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Impulse-Response Functions in Markov-Switching Structural Vector AutoRegressions: a Step Further

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  • Frédéric Karamé

    (EPEE, Université d’Evry Val d’Essonne, Centre d’Etudes de l’Emploi TEPP (FR n°3126, CNRS))

Abstract

Ehrmann et al. (2003) proposed an IRF in the frame of Markov- Switching structurally VARs. Their IRF provides insights on the dynamics within the regime in which the shock occurs. We propose an IRF that captures the global response of the system and illustrate its use with examples.

Suggested Citation

  • Frédéric Karamé, 2010. "Impulse-Response Functions in Markov-Switching Structural Vector AutoRegressions: a Step Further," Documents de recherche 10-03, Centre d'Études des Politiques Économiques (EPEE), Université d'Evry Val d'Essonne.
    • Handle: RePEc:eve:wpaper:10-03
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    References listed on IDEAS

    as
    1. Ehrmann, Michael & Ellison, Martin & Valla, Natacha, 2003. "Regime-dependent impulse response functions in a Markov-switching vector autoregression model," Economics Letters, Elsevier, vol. 78(3), pages 295-299, March.
    2. 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.
    3. Hall, Stephen G & Psaradakis, Zacharias & Sola, Martin, 1999. "Detecting Periodically Collapsing Bubbles: A Markov-Switching Unit Root Test," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 14(2), pages 143-154, March-Apr.
    4. Weise, Charles L, 1999. "The Asymmetric Effects of Monetary Policy: A Nonlinear Vector Autoregression Approach," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 31(1), pages 85-108, February.
    5. 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.
    6. 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.
    7. Koop, Gary & Pesaran, M. Hashem & Potter, Simon M., 1996. "Impulse response analysis in nonlinear multivariate models," Journal of Econometrics, Elsevier, vol. 74(1), pages 119-147, September.
    Full references (including those not matched with items on IDEAS)

    Citations

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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. Maximo Camacho & Gabriel Perez-Quiros, 2014. "Commodity Prices and the Business Cycle in Latin America: Living and Dying by Commodities?," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 50(2), pages 110-137, March.
    3. Cavicchioli, Maddalena, 2023. "Impulse response function analysis for Markov switching var models," Economics Letters, Elsevier, vol. 232(C).
    4. Karamé, F., 2012. "An algorithm for generalized impulse-response functions in Markov-switching structural VAR," Economics Letters, Elsevier, vol. 117(1), pages 230-234.
    5. Kole, Erik & van Dijk, Dick, 2023. "Moments, shocks and spillovers in Markov-switching VAR models," Journal of Econometrics, Elsevier, vol. 236(2).
    6. Karamé, Frédéric, 2015. "Asymmetries and Markov-switching structural VAR," Journal of Economic Dynamics and Control, Elsevier, vol. 53(C), pages 85-102.
    7. Hamilton, J.D., 2016. "Macroeconomic Regimes and Regime Shifts," Handbook of Macroeconomics, in: J. B. Taylor & Harald Uhlig (ed.), Handbook of Macroeconomics, edition 1, volume 2, chapter 0, pages 163-201, Elsevier.

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    More about this item

    Keywords

    Structural VAR; Markov-Switching model; impulse response function; state asymmetry; regime-dependent IRF;
    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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