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Bayesian Model Selection with an Uninformative Prior*
Author(s) -
Strachan Rodney W.,
Dijk Herman K.
Publication year - 2003
Publication title -
oxford bulletin of economics and statistics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.131
H-Index - 73
eISSN - 1468-0084
pISSN - 0305-9049
DOI - 10.1046/j.0305-9049.2003.00095.x
Subject(s) - prior probability , bayesian probability , model selection , cointegration , econometrics , bayes factor , bayes' theorem , mathematics , posterior probability , bayesian inference , bayes estimator , dimension (graph theory) , selection (genetic algorithm) , mathematical economics , computer science , statistics , artificial intelligence , pure mathematics
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.