Generalized moment based estimation and inference
AbstractWe extend the empirical likelihood method of estimation and inference proposed by Owen and others and demonstrate how it may be used in a general linear model context and to mitigate the impact of an ill-conditioned design matrix. A dual loss information theoretic estimating function is used along with extended moment conditions to yield a data based estimator that has the usual consistency and asymptotic normality results. Limiting chi-square distributions may be used to obtain hypothesis test or confidence intervals. The estimator appears to have excellent finite sample properties under a squared error loss measure.
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Bibliographic InfoArticle provided by Elsevier in its journal Journal of Econometrics.
Volume (Year): 107 (2002)
Issue (Month): 1-2 (March)
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Web page: http://www.elsevier.com/locate/jeconom
Other versions of this item:
- George Judge & Marco Van_Akkeren, 2000. "Generalized Moment Based Estimation and Inference," Econometric Society World Congress 2000 Contributed Papers 0073, Econometric Society.
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