Impacts of Land Transfer on Multidimensional Relative Poverty of Farmers:From the Perspective of Optimizing Production Resource Allocation
The purpose of the study is to estimate the impact,mechanism and heterogeneity of land transfer on the multidimensional relative poverty of farmers,to further deepen the reform of rural land institutions and build a long-term mechanism to alleviate relative poverty in rural China.The research methods are as follows.Using the data of China Family Panel Studies from 2010 to 2018,this paper constructs a multi-dimensional relative poverty evaluation index system and measures the multidimensional relative poverty of farmers through BP neural network empowerment model and AF method.We then employ the instrumental variable method to estimate the impact of land transfer on the multidimensional relative poverty of farmers.The results show that:1)land transfer significantly reduces the multidimensional relative poverty of farmers.The poverty-reduction effect of land outflow is robust for all five sub-dimensions of relative poverty,while the effect of land inflow is mainly concentrated on the three dimensions:household viability,development opportunities and social insurance.2)Land transfer reduces multidimensional relative poverty mainly through optimizing the allocation of land and labor resources of farmers.3)The poverty alleviation effect of land transfer is stronger for farmers in western regions and counties with lower agricultural output values,as well as households with younger labor forces and lower land values.In conclusion,land transfer helps enhance the endogenous motivation of relatively poor groups and cultivates a long-term mechanism for self-development,leading to a narrower disparity across regions and households.Thus,to achieve the goal of common prosperity,it is crucial to establish a unified market for land management rights transfer,promoting well-organized land transfers.
land transferinstrumental variablesmultidimensional relative povertyoptimal resource allocationBP neural network
NETL
NSTL
万方数据
