We address the problem of ranking distributions of attributes in terms of poverty, when the attributes are represented by binary variables. To accomplish this task, we identify a suitable notion of “multidimensional poverty line” and characterize axiomatically the Head‐Count and the Attribute‐Gap poverty rankings, which are the natural counterparts of the most widely used income poverty indices. Finally, we apply our methodology and compare our empirical results with those obtained with some other well‐known poverty measures.

中文翻译：

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关于二元属性的多维贫困等级

当属性由二进制变量表示时，我们解决了按贫困程度对属性的分布进行排序的问题。为了完成此任务，我们确定了“多维贫困线”的合适概念，并公然地表征了“头数”和“属性差距”贫困排名，这是最广泛使用的收入贫困指数的自然对应。最后，我们运用我们的方法，并将我们的经验结果与通过其他一些著名的贫困测度获得的结果进行比较。