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Research On The Measurement Of Chinese Service Industry Development Level And Spatial Spillover Effect

Posted on:2020-10-02Degree:MasterType:Thesis
Country:ChinaCandidate:J J WuFull Text:PDF
GTID:2439330596481751Subject:Master of Applied Statistics
Abstract/Summary:PDF Full Text Request
Xi Jinping's report at 19 th CPC National Congress states that "it is necessary to carry out the new concept of development and build a modern economic system." In recent years,China's service industry has maintained a relatively rapid development and expanded in scale,playing an important role in the process of steady growth,adjustment of structure and promotion of transformation.However,the regional uncoordinated problem of China's service industry development is more prominent.The main problem is that the level of service industry development in the eastern region is significantly higher than that in the central region and western region.And the differences between provincial domains are also large,which not benefits to the all-round and high quality development of service industry.The study on the measurement and spatial effect of the development level of China's service industry is helpful to understand the overall development level and spatial distribution characteristics of the national service industry,providing the theory for the relevant departments to make scientific decisions.Considering the four aspects,such as scale,quality,structure and potentiality of service industry development,this paper selects 13 two-level indexes,builting the index system of service industry development.Using Topsis-entropy method to measure the development level of China's provincial service industry in 2006~2016 years,then adopting logarithmic deviation mean,the Terre index and Gini coefficient to analyze the regional differences of service industry,discussing the difference level of service industry development among the eastern region,the central region and the western region.Using the Global Moran Index and Moran scatter chart to analyze the spatial correlation and spatial distribution status of China's service industry development.On the basis of considering the spatial effect,selecting five control variables such as the infrastructure construction,technology level,industrialization level,openness and population density,the paper constructs a double fixed SDM model to study the spatial spillover effect of China's service industry development.Finally,the relevant policy recommendations are put forward to provide references for leaders at all levels and relevant departments.In this paper,it is found that: first,the service industry development level of China shows a decreasing trend from the east to the central and western regions,the coastal areas to the inland areas.The top ten provinces of the service industry development average level are Shanghai,Beijing,Tianjin,Guangdong,Jiangsu,Zhejiang,Shandong,Liaoning,Fujian and Hubei,of which nine provinces are from the eastern region.Second,in the 2006~2016 years,the regional difference of Chinese service industry development is small and the spatial pattern has not changed significantly,showing that the difference of eastern region is much larger,the central is second,the west is the smallest.The regional differences account for the main difference,indicating that the differences of Chinese service industry are mainly caused by regional differences.Third,there is a significant positive spatial correlation among Chinese service industry development.The spatial distribution status are mainly shown that Beijing,Shanghai,Jiangsu are the core of the "high-high" agglomeration,Qinghai,Xinjiang,Ningxia,Yunnan,Gansu,Guizhou are the core of the "low-low" agglomeration,Guangdong and Liaoning are the core of the "high-low" agglomeration.Fourth,infrastructure construction,technology level and openness not only play a significant role in promoting the development of the service industry,but also have a positive impact on neighboring provinces.That is,there is a strong spatial spillover effect.
Keywords/Search Tags:Topsis-Entropy Method, Moran's I, Spatial Dubin Model, Spatial Spillov
PDF Full Text Request
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