我国地区节能减排效率的差异及影响因素研究  

Regional Differences of China's Energy-saving and Emission Reduction Efficiency and Its Determinants

作　　者：赵成柏[1,2] 毛春梅[3] 

机构地区：[1]河海大学商学院,江苏南京210098 [2]淮阴工学院经济管理学院,江苏淮安223001 [3]河海大学公共管理学院,江苏南京210098

出　　处：《中国科技论坛》2012年第6期102-108,共7页Forum on Science and Technology in China

基　　金：教育部人文社会科学研究规划基金项目"我国经济增长中的碳排放强度评估及其目标实现路径研究"(11YJA790214);国家统计局科研项目(2010LC70)

摘　　要：能源和环境问题已得到国际社会的共同关注。节能减排已成为我国的基本国策,更是落实科学发展观和构建和谐社会的重要举措。本文在构建节能减排效率评价指标体系的基础上,应用BP人工神经网络方法,对我国30个省市节能减排效率进行综合评估,进而从不同层面分析节能减排效率的区域差异,结果显示:区域梯度分布格局明显,从东向西递减;呈正偏态分布,第三、第四级别的区域比例略大;区域内部差异明显。同时,本文还实证考察了经济发展水平、能源结构、技术进步和制度等因素对节能减排效率的影响效果,并据此给出了一些政策性建议。The paper establishes an index system which can judge the regional energy-saving and emission reduction efficiency, to evalu- ate the energy-saving and emission reduction efficiency in 30 provinces and cities in China by BP artificial neural network, so as to analyze regional differentiation of energy-saving and emission reduction efficiency from different levels. The study shows that ： Energy-saving and emission reduction efficiency has declined from east to west ; Its frequency distribution has positive features, and a bigger proportion of counties in the third degree and fourth degree;Great differentiations appeared within each region. Meanwhile, this paper does econometric analysis on a number of variables which has important effects on energy-saving emission reduction efficiency, including variables relating economy development, energy structure, technology progress and system. The results show that these variables have different effects. Based on this, this paper discusses some policy suggestions.

关 键 词：节能减排效率 BP神经网络 区域差异 

分 类 号：TK018[动力工程及工程热物理]