In this paper I investigate the problem of de
ning a multivariate dependence ordering. First, I provide a characterization of the concordance dependence ordering between multivariate random vectors with fi
xed margins. Central to the characterization is a multivariate generalization of a well-known bivariate elementary dependence increasing rearrangement. Second, to order multivariate random vectors with non fxed margins, I impose a scale invariance principle which leads to a copula-based concordance dependence ordering. Finally, a wide family of copula-based measures of dependence is characterized to which Spearman's rank correlation coefficient belongs.
Keywords: copula, concordance ordering, dependence measures, dependence order-
ings, multivariate stochastic dominance, supermodular ordering.
JEL Classi
cation: C14
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