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Regime-switching global vector autoregressive models

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  • Gross, Marco
  • Binder, Michael

Abstract

The purpose of the paper is to develop a Regime-Switching Global Vector Autoregressive (RS-GVAR) model. The RS-GVAR model allows for recurring or non-recurring structural changes in all or a subset of countries. It can be used to generate regime-dependent impulse response functions which are conditional upon a regime-constellation across countries. Coupling the RS and the GVAR methodology improves out-of-sample forecast accuracy significantly in an application to real GDP, price inflation, and stock prices. JEL Classification: C32, E17, G20

Suggested Citation

  • Gross, Marco & Binder, Michael, 2013. "Regime-switching global vector autoregressive models," Working Paper Series 1569, European Central Bank.
    • Handle: RePEc:ecb:ecbwps:20131569
    Note: 3098116
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    File URL: https://www.ecb.europa.eu//pub/pdf/scpwps/ecbwp1569.pdf
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    Cited by:

    1. Kok, Christoffer & Gross, Marco & Żochowski, Dawid, 2016. "The impact of bank capital on economic activity - evidence from a mixed-cross-section GVAR model," Working Paper Series 1888, European Central Bank.
    2. Kaizoji, Taisei & Leiss, Matthias & Saichev, Alexander & Sornette, Didier, 2015. "Super-exponential endogenous bubbles in an equilibrium model of fundamentalist and chartist traders," Journal of Economic Behavior & Organization, Elsevier, vol. 112(C), pages 289-310.
    3. Alexander Chudik & M. Hashem Pesaran, 2016. "Theory And Practice Of Gvar Modelling," Journal of Economic Surveys, Wiley Blackwell, vol. 30(1), pages 165-197, February.
    4. Özcan Ceyhun Can & Uçak Harun, 2016. "Outbound Tourism Demand of Turkey: A Markov Switching Vector Autoregressive Approach," Czech Journal of Tourism, Sciendo, vol. 5(2), pages 59-72, December.
    5. Dovern, Jonas & Huber, Florian, 2015. "Global prediction of recessions," Economics Letters, Elsevier, vol. 133(C), pages 81-84.
    6. Chen, Pu & Semmler, Willi, 2018. "Financial stress, regime switching and spillover effects: Evidence from a multi-regime global VAR model," Journal of Economic Dynamics and Control, Elsevier, vol. 91(C), pages 318-348.
    7. Gross, Marco & Población García, Francisco Javier, 2016. "Assessing the efficacy of borrower-based macroprudential policy using an integrated micro-macro model for European households," Working Paper Series 1881, European Central Bank.
    8. Ernst, Ekkehard & Semmler, Willi & Haider, Alexander, 2017. "Debt-deflation, financial market stress and regime change – Evidence from Europe using MRVAR," Journal of Economic Dynamics and Control, Elsevier, vol. 81(C), pages 115-139.
    9. Olfa Manai Daboussi & Amira Majoul, 2014. "The transmission effects of the subprime crisis to emerging markets: A global VAR analysis," Asian Journal of Empirical Research, Asian Economic and Social Society, vol. 4(9), pages 427-438, September.
    10. Renaud St-Cyr, 2018. "Non-linéarité de la courbe de Phillips : un survol de la littérature," Staff Analytical Notes 2018-3, Bank of Canada.
    11. Peltonen, Tuomas A. & Gross, Marco & Behn, Markus, 2016. "Assessing the costs and benefits of capital-based macroprudential policy," Working Paper Series 1935, European Central Bank.
    12. Wei, Honghong & Lahiri, Radhika, 2019. "The impact of commodity price shocks in the presence of a trading relationship: A GVAR analysis of the NAFTA," Energy Economics, Elsevier, vol. 80(C), pages 553-569.
    13. Gross, Marco & Henry, Jerome & Semmler, Willi, 2018. "Destabilizing Effects Of Bank Overleveraging On Real Activity—An Analysis Based On A Threshold Mcs-Gvar," Macroeconomic Dynamics, Cambridge University Press, vol. 22(7), pages 1750-1768, October.
    14. Burhan Biçer & Almila Burgac Cil, 2023. "Symmetric and Asymmetric Dynamics of Output Gap and Inflation Relation for Turkish Economy," Prague Economic Papers, Prague University of Economics and Business, vol. 2023(5), pages 520-549.
    15. Gutierrez, Luciano & Piras, Francesco, 2014. "A global VAR model for the analysis of wheat export prices," 2014 International Congress, August 26-29, 2014, Ljubljana, Slovenia 182723, European Association of Agricultural Economists.
    16. Spezia, Luigi, 2020. "Bayesian variable selection in non-homogeneous hidden Markov models through an evolutionary Monte Carlo method," Computational Statistics & Data Analysis, Elsevier, vol. 143(C).
    17. Dovern, Jonas & van Roye, Björn, 2014. "International transmission and business-cycle effects of financial stress," Journal of Financial Stability, Elsevier, vol. 13(C), pages 1-17.
    18. Muhsin Kar & Tayfur Bayat & Selim Kayhan, 2016. "Impacts of Credit Default Swaps on Volatility of the Exchange Rate in Turkey: The Case of Euro," IJFS, MDPI, vol. 4(3), pages 1-18, July.
    19. Marco Gross & Willi Semmler, 2019. "Mind the Output Gap: The Disconnect of Growth and Inflation during Recessions and Convex Phillips Curves in the Euro Area," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 81(4), pages 817-848, August.
    20. José Da Fonseca & Peiming Wang, 2016. "A joint analysis of market indexes in credit default swap, volatility and stock markets," Applied Economics, Taylor & Francis Journals, vol. 48(19), pages 1767-1784, April.
    21. Gross, Marco, 2013. "Estimating GVAR weight matrices," Working Paper Series 1523, European Central Bank.

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    More about this item

    Keywords

    forecasting and simulation; Global macroeconometric modeling; nonlinear modeling; regime switching;
    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
    • E17 - Macroeconomics and Monetary Economics - - General Aggregative Models - - - Forecasting and Simulation: Models and Applications
    • G20 - Financial Economics - - Financial Institutions and Services - - - General

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