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Research On The Efficiency And Influencing Factors Of Financial Support For High-quality Development Of The Service Industry In Shandong Provinc

Posted on:2024-02-06Degree:MasterType:Thesis
Country:ChinaCandidate:Y ZhuFull Text:PDF
GTID:2569306914491394Subject:Financial
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The service industry in Shandong Province is developing rapidly.The 2021 "Shandong Peninsula Urban Agglomeration Development Plan" points out that it is necessary to promote the high-quality development of the modern service industry economy.However,the inefficient development of the service industry and the unreasonable structure of the service industry are still problems that plague the high-quality development of the service industry in Shandong Province.Financial resources,as the source of supporting industry development,are crucial to the development of the service industry.The innovative development model of "fine,specialized,special and new" puts forward higher requirements for financial support,and the high-quality development of the service industry should use financial resources more efficiently.Therefore,the research on the efficiency of financial support for the high-quality development of the service industry in Shandong Province has practical significance.This paper takes 16 prefecture-level cities in Shandong Province as the research object to measure their financial support efficiency and analyze the influencing factors,hoping to improve the high-quality development of the service industry in Shandong Province.Quality development finance provides an effective way to support efficiency.The research content of this paper is as follows: First,learn the theoretical basis of related finance and service industry,sort out relevant literature according to the research level,collect relevant data and materials to roughly analyze the current situation of service industry and financial development in Shandong Province,and lay the foundation for the following research.Second,build an evaluation index system for the efficiency of financial support for the high-quality development of the service industry in Shandong Province,use the DEA model to calculate the static efficiency value of Shandong Province from 2011 to 2021,make comparisons between regions,and then analyze its redundancy and insufficient output.Finally,the Malmquist index model is used to measure the total factor productivity of financial support for the high-quality development of the service industry in Shandong Province in the past 11 years,and the analysis is carried out according to the three dimensions of overall,time and region.Third,on the basis of efficiency research,select relevant financial,industrial and macro-environmental variables to build an index system of factors affecting financial support efficiency,and use the Tobit model to empirically analyze the direction and effect of each variable on the efficiency of financial support for the high-quality development of the service industry in Shandong Province.influence level.The empirical results show that:(1)The overall financial support efficiency in Shandong Province is good,and the overall efficiency shows an increasing trend.The measured static efficiency began to increase after 2015,which proves that the promotion of supply-side structural reform can improve the efficiency of resource allocation.Judging from the calculation results of the Malmquist index,the average Malmquist index of financial support in Shandong Province from 2011 to 2021 is 1.018,indicating that technological progress and the improvement of scale efficiency during this period have promoted the improvement of the development efficiency of financial support for the service industry in Shandong Province.(2)The circulation of resources between regions is not smooth,and the redundancy problem restricts the improvement of the overall efficiency of Shandong Province.Zaozhuang,Dezhou,Liaocheng,Weihai and other prefecture-level cities had relatively serious capital and labor redundancy problems during the study period,which restricted the further improvement of the efficiency of relevant prefecture-level cities.In addition,the two cities of Rizhao and Weihai have a large room for improvement in increasing the output of the service industry.(3)Financial factors,industrial factors and macro-environmental factors will affect the efficiency of financial support for the high-quality development of the service industry in Shandong Province,and the influencing factors have different effects on different regions.In the overall regression results,the variables that can promote efficiency improvement include financing structure,insurance density,industrial structure and real estate scale,while the financial scale and government intervention degree that can inhibit the efficiency of financial support.In the heterogeneity analysis,the scale of finance and related variables in the industry and macro environment have a significant impact on the provincial capital economic circle;financial factors have a significant impact on the Jiaodong economic circle;and in the southern Shandong economic circle,the depth of insurance and urbanization have a significant impact on the provincial capital economic circle.It has a significant impact.Finally,on the basis of combining the current situation of financial support for the high-quality development of the service industry in Shandong Province and the results of empirical analysis,the following suggestions are put forward: first,optimize the industrial structure of the service industry and prevent the risks brought about by the bubble of the real estate market;second,Reasonably control the financial scale and guide financial institutions to serve the real economy,especially the real economy in the service industry;third,optimize the financing structure and improve the liquidity of resource allocation;fourth,accelerate the creation of a pragmatic and efficient government environment and respect for business social environment.
Keywords/Search Tags:Financial support efficiency, Service industry in Shandong Province, Data Envelope Model, Redundancy analysis, Tobit model
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