Controlling the significance levels of prediction error tests for linear regression models

This paper provides evidence on problems associated with using standard tests for predictive failure when the errors of a linear regression model are not normally distributed. The ability of a simple bootstrap procedure to give a useful degree of control over the significance levels is examined.

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Year of publication:	2000
Authors:	GODFREY, LESLIE G. ; ORME, CHRIS D.
Published in:	Econometrics Journal. - Royal Economic Society - RES. - Vol. 3.2000, 1, p. 66-83
Publisher:	Royal Economic Society - RES
Subject:	Asymptotic theory \| Bootstrap \| Prediction error tests \| Non-normality

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Type of publication:	Article
Source:	RePEc - Research Papers in Economics

Persistent link: https://www.econbiz.de/10005607117