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作 者:王虎邦 夏卫杰 逯鹏飞 WANG Hu-bang;XIA Wei-jie;LU Peng-fei(School of Statistics,Jilin University of Finance and Economics,Changchun 130117,China)
出 处:《统计学报》2024年第4期80-94,共15页Journal of Statistics
基 金:教育部人文社会科学研究青年项目资助“基于机器学习的农村相对贫困多维识别及监测预警研究”(21YC910008)。
摘 要:促进农民工返乡创业是解决乡村发展问题、实现共同富裕的重要途径,在此背景下,借助2010—2020年中国1713个县域的面板数据,运用双重差分法和机器学习中的因果森林算法探讨农民工返乡创业政策与县域共同富裕之间的关系。研究表明,农民工返乡创业政策能够促进县域共同富裕发展。机制检验发现,农民工返乡创业政策可通过产业结构效应、就业结构效应推动县域共同富裕发展。异质性分析发现,返乡创业政策对县域共同富裕的平均处理效应整体水平偏低,且在弱财政压力、高城镇化进程、高金融发展水平和高基础设施建设的县域政策实施效果更好。Promoting the return of migrant workers to their hometowns to start their own businesses is an important way of solving rural development problems and realizing common prosperity.Based on the panel data of 1,713 counties in China from 2010 to 2020,the study applied the difference-in-differences method and the causal forest algorithm from machine learning to explore the relationship between policies promoting migrant workers’return forentrepreneurship and common prosperity in county regions.The study found that policie sencouraging migrant workers’return for entrepreneurship could promote the development of common prosperity in county regions.Mechanism tests revealed that these policies could drive the development of common wealth in counties through industrial structure effects and employment structure effects.Heterogeneity analysis showed that,the average treatment effect of hometown entrepreneurship policies on common prosperity in county regions was generally at a lower level,but the policies were more effective in counties with weak fiscal pressure,high levels of urbanization,high financial development,and high infrastructure construction.
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