Combining forecast densities from VARs with uncertain instabilities

Anne-Sofie Jore, James Mitchell and Shaun Vahey
Additional contact information
Anne-Sofie Jore: Norges Bank (Central Bank of Norway)

No 2008/01, Working Paper from Norges Bank

Abstract: Clark and McCracken (2008) argue that combining real-time point forecasts from VARs of output, prices and interest rates improves point forecast accuracy in the presence of uncertain model instabilities. In this paper, we generalize their approach to consider forecast density combinations and evaluations. Whereas Clark and McCracken (2008) show that the point forecast errors from particular equal-weight pairwise averages are typically comparable or better than benchmark univariate time series models, we show that neither approach produces accurate real-time forecast densities for recent US data. If greater weight is given to models that allow for the shifts in volatilities associated with the Great Moderation, predictive density accuracy improves substantially.

Keywords: Density forecasts; Uncertainty; Combining forecasts; Evaluating forcasts; VAR models (search for similar items in EconPapers)
JEL-codes: C32 E37 F53 (search for similar items in EconPapers)
Pages: 26 pages
Date: 2008-01-24
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (55)

Downloads: (external link)
https://www.norges-bank.no/en/news-events/news-pub ... apers/2008/WP-20081/

Related works:
Journal Article: Combining forecast densities from VARs with uncertain instabilities (2010)
Working Paper: Combining Forecast Densities from VARs with Uncertain Instabilities (2008)
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:bno:worpap:2008_01

Access Statistics for this paper

More papers in Working Paper from Norges Bank Contact information at EDIRC.
Bibliographic data for series maintained by ().