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Which Global Cycle? A Stochastic Factor Selection Approach for Global Macro-Financial Cycles

Author

Listed:
  • Berger Tino

    (9375 University of Göttingen , Platz der Göttinger Sieben 3, 37073 Göttingen, Germany)

  • Hienzsch Sebastian

    (9375 University of Göttingen , Platz der Göttinger Sieben 3, 37073 Göttingen, Germany)

Abstract

Instead of assuming a certain factor structure, we statistically test for the factor structure driving common global dynamics in macroeconomic and financial data by employing a stochastic factor selection approach. Using a sample of 16 developed countries from 1996Q1 to 2019Q4, we present strong empirical evidence of a global macro-financial cycle and an independent global financial cycle. Moreover, the global macro-financial cycle we estimate is essentially the global business cycle identified in the literature. It captures the common global macroeconomic dynamics and drives a significant share of the comovement in the financial sector. The remaining commonality in financial variables is driven by separate global financial cycles: the global credit cycle and the global capital flow cycle.

Suggested Citation

  • Berger Tino & Hienzsch Sebastian, 2025. "Which Global Cycle? A Stochastic Factor Selection Approach for Global Macro-Financial Cycles," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 29(5), pages 541-559.
    • Handle: RePEc:bpj:sndecm:v:29:y:2025:i:5:p:541-559:n:1003
    DOI: 10.1515/snde-2023-0093
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    Keywords

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    JEL classification:

    • E44 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Financial Markets and the Macroeconomy
    • F44 - International Economics - - Macroeconomic Aspects of International Trade and Finance - - - International Business Cycles
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
    • 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

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