Estimating the Demand for Health Care with Panel Data: A Semiparametric Bayesian Approach

Markus Jochmann () and Roberto Leon-Gonzalez

No 2003005, Working Papers from The University of Sheffield, Department of Economics

Abstract: This paper is concerned with the problem of estimating the demand for health care with panel data. A random effects model is specifed in a semiparametric Bayesian fashion using a Dirichlet process prior. This results in a very exible mixture distribution with an in nite number of components for the random effects. Therefore, the model can be seen as a natural extension of prevailing latent class models. A full Bayesian analysis using Markov chain Monte Carlo (MCMC)simulation methods is discussed. The methodology is illustrated with an application using data from Germany.

Keywords: random efects model; Dirichlet process prior; MCMC (search for similar items in EconPapers)
JEL-codes: C14 C23 I10 (search for similar items in EconPapers)
Pages: 26 pages
Date: 2003-10, Revised 2003-10
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Journal Article: Estimating the demand for health care with panel data: a semiparametric Bayesian approach (2004)
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