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Model-based clustering of non-Gaussian panel data based on skew-t distributions

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Juárez, Miguel A. and Steel, Mark F. J.. (2010) Model-based clustering of non-Gaussian panel data based on skew-t distributions. Journal of Business and Economic Statistics, Vol.28 (No.1). pp. 52-66. ISSN 0735-0015

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Official URL: http://dx.doi.org/10.1198/jbes.2009.07145

Abstract

We propose a model-based method to cluster units within a panel. The underlying model is autoregressive and non-Gaussian, allowing for both skewness and fat tails, and the units are clustered according to their dynamic behavior. equilibrium level, and the effect of covariates. Inference is addressed from a Bayesian perspective, and model comparison is conducted using Bayes factors. Particular attention is paid to prior elicitation and posterior propriety. We suggest priors that require little subjective input and have hierarchical structures that enhance inference robustness. We apply our methodology to GDP growth of European regions and to employment growth of Spanish firms.

Item Type:	Journal Article
Subjects:	H Social Sciences > HB Economic Theory Q Science > QA Mathematics
Divisions:	Faculty of Science > Statistics
Library of Congress Subject Headings (LCSH):	Cluster analysis, Gross domestic product -- Europe -- Econometric models, Labor market -- Spain -- Econometric models
Journal or Publication Title:	Journal of Business and Economic Statistics
Publisher:	Americal Statistical Association
ISSN:	0735-0015
Date:	January 2010
Volume:	Vol.28
Number:	No.1
Number of Pages:	15
Page Range:	pp. 52-66
Identification Number:	10.1198/jbes.2009.07145
Status:	Peer Reviewed
Publication Status:	Published
Access rights to Published version:	Restricted or Subscription Access
Funder:	Engineering and Physical Sciences Research Council (EPSRC)
Grant number:	GR/T17908/01 (EPSRC)
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URI:	http://wrap.warwick.ac.uk/id/eprint/16591