Effcient M-estimators with auxiliary information
AbstractThis paper introduces a new class of M-estimators based on generalised empirical likelihood estimation with some auxiliary information available in the sample. The resulting class of estimators is efficient in the sense that it achieves the same asymptotic lower bound as that of the efficient generalised method of moment-based M-estimator with the same auxiliary information. The results of the paper are quite general and apply to M-estimators defined by both smooth and nonsmooth estimating equations. Simulations show that the proposed estimators perform well in finite samples, and can be less biased and more precise than standard M-estimators within China.
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Bibliographic InfoPaper provided by Department of Economics, University of York in its series Discussion Papers with number 08/26.
Date of creation: Aug 2008
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Asymptotic efficiency. Generalised empirical likelihood. Generalised method of moments. M-estimators. Generalised method of moments; M-estimators.;
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