AN EXHAUSTIVE COEFFICIENT OF RANK CORRELATION
Agostino Tarsitano () and
Rosetta Lombardo ()
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Rosetta Lombardo: Dipartimento di Economia e Statistica, Università della Calabria
No 201111, Working Papers from Università della Calabria, Dipartimento di Economia, Statistica e Finanza "Giovanni Anania" - DESF
Abstract:
Rank association is a fundamental tool for expressing dependence in cases in which data are arranged in order. Measures of rank correlation have been accumulated in several contexts for more than a century and we were able to cite more than thirty of these coefficients, from simple ones to relatively complicated definitions invoking one or more systems of weights. However, only a few of these can actually be considered to be admissible substitutes for Pearson’s correlation. The main drawback with the vast majority of coefficients is their “resistance-tochange” which appears to be of limited value for the purposes of rank comparisons that are intrinsically robust. In this article, a new nonparametric correlation coefficient is defined that is based on the principle of maximization of a ratio of two ranks. In comparing it with existing rank correlations, it was found to have extremely high sensitivity to permutation patterns. We have illustrated the potential improvement that our index can provide in economic contexts by comparing published results with those obtained through the use of this new index. The success that we have had suggests that our index may have important applications wherever the discriminatory power of the rank correlation coefficient should be particularly strong.
Keywords: Ordinal data; Nonparametric agreement; Economic applications (search for similar items in EconPapers)
JEL-codes: A12 C14 C18 (search for similar items in EconPapers)
Pages: 29 pages
Date: 2011-10
New Economics Papers: this item is included in nep-ecm
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http://www.ecostat.unical.it/RePEc/WorkingPapers/WP11_2011.pdf First version, 2011-10 (application/pdf)
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Persistent link: https://EconPapers.repec.org/RePEc:clb:wpaper:201111
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