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Multivariate contemporaneous threshold autoregressive models

Author

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  • Michael J. Dueker
  • Zacharias Psaradakis
  • Martin Sola
  • Fabio Spagnolo

Abstract

In this paper we propose a contemporaneous threshold multivariate smooth transition autoregressive (C-MSTAR) model in which the regime weights depend on the ex ante probabilities that latent regime-specific variables exceed certain threshold values. The model is a multivariate generalization of the contemporaneous threshold autoregressive model introduced by Dueker et al. (2007). A key feature of the model is that the transition function depends on all the parameters of the model as well as on the data. The stability and distributional properties of the proposed model are investigated. The C-MSTAR model is also used to examine the relationship between US stock prices and interest rates.

Suggested Citation

  • Michael J. Dueker & Zacharias Psaradakis & Martin Sola & Fabio Spagnolo, 2007. "Multivariate contemporaneous threshold autoregressive models," Working Papers 2007-019, Federal Reserve Bank of St. Louis.
  • Handle: RePEc:fip:fedlwp:2007-019
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    References listed on IDEAS

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    1. Dueker, Michael J. & Sola, Martin & Spagnolo, Fabio, 2007. "Contemporaneous threshold autoregressive models: Estimation, testing and forecasting," Journal of Econometrics, Elsevier, vol. 141(2), pages 517-547, December.
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    3. De Gooijer, Jan G. & Vidiella-i-Anguera, Antoni, 2004. "Forecasting threshold cointegrated systems," International Journal of Forecasting, Elsevier, vol. 20(2), pages 237-253.
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    7. Eklund, Bruno, 2003. "A nonlinear alternative to the unit root hypothesis," SSE/EFI Working Paper Series in Economics and Finance 547, Stockholm School of Economics.
    8. 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.
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    10. Frédérique Bec & Anders Rahbek & Neil Shephard, 2008. "The ACR Model: A Multivariate Dynamic Mixture Autoregression," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 70(5), pages 583-618, October.
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    13. Zacharias Psaradakis & Martin Sola & Fabio Spagnolo & Nicola Spagnolo, 2009. "Selecting nonlinear time series models using information criteria," Journal of Time Series Analysis, Wiley Blackwell, vol. 30(4), pages 369-394, July.
    14. Diks, Cees & Panchenko, Valentyn, 2006. "A new statistic and practical guidelines for nonparametric Granger causality testing," Journal of Economic Dynamics and Control, Elsevier, vol. 30(9-10), pages 1647-1669.
    15. Ben S. Bernanke & Mark Gertler, 1999. "Monetary policy and asset price volatility," Proceedings - Economic Policy Symposium - Jackson Hole, Federal Reserve Bank of Kansas City, pages 77-128.
    16. Zacharias Psaradakis & Nicola Spagnolo, 2006. "Joint Determination of the State Dimension and Autoregressive Order for Models with Markov Regime Switching," Journal of Time Series Analysis, Wiley Blackwell, vol. 27(5), pages 753-766, September.
    17. Kapetanios, G., 1999. "Model Selection in Threshold Models," Cambridge Working Papers in Economics 9906, Faculty of Economics, University of Cambridge.
    18. Sola, Martin & Driffill, John, 1994. "Testing the term structure of interest rates using a stationary vector autoregression with regime switching," Journal of Economic Dynamics and Control, Elsevier, vol. 18(3-4), pages 601-628.
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    Citations

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    Cited by:

    1. Jan Pablo Burgard & Matthias Neuenkirch & Matthias Nöckel, 2016. "State-Dependent Transmission of Monetary Policy in the Euro Area," Research Papers in Economics 2016-15, University of Trier, Department of Economics.
    2. repec:bla:intfin:v:20:y:2017:i:1:p:64-91 is not listed on IDEAS
    3. Paulo Rodrigues & Nazarii Salish, 2015. "Modeling and forecasting interval time series with threshold models," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 9(1), pages 41-57, March.
    4. Leena Kalliovirta & Mika Meitz & Pentti Saikkonen, 2015. "A Gaussian Mixture Autoregressive Model for Univariate Time Series," Journal of Time Series Analysis, Wiley Blackwell, vol. 36(2), pages 247-266, March.
    5. Ching-Wai (Jeremy) Chiu & Haroon Mumtaz & Gabor Pinter, 2016. "Bayesian Vector Autoregressions with Non-Gaussian Shocks," CReMFi Discussion Papers 5, CReMFi, School of Economics and Finance, QMUL.
    6. Demian Pouzo & Zacharias Psaradakis & Martin Sola, 2016. "Maximum Likelihood Estimation in Possibly Misspecified Dynamic Models with Time-Inhomogeneous Markov Regimes," Papers 1612.04932, arXiv.org, revised May 2018.
    7. Dueker Michael J. & Psaradakis Zacharias & Sola Martin & Spagnolo Fabio, 2011. "Contemporaneous-Threshold Smooth Transition GARCH Models," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 15(2), pages 1-25, March.
    8. Zacharias Psaradakis & Martin Sola & Fabio Spagnolo & Nicola Spagnolo, 2009. "Selecting nonlinear time series models using information criteria," Journal of Time Series Analysis, Wiley Blackwell, vol. 30(4), pages 369-394, July.
    9. Kalliovirta, Leena & Meitz, Mika & Saikkonen, Pentti, 2016. "Gaussian mixture vector autoregression," Journal of Econometrics, Elsevier, vol. 192(2), pages 485-498.

    More about this item

    Keywords

    Time-series analysis ; Capital assets pricing model;

    JEL classification:

    • 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
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates

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