综合贫困指数可分解性差距的统计估计
Statistical estimation of gap of decomposability of the general poverty index
摘要：
由于可分解性在福利分析中具有很强的实用性，大多数研究者和使用者都青睐于可分解的贫困指数，如Foster-Greer-Thorbeck贫困指数。这可能会导致忽视如此重要的加权指标，如Kakwani和Shorrocks的福利分析中有有趣的其他属性。针对这一问题，本文利用广义贫困指数（GPI），根据泛函经验过程理论，给出了一个新的渐近表示定理，并对一大类指数的可分解性缺口进行了统计估计。然后，结果使目标群体的独立处理和下一个具有显著置信区间的全球报告成为可能。数据驱动的例子给出了真实的数据。
英文摘要：
For the decomposability property is very a practical one in Welfare analysis, most researchers and users favor decomposable poverty indices such as the Foster-Greer-Thorbeck poverty index. This may lead to neglect the so important weighted indices like the Kakwani and Shorrocks ones which have interesting other properties in Welfare analysis. To face up to this problem, we give in this paper, statistical estimations of the gap of decomposability of a large class of such indices using the General Poverty Indice (GPI) and of a new asymptotic representation Theorem for it, in terms of functional empirical processes theory. The results then enable independent handling of targeted groups and next global reporting with significant confidence intervals. Data-driven examples are given with real data.
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