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Analytic Expressions for Multivariate Lorenz Surfaces

  • Barry C. Arnold
  • José María Sarabia
Article
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Abstract

The Lorenz curve is a much used instrument in economic analysis. It is typically used for measuring inequality and concentration. In insurance, it is used to compare the riskiness of portfolios, to order reinsurance contracts and to summarize relativity scores (see Frees et al. J. Am. Statist. Assoc.106, 1085–1098, 2011; J. Risk Insur.81, 335–366, 2014 and Samanthi et al. Insur. Math. Econ.68, 84–91, 2016). It is sometimes called a concentration curve and, with this designation, it attracted the attention of Mahalanobis (Econometrica28, 335–351, 1960) in his well known paper on fractile graphical analysis. The extension of the Lorenz curve to higher dimensions is not a simple task. There are three proposed definitions for a suitable Lorenz surface, proposed by Taguchi (Ann. Inst. Statist. Math.24, 355–382, 1972a, 599–619, 1972b; Comput. Stat. Data Anal.6, 307–334, 1988) and Lunetta (1972), Arnold (1987, 2015) and Koshevoy and Mosler (J. Am. Statist. Assoc.91, 873–882, 1996). In this paper, using the definition proposed by Arnold (1987, 2015), we obtain analytic expressions for many multivariate Lorenz surfaces. We consider two general classes of models. The first is based on mixtures of Lorenz surfaces and the second one is based on some simple classes of bivariate mixture distributions.

Keywords

Multivariate distributions Mixture distributions Laplace transform Gini index. 

AMS (2000) subject classification

Primary 62E10; Secondary 91B82 

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Notes

Acknowledgements

The second author gratefully acknowledge financial support from the Programa Estatal de Fomento de la Investigación Científica y Técnica de Excelencia, Spanish Ministry of Economy and Competitiveness, project ECO2016-76203-C2-1-P. The authors thank two anonymous reviewers for helpful and detailed comments and suggestions that have improved the paper.

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Copyright information

© Indian Statistical Institute 2018

Authors and Affiliations

  1. 1.Department of StatisticsUniversity of CaliforniaRiversideUSA
  2. 2.Department of EconomicsUniversity of CantabriaSantanderSpain

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