【作者】 李卫坤；

【导师】 李力；

【作者基本信息】 哈尔滨工业大学 ， 管理科学与工程， 2010， 硕士

【摘要】 近些年,由于能源短缺以及能源消费所带来的环境问题日益严重,能源效率研究逐渐成为科学研究者们关注的焦点。而能源效率的评价及影响因素分析是能源效率研究的主要内容。本文以能源效率的评价及影响因素分析作为研究内容,首先对国内外能源效率研究文献进行了详细的综述。综述发现:目前能源效率的评价模型已加入环境污染作为非合意产出变量,但对环境污染变量的处理仍不成熟;能源效率的评价方法主要有数据包络分析(DEA)和随机前沿分析(SFA)两种,两者各有优缺点,还没有一种将两者整合的方法;能源效率的影响因素研究主要集中于外部因素的分析,对内部因素的分析较少。本文基于DEA和SFA提出了综合分析法(D&S),利用全球49个国家1999–2008年的数据对这三种评价模型进行了实证检验,并分析了三种实证结果的相关性、一致性以及稳定性,同时通过对能源效率差异的因素分解,分析和阐明了各内部因素对能效差异的影响机理及贡献值。实证结果表明,通过配对T检验和Spearman和Kendall等级相关系数检验,DEA、SFA与D&S三种方法的评价结果具有显著的相关性和排序上的一致性。从稳定性来看,SFA评价结果的稳定性明显优于DEA,D&S稳定性介于两者之间,但也明显优于DEA,这说明通过SFA剔除随机因素对提高DEA评价结果的稳定性效果显著。样本总体的能源效率值有随时间提升的趋势,中国与样本总体的能源效率存在较大的差距,但中国的能效提升速度略快于样本总体,能源效率差距在不断缩小。通过能源效率差异的因素分解,将能效差异产生的内因归结为能源强度差异、资本–能源比率差异、人力–能源比率差异以及污染–能源比率差异四个部分,皆与能源效率差异负相关。能源强度差异和人力–能源比率差异的对能效差异的贡献率大于资本–能源比率差异和污染–能源比率差异。更多还原

【Abstract】 In recent years, due to energy shortages and increasingly serious environmental problems posed by energy consumption,energy efficiency attracts more and more researchers’attention. The evaluation of energy efficiency and related factors to energy efficiency are the most important aspects in energy efficiency studies.In this paper, the evaluation of energy efficiency and analysis of related factors are the main research content. First of all, domestic and international literature of energy efficiency is reviewed in detail. It is found that: the current evaluation model of energy efficiency has taken the environmental pollution as a non-consensual output variable, but it is still immature when processing environmental pollution variable. Data envelopment analysis (DEA) and Stochastic Frontier Analysis (SFA) are two main methods of energy efficiency evaluation, both of which have advantages and disadvantages, and there is no method to integrate them. Previous studies on related factors to energy efficiency are mostly focused on the analysis of external factors, and less can be seen on internal factors. Based on DEA and SFA, a new integrated analysis method (D&S) was proposed. Panel data from 49 countries during the period of 1999-2008 are used to compute energy efficiency in these three methods. Then, relevance, consistency and stability of the results were analyzed. Through the differentiation decomposition of internal factors of energy this paper further illustrates its mechanism and contribution.The empirical results show as follow: By the paired T test, Spearman and Kendall rank correlation coefficient test, it is proved that evaluation results of DEA, SFA and D&S are significantly relevant and orderly consistent. From the point of view of stability, SFA is much better than D&S, and followed by DEA, which indicate that the stability of evaluation results of DEA is improved obviously by removing random factors via SFA. There is a tendency that energy efficiency values of the overall sample is increasing over time, while, a big gap about this value still do exist between China and overall sample and this gap tends to gradually narrow, meanwhile, China’s efficiency increases faster than that of over sample. Differences in energy efficiency are decomposed into four factors, that is, energy intensity, capital-energy ratio, human-energy ratio and energy-pollution ratio. All factors are negatively correlated with energy efficiency, and their contribution rate of energy intensity and human-energy ratio to the differences in energy efficiency is greater than capital-energy ratio and energy-pollution ratio.更多还原