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Non-Gaussian dynamic Bayesian modelling for panel data

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Juárez, Miguel A. and Steel, Mark F. J.. (2010) Non-Gaussian dynamic Bayesian modelling for panel data. Journal of Applied Econometrics, Vol.25 (No.7). pp. 1128-1154. ISSN 0883-7252

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Official URL: http://dx.doi.org/10.1002/jae.1113

Abstract

A first order autoregressive non-Gaussian model for analysing panel data is proposed. The main feature is that the model is able to accommodate fat tails and also skewness, thus allowing for outliers and asymmetries. The modelling approach is designed to gain sufficient flexibility, without sacrificing interpretability and computational ease. The model incorporates individual effects and covariates and we pay specific attention to the elicitation of the prior. As the prior structure chosen is not proper, we derive conditions for the existence of the posterior. By considering a model with individual dynamic parameters we are also able to formally test whether the dynamic behaviour is common to all units in the panel. The methodology is illustrated with two applications involving earnings data and one on growth of countries.

Item Type:	Journal Article
Subjects:	Q Science > QA Mathematics
Divisions:	Faculty of Science > Statistics Faculty of Science > Centre for Systems Biology
Library of Congress Subject Headings (LCSH):	Mathematical statistics
Journal or Publication Title:	Journal of Applied Econometrics
Publisher:	Wiley-Blackwell Publishing, Inc
ISSN:	0883-7252
Date:	2010
Volume:	Vol.25
Number:	No.7
Page Range:	pp. 1128-1154
Identification Number:	10.1002/jae.1113
Status:	Not Peer Reviewed
Publication Status:	Published
Access rights to Published version:	Open 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/4581