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Bayesian Model Selection with an Uninformative Prior

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Author Info
Rodney W. Strachan
Herman K. Dijk

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Abstract

Bayesian model selection with posterior probabilities and no subjective prior information is generally not possible because of the Bayes factors being ill-defined. Using careful consideration of the parameter of interest in cointegration analysis and a re-specification of the triangular model of Phillips ("Econometrica", Vol. 59, pp. 283-306, 1991), this paper presents an approach that allows for Bayesian comparison of models of cointegration with 'ignorance' priors. Using the concept of Stiefel and Grassman manifolds, diffuse priors are specified on the dimension and direction of the cointegrating space. The approach is illustrated using a simple term structure of the interest rates model. Copyright 2003 Blackwell Publishing Ltd.

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File URL: http://www.blackwell-synergy.com/doi/abs/10.1046/j.0305-9049.2003.00095.x
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Publisher Info
Article provided by Department of Economics, University of Oxford in its journal Oxford Bulletin of Economics & Statistics.

Volume (Year): 65 (2003)
Issue (Month): s1 (December)
Pages: 863-876
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Handle: RePEc:bla:obuest:v:65:y:2003:i:s1:p:863-876

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  1. Villani, Mattias, 2005. "Bayesian Inference of General Linear Restrictions on the Cointegration Space," Working Paper Series 189, Sveriges Riksbank (Central Bank of Sweden). [Downloadable!]
  2. Anders Warne, 2006. "Bayesian inference in cointegrated VAR models - with applications to the demand for euro area M3," Working Paper Series 692, European Central Bank. [Downloadable!]
  3. Andrea, SILVESTRINI, 2007. "Testing fiscal sustainability in Poland : a Bayesian analysis of cointegration," Discussion Papers (ECON - Département des Sciences Economiques) 2007040, Université catholique de Louvain, Département des Sciences Economiques. [Downloadable!]
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  4. Deborah Gefang, 2008. "Revisiting money-output causality from a Bayesian logistic smooth transition VECM perspective," Discussion Papers in Economics 08/5, Department of Economics, University of Leicester. [Downloadable!]
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