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Efficiency of Weighted Average Derivative Estimators and Index Models

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Author Info
Newey, Whitney K
Stoker, Thomas M
Abstract

Weighted average derivatives are useful parameters for semiparametric index models and nonparametric demand analysis. This paper gives efficiency results for average derivative estimators, including formulating estimators that have high efficiency. The authors derive the efficiency bound for weighted average derivatives of conditional location functionals, such as the conditional mean and median. They also derive the efficiency bound for semiparametric index models, where the location measure depends on indices or linear combinations of the regressors. The authors derive the efficient weight function when the distribution of the regressors is elliptically symmetric. They also discuss how to combine estimators with different known weight functions to achieve efficiency. Copyright 1993 by The Econometric Society.

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Article provided by Econometric Society in its journal Econometrica.

Volume (Year): 61 (1993)
Issue (Month): 5 (September)
Pages: 1199-223
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Handle: RePEc:ecm:emetrp:v:61:y:1993:i:5:p:1199-223

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  1. Pedro Carneiro & James J. Heckman & Edward J. Vytlacil, 2009. "Evaluating Marginal Policy Changes and the Average Effect of Treatment for Individuals at the Margin," NBER Working Papers 15211, National Bureau of Economic Research, Inc. [Downloadable!] (restricted)
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  2. Juan Carlos Escanciano & Kyungchul Song, 2007. "Asymptotically Optimal Tests for Single-Index Restrictions with a Focus on Average Partial Effects," PIER Working Paper Archive 07-005, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania. [Downloadable!]
  3. Subbotin, Viktor, 2008. "Essays on the econometric theory of rank regressions," MPRA Paper 14086, University Library of Munich, Germany. [Downloadable!]
  4. Matias D. Cattaneo & Richard K. Crump & Michael Jansson, 2008. "Small Bandwidth Asymptotics for Density-Weighted Average Derivatives," CREATES Research Papers 2008-24, School of Economics and Management, University of Aarhus. [Downloadable!]
  5. Chunrong Ai & Xiaohong Chen, 2009. "Semiparametric Efficiency Bound for Models of Sequential Moment Restrictions Containing Unknown Functions," Cowles Foundation Discussion Papers 1731, Cowles Foundation, Yale University. [Downloadable!]
  6. Andrew Chesher, 2005. "Identification with excess heterogeneity," CeMMAP working papers CWP19/05, Centre for Microdata Methods and Practice, Institute for Fiscal Studies. [Downloadable!]
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