An Exhaustive Coefficient Of Rank Correlation
AbstractRank 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.
Download InfoIf you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
Bibliographic InfoPaper provided by Università della Calabria, Dipartimento di Economia, Statistica e Finanza (Ex Dipartimento di Economia e Statistica) in its series Working Papers with number 201111.
Length: 29 pages
Date of creation: Oct 2011
Date of revision:
Contact details of provider:
Postal: Università della Calabria, Dipartimento di Economia, Statistica e Finanza, Ponte Pietro Bucci, Cubo 0/C, I-87036 Arcavacata di Rende, CS, Italy
Phone: +39 0984 492413
Fax: +39 0984 492421
Web page: http://www.unical.it/portale/strutture/dipartimenti_240/disesf/
More information through EDIRC
Ordinal data; Nonparametric agreement; Economic applications;
Find related papers by JEL classification:
- C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
- C18 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Methodolical Issues: General
- A12 - General Economics and Teaching - - General Economics - - - Relation of Economics to Other Disciplines
This paper has been announced in the following NEP Reports:
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Russell Davidson & Jean-Yves Duclos, 2000.
"Statistical Inference for Stochastic Dominance and for the Measurement of Poverty and Inequality,"
Econometric Society, vol. 68(6), pages 1435-1464, November.
- Davidson, R. & Duclos, J.-Y., 1998. "Statistical Inference for Stochastic Dominance and for the Measurement of Poverty and Inequality," G.R.E.Q.A.M. 98a14, Universite Aix-Marseille III.
- Davidson, Russell & Duclos, Jean-Yves, 1998. "Statistical Inference for Stochastic Dominance and for the Measurement of Poverty and Inequality," Cahiers de recherche 9805, Université Laval - Département d'économique.
- Christophe Croux & Catherine Dehon, 2010.
"Influence functions of the Spearman and Kendall correlation measures,"
Statistical Methods and Applications,
Springer, vol. 19(4), pages 497-515, November.
- Croux, C. & Dehon, C., 2010. "Influence Functions of the Spearman and Kendall Correlation Measures," Discussion Paper 2010-40, Tilburg University, Center for Economic Research.
- Korhonen, Pekka & Siljamaki, Aapo, 1998. "Ordinal principal component analysis theory and an application," Computational Statistics & Data Analysis, Elsevier, vol. 26(4), pages 411-424, February.
- Vito Peragine, 2004. "Ranking Income Distributions According to Equality of Opportunity," Journal of Economic Inequality, Springer, vol. 2(1), pages 11-30, April.
- Michael Gapen & Dale Gray & Cheng Hoon Lim & Yingbin Xiao, 2008. "Measuring and Analyzing Sovereign Risk with Contingent Claims," IMF Staff Papers, Palgrave Macmillan, vol. 55(1), pages 109-148, April.
- Maurizio Brizzi, 1992. "Misure di variabilità, concentrazione e dissomiglianza come sintesi di rapporti," Quaderni di Dipartimento 2, Department of Statistics, University of Bologna.
- Roll, Richard, 1978. "Ambiguity when Performance is Measured by the Securities Market Line," Journal of Finance, American Finance Association, vol. 33(4), pages 1051-69, September.
- William Horrace & Joseph Marchand & Timothy Smeeding, 2008.
"Ranking inequality: Applications of multivariate subset selection,"
Journal of Economic Inequality,
Springer, vol. 6(1), pages 5-32, March.
- William C. Horrace & Joseph T. Marchand & Timothy M. Smeeding, 2006. "Ranking Inequality: Applications of Multivariate Subset Selection," Working Papers 21, ECINEQ, Society for the Study of Economic Inequality.
- William C. Horrace & Joseph T. Marchand & Timothy M. Smeeding, 2005. "Ranking Inequality: Applications of Multivariate Subset Selection," Center for Policy Research Working Papers 70, Center for Policy Research, Maxwell School, Syracuse University.
- Shieh, Grace S., 1998. "A weighted Kendall's tau statistic," Statistics & Probability Letters, Elsevier, vol. 39(1), pages 17-24, July.
- Robert J. Hill, 1999. "Comparing Price Levels across Countries Using Minimum-Spanning Trees," The Review of Economics and Statistics, MIT Press, vol. 81(1), pages 135-142, February.
- Daniele Checchi, 1997. "Education and Intergenerational Mobility in Occupations," Vierteljahrshefte zur Wirtschaftsforschung / Quarterly Journal of Economic Research, DIW Berlin, German Institute for Economic Research, vol. 66(1), pages 136-144.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Giovanni Dodero).
If references are entirely missing, you can add them using this form.