Forecast combination for U.S. recessions with real-time data |
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| Institution: | 1. Banca d’Italia, Via Nazionale, 91, 00184 Rome, Italy;2. Bank for International Settlements, Centralbahnplatz 2, CH-4002 Basel, Switzerland;1. Department of Banking and Finance, National Chiayi University, No. 580, Sinmin Road, Chiayi City 60054, Taiwan;2. Department of Finance, National Yunlin University of Science & Technology, No. 123, University Road, Section 3, Douliou City 64002, Taiwan;3. Department of Wealth and Taxation Management, National Kaohsiung University of Applied Sciences, No. 415, Chien-Kung Road, Sanmin District, Kaohsiung City 80778, Taiwan;4. Graduate Institute of Finance, National Pingtung University of Science and Technology, No. 1, Hseuhfu Road, Neipu, Pingtung 91201, Taiwan;1. De Nederlandsche Bank, PO Box 98, 1000 AB Amsterdam, Netherlands;2. Cass Business School, London, United Kingdom;1. School of Finance, Zhejiang Gongshang University, No. 18 Xuezheng Street, Hangzhou 310018, China;2. Department of Banking & Finance, Tamkang University, Taiwan and the Center for Research of Private Economy at Zhejiang University, Hangzhou, China;3. College of Management, Taiwan Normal University, Taiwan;1. College of Business, University of Texas at San Antonio, San Antonio, TX, USA;2. School of Banking and Finance, University of New South Wales, Kensington, NSW, Australia;3. Antai College of Economics and Management, Shanghai Jiaotong University, Shanghai, China |
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| Abstract: | This paper proposes the use of forecast combination to improve predictive accuracy in forecasting the U.S. business cycle index, as published by the Business Cycle Dating Committee of the NBER. It focuses on one-step ahead out-of-sample monthly forecast utilising the well-established coincident indicators and yield curve models, allowing for dynamics and real-time data revisions. Forecast combinations use log-score and quadratic-score based weights, which change over time. This paper finds that forecast accuracy improves when combining the probability forecasts of both the coincident indicators model and the yield curve model, compared to each model's own forecasting performance. |
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| Keywords: | U S business cycle Forecast combination Density forecast Probit models Yield curve Coincident indicators |
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