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A suggestion for a multivariate concordance coefficient

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  • Silvia Terzi
  • Luca Moroni

Abstract

In the present paper we will introduce a coecient of multivariate association i.e. association in a d-variate vector of observations x = (x1; : : : ; xd), where d 2 and where each xj is itself a vector of n observations. We order the observations, divide them in slices and count how many times one observation in the r-th slice of any of the d distributions also belongs to the r-th slice of any of the others. The greater the number of overlaps between the units belonging to corresponding slices, the greater the concordance between the d distributions. This is the simple and intuitive idea our multivariate association coecient stems from. It is in fact a multidimensional concordance coecient since it assumes comonotonicity for all variables.

Suggested Citation

  • Silvia Terzi & Luca Moroni, 2014. "A suggestion for a multivariate concordance coefficient," Departmental Working Papers of Economics - University 'Roma Tre' 0189, Department of Economics - University Roma Tre.
    • Handle: RePEc:rtr:wpaper:0189
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    File URL: http://dipeco.uniroma3.it/db/docs/wp%20189.pdf
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    References listed on IDEAS

    as
    1. Koen DECANCQ, 2010. "Copula-based orderings of multivariate dependence," Working Papers of Department of Economics, Leuven ces10.08, KU Leuven, Faculty of Economics and Business (FEB), Department of Economics, Leuven.
    2. Marco Scarsini, 1984. "On measures of concordance," Post-Print hal-00542380, HAL.
    3. M. Taylor, 2007. "Multivariate measures of concordance," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 59(4), pages 789-806, December.
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    More about this item

    Keywords

    Copula; Concordance; Local concordance; Measures of multivariate association;
    All these keywords.

    JEL classification:

    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General

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