用能权交易制度能否实现能耗总量和强度“双控”?
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摘要
用能权交易是我国一项重要的制度创新,对于推进经济可持续发展有着深远意义。为了探讨用能权交易制度能否实现能耗总量和强度"双控"的任务目标,本文首先测度了用能权交易模式下的最优能源投入和期望产出,并以此为基础,构建了一个改进的综合能源强度变化的分解模型。借助2001—2015年30个省份三大产业的投入产出数据,量化分析了三个"五年计划"期间中国能源强度变化及其影响因素。研究发现:(1)中国第三产业的经济增长潜能最大,第一产业次之,第二产业最小。同时发现,第二产业能耗偏高,应该让渡部分用能权,而第一、第三产业还可以适当提高能源消费,以实现资源配置的帕累托最优。(2)地区效应是影响能源强度变化的重要因素,而地区内部的产业结构效应对能源强度变化的影响较小。这意味着中国能源市场的分割、要素扭曲主要来自于省际间的资源贸易壁垒,而在地区内部的产业结构并不存在该壁垒,"诸侯经济"的现象依旧存在。(3)用能权交易模式下的能源强度相比于实际的能源强度能下降约14. 02%,总能耗下降7. 07%。通过用能权交易制度,使能源在省际间产业内进行跨期流通(时间和空间两个维度上),能够实现资源合理利用,经济更加平衡充分地发展,进而实现能耗总量和能源强度"双控"的任务。
Energy-Consuming Right( ECR) is an important institutional innovation in China,which has far-reaching significance for promoting the green economy. In order to explore whether the Energy-Consuming Right Transaction System can achieve the dual control of both energy consumptions and intensity,this paper measured the policy dividends under the two modes of Command and Control as well as Tradable Permits. Based on this,an improved integrated energy intensity decomposition model was constructed. Using the input-output data of the three major industries in 30 provinces from year 2001 to 2015,it quantitatively analyzed the changes of China's energy intensity and their influencing factors. The findings were as follows:(1) China's tertiary industry had the greatest potential for economic growth,followed by the primary industry and the secondary industry. At the same time,we found that the energy consumption of the secondary industry was high,and some of the energy should be given away,while the primary and tertiary industries could also appropriately increase energy consumption to achieve the Pareto optimality of resource allocation.(2)The regional effect was an important factor affecting the change of energy intensity,and the effect of the industrial structure within the region on the change of energy intensity was small. This showed that the fragmentation of China's energy market and its distortions were mainly attributed to the inter-provincial barriers to resource trade. However,this barrier did not exist in the industrial structure within the region. The phenomenon of‘prince economy'still existed.(3)The energy intensity under the Tradable Permits model could be reduced by about14. 02% compared to the actual energy intensity,and the total energy consumption was decreased by 7. 07%. By using the EnergyConsuming Right Transaction System,energy could be inter-periodically and inter-provincially distributed( in both time and space),resources could be used rationally,and economy could be more balanced and fully developed,thus realizing‘dual control'task of total energy consumption and energy intensity.
Energy-Consuming Right( ECR) is an important institutional innovation in China,which has far-reaching significance for promoting the green economy. In order to explore whether the Energy-Consuming Right Transaction System can achieve the dual control of both energy consumptions and intensity,this paper measured the policy dividends under the two modes of Command and Control as well as Tradable Permits. Based on this,an improved integrated energy intensity decomposition model was constructed. Using the input-output data of the three major industries in 30 provinces from year 2001 to 2015,it quantitatively analyzed the changes of China's energy intensity and their influencing factors. The findings were as follows:(1) China's tertiary industry had the greatest potential for economic growth,followed by the primary industry and the secondary industry. At the same time,we found that the energy consumption of the secondary industry was high,and some of the energy should be given away,while the primary and tertiary industries could also appropriately increase energy consumption to achieve the Pareto optimality of resource allocation.(2)The regional effect was an important factor affecting the change of energy intensity,and the effect of the industrial structure within the region on the change of energy intensity was small. This showed that the fragmentation of China's energy market and its distortions were mainly attributed to the inter-provincial barriers to resource trade. However,this barrier did not exist in the industrial structure within the region. The phenomenon of‘prince economy'still existed.(3)The energy intensity under the Tradable Permits model could be reduced by about14. 02% compared to the actual energy intensity,and the total energy consumption was decreased by 7. 07%. By using the EnergyConsuming Right Transaction System,energy could be inter-periodically and inter-provincially distributed( in both time and space),resources could be used rationally,and economy could be more balanced and fully developed,thus realizing‘dual control'task of total energy consumption and energy intensity.
引文
[1]林伯强,吴微.中国现阶段经济发展中的煤炭需求[J].中国社会科学,2018(2):141-161.
[2]陈诗一,陈登科.中国资源配置效率动态演化---纳入能源要素的新视角[J].中国社会科学,2017(4):67-83.
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[4]韩英夫,黄锡生.论用能权的法理属性及其立法控索[J].理论与改革,2017(4):159-169.
[5]刘明明.论构建中国用能权交易体系的制度衔接之维[J].中国人口·资源与环境,2017,27(10):217-224.
[6]COASE R H.The problem of social cost[J].The journal of law and economics,1960,3(1):1-44.
[7]安崇义,唐跃军.排放权交易机制下企业碳减排的决策模型研究[J].经济研究,2012(8):45-58.
[8]吴力波,钱浩祺,汤维祺.基于动态边际减排成本模拟的碳排放权交易与碳税选择机制[J].经济研究,2014(9):48-61.
[9]范庆泉,周县华,张同斌.动态环境税外部性,污染累积路径与长期经济增长---兼论环境税的开征时点选择问题[J].经济研究,2016,51(8):116-128.
[10]BRNNLUND R,CHUNG Y,FRE R,et al.Emissions trading and profitability:the Swedish pulp and paper industry[J].Environmental and resource economics,1998,12(3):345-356.
[11]BRNNLUND U,LINDBERG P O,NOU A,et al.Railway timetabling using Lagrangian relaxation[J].Transportation science,1998,32(4):358-369.
[12]FRE R,GROSSKOPF S,PASURKA C.Potential gains from trading bad outputs:the case of US electric power plants[J].Resource and energy economics,2014,36(1):99-112.
[13]FRE R,GROSSKOPF S,PASURKA C.Tradable permits and unrealized gains from trade[J].Energy economics,2013,40:416-424.
[14]涂正革,谌仁俊.排污权交易机制在中国能否实现波特效应?[J].经济研究,2015,50(7):160-173.
[15]WANG K,WEI Y M,HUANG Z.Potential gains from carbon emissions trading in China:a DEA based estimation on abatement cost savings[J].Omega,2016,63:48-59.
[16]周五七.能源价格,效率增进及技术进步对工业行业能源强度的异质性影响[J].数量经济技术经济研究,2016,33(2):130-143.
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[18]ANG B W.LMDI decomposition approach:a guide for implementation[J].Energy policy,2015,86:233-238.
[19]涂正革.中国的碳减排路径与战略选择[J].中国社会科学,2012(3):78-94.
[20]WU L,KANEKO S,MATSUOKA S.Driving forces behind the stagnancy of China’s energy-related CO2emissions from 1996 to1999:the relative importance of structural change,intensity change and scale change[J].Energy policy,2005,33(3):319-335.
[21]王锋,吴丽华,杨超.中国经济发展中碳排放增长的驱动因素研究[J].经济研究,2010,45(2):123-136.
[22]涂正革,谌仁俊.工业化,城镇化的动态边际碳排放量研究---基于LMDI“两层完全分解法”的分析框架[J].中国工业经济,2013(9):31-43.
[23]WANG C.Decomposing energy productivity change:a distance function approach[J].Energy,2007,32(8):1326-1333.
[24]林伯强,毛东昕.中国碳排放强度下降的阶段性特征研究[J].金融研究,2014(8):101-117.
[25]林伯强,杜克锐.理解中国能源强度的变化:一个综合的分解框架[J].世界经济,2014(4):69-87.
[26]AROCENA P,GMEZ-PLANA A G,PEA S.A decomposition of the energy intensity change in Spanish manufacturing[R].Springer international publishing,2016.
[27]刘朝,周宵宵,张欢,等.中国居民能源消费间接回弹效应测算:基于投入产出和再分配模型的研究[J].中国社会科学,2018(10):142-157.
[28]FRE R,GROSSKOPF S,PASURKA C.Environmental production functions and environmental directional distance functions[J].Energy,2007,32(7):1055-1066.
[29]王兵,吴延瑞,颜鹏飞.环境管制与全要素生产率增长:APEC的实证研究[J].经济研究,2008(5):19-32.
[30]WU Y.China’s capital stock series by region and sector[J].Frontiers of economics in China,2016,11(1):156-173.
[31]徐现祥,周吉梅,舒元.中国省区三次产业资本存量估计[J].统计研究,2007,24(5):6-13.
[32]MA C,STERN D I.China’s changing energy intensity trend:a decomposition analysis[J].Energy economics,2008,30(3):1037-1053.
[33]陈诗一.能源消耗,二氧化碳排放与中国工业的可持续发展[J].经济研究,2009,44(4):41-55.
[34]袁鹏.中国能源需求增长的因素分解[J].数量经济技术经济研究,2014(11):70-85.
[35]王兵,刘光天.节能减排与中国绿色经济增长---基于全要素生产率的视角[J].中国工业经济,2015(5):57-69.
[36]陈诗一.边际减排成本与中国环境税改革[J].中国社会科学,2011(3):85-100.
[37]王兵,於露瑾,杨雨石.碳排放约束下中国工业行业能源效率的测度与分解[J].金融研究,2013(10):128-141.
[38]董香书,肖翔.“振兴东北老工业基地”有利于产值还是利润?---来自中国工业企业数据的证据[J].管理世界,2017(7):24-34.
[39]邓健,王新宇.区域发展战略对我国地区能源效率的影响---以东北振兴和西部大开发战略为例[J].中国软科学,2015(10):146-154.
[40]LAI P,DU M,WANG B,et al.Assessment and decomposition of total factor energy efficiency:an evidence based on energy shadow price in China[J].Sustainability,2016,8(5):408.
[41]刘瑞明,赵仁杰.西部大开发:增长驱动还是政策陷阱---基于PSM-DID方法的研究[J].中国工业经济,2015(6):32-43.
[42]李兰冰.中国能源绩效的动态演化,地区差距与成因识别---基于一种新型全要素能源生产率变动指标[J].管理世界,2015(11):40-52.
[43]宋马林,金培振.地方保护,资源错配与环境福利绩效[J].经济研究,2016(12):47-61.
[44]林伯强,杜克锐.要素市场扭曲对能源效率的影响[J].经济研究,2013(9):125-136.
[45]孙传旺,林伯强.中国工业能源要素配置效率与节能潜力研究[J].数量经济技术经济研究,2014(5):86-99.
[46]魏楚,郑新业.能源效率提升的新视角---基于市场分割的检验[J].中国社会科学,2017(10):90-111.
[47]郑毓盛,李崇高.中国地方分割的效率损失[J].中国社会科学,2003(1):64-72.
[2]陈诗一,陈登科.中国资源配置效率动态演化---纳入能源要素的新视角[J].中国社会科学,2017(4):67-83.
[3]国家发展改革委,国家能源局.关于印发能源发展“十三五”规划的通知[R].2016.
[4]韩英夫,黄锡生.论用能权的法理属性及其立法控索[J].理论与改革,2017(4):159-169.
[5]刘明明.论构建中国用能权交易体系的制度衔接之维[J].中国人口·资源与环境,2017,27(10):217-224.
[6]COASE R H.The problem of social cost[J].The journal of law and economics,1960,3(1):1-44.
[7]安崇义,唐跃军.排放权交易机制下企业碳减排的决策模型研究[J].经济研究,2012(8):45-58.
[8]吴力波,钱浩祺,汤维祺.基于动态边际减排成本模拟的碳排放权交易与碳税选择机制[J].经济研究,2014(9):48-61.
[9]范庆泉,周县华,张同斌.动态环境税外部性,污染累积路径与长期经济增长---兼论环境税的开征时点选择问题[J].经济研究,2016,51(8):116-128.
[10]BRNNLUND R,CHUNG Y,FRE R,et al.Emissions trading and profitability:the Swedish pulp and paper industry[J].Environmental and resource economics,1998,12(3):345-356.
[11]BRNNLUND U,LINDBERG P O,NOU A,et al.Railway timetabling using Lagrangian relaxation[J].Transportation science,1998,32(4):358-369.
[12]FRE R,GROSSKOPF S,PASURKA C.Potential gains from trading bad outputs:the case of US electric power plants[J].Resource and energy economics,2014,36(1):99-112.
[13]FRE R,GROSSKOPF S,PASURKA C.Tradable permits and unrealized gains from trade[J].Energy economics,2013,40:416-424.
[14]涂正革,谌仁俊.排污权交易机制在中国能否实现波特效应?[J].经济研究,2015,50(7):160-173.
[15]WANG K,WEI Y M,HUANG Z.Potential gains from carbon emissions trading in China:a DEA based estimation on abatement cost savings[J].Omega,2016,63:48-59.
[16]周五七.能源价格,效率增进及技术进步对工业行业能源强度的异质性影响[J].数量经济技术经济研究,2016,33(2):130-143.
[17]CHOI K,ANG B W.Attribution of changes in Divisia real energy intensity index:an extension to index decomposition analysis[J].Energy economics,2012,34(1):171-176.
[18]ANG B W.LMDI decomposition approach:a guide for implementation[J].Energy policy,2015,86:233-238.
[19]涂正革.中国的碳减排路径与战略选择[J].中国社会科学,2012(3):78-94.
[20]WU L,KANEKO S,MATSUOKA S.Driving forces behind the stagnancy of China’s energy-related CO2emissions from 1996 to1999:the relative importance of structural change,intensity change and scale change[J].Energy policy,2005,33(3):319-335.
[21]王锋,吴丽华,杨超.中国经济发展中碳排放增长的驱动因素研究[J].经济研究,2010,45(2):123-136.
[22]涂正革,谌仁俊.工业化,城镇化的动态边际碳排放量研究---基于LMDI“两层完全分解法”的分析框架[J].中国工业经济,2013(9):31-43.
[23]WANG C.Decomposing energy productivity change:a distance function approach[J].Energy,2007,32(8):1326-1333.
[24]林伯强,毛东昕.中国碳排放强度下降的阶段性特征研究[J].金融研究,2014(8):101-117.
[25]林伯强,杜克锐.理解中国能源强度的变化:一个综合的分解框架[J].世界经济,2014(4):69-87.
[26]AROCENA P,GMEZ-PLANA A G,PEA S.A decomposition of the energy intensity change in Spanish manufacturing[R].Springer international publishing,2016.
[27]刘朝,周宵宵,张欢,等.中国居民能源消费间接回弹效应测算:基于投入产出和再分配模型的研究[J].中国社会科学,2018(10):142-157.
[28]FRE R,GROSSKOPF S,PASURKA C.Environmental production functions and environmental directional distance functions[J].Energy,2007,32(7):1055-1066.
[29]王兵,吴延瑞,颜鹏飞.环境管制与全要素生产率增长:APEC的实证研究[J].经济研究,2008(5):19-32.
[30]WU Y.China’s capital stock series by region and sector[J].Frontiers of economics in China,2016,11(1):156-173.
[31]徐现祥,周吉梅,舒元.中国省区三次产业资本存量估计[J].统计研究,2007,24(5):6-13.
[32]MA C,STERN D I.China’s changing energy intensity trend:a decomposition analysis[J].Energy economics,2008,30(3):1037-1053.
[33]陈诗一.能源消耗,二氧化碳排放与中国工业的可持续发展[J].经济研究,2009,44(4):41-55.
[34]袁鹏.中国能源需求增长的因素分解[J].数量经济技术经济研究,2014(11):70-85.
[35]王兵,刘光天.节能减排与中国绿色经济增长---基于全要素生产率的视角[J].中国工业经济,2015(5):57-69.
[36]陈诗一.边际减排成本与中国环境税改革[J].中国社会科学,2011(3):85-100.
[37]王兵,於露瑾,杨雨石.碳排放约束下中国工业行业能源效率的测度与分解[J].金融研究,2013(10):128-141.
[38]董香书,肖翔.“振兴东北老工业基地”有利于产值还是利润?---来自中国工业企业数据的证据[J].管理世界,2017(7):24-34.
[39]邓健,王新宇.区域发展战略对我国地区能源效率的影响---以东北振兴和西部大开发战略为例[J].中国软科学,2015(10):146-154.
[40]LAI P,DU M,WANG B,et al.Assessment and decomposition of total factor energy efficiency:an evidence based on energy shadow price in China[J].Sustainability,2016,8(5):408.
[41]刘瑞明,赵仁杰.西部大开发:增长驱动还是政策陷阱---基于PSM-DID方法的研究[J].中国工业经济,2015(6):32-43.
[42]李兰冰.中国能源绩效的动态演化,地区差距与成因识别---基于一种新型全要素能源生产率变动指标[J].管理世界,2015(11):40-52.
[43]宋马林,金培振.地方保护,资源错配与环境福利绩效[J].经济研究,2016(12):47-61.
[44]林伯强,杜克锐.要素市场扭曲对能源效率的影响[J].经济研究,2013(9):125-136.
[45]孙传旺,林伯强.中国工业能源要素配置效率与节能潜力研究[J].数量经济技术经济研究,2014(5):86-99.
[46]魏楚,郑新业.能源效率提升的新视角---基于市场分割的检验[J].中国社会科学,2017(10):90-111.
[47]郑毓盛,李崇高.中国地方分割的效率损失[J].中国社会科学,2003(1):64-72.