Decomposing the Difference Between Well-Being Inequality and Income Inequality: Method and Application

M. Ledić, Ivica Rubil
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引用次数: 4

Abstract

The authors study the difference between multidimensional well-being inequality and income inequality and propose a method to decompose the difference between the Gini coefficients of income and equivalent income (EI), a multidimensional well-being measure that respects individual preferences towards what constitutes a good life. The authors propose a method to decompose the inequality difference into two parts: the vertical and reranking effects. The vertical effect arises from the correlation between income and non-income dimensions, and between income and preferences. The reranking effect arises from the fact that some persons occupy a different position in the EI distribution compared to the income distribution. The authors also propose a detailed decomposition method based on the Shapley value to decompose each of the two effects by non-income dimensions. The authors apply the decompositions using data for 27 countries, considering five non-income dimensions: unemployment, health, housing, crime and environment. The results show that inequality is much higher for EI that the reranking effect accounts for a large part of the inequality difference, and that health is the non-income dimension contributing most to both effects.
分解贫富差距的方法与应用
作者研究了多维幸福不平等和收入不平等之间的差异,并提出了一种分解收入的基尼系数和等效收入(EI)之间差异的方法。EI是一种多维幸福衡量标准,尊重个人对美好生活的偏好。本文提出了一种将不平等差异分解为垂直效应和重排序效应两部分的方法。垂直效应源于收入与非收入维度之间以及收入与偏好之间的相关性。重新排序效应是由于一些人在EI分配中所处的位置与收入分配中所处的位置不同。作者还提出了一种基于Shapley值的详细分解方法,通过非收入维度来分解这两种效应。作者使用27个国家的数据进行了分解,考虑了五个非收入方面:失业、健康、住房、犯罪和环境。结果表明,EI的不平等程度要高得多,重新排名效应占不平等差异的很大一部分,而健康是对这两种影响贡献最大的非收入维度。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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