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Detecting turning points in global economic activity

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  • Baumann, Ursel
  • Gomez-Salvador, Ramon
  • 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 & Gomez-Salvador, Ramon & Seitz, Franz, 2019. "Detecting turning points in global economic activity," Working Paper Series 2310, European Central Bank.
  • Handle: RePEc:ecb:ecbwps:20192310
    Note: 345263
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    References listed on IDEAS

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    More about this item

    Keywords

    global GDP; Markov switching; multinomial logit; turning points;
    All these keywords.

    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

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