Applied Mathematics and Nonlinear Sciences
Journal license

Journal

Applied Mathematics and Nonlinear Sciences


Volume
& Issue

Volume 8, Issue 2


Published
on

December 26, 2023


Pages


DOI

Article

Exploring the research on the follow-up industrial development of relocation for poverty alleviation based on the background of big data

Check for updates


Authors

Jian Wei Affiliation:
GuangXi Vocational Normal University, Nanning, Guangxi, 530000, China.


Abstract

Relocation for poverty alleviation is an important part of the implementation of the “five batches” project for poverty alleviation and has now entered the stage of consolidating the relocation results and promoting industrial development and economic growth. Based on this, this paper firstly explains the techniques related to the subsequent industrial development of relocation for poverty alleviation, including the double difference model, partial least squares regression algorithm and forward score matching algorithm, which provides the basis for the relevant analysis in the following paper. Secondly, the poverty reduction mechanism of industrial development in relocation for poverty alleviation is discussed, and the formation mechanism of poverty in relocation for poverty alleviation is explored. Finally, the impact of livelihood capital of relocated farmers was analyzed by using the double difference model, the partial least squares regression model analyzed the impact of industrial development, and the ATT effect of industrial development was analyzed by the PSM method. The results show that industrial development has a significant effect on reducing the multidimensional poverty index, multidimensional poverty order, income, education, health, and life-related poverty of relocated farmers, and their R2 test results are all above 0.6. The livelihood capital of relocated farmers is more affected by concentrated industrial development than decentralized development, and all of them have significant differences at the 5% level. The ATT effect based on PSM reflects that industrial development will increase the per capita total consumption level of relocated farmers, which can improve the living standard of relocated farmers to a certain extent. The subsequent industrial development of relocation for poverty alleviation should further optimize its industrial structure to provide an industrial foundation for the implementation of rural revitalization strategies.


Keywords

Double difference model, Partial least squares regression, Propensity score matching, Industrial development, 68P01


Citation

Wei, J. (2023). Exploring the research on the follow-up industrial development of relocation for poverty alleviation based on the background of big data. Applied Mathematics and Nonlinear Sciences, 8(2). https://doi.org/10.2478/amns.2023.2.01617

Published by: Engineering Journals

Engineering Journals Logo