A note on testing symmetry of the error distribution in linear regression models

Natalie Neumeyer, Holger Dette and Eva-Renate Nagel

No 2003,25, Technical Reports from Technische Universität Dortmund, Sonderforschungsbereich 475: Komplexitätsreduktion in multivariaten Datenstrukturen

Abstract: In the classical linear regression model the problem of testing for symmetry of the error distribution is considered. The test statistic is a functional of the difference between the two empirical distribution functions of the estimated residuals and their counterparts with opposite signs. The weak convergence of the difference process to a Gaussian process is established. The covariance structure of this process depends heavily on the density of the error distribution, and for this reason the performance of a symmetric wild bootstrap procedure is discussed in asymptotic theory and by means of a simulation study.

Keywords: M-estimation; goodness-of-fit tests; testing for symmetry; empirical process of residuals; linear model (search for similar items in EconPapers)
Date: 2003
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