ABSTRACT

A looming question for U.S. social policy is whether the over 50-year old federal poverty measure paints an accurate picture of the poor in America today. A panel of experts from the National Academy of Sciences (NAS), commissioned by Congress to address the key shortcomings of the federal measure, proposed an alternative poverty measure in the early 1990s that laid the groundwork for the Supplemental Poverty Measure adopted in 2010. However, while, internationally, poverty scholars have argued that poverty is more aptly understood as a constellation of deprivations – a multi-dimensional concept, U.S. poverty measurement continues to focus on economic deprivation. Amartya Sen’s groundbreaking capability approach that focuses on individuals’ capacities provides the framework for the author-created multi-dimensional poverty index encompassing three dimensions Sen considers intrinsically valuable capabilities: education, health, and living standard. Drawing on publically available secondary data, this study adopts a comparative framework to examine national-level racial differences in profiles of poverty, pre-and post-the Great Recession (2005–2010), based on the federal poverty measure, the NAS measure, and the proposed multi-dimensional measure. This multi-dimensional perspective thus offers insights into the type of capability disadvantages contributing to poverty among the citizenry by race.

摘要

美国社会政策面临的一个迫在眉睫的问题是，已有 50 多年历史的联邦贫困衡量标准是否准确地描绘了当今美国的贫困状况。美国国家科学院 (NAS) 的一个专家小组受国会委托解决联邦措施的主要缺陷，在 1990 年代初期提出了一项替代贫困措施，为 2010 年通过的补充贫困措施奠定了基础。然而，而在国际上，贫困学者认为贫困更恰当地被理解为剥夺的星座——一个多维的概念，美国贫困测量继续关注经济剥夺。Amartya Sen 以个人能力为重点的开创性能力方法为作者创建的多维贫困指数提供了框架，该指数包含 Sen 认为具有内在价值的三个维度：教育、健康和生活水平。本研究利用公开可用的二手数据，采用一个比较框架，根据联邦贫困衡量标准、NAS 衡量标准、大萧条前后（2005-2010 年）的贫困状况，检查国家层面的种族差异。以及提出的多维度量。因此，这种多维视角提供了对导致不同种族公民贫困的能力劣势类型的洞察。本研究利用公开可用的二手数据，采用一个比较框架，根据联邦贫困衡量标准、NAS 衡量标准、大萧条前后（2005-2010 年）的贫困状况，检查国家层面的种族差异。以及提出的多维度量。因此，这种多维视角提供了对导致不同种族公民贫困的能力劣势类型的洞察。本研究利用公开可用的二手数据，采用一个比较框架，根据联邦贫困衡量标准、NAS 衡量标准、大萧条前后（2005-2010 年）的贫困状况，检查国家层面的种族差异。以及提出的多维度量。因此，这种多维视角提供了对导致不同种族公民贫困的能力劣势类型的洞察。