摘要
能源是经济发展的基本要素之一。近几十年来,西方主要发达国家在经济发展过程中消耗了大量化石能源,使全球有限的化石能源储量成为各国争夺的焦点,化石能源消费带来的温室效应也成为全球各国谈判的难题。随着经济的发展,全球能源消费总量仍将大幅增长,控制能源消费总量和降低能源强度必将成为世界各国共同努力的方向。
中国是世界最大的发展中国家,其人口总量占世界的五分之一。中国必须保持一定的经济增长速度来提高国民生活质量、缓解就业压力和保持社会稳定,短期内不可能通过牺牲经济增长速度来实现能源消费总量降低和二氧化碳排放总量减少。另一方面,作为世界第二大能源生产、消费及碳排放国家,中国也面临更大的节能减排压力。多年来,中国政府一直致力于节能减排并取得了一定成效。中国《国民经济和社会发展第十一个五年规划纲要》提出了“十一五”期间能源强度降低20%的约束性指标,《国民经济和社会发展第十二个五年规划纲要》中再次明确提出了“十二五”期间,能源强度下降16%的约束性指标。节能目标的提出,使中国节能有了量化指标,使中国的战略规划、政策制定和政府监管有了落实的标准,节能目标的实现成为保障中国经济和能源可持续发展的核心问题之一。以较低的资源消耗实现较快的经济增长,对于中国这样一个资源相对贫乏而又必须保持一定经济增长的大国来说,意义重大而深远。
中国幅员辽阔,各地区经济发展水平、科技装备水平和经济结构等存在较大差异,地区间和产业间单位增加值能源消耗存在一定差异,各地区能源强度受非经济结构和经济结构的影响程度也存在差异,这些都使各地区节能潜力存在客观差异。
直观来看,除经济发展水平和科技进步这一影响各地区能源消费和能源强度的主要因素外,经济结构也是影响各地区能源强度的重要原因。目前研究经济发展水平和科技进步等对能源强度影响的成果比较多,对产业结构与能源强度关系的讨论也比较多,但结合中国及各地区实际,对经济结构与能源强度数量规律的研究却较少,尚未有文献对在经济结构约束下中国各地区的节能差异系数进行研究。因此,用计量经济学方法研究中国经济结构与能源强度的数量关系,探索计算各地区节能差异系数的方法,对国家节能政策的制定及节能减排任务的分解和实现具有迫切的现实意义,也是对中国能源经济学理论研究的深化。
在中国经济和能源发展形势的要求下,在总结和借鉴前人的研究成果基础上,本文通过综合运用多种计量经济学方法,对中国经济结构与能源强度之间的关系进行了深入研究,力图揭示它们之间的数量规律,探索计算各地区节能差异系数的方法。本文的研究沿着以下思路进行：首先界定能源强度和经济结构的相关概念；然后检验各种经济结构与能源强度之间数量关系的存在性；随后建立中国能源强度影响因素综合模型,研究经济结构对能源强度的直接影响和间接影响；接着建立各地区能源强度的面板模型,研究各地区经济结构对能源强度的差异性影响；最后建立各地区能源强度对数面板模型,从经济结构差异性角度探索各地区节能差异系数的计算方法。基于以上研究思路,本文的主要内容包括：
1.中国产业结构、需求结构和能源消费结构与能源强度数量关系存在性检验。第四章首先总结了中国产业结构的基本特点,对研究产业结构与能源强度的文献做了回顾。然后采用LMID分解法分解三次产业结构对能源强度的影响,结果表明工业是影响能源强度的主要因素。通过对工业对能源强度影响的进一步分解发现,工业占GDP的比重对能源强度的影响较小,工业行业能源利用效率的提高是影响能源强度的主要因素。为进一步验证工业比重与能源强度之间的数量关系,利用中国30个地区(剔除西藏,下同)的面板数据对工业比重与能源强度进行面板协整检验,结果表明工业比重与能源强度间不存在面板协整关系。为进一步探索产业结构与能源强度之间是否存在数量关系,将工业内部40个行业进行分类,得出12个高耗能行业。通过对30个地区高耗能行业占工业比重与能源强度的面板协整检验,证明高耗能行业比重与能源强度间存在面板协整关系。第五章和第六章分别介绍了中国需求结构和能源消费结构的特点,进一步检验了二者与能源强度之间的数量关系,结果表明需求结构和能源消费结构与能源强度间都存在长期稳定的协整关系。
2.基于通径分析模型揭示了中国经济结构对能源强度直接影响和间接影响的数量规律。第七章在第四章到第六章检验各种经济结构与能源强度数量关系存在性的基础上,选取人均GDP作为影响能源强度的非经济结构因素,选取重工业比重、投资率和煤炭消费比重作为影响中国能源强度的经济结构因素建立能源强度的综合模型。首先检验选取的非经济结构因素和经济结构因素与能源强度之间的协整关系,然后建立通径分析模型,研究经济结构对能源强度的直接影响和间接影响。结果表明,中国重工业比重和投资率对能源强度有正的直接影响和负的总影响,煤炭消费比重对能源强度有正的直接影响和正的总影响。
3.基于固定影响不变斜率面板模型和变斜率面板模型研究了各地区经济结构对能源强度差异影响的数量规律。第八章在第四章到第六章检验各种经济结构与能源强度数量关系存在性的基础上,以及第七章中国经济结构对能源强度影响的数量规律研究基础上,选取人均地区生产总值作为影响能源强度的非经济结构因素,选取高耗能行业比重、投资率和煤炭消费比值作为影响能源强度的经济结构因素建立面板模型。固定影响不变斜率面板模型研究结果表明,地区高耗能行业比重、投资率和煤炭消费比值对能源强度有正的影响,截距项的差异表明不同地区经济结构对能源强度有差异影响,地区经济结构对能源强度影响较大的地区有贵州、青海和宁夏等。变斜率面板模型研究结果表明,不同地区高耗能行业比重和煤炭消费比值均对能源强度有差异影响,地区投资率对能源强度的影响不明显。高耗能行业比重对能源强度影响较大的地区包括宁夏、青海和贵州等,影响较小的地区包括陕西、浙江和云南等。煤炭消费比值对能源强度影响较大的地区包括青海、宁夏和贵州等,影响较小的地区包括陕西、河北和山西等。
4.基于变系数对数面板模型,探索出一种计算中国各地区节能差异系数的方法。根据第八章的研究结果,同时考虑中国各地区影响能源强度的非经济结构因素和经济结构因素,选取人均地区生产总值对数、高耗能行业比重对数和煤炭消费比值对数,建立能源强度的变系数对数面板模型。通过实证模型结果发现,全国和各地区高耗能行业比重对数和煤炭消费比值对数回归系数之比即为基于高耗能行业比重和煤炭消费比值的地区节能差异系数,通过对他们的组合得到各地区综合节能差异系数。计算结果表明,中国的30个地区节能差异系数差距较大。节能差异系数最小的5个地区为江西、江苏、福建、浙江和广东,节能差异系数最大的5个地区为宁夏、青海、贵州、新疆和山西。通过将节能差异系数在“十二五”中国节能目标地区分解的应用中发现,由于充分考虑了影响能源强度的非经济结构影响因素和经济结构影响因素,本文关于各地区节能潜力的计算结果比目前制定的各地区节能任务更合理。
综合全文研究,本文的创新表现在以下三个方面：
1.揭示了中国经济结构对能源强度直接影响和间接影响的数量规律。有不少学者对经济结构与能源强度的关系进行了研究,这些研究基本都只考虑了经济结构对能源强度的直接影响。本文采用通径分析模型,研究了经济结构对能源强度的直接影响和间接影响,更深入的揭示了经济结构对能源强度影响的数量规律。
2.探索出一种从经济结构差异性角度计算各地区节能差异系数的数量方法。“十一五”中国制定全国节能20%的约束性目标以来,有学者对各地区的节能潜力进行了估算,有的以全国能源强度较低的地区作为标准,有的对节能潜力进行了定性分析,但几乎没有文献在各地区经济结构对能源强度的差异性影响约束下计算各地区的节能差异系数。本文通过建立能源强度的对数面板模型,计算得出了各地区节能差异系数。
3.揭示了经济结构对地区能源强度差异影响的数量规律。目前研究中国各地区经济结构与能源强度关系的文献通常从两个角度进行研究,一是单独研究某一地区经济结构对能源强度的影响,二是利用全国各地区经济结构和能源强度数据建立面板回归模型计算经济结构对能源强度的影响,但并没有得出各地区的差异影响。本章采用固定效应不变斜率模型和变斜率模型,研究各地区高耗能行业比重、投资率和煤炭消费比值对地区能源强度的差异性影响,揭示了各地区经济结构对能源强度差异性影响的数量规律。
由于数据来源的限制和作者的条件限制,本文的不足表现在以下几个方面：一是没有定量考虑经济结构的调整和变化。本文计算节能差异系数时,虽然考虑了经济结构对能源强度的影响,但在将节能差异系数进行应用时,实际隐含了各地区产业结构不变的假定。二是面板数据序列不够长。由于中国高耗能行业分类统计从1999年开始,本文计算影响能源强度的重要经济结构变量高耗能行业比重也只能从1999年开始,整个时间跨度仅为12年。由于数据长度限制,本文在变系数面板模型建模时,不得不将非经济结构影响因素和部分经济结构影响因素变量设为不变系数。三是尚未进一步研究全国产业布局对能源强度的影响。产业布局优化是国家产业政策的重要目标之一科学的产业布局能促进能源利用效率的提高,有利于节能降耗目标的实现。科学的产业布局应统筹考虑全国资源分布和技术条件,鉴于本文对产业布局的研究有限,本文没有进一步研究如何通过科学的产业布局提高能源利用效率。
Energy is one of the basic elements of economic development. In the past decades, the major western developed countries have consumed a large amount of fossil energy in the process of economic development.The global limited fossil energy reserves has become a point of contention, fossil energy consumption brings the greenhouse effect has become a global negotiation problem. With the development of economy, the global energy consumption is expected to grow considerably, controlling the total energy consumption and reducing energy intensity will become the world common direction.
China is the largest developing country in the world, its population accounted for1/5of the world's. China must maintain a certain growth rate to improve the national's standard of living, ease the employment pressure and to maintain social stability.Can not to slow economy growth speed to reduce the total energy consumption and total carbon dioxide emissions in short term.On the other hand, as the world's second largest energy production, consumption and carbon emission country, China also faces more pressure of energy conservation and emission reduction.
Over the past years, the Chinese government has been committed to energy-saving emission reduction and achieved certain results. China's" National economy and social development in the Eleventh Five Years Plan" had put forward the energy intensity reduction20%in Eleventh Five Years Plan period,"National economy and social development in the Twelfth Five Years Plan "has put forward clearly again energy intensity decreased in16%in the Twelfth Five-Year Plan period.Energy saving target putted forward,has make China's energy-saving with quantitative indicators, so that China's strategic planning, policy formulation and implementation of government supervision have standards. The implementation of energy-saving target is the guarantee of China's economic and energy sustainable development. China as a relative lack of resources and must maintain a certain economic growth country,to lower the consumption of resources and to achieve rapid economic growth, is significant and far-reaching thing.
China has a vast territory, the economic development level, technology and equipment level and economic structure have big differences in regions.Different influences of non-economic structure and economic structure on regional energy intensity make the energy saving potential different in regions.The visual point of view, in addition to the economic development level and the progress of science and technology, economic structure is the most important factor affecting energy intensity.Current research on the ralationship between the economic development level and the progress of scientific and technological and the energy intensity is more, on the qualitative relationship between industrial structure and energy intensity is more also, but research on the quantitative relationship between the economic structure and energy intensity is less, yet there has no literature on the calculation method of energy-saving difference coefficient under the constraint of economic structure.Therefore, using econometric methods to research the quantitative relationship between China's economic structure and energy intensity, explore the calculation method of energy-saving difference coefficient, has the realistic significance for the national energy conservation policy and energy-saving emission reduction task decomposition and implementation, but also has the theoretical significance for the China's energy economics research.
In the case of China's economy and energy development,based on the previous studies, this article uses a variety of econometric methods, thoroughly researches on the relationship between China's economic structure and energy intensity, tries to reveal the quantities regularity, explores calculation method of energy-saving difference coefficient.This paper studies along the following ideas: first defines the relevant concepts of energy intensity and economic structure; and then examines the existence of quantitative relations between various economic structures and energy intensity;followed by the establishment of China's energy intensity integrated model of influence factors, comes to conclusion quantities regularity of direct effects and indirect effects of economic structure; and then establishes the regional energy intensity panel data model, studies the regional economic structure different influences on energy intensity; finally establishes the regional energy intensity logarithmic panel model, from the economic structure difference angle explores the calculation method of energy-saving difference coefficient. Based on the above research, the main contents of this paper includes four points:
1.Tests the quantitative relationship between the China's industrial structure, demand structure and the structure of energy consumption and energy intensity. The fourth chapter summarizes the characteristics of China's industrial structure, review research literatures on the relationship between industrial structure and energy intensity. And then using the LMID method decomposes the effects of three industrial structure on energy intensity, the results show that industry is the main factor affecting energy intensity. The further decomposition shows that the proportion of industry has small effect, the energy utilization efficiency improving in industry is the main factor affecting energy intensity. In order to further demonstrate the quantitative relationship between the proportion of industry and energy intensity, using30regional panel data of.the proportion of industry and energy intensity to do cointegration test, results show that panel cointegration relationship does not exist between the proportion of industry and energy intensity. In order to further explore the quantitative relationship between the industrial structure and energy intensity, we classify the40industries, draw12high energy-consuming industries. Based on the30regional panel data of the proportion of high energy-consuming industries and energy intensity,we do panel cointegration test,results show that there exists panel cointegration relationship between the proportion of high energy-consuming industries and energy intensity.The fifth chapter and the sixth chapter introduce China's demand structure and energy consumption structure features, and then test the cointegration relationship between them and energy intensity, the results show that there exist long term stability cointegration relationships between the structure of demand and the structure of energy consumption and energy intensity.
2.Based on the model of the path analysis,reveals the quantities regularity of the direct and indirect influences of China's economic structure on energy intensity. In the seventh chapter, based on the fourth chapter to the sixth chapter,we choose GDP per capita as non-economic structure factor, the proportion of heavy industry, investment rate and the proportion of coal consumption as economic structure factors, establish the energy intensity integrated model.At the first, test the cointegration relationship between selected non economic structure factor and economic structure factors and energy intensity, then set up the path analysis model, study the direct and indirect influence of economic structure on energy intensity. The results show that in China, the proportion of heavy industry and investment rate has positive direct effect and negative total effect on the energy intensity,the proportion of coal consumption has positive direct effect and total positive effect on energy intensity.
3.Based on fixed effect panel constant slope model and variable slope panel model of regional economic structure on energy intensity, comes to conclusion the difference influences in regions. In the eighth chapter, based on the fourth chapter to the seventh chapter, researches on the influence of China's economic structure on energy intensity.We selecte per capita GDP as the non economic structure factor, the proportion of high energy-consuming industries, investment rate and coal consumption ratio as economic structure factors to establish the panel data model. the results of fixed effect panel constant slope model show that, the proportion of high energy-consuming industries, investment rate and coal consumption ratio have positive effects on energy intensity.The intercept terms indicate different effects of different regional economy structures on energy intensity, economy structure has more effect on energy intensity in Guizhou, Qinghai and Ningxia. Variable slope panel model results show, the proportion of high energy-consuming industries and the coal consumption ratio have different effects on energy intensity in different regions. effect of investment rate on energy intensity is not obvious.The proportion of high energy-consuming industries has more effect on energy intensity including Ningxia, Qinghai and Guizhou, has little effect including Shaanxi, Zhejiang and Yunnan. Coal consumption ratio has more effect on energy intensity including Qinghai, Ningxia and Guizhou, has little effect including Shaanxi, Hebei and Shanxi.
4.Based on the variable slope logarithm panel model, from the economic structure difference angle explores the calculation method of energy-saving difference coefficient.According to the eighth chapter of the research results, considering the different influences of non-economic structure factor and economic structure factors on energy intensity in regions, selecte logarithmic per capita GDP, logarithmic the proportion of high energy-consuming industries, logarithmic the coal consumption ratio, establish the logarithmic energy intensity panel date model.Through the empirical model results, The ratio of national and regional proportion of high energy consumption industries and coal consumption ratio logarithm regression coefficient is energy-saving difference coefficient based on the high energy-consuming industries and the proportion of coal consumption ratio.The calculation results show that, the energy saving difference coefficients are different in China's30regions, maximums are Jiangxi, Jiangsu, Fujian, Zhejiang and Guangdong.minimums are Ningxia, Qinghai, Guizhou, Xinjiang and Shanxi. Using the coefficients in " Twelfth Five-Year Plan" show that this is more reasonable than the China's energy saving target decomposition application.
In summary, the innovation of this paper followes three aspects:
1.Revealing the quantities regularity of direct and indirect influence of China's economic structure on energy intensity. Many scholars have studied the relationships between the economic structure and energy intensity, these studies have only considered the direct influence of the economic structure on energy intensity.This paper uses the path analysis model, study the direct and indirect influence of the economic structure on energy intensity, further reveals the quantities regularity of the effect of economic structure on energy intensity.
2.Exploring from an economic structure difference angle quantitative calculation method of energy-saving difference coefficient. From "the Eleventh five years", scholars estimate the energy saving potential of various regions, some set the low energy intensity areas as standard, some qualitatively analys the energy saving potential, nobody calculates the energy-saving difference coefficient under the constraint of economic structure. In this paper, through establishing logarithmic energy intensity panel model, we calculate energy-saving difference coefficient under the constraint of economic structure.
3.Revealing the difference ralationships between the economic structures and energy intensity in different regions. Literatures usually from two perspectives research the ralationship between economic structure and energy intensity, separately study an area's economic structure influence on energy intensity, or using regional data,establish panel models for calculating the influence of economic structure on energy intensity. In this paper,we use fixed effect constant slope model and variable slope model, study the different influences of the proportion of high energy-consuming industries, investment rate and coal consumption ratio on regional energy intensity, reveal quantities regularity of difference influences of the regional economic structure on energy intensity.
Certainly,there are some questions in this article,For example, not considered the adjustment of economic structure and change. panel data is not long enough.not further studied the influence of the industrial layout on energy intensity.
引文
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