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Efficient Posterior Simulation for Cointegrated Models with Priors On the Cointegration Space

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Author Info
Gary Koop ()
Roberto León-González ()
Rodney W. Strachan ()

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Abstract

A message coming out of the recent Bayesian literature on cointegration is that it is important to elicit a prior on the space spanned by the cointegrating vectors (as opposed to a particular identified choice for these vectors). In this note, we discuss a sensible way of eliciting such a prior. Furthermore, we develop a collapsed Gibbs sampling algorithm to carry out efficient posterior simulation in cointegration models. The computational advantages of our algorithm are most pronounced with our model, since the form of our prior precludes simple posterior simulation using conventional methods (e.g. a Gibbs sampler involves non-standard posterior conditionals). However, the theory we draw upon implies our algorithm will be more efficient even than the posterior simulation methods which are used with identified versions of cointegration models.

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File URL: http://www.le.ac.uk/economics/research/RePEc/lec/leecon/dp05-13.pdf
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Publisher Info
Paper provided by Department of Economics, University of Leicester in its series Discussion Papers in Economics with number 05/13.

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Date of creation: Jul 2005
Date of revision: Apr 2006
Handle: RePEc:lec:leecon:05/13

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  1. Gary Koop & Rodney Strachan & Herman van Dijk & Mattias Villani, 2004. "Bayesian Approaches to Cointegration," Discussion Papers in Economics 04/27, Department of Economics, University of Leicester. [Downloadable!]
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