-Aeppli distribution, a Poisson process for seeking medical care and a geometric process for the number of treatments are specified. Moreover, this paper introduces unobserved heterogeneities to both Poisson and geometric processes. Using the National Medical Expenditure Survey, the proposed models demonstrate good performance and the large differences in estimated coefficients compared with conventional hurdle and finite mixture count data models. It is useful to apply the multi-episode count data models proposed in this paper.

Suggested Citation

  • Hiroaki Masuhara, 2021. "Multi-episode count data estimation for health care demand," Economics Bulletin, AccessEcon, vol. 41(4), pages 2281-2290.
    • Handle: RePEc:ebl:ecbull:eb-21-00842
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    File URL: http://www.accessecon.com/Pubs/EB/2021/Volume41/EB-21-V41-I4-P196.pdf
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    More about this item

    Keywords

    count data; multi-episode; geometric distribution; health care demand; finite mixture model; hurdle (two-part) model;
    All these keywords.

    JEL classification:

    • C3 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables
    • C2 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables

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