Using the Dynamic Bi-Factor Model with Markov Switching to Predict the Cyclical Turns in the Large European Economies

Arbeitspapier

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 three largest European economies (France, Germany, and UK) we construct composite leading indicator (CLI) and 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 dates 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.

Object Details

• Language: Englisch

References and Relationships

• Bibliographic citation: Series: DIW Discussion Papers ; No. 554

Classification and Topics

• Classification: Wirtschaft ; Business Fluctuations; Cycles ; Econometric and Statistical Methods and Methodology: General
• Subject: Forecasting turning points ; composite coincident indicator ; composite leading indicator ; dynamic bi-factor model ; Markov switching

Contributors, Location and Time

• Event: Geistige Schöpfung
• (who): Kholodilin, Konstantin Arkadievich
• Event: Veröffentlichung
• (who): Deutsches Institut für Wirtschaftsforschung (DIW)
• (where): Berlin
• (when): 2006

Further information

• Handle: http://hdl.handle.net/10419/18447
• Last update: 20.09.2024, 8:25 AM CEST