Semiparametric estimation with generated covariates

We study a general class of semiparametric estimators when the in nite-dimensional nuisance parameters include a conditional expectation function that has been estimated nonparametrically using generated covariates. Such estimators are used frequently to e.g. estimate nonlinear models with endogenou...

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Bibliographische Detailangaben
Hauptverfasser: Mammen, Enno (VerfasserIn) , Rothe, Christoph (VerfasserIn) , Schienle, Melanie (VerfasserIn)
Dokumenttyp: Book/Monograph Arbeitspapier
Sprache:Englisch
Veröffentlicht: Berlin SFB 649, Economic Risk 2014
Schriftenreihe:SFB 649 discussion paper 2014-043
In: SFB 649 discussion paper (2014-043)

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Online-Zugang:Verlag, Volltext: http://sfb649.wiwi.hu-berlin.de/papers/pdf/SFB649DP2014-043.pdf
Download aus dem Internet, Stand: 15.09.2014, Volltext: http://hdl.handle.net/10419/103778
Volltext
Verfasserangaben:Enno Mammen, Christoph Rothe, and Melanie Schienle
Beschreibung
Zusammenfassung:We study a general class of semiparametric estimators when the in nite-dimensional nuisance parameters include a conditional expectation function that has been estimated nonparametrically using generated covariates. Such estimators are used frequently to e.g. estimate nonlinear models with endogenous covariates when identification is achieved using control variable techniques. We study the asymptotic properties of estimators in this class, which is a non-standard problem due to the presence of generated covariates. We give conditions under which estimators are root-n consistent and asymptotically normal, derive a general formula for the asymptotic variance, and show how to establish validity of the bootstrap.
Beschreibung:Online Resource
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