Asymptotic Admissibility and Uniqueness of Efficient Estimates in Semiparametric Models

Helmut Strasser
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Helmut Strasser: University of Economics and Business Administration

Chapter 24 in Festschrift for Lucien Le Cam, 1997, pp 369-376 from Springer

Abstract: Abstract The concept of local asymptotic efficiency of estimators can be made precise in several ways. In semiparametric theory most authors are using local asymptotic minimaxity or asymptotic convolution theorems. We will show how Le Cam’s asymptotic admissibility theorem and Hájek’s asymptotic uniqueness result can be applied to semiparametric problems.

Keywords: Loss Function; Nuisance Parameter; Linear Process; Estimator Sequence; Semiparametric Model (search for similar items in EconPapers)
Date: 1997
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-1-4612-1880-7_24

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DOI: 10.1007/978-1-4612-1880-7_24

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