Nonlinear quantile regression under dependence and heterogeneity

Walter Oberhofer and Harry Haupt

No 388, University of Regensburg Working Papers in Business, Economics and Management Information Systems from University of Regensburg, Department of Economics

Abstract: This paper derives the asymptotic normality of the nonlinear quantile regression estimator with dependent errors. The required assumptions are weak, and it is neither assumed that the error process is stationary nor that it is mixing. In fact, the notion of weak dependence introduced in this paper, can be considered as a quantile specific local variant of known concepts. The connection of the derived asymptotic results to corresponding results of least squares estimation is obvious. In dieser Arbeit wird die asymptotische Normalität des nichtlinearen Quantilsregressionsschätzers bei abhängigen Fehlertermen bewiesen. Die Annahmen die dabei zu Grunde liegen sind sehr schwach, wobei gezeigt wird, dass weder die Stationarität noch eine Mixing-Eigenschaft des Fehlerprozesses erforderlich sind. Von besonderer Bedeutung ist die in diesem Papier eingeführte quantilsspezifische Form von schwacher Abhängigkeit, die als lokale Variante existierender Konzepte interpretiert werden kann. Zudem zeigt sich, dass die Asymptotik starke Parallelen zum Fall der Minimumquadratschätzung aufweist.

Keywords: Quantil; Nichtlineares Regressionsmodell; Asymptotik; Quantile regression; nonlinear regression; asymptotics (search for similar items in EconPapers)
JEL-codes: C22 (search for similar items in EconPapers)
Date: 2003
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