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Nonlinear Forecast Combinations:: An Example Using Euro-Area GDP Growth

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journal contribution
posted on 14.05.2019, 13:40 by Heather D. Gibson, Stephen G. Hall, George S. Tavlas
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.

History

Citation

Journal of Economic Behavior and Organization, 2018

Author affiliation

/Organisation/COLLEGE OF SOCIAL SCIENCES, ARTS AND HUMANITIES/School of Business

Version

AM (Accepted Manuscript)

Published in

Journal of Economic Behavior and Organization

Publisher

Elsevier

issn

0167-2681

Acceptance date

28/09/2018

Copyright date

2018

Publisher version

https://www.sciencedirect.com/science/article/pii/S0167268118302695

Notes

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.

Language

en