技术进步视角下中国能源效率的测算与实证分析
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摘要
能源问题是我国经济发展过程中的焦点和热点问题。十二五规划提出深入贯彻节约资源和保护环境基本国策,节约能源,降低温室气体排放强度,发展循环经济,走可持续发展之路。能源是人类活动的物质基础,影响着经济、社会的发展,而能源效率被称为“第五类能源”。提高能源效率、节能减排是建设两型社会的重要途径,对可持续发展有着重要的意义。
能源效率的涵义是什么,以及能源效率如何测算?为了明确能源效率测算方面的理论模型,我们对相关的研究进行了梳理,认为全要素能源效率模型更适合来描述中国的能源效率水平。为了更好的比较同处于效率前沿的决策单元(即省份、地区或产业部门)的效率,我们运用超效率DEA模型对其进行估算。而为了更好的估计能源消耗过程中所造成的环境污染问题,我们利用MLT方法的或者INP方法对非期望产出进行转换,并且运用了DEA-SBM模型对加入非期望产出的全要素能源效率进行测算。
我国和世界发达国家的能源效率水平究竟有多大的差距?知识要素对能源效率水平的影响如何?加入非期望产出的中国能源效率呈现怎样的特征?我们基于全要素能源效率模型,结合超效率DEA方法,对我国与其他OECD国家的能源效率进行估算和比较,发现能源消耗强度指标会相对夸大能源效率差距。而当考虑知识投入时,中国与能源效率先进水平国家差距比未考虑的情形反而拉大了为了进一步细致区分中国区域能源效率的情况,我们基于CCR模型测算了1995年——2009年中国八大综合经济区全要素能源效率；然后分别用INP方法和MLT方法处理了非期望产出,并将其纳入了DEA模型后,对1989-2009年中国省际全要素能源效率进行了测算；运用DEA-SBM模型对加入了非期望产出的全要素能源效率进行了估计,得到了1989-2009年中国29个省份包含环境约束的全要素能源效率。我们发现,中国地区之间的能源效率在横向来看,呈现东高西低的局面,在纵向来看,呈现先升高后微弱下降的一个趋势,其转折点大概在2000年左右。其可能的解释是,经济发达地区运用先进的管理和技术,提高能源效率,而能源消耗较多的地方的产业结构和能源消费结构都不利于能源效率的提高；转折点的出现可能是由于产业结构的调整进入重工业化阶段所致。
中国各地区的能源利用效率水平的差距是否会随着时间的推移而缩小?能源消耗强度和全要素能源效率是否会最终收敛?为此,我们对所得到的能源消耗强度、全要素能源效率进行了收敛分析。在验证能源利用效率的绝对p收敛时,我们发现能源消耗强度、使用MLT方法的全要素能源效率以及使用DEA-SBM模型的全要素能源效率都存在绝对β收敛,即能源利用效率落后的地区通过加速提高能源使用的利用程度,节约能源,可以缩小了与能源利用效率先进地区的差距。而后,为了我们加入了四个控制变量,分别是加入了产业结构、能源消费结构、对外开放程度以及劳动力平均实际GDP增长率,运用面板数据模型对三个能源利用效率进行了计量分析,进一步分析中国各省、地区的能源利用效率是否存在条件p收敛?实证的结果同时表明,三个能源利用效率均存在条件p收敛,且都在1%或者100%的显著性水平下通过检验,其中劳动力平均实际GDP增长率与对外开放程度的系数一般为正,而产业结构、能源消费结构的系数一般为负,但不同的估计所使用的模型不同。
在分析了影响能源效率的因素后,本文着重强分析了技术进步对能源效率的提升作用。首先运用DEA—Malmquist指数估计方法,将全要素生产率进行分解为技术进步、技术效率。从分解的结果看,2005—2009年,制造业全要素生产率的平均增长率约为7%,累计增长率为30%,总体上呈现了上升的态势。其中技术进步对全要素生产率的提升起了较大贡献,平均增长率为5.6%,而技术效率却仅为1.3%。以2007年为分界,2005—2007年,我国制造业总体的全要素生产率为上升阶段,2007—2009年为下降阶段。其次,为了研究技术进步对全要素生产率及对全要素能源效率的影响,重点针对2005—2009年制造业29个行业展开研究。从回归结果中可以发现,科技人员、技术引进、吸收能力、FDI对技术进步影响均比较显著。此外,技术引进对制造业技术进步并没有积极的推动作用,反而对其产生了较为明显的抑制作用,而技术吸收能力对制造业技术进步有较为明显的推动作用。
最后,本文认为中国能源效率整体上仍然偏低,但结合本论文的分析,我们可以通过产业结构调整,地区之间加强技术交流和技术扩散,改变经济发展方式,增强技术研发能力等来提升中国各区域的能源效率,实现节约能源,保护环境,从而破解资源、环境的约束。
Energy is always being the focus and central issue in the process of China's economic development. The12th Five-Year Plan proposed that we implement thoroughly the basic national policy of conserving resources and protecting the environment, save energy and reduce the intensity of greenhouse gas emissions, develop cyclic economy, and take the road of sustainable development. Energy is the material base of human activities, and impacts economy and society. Energy efficiency was known as "the fifth energy". Enhancing energy efficiency, saving energy and emission reduction of pollution are important ways for constructing resource-conserving, environment-friendly society, which also means a lot to sustainable development.
What is the meaning of energy efficiency, and how to measure energy efficiency? In order to clarify the aspects of energy efficiency and the theoretical calculating model, we sort out the relevant studies and argue that the total factor energy efficiency model is a more suitable one to describe the level of China's energy efficiency. In order to better compare the efficiency of the same efficiency forefront of decision making units (i.e. province, region or industry sector), we need to use super-efficiency DEA model to estimate their energy efficiency. In order to better estimate the environmental pollution problems in the course of the energy consumption, we need to use the MLT method or INP method to convert undesirable outputs, or use DEA-SBM model to calculate the total factor energy efficiency, which includes undesirable outputs.
What is the meaning of energy efficiency, and how to measure energy efficiency? In order to clarify aspects of energy efficiency, the theoretical model calculation, we sort out the relevant studies were that the total factor energy efficiency model is more suitable to describe the level of China's energy efficiency. In order to better compare the efficiency of the same in the forefront of decision making units (i.e., province, region or industry sector) efficiency, we need to use their super-efficiency DEA model to estimate. In order to better estimate the energy consumed in the course of the environmental pollution problems, we need to use the MLT method or INP method to convert undesirable outputs, and the use of DEA-SBM model, inclusion of non-expected energy output of all elements Efficiency measure.
What is the energy efficiency gap between China and the world's developed countries? How does the knowledge factor impact the level of energy efficiency? What are the characteristics of energy efficiency China when the model includes the undesirable outputs? Based on total factor energy efficiency model, using the method of super-efficiency DEA approach, we find that the energy intensity indicators would exaggerate the relative gap of the energy efficiency between China and other OECD countries. When we take to knowledge investment into account, the results tell us that the gap between China and other countries becomes bigger rather than the case without considering knowledge factor. To further distinguish detailed regional energy efficiency in China, we use CCR model to estimate full-factor energy efficiency of eight China's comprehensive economic zone for period1995-2009. And then we use MLT and INP method respectively to deal with the undesirable output, which also are included in the DEA model as inputs, and calculate the Chinese Provinces'total factor energy efficiency for period1989-2009. We use DEA-SBM model to estimate29provinces'energy efficiency of China for period1989-2009, to accurately find out the constraints of environmental elements. We discover that, in the lateral view, the China's energy efficiency shows the gap among eastern China, middle China and the western still exists and is yawning, and eastern China is of highest energy efficiency region. In the longitudinal view, there is a slight decline after the first increase in a trend, and the turning point is around2000. The possible explanation is that economically developed areas have better management and use of advanced technology to improve energy efficiency, and the local industrial structure and energy consumption structure of those places with more energy consumption are not conducive to enhance energy efficiency; turning point may be due to the industrial structure enter the stage of heavy industrialization adjustment.
Will the gap of energy efficiency among various regions of China get smaller as time goes on? Will energy consumption intensity and total factor energy efficiency eventually converge? To answer these questions, we analyze empirically the convergence of the energy consumption intensity and total factor analysis energy efficiency. When we test whether there are absolute (3convergence of energy efficiency, we found that energy consumption intensity, the on total factor energy efficiency using of MLT and total factor energy efficiency using DEA-SBM model the all show absolute β convergence, which means the backward areas of energy efficiency could accelerate the level of utilization of energy use and energy conservation, to narrow the gap between it and region with advanced energy efficiency. Then, we use four control variables, such as the industrial structure, energy consumption structure, openness, and the growth rate of per labor force real GDP respectively. We further analysis whether there is conditional β convergence of the energy efficiency of Chinese provinces or regions, using of panel data model to empirically analyze three energy efficiencies. The empirical results also showed that there are conditional β convergences of those energy efficiencies, which have pass significance test at the level of1%or10%respectively. As a whole, the growth rate of per labor force real GDP and the coefficient of openness are generally positive, and the industrial structure, the energy consumption structure coefficients are generally negative, by different estimates of the models.
After the analysis of the factors affecting energy efficiency, the dissertation highlights the important role of the technological advances enhancing energy efficiency. Firstly, we will use the DEA-Malmquist index estimation method to decompose total factor productivity into technical progress, technical efficiency. We would know from the decomposition results. For period2005-2009, the average TFP growth rate of manufacturing industry is about7%, the cumulative growth rate is about30%, generally showed an upward trend. Technological advance has played a large contribution to enhance the total factor productivity, whose average growth rate is about5.6%, while the average growth rate of technical efficiency is only1.3%. And the period is divided the year of2007. For period2005-2007, the production rate of Chinese manufacturing industry overall increases. However, the period of2007-2009is as the stage of decline phase. Secondly, in order to analyze how the technical progress effect on total factor productivity and total factor energy efficiency, we focus on studying29manufacturing industries for period2005-2009. The empirical results show that scientists, the introduction of technology, absorption Capacity of technology, FDI impact on technological progress are significant. In addition, the introduction of technology for technological progress of the manufacturing industry does not show a positive role, in contrast, it inhibits technological progress. And absorption capacity of technology of technological progress of manufacturing industry has a more significant positive role.
Finally, the dissertation argues that China's energy efficiency is still low. By the analysis in this dissertation, we could adjust the industrial structure, strengthen technical exchanges and technology diffusion among regions, change the mode of economic development, and enhance technological research and development capabilities to enhance energy efficiency of China's regions to save energy, protect environment, and thus break the constraints of resources and environment.
能源效率的涵义是什么,以及能源效率如何测算?为了明确能源效率测算方面的理论模型,我们对相关的研究进行了梳理,认为全要素能源效率模型更适合来描述中国的能源效率水平。为了更好的比较同处于效率前沿的决策单元(即省份、地区或产业部门)的效率,我们运用超效率DEA模型对其进行估算。而为了更好的估计能源消耗过程中所造成的环境污染问题,我们利用MLT方法的或者INP方法对非期望产出进行转换,并且运用了DEA-SBM模型对加入非期望产出的全要素能源效率进行测算。
我国和世界发达国家的能源效率水平究竟有多大的差距?知识要素对能源效率水平的影响如何?加入非期望产出的中国能源效率呈现怎样的特征?我们基于全要素能源效率模型,结合超效率DEA方法,对我国与其他OECD国家的能源效率进行估算和比较,发现能源消耗强度指标会相对夸大能源效率差距。而当考虑知识投入时,中国与能源效率先进水平国家差距比未考虑的情形反而拉大了为了进一步细致区分中国区域能源效率的情况,我们基于CCR模型测算了1995年——2009年中国八大综合经济区全要素能源效率；然后分别用INP方法和MLT方法处理了非期望产出,并将其纳入了DEA模型后,对1989-2009年中国省际全要素能源效率进行了测算；运用DEA-SBM模型对加入了非期望产出的全要素能源效率进行了估计,得到了1989-2009年中国29个省份包含环境约束的全要素能源效率。我们发现,中国地区之间的能源效率在横向来看,呈现东高西低的局面,在纵向来看,呈现先升高后微弱下降的一个趋势,其转折点大概在2000年左右。其可能的解释是,经济发达地区运用先进的管理和技术,提高能源效率,而能源消耗较多的地方的产业结构和能源消费结构都不利于能源效率的提高；转折点的出现可能是由于产业结构的调整进入重工业化阶段所致。
中国各地区的能源利用效率水平的差距是否会随着时间的推移而缩小?能源消耗强度和全要素能源效率是否会最终收敛?为此,我们对所得到的能源消耗强度、全要素能源效率进行了收敛分析。在验证能源利用效率的绝对p收敛时,我们发现能源消耗强度、使用MLT方法的全要素能源效率以及使用DEA-SBM模型的全要素能源效率都存在绝对β收敛,即能源利用效率落后的地区通过加速提高能源使用的利用程度,节约能源,可以缩小了与能源利用效率先进地区的差距。而后,为了我们加入了四个控制变量,分别是加入了产业结构、能源消费结构、对外开放程度以及劳动力平均实际GDP增长率,运用面板数据模型对三个能源利用效率进行了计量分析,进一步分析中国各省、地区的能源利用效率是否存在条件p收敛?实证的结果同时表明,三个能源利用效率均存在条件p收敛,且都在1%或者100%的显著性水平下通过检验,其中劳动力平均实际GDP增长率与对外开放程度的系数一般为正,而产业结构、能源消费结构的系数一般为负,但不同的估计所使用的模型不同。
在分析了影响能源效率的因素后,本文着重强分析了技术进步对能源效率的提升作用。首先运用DEA—Malmquist指数估计方法,将全要素生产率进行分解为技术进步、技术效率。从分解的结果看,2005—2009年,制造业全要素生产率的平均增长率约为7%,累计增长率为30%,总体上呈现了上升的态势。其中技术进步对全要素生产率的提升起了较大贡献,平均增长率为5.6%,而技术效率却仅为1.3%。以2007年为分界,2005—2007年,我国制造业总体的全要素生产率为上升阶段,2007—2009年为下降阶段。其次,为了研究技术进步对全要素生产率及对全要素能源效率的影响,重点针对2005—2009年制造业29个行业展开研究。从回归结果中可以发现,科技人员、技术引进、吸收能力、FDI对技术进步影响均比较显著。此外,技术引进对制造业技术进步并没有积极的推动作用,反而对其产生了较为明显的抑制作用,而技术吸收能力对制造业技术进步有较为明显的推动作用。
最后,本文认为中国能源效率整体上仍然偏低,但结合本论文的分析,我们可以通过产业结构调整,地区之间加强技术交流和技术扩散,改变经济发展方式,增强技术研发能力等来提升中国各区域的能源效率,实现节约能源,保护环境,从而破解资源、环境的约束。
Energy is always being the focus and central issue in the process of China's economic development. The12th Five-Year Plan proposed that we implement thoroughly the basic national policy of conserving resources and protecting the environment, save energy and reduce the intensity of greenhouse gas emissions, develop cyclic economy, and take the road of sustainable development. Energy is the material base of human activities, and impacts economy and society. Energy efficiency was known as "the fifth energy". Enhancing energy efficiency, saving energy and emission reduction of pollution are important ways for constructing resource-conserving, environment-friendly society, which also means a lot to sustainable development.
What is the meaning of energy efficiency, and how to measure energy efficiency? In order to clarify the aspects of energy efficiency and the theoretical calculating model, we sort out the relevant studies and argue that the total factor energy efficiency model is a more suitable one to describe the level of China's energy efficiency. In order to better compare the efficiency of the same efficiency forefront of decision making units (i.e. province, region or industry sector), we need to use super-efficiency DEA model to estimate their energy efficiency. In order to better estimate the environmental pollution problems in the course of the energy consumption, we need to use the MLT method or INP method to convert undesirable outputs, or use DEA-SBM model to calculate the total factor energy efficiency, which includes undesirable outputs.
What is the meaning of energy efficiency, and how to measure energy efficiency? In order to clarify aspects of energy efficiency, the theoretical model calculation, we sort out the relevant studies were that the total factor energy efficiency model is more suitable to describe the level of China's energy efficiency. In order to better compare the efficiency of the same in the forefront of decision making units (i.e., province, region or industry sector) efficiency, we need to use their super-efficiency DEA model to estimate. In order to better estimate the energy consumed in the course of the environmental pollution problems, we need to use the MLT method or INP method to convert undesirable outputs, and the use of DEA-SBM model, inclusion of non-expected energy output of all elements Efficiency measure.
What is the energy efficiency gap between China and the world's developed countries? How does the knowledge factor impact the level of energy efficiency? What are the characteristics of energy efficiency China when the model includes the undesirable outputs? Based on total factor energy efficiency model, using the method of super-efficiency DEA approach, we find that the energy intensity indicators would exaggerate the relative gap of the energy efficiency between China and other OECD countries. When we take to knowledge investment into account, the results tell us that the gap between China and other countries becomes bigger rather than the case without considering knowledge factor. To further distinguish detailed regional energy efficiency in China, we use CCR model to estimate full-factor energy efficiency of eight China's comprehensive economic zone for period1995-2009. And then we use MLT and INP method respectively to deal with the undesirable output, which also are included in the DEA model as inputs, and calculate the Chinese Provinces'total factor energy efficiency for period1989-2009. We use DEA-SBM model to estimate29provinces'energy efficiency of China for period1989-2009, to accurately find out the constraints of environmental elements. We discover that, in the lateral view, the China's energy efficiency shows the gap among eastern China, middle China and the western still exists and is yawning, and eastern China is of highest energy efficiency region. In the longitudinal view, there is a slight decline after the first increase in a trend, and the turning point is around2000. The possible explanation is that economically developed areas have better management and use of advanced technology to improve energy efficiency, and the local industrial structure and energy consumption structure of those places with more energy consumption are not conducive to enhance energy efficiency; turning point may be due to the industrial structure enter the stage of heavy industrialization adjustment.
Will the gap of energy efficiency among various regions of China get smaller as time goes on? Will energy consumption intensity and total factor energy efficiency eventually converge? To answer these questions, we analyze empirically the convergence of the energy consumption intensity and total factor analysis energy efficiency. When we test whether there are absolute (3convergence of energy efficiency, we found that energy consumption intensity, the on total factor energy efficiency using of MLT and total factor energy efficiency using DEA-SBM model the all show absolute β convergence, which means the backward areas of energy efficiency could accelerate the level of utilization of energy use and energy conservation, to narrow the gap between it and region with advanced energy efficiency. Then, we use four control variables, such as the industrial structure, energy consumption structure, openness, and the growth rate of per labor force real GDP respectively. We further analysis whether there is conditional β convergence of the energy efficiency of Chinese provinces or regions, using of panel data model to empirically analyze three energy efficiencies. The empirical results also showed that there are conditional β convergences of those energy efficiencies, which have pass significance test at the level of1%or10%respectively. As a whole, the growth rate of per labor force real GDP and the coefficient of openness are generally positive, and the industrial structure, the energy consumption structure coefficients are generally negative, by different estimates of the models.
After the analysis of the factors affecting energy efficiency, the dissertation highlights the important role of the technological advances enhancing energy efficiency. Firstly, we will use the DEA-Malmquist index estimation method to decompose total factor productivity into technical progress, technical efficiency. We would know from the decomposition results. For period2005-2009, the average TFP growth rate of manufacturing industry is about7%, the cumulative growth rate is about30%, generally showed an upward trend. Technological advance has played a large contribution to enhance the total factor productivity, whose average growth rate is about5.6%, while the average growth rate of technical efficiency is only1.3%. And the period is divided the year of2007. For period2005-2007, the production rate of Chinese manufacturing industry overall increases. However, the period of2007-2009is as the stage of decline phase. Secondly, in order to analyze how the technical progress effect on total factor productivity and total factor energy efficiency, we focus on studying29manufacturing industries for period2005-2009. The empirical results show that scientists, the introduction of technology, absorption Capacity of technology, FDI impact on technological progress are significant. In addition, the introduction of technology for technological progress of the manufacturing industry does not show a positive role, in contrast, it inhibits technological progress. And absorption capacity of technology of technological progress of manufacturing industry has a more significant positive role.
Finally, the dissertation argues that China's energy efficiency is still low. By the analysis in this dissertation, we could adjust the industrial structure, strengthen technical exchanges and technology diffusion among regions, change the mode of economic development, and enhance technological research and development capabilities to enhance energy efficiency of China's regions to save energy, protect environment, and thus break the constraints of resources and environment.
引文
①有关能源进出口的数据均来源于《中国能源统计年鉴——2010》。
②有关能源强度的倒U型曲线规律,可以参看WWF(1991)、Sun(1999)。
①《中共中央关于制定国民经济和社会发展第十二个五年规划的建议》
①国务院发展研究中心,《地区协调发展的战略和政策》,2005。
①中国社科院经济研究所,中国圈经济增长与宏观稳定课题组,《经济研究》2010年第5期。
①具体的证明和详细过程可以参考Scheel(2001)和Seiford and Zhu (2002).
②李廉水,周勇(2006)。
①涂正革,肖耿,2006
①王珊珊,屈小娥(2011)
①Gale A. Boyd and Joseph X. Pang.Estimating the linkage between energy efficiency and productivity.2000
②可以参见J. L. Hu, S. C. Wang, "Total-factor Energy Efficiency of Regions in China, "
①具体的论证可以参考Findley(1978)、Koizumi和 Kopecky(1977)、Wang(1990)、Rivera Batiz(1991)、(?)可洁(2000)。
②可参见刘小玄、李利英(2005)。
①这类文献可以参看Romer(1990)、Young (1998)、秦晓钟(1998)、何洁(2000)、姜奇平(2004)等。
②有关支持FDI对东道国技术进步正向促进观点的有姚洋(1998)、沈坤荣(1999)、胡祖六(2004)等。
①参见Rachel van Elkan(1996), Barro(1997), Acemoglu,et al.(2006)，易先忠(2008)。
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②有关能源强度的倒U型曲线规律,可以参看WWF(1991)、Sun(1999)。
①《中共中央关于制定国民经济和社会发展第十二个五年规划的建议》
①国务院发展研究中心,《地区协调发展的战略和政策》,2005。
①中国社科院经济研究所,中国圈经济增长与宏观稳定课题组,《经济研究》2010年第5期。
①具体的证明和详细过程可以参考Scheel(2001)和Seiford and Zhu (2002).
②李廉水,周勇(2006)。
①涂正革,肖耿,2006
①王珊珊,屈小娥(2011)
①Gale A. Boyd and Joseph X. Pang.Estimating the linkage between energy efficiency and productivity.2000
②可以参见J. L. Hu, S. C. Wang, "Total-factor Energy Efficiency of Regions in China, "
①具体的论证可以参考Findley(1978)、Koizumi和 Kopecky(1977)、Wang(1990)、Rivera Batiz(1991)、(?)可洁(2000)。
②可参见刘小玄、李利英(2005)。
①这类文献可以参看Romer(1990)、Young (1998)、秦晓钟(1998)、何洁(2000)、姜奇平(2004)等。
②有关支持FDI对东道国技术进步正向促进观点的有姚洋(1998)、沈坤荣(1999)、胡祖六(2004)等。
①参见Rachel van Elkan(1996), Barro(1997), Acemoglu,et al.(2006)，易先忠(2008)。
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