Nonparametric tests for tail monotonicity

dc.contributor.author	Berghaus, Betina
dc.contributor.author	Bücher, Axel
dc.date.accessioned	2013-03-14T10:21:20Z
dc.date.available	2013-03-14T10:21:20Z
dc.date.issued	2013-03-14
dc.description.abstract	This article proposes nonparametric tests for tail monotonicity of bivariate random vectors. The test statistic is based on a Kolmogorov-Smirnov-type functional of the empirical copula. Depending on the serial dependence features of the data, we propose two multiplier bootstrap techniques to approximate the critical values. We show that the test is able to detect local alternatives converging to the null hypothesis at rate n^-1/2 with a non-trivial power. A simulation study is performed to investigate the finite-sample performance and finally the procedure is illustrated by testing intergenerational income mobility.	en
dc.identifier.uri	http://hdl.handle.net/2003/30095
dc.identifier.uri	http://dx.doi.org/10.17877/DE290R-14594
dc.language.iso	en	de
dc.relation.ispartofseries	Discussion Paper / SFB 823;7/2013	en
dc.subject	copula	en
dc.subject	left tail decreasing	en
dc.subject	multiplier bootstrap	en
dc.subject	ranks	en
dc.subject	tail monotonicity	en
dc.subject.ddc	310
dc.subject.ddc	330
dc.subject.ddc	620
dc.title	Nonparametric tests for tail monotonicity	en
dc.type	Text	de
dc.type.publicationtype	workingPaper	de
dcterms.accessRights	open access

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