Griffin, Jim E. and Steel, Mark F. J.. (2011) Stick-breaking autoregressive processes. Journal of Econometrics, Vol.162 (No.2). pp. 383-396. ISSN 0304-4076

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Abstract

This paper considers the problem of defining a time-dependent nonparametric prior for use in Bayesian nonparametric modelling of time series. A recursive construction allows the definition of priors whose marginals have a general stick-breaking form. The processes with Poisson-Dirichlet and Dirichlet process marginals are investigated in some detail. We develop a general conditional Markov Chain Monte Carlo (MCMC) method for inference in the wide subclass of these models where the parameters of the marginal stick-breaking process are nondecreasing sequences. We derive a generalised Polya urn scheme type representation of the Dirichlet process construction, which allows us to develop a marginal MCMC method for this case. We apply the proposed methods to financial data to develop a semi-parametric stochastic volatility model with a time-varying nonparametric returns distribution. Finally, we present two examples concerning the analysis of regional GDP and its growth. (C) 2011 Elsevier B.V. All rights reserved.

Item Type:	Journal Article
Subjects:	Q Science > QA Mathematics
Divisions:	Faculty of Science > Statistics
Library of Congress Subject Headings (LCSH):	Bayesian statistical decision theory, Nonparametric statistics
Journal or Publication Title:	Journal of Econometrics
Publisher:	Elsevier BV * North-Holland
ISSN:	0304-4076
Date:	June 2011
Volume:	Vol.162
Number:	No.2
Page Range:	pp. 383-396
Identification Number:	10.1016/j.jeconom.2011.03.001
Status:	Peer Reviewed
Publication Status:	Published
Access rights to Published version:	Restricted or Subscription Access
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URI:	http://wrap.warwick.ac.uk/id/eprint/39933

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