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Research On The Influence Of Social Embedding Factors On The Economic Efficiency Of Chinese Cities

Posted on:2020-08-15Degree:MasterType:Thesis
Country:ChinaCandidate:Y WangFull Text:PDF
GTID:2439330575458947Subject:Statistics
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Urban economic efficiency is the economic benefit that a city can obtain on the basis of a certain economic cost.In the context of China's rapid economic development and further increase in urbanization rate,the need to invest in urban development,the demand for various factors such as labor and technology has also increased dralatically.At the same time,a series of unfavorable development phenomena such as transportation and environment and pollutant discharge caused by rapid population migration,the efficiency of urban development has been more and more concerned by the society,and various literature studies have gradually turned to how to improve the economic benefits of the city.Not only focus on economic growth.Only when a city achieves high efficiency in econolic operations can it achieve maximum efficiency with minimum investment,and then play an active role in the city's internal capital accumulation,industrial scale and industrial structure,and strengthen it.Radiation and attraction to surrounding areas and residents.The efficiency of urban economic operation is not only important for promoting the rapid growth of regional economy,but also important for promoting urbanization and improving the current environmental pollution waste in the process of urbanization.This paper solves the current impact on urban economic efficiency by integrating the current literature on the integration of urban economic efficiency research results and adding new economic sociology theory,using multi-level statistical models to establish the influencing factors model of urban economic efficiency from the perspective of social embedding.Lack of social factors,fiurther precise path of the impact of various influencing factors on economic efficiency.The research in this paper is mainly divided into two parts.The paper uses the super-efficiency EBM model with undesired output in the data envelopment analysis method to measure the economic efficiency of 240 prefecture-level cities and above in China from 2006 to 2015.And a brief analysis of the results of the calculation;the second is based on the multi-level statistical model based on the panel data of China's municipal decade for embeddedness and path analysis of the factors affecting urban efficiency.The results show that:(l)Due to its geographical location and the advantages of various national policy support,the urban economic efficiency is significantly higher than that' of the western and central regions;the efficiency level of each region generally rises first and then rises and finally rises slightly.The trend is not consistent with the year-on-year growth of China's economy.It can be seen that the economic development alone is not unilaterally specific.It should focus on the improvement of economic efficiency.(2)The economic efficiency level of urban cities in China is significantly different between cities.In the overall difference of urban economic efficiency,70.08%of the differences are caused by the social embedded factors of the city characteristics;cultural and structural embedded variables are for cities.Economic efi-iciency has a significant positive effect.Politics and relationship embedded variables have a significant negative effect on urban economic efi-iciency.Cultural embedding and political embedding will have an indirect impact on urban economic efficiency through marketization degree variables.(3)The social embeddedness factors of urban economic efficiency in different regions have different effects,so the formulation of relevant policies should be tailored to local conditions.The article analyzes the influencing factors of urban economic efficiency,and confirms the role of social factors in urban economic efficiency,which has certain significance for improving the efficiency of urban economic operation.
Keywords/Search Tags:urban economic efficiency, data envelopment analysis, social embeddedness, multilevel statistical model
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