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

Jochmann, M. and Leon-Gonzalez, R. (2003) Estimating the Demand for Health Care with Panel Data: A Semiparametric Bayesian Approach. Working Paper. Department of Economics, University of Sheffield ISSN 1749-8368

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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.

Item Type: Monograph (Working Paper)
Copyright, Publisher and Additional Information: The Sheffield Economics Research Paper (SERP) series offers a forum for the research output of the academic staff and research students of the Department of Economics, University of Sheffield. Papers are reviewed for quality and presentation by a departmental editor. However, the contents and opinions expressed remain the responsibility of the authors. All papers may be downloaded free on the understanding that the contents are preliminary and therefore permission from the author(s) should be sought before they are referenced.
Keywords: random effects model, Dirichlet process prior, MCMC
Institution: The University of Sheffield
Academic Units: The University of Sheffield > Faculty of Social Sciences (Sheffield) > Department of Economics (Sheffield) > Sheffield Economics Research Papers Series
Depositing User: Repository Officer
Date Deposited: 20 Oct 2009 12:22
Last Modified: 07 Jun 2014 20:02
Published Version: http://www.shef.ac.uk/economics/research/serps/yea...
Status: Published
Publisher: Department of Economics, University of Sheffield
Identification Number: Sheffield Economic Research Paper Series 2003005
Related URLs:
URI: http://eprints.whiterose.ac.uk/id/eprint/9882

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