统计研究 ›› 2021, Vol. 38 ›› Issue (10): 90-104.doi: 10.19343/j.cnki.11-1302/c.2021.10.008

• • 上一篇    下一篇

我国农村贫困的动态转化、持续时间与状态依赖研究——基于收入贫困与多维贫困的双重视角

周强   

  • 出版日期:2021-10-25 发布日期:2021-10-25

Dynamic Transformation, Duration and State Dependence of Rural Poverty in China:Based on Income Poverty and Multidimensional Poverty

Zhou Qiang   

  • Online:2021-10-25 Published:2021-10-25

摘要: 本文使用中国健康与营养调查2000—2015年跟踪数据,比较分析了农村家庭收入贫困与多维贫困的长期变动情况。在此基础上,使用Cox比例风险与动态Probit模型实证研究了跨期贫困的动态转化概率、状态依赖及其影响因素等问题。研究发现,农村多维贫困发生率下降幅度比收入贫困发生率下降幅度高出近20个百分点,但未脱贫的多维贫困家庭比收入贫困家庭具有更明显的贫困适应性。随着贫困持续时间的增加,无论是收入贫困还是多维贫困,中断当前贫困状态的可能性都下降了。进一步分析发现,子代职业地位、子代教育、城镇化水平和交通便捷度等因素显著降低了贫困家庭的贫困适应性与状态依赖,而贫困补贴对部分贫困家庭产生了补贴依赖效应,从而一定程度上促进了其贫困适应性。本研究在理论上丰富了有关贫困动态性的探讨,为有效破解低收入群体的贫困状态依赖提供了经验证据。

关键词: 贫困适应性, 多维贫困, Cox比例风险, 动态Probit模型

Abstract: Based on the panel data of the China Health and Nutrition Survey from 2000 to 2015, this paper compares and analyzes the long-term dynamic trends of income poverty and multidimensional poverty in rural China. On the basis of measuring poverty, this paper evaluates the dynamic transformation probability, state dependence and the influencing factors of intertemporal poverty using the Cox proportional risk model and the dynamic Probit model. The results show that the decline rate of multidimensional poverty is nearly 20 percent higher than that of income poverty in rural China. However, the families in multidimensional poverty have stronger poverty adaptability than those in income poverty. Whether it is income poverty or multidimensional poverty, the possibility of interrupting the current state of poverty is significantly reduced with the increase of the duration of poverty. Further analysis shows that factors such as offspring’ s occupation status, education of

Key words: Adaptability to Poverty, Multidimensional Poverty, Cox Proportional Risk Model, Dynamic Probit Model