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Estimating Healthcare Demand for an Aging Population: A Flexible and Robust Bayesian Joint Model

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Author Info

  • Arnab Mukherji

    ()
    (Centre for Public Policy, Indian Institute of Management Bangalore)

  • Satrajit Roychowdhury

    (Expert Statistical Methodologist, Novartis Pharmaceutical Company)

  • Pulak Ghosh

    (Department of QM & IS, Indian Institute of Management Bangalore)

  • Sarah Brown

    (Department of Economics, The University of Sheffield)

Abstract

In this paper, we analyse two frequently used measures of the demand for health care, namely hospital visits and out-of-pocket health care expenditure, which have been analysed separately in the existing literature. Given that these two measures of healthcare demand are highly likely to be closely correlated, we propose a framework to jointly model hospital visits and out-of-pocket medical expenditure. Furthermore, the joint framework allows for the presence of non-linear effects of covariates using splines to capture the effects of aging on healthcare demand. Sample heterogeneity is modelled robustly with the random effects following Dirichlet process priors with explicit cross-part correlation. The findings of our empirical analysis of the U.S. Health and Retirement Survey indicate that the demand for healthcare varies with age and gender and exhibits significant cross-part correlation that provides a rich understanding of how aging affects health care demand, which is of particular policy relevance in the context of an aging population.

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File URL: http://www.shef.ac.uk/economics/research/serps/articles/2012_027.html
File Function: First version, 2012
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Bibliographic Info

Paper provided by The University of Sheffield, Department of Economics in its series Working Papers with number 2012027.

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Length: 37 pages
Date of creation: 2012
Date of revision:
Handle: RePEc:shf:wpaper:2012027

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Keywords: aging; Bayesian methods; healthcare demand; joint model; splines;

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