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Research On The Calculation And Convergence Of Provincial Green Innovation Efficiency In China

Posted on:2020-05-03Degree:MasterType:Thesis
Country:ChinaCandidate:X J LiuFull Text:PDF
GTID:2439330596981723Subject:Applied Statistics
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Innovation is the key word in the new stage of China's development.And green reflects the result of innovation and development.Green innovation makes economic growth rely on scientific and technological innovation.Replacing the traditional cheap labor and energy-driven economic development mode and achieving the goal of ecological environment improvement and sustainable development.And achieving the green development of the whole society.Green innovation efficiency includes innovation and green.It is of great significance to judge whether innovation is efficient,whether it can promote environmental improvement and resource utilization,and whether it can really promote economic green development.The article adopts the two step analysis method to carry out a comprehensive study of China's green innovation efficiency.Firstly,through combing the related concepts and theories of green innovation,this paper puts forward the concept of green innovation efficiency which conforms to the research purpose.And based on this,combining with the target and criteria of this evaluation index system,establishing the evaluation index system of green innovation efficiency.Using data envelopment analysis method and vertical and horizontal grade pull-out method to calculate the efficiency of green innovation in thirty provinces of China;secondly,in order to further study the regional characteristics of green innovation efficiency,this paper examines the spatial characteristics and spatial correlation of regional green innovation efficiency.And this paper introduces spatial effect on the basis of traditional convergence analysis model to explore the convergence of regional green innovation efficiency.The main conclusions of this paper are as follows:(1)The efficiency of green innovation in China's provinces continues to improve,and the regional differences narrow year by year.Vertical analysis shows that the green innovation efficiency of most provinces in China in 2007-2017 has a positive change trend and the efficiency value increases steadily with time.Horizontal comparison shows that the average green innovation efficiency in the eastern region is higher than that in the western and middle regions.The regional differences are obvious.But the gap between these regions is narrowed with time.(2)The spatial agglomeration characteristics of green innovation efficiency are obvious and the spatial correlation is significant.From a visual point of view,the quartile map shows that the green innovation efficiency has spatial agglomeration of adjacent areas in the eastern coastal areas,remote areas in the central and western regions,the central region.This spatial concentration characteristics are more intuitive with time.Judging from the test results,in 2007-2017 the global Moran's I index is significantly greater than 0,indicating that China's green innovation efficiency has a strong positive spatial autocorrelation;(3)Green innovation efficiency has the characteristics of spatialconvergence and is affected by a variety of factors.The convergence analysis model considering spatial factors has stronger explanatory power to green innovation efficiency than the traditional panel convergence model.This confirms the rationality of this paper.The convergence coefficients of the spatial absolute convergence model and the spatial conditional convergence model are significantly less than 0,which shows that the green innovation efficiency of provinces in China has the characteristics of spatial convergence.Spatial conditional convergence model shows that regional opening,economic development,human capital,science and technology support can have a significant influence on the convergence of green innovation.
Keywords/Search Tags:green innovation efficiency, data envelopment analysis, sigma convergence, spatial absolute beta convergence, spatial conditional beta convergence
PDF Full Text Request
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