Asymptotic optimality of the quasi-score estimator in a class of linear score estimators
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.
Year of publication: |
2006
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Authors: | Kukush, Alexander ; Schneeweiss, Hans |
Publisher: |
München : Ludwig-Maximilians-Universität München, Sonderforschungsbereich 386 - Statistische Analyse diskreter Strukturen |
Saved in:
freely available
Series: | Discussion Paper ; 477 |
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Type of publication: | Book / Working Paper |
Type of publication (narrower categories): | Working Paper |
Language: | English |
Other identifiers: | 10.5282/ubm/epub.1845 [DOI] 510831249 [GVK] hdl:10419/31040 [Handle] |
Source: |
Persistent link: https://www.econbiz.de/10010266167
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