A nonparametric approach to identifying a subset of forecasters that outperforms the simple average

Constantin Bürgi and Tara Sinclair

Empirical Economics, 2017, vol. 53, issue 1, No 7, 115 pages

Abstract: Abstract Empirical studies in the forecast combination literature have shown that it is notoriously difficult to improve upon the simple average despite the availability of optimal combination weights. In particular, historical performance-based combination approaches do not select forecasters that improve upon the simple average going forward. This paper shows that this is due to the high correlation among forecasters, which only by chance causes some individuals to have lower root-mean-squared error (RMSE) than the simple average. We introduce a new nonparametric approach to eliminate forecasters who perform well based on chance as well as poor performers. This leaves a subset of forecasters with better performance in subsequent periods. The average of this group improves upon the simple average in the SPF particularly for bond yields where some forecasters may be more likely to have superior forecasting ability.

Keywords: Forecast combination; Forecast evaluation; Multiple model comparisons; Real-time data; Survey of professional forecasters (search for similar items in EconPapers)
JEL-codes: C22 C52 C53 (search for similar items in EconPapers)
Date: 2017
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (9)

Downloads: (external link)
http://link.springer.com/10.1007/s00181-016-1152-y Abstract (text/html)
Access to the full text of the articles in this series is restricted.

Related works:
Working Paper: A Nonparametric Approach to Identifying a Subset of Forecasters that Outperforms the Simple Average (2015)
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:spr:empeco:v:53:y:2017:i:1:d:10.1007_s00181-016-1152-y

Ordering information: This journal article can be ordered from
http://www.springer. ... rics/journal/181/PS2

DOI: 10.1007/s00181-016-1152-y

Access Statistics for this article

Empirical Economics is currently edited by Robert M. Kunst, Arthur H.O. van Soest, Bertrand Candelon, Subal C. Kumbhakar and Joakim Westerlund

More articles in Empirical Economics from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().