Industrial structure upgrading and agricultural labor productivity improvement:empirical evidence from 282 prefecture-level cities in China
Industrial structure upgrading can drive the flow of production resources among different industries,which is of great significance to promoting high-quality development of agriculture and improving resource efficiency.Based on the panel data of 282 prefecture-level cities in China from 2000 to 2022,using dynamic panel regression model,this paper empirically explores the effect of industrial structure upgrading on agricultural labor productivity in the perspectives of the optimization and rationalization of industrial structure,and examines the mechanism of agricultural technology application and agricultural labor transfer in improving agricultural labor productivity through industrial structure upgrading.It finds that the optimization and rationalization of industrial structure have significant effects on the improvement of agricultural labor productivity.The analysis of mediating effect reveals that industrial structure upgrading has an indirect effect on agricultural labor productivity through the extension of agricultural mechanization and the transfer of rural labor.Regional heterogeneity shows that the optimization of industrial structure has a greater effect on the improvement of agricultural labor productivity in the central and western regions while the rationalization of industrial structure has a more obvious effect on the improvement of agricultural labor productivity in the eastern and central regions.Finally,the paper puts forward some suggestions from the aspects of promoting the integration and development of three industries,strengthening the extension and application of agricultural technology,improving the quality of human capital in agricultural sector,and implementing regionally differentiated industrial adjustment and optimization strategies.
optimization of industrial structurerationalization of industrial structureagricultural labor productivity
NETL
NSTL
万方数据
