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Decision Maps for Bivariate Time Series with Potential Thrshold Cointegration


  • Kunst, Robert M.

    (University of Vienna and Department of Economics, Institute for Advanced Studies, Vienna)


Bivariate time series data often show strong relationships between the two components, while both individual variables can be approximated by random walks in the short run andare obviously bounded in the long run. Three model classes are considered for a time-series model selection problem: stable vector autoregressions, cointegrated models, and globally stable threshold models. It is demonstrated how simulated decision maps help in classifying observed time series. The maps process the joint evidence of two test statistics: a canonical root and an LR--type specification statistic for threshold effects.

Suggested Citation

  • Kunst, Robert M., 2002. "Decision Maps for Bivariate Time Series with Potential Thrshold Cointegration," Economics Series 121, Institute for Advanced Studies.
  • Handle: RePEc:ihs:ihsesp:121

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    References listed on IDEAS

    1. Balke, Nathan S & Fomby, Thomas B, 1997. "Threshold Cointegration," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 38(3), pages 627-645, August.
    2. Hansen, Bruce E. & Seo, Byeongseon, 2002. "Testing for two-regime threshold cointegration in vector error-correction models," Journal of Econometrics, Elsevier, vol. 110(2), pages 293-318, October.
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    4. Jumah, Adusei & Kunst, Robert M., 2002. "On Mean Reversion in Real Interest Rates: An Application of Threshold Cointegtation," Economics Series 109, Institute for Advanced Studies.
    5. Berger, James O. & Yang, Ruo-Yong, 1994. "Noninformative Priors and Bayesian Testing for the AR(1) Model," Econometric Theory, Cambridge University Press, vol. 10(3-4), pages 461-482, August.
    6. Johansen, Soren, 1995. "Likelihood-Based Inference in Cointegrated Vector Autoregressive Models," OUP Catalogue, Oxford University Press, number 9780198774501, June.
    7. Bauwens, Luc & Lubrano, Michel & Richard, Jean-Francois, 2000. "Bayesian Inference in Dynamic Econometric Models," OUP Catalogue, Oxford University Press, number 9780198773139, June.
    8. Hall, Anthony D & Anderson, Heather M & Granger, Clive W J, 1992. "A Cointegration Analysis of Treasury Bill Yields," The Review of Economics and Statistics, MIT Press, vol. 74(1), pages 116-126, February.
    9. Engle, Robert & Granger, Clive, 2015. "Co-integration and error correction: Representation, estimation, and testing," Applied Econometrics, Publishing House "SINERGIA PRESS", vol. 39(3), pages 106-135.
    10. Lo, Ming Chien & Zivot, Eric, 2001. "Threshold Cointegration And Nonlinear Adjustment To The Law Of One Price," Macroeconomic Dynamics, Cambridge University Press, vol. 5(04), pages 533-576, September.
    11. Campbell, John Y & Shiller, Robert J, 1987. "Cointegration and Tests of Present Value Models," Journal of Political Economy, University of Chicago Press, vol. 95(5), pages 1062-1088, October.
    12. Kunst, Robert M., 2002. "Testing for Stationarity in a Cointegrated System," Economics Series 117, Institute for Advanced Studies.
    13. Enders, Walter & Granger, Clive W J, 1998. "Unit-Root Tests and Asymmetric Adjustment with an Example Using the Term Structure of Interest Rates," Journal of Business & Economic Statistics, American Statistical Association, vol. 16(3), pages 304-311, July.
    14. Johansen, Soren, 1988. "Statistical analysis of cointegration vectors," Journal of Economic Dynamics and Control, Elsevier, vol. 12(2-3), pages 231-254.
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    Cited by:

    1. Kunst, Robert M., 2005. "Approaches for the Joint Evaluation of Hypothesis Tests: Classical Testing, Bayes Testing, and Joint Confirmation," Economics Series 177, Institute for Advanced Studies.
    2. Mendonca, Gui Pedro, 2008. "Structural Breaks, Regime Change and Asymmetric Adjustment: A Short and Long Run Global Approach to the Output/Unemployment Dynamics," MPRA Paper 14648, University Library of Munich, Germany.

    More about this item


    Model selection; Bayes testing; Nonlinear time series models;

    JEL classification:

    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: 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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