单调弹性Lorenz曲线的一个性质及其在税收数据不等式研究中的应用

IF 0.7 4区数学 Q4 OPERATIONS RESEARCH & MANAGEMENT SCIENCE

Sort-Statistics and Operations Research Transactions Pub Date : 2017-01-01 DOI:10.2436/20.8080.02.50

M. A. S. Díaz, Ángel Berihuete Macías, Carmen Dolores Ramos González, H. M. R. Romero

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引用次数: 1

摘要

洛伦兹曲线是用于描述和比较收入分配不平等的最广泛使用的图形工具。在本文中，我们证明了这条曲线的弹性是收入分配截断对不平等的影响的一个指标。作为一种应用，我们认为纳税申报单相当于从下面截断一个假设的收入分配。然后，我们用从一般家庭调查中获得的收入分布来取代这种假设分布，并使用双洛伦兹曲线来预测这种影响。

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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On a property of Lorenz curves with monotone elasticity and its application to the study of inequality by using tax data

The Lorenz curve is the most widely used graphical tool for describing and comparing inequality of income distributions. In this paper, we show that the elasticity of this curve is an indicator of the effect, in terms of inequality, of a truncation of the income distribution. As an application, we consider tax returns as equivalent to the truncation from below of a hypothetical income distribution. Then, we replace this hypothetical distribution by the income distribution obtained from a general household survey and use the dual Lorenz curve to anticipate this effect.

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来源期刊

Sort-Statistics and Operations Research Transactions 管理科学-统计学与概率论

CiteScore

3.10

自引率

0.00%

发文量

审稿时长

>12 weeks

期刊介绍： SORT (Statistics and Operations Research Transactions) —formerly Qüestiió— is an international journal launched in 2003. It is published twice-yearly, in English, by the Statistical Institute of Catalonia (Idescat). The journal is co-edited by the Universitat Politècnica de Catalunya, Universitat de Barcelona, Universitat Autonòma de Barcelona, Universitat de Girona, Universitat Pompeu Fabra i Universitat de Lleida, with the co-operation of the Spanish Section of the International Biometric Society and the Catalan Statistical Society. SORT promotes the publication of original articles of a methodological or applied nature or motivated by an applied problem in statistics, operations research, official statistics or biometrics as well as book reviews. We encourage authors to include an example of a real data set in their manuscripts.