Misspecification testing in a class of conditional distributional models

dc.contributor.author	Rothe, Christoph
dc.contributor.author	Wied, Dominik
dc.date.accessioned	2011-01-18T14:45:49Z
dc.date.available	2011-01-18T14:45:49Z
dc.date.issued	2011-01-18
dc.description.abstract	We propose a specification test for a wide range of parametric models for conditional distribution function of an outcome variable given a vector of covariates. The test is based on the Cramer-von Mises distance between an unrestricted estimate of the joint distribution function of the data, and an restricted estimate that imposes the structure implied by the model. The procedure is straightforward to implement, is consistent against fixed alternatives, has non-trivial power against local deviations from the null hypothesis of order n^(-1/2), and does not require the choice of smoothing parameters. We also provide an empirical application using data on wages in the US.	en
dc.identifier.uri	http://hdl.handle.net/2003/27575
dc.identifier.uri	http://dx.doi.org/10.17877/DE290R-4172
dc.language.iso	en	de
dc.relation.ispartofseries	Discussion Paper / SFB 823 ; 03/2011
dc.relation.isreplacedby	http://hdl.handle.net/2003/27595
dc.subject	Bootstrap	en
dc.subject	Cramer-von Mises Distance	en
dc.subject	Distributional Regression	en
dc.subject	Quantile Regression	en
dc.subject.ddc	310
dc.subject.ddc	330
dc.subject.ddc	620
dc.title	Misspecification testing in a class of conditional distributional models	en
dc.type	Text	de
dc.type.publicationtype	workingPaper	de
dcterms.accessRights	restricted

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