Convergence of the risk for nonparametric IV quantile regression and nonparametric IV regression with full independence

dc.contributor.authorDunker, Fabian
dc.date.accessioned2015-11-27T15:53:59Z
dc.date.available2015-11-27T15:53:59Z
dc.date.issued2015
dc.description.abstractIn econometrics some nonparametric instrumental regression models and nonparametric demand models with endogeneity lead to nonlinear integral equations with unknown integral kernels. We prove convergence rates of the risk for the iteratively regularized Newton method applied to these problems. Compared to related results we relay on a weaker non-linearity condition and have stronger convergence results. We demonstrate by numerical simulations for a nonparametric IV regression problem with continuous instrument and regressor that the method produces better results than the standard method.en
dc.identifier.urihttp://hdl.handle.net/2003/34373
dc.identifier.urihttp://dx.doi.org/10.17877/DE290R-16447
dc.language.isoende
dc.relation.ispartofseriesDiscussion Paper / SFB 823;45/2015en
dc.subjectnonparametric regressionen
dc.subjectiterative regularizationen
dc.subjectnonlinear inverse problemsen
dc.subjectinstrumental variablesen
dc.subject.ddc310
dc.subject.ddc330
dc.subject.ddc620
dc.titleConvergence of the risk for nonparametric IV quantile regression and nonparametric IV regression with full independenceen
dc.typeTextde
dc.type.publicationtypeworkingPaperde
dcterms.accessRightsopen access

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