Controlling the significance levels of prediction error tests for linear regression models
Leslie Godfrey and
Chris Orme ()
Econometrics Journal, 2000, vol. 3, issue 1, 66-83
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.
Keywords: Asymptotic theory; Bootstrap; Prediction error tests; Non-normality. (search for similar items in EconPapers)
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Persistent link: https://EconPapers.repec.org/RePEc:ect:emjrnl:v:3:y:2000:i:1:p:66-83
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