Estimating the demand for health care with panel data: a semiparametric Bayesian approach

Markus Jochmann () and Roberto León‐González
Authors registered in the RePEc Author Service: Roberto Leon-Gonzalez

Health Economics, 2004, vol. 13, issue 10, 1003-1014

Abstract: This paper is concerned with the problem of estimating the demand for health care with panel data. A random effects model is specified within a semiparametric Bayesian approach using a Dirichlet process prior. This results in a very flexible distribution for both the random effects and the count variable. In particular, the model can be seen as a mixture distribution with a random number of components, and is therefore a natural extension of prevailing latent class models. A full Bayesian analysis using Markov chain Monte Carlo simulation methods is proposed. The methodology is illustrated with an application using data from Germany. Copyright © 2004 John Wiley & Sons, Ltd.

Date: 2004
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Citations: View citations in EconPapers (18)

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https://doi.org/10.1002/hec.936

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Working Paper: Estimating the Demand for Health Care with Panel Data: A Semiparametric Bayesian Approach (2003)
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Persistent link: https://EconPapers.repec.org/RePEc:wly:hlthec:v:13:y:2004:i:10:p:1003-1014

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