Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/308604 
Year of Publication: 
2022
Citation: 
[Journal:] The Journal of Economic Inequality [ISSN:] 1573-8701 [Volume:] 20 [Issue:] 3 [Publisher:] Springer US [Year:] 2022 [Pages:] 727-748
Publisher: 
Springer US
Abstract: 
Abstract We propose an extension of the univariate Lorenz curve and of the Gini coefficient to the multivariate case, i.e., to simultaneously measure inequality in more than one variable. Our extensions are based on copulas and measure inequality stemming from inequality in each single variable as well as inequality stemming from the dependence structure of the variables. We derive simple nonparametric estimators for both instruments and exemplary apply them to data of individual income and wealth for various countries.
Subjects: 
Copula
Gini coefficient
Inequality
Multidimensional inequality
Joint inequality of income and wealth
Lorenz curve
Dependence of income and wealth
Persistent Identifier of the first edition: 
Creative Commons License: 
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Document Type: 
Article
Document Version: 
Published Version
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