Conditions for the Asymptotic Semiparametric Efficiency of an Omnibus Estimator of Dependence Parameters in Copula Models

Christian Genest and Bas J. M. Werker
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Christian Genest: Université Laval, Département de mathématiques et de statistique
Bas J. M. Werker: Tilburg University, Finance Group

A chapter in Distributions With Given Marginals and Statistical Modelling, 2002, pp 103-112 from Springer

Abstract: Abstract Oakes (1994) described in broad terms an omnibus semiparametric procedure for estimating the dependence parameter in a copula model when marginal distributions are treated as (infinite-dimensional) nuisance parameters. The resulting estimator was subsequently shown to be consistent and normally distributed asymptotically (Genest et al. 1995, Shih and Louis 1995). Conditions under which it is also semiparametrically efficient in large samples are given. While these requirements are met for the normal copula model (Klaassen and Wellner 1997), it is argued that this is an exception rather than the norm.

Keywords: Copula model; Efficient influence function; Efficient score function; Semiparametric estimation; Sturm-Liouville differential equations; 62G05; 62G20; 62H99 (search for similar items in EconPapers)
Date: 2002
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-94-017-0061-0_12

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DOI: 10.1007/978-94-017-0061-0_12

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