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dc.contributor.authorMammen, Ennoen_US
dc.contributor.authorRothe, Christophen_US
dc.contributor.authorSchienle, Melanieen_US
dc.date.accessioned2011-11-02en_US
dc.date.accessioned2012-04-05T16:21:06Z-
dc.date.available2012-04-05T16:21:06Z-
dc.date.issued2011en_US
dc.identifier.urihttp://hdl.handle.net/10419/56726-
dc.description.abstractIn this paper, we study a general class of semiparametric optimization estimators of a vector-valued parameter. The criterion function depends on two types of infinite-dimensional nuisance parameters: a conditional expectation function that has been estimated nonparametrically using generated covariates, and another estimated function that is used to compute the generated covariates in the first place. We study the asymptotic properties of estimators in this class, which is a nonstandard problem due to the presence of generated covariates. We give conditions under which estimators are root-n consistent and asymptotically normal, and derive a general formula for the asymptotic variance.en_US
dc.language.isoengen_US
dc.publisherSFB 649, Economic Risk Berlinen_US
dc.relation.ispartofseriesSFB 649 discussion paper 2011-064en_US
dc.subject.jelC14en_US
dc.subject.jelC31en_US
dc.subject.ddc330en_US
dc.subject.keywordsemiparametric estimationen_US
dc.subject.keywordgenerated covariatesen_US
dc.subject.keywordprofilingen_US
dc.subject.keywordpropensity scoreen_US
dc.subject.stwNichtparametrisches Verfahrenen_US
dc.subject.stwSchätztheorieen_US
dc.subject.stwKorrelationen_US
dc.subject.stwTheorieen_US
dc.titleSemiparametric estimation with generated covariatesen_US
dc.typeWorking Paperen_US
dc.identifier.ppn671178881en_US
dc.rightshttp://www.econstor.eu/dspace/Nutzungsbedingungenen_US
Appears in Collections:SFB 649 Discussion Papers, HU Berlin

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