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Bayesian inference in Markov switching vector error correction model

Author

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  • Katsuhiro Sugita

    (Faculty of Law and Letters, University of the Ryukyus)

Abstract

In this paper we consider a Bayesian approach to a Markov switching vector error correction model that allows for regime shifts in the number of cointegrating rank, the cointegrating vectors, the adjustment terms, the deterministic terms, the lag terms and the variance-covariance matrix. We use a valid prior for the cointegrating space, and sample the state variable by employing the multi-move Gibbs sampler, and estimate the cointegrating vectors by a collapsed Gibbs sampler. We also drive the posterior densities for the model where cointegrating vectors are regime-independent.

Suggested Citation

  • Katsuhiro Sugita, 2016. "Bayesian inference in Markov switching vector error correction model," Economics Bulletin, AccessEcon, vol. 36(3), pages 1534-1546.
    • Handle: RePEc:ebl:ecbull:eb-16-00175
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    References listed on IDEAS

    as
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    Cited by:

    1. Katsuhiro Sugita, 2017. "Time Series Analysis of the US Term Structure of Interest Rates Using a Bayesian Markov Switching Cointegration Model," International Journal of Economics and Finance, Canadian Center of Science and Education, vol. 9(3), pages 49-56, March.
    2. Katsuhiro Sugita, 2017. "Non-Linear Analysis of the Fisher Effect: In the Case of Japan," International Journal of Economics and Finance, Canadian Center of Science and Education, vol. 9(11), pages 1-9, November.

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    More about this item

    Keywords

    Bayesian; Markov switching; cointegration;
    All these keywords.

    JEL classification:

    • C4 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics
    • C5 - Mathematical and Quantitative Methods - - Econometric Modeling

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