Accelerating Peak Dating in a Dynamic Factor Markov-Switching Model

Arbeitspapier

The dynamic factor Markov-switching (DFMS) model introduced by Diebold and Rudebusch (1996) has proven to be a powerful framework to measure the business cycle. We extend the DFMS model by allowing for time-varying transition probabilities, with the aim of accelerating the real-time dating of turning points between expansion and recession regimes. Time-variation of the transition probabilities is brought about endogenously using the accelerated score-driven approach and exogenously using the term spread. In a real-time application using the four components of The Conference Board’s Coincident Economic Index for the period 1959-2020, we find that signaling power for recessions is significantly improved and are able to date the 2001 and 2008 recession peaks four and ten months before the NBER.

Object Details

• Language: Englisch

References and Relationships

• Bibliographic citation: Series: Tinbergen Institute Discussion Paper ; No. TI 2020-057/VI

Classification and Topics

• Classification: Wirtschaft ; Business Fluctuations; Cycles ; Multiple or Simultaneous Equation Models: Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
• Subject: Business cycles ; generalized autoregressive score models ; time-varying transition probabilities ; turning points

Contributors, Places and Time

• Event: Geistige Schöpfung
• (who): van Os, Bram ; van Dijk, Dick
• Event: Veröffentlichung
• (who): Tinbergen Institute
• (where): Amsterdam and Rotterdam
• (when): 2020

Further information

• Handle: http://hdl.handle.net/10419/229677
• Last update: 10.03.2025, 11:42 AM CET