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A suggestion for a multivariate concordance coefficient

Author

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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

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    1. Nikolay Nenovsky & S. Statev, 2006. "Introduction," Post-Print halshs-00260898, HAL.
    2. Koen DECANCQ, 2010. "Copula-based orderings of multivariate dependence," Working Papers Department of Economics ces10.08, KU Leuven, Faculty of Economics and Business, Department of Economics.
    3. repec:sae:ecolab:v:16:y:2006:i:2:p:1-2 is not listed on IDEAS
    4. 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.
    Full references (including those not matched with items on IDEAS)

    More about this item

    Keywords

    Copula; Concordance; Local concordance; Measures of multivariate association;

    JEL classification:

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

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