In this paper, we propose a method for jointly estimating indexes of economic and financial conditions by exploiting the intertemporal link between their cyclical behavior. This method combines a dynamic factor model for the joint modeling of economic and financial variables with mixed frequencies together with a tailored Markov regime switching specification for capturing their cyclical behavior. It allows for imperfect synchronization between the cycles in economic and financial conditions/factors by explicitly estimating the phase shifts between their cyclical regimes. We examine the efficacy of the model for predicting cyclical activity in a key emerging economy, namely, Turkey, by making use of a mixed frequency ragged-edge data set. A comparison of our framework with more conventional cases imposing common cyclical dynamics as well as independent cyclical dynamics for the economic and financial indicators reveals that the proposed specification provides precise estimates of indexes of economic and financial activity together with accurate and timely recession probabilities. Recession probabilities estimated using the available data in the first week of November 2018 indicate that Turkey entered a recession that is still ongoing starting from August 2018. We further conduct a recursive real-time exercise of nowcasting and forecasting business cycle turning points. The results show evidence for the superior predictive power of our specification by signaling oncoming recessions (expansions) as early as 3.6 (3.3) months ahead of the actual realization.
Financial conditions index Coincident economic index Dynamic factor model Markov switching Imperfect synchronization Bayesian inference