Abstract
We propose a novel chronology of global business cycles based on industrial production data for a sample of 85 countries at a monthly frequency from 1980 until 2012 and the Bry and Boschan (1971) algorithm. We assess the methodology with statistical tools of signal detection theory and against existing chronologies of country-specific turning points. Finally, we conclude by introducing and evaluating a logit model of the probability of a global downturn occurring up to 12 months ahead. This model uses the macro and financial indicators tracked by the Database of Global Economic Indicators (DGEI) of the Federal Reserve Bank of Dallas (see Grossman et al., 2014) to offer advanced warning of upcoming turning points of the global cycle.
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