Practical Use of Sensitivity in Econometrics with an Illustration to Forecast Combinations

22 Pages Posted: 7 Mar 2013

See all articles by J.R. Magnus

J.R. Magnus

Vrije Universiteit Amsterdam, School of Business and Economics

Andrey L. Vasnev

University of Sydney

Date Written: March 6, 2013

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.

Keywords: Sensitivity analysis, Forecast combination, Yield curve prediction

JEL Classification: C10, C53

Suggested Citation

Magnus, Jan R. and Vasnev, Andrey L., Practical Use of Sensitivity in Econometrics with an Illustration to Forecast Combinations (March 6, 2013). Available at SSRN: https://ssrn.com/abstract=2229548 or http://dx.doi.org/10.2139/ssrn.2229548

Jan R. Magnus

Vrije Universiteit Amsterdam, School of Business and Economics ( email )

De Boelelaan 1105
Amsterdam, 1081HV
Netherlands

Andrey L. Vasnev (Contact Author)

University of Sydney ( email )

Sydney, NSW 2006
Australia

HOME PAGE: http://www.econ.usyd.edu.au/staff/andreyv

Register to save articles to
your library

Register

Paper statistics

Downloads
30
Abstract Views
305
PlumX Metrics