期刊
INTERNATIONAL JOURNAL OF FORECASTING
卷 40, 期 1, 页码 313-323出版社
ELSEVIER
DOI: 10.1016/j.ijforecast.2023.03.005
关键词
Business cycles; Generalized autoregressive score models; Time-varying transition probabilities; Turning points; Term spread
By extending the DFMS model and introducing time-varying transition probabilities using the score-driven approach and the term spread, this study accelerates the real-time dating of business cycle peaks and improves the ability to predict recessions.
The dynamic factor Markov-switching (DFMS) model introduced by Diebold and Rudebusch (1996) has proven to be a powerful framework for measuring the business cycle. We extend the DFMS model by allowing for time-varying transition probabilities, intending to accelerate the real-time dating of business cycle peaks. Time-variation of the transition probabilities is brought about endogenously using the 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 1959-2020, we find that signaling power for recessions is significantly improved. We are able to date the 2001 and 2008 recession peaks four and two months after the peak date, which is four and ten months before the NBER. (c) 2023 The Author(s). Published by Elsevier B.V. on behalf of International Institute of Forecasters. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据