IDEAS home Printed from https://ideas.repec.org/p/mlb/wpaper/1191.html
   My bibliography  Save this paper

Granger Causality and Regime Inference in Bayesian Markov-Switching VARs

Author

Listed:
  • Matthieu Droumaguet

    (Department of Economics, European University Institute)

  • Anders Warne

    (Directorate General Research, European Central Bank)

  • Tomasz Wozniak

    () (Department of Economics, University of Melbourne)

Abstract

We derive restrictions for Granger noncausality in Markov-switching vector autoregressive models and also show under which conditions a variable does not affect the forecast of the hidden Markov process. Based on Bayesian approach to evaluating the hypotheses, the computational tools for posterior inference include a novel block Metropolis-Hastings sampling algorithm for the estimation of the restricted models. We analyze a system of monthly US data on money and income. The results of testing in MS-VARs contradict those in linear VARs: the money aggregate M1 is useful for forecasting income and for predicting the next period’s state.

Suggested Citation

  • Matthieu Droumaguet & Anders Warne & Tomasz Wozniak, 2015. "Granger Causality and Regime Inference in Bayesian Markov-Switching VARs," Department of Economics - Working Papers Series 1191, The University of Melbourne.
  • Handle: RePEc:mlb:wpaper:1191
    as

    Download full text from publisher

    File URL: http://fbe.unimelb.edu.au/__data/assets/pdf_file/0008/1427453/1191Wozniak.pdf
    Download Restriction: no

    References listed on IDEAS

    as
    1. Marta Bańbura, 2008. "Large Bayesian VARs," 2008 Meeting Papers 334, Society for Economic Dynamics.
    2. Halbert White & Xun Lu, 2010. "Granger Causality and Dynamic Structural Systems," Journal of Financial Econometrics, Society for Financial Econometrics, vol. 8(2), pages 193-243, spring.
    3. Dufour, Jean-Marie & Pelletier, Denis & Renault, Eric, 2006. "Short run and long run causality in time series: inference," Journal of Econometrics, Elsevier, vol. 132(2), pages 337-362, June.
    4. Boudjellaba, Hafida & Dufour, Jean-Marie & Roy, Roch, 1994. "Simplified conditions for noncausality between vectors in multivariate ARMA models," Journal of Econometrics, Elsevier, vol. 63(1), pages 271-287, July.
    5. Thomas Doan & Robert B. Litterman & Christopher A. Sims, 1983. "Forecasting and Conditional Projection Using Realistic Prior Distributions," NBER Working Papers 1202, National Bureau of Economic Research, Inc.
    6. Sims, Christopher A. & Waggoner, Daniel F. & Zha, Tao, 2008. "Methods for inference in large multiple-equation Markov-switching models," Journal of Econometrics, Elsevier, vol. 146(2), pages 255-274, October.
    7. Christiano, Lawrence J. & Ljungqvist, Lars, 1988. "Money does Granger-cause output in the bivariate money-output relation," Journal of Monetary Economics, Elsevier, vol. 22(2), pages 217-235, September.
    8. Koop, Gary & Korobilis, Dimitris, 2010. "Bayesian Multivariate Time Series Methods for Empirical Macroeconomics," Foundations and Trends(R) in Econometrics, now publishers, vol. 3(4), pages 267-358, July.
    9. Jeantheau, Thierry, 1998. "Strong Consistency Of Estimators For Multivariate Arch Models," Econometric Theory, Cambridge University Press, vol. 14(01), pages 70-86, February.
    10. Dimitris K. Christopoulos & Miguel A. León-Ledesma, 2008. "Testing for Granger (non-)causality in a time-varying coefficient VAR model," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 27(4), pages 293-303.
    11. John Geweke, 1999. "Using simulation methods for bayesian econometric models: inference, development,and communication," Econometric Reviews, Taylor & Francis Journals, vol. 18(1), pages 1-73.
    12. Ni, Shawn & Sun, Dongchu, 2003. "Noninformative priors and frequentist risks of bayesian estimators of vector-autoregressive models," Journal of Econometrics, Elsevier, vol. 115(1), pages 159-197, July.
    13. Morten O. Ravn & Zacharias Psaradakis & Martin Sola, 2005. "Markov switching causality and the money-output relationship," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 20(5), pages 665-683.
    14. Anna Pajor, 2011. "A Bayesian Analysis of Exogeneity in Models with Latent Variables," Central European Journal of Economic Modelling and Econometrics, CEJEME, vol. 3(2), pages 49-73, June.
    15. James Tobin, 1970. "Rejoinder," The Quarterly Journal of Economics, Oxford University Press, vol. 84(2), pages 328-329.
    16. Matthieu Droumaguet & Tomasz Wozniak, 2012. "Bayesian Testing of Granger Causality in Markov-Switching VARs," Economics Working Papers ECO2012/06, European University Institute.
    17. 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.
    18. Hamilton, James D, 1989. "A New Approach to the Economic Analysis of Nonstationary Time Series and the Business Cycle," Econometrica, Econometric Society, vol. 57(2), pages 357-384, March.
    19. Chib S. & Jeliazkov I., 2001. "Marginal Likelihood From the Metropolis-Hastings Output," Journal of the American Statistical Association, American Statistical Association, vol. 96, pages 270-281, March.
    20. Marta Banbura & Domenico Giannone & Lucrezia Reichlin, 2010. "Large Bayesian vector auto regressions," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 25(1), pages 71-92.
    21. Mosconi, Rocco & Seri, Raffaello, 2006. "Non-causality in bivariate binary time series," Journal of Econometrics, Elsevier, vol. 132(2), pages 379-407, June.
    22. Kim, Chang-Jin, 1994. "Dynamic linear models with Markov-switching," Journal of Econometrics, Elsevier, vol. 60(1-2), pages 1-22.
    23. Chang-Jin Kim & Charles R. Nelson, 1999. "Has The U.S. Economy Become More Stable? A Bayesian Approach Based On A Markov-Switching Model Of The Business Cycle," The Review of Economics and Statistics, MIT Press, vol. 81(4), pages 608-616, November.
    24. James Tobin, 1970. "Money and Income: Post Hoc Ergo Propter Hoc?," The Quarterly Journal of Economics, Oxford University Press, vol. 84(2), pages 301-317.
    25. Granger, C W J, 1969. "Investigating Causal Relations by Econometric Models and Cross-Spectral Methods," Econometrica, Econometric Society, vol. 37(3), pages 424-438, July.
    26. Sims, Christopher A, 1972. "Money, Income, and Causality," American Economic Review, American Economic Association, vol. 62(4), pages 540-552, September.
    27. Jean-Marie Dufour & David Tessier, 2006. "Short-Run and Long-Run Causality between Monetary Policy Variables and Stock Prices," Staff Working Papers 06-39, Bank of Canada.
    28. Lutkepohl, Helmut & Burda, Maike M., 1997. "Modified Wald tests under nonregular conditions," Journal of Econometrics, Elsevier, vol. 78(2), pages 315-332, June.
    Full references (including those not matched with items on IDEAS)

    More about this item

    Keywords

    Technical Efficiency; Penalised Splines; Gibbs Sampling;

    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
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:mlb:wpaper:1191. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Dandapani Lokanathan). General contact details of provider: http://edirc.repec.org/data/demelau.html .

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.