تعميم چند متغيره منحني لورنز و ضريب جيني بر اساس مفصل

A multivariate extension of the Lorenz curve an‎d Gini coefficient based on copulas

آمار

Economic inequality, as one of the fundamental challenges of contemporary societies, refers to the unequal distribution of income an‎d wealth, an‎d has wide-ranging effects on economic growth, social justice, an‎d political stability. To measure it, the Lorenz curve an‎d the Gini coefficient are used as stan‎dard tools that measure univariate inequality. In this study, a multivariate generalization of these indicators is presented, which allows for the simultaneous measurement of inequality in variables such as income an‎d wealth. The proposed method is based on copulas theory an‎d considers not only the marginal inequality of each variable, but also the inequality resulting from the structure of the dependence between them. For this purpose, simple an‎d computable nonparametric estimators for the multivariate Lorenz curve an‎d the Gini coefficient are developed an‎d empirically applied to individual income an‎d wealth data in several countries. The findings show that considering multiple dimensions of inequality an‎d the interdependence between them provides a deeper an‎d more realistic picture of the level of economic inequality. In this study, we will examine the theoretical structure of the Lorenz curve an‎d the generalized Gini coefficient, an‎d use simulation to calculate an‎d interpret these measures.

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