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Publication Date:
June 2009
ISSN:
1557-4679
DOI:
10.2202/1557-4679.1153

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Ed. by Hubbard, Alan E. / van der Laan, Mark J.

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IMPACT FACTOR 2011: 1.284

Semiparametrically Efficient Estimation of Conditional Instrumental Variables Parameters

Maximilian Kasy

1University of California, Berkeley

Citation Information: The International Journal of Biostatistics. Volume 5, Issue 1, Pages –, ISSN (Online) 1557-4679, DOI: 10.2202/1557-4679.1153, June 2009

Publication History:
Published Online:
2009-06-30

In this paper, I propose a set of parameters designed to identify the slope of structural relationships based on a combination of conditioning on covariates and the use of an exogenous instrument. After giving structural interpretations to these parameters in the context of specific semiparametric models, I derive their efficient influence curves in a fully nonparametric context as well as under imposition of restrictions on the instrument. These influence curves give the semiparametric efficiency bounds for regular asymptotically linear estimators of the parameters and allow the construction of asymptotically efficient estimators. Monte Carlo experiments finally demonstrate the good finite sample performance of such estimators.

Keywords: instrumental variables; efficient influence curve

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