Local Sensitivity and Diagnostic Tests

CentER Discussion Paper No. 2004-105

29 Pages Posted: 7 Dec 2004

See all articles by J.R. Magnus

J.R. Magnus

Vrije Universiteit Amsterdam, School of Business and Economics

Andrey L. Vasnev

University of Sydney

Multiple version iconThere are 2 versions of this paper

Date Written: October 2004


In this paper we confront sensitivity analysis with diagnostic testing. Every model is misspecified, but a model is useful if the parameters of interest (the focus) are not sensitive to small perturbations in the underlying assumptions. The study of the e ect of these violations on the focus is called sensitivity analysis. Diagnostic testing, on the other hand, attempts to find out whether a nuisance parameter is large or small. Both aspects are important, but traditional applied econometrics tends to use only diagnostics and forget about sensitivity analysis. We develop a theory of sensitivity in a maximum likelihood framework, propose a sensitivity test, give conditions under which the diagnostic and sensitivity tests are asymptotically independent, and demonstrate with three core examples that this independence is the rule rather than the exception, thus underlying the importance of sensitivity analysis.

Keywords: Maximum likelihood, sensitivity, diagnostic test, regression

JEL Classification: C12, C22, C51, C52

Suggested Citation

Magnus, Jan R. and Vasnev, Andrey L., Local Sensitivity and Diagnostic Tests (October 2004). CentER Discussion Paper No. 2004-105. Available at SSRN: https://ssrn.com/abstract=627366 or http://dx.doi.org/10.2139/ssrn.627366

Jan R. Magnus (Contact Author)

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

De Boelelaan 1105
Amsterdam, 1081HV

Andrey L. Vasnev

University of Sydney ( email )

Sydney, NSW 2006

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

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