| Since the reform and opening up, China’s economy has been in a rapid pace of development, people’s living standard has also been significantly improved, and come accompanied by the energy demand, growing consumption. China has to improve energy efficiency in the core of the energy strategy to effectively reduce energy consumption per unit of GDP, and transform economic growth mode. Yunnan, Guizhou and Guangxi region are as the areas with karst landforms, and which level of development is relatively backward, and they are in the medium-term development of important strategic period of industrialization, relying on structural saving space in the short term is not great. Data show that technological progress has brought good energy-saving effect. Yunnan, Guizhou and Guangxi region due to there are some differences among the conditions, the level of social development in their respective geographic. In the role of research and innovation factors play in reducing energy consumption per unit of GDP also reflects the different benefits. In the implementation of the strategy of independent innovation and energy saving macro backdrop, researching the spatial structure, the spatial spillover effect and influence relationship between the research and development and energy consumption per unit of GDP have very important significance in Yunnan, Guizhou and Guangxi region, and from the perspective of space, whether there exists a spatial correlation and spillover effects between the technical level and energy consumption among regions? If there exist, to improve the technical level of a region whether will affect the energy and skill level with which it has relations in areas adjacent space it? Whether the R&D of research institutions affects the reduction of energy consumption per unit of GDP? If so, how much impact? But after considering the spatial heterogeneity, whether there is a significant difference for the influencing of energy consumption per unit of GDP among prefecture-level city. Those for improving energy efficiency, reducing energy consumption per unit of GDP, resolving conflicts among the "Energy-environment-economy", and improving the quality of economic growth.Based on the existing literature, this paper tries to make an analysis of the spatial structure and influencing factors of the relationship between research and innovation and energy consumption per unit of GDP of prefecture-level city in Yunnan and Guizhou Guangxi region by the exploratory spatial data analysis and empirical research from the perspective of geospatial. Contents of this paper are as follows:Firstly, make a verification analysis for spatial agglomeration and spillover effects of the research and innovation and energy consumption per unit of GDP of26prefecture-level cities in Yunnan, Guizhou and Guangxi region by the method of ESDA, and analysis the temporal and spatial concentration degree of evolution, stability and spatial structure in space stability of the spatial structure under agglomeration spillovers effect. Specifically, using the spatial autocorrelation method to analysis the development pattern formation and evolution of the research and innovation and energy consumption per unit of GDP of26prefecture-level cities in Yunnan, Guizhou and Guangxi region from2005to2010, including the global spatial autocorrelation and local spatial autocorrelation analysis.Secondly, using the spatial econometric models include spatial error model, spatial lag model and geographically weighted regression model to study the effects of the research and innovation on energy consumption per unit of GDP under the interaction of the spatial spillover effects and the other factors. Specifically, putting the spatial variable and patent grants, R&D expenditure as a percentage of GDP, R&D personnel, industrial structure and other control variables into the space econometric model to analyze the influencing action and spatial heterogeneity that the spatial agglomeration generated effect to energy consumption per unit of GDP of26prefecture-level cities in Yunnan, Guizhou and Guangxi region.Again, through the empirical research on26prefecture-level cities in Yunnan, Guizhou and Guangxi region, it gets the following conclusions:(1) it showed that by descriptive statistics data analysis of patents granted and energy consumption per unit of GDP data of26prefecture-level cities in Yunnan, Guizhou and Guangxi region from2005to2010:the country-level city of patents granted in Yunnan, Guizhou and Guangxi region has been greatly improved and prefecture-level city of patents granted are in an upward trend, the average annual growth rate of patents granted of prefecture-level city reaches35.6%. Secondly, the energy consumption per unit of GDP in most of the downward trend, the overall level is also showing a downward trend; the average annual level city declined2.67percent in prefecture-level cities in Yunnan, Guizhou and Guangxi region.(2) The use of exploratory spatial data analysis (ESDA) can be found that the bivariate of the research and innovation and energy consumption per unit of GDP on spatial distribution is not random in26prefecture-level cities in Yunnan, Guizhou and Guangxi region, it has a certain spatial agglomeration phenomena. Research and innovation activities are relatively frequent in the city, which are mostly economically developed prefecture-level cities, provinces and autonomous regions to the capital city as the center of its neighboring cities have a higher intensity of innovation, research and innovation clusters outside a certain circle, such as the evolution of the pattern formed center-periphery spatial pattern may indicate the presence of spatial clustering effect around the capital city of considerable size. Higher energy consumption per unit of GDP is basically a prefecture-level city located on the periphery of the provinces, and the provinces at the junction of prefecture-level city is also showing the same level of energy consumption per unit of GDP, higher energy consumption per unit of GDP of provincial level, another provincial-level city is connected to its energy consumption per unit of GDP is also high, showing some agglomeration effects. This distribution exhibit space and a negative correlation:the higher the degree of development of innovative cities, often lower its energy consumption per unit of GDP surrounding cities, and vice versa.(3) it found that the spatial error model and spatial lag model that consider spatial factors are superior to the conventional least squares regression estimation model by OLS, SEM and SLM econometric analysis, and further comparison, the spatial error model is the most suitable for estimated analysis of the relationship between the research and innovation and energy consumption per unit of GDP of prefecture-level city in Yunnan, Guizhou and Guangxi region. From the view of the meaning of spatial error model and elasticity of each variable, in2009, the reduction of energy consumption per unit of GDP of prefecture-level citiy in Yunnan, Guizhou and Guangxi region mainly rely on patents granted, R&D spending and industrial Intramural structure promoted. Among the factors of the research and innovation, the contribution value of the patent grants to reduce energy consumption per unit of GDP is the highest, followed by the Intramural R&D expenditure factor. For industrial structure factors, it showed a negative correlation between industrial structure and energy consumption per unit of GDP, at the same time, the λ value of the spatial error model is positive and passed the1%significance level test, which indicates that there exists a certain positive correlation and certain cluster effect for energy consumption per unit of GDP of prefecture-level citiy in Yunnan, Guizhou and Guangxi region.(4) using the geographical weighted regression analysis method, this paper confirmed the factors affect the energy consumption per unit of GDP of prefecture-level city in Yunnan and Guizhou Guangxi region exist heterogeneity in space. Output elasticity of patents granted has significant spatial variability, which shows a decreasing trend roughly from north to south. In all prefecture-level cities Intramural R&D expenditure elasticity coefficients, the city of Beihai, Laibin, Liuzhou, Yulin, Hezhou, Qinzhou in Guangxi have not passed the10%significance level, the rest of prefecture-level cities have passed the5%or more significant level test, which indicates that R&D funding exists a certain lag. The spatial variability of estimated value of the industrial structure is not so strong. From the differences of the prefecture-level cities of provinces and autonomous regions, the elastic modulus in the capital city are slightly better than other prefecture-level cities.Finally, based on the research results, the corresponding policy recommendations:(1) The research and innovation as Yunnan, Guizhou and Guangxi cities to reduce energy consumption per unit of GDP "engine" of strategic thinking;(2) Strengthen Yunnan, Guizhou and Guangxi regional R&D investment, improve the overall quality of R&D personnel, the formation of the region’s core competitiveness, and reduce energy consumption per unit of GDP;(3) Yunnan, Guizhou and Guangxi region to strengthen cooperation between research, science and technology into productivity, reduce energy consumption;(4) Optimizing the industrial structure, vigorously develop the tertiary industry, to reduce energy intensity;(5) To strengthen cooperation provincial, prefecture-level city between realization enhance research and innovation capacity and to reduce energy consumption per unit of GDP in the win. |
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