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Regime-Switching Cointegration

Author

Listed:
  • Markus Jochmann

    (Newcastle University, UK; The Rimini Centre for Economic Analysis (RCEA), Italy)

  • Gary Koop

    (University of Strathclyde, UK; The Rimini Centre for Economic Analysis (RCEA), Italy)

Abstract

We develop methods for Bayesian inference in vector error correction models which are subject to a variety of switches in regime (e.g. Markov switches in regime or structural breaks). An important aspect of our approach is that we allow both the cointegrating vectors and the number of cointegrating relationships to change when the regime changes. We show how Bayesian model averaging r model selection methods can be used to deal with the high-dimensional model space that results. Our methods are used in an empirical study of the Fisher effect.

Suggested Citation

  • Markus Jochmann & Gary Koop, 2011. "Regime-Switching Cointegration," Working Paper series 40_11, Rimini Centre for Economic Analysis.
  • Handle: RePEc:rim:rimwps:40_11
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    References listed on IDEAS

    as
    1. Gary Koop & Roberto Leon-Gonzalez & Rodney W. Strachan, 2008. "Bayesian Inference in the Time Varying Cointegration Model," Working Paper series 23_08, Rimini Centre for Economic Analysis.
    2. Markus Jochmann & Gary Koop & Roberto Leon‐Gonzalez & Rodney W. Strachan, 2013. "Stochastic search variable selection in vector error correction models with an application to a model of the UK macroeconomy," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 28(1), pages 62-81, January.
    3. Strachan, Rodney W, 2003. "Valid Bayesian Estimation of the Cointegrating Error Correction Model," Journal of Business & Economic Statistics, American Statistical Association, vol. 21(1), pages 185-195, January.
    4. Gary Koop & Simon M. Potter & Rodney W. Strachan, 2008. "Re-Examining the Consumption-Wealth Relationship: The Role of Model Uncertainty," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 40(2-3), pages 341-367, March.
    5. Jochmann Markus & Koop Gary, 2015. "Regime-switching cointegration," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 19(1), pages 35-48, February.
    6. Paap, Richard & van Dijk, Herman K, 2003. "Bayes Estimates of Markov Trends in Possibly Cointegrated Series: An Application to U.S. Consumption and Income," Journal of Business & Economic Statistics, American Statistical Association, vol. 21(4), pages 547-563, October.
    7. Beyer, Andreas & Dewald, William G. & Haug, Alfred A., 2009. "Structural breaks, cointegration and the Fisher effect," Working Paper Series 1013, European Central Bank.
    8. Strachan, Rodney W. & Inder, Brett, 2004. "Bayesian analysis of the error correction model," Journal of Econometrics, Elsevier, vol. 123(2), pages 307-325, December.
    9. Gael M. Martin, 2000. "US deficit sustainability: a new approach based on multiple endogenous breaks," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 15(1), pages 83-105.
    10. Ang, Andrew & Bekaert, Geert, 2002. "Regime Switches in Interest Rates," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(2), pages 163-182, April.
    11. Sugita, Katsuhiro, 2006. "Bayesian Analysis of Dynamic Multivariate Models with Multiple Structural Breaks," Discussion Papers 2006-14, Graduate School of Economics, Hitotsubashi University.
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    20. Stock, James H & Watson, Mark W, 1996. "Evidence on Structural Instability in Macroeconomic Time Series Relations," Journal of Business & Economic Statistics, American Statistical Association, vol. 14(1), pages 11-30, January.
    21. Geweke, John, 1996. "Bayesian reduced rank regression in econometrics," Journal of Econometrics, Elsevier, vol. 75(1), pages 121-146, November.
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    23. Chib, Siddhartha, 1998. "Estimation and comparison of multiple change-point models," Journal of Econometrics, Elsevier, vol. 86(2), pages 221-241, June.
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    Citations

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    Cited by:

    1. Inoue,Tomoo & Kaya,Demet & Ohshige,Hitoshi, 2015. "The impact of China?s slowdown on the Asia Pacific region : an application of the GVAR model," Policy Research Working Paper Series 7442, The World Bank.
    2. Christina Christou & Rangan Gupta & Wendy Nyakabawo & Mark E. Wohar, 2017. "Do House Prices Hedge Inflation in the US? A Quantile Cointegration Approach," Working Papers 201707, University of Pretoria, Department of Economics.
    3. Maheu, John M & Song, Yong, 2017. "An Efficient Bayesian Approach to Multiple Structural Change in Multivariate Time Series," MPRA Paper 79211, University Library of Munich, Germany.
    4. Jochmann Markus & Koop Gary, 2015. "Regime-switching cointegration," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 19(1), pages 35-48, February.
    5. Joscha Beckmann & Robert Czudaj, 2017. "Effective Exchange Rates, Current Accounts and Global Imbalances," Review of International Economics, Wiley Blackwell, vol. 25(3), pages 500-533, August.
    6. repec:eee:intfor:v:33:y:2017:i:4:p:1025-1043 is not listed on IDEAS
    7. Dark, Jonathan, 2015. "Futures hedging with Markov switching vector error correction FIEGARCH and FIAPARCH," Journal of Banking & Finance, Elsevier, vol. 61(S2), pages 269-285.
    8. Chew Lian Chua & Sarantis Tsiaplias, 2014. "A Bayesian Approach to Modelling Bivariate Time-Varying Cointegration and Cointegrating Rank," Melbourne Institute Working Paper Series wp2014n27, Melbourne Institute of Applied Economic and Social Research, The University of Melbourne.

    More about this item

    Keywords

    Bayesian; Markov switching; structural breaks; cointegration; model averaging;

    JEL classification:

    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: 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
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection

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