广义lorenz曲线的渐近无分布统计检验:另一种方法

Kuan Xu
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引用次数: 19

摘要

广义洛伦兹曲线(GL)与洛伦兹曲线的不同之处在于前者是后者的一个缩放版本。GL曲线表示根据人口的累积百分比计算出的平均收入与相应的累积百分比之间的关系。对于一个经济体或多个经济体在同一时间点的GL曲线排名,GL主导地位是一个有用的标准。相对于占主导地位的GL曲线,占主导地位的GL曲线表明,人口的总收入更高,而且分配更均匀。因此,在某种社会意义上,它显然是更可取的。虽然可靠的统计检验对于从样本GL曲线估计中对GL优势进行统计推断是必不可少的,但缺乏合适的GL优势联合检验程序是收入分配文献中尚未解决的问题。本文旨在解决这一问题,并提供了一个说明性的实证例子来说明如何将该测试程序应用于实证研究。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Asymptotically distribution-free statistical test for generalized lorenz curves: An alternative approach

A generalized Lorenz (GL) curve differs from a Lorenz curve in that the former is a rescaled version of the latter. A GL curve represents the relationship between the average income computed from a cumulative percentage of the population and the corresponding cumulative percentage. GL dominance is a useful criterion for ranking GL curves either for an economy over time or for a number of economies at one point in time. Relative to a dominated GL curve, a dominating GL curve indicates both that total income for the population is higher and that it is more equally distributed. Hence, it is obviously more desirable in a certain social sense. While sound statistical tests are essential for making statistical inference about GL dominance from sample GL curve estimates, the lack of a suitable joint test procedure for GL dominance is an unsolved problem in income distribution literature. This paper aims at solving this problem and provides an illustrative empirical example to show how to apply this test procedure in empirical research.

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