Bitte verwenden Sie diesen Link, um diese Publikation zu zitieren, oder auf sie als Internetquelle zu verweisen: https://hdl.handle.net/10419/308604 
Erscheinungsjahr: 
2022
Quellenangabe: 
[Journal:] The Journal of Economic Inequality [ISSN:] 1573-8701 [Volume:] 20 [Issue:] 3 [Publisher:] Springer US [Place:] New York, NY [Year:] 2022 [Pages:] 727-748
Verlag: 
Springer US, New York, NY
Zusammenfassung: 
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.
Schlagwörter: 
Copula
Gini coefficient
Inequality
Multidimensional inequality
Joint inequality of income and wealth
Lorenz curve
Dependence of income and wealth
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