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Document Details :

Title: Testing for Concordance Ordering
Author(s): CEBRIAN, A.C. , DENUIT, M. , SCAILLET, O.
Journal: ASTIN Bulletin
Volume: 34    Issue: 1   Date: May 2004   
Pages: 151-173
DOI: 10.2143/AST.34.1.504960

Abstract :
We propose inference tools to analyse the concordance (or correlation) order of random vectors. The analysis in the bivariate case relies on tests for upper and lower quadrant dominance of the true distribution by a parametric or semiparametric model, i.e. for a parametric or semiparametric model to give a probability that two variables are simultaneously small or large at least as great as it would be were they left unspecified. Tests for its generalisation in higher dimensions, namely joint lower and upper orthant dominance, are also analysed. The parametric and semiparametric settings are based on the copula representation for multivariate distribution, which allows for disentangling behaviour of margins and dependence structure. A distance test and an intersection-union test for inequality constraints are developed depending on the definition of null and alternative hypotheses. An empirical illustration is given for US insurance claim data.