Generalised empirical likelihood-based kernel density estimation

Vitaliy Oryshchenko () and Richard Smith ()

No 662, Economics Series Working Papers from University of Oxford, Department of Economics

Abstract: If additional information about the distribution of a random variable is available in the form of moment conditions, a weighted kernel density estimate reflecting the extra information can be constructed by replacing the uniform weights with the generalised empirical likelihood probabilities. It is shown that the resultant density estimator provides an improved approximation to the moment constraints. Moreover, a reduction in variance is achieved due to the systematic use of the extra moment information.

Keywords: Weighted kernel density estimation; moment conditions; higher-order expansions; normal mixtures (search for similar items in EconPapers)
JEL-codes: C14 (search for similar items in EconPapers)
Date: 2013-07-02
New Economics Papers: this item is included in nep-dcm
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Working Paper: Generalised empirical likelihood-based kernel density estimation (2013)
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