Forecast Combination for U.S. Recessions with Real-Time Data

15 Pages Posted: 19 Jan 2013 Last revised: 6 Dec 2013

See all articles by Laurent L. Pauwels

Laurent L. Pauwels

The University of Sydney; Australian National University (ANU) - Centre for Applied Macroeconomic Analysis (CAMA)

Andrey L. Vasnev

University of Sydney

Date Written: December 2013

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.

Keywords: U.S. business cycle, forecast combination, density forecast, probit models, yield curve, coincident indicators

JEL Classification: C5, C3

Suggested Citation

Pauwels, Laurent L. and Vasnev, Andrey L., Forecast Combination for U.S. Recessions with Real-Time Data (December 2013). Available at SSRN: https://ssrn.com/abstract=2203574 or http://dx.doi.org/10.2139/ssrn.2203574

Laurent L. Pauwels

The University of Sydney ( email )

University of Sydney
Sydney, NSW 2006
Australia

Australian National University (ANU) - Centre for Applied Macroeconomic Analysis (CAMA) ( email )

ANU College of Business and Economics
Canberra, Australian Capital Territory 0200
Australia

Andrey L. Vasnev (Contact Author)

University of Sydney ( email )

Sydney, NSW 2006
Australia

HOME PAGE: http://www.econ.usyd.edu.au/staff/andreyv

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