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Business Cycles across Space and Time

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  • NEVILLE FRANCIS
  • MICHAEL T. OWYANG
  • DANIEL SOQUES

Abstract

We study the comovement of international business cycles in a time‐series clustering model with regime switching. We extend the framework of Hamilton and Owyang (2012) to include time‐varying transition probabilities to determine what drives simultaneous business cycle turning points. We find four groups, or “clusters,” of countries that experience idiosyncratic recessions relative to the global cycle. In addition, we find the primary indicators of international recessions to be fluctuations in the term spread, equity markets, and geopolitical risk. In out‐of‐sample forecasting exercises, our model is an improvement over standard benchmark models for forecasting both aggregate output growth and country‐level recessions.

Suggested Citation

  • Neville Francis & Michael T. Owyang & Daniel Soques, 2022. "Business Cycles across Space and Time," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 54(4), pages 921-952, June.
  • Handle: RePEc:wly:jmoncb:v:54:y:2022:i:4:p:921-952
    DOI: 10.1111/jmcb.12860
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    Cited by:

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    2. Jochen Güntner & Johannes Henßler, 2021. "Ease on the Cannons, Tighten on the Trumpets: Geopolitical Risk and the Transmission of Monetary Policy Shocks," Economics working papers 2021-09, Department of Economics, Johannes Kepler University Linz, Austria.
    3. Dieppe, Alistair & Francis, Neville & Kindberg-Hanlon, Gene, 2021. "Technology and demand drivers of productivity dynamics in developed and emerging market economies," Working Paper Series 2533, European Central Bank.
    4. Coroneo, Laura & Jackson, Laura E. & Owyang, Michael T., 2020. "International Stock Comovements with Endogenous Clusters," Journal of Economic Dynamics and Control, Elsevier, vol. 116(C).
    5. Fiorillo, Paolo & Meles, Antonio & Pellegrino, Luigi Raffaele & Verdoliva, Vincenzo, 2024. "Geopolitical risk and stock price crash risk: The mitigating role of ESG performance," International Review of Financial Analysis, Elsevier, vol. 91(C).
    6. Jeffrey P. Cohen & Cletus C. Coughlin & Daniel Soques, 2019. "House Price Growth Interdependencies and Comovement," Working Papers 2019-028, Federal Reserve Bank of St. Louis, revised 11 Jan 2021.

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    More about this item

    JEL classification:

    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
    • 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
    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles
    • F44 - International Economics - - Macroeconomic Aspects of International Trade and Finance - - - International Business Cycles

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