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Multidimensional poverty and types of impoverished counties in Gansu province of China
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作者 Fangfang Zhang Hui Liu +1 位作者 Weinan Gu Jianpeng Zhang 《Economic and Political Studies》 2022年第1期105-125,共21页
Gansu province,considered as one of the poorest provinces in China,faces great challenges in fighting against poverty.This study highlights the importance of studying multidimensional poverty in Gansu province.The Mul... Gansu province,considered as one of the poorest provinces in China,faces great challenges in fighting against poverty.This study highlights the importance of studying multidimensional poverty in Gansu province.The Multidimensional Poverty Indices of 75 poverty-stricken counties in Gansu province are measured quantitatively.The main driving factors of poverty are identified through the construction and application of a multidimensional poverty measurement system,classifying the impoverished counties into several categories.This study provides a scientific basis for formulating effective policies to achieve sustainable poverty reduction and highquality development in the region after 2020.The results show that:(1)more than half of the poverty-stricken counties in Gansu province have a degree of multidimensional poverty that is below the median poverty level,with regional variations;(2)the main factors driving poverty in these counties include shortages in water and land resources,educational disruptions,undesirable medical conditions,and the underutilisation of labour,which show spatial variations;and(3)these poverty-stricken counties are categorised into four types:counties with fragile ecological environments and insufficient natural resources,counties with undesirable socio-economic conditions,counties with unfavourable conditions in development,and counties with relatively balanced development conditions.Finally,this paper proposes policy recommendations to achieve stable poverty alleviation based on different types of impoverished counties. 展开更多
关键词 Multidimensional poverty poverty dimensions poverty identification targeted and differentiated measures impoverished counties
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