Counting poverty orderings and deprivation curves
Counting poverty orderings and deprivation curves
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计算贫困顺序和剥夺曲线
DOI：
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发表时间：
2009
期刊：
影响因子：
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通讯作者：
Casilda Lasso de la Vega
中科院分区：
文献类型：
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作者：
Casilda Lasso de la Vega
可用于衡量贫穷能力或层面的大多数数据要么是顺序数据，要么是分类数据。然而，用于评估多维贫困的大多数指数仅在基本变量中表现良好。Atkinson（2003）引入的计数方法专注于每个人被剥夺的维度数量，是一种适当的程序，可以很好地处理顺序和分类变量。考虑到这一框架，提出了一种确定穷人和若干贫穷指数的方法。但是，执行这一方法需要选择被认定为贫穷所需的最低限度的贫困情况。这一界限增加了贫困比较的随意性。本文的目的是双重的。首先，我们探索了使我们能够将识别方法描述为在多维环境中识别穷人的最合适程序的属性。然后，为了在计数框架下保证贫困排名的一致性，研究了优势条件。我们的条件基于简单的图形设备，这些设备提供了一种工具，用于检查贫困排名对识别截止值变化的稳健性，并用于检查适用于有序和分类数据的广泛多维贫困指数中的一致顺序。
Most of the data available for measuring capabilities or dimensions of poverty is either ordinal or categorical. However, the majority of the indices introduced for the assessment of multidimensional poverty behave well only with cardinal variables. The counting approach introduced by Atkinson (2003) concentrates on the number of dimensions in which each person is deprived, and is an appropriate procedure that deals well with ordinal and categorical variables. A method to identify the poor and a number of poverty indices has been proposed taking this framework into account. However, the implementation of this methodology involves the choice of a minimum number of deprivations required in order to be identified as poor. This cut-off adds arbitrariness to poverty comparisons. The aim of this paper is two-fold. Firstly, we explore properties which allow us to characterize the identification method as the most appropriate procedure to identify the poor in a multidimensional setting. Then the paper examines dominance conditions in order to guarantee unanimous poverty rankings in a counting framework. Our conditions are based on simple graphical devices that provide a tool for checking the robustness of poverty rankings to changes in the identification cut-off, and also for checking unanimous orderings in a wide set of multidimensional poverty indices that suit ordinal and categorical data.