Generalised empirical likelihood-based kernel density estimation
If additional information about the distribution of a random variable is available in the form of moment conditions, a weighted kernel density estimate re ecting 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.
|Date of creation:||12 Feb 2013|
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- Whitney K. Newey & Richard J. Smith, 2004.
"Higher Order Properties of Gmm and Generalized Empirical Likelihood Estimators,"
Econometric Society, vol. 72(1), pages 219-255, 01.
- Whitney Newey & Richard Smith, 2003. "Higher order properties of GMM and generalised empirical likelihood estimators," CeMMAP working papers CWP04/03, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
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