Research On The Effect And Mechanism Of Artificial Intelligence On Green Economic Efficiency

The improvement of environmental quality is not only related to the effect of reform and development shared by the people,but also directly characterizes the requirements of high-quality development of national economy.In this regard,in the face of the increasingly tightening resource and environmental constraints,promoting the transformation of green development is the right thing to do to achieve high-quality development.The iterative evolution of artificial intelligence(AI)technology and its integration with the development of the real economy have become the key grip to enhance the efficiency of China’s green economy.In this context,this thesis attempts to explore the following core but not yet well answered questions: Is AI effective in improving the efficiency of the green economy? What is the path of its mechanism? Is there a significant difference in the effect of AI on the green efficiency of the economy considering the realistic factors facing China in the new stage of economic transformation and development?This thesis theoretically explains the inner logic of AI’s influence on green economic efficiency,and systematically examines the effect of AI on green economic efficiency based on Chinese provincial panel data from 2010-2021,based on the super-efficiency EBM model and entropy value method to measure green economic efficiency and AI comprehensive development index in each region of China respectively.Specifically,firstly,a two-way fixed effects model is constructed to analyze the direct impact of AI on green economic efficiency,and model methods such as double difference model,instrumental variables method,dynamic panel model and time lag effect test are used for robustness analysis;secondly,group differences,i.e.,group regression method,are used to further explore the three path mechanisms of AI impact on green economic efficiency;again,based on China’s transition economic context,the role of two institutional environment factors,domestic and foreign,in the process of AI-enabled green economic efficiency is considered to capture the differential impact of AI in enhancing green economic efficiency.Finally,a spatial Durbin model is used to reveal the actual effect of the development of intelligent technology to enhance green economic efficiency from a spatial spillover perspective,while further focusing on the energy efficiency optimization dimension in the green development transition and examining the impact role of AI on energy efficiency optimization.The main conclusions of this thesis are:(1)AI will enhance green economic efficiency,which still holds after adopting a double difference model,endogeneity control with regional fiber optic cable density as an instrumental variable and various robustness analyses.(2)The mechanism path reveals that AI will significantly improve green economic efficiency through industrial structure upgrading,human capital level improvement and green technology innovation.(3)Heterogeneity analysis finds that there are significant institutional boundary conditions for the impact of AI on green economic efficiency,and accelerating the domestic marketization process and expanding the level of openness to the outside world can effectively strengthen the positive marginal effect of AI on green economic efficiency.(4)Expanded analysis shows that there is a radiating effect of local AI development on green economic efficiency in spatially connected areas.In addition,focusing on the energy efficiency optimization dimension in the green development transition,it is found that AI has a significant promoting effect on energy efficiency optimization.