On the uncertainty of a combined forecast: The critical role of correlation

Jan Magnus and Andrey Vasnev

No BAWP-2022-01, Working Papers from University of Sydney Business School, Discipline of Business Analytics

Abstract: The purpose of this paper is to show that the effect of the zero-correlation assumption in combining forecasts can be huge, and that ignoring (positive) correlation can lead to confidence bands around the forecast combination that are much too narrow. In the typical case where three or more forecasts are combined, the estimated variance increases without bound when correlation increases. Intuitively, this is because similar forecasts provide little information if we know that they are highly correlated. Although we concentrate on forecast combinations and confidence bands, our theory applies to any statistic where the observations are linearly combined. We apply our theoretical results to explain why forecasts by Central Banks (in our case, the Bank of Japan) are so frequently misleadingly precise. In most cases, a correlation above 0.7 is required to produce reasonable confidence bands.

Keywords: Combining information; Correlation; Growth forecasting; Inflation forecasting; Central Banks (search for similar items in EconPapers)
JEL-codes: C52 C53 E31 E37 O40 (search for similar items in EconPapers)
Date: 2021-12-21
New Economics Papers: this item is included in nep-for
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://hdl.handle.net/2123/27307

Related works:
Journal Article: On the uncertainty of a combined forecast: The critical role of correlation (2023)
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:syb:wpbsba:2123/27307

Access Statistics for this paper

More papers in Working Papers from University of Sydney Business School, Discipline of Business Analytics Contact information at EDIRC.
Bibliographic data for series maintained by Artem Prokhorov ().