A New Goodness of Fit Measure Based on Income Inequality Curves

S. Mirzaei, Payam Noor
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Abstract

This paper uses inequality-measurement techniques to assess goodness of fit in income distribution models. It exposes the shortcomings of the use of conventional goodness of fit criteria in face of the big income data and proposes a new set of metrics, based on income inequality curves. In this note, we mentioned that the distance between theoretical and empirical inequality curves can be considered as a goodness of fit criterion. We demonstrate certain advantages of this measure over the other general goodness of fit criteria. Unlike other goodness of fit measures, this criterion is bounded. It is 0 in minimum difference and 1 in maximum distance. Furthermore, there is a consistency between this new goodness of fit measure and the other conventional criteria. A simulation study based on fitted distribution to real income data is performed in order to investigate some statistical properties of the new goodness of fit measure. An empirical study and comparisons are also provided.
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基于收入不平等曲线的拟合优度新测度
本文使用不平等测量技术来评估收入分配模型的拟合优度。它暴露了在面对大收入数据时使用传统拟合优度标准的缺点,并提出了一套基于收入不平等曲线的新指标。在这篇注释中,我们提到理论和经验不等式曲线之间的距离可以被视为拟合优度标准。我们证明了该度量相对于其他一般拟合优度标准的某些优势。与其他拟合优度度量不同,该准则是有界的。最小差值为0,最大距离为1。此外,这种新的拟合优度度量与其他传统标准之间存在一致性。为了研究新的拟合优度测度的一些统计性质,对实际收入数据进行了基于拟合分布的模拟研究。还提供了实证研究和比较。
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来源期刊
CiteScore
0.50
自引率
0.00%
发文量
5
期刊介绍: The Journal of Modern Applied Statistical Methods is an independent, peer-reviewed, open access journal designed to provide an outlet for the scholarly works of applied nonparametric or parametric statisticians, data analysts, researchers, classical or modern psychometricians, and quantitative or qualitative methodologists/evaluators.
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