Given many popular functional forms for the Lorenz curve do not have a closed-form expression for the Gini index and no study has utilized the observed Gini index to estimate parameter(s) associated with the corresponding parametric functional form, a simple method for estimating the Lorenz curve is introduced. It utilizes 3 indicators, namely, the Gini index and the income shares of the bottom and the top in order to calculate the values of parameters associated with the specified functional form which has a closed-form expression for the Gini index. No error minimization technique is required in order to estimate the Lorenz curve. The data on the Gini index and the income shares of 4 countries that have different level of income inequality, economic, sociological, and regional backgrounds from the United Nations University-World Income Inequality Database are used to illustrate how the simple method works. The overall results indicate that the estimated Lorenz curves fit the actual observations practically well. This simple method could be useful in the situation where the availability of data on income distribution is low. However, if more data on income distribution are available, this study shows that the specified functional form could be used to directly estimate the Lorenz curve. Moreover, the estimated values of the Gini index calculated based on the specified functional form are virtually identical to their actual observations.
翻译:鉴于Lorenz曲线的许多流行功能表没有基尼指数的封闭式表达式表达式,而且没有研究使用观察到的吉尼指数来估计与相应的参数功能表有关的参数,因此采用了一种简单的方法来估计洛伦斯曲线,采用了3个指标,即基尼指数以及底部和顶部的收入份额,以便计算与特定功能表有关的参数值,该功能表对吉尼指数具有封闭式表达式。在估算洛伦斯曲线时,不需要使用尽可能减少错误的方法。关于吉尼指数和四个收入不平等程度、经济、社会学和区域背景不同的国家的收入份额的数据,用来说明该简单方法是如何运作的。总体结果显示,估计的洛伦斯曲线与实际观测结果基本吻合。这一简单方法在收入分配数据少的情况下可能有用。但是,如果有更多关于收入分布的数据,则需要尽量减少错误的方法。这项研究表明,在直接估计Lorenz指数的实际观测结果时,可以使用特定功能表。此外,根据实际的数值计算,根据Lorenz的精确值计算,估计是完全相同的。