Forecast combination for U.S. recessions with real-time data
AbstractThis 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 logscore 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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Bibliographic InfoPaper provided by University of Sydney Business School, Discipline of Business Analytics in its series Working Papers with number 02/2013.
Date of creation: Jan 2013
Date of revision:
Other versions of this item:
- Pauwels, Laurent & Vasnev, Andrey, 2013. "Forecast combination for U.S. recessions with real-time data," Working Papers 13 BAWP, University of Sydney Business School, Discipline of Business Analytics.
- NEP-ALL-2013-10-25 (All new papers)
- NEP-FOR-2013-10-25 (Forecasting)
- NEP-MAC-2013-10-25 (Macroeconomics)
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