Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/31040 
Year of Publication: 
2006
Series/Report no.: 
Discussion Paper No. 477
Publisher: 
Ludwig-Maximilians-Universität München, Sonderforschungsbereich 386 - Statistische Analyse diskreter Strukturen, München
Abstract: 
we prove that the quasi-score estimator in a mean-variance model is optimal in the class of (unbiased) linear score estimators, in the sense that the difference of the asymptotic covariance matrices of the linear score and quasi-score estimator is positive semi-definite. We also give conditions under which this difference in zero or under which it is positive definite. This result can be applied to measurement error models where it implies that the quasi-score estimator is asymptotically more efficient than the corrected score estimator.
Persistent Identifier of the first edition: 
Document Type: 
Working Paper

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