Abstract

The challenges associated with poverty measurement using a cardinal variable have received much attention over the past four decades, but there is a dearth of literature on how to meaningfully assess poverty with an ordinal variable. This article proposes a class of simple, intuitive, and policy-relevant poverty measures for ordinal variables. The measures are sensitive to the depth of deprivations, unlike the headcount ratio. Moreover, under appropriate restrictions, the measures ensure that priority is given to the poorest among the poor when targeting, monitoring, and evaluating poverty alleviation programs. To assess the robustness of poverty comparisons to alternative choices of parameters, the article develops various stochastic dominance tests (some of which are novel contributions to the stochastic dominance literature). The empirical illustration documenting changes in sanitation deprivation in Bangladesh showcases the measures’ ability to identify instances in which overall sanitation deprivation improved while leaving the poorest behind.

中文翻译：

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用有序变量评估剥夺：孟加拉国卫生剥夺的理论与应用

摘要

在过去的 40 年中，与使用基数变量衡量贫困相关的挑战受到了很多关注，但关于如何使用有序变量有意义地评估贫困的文献却很少。本文针对序数变量提出了一类简单、直观且与政策相关的贫困测度。与员工人数比率不同，这些措施对剥夺的深度很敏感。此外，在适当的限制下，这些措施确保在瞄准、监测和评估扶贫项目时，优先考虑贫困人口中的最贫困人口。为了评估贫困比较与其他参数选择的稳健性，本文开发了各种随机优势测试（其中一些是对随机优势文献的新贡献）。