EconPapers    
Economics at your fingertips  
 

On the Forecast Combination Puzzle

Wei Qian, Craig A. Rolling, Gang Cheng and Yuhong Yang
Additional contact information
Wei Qian: Department of Applied Economics and Statistics, University of Delaware, Newark, DE 19716, USA
Craig A. Rolling: School of Statistics, University of Minnesota, Minneapolis, MN 55455, USA
Gang Cheng: School of Statistics, University of Minnesota, Minneapolis, MN 55455, USA
Yuhong Yang: School of Statistics, University of Minnesota, Minneapolis, MN 55455, USA

Econometrics, 2019, vol. 7, issue 3, 1-26

Abstract: It is often reported in the forecast combination literature that a simple average of candidate forecasts is more robust than sophisticated combining methods. This phenomenon is usually referred to as the “forecast combination puzzle”. Motivated by this puzzle, we explore its possible explanations, including high variance in estimating the target optimal weights (estimation error), invalid weighting formulas, and model/candidate screening before combination. We show that the existing understanding of the puzzle should be complemented by the distinction of different forecast combination scenarios known as combining for adaptation and combining for improvement. Applying combining methods without considering the underlying scenario can itself cause the puzzle. Based on our new understandings, both simulations and real data evaluations are conducted to illustrate the causes of the puzzle. We further propose a multi-level AFTER strategy that can integrate the strengths of different combining methods and adapt intelligently to the underlying scenario. In particular, by treating the simple average as a candidate forecast, the proposed strategy is shown to reduce the heavy cost of estimation error and, to a large extent, mitigate the puzzle.

Keywords: combining for adaptation; combining for improvement; multi-level AFTER; model selection; structural break (search for similar items in EconPapers)
JEL-codes: B23 C C00 C01 C1 C2 C3 C4 C5 C8 (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

Downloads: (external link)
https://www.mdpi.com/2225-1146/7/3/39/pdf (application/pdf)
https://www.mdpi.com/2225-1146/7/3/39/ (text/html)

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:gam:jecnmx:v:7:y:2019:i:3:p:39-:d:265946

Access Statistics for this article

Econometrics is currently edited by Ms. Jasmine Liu

More articles in Econometrics from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().

 
Page updated 2025-03-19
Handle: RePEc:gam:jecnmx:v:7:y:2019:i:3:p:39-:d:265946