Federal Reserve Bank of St. Louis
Business Cycles Across Space and Time
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 similarities in business cycle turning points. We find four groups, or “clusters”, of countries which experience idiosyncratic recessions relative to the global cycle. Additionally, we find the primary indicators of international recessions to be fluctuations in equity markets and geopolitical uncertainty. In out-of-sample forecasting exercises, we find that our model is an improvement over standard benchmark models for forecasting both aggregate output growth and country-level recessions.
Cite this item
Neville Francis & Michael T. Owyang & Daniel Soques, Business Cycles Across Space and Time, Federal Reserve Bank of St. Louis, Working Papers 2019-10, 22 Jan 2019.
- 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
Keywords: Markov-switching; time-varying transition probabilities; cluster analysis
This item with handle RePEc:fip:fedlwp:2019-010
is also listed on EconPapers
For corrections, contact Anna Oates ()