| According to the statistics by International Energy Agency, in 2007, China overtook the United States in carbon dioxide emission to become the largest producer of carbon dioxide in the world. For a prolonged period of time in the future, while China's economy will continue to grow at a relatively fast speed, the urbanization and industrialization will add to the discrepancy between economic growth and energy environment, bringing greater pressures to China in emission reduction. Under such a background, in 2009 the Chinese government for the first time put forward a specific target in reducing the emission of greenhouse gases, specifically, by 2020, the carbon emission intensity will be reduced by 40%~45% compared with 2005, and restraint index will also be included in the middle and long term plan for national economy and social development. Due to the discrepancy in regional economy development and energy resources, remarkable differences can be found in China's carbon emission in different provinces and region. To attain the target of emission reduction, the spatial characteristic of carbon emission should be taken into full account, meanwhile relevant industry and energy policies should be put in place accordingly, so as to attain the set goal in a fair and effective manner with relatively low social and economic cost.This paper focuses on the discussion of the factors, spillover effect that influence China's carbon emission intensity, with a view to providing therectical support and policy advice for the government in the formation and application of relevant policies on energy saving and emission reduction. Based on the IPCC referece method, the data of carbon emission and its intensity at national and regional level were estimated. Firstly, from the perspective of time serial data, a cointegration analysis was conducted on the influence factors of China's carbon emission intensity. Secondly, based on provincial panel data, the author analyses the evolution trend and regional difference of China's carbon emission intensity. The method of Spatial Statistics Analysis was also used to discuss the spatial distribution features of China's carbon emission intensity from the perspective of spatial agglomation effect and radiation effect. Thirdly, by constructing the absolute convergence, conditional convergence, and club convergence which include spatial effect, the author goes on to examine the convergency feature of carbon emission intensity. Finally, the three models of SLM, SEM and SDM have been employed to examine the reasons lying behind the difference in regional carbon emission reduction, meanwhile separate discussion was devoted to the spatial effect of different factors, so as to get to know the direct effect, indirect effect and overall effect of different variables on carbon emission intensity, to verify whether different variables play a role of significant spatial spillover in the process of spatial change of carbon emission intensity. Based on data characteristic of China's carbon emission intensity, two phases, namely 1997 to 2004, and 2005 to 2013, have been determined, to examine the variable change during different time frame and the evolution trend of spatial spillover effect.Based on the above therectical research and empirical test, the author comes to the following conclusion:(1) There is long and stable cointegration between energy structure, urbanization, per capita GDP and China's carbon emission intensity, with elasticity coefficient of carbon emission intensity at 1.98?0.97 and-0.65, suggesting that an energy structure with heavy reliance on carbon constitutes the biggest barrier in the reduction of China's carbon emission.(2) Carbon emission intensity at provincial level presents obvious spatial correlation, suggesting that the spatial distribution of China's provincial carbon intensity is characterized by obvious spatial reliance, rather than a wholly stochastic state. Provinces having similar carbon emission intensity tend to stay adjacent to each other.(3) The spatial agglomoration of China's carbon emission intensity presents a trend of gradual optimation. During the observation time frame, the scatter diagram of China's carbon emission intensity shows that while the number of those“low-low” agglomorated area is on the rise, the “high-high” agglomorated provinces is on the decrease.(4) Different provinces play different roles and make different contribution in spatial agglomoration of carbon emission intensity. “High-high” agglomorated provinces such as Inner Mogolia, Ningxia, Shanxi and Gansu, unfavorably push up the carbon emission of neigboring regions, while “low-low” agglomorated areas such as Guangdong, Fujian and Zhejiang favorably push down the carbon emission intensity.(5) China's carbon emission intensity is characterized by obvious absolute convergence, conditional convergence, and club convergence. In Club Convergence Model, the convergence speed of the middle and the eastern part is the fastest, while the middle part less fast, and the western part the lowest.(6) The lag item of carbon emission intensity is significantly negative, suggesting that the carbon emission intensity of neighboring areas has an important influence on the carbon emission reduction in the area. Therefore, it is safe to conclude that spatial panel regression is more suitable in analyzing the influence factors of carbon emission intensity.(7) The economic development, ownership system, opening up to the outside world, foreign direct investment is beneficial to carbon emission reduction while the energy structure, energy resources, industry structure and urbanization will increase the regional carbon emission internsity.(8) Technology advance, foreign direct investment, opening up to the outside world, urbanization, energy structure and energy resources have obvious spatial spillover effect, indicating that the change of the above variables not only exert influence on carbon emission intensity in the area, but also extend this influence to neighboring areas through spatial transmission mechanism.(9) Optimizing the structure of foreign direct investment and improving economic growth constitute effective approch to achieving the goal of carbon emission reduction. Finally, based on the analysis and research conclusion, the author put forward some proposals on carbon emission reduction, and goes further to point out the shortcoming of the research, as well as the future research direction. |
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