农村家庭多维贫困测度与分析

发布时间：2019-04-02 13:39

【摘要】：多维贫困理论与方法更有助于对贫困的精准识别和量化。本文构建了新型多维贫困指标体系,利用中国家庭追踪调查(CFPS)数据,引入人工神经网络方法,测度并分解了农村家庭多维贫困的广度、深度和强度水平。研究结论表明:随着贫困维度的增加,多维贫困的广度、深度和强度指数下降,表明农村家庭不易发生多维极端贫困;农村家庭多维贫困指数(MPI)呈西高东低态势,表明农村家庭多维贫困具有典型的区域分布特征。此外,多维贫困指数分解结果显示,收入、金融和教育等因素是我国农村家庭致贫的主因。其中,东部地区金融因素影响最大,而中西部地区则为收入因素。研究结论为贫困的识别和精准扶贫提供了政策依据。
[Abstract]:Multi-dimensional poverty theory and methods are more helpful to accurately identify and quantify poverty. In this paper, a new multidimensional poverty index system is constructed, and the extent, depth and intensity of multidimensional poverty in rural households are measured and decomposed by using the (CFPS) data of Chinese household tracking survey and the introduction of artificial neural network (Ann) method. The results show that: with the increase of poverty dimension, the breadth, depth and intensity index of multidimensional poverty decrease, indicating that rural households are not prone to multidimensional extreme poverty; The multidimensional poverty index (MPI) of rural households is higher in the west and lower in the east, which indicates that the multidimensional poverty in rural households has typical regional distribution characteristics. In addition, the results of decomposition of multidimensional poverty index show that income, finance and education are the main causes of poverty caused by rural households in China. Among them, the eastern region financial factor is the biggest influence, and the central and western region is the income factor. The conclusion provides the policy basis for the identification of poverty and accurate poverty alleviation.
【作者单位】：西南大学经济管理学院;
【基金】：国家社会科学基金重点项目“巨灾风险管理机制设计及路径选择研究”(12AGL008) 重庆市重点文科基地项目“社会转型背景下农户风险偏好与农户收入差距”(16SKB041) 西南大学决策咨询项目“社会化预期与公共情绪管理”(2016SWUJCZX09) 中央高校基本科研业务费专项资金项目“社会资本与农户多维贫困”(SWU1709413)的资助
【分类号】：F323.8

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