Statistical Measurement And Spatial-temporal Heterogeneity Analysis Of China’s Digital Countryside

The Chinese government is actively promoting the construction of a digital village that integrates digital technology and rural development.With the aid of the policy dividend of the implementation of digital rural construction,accelerate the process of promoting agricultural and rural informatization,utilize the diffusion effect of digital technology innovation and development,effectively bridge the digital divide between regions,and provide an important guarantee for the overall "layout" and key "breaking" of rural revitalization.The research object of this article is the statistical measurement and spatiotemporal heterogeneity strategy of China’s digital countryside.Through the systematic policy basis for the construction of digital countryside,the connotation,significance,and practical challenges of China’s digital countryside are clarified.The Gini coefficient and polarization index are used to measure regional differences in the development of China’s digital countryside.The spatiotemporal changes of factors such as technological innovation,industrial structure,human resources,urbanization,and openness during the research period are used as research materials,The focus is on analyzing China’s digital rural development policies and guidelines from theoretical mechanisms,impact effects,and implementation paths.Firstly,on the basis of summarizing the connotation of digital rural development,this paper constructs an indicator system from five aspects: rural digital infrastructure,rural digital economy,rural digital industrialization,rural industry digitization,and rural digital participation.Using entropy weight method,the digital rural index of 31 provinces and 257 cities in China from 2011 to 2020 is measured and calculated;In addition,using the Gini coefficient and polarization index,we conducted a differential decomposition of the development level of digital villages in China to study the regional differences in the level of digital villages.The research results show that the overall level of digital rural development in China is continuously improving,and there are significant differences in the development level of digital rural areas among regions,but the degree of regional differentiation is constantly shrinking.Inter regional differences are mainly concentrated between the eastern and western regions,while intra regional differences are mainly manifested in the central region.Secondly,by constructing a spatial Dubin model,we study the influencing factors of the development level of digital villages,and consider the spatial effects of the development level of digital villages among regions from the spatial dimension.The research results show that the level of openness,human resources,industrial structure,and technological innovation will have a positive effect on the construction of digital villages in China,while the development of urbanization will have a negative effect on the construction of digital villages;From the perspective of dynamic fitting,there is a strong time accumulation in the development level of digital villages,that is,the early development level of digital villages will have a positive impact on the current development level of digital villages;From the perspective of spatial effects,the development of openness in neighboring regions will have a negative impact on the development of local digital villages,while the improvement of urbanization in neighboring regions will have a positive impact on the construction of local digital villages.Thirdly,the method of random causal inference is used to study the impact of each covariate on the development of digital villages under the influence of different policies,as well as the importance of each covariate on the construction of digital villages in different periods.The research results show that the validity of the impact of technological innovation on the digital village changes from negative to positive at different stages,and the importance of each variable’s impact on the digital village varies at different stages.