广义收入不平等指数

IF 1.7 3区 数学 Q1 STATISTICS & PROBABILITY
Ziqing Dong, Yves Tille, Giovanni Maria Giorgi, Alessio Guandalini
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引用次数: 0

摘要

本文提出了收入不平等指数的深度概括。提出了一个广义的收入不平等指数,该指数依赖于两个参数,并在同一框架内涉及大量的收入不平等指数。这两个参数控制了广义指数对不同收入分配水平的敏感性。对广义指数的深入研究,有助于理解低、中、高收入对各种收入不平等指数的影响,从而有助于同时选择多个指数,以便更好地分析最近几项研究所提倡的不平等。此外,给出了有限总体情况下广义指数的两种估计方法。提出了一种估计不等式指标的新方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Generalised Income Inequality Index

Generalised Income Inequality Index

This paper proposes a deep generalisation for income inequality indices. A generalised income inequality index that depends on two parameters and that involves a large set of income inequality indices in the same framework is proposed. The two parameters control the sensitivity of the generalised index to different levels of the income distribution. A thorough investigation of the generalised index paves the way for understanding the influence of the low, middle and high incomes on various income inequality indices and thereby facilitates the choice of multiple indices simultaneously for a better analysis of inequality as advocated by several recent studies. Moreover, two methods for estimating the generalised index in the case of finite populations are shown. A new method for estimating the inequality indices is proposed.

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来源期刊
International Statistical Review
International Statistical Review 数学-统计学与概率论
CiteScore
4.30
自引率
5.00%
发文量
52
审稿时长
>12 weeks
期刊介绍: International Statistical Review is the flagship journal of the International Statistical Institute (ISI) and of its family of Associations. It publishes papers of broad and general interest in statistics and probability. The term Review is to be interpreted broadly. The types of papers that are suitable for publication include (but are not limited to) the following: reviews/surveys of significant developments in theory, methodology, statistical computing and graphics, statistical education, and application areas; tutorials on important topics; expository papers on emerging areas of research or application; papers describing new developments and/or challenges in relevant areas; papers addressing foundational issues; papers on the history of statistics and probability; white papers on topics of importance to the profession or society; and historical assessment of seminal papers in the field and their impact.
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