Forecast combination for U.S. recessions with real-time data

Laurent Pauwels and Andrey Vasnev

The North American Journal of Economics and Finance, 2014, vol. 28, issue C, 138-148

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 (search for similar items in EconPapers)
JEL-codes: C5 E3 (search for similar items in EconPapers)
Date: 2014
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S1062940814000096
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:ecofin:v:28:y:2014:i:c:p:138-148

DOI: 10.1016/j.najef.2014.02.005

Access Statistics for this article

The North American Journal of Economics and Finance is currently edited by Hamid Beladi

More articles in The North American Journal of Economics and Finance from Elsevier
Bibliographic data for series maintained by Catherine Liu ().