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


Arnab Mukherji


Center for Public Policy, IIM Bangalore; Indian Institute of Management (IIMB), Bangalore

Pulak Ghosh


Indian Institute of Management (IIMB), Bangalore

Satrajit Roychowdhury


affiliation not provided to SSRN

December 30, 2011

IIM Bangalore Research Paper No. 357

Abstract:     
We propose a joint model to combine models for hospital visits and out-of-pocket medical expenditures. It allows for the presence of non-linear effects of covariates using splines to capture the effects of aging on healthcare demand. Sample heterogeneity is modeled robustly with the random effects following Dirichlet process priors with explicit cross-part correlation. We validate our model using a simulation study. We apply this model to Health and Retirement Survey data and show that healthcare varies with age and gender and exhibits significant cross-part correlation that provides a richer understanding of how aging affects healthcare demand.

Number of Pages in PDF File: 33

Keywords: Bayesian Methods, Joint Model, Healthcare Demand, Aging, Splines

JEL Classification: C11, C14, I10

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Date posted: July 27, 2012  

Suggested Citation

Mukherji, Arnab, Ghosh, Pulak and Roychowdhury, Satrajit, Estimating Healthcare Demand for an Aging Population: A Flexible and Robust Bayesian Joint Model (December 30, 2011). IIM Bangalore Research Paper No. 357. Available at SSRN: http://ssrn.com/abstract=2117681 or http://dx.doi.org/10.2139/ssrn.2117681

Contact Information

Arnab Mukherji (Contact Author)
Center for Public Policy, IIM Bangalore ( email )
Bannerghata Road
Bangalore, Karnataka 560076
India
HOME PAGE: http://www342.pair.com/mukherji/arnab
Indian Institute of Management (IIMB), Bangalore ( email )
Bannerghatta Road
Bangalore, Karnataka 560076
India

Pulak Ghosh
Indian Institute of Management (IIMB), Bangalore ( email )
Bannerghatta Road
Bangalore, Karnataka 560076
India

Satrajit Roychowdhury
affiliation not provided to SSRN
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