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Testing For Cointegration Rank Using Bayes Factors

Author

Listed:
  • Sugita, Katsuhiro

    (Department of Economics, University of Warwick)

Abstract
This paper proposes Bayesian methods for estimating the cointegration rank using Bayes factors. We consider natural conjugate priors for computing Bayes factors. First, we estimate the cointegrating vectors for each possible rank. Then, we compute the Bayes factors for each rank against 0 rank. Monte Carlo simulations show that using Bayes factor with conjugate priors produces fairly good results. We apply the method to demand for money in the US.

Suggested Citation

  • Sugita, Katsuhiro, 2002. "Testing For Cointegration Rank Using Bayes Factors," The Warwick Economics Research Paper Series (TWERPS) 654, University of Warwick, Department of Economics.
    • Handle: RePEc:wrk:warwec:654
    as

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    File URL: https://warwick.ac.uk/fac/soc/economics/research/workingpapers/2008/twerp654.pdf
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    References listed on IDEAS

    as
    1. Geweke, John, 1989. "Bayesian Inference in Econometric Models Using Monte Carlo Integration," Econometrica, Econometric Society, vol. 57(6), pages 1317-1339, November.
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    4. Goldfeld, Stephen M. & Sichel, Daniel E., 1990. "The demand for money," Handbook of Monetary Economics, in: B. M. Friedman & F. H. Hahn (ed.), Handbook of Monetary Economics, edition 1, volume 1, chapter 8, pages 299-356, Elsevier.
    5. Johansen, S., 2000. "A Small Sample Correction of the Test for Cointegrating Rank in the Vector Autoregressive Model," Economics Working Papers eco2000/15, European University Institute.
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    9. BAUWENS, Luc & LUBRANO , Michel, 1994. "Identification Restrictions and Posterior Densities in Cointegrated Gaussian VAR Systems," LIDAM Discussion Papers CORE 1994018, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
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    12. Kleibergen, Frank & Paap, Richard, 2002. "Priors, posteriors and bayes factors for a Bayesian analysis of cointegration," Journal of Econometrics, Elsevier, vol. 111(2), pages 223-249, December.
    13. Geweke, John, 1996. "Bayesian reduced rank regression in econometrics," Journal of Econometrics, Elsevier, vol. 75(1), pages 121-146, November.
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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.
    3. Gareth W. Peters & Balakrishnan B. Kannan & Ben Lasscock & Chris Mellen & Simon Godsill, 2010. "Bayesian Cointegrated Vector Autoregression models incorporating Alpha-stable noise for inter-day price movements via Approximate Bayesian Computation," Papers 1008.0149, arXiv.org.

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    More about this item

    Keywords

    Cointegration ; MCMC ; Bayes factor;
    All these keywords.

    JEL classification:

    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: 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

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