{"title":"Pareto's Limits: Improving Inequality Estimates in America, 1917 to 1965","authors":"Vincent Geloso, Alexis Akira Toda","doi":"arxiv-2408.16861","DOIUrl":null,"url":null,"abstract":"American income inequality, generally estimated with tax data, in the 20th\ncentury is widely recognized to have followed a U-curve, though debates persist\nover the extent of this curve, specifically regarding how high the peaks are\nand how deep the trough is. These debates focus on assumptions about defining\nincome and handling deductions. However, the choice of interpolation methods\nfor using tax authorities' tabular data to estimate the income of the richest\ncentiles -- especially when no micro-files are available -- has not been\ndiscussed. This is crucial because tabular data were consistently used from\n1917 to 1965. In this paper, we show that there is an alternative to the\nstandard method of Pareto Interpolation (PI). We demonstrate that this\nalternative -- Maximum Entropy (ME) -- provides more accurate results and leads\nto significant revisions in the shape of the U-curve of income inequality.","PeriodicalId":501273,"journal":{"name":"arXiv - ECON - General Economics","volume":"204 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-08-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"arXiv - ECON - General Economics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/arxiv-2408.16861","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
American income inequality, generally estimated with tax data, in the 20th
century is widely recognized to have followed a U-curve, though debates persist
over the extent of this curve, specifically regarding how high the peaks are
and how deep the trough is. These debates focus on assumptions about defining
income and handling deductions. However, the choice of interpolation methods
for using tax authorities' tabular data to estimate the income of the richest
centiles -- especially when no micro-files are available -- has not been
discussed. This is crucial because tabular data were consistently used from
1917 to 1965. In this paper, we show that there is an alternative to the
standard method of Pareto Interpolation (PI). We demonstrate that this
alternative -- Maximum Entropy (ME) -- provides more accurate results and leads
to significant revisions in the shape of the U-curve of income inequality.
人们普遍认为,20 世纪美国的收入不平等(一般通过税收数据估算)呈现出一条 U 型曲线,但关于这条曲线的范围,特别是关于峰值有多高和谷值有多深的争论一直存在。这些争论主要集中在对收入的定义和扣除额的处理上。然而,在使用税务机关的表格数据估算最富裕阶层的收入时,尤其是在没有微观档案的情况下,如何选择内插法还没有得到讨论。这一点至关重要,因为从 1917 年到 1965 年,我们一直使用表格数据。在本文中,我们展示了帕累托内插法(PI)的标准方法之外的另一种方法。我们证明,这种替代方法--最大熵(ME)--能提供更准确的结果,并能显著修正收入不平等的 U 曲线形状。