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An Algorithm for Generalized Impulse-Response Functions in Markov-Switching Structural VAR

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  • Frédéric Karamé

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

Abstract

We transpose the Generalized Impulse-Response Function (GIRF) developed by Koop et al. (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.

Suggested Citation

  • Frédéric Karamé, 2012. "An Algorithm for Generalized Impulse-Response Functions in Markov-Switching Structural VAR," Documents de recherche 12-04, Centre d'Études des Politiques Économiques (EPEE), Université d'Evry Val d'Essonne.
  • Handle: RePEc:eve:wpaper:12-04
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    References listed on IDEAS

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    1. Potter, Simon M., 2000. "Nonlinear impulse response functions," Journal of Economic Dynamics and Control, Elsevier, vol. 24(10), pages 1425-1446, September.
    2. Steven J. Davis & R. Jason Faberman & John Haltiwanger, 2006. "The Flow Approach to Labor Markets: New Data Sources and Micro-Macro Links," Journal of Economic Perspectives, American Economic Association, pages 3-26.
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    5. 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.
    6. Beaudry, Paul & Koop, Gary, 1993. "Do recessions permanently change output?," Journal of Monetary Economics, Elsevier, pages 149-163.
    7. Ehrmann, Michael & Ellison, Martin & Valla, Natacha, 2003. "Regime-dependent impulse response functions in a Markov-switching vector autoregression model," Economics Letters, Elsevier, pages 295-299.
    8. 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.
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    11. Sensier, Marianne & Osborn, Denise R & Ocal, Nadir, 2002. " Asymmetric Interest Rate Effects for the UK Real Economy," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 64(4), pages 315-339, September.
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    13. 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, pages 110-137.
    14. Steven J. Davis & R. Jason Faberman & John Haltiwanger, 2006. "The Flow Approach to Labor Markets: New Data Sources and Micro-Macro Links," Journal of Economic Perspectives, American Economic Association, pages 3-26.
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    Cited by:

    1. 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.
    2. Karamé, Frédéric, 2015. "Asymmetries and Markov-switching structural VAR," Journal of Economic Dynamics and Control, Elsevier, vol. 53(C), pages 85-102.

    More about this item

    Keywords

    structural VAR; Markov-switching regime; generalized impulse-response function;

    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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