Semiparametric estimation with generated covariates
We study a general class of semiparametric estimators when the infinite-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 endogen...
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| Hauptverfasser: | , , |
|---|---|
| Dokumenttyp: | Article (Journal) |
| Sprache: | Englisch |
| Veröffentlicht: |
October 2016
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| In: |
Econometric theory
Year: 2016, Jahrgang: 32, Heft: 5, Pages: 1140-1177 |
| ISSN: | 1469-4360 |
| DOI: | http://dx.doi.org/10.1017/S0266466615000134 |
| Online-Zugang: | Verlag, lizenzpflichtig, Volltext: https://doi.org/http://dx.doi.org/10.1017/S0266466615000134 Verlag, lizenzpflichtig, Volltext: https://search.proquest.com/docview/1819082988?pq-origsite=gscholar |
| Verfasserangaben: | Enno Mammen, Christoph Rothe, Melanie Schienle |
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| 520 | |a We study a general class of semiparametric estimators when the infinite-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 nonstandard 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. | ||
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