IDEAS home Printed from https://ideas.repec.org/p/ecb/ecbwps/20192310.html
   My bibliography  Save this paper

Detecting turning points in global economic activity

Author

Listed:
  • Baumann, Ursel
  • Gómez-Salvador, Ramón
  • Seitz, Franz

Abstract

We present non-linear models to capture the turning points in global economic activity as well as in advanced and emerging economies from 1980 to 2017. We first estimate Markov Switching models within a univariate framework. These models support the relevance of three business cycle regimes (recessions, low growth and high growth) for economic activity at the global level and in advanced and emerging economies. In a second part, we find that the regimes of the Markov Switching models can be well explained with activity, survey and commodity price variables within a discrete choice framework, specifically multinomial logit models, therefore reinforcing the economic interpretation of the regimes. JEL Classification: C34, C35, E32

Suggested Citation

  • Baumann, Ursel & Gómez-Salvador, Ramón & Seitz, Franz, 2019. "Detecting turning points in global economic activity," Working Paper Series 2310, European Central Bank.
  • Handle: RePEc:ecb:ecbwps:20192310
    Note: 345263
    as

    Download full text from publisher

    File URL: https://www.ecb.europa.eu//pub/pdf/scpwps/ecb.wp2310~b27180482a.en.pdf
    Download Restriction: no

    References listed on IDEAS

    as
    1. Fornari, Fabio & Lemke, Wolfgang, 2010. "Predicting recession probabilities with financial variables over multiple horizons," Working Paper Series 1255, European Central Bank.
    2. Falk Bräuning & Victoria Ivashina, 2017. "U. S. monetary policy and emerging market credit cycles," Working Papers 17-9, Federal Reserve Bank of Boston, revised 29 Aug 2017.
    3. Klaus Abberger & Wolfgang Nierhaus, 2010. "Markov-Switching and the Ifo Business Climate: the Ifo Business Cycle Traffic Lights," OECD Journal: Journal of Business Cycle Measurement and Analysis, OECD Publishing, Centre for International Research on Economic Tendency Surveys, vol. 2010(2), pages 1-13.
    4. Christiansen, Charlotte & Eriksen, Jonas Nygaard & Møller, Stig Vinther, 2014. "Forecasting US recessions: The role of sentiment," Journal of Banking & Finance, Elsevier, vol. 49(C), pages 459-468.
    5. Golinelli, Roberto & Parigi, Giuseppe, 2014. "Tracking world trade and GDP in real time," International Journal of Forecasting, Elsevier, vol. 30(4), pages 847-862.
    6. Harding, Don & Pagan, Adrian, 2002. "Dissecting the cycle: a methodological investigation," Journal of Monetary Economics, Elsevier, vol. 49(2), pages 365-381, March.
    7. Laurent Ferrara & Clément Marsilli, 2019. "Nowcasting global economic growth: A factor‐augmented mixed‐frequency approach," The World Economy, Wiley Blackwell, vol. 42(3), pages 846-875, March.
    8. Sebastian Fossati, 2015. "Forecasting US recessions with macro factors," Applied Economics, Taylor & Francis Journals, vol. 47(53), pages 5726-5738, November.
    9. Camacho, Maximo & Martinez-Martin, Jaime, 2015. "Monitoring the world business cycle," Economic Modelling, Elsevier, vol. 51(C), pages 617-625.
    10. Guérin, Pierre & Leiva-Leon, Danilo, 2017. "Model averaging in Markov-switching models: Predicting national recessions with regional data," Economics Letters, Elsevier, vol. 157(C), pages 45-49.
    11. Billio, Monica & Casarin, Roberto & Ravazzolo, Francesco & van Dijk, Herman K., 2012. "Combination schemes for turning point predictions," The Quarterly Review of Economics and Finance, Elsevier, vol. 52(4), pages 402-412.
    12. Anaya, Pablo & Hachula, Michael & Offermanns, Christian J., 2017. "Spillovers of U.S. unconventional monetary policy to emerging markets: The role of capital flows," Journal of International Money and Finance, Elsevier, vol. 73(PB), pages 275-295.
    13. Ivo Krznar, 2011. "Identifying Recession and Expansion Periods in Croatia," Working Papers 29, The Croatian National Bank, Croatia.
    14. Harding, Don, 2008. "Detecting and forecasting business cycle turning points," MPRA Paper 33583, University Library of Munich, Germany.
    15. Jens Boysen-Hogrefe, 2012. "A note on predicting recessions in the euro area using real M1," Economics Bulletin, AccessEcon, vol. 32(2), pages 1291-1301.
    16. Gerhard Bry & Charlotte Boschan, 1971. "Programmed Selection of Cyclical Turning Points," NBER Chapters, in: Cyclical Analysis of Time Series: Selected Procedures and Computer Programs, pages 7-63, National Bureau of Economic Research, Inc.
    17. Klaus Abberger & Wolfgang Nierhaus, 2010. "Markov-Switching and the Ifo Business Climate: The Ifo Business Cycle Traffic Lights," CESifo Working Paper Series 2936, CESifo Group Munich.
    18. Chauvet, Marcelle & Potter, Simon, 2010. "Business cycle monitoring with structural changes," International Journal of Forecasting, Elsevier, vol. 26(4), pages 777-793, October.
    Full references (including those not matched with items on IDEAS)

    More about this item

    Keywords

    global GDP; Markov switching; multinomial logit; turning points;

    JEL classification:

    • C34 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Truncated and Censored Models; Switching Regression Models
    • C35 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions
    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:ecb:ecbwps:20192310. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Official Publications). General contact details of provider: http://edirc.repec.org/data/emieude.html .

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.