The dual approach for measuring multidimensional deprivation: Theory and empirical evidence
提出基于双重社会评价函数的二元剥夺变量多维分布排序与度量方法，利用EU-SILC数据证明该方法比标准截断法更稳健。
This paper is concerned with the problem of ranking and quantifying the extent of deprivation in multidimensional distributions of dichotomous deprivation variables. To this end, we introduce a family of measures of deprivation justified on the basis of dual social evaluation functions. Two alternative criteria of second-degree deprivation count distribution dominance are shown to divide the proposed family of deprivation measures into two separate subfamilies, which can be justified by a combination of correlation increasing and count neutral rearrangements. Based on EU-SILC data, we show that application of the proposed measures might lead to conclusions that differ from those attained by standard cut-off measures, and that results based on cut-off measures are more sensitive to the choice of specific measure.