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Title: Nonlinear Forecast Combinations:: An Example Using Euro-Area GDP Growth
Authors: Gibson, Heather D.
Hall, Stephen G.
Tavlas, George S.
First Published: 30-Nov-2018
Publisher: Elsevier
Citation: Journal of Economic Behavior and Organization, 2018
Abstract: The forecasting literature shows that when a number of different forecasters produce forecasts of the same variable it is almost always possible to produce a better forecast by linearly combining the individual forecasts. Moreover, it is often argued that a simple average of the forecasts will outperform more complex combination methods. This paper shows that, analytically, nonlinear combinations of forecasts are superior to linear combinations. Empirical results, based on comparisons of real GDP growth projections with outturns for the euro area using time-varying-coefficient estimation, confirm that analytical result, especially for periods marked by structural changes.
DOI Link: 10.1016/j.jebo.2018.09.021
ISSN: 0167-2681
Embargo on file until: 30-May-2020
Version: Post-print
Status: Peer-reviewed
Type: Journal Article
Rights: Copyright © Elsevier 2018. After an embargo period this version of the paper will be an open-access article distributed under the terms of the Creative Commons Attribution-Non Commercial-No Derivatives License (, which permits use and distribution in any medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are made.
Description: Supplementary material associated with this article can be found, in the online version, at doi:10.1016/j.jebo.2018.09.021.
The file associated with this record is under embargo until 18 months after publication, in accordance with the publisher's self-archiving policy. The full text may be available through the publisher links provided above.
Appears in Collections:Published Articles, School of Management

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