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Model comparison of coordinate-free multivariate skewed distributions with an application to stochastic frontiers

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Ferreira, Jose T. A. S. and Steel, Mark F. J.. (2007) Model comparison of coordinate-free multivariate skewed distributions with an application to stochastic frontiers. Journal of Econometrics, Vol.137 (No.2). pp. 641-673. ISSN 0304-4076

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Official URL: http://dx.doi.org/10.1016/j.jeconom.2005.11.016

Abstract

We consider classes of multivariate distributions which can model skewness and are closed under orthogonal transformations. We review two classes of such distributions proposed in the literature and focus our attention on a particular, yet quite flexible, subclass of one of these classes. Members of this subclass are defined by affine transformations of univariate (skewed) distributions that ensure the existence of a set of coordinate axes along which there is independence and the marginals are known analytically. The choice of an appropriate m-dimensional skewed distribution is then restricted to the simpler problem of choosing m univariate skewed distributions. We introduce a Bayesian model comparison setup for selection of these univariate skewed distributions. The analysis does not rely on the existence of moments (allowing for any tail behaviour) and uses equivalent priors on the common characteristics of the different models. Finally, we apply this framework to multi-output stochastic frontiers using data from Dutch dairy farms. (C) 2006 Elsevier B.V. All rights reserved.

Item Type: Journal Article
Subjects: H Social Sciences > HC Economic History and Conditions
Q Science > QA Mathematics
H Social Sciences
Divisions: Faculty of Science > Statistics
Journal or Publication Title: Journal of Econometrics
Publisher: Elsevier BV * North-Holland
ISSN: 0304-4076
Date: April 2007
Volume: Vol.137
Number: No.2
Number of Pages: 33
Page Range: pp. 641-673
Identification Number: 10.1016/j.jeconom.2005.11.016
Status: Peer Reviewed
Publication Status: Published
Access rights to Published version: Restricted or Subscription Access
URI: http://wrap.warwick.ac.uk/id/eprint/32097

Data sourced from Thomson Reuters' Web of Knowledge

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