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Semiparametric estimation with generated covariates

Listed author(s):
  • Mammen, Enno
  • Rothe, Christoph
  • Schienle, Melanie

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 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.

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Paper provided by Karlsruhe Institute of Technology (KIT), Department of Economics and Business Engineering in its series Working Paper Series in Economics with number 81.

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Date of creation: 2016
Handle: RePEc:zbw:kitwps:81
Contact details of provider: Web page: http://www.wiwi.kit.edu/

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