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Sampling the Variance-Covariance Matrix in the Bayesian Multivariate Probit Model

Leon-Gonzalez, R. (2003) Sampling the Variance-Covariance Matrix in the Bayesian Multivariate Probit Model. Working Paper. Department of Economics, University of Sheffield ISSN 1749-8368

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Abstract

This paper is concerned with the Bayesian estimation of a Multivariate Probit model. In particular, this paper provides a method to sample the restricted variancecovariance matrix directly from its conditional posterior density. The method allows the application of a standard Gibbs sampling algorithm to sample from the posterior density of the parameters, and hence it avoids the use of a Metropolis step. The method uses a decomposition of the Inverted Wishart density and alternative identification restrictions.

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.
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: 14 Jun 2014 09:10
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 2003008
Related URLs:
URI: http://eprints.whiterose.ac.uk/id/eprint/9879

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