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SEMIPARAMETRIC ESTIMATION WITH GENERATED COVARIATES

Enno Mammen, Christoph Rothe and Melanie Schienle

Econometric Theory, 2016, vol. 32, issue 5, 1140-1177

Abstract: 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.

Date: 2016
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Working Paper: Semiparametric estimation with generated covariates (2016) Downloads
Working Paper: Semiparametric Estimation with Generated Covariates (2014) Downloads
Working Paper: Semiparametric Estimation with Generated Covariates (2011) Downloads
Working Paper: Semiparametric Estimation with Generated Covariates (2011) Downloads
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