Bayesian Model Selection with an Uninformative Prior
AbstractBayesian model selection with posterior probabilities and no subjective prior information is generally not possible due to the Bayes factors being ill-defined. Using careful consideration of the parameter of interest in cointegration analysis and a respecifcation of the triangular model of Phillips (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 dimension and direction of the cointegrating space. The approach is illustrated using a simple term structure of interest rates model.
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Bibliographic InfoPaper provided by Centre for Economic Research, Keele University in its series Keele Economics Research Papers with number KERP 2004/01.
Length: 19 pages
Date of creation: Jan 2004
Date of revision:
Publication status: Published in Oxford Bulletin of Economics and Statistics, Volume 65, Supplement 1, December 2003, pp. 863-876. [ doi:10.1046/j.0305-9049.2003.00095.x ]
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Postal: Centre for Economic Research, Research Institute for Public Policy and Management, Keele University, Staffordshire ST5 5BG - United Kingdom
Other versions of this item:
- Rodney W. Strachan & Herman K. Dijk, 2003. "Bayesian Model Selection with an Uninformative Prior," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 65(s1), pages 863-876, December.
- C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
- C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
- C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
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