摘要
后小康时代,实证检验收入判别贫困的有效性和准确性,能为降低贫困识别成本、建立返贫预警机制提供有效经验支持。基于湖南省石门县18个村、2个社区1010份农户调查问卷数据,分别从农户家庭决策风险、能力风险、经济风险、健康风险等层面选取变量,运用倾向得分匹配法实证分析农户收入对贫困风险的识别效应。结果表明:农户家庭遭遇贫困风险与户主性别、家中义务教育阶段学生、家中慢性病患者数、家中大病患者数显著正相关,与户主年龄、户主文化程度、少儿人口数则显著负相关;农户工资性、经营性收入对贫困风险的识别效应较强,财产性、转移性收入的识别准确率较低,但如果忽略样本选择偏差产生的内生性问题,则容易高估收入识别效应。据此提出,加快构建以农户收入为导向、兼顾家庭异质性的防贫监测帮扶机制,多元拓展低收入人口收入来源,健全完善弱势群体分层分类社会救助体系等建议。
It is a support for costing down poverty identification and establishing the early warning fighting poverty to identify the income standard accurately in the post-small prosperity era.Our study analyzes the identification effect of farmers income fighting poverty using the propensity score matching method from the farm household decision risk,ability risk,economic risk,and health risk based on 1010 questionnaire data from 18 villages and 2 communities in Shimen,Hunan province.The results show as follows.The poverty risk level of farm household is positively correlated with the gender,students in compulsory education,chronic illnesses and critical disease of the household and negatively correlated with the age,education level and the number of children.The identification effects of farm households are more dependent on the wage income and business income than and property income and transfer income.At the same time,the sample selection bias leads to the endogeneity problem and overlook the identification effects.Accordingly,our study suggests and construct an identification system for increasing income and creating income for low-income groups to fight poverty and establish a sound social assistance system for vulnerable groups in hierarchical classification.
作者
唐小兵
宾津佑
谭雪兰
TANG Xiao-bing;BIN Jin-you;TAN Xue-lan(Department of Think Tank Construction,Hunan Academy of Social Sciences,Changsha 410005,China;College of Management,Guangdong Ocean University,Zhanjiang 524088,China;College of Resources and Environment,Hunan Agricultural University,Changsha 410128,China)
出处
《湖南师范大学自然科学学报》
CAS
北大核心
2023年第2期98-105,115,共9页
Journal of Natural Science of Hunan Normal University
基金
国家自然科学基金项目(41971219)
湖南省哲学社会科学基金项目(18ZDB015)。