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联合国西亚经济社会委员会-阿拉伯国家经修订的多维贫困指数的稳健性检验(英)-2021

# 阿拉伯国家 # 多维贫困指数 大小:2.78M | 页数:23 | 上架时间:2021-07-05 | 语言:英文

联合国西亚经济社会委员会-阿拉伯国家经修订的多维贫困指数的稳健性检验(英)-2021.pdf

联合国西亚经济社会委员会-阿拉伯国家经修订的多维贫困指数的稳健性检验(英)-2021.pdf

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类型: 专题

上传者: FF

撰写机构: 联合国西亚经济社会委员会

出版日期: 2021-07-02

摘要:

The construction of a multidimensional poverty index (MPI) involves crucial decisions: the choice and definition of indicators, deprivation cut-offs, weights and poverty cut-offs. Determining the values of these parameters affects the identification of the poor, the contributions of dimensions and indicators to MPI, and the raking of countries. These decisions involve normative choices (Alkire and Jahan, 2018), but also empirical and statistical considerations. It is critical to use uncertainty analysis and sensitivity analysis to set the parameter values in constructing MPI (Saisana and others, 2005). The present section sets out the various tools for examining the robustness properties of the revised Arab MPI and its partial indices of the headcount ratio and the poverty intensity, as well as the sensitivity of countries’ ordering when assumptions change. An ordering of entities 

(countries or population groups) is defined as robust when the order is unchanged as one of the parameter values changes. For regional policy relevance, the Arab MPI must be robust and consistent with various parameter specifications. 

Various methods can be used to evaluate different kinds of ordering robustness. They can be categorized into two complementary strands: internal validity and external robustness checks. External robustness considers the effect of changes in parameters, such as weights, poverty cut-off, and aggregation on country rankings. Internal validity assesses the choice of indicators, the deprivation cut-offs within indicators, potential redundancy of information, and consistency and coherence of correlations among indicators within and between dimensions. It guides the choice of indicators regardless of country rankings, so it is internal to the index itself. By contrast, external robustness simulates and tests different weighting schemes in an attempt to study the ranking sensitivity to changes in weights; and it simulates and tests different poverty cut-offs for the same purpose. The present paper focuses on external robustness, while internal validity is discussed in a forthcoming companion technical paper.1 

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