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A Monte Carlo comparison of Bayesian testing for cointegration rank

Author

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  • Katsuhiro Sugita

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

Abstract

This article considers a Bayesian testing for cointegration rank, using an approach developed by Strachan and van Dijk (2007), that is based on Koop, Leon-Gonzalez, and Strachan (2006). The Bayes factors are calculated for selecting cointegrating rank. We calculate the Bayes factors using two methods - the Schwarz BIC approximation and Chib's (1995) algorithm for calculating the marginal likelihood. We run Monte Carlo simulations to compare the two methods.

Suggested Citation

  • Katsuhiro Sugita, 2009. "A Monte Carlo comparison of Bayesian testing for cointegration rank," Economics Bulletin, AccessEcon, vol. 29(3), pages 2145-2151.
    • Handle: RePEc:ebl:ecbull:eb-08c10009
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    File URL: http://www.accessecon.com/Pubs/EB/2009/Volume29/EB-09-V29-I3-P63.pdf
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    Cited by:

    1. Karlsson, Sune, 2013. "Forecasting with Bayesian Vector Autoregression," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 791-897, Elsevier.
    2. Gareth W. Peters & Balakrishnan Kannan & Ben Lasscock & Chris Mellen, 2010. "Model Selection and Adaptive Markov chain Monte Carlo for Bayesian Cointegrated VAR model," Papers 1004.3830, arXiv.org.

    More about this item

    JEL classification:

    • C1 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General

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