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An algorithm for generalized impulse-response functions in Markov-switching structural VAR

Author

Listed:
  • F. Karamé

    (EPEE - Centre d'Etudes des Politiques Economiques - UEVE - Université d'Évry-Val-d'Essonne)

Abstract

We transpose the Generalized Impulse-Response Function (GIRF) developed by. Koop etal. (1996) to Markov-Switching structural VARs. As the algorithm displays an exponentially increasing complexity as regards the prediction horizon, we use the collapsing technique to easily obtain simulated trajectories (shocked or not), even for the most general representations. Our approach encompasses the existing IRFs proposed in the literature and is illustrated with an applied example on gross job flows. © 2012 Elsevier B.V.

Suggested Citation

  • F. Karamé, 2012. "An algorithm for generalized impulse-response functions in Markov-switching structural VAR," Post-Print hal-02877971, HAL.
    • Handle: RePEc:hal:journl:hal-02877971
    DOI: 10.1016/j.econlet.2012.04.089
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    1. Mike Artis & Hans-Martin Krolzig & Juan Toro, 2004. "The European business cycle," Oxford Economic Papers, Oxford University Press, vol. 56(1), pages 1-44, January.
    2. Karamé, F., 2010. "Impulse-response functions in Markov-switching structural vector autoregressions: A step further," Economics Letters, Elsevier, vol. 106(3), pages 162-165, March.
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    Cited by:

    1. Cavicchioli, Maddalena, 2024. "A matrix unified framework for deriving various impulse responses in Markov switching VAR: Evidence from oil and gas markets," The Journal of Economic Asymmetries, Elsevier, vol. 29(C).
    2. Huang, Shupei & An, Haizhong & Wen, Shaobo & An, Feng, 2017. "Revisiting driving factors of oil price shocks across time scales," Energy, Elsevier, vol. 139(C), pages 617-629.
    3. Markku Lanne & Henri Nyberg, 2016. "Generalized Forecast Error Variance Decomposition for Linear and Nonlinear Multivariate Models," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 78(4), pages 595-603, August.
    4. Cavicchioli, Maddalena, 2023. "Impulse response function analysis for Markov switching var models," Economics Letters, Elsevier, vol. 232(C).
    5. Markku Lanne & Henri Nyberg, 2015. "Nonlinear dynamic interrelationships between real activity and stock returns," CREATES Research Papers 2015-36, Department of Economics and Business Economics, Aarhus University.
    6. Kole, Erik & van Dijk, Dick, 2023. "Moments, shocks and spillovers in Markov-switching VAR models," Journal of Econometrics, Elsevier, vol. 236(2).
    7. Thomas St rdal Gundersen & Even Soltvedt Hvinden, 2021. "OPEC's crude game: Strategic Competition and Regime-switching in Global Oil Markets," Working Papers No 01/2021, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School.
    8. Karamé, Frédéric, 2015. "Asymmetries and Markov-switching structural VAR," Journal of Economic Dynamics and Control, Elsevier, vol. 53(C), pages 85-102.

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    More about this item

    Keywords

    Generalized impulse-response function; Markov-switching regime; Structural VAR;
    All these keywords.

    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
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods

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