摘要
贫困问题是我国社会经济发展中普遍存在且最尖锐的社会问题之一,当前我国确立的精准扶贫政策是解决贫困问题的根本保证。研究利用广东省精准扶贫政策确定的连州市66个贫困村的基础数据,借助多维贫困理论构建了连州市贫困村的多维贫困测量体系,利用A-F双临界值法测算了多个维度的权重,同时结合AHP-熵值法计算各测量指标的组合权重,借助维度权重和组合权重构建综合贫困度测算模型,计算了连州市66个贫困村的自然致贫、社会致贫、经济致贫指数,以及3个指数加总所得的综合贫困度。结果表明:66个贫困村中的综合贫困程度可划分为4个等级,其中轻度贫困村占21.2%、中度贫困村占16.7%、重度贫困村占34.8%、极重度贫困村占27.3%。连州市贫困村的贫困深度较重,重度贫困和极重度贫困村的占比较大且分布较集中,因此在制定精准扶贫政策中需要充分考虑其贫困深度和空间分布问题。
In China,poverty is one of the most prevalent and acute social problems in the development of social economy. And the current policy of poverty alleviation established by the Chinese government is the fundamental guarantee for solving the problem of poverty. This article is based on the theory of multidimensional poverty,constructs a multidimensional poverty measurement system with the basic data of 66 poor villages in Lianzhou City,which are determined by the policy of poverty alleviation in Guangdong Province. The dimension weights of multiple dimensions are calculated through the" A-F dual cutoff". Besides,combined with the weight of the index calculated by AHP-EVM method,the model of comprehensive poverty in poor villages is constructed. Through the model,the 66 poor-village's natural poverty index,social poverty index,economic poverty index and the comprehensive poverty are calculated. According to the calculation results,the poverty level is divided into four classes,the poor villages with mild-poverty accountes for 21.2% ,moderate-poverty accountes for 16.7% ,severe-poverty accountes for 34.8% ,extreme-poverty accountes for 27.3% . The depth of poverty of Lianzhou poor villages is heavy,whichsevere-poverty and extreme-poverty accountes for larger proportion,and the distribution is concentrated. Therefore,making targeted poverty alleviation policy should need to fully consider the depth of poverty and spatial distribution.
出处
《广东农业科学》
CAS
2017年第10期156-165,178,共11页
Guangdong Agricultural Sciences
基金
广东省哲学社会科学"十三五"规划项目(GD16CGL03)
