Score contribution per author:
α: calibrated so average coauthorship-adjusted count equals average raw count
In this paper, we propose a method for real‐time prediction of recessions using large sets of economic and financial variables with mixed frequencies. This method combines a dynamic factor model for the extraction of economic and financial conditions together with a tailored Markov regime switching specification for capturing their cyclical behaviour. Unlike conventional methods that estimate a single common cycle governing economic and financial conditions or extract economic and financial cycles in isolation of each other, the model allows for a common cycle which is reflected with potential phase shifts in the financial conditions estimated alongside with other parameters. This, in turn, provides timely recession predictions by enabling efficient modelling of the financial cycle systematically leading the business cycle. We examine the performance of the model using a mixed frequency ragged‐edge data set for Turkey in real time. The results show evidence for the superior predictive power of our specification by signalling oncoming recessions (expansions) as early as 3.6 (3.0) months ahead of the actual realization.