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Bayesian Model Selection with an Uninformative Prior

Author

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  • Rodney W. Strachan

    () (Keele University, Department of Economics)

  • Herman K. van Dijk

    () (Erasmus University Rotterdam)

Abstract

Bayesian 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.

Suggested Citation

  • Rodney W. Strachan & Herman K. van Dijk, 2004. "Bayesian Model Selection with an Uninformative Prior," Keele Economics Research Papers KERP 2004/01, Centre for Economic Research, Keele University.
  • Handle: RePEc:kee:kerpuk:2004/01
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    References listed on IDEAS

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    Citations

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    Cited by:

    1. Villani, Mattias, 2005. "Bayesian Inference of General Linear Restrictions on the Cointegration Space," Working Paper Series 189, Sveriges Riksbank (Central Bank of Sweden).
    2. Rodney W. Strachan & Herman K. van Dijk, 2014. "Divergent Priors and Well Behaved Bayes Factors," Central European Journal of Economic Modelling and Econometrics, CEJEME, vol. 6(1), pages 1-31, March.
    3. Warne, Anders, 2006. "Bayesian inference in cointegrated VAR models: with applications to the demand for euro area M3," Working Paper Series 692, European Central Bank.
    4. Andrea Silvestrini, 2010. "Testing fiscal sustainability in Poland: a Bayesian analysis of cointegration," Empirical Economics, Springer, vol. 39(1), pages 241-274, August.
    5. Sugita, Katsuhiro, 2006. "Bayesian Analysis of Dynamic Multivariate Models with Multiple Structural Breaks," Discussion Papers 2006-14, Graduate School of Economics, Hitotsubashi University.

    More about this item

    Keywords

    Posterior probability; Laplace approximation; Structural modelling; Cointegration; Exogeneity; Model averaging;

    JEL classification:

    • 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; State Space Models
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection

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