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A geographic identification of multidimensional poverty in rural China under the framework of sustainable livelihoods analysis

机译:可持续生计分析框架下中国农村多维贫困的地理识别

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Developing methods of measuring multidimensional poverty and improving the accuracy of poverty identification have been hot topics in international poverty research for decades. They are also key issues for improving the quality and effectiveness of rural poverty reduction programs in China. So far, selection and integration of poverty indicators remains the main difficult for measurement of multidimensional poverty. Guided by the sustainable livelihoods framework developed in the UK by the Department for International Development (DFID), an index system and an integration method for geographical identification of multidimensional poverty were established, and they were further used to carry out a county-level identification of poverty in rural China. Additionally, comparisons were made of the identification results with counties having single-dimension income poverty in rural areas and poor counties designated by the Chinese central government. The results showed that a total of 655 counties, with 141 million rural residents, were identified as multidimensionally poor. They are concentrated and conjointly distributed geographically, and evil natural conditions are their common features. In comparison to the income poor and the designated poor counties, the multidimensionally poor counties were not only worse in single-dimensional and composite scores, but also having multiple disadvantages and deprivations. By identifying the disadvantage and deprived dimensions, the measurement of multidimensional poverty should be very helpful for each county to work out and implement antipoverty programs accordingly, and it would make contribution to improve the sustainability of poverty reduction. Hopefully, this research may also shed light on multidimensional poverty measurement for other developing countries. (C) 2016 Elsevier Ltd. All rights reserved.
机译:数十年来,开发测量多维贫困和提高贫困识别准确性的方法一直是国际贫困研究的热门话题。它们也是提高中国农村扶贫项目质量和有效性的关键问题。迄今为止,贫困指标的选择和整合仍然是衡量多维贫困的主要困难。在国际发展部(DFID)在英国开发的可持续生计框架的指导下,建立了用于多维贫困地理识别的指标体系和集成方法,并将其进一步用于县级贫困人口的识别。中国农村的贫困。此外,将识别结果与农村地区一维收入贫困县和中国中央政府指定的贫困县的识别结果进行了比较。结果显示,共有655个县(1.41亿农村居民)被确定为多维贫困。它们集中并在地理上共同分布,邪恶的自然条件是它们的共同特征。与收入贫困县和指定贫困县相比,多维贫困县不仅在一维和综合得分上更差,而且还具有多种劣势和剥夺。通过确定劣势和被剥夺的层面,对多维贫困的衡量应该对每个县制定和实施反贫困计划非常有帮助,这将有助于提高减贫的可持续性。希望这项研究也可以为其他发展中国家的多维贫困衡量提供启发。 (C)2016 Elsevier Ltd.保留所有权利。

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