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Applying Flexible Parameter Restrictions in Markov-Switching Vector Autoregression Models

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  • Andrew Binning
  • Junior Maih

Abstract

We present a new method for imposing parameter restrictions in Markov-Switching Vector Autoregression (MS-VAR) models. Our method is more flexible than competing methodologies and easily handles a range of parameter restrictions over different equations, regimes and parameter types. We also expand the range of priors used in the MS-VAR literature. We demonstrate the versatility of our approach using three appropriate examples.

Suggested Citation

  • Andrew Binning & Junior Maih, 2015. "Applying Flexible Parameter Restrictions in Markov-Switching Vector Autoregression Models," Working Papers No 12/2015, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School.
  • Handle: RePEc:bny:wpaper:0040
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    References listed on IDEAS

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    7. Waggoner, Daniel F. & Zha, Tao, 2003. "A Gibbs sampler for structural vector autoregressions," Journal of Economic Dynamics and Control, Elsevier, vol. 28(2), pages 349-366, November.
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    More about this item

    Keywords

    Parameter Restrictions; MS-VAR estimation; Block Exogeneity; Zero Restrictions; Bayesian estimation;
    All these keywords.

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