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 every single variable as well as inequality stemming from the dependence structure of the variables. We derive simple nonparametric estimators for both instruments and apply them exemplary to data of individual income and wealth for various countries.
翻译:我们提议将单象体Lorenz曲线和基尼系数扩展至多变量案例,即同时衡量一个以上变量的不平等情况,我们的扩展是基于每个变量的共生数,衡量每个变量的不平等以及变量依赖性结构产生的不平等。我们为这两个工具获取简单的非对称估量器,并将其用于不同国家的个人收入和财富数据中堪称典范。