统计研究 ›› 2017, Vol. 34 ›› Issue (11): 86-97.doi: 10.19343/j.cnki.11-1302/c.2017.11.008

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中国农村长期多维贫困的测量、分解与影响因素分析

侯亚景   

  • 出版日期:2017-11-15 发布日期:2017-11-25

Analysis of Chronic Multidimensional Poverty Measurement, Decomposition and Influencing Factors in Rural China: Based on the Panel Data of CFPS

Hou Yajing   

  • Online:2017-11-15 Published:2017-11-25

摘要: 多维贫困的发生具有动态性和长期性。本文在当前多维贫困的研究中引入了时间因素,考虑了多维贫困的长期变化特征;同时基于内源性扶贫理念,强调关注贫困人口的内生发展动力和主观感受,建立了主客观维度结合的长期多维贫困测量框架,利用中国家庭追踪调查(CFPS)2010-2012-2014年的三期面板数据,通过多层回归模型实证分析了中国农村家庭长期多维贫困及不平等的影响因素。研究结果表明:区域子群分解下,西部地区对农村整体长期多维贫困指数的贡献最大,但随着长期多维贫困持续期临界值的提高,西部地区在长期多维贫困平均持续期的作用减弱,而东部、中部和东北的长期多维贫困平均持续期更为持久;维度分解下,生活条件维度对农村长期多维贫困指数贡献最大,但主观福利维度对长期多维贫困的贡献不能忽视;多层回归模型较混合模型的估计结果更精确,宏观层次变量对农村家庭长期多维贫困发生率与不平等的解释能力分别为11.28%和9.51%;农村家庭长期多维贫困发生率和不平等状况不仅与家庭人口特征、生产经营特征、资产特征、社会关系特征等微观层次因素显著相关,而且还与非农户口状况、经济发展水平等宏观层次因素显著相关。

关键词: 长期多维贫困, 精准扶贫, 多维贫困, 多层回归模型, 不平等

Abstract: The occurrence of multidimensional poverty has a dynamic and chronic nature. Using the micro household panel data of China Family Panel Survey(CFPS) in 2010, 2012, and 2014 year, this paper introduces the time factor in the study of multidimensional poverty, considering the chronicity characteristic of multidimensional poverty, and based on the endogenous poverty concept, emphasizes the endogenous development momentum and subjective feelings, and establishes objective and subjective chronic multidimensional poverty measurement framework, and empirically analyses the influencing factors of rural chronic multidimensional poverty and inequality with the multilevel regression model. The results show that the western region is the largest contribution to the rural overall chronic multidimensional poverty; but with the increasing of the duration cut-off, the average duration of chronic multidimensional poverty in the east, central and northeast is more lasting. The dimension of living condition is the greatest contribution to the rural overall chronic multidimensional poverty index, but the contribution of the dimension of subjective wellbeing can’t be neglected. Multilevel regression model more accurate than the mixed model, and the macro level variables can account for 11.28% of difference of chronic multidimensional poverty incidence and 9.51% of difference of inequality in rural chronic multidimensional poverty household. Rural chronic multidimensional poverty incidence and inequality are not only significantly influenced by the micro level factors of family demographic characteristics, production and engagement characteristics, asset characteristics social relationship, but also the macro level factors of non-agricultural residence permit status and village economic condition.

Key words: Chronic Multidimensional Poverty, Precise Poverty Alleviation, Multidimensional Poverty, Multilevel Regression Model, Inequality