Efficient estimation of forecast uncertainty based on recent forecast errors

Malte Knüppel

No 2009,28, Discussion Paper Series 1: Economic Studies from Deutsche Bundesbank

Abstract: Multi-step-ahead forecasts of forecast uncertainty in practice are often based on the horizon-specific sample means of recent squared forecast errors, where the number of available past forecast errors decreases one-to-one with the forecast horizon. In this paper, the efficiency gains from the joint estimation of forecast uncertainty for all horizons in such samples are investigated. Considering optimal forecasts, the efficiency gains can be substantial if the sample is not too large. If forecast uncertainty is estimated by seemingly unrelated regressions, the covariance matrix of the squared forecast errors does not have to be estimated, but simply needs to have a certain structure. In Monte Carlo studies it is found that seemingly unrelated regressions mostly yield estimates which are more efficient than the sample means even if the forecasts are not optimal. Seemingly unrelated regressions are used to address questions concerning the inflation forecast uncertainty of the Bank of England.

Keywords: Multi-step-ahead forecasts; forecast error variance; GLS; SUR (search for similar items in EconPapers)
JEL-codes: C13 C32 C53 (search for similar items in EconPapers)
Date: 2009
New Economics Papers: this item is included in nep-ecm, nep-ets and nep-for
References: View complete reference list from CitEc
Citations: View citations in EconPapers (2)

Downloads: (external link)
https://www.econstor.eu/bitstream/10419/28390/1/610023179.PDF (application/pdf)

Related works:
Journal Article: Efficient estimation of forecast uncertainty based on recent forecast errors (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:zbw:bubdp1:200928

Access Statistics for this paper

More papers in Discussion Paper Series 1: Economic Studies from Deutsche Bundesbank Contact information at EDIRC.
Bibliographic data for series maintained by ZBW - Leibniz Information Centre for Economics ().