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

✍ Scribed by Markus Jochmann; Roberto León-González

Publisher
John Wiley and Sons
Year
2004
Tongue
English
Weight
242 KB
Volume
13
Category
Article
ISSN
1057-9230

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✦ Synopsis

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.

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