Generalised density forecast combinations

George Kapetanios, James Mitchell, Simon Price and Nicholas Fawcett

Journal of Econometrics, 2015, vol. 188, issue 1, 150-165

Abstract: Density forecast combinations are becoming increasingly popular as a means of improving forecast ‘accuracy’, as measured by a scoring rule. In this paper we generalise this literature by letting the combination weights follow more general schemes. Sieve estimation is used to optimise the score of the generalised density combination where the combination weights depend on the variable one is trying to forecast. Specific attention is paid to the use of piecewise linear weight functions that let the weights vary by region of the density. We analyse these schemes theoretically, in Monte Carlo experiments and in an empirical study. Our results show that the generalised combinations outperform their linear counterparts.

Keywords: Density forecasting; Model combination; Scoring rules (search for similar items in EconPapers)
JEL-codes: C53 (search for similar items in EconPapers)
Date: 2015
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (51)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0304407615001232
Full text for ScienceDirect subscribers only

Related works:
Working Paper: Generalised density forecast combinations (2014)
Working Paper: Generalised Density Forecast Combinations (2014)
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:econom:v:188:y:2015:i:1:p:150-165

DOI: 10.1016/j.jeconom.2015.02.047

Access Statistics for this article

Journal of Econometrics is currently edited by T. Amemiya, A. R. Gallant, J. F. Geweke, C. Hsiao and P. M. Robinson

More articles in Journal of Econometrics from Elsevier
Bibliographic data for series maintained by Catherine Liu ().