This paper introduces a new empirical strategy for the characterization of business cycles. It combines non-parametric decoding methods that classify a series into expansions and recessions but does not require specification of the underlying stochastic process generating the data. It then uses network analysis to combine the signals obtained from different economic indicators to generate a unique chronology. These methods generate a record of peak and trough dates comparable, and in one sense superior, to the NBER’s own chronology. The methods are then applied to 22 OECD countries to obtain a global business cycle chronology.