Practical use of sensitivity in econometrics with an illustration to forecast combinations

Jan Magnus () and Andrey Vasnev

No 2013-04, Working Papers from University of Sydney Business School, Discipline of Business Analytics

Abstract: Sensitivity analysis is important for its own sake and also in combination with diagnostic testing. We consider the question how to use sensitivity statistics in practice, in particular how to judge whether sensitivity is large or small. For this purpose we distinguish between absolute and relative sensitivity and highlight the context-dependent nature of any sensitivity analysis. Relative sensitivity is then applied in the context of forecast combination and sensitivity-based weights are introduced. All concepts are illustrated through the European yield curve. In this context it is natural to look at sensitivity to autocorrelation and normality assumptions. Different forecasting models are combined with equal, fit-based and sensitivity-based weights, and compared with the multivariate and random walk benchmarks. We show that the fit-based weights and the sensitivity-based weights are complementary. For long-term maturities the sensitivity-based weights perform better than other weights.

Date: 2013-03
New Economics Papers: this item is included in nep-ecm and nep-for
References: Add references at CitEc
Citations:

Downloads: (external link)
http://hdl.handle.net/2123/8964

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:syb:wpbsba:2123/8964

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 ().