ESTIMATING THE GINI INDEX FOR HEAVY-TAILED INCOME DISTRIBUTIONS

被引：0
|
作者：
Bari, Amina [1 ]
Rassoul, Abdelaziz [2 ]
Rouis, Hamid Ould [3 ]
机构：
[1] Ctr Univ Tindouf, Tindouf, Algeria
[2] Natl Higher Sch Hydraul, Blida, Algeria
[3] Univ Blida 1, LRDSI Lab, Blida, Algeria
来源：
SOUTH AFRICAN STATISTICAL JOURNAL | 2021年 / 55卷 / 01期
关键词：
Extreme quantile; Gini index; Heavy-tailed incomes; Income inequality; SAMPLE FRACTION; REGULAR VARIATION; PARAMETERS; INFERENCE; QUANTILES; VARIANCE;
D O I：
10.37920/sasj.2021.55.1.2
中图分类号：
O21 [概率论与数理统计]; C8 [统计学];
学科分类号：
020208 ; 070103 ; 0714 ;
摘要：
In the present paper, we define and study one of the most popular indices which measures the inequality of capital incomes, known as the Gini index. We construct a semiparametric estimator for the Gini index in case of heavy-tailed income distributions and we establish its asymptotic distribution and derive bounds of confidence. We explore the performance of the confidence bounds in a simulation study and draw conclusions about capital incomes in some income distributions.
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页码：15 / 28
页数：14
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