摘要
本文基于至强有效前沿的最小距离法测算了我国1998-2011年的省际CO2排放效率,这种方法的优点是效率达到生产前沿后在投入或产出方面所做出的改动最小。然后在此基础上分析了我国省际碳排放效率的区域差异性以及空间相关性,最后运用1998-2011年我国30个省份的面板数据,建立空间面板数据模型,对我国碳排放效率的影响因素进行了实证研究。研究结果表明:样本期内,我国省际碳排放效率表现出较大的省际差异性,东部沿海省份的平均碳排放效率显著高于内陆省份。分地区看,东部地区的碳排放效率走势相对平稳,全国及中西部地区的碳排放效率则呈现出"U"型曲线的走势,并且东部地区的碳排放效率明显要高于中西部地区;空间自相关Moran’s I检验显示,省际碳排放效率在空间上存在着显著的空间自相关性,具有明显的集群趋势,而空间LISA图则表明省际碳排放效率不仅具有空间依赖性的特征,同时也有空间异质性的表现;经济规模、工业结构和能源消费结构对碳排放效率造成了较大的负面影响,对外开放、企业所有制结构以及政府干预对碳排放效率有正向影响,而产业结构对碳排放效率的影响则不显著。因此,对于将来中国提高碳排放效率工作的重点应该是实现经济增长模式由粗放型向集约型的转变,着重调整工业结构和能源消费结构,同时进一步提升对外开放的质量,加强政府的碳减排工作力度。
The paper measures the efficiency of inter-provincial carbon dioxide emissions from 1998 to 2011 by using minimum distance algorithm which is strongest frontier. The advantage of this approach is that the change of inputs or outputs is minimum after the efficiency reaching the production frontier. On this basis, we analyze the regional differences and spatial correlation of inter- provincial carbon emissions efficiency. At last, we establish the spatial econometric model to make an empirical study on influence factors of carbon emissions efficiency by using panel data of 30 provinces from 1998 to 2011. The results show that： during the sample period, the efficiency of inter-provincial carbon dioxide emissions shows a large inter-provincial differences, and average carbon emission efficiency in the eastern coastal provinces is significantly higher than of it in the inland provinces. From the perspective of region, the trend of carbon emissions efficiency in the east is relatively stable, but the trend of carbon emissions efficiency in nationwide and midwest China shows a ＂U＂ curve. And the carbon emission efficiency in the east of China is significantly higher than of it in the midwest China. Spatial autocorrelation test Moran＇ s I shows that the efficiency of inter-provincial carbon emissions has the characteristics of spatial correlation and a significant clustering tendency. While LISA space diagram indicates that the inter-provincial carbon emissions efficiency has not only the characteristics of spatial dependence, but also the performance of spatial heterogeneity. The economic scale, industry structure and energy consumption structure have a negative impact on carbon emission efficiency, while opening-up, enterprise ownership structure and government intervention have a positive impact on it. But industrial structure has no significant influence on carbon emission efficiency. Therefore, the focus of the work for future China to improve the carbon emissions efficiency is as below ： realizing the economic growth mode from extensive to intensive, focusing on the adjustment of industrial structure and energy consumption structure, further enhancing the quality of opening-up and strengthening the government＇ s efforts to reduce carbon emission.
出处
《中国人口·资源与环境》
CSSCI
CSCD
北大核心
2015年第1期67-77,共11页
China Population,Resources and Environment
基金
国家社科基金重点项目"新一轮西部大开发的跟踪研究"(编号:11AJL011)
关键词
碳排放效率
空间计量
至强有效前沿的最小距离法
carbon emissions efficiency
spatial econometrics
minimum distance to the strong frontier
