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Multidimensional poverty measure and analysis: a case study from Hechi City China

机译:多维贫困测度与分析:以河池市为例

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摘要

Aiming at the anti-poverty outline of China and the human–environment sustainable development, we propose a multidimensional poverty measure and analysis methodology for measuring the poverty-stricken counties and their contributing factors. We build a set of multidimensional poverty indicators with Chinese characteristics, integrating A–F double cutoffs, dimensional aggregation and decomposition approach, and GIS spatial analysis to evaluate the poor’s multidimensional poverty characteristics under different geographic and socioeconomic conditions. The case study from 11 counties of Hechi City shows that, firstly, each county existed at least four respects of poverty, and overall the poverty level showed the spatial pattern of surrounding higher versus middle lower. Secondly, three main poverty contributing factors were unsafe housing, family health and adults’ illiteracy, while the secondary factors include fuel type and children enrollment rate, etc., generally demonstrating strong autocorrelation; in terms of poverty degree, the western of the research area shows a significant aggregation effect, whereas the central and the eastern represent significant spatial heterogeneous distribution. Thirdly, under three kinds of socioeconomic classifications, the intra-classification diversities of H, A, and MPI are greater than their inter-classification ones, while each of the three indexes has a positive correlation with both the rocky desertification degree and topographic fragmentation degree, respectively. This study could help policymakers better understand the local poverty by identifying the poor, locating them and describing their characteristics, so as to take differentiated poverty alleviation measures according to specific conditions of each county.
机译:针对中国的反贫困纲要和人类环境的可持续发展,我们提出了一种多维贫困测度和分析方法,用于测度贫困县及其影响因素。我们建立了一套具有中国特色的多维贫困指标,结合了A–F双临界,维数聚合和分解方法以及GIS空间分析,以评估不同地理和社会经济条件下贫困者的多维贫困特征。以河池市11个县为例,首先,每个县至少存在四个贫困方面,总体贫困水平呈现出上高中下的空间格局。其次,造成贫困的三个主要因素是住房不安全,家庭健康和成年人的文盲,而次要因素包括燃料类型和儿童入学率等,通常表现出很强的自相关性。就贫困程度而言,研究区域的西部表现出显着的聚集效应,而中部和东部则表现出明显的空间异质分布。第三,在三种社会经济分类中,H,A和MPI的分类内多样性大于分类间的多样性,而这三个指标中的每一个都与石漠化程度和地形破碎程度均呈正相关。 , 分别。这项研究可以帮助政策制定者通过识别穷人,找到他们并描述他们的特征来更好地了解当地的贫困状况,从而根据每个县的具体情况采取不同的扶贫措施。

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