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Research On The Impact Of Digital Economy Development On The Total Factor Productivity Of China’s Service Industry

Posted on:2024-09-10Degree:MasterType:Thesis
Country:ChinaCandidate:M R WangFull Text:PDF
GTID:2569307091463764Subject:Industrial Economics
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At present,with the change of China’s population structure and the negative impact of resource and environmental constraints gradually appearing,the extensive economic growth mode dominated by large-scale input of capital,labor and land is difficult to sustain.In the new stage of economic development,seeking a new efficiency-driven economic growth mode characterized by high economic efficiency has become the common concern of people from all walks of life,among which improving Total Factor Productivity is particularly critical.Under the new round of information technology revolution and industrial transformation,digital technology has accelerated the penetration into various areas of the economy and society.The digital economy is giving "new momentum" to economic and social development.As a crucial part of the national economy,the service industry,along with the development of the digital economy,is deepening its integration with the digital economy.Improving the Total Factor Productivity of the service industry can not only give full play to the sustainable growth potential of the service industry and explore the sources of efficiency-driven economic growth,but also effectively promote the development of modern society.In this context,this article attempts to study the theoretical mechanism and practical effects of the development of the digital economy on the Total Factor Productivity of the service industry,which is important to seize the opportunity of digital economy era and enhance the Total Factor Productivity of service industry.As for the prospect in theorical research,based on the theories of endogenous economic growth,network externalities and knowledge spillover effects,this article explores the impact mechanism of digital economy development on Total Factor Productivity of the service industry from the aspects of technological progress and technological efficiency,and proposes research hypotheses.At the terms of empirical research,firstly,based on the data of 30 provinces in China from 2011 to 2021,the entropy method is used to construct a digital economy development level index and the Total Factor Productivity of the service industry is measured by the DEA-Malmquist index method.Then,through the two-way fixed panel regression model,instrumental variable method,heterogeneity analysis and other methods,the effects,mechanism and regional impact of digital economy development on Total Factor Productivity of the service industry were empirically examined from the aspects of wholeness,technological progress and technological efficiency.Through the theorical and empirical analysis,the following conclusions can be drew:(1)Overall,the development of the digital economy can significantly improve the level of Total Factor Productivity of in the service sector.(2)From the perspective of improvement,the enhancement of the Total Factor Productivity of China’s service industry by the digital economy is reflected in both improving technological efficiency and driving technological progress,but more in terms of technological efficiency.(3)From a sub-regional point of view,compared with the central and western regions,the development of digital economy in the eastern region of China has had the most significant impact on the improvement of Total Factor Productivity of the service industry,and "Digital divide" still exists.Finally,this paper proposes policy recommendations to bring into play the role of the digital economy in promoting Total Factor Productivity of the service industry and narrowing the "digital divide" from the measurement dimensions of digital economy development index—— digital infrastructure,digital industrialization,digital application and digital economy development ecology.
Keywords/Search Tags:digital economy, total factor productivity of the service industry, tentropy method, DEA-Malmquist index method, digital divide
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