Using the Dynamic Bi-Factor Model with Markov Switching to Predict the Cyclical Turns in the Large European Economies
The appropriately selected leading indicators can substantially improve the forecasting of the peaks and troughs of the business cycle. Using the novel methodology of the dynamic bi-factor model with Markov switching and the data for the three largest European economies (France, Germany, and UK) we construct a composite leading indicator (CLI) and a composite coincident indicator (CCI) as well as corresponding recession probabilities. We estimate also a rival model of the Markov-switching VAR in order to see, which of the two models brings better outcomes. The recession data derived from these models are compared to three reference chronologies: those of OECD and ECRI (growth cycles) and those obtained with quarterly Bry-Boschan procedure (classical cycles). Dynamic bi-factor model and MSVAR appear to predict the cyclical turning points equally well without systematic superiority of one model over another.
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