A nonparametric distributionf-free test for serial independence of errors

Du, Zaichao; Escanciano, Juan Carlos

A nonparametric distributionf-free test for serial independence of errors

Author(s): Du, Zaichao; Escanciano, Juan Carlos

Publisher: Taylor & Francis

Issued date: 2014-09-03

Citation: Du, Z., & Escanciano, J. C. (2014). A Nonparametric Distribution-Free Test for Serial Independence of Errors. Econometric Reviews, 34(6-10), pp. 1011-1034.

ISSN: 0747-4938

DOI: https://doi.org/10.1080/07474938.2014.956616

xmlui.dri2xhtml.METS-1.0.item-contributor-funder: Ministerio de Educación y Ciencia (España)

Sponsor: Research of first author funded by Ministry of Education of China, 11XJC790002 and the National Natural Science Foundation of China, 71401140. Research of second author has been funded by the Spanish Plan Nacional de I+ D+ I, reference number SEJ2007-62908.

Project: Gobierno de España. SEJ2007-62908

Keywords: Empirical processes , Generalized spectral test , Location-scale model , Parameter estimation uncertainty , Serial dependence , Unobservable errors

JEL Classification: C12 , C14 , C52

URI: http://hdl.handle.net/10016/35043

Rights: © Taylor & Francis Group
Atribución-NoComercial-SinDerivadas 3.0 España

Abstract:

In this article, we propose a test for the serial independence of unobservable errors in location-scale models. We consider a Hoeffding-Blum-Kiefer-Rosenblat type empirical process applied to residuals, and show that under certain conditions it converges weakl [+]

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