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Efficiency bounds for estimating linear functionals of nonparametric regression models with endogenous regressors

Thomas A. Severini and Gautam Tripathi ()

Journal of Econometrics, 2012, vol. 170, issue 2, 491-498

Abstract: Let Y=μ∗(X)+ε, where μ∗ is unknown and E[ε|X]≠0 with positive probability but there exist instrumental variables W such that E[ε|W]=0 w.p.1. It is well known that such nonparametric regression models are generally “ill-posed” in the sense that the map from the data to μ∗ is not continuous. In this paper, we derive the efficiency bounds for estimating certain linear functionals of μ∗ without assuming μ∗ itself to be identified.

Date: 2012
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Related works:
Working Paper: Efficiency bounds for estimating linear functionals of nonparametric regression models with endogenous regressors (2007) Downloads
Working Paper: Efficiency Bounds for Estimating Linear Functionals of Nonparametric Regression Models with Endogenous Regressors (2007) Downloads
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