我国区域碳排放分配研究
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摘要
随着全球范围内气候和环境形势的日益严峻,作为温室气体主要构成的二氧化碳排放问题备受瞩目。随着我国区域性碳交易市场的逐步推进,碳排放分配方法选择以及初始额度分配,成为学术界亟须解决的重要课题。
     经文献整理,发现目前的碳排放相关分配研究以简单的线性分配为主要形式,缺乏对碳排放产生的宏观机理的系统性考虑。本文以技术效率测定和生产经济学的相关理论作为研究的切入点,在宏观的生产函数框架下研究碳排放的相关分配问题,其研究结论及创新点主要有以下几个方面:
     (1)将碳排放作为宏观生产过程的非期望产出变量,使用环境生产技术,结合ZSG-DEA方法提出基于环境生产技术的零和博弈(Zero Sum Gains,简称ZSG)效率分配模型,利用DEA方法进行规划求解,以整体技术效率最大化为目标,完成我国碳排放的效率分配建模;在此基础上,以2010年为例,对我国省级碳排放效率分配进行研究;
     (2)通过对我国“十二五”时期数据的合理预测,完成对我国“十二五”时期省级碳强度约束指标的效率分配,对中央政府的行政分配与ZSG效率分配的不同思路进行比较和说明,结果发现部分省区存在较大差异;根据各省区在“十二五”期末应该达到的碳强度约束和GDP的预测数值,研究结果还将全部30个省区划分为4类地区并进行分析,每类地区的“低碳”路径不尽相同;
     (3)结合2006-2010年的历史数据,完成我国“十一五”时期的省级能源强度约束指标的效率分配,对中央政府的“下降20%”行政分配指标与ZSG效率分配的不同思路进行比较和说明,结果发现部分省区存在较大差异;根据各省区在“十二五”期末应该达到的能源强度约束和GDP的预测数值,对各省区的“十二五”能源强度约束指标和“十一五”实际下降幅度进行综合分析;研究结果还将全部30个省区划分为4类地区,每类地区的“节能”路径不尽相同;
     (4)结合潜力权重因子,构建出兼顾节能潜力、减排潜力和GDP增长潜力的碳排放额度分配机制,通过多阶段DEA规划求解完成分配,从而实现多重兼顾的分配导向结论的整体帕累托最优;针对权重因子对不同导向分配结果的影响,提出测算各省区的权重因子临界值的方法,该临界值可以用来明确不同政策导向之间的选择弹性。实证研究表明,对我国的东、中和西部地区以及30个省区而言,不同权重因子的选择和组合会影响到分配额度的数量变化;东部和中部地区在侧重于节能潜力和减排潜力的挖掘、西部地区在侧重于GDP增长潜力导向下,各地区获取的碳排放额度相对较多,这也符合目前我国产业结构调整、沿海工业内迁的经济发展现状。
     (5)借鉴欧盟分配原则,结合公平权重因子和溯往权重因子,构建出兼顾效率、公平、产值和溯往原则的碳排放额度分配机制,通过多阶段DEA规划求解完成分配,从而实现多重兼顾的分配导向结论的整体帕累托最优;针对权重因子对不同导向分配结果的影响,提出测算各省区的权重因子临界值的方法,该临界值可以用来明确不同政策导向之间的选择弹性。实证研究表明,对我国的东、中和西部地区以及30个省区而言,不同权重因子的选择和组合会影响到分配额度的数量变化;基于溯往原则和产值原则的分配结果对东部地区较为有利,基于效率与公平原则的分配结果对中西部地区较为有利。
Along with the global climate and environment situation becoming more serious, as main elementof greenhouse gas, carbon dioxide emissions are concerned. With China regional carbon dioxideemissions trading market gradually constrution, the choice of carbon dioxide emissions allocationmethod and initial quotas confirmation, must be solved as important topic of research.
     Through literature research, we found that current research are related to the carbon dioxideemissions in a simple linear pattern, show lack of macroscopic production in systemic mechanism.Based on the technical efficiency measurement and production economics related theory as startingpoint of research, we perform carbon dioxide emissions allocation in the macro production functionframework, the main research conclusions and innovation point as the following several aspects:
     (1) taking carbon dioxide emissions as a macro undesirable output variables, using the environmentproduction technology, combined with ZSG-DEA method, we propose Zero Sum Gains (short namefor ZSG) environmental production technology allocation model, using DEA method formathematical programming, in order to maximize the overall technical efficiency as the goal,complete serial China provincial carbon dioxide emissions efficiency allocation model construction;after that, taking2010as an example, finish carbon dioxide emissions efficiency allocation;
     (2) through reasonable forecasting data during the China "twelfth five-year" period, we completethe provincial carbon intensity constraint of ZSG efficiency allocation for "twelfth five-year" period,compare different mechanism between central government allocation and ZSG efficiency allocation,find that some provinces show great difference in differnt mechanism; According to each province’sfinal carbon intensity constraints and predicted values of GDP in the end of "twelfth five-year", all30provinces regions are divided into4types regions, each type of area has different "low carbon" path;
     (3) based on historical data from2006to2010, we complete the "eleventh five-year " periodprovincial energy intensity constraint of ZSG efficiency allocation, compared with "20%" for thecentral government administrative allocation of energy saving aim and ZSG efficiency allocation, findthat some provinces show great difference in differnt mechanism; According to each province’s finalenergy intensity constraints and actual values of GDP in the end of "eleventh five-year", all30provinces regions are divided into4types regions, each area of the path of " energy saving " hasdifferent "low carbon" path;
     (4) combined with potential weight factor, we complete optimum allocation based on potential of energy saving and potential of emission reduction and potential of GDP growth, through multi-stageDEA programming to complete allocation mechanism, so as to realize multiple aims allocation for“overall pareto optimality”; In view of potential weight factor influence on the different allocationresult, measure potential weight factor critical value, the critical value can be used to reflect choiceelastic between different policy. Empirical analysis shows that the different potential weight factorand critical value will cause greater influence of allocation results for east, middle and west regionsand30provinces; eastern and middle region should focus on the potential energy saving and emissionreduction potential results, western region should focus on GDP growth potential results, so eachregion would obtain more carbon dioxide emissions quotas, it conforms to the present status ofindustrial structure adjustment and coastal region industrial migration.
     (5) based on EU's carbon emissions allocation mechanism balances Equity Principle,Grandfathering Rule and Value Principle, combined with potential weight factor, we completeoptimum allocation based on Equity Principle, Grandfathering Rule and Value Principle, throughmulti-stage DEA programming to complete allocation mechanism, so as to realize multiple aimsallocation for “overall pareto optimality”; In view of Equity weight factor and Grandfathering Ruleweight factor influence on the different allocation result, measure weight factor critical value, thecritical value can be used to reflect choice elastic between different policy. Empirical analysis showsthat the different weight factor and critical value will cause greater influence of allocation results foreast, middle and west regions and30provinces; eastern region should focus on Efficiency and Equityresults, middle and western region should focus on Grandfathering Rule and Value Principle, so eachregion would obtain more carbon dioxide emissions quotas.
引文
[1]http://en.wikipedia.org/wiki/stern_Review.
    [2]樊纲.走向低碳发展:中国与世界[M].北京:中国经济出版社,2009.
    [3]张志强,曲建升,曾静静.温室气体排放科学评价与减排政策[M].科学出版社,2009,76-81.
    [4]王伟中,陈滨,鲁传一,等.《京都议定书》和碳排放权分配问题[J].清华大学学报(哲学社会科学版),2002,17(6):81-85.
    [5祁悦,谢高地.碳排放空间分配及其对中国区域功能的影响[J].资源科学,2009,31(4):590-597.
    [6]丁仲礼,段晓南,葛全胜,等.2050年大气浓度控制:各国排放量计[J].中国科学D辑:地球科学,2009,39(8):1009-1027.
    [7]查冬兰,周德群.地区能源效率与二氧化碳排放的区域差异性-基于Kaya因素分解[J].系统工程,2007,25(11):65-71.
    [8]苏利阳,王毅,汝醒君,等.面向碳排放权分配的衡量指标的公正性评价[J].生态环境学报,2009,18(4):1594-1598.
    [9]Larsen B, Shah A. Global tradable carbon PERMIT, participation incentives andtransfers[J]. Oxford economic papers,1994,46:841-856.
    [10]高广生.气候变化与碳排放权分配,气候变化研究进展[J].2006,2(6):301-305.[11]潘家华,陈迎.碳预算方案:一个公平、可持续的国际气候制度框架[J].中国社会科学,2009,(5):83-98.
    [12]张志强,曲建生,曾静静.温室气体排放评价指标及其定量分析[J].地理学报,2008,63(7):693-702.
    [13]陈文颖,吴宗鑫.碳排放权分配与碳排放权交易[J].清华大学学报(自然科学版),1998,38(12):15-18.
    [14]Rose A, Stevens B, Edmonds J,et al..International Equity and Differentiation inGlobal Warming Policy[J].Environmental and Resource Economics,1998,12(1):25-51.
    [15]Global Commons Institute. Contraction and Convergence: A Global Solution to aGlobal Problem [EB/OL]. http://www.gn.apc.org/gci/contconv/cc. html.1997.
    [16]Elzen M, Berk M, Both S, et al. FAIR1.0(Framework to assess international regimesfor differentiation of commitments):An interactive model to explore options fordifferentiation of future commitments in international climate policy making[R].RIVM Report,Holland,2000.
    [17]Phylipsen G J, Bode M J, Blok W K, et al.A triptych sectoral approach to burdensharing; Greenhouse gas emissions in the European Bubble[J].EnergyPolicy,1998,26:929-943.
    [18]Berk M M, Elzen M G. The brazilian Proposal evaluated [J].CHANGE,1998,44:19-23.
    [19]丁霄泉,排放权交易相关文献及评议[J].金融发展研究,2010,(4):21-25.
    [20]陈文颖,吴宗鑫,何建坤.全球未来碳排放权“两个趋同”的分配方法[J].清华大学学报(自然科学版),2005,45(6):850-857.
    [21]杨玲玲,马向春.电力市场环境下碳排放分配模型的比较研究[J].陕西电力,2010,(2):5-9.
    [22]杜少甫,董骏峰,梁樑,等.考虑排放许可与交易的生产优化[J].中国管理科学,2009,17(3):81-87.
    [23]Westskog H. Market power in a system of tradable CO2quotas[J].Energy,1996,17:85-103.
    [24]Janssen M, de Vries B. The battle of perspectives: a multi-agent model with adaptiveresponses to climate change[J].Ecological Economics,1998,26:43-65.
    [25]Cramton P,Kerr S. Tradable carbon permit auctions How and why to Auction notgrandfather[J].Energy Policy,2002,30:333-345.
    [26]Helm C. International Emissions Trading with Endogenous Allowance Choices[J].Journal of Public Economics,2003,87(12):2737-2747.
    [27]Jensen, Jesper, Tobias N R. Allocation of CO2emission permits: a generalequilibrium analysis of policy instruments[J].Journal of Environmental Economicsand Management,2000,40(2):111-136.
    [28]Edwards T H, Hutton J P. Allocation of carbon permits within a country:a generalequilibrium analysis of the United Kingdom[J].EnergyEconomics,2001,23(4):371-386.
    [29]李寿德,仇胜萍.排污权交易思想及其初始分配与定价问题探析[J].科学学与科学技术管理,2002,(1):69-71.
    [30]李寿德.排污权交易产生的经济根源及其研究动态[J].预测,2003,22(5):1-5.
    [31]肖江文,罗云峰,赵勇,等.排污权交易制度与初始排污权分配[J].科技进步与对策,2002,(1):126-127.
    [32]陈德湖.排污权交易理论及其研究综述[J].外国经济与管理,2004,26(5):45-49.
    [33]赵文会.初始排污权分配理论研究综述[J].工业技术经济,2008,27(8):111-113.
    [34]鲁炜,崔丽琴.可交易排污权初始分配模式分析[J].中国环境管理,2003,(10):8-9.
    [35]林巍,傅国伟,刘春华.基于公理体系的排污总量公平分配模型[J].环境科学,1996,17:35-37.
    [36]汪俊启,张颖.总量控制中水污染物允许排放量公平分配研究[J].安庆师范学院学报(自然科学版),2000,(6):37-40.
    [37]肖江文,罗云峰,赵勇,等.初始排污权拍卖的博弈分析[J].华中科技大学学报,2001,29(9):36-38.
    [38]肖江文.财务申报机制设计的博弈分析[J].系统工程理论与实践,2002,22(11):87-91.
    [39]张志耀,张海明.污染物排放总量分配的群体决策方法研究[J].系统科学与数学,2001,21(4):473-479.
    [40]李寿德,黄桐城.初始排污权分配的一个多目标决策模型[J].中国管理科学,2003,(12):40-44.
    [41]吴亚琼,赵勇,吴相林,等.初始排污权分配的协商仲裁机制[J].系统工程,2003,21(5):70-74.
    [42]陈德湖,李寿德,蒋馥.寡头垄断和排污权初始分配[J].系统工程,2004,22(10):51-54.
    [43]王勤耕,李宗恺,陈志鹏,等.总量控制区域排污权的初始分配方法[J].中国环境科学,2000,20(1):68-72.
    [44]李爱年,胡春冬.排污权初始分配的有偿性研究[J].中国软科学,2003,(5):17-21.
    [45]古宏伟,吴椒军.浅析大气排污权初始分配的方法及其效率[J].华东经济与管理,2007,21(10):64-67.
    [46]赵文会,高岩,戴天晟.初始排污权分配的优化模型[J].系统工程,2007,25(6):57-61.
    [47]刘力,周维.广东SO2排污权交易的初始分配与动态纠正机制[J].科技管理研究,2010,(7):14-17.
    [48]Scheel H. Undesirable outputs in efficiency evaluation[J]. European Journal ofOperational Research,2001,132(2):400-410.
    [49]Berg S A, Forsund F R, Jansen E S. Malmquist indices of productivity growth duringthe deregulation of Norwegian Banking1980-89[J].Scandinavian Journal ofEconomics,1992,94(3):211-228.
    [50]Hailu A, Veeman T. Non-parametric productivity analysis with undesirable outputs:an application to Canadian pulp and paper industry[J].American Journal ofAgricultural Economics,2000,83(3):605-616.
    [51]Seiford L M, Zhu J. Modeling undesirable factors in efficiency evaluation[J].European Journal of Operational Research,2002,147(1):16-20.
    [52]Hua Z S, Bian Y W, Liang L. Eco-efficiency analysis of paper mills along the HuaiRiver: An extended DEA approach[J].Omega,2007,35(5):578-587.
    [53]F re R, Grosskopf S, Lovell C K. Multilateral productivity comparisons when someoutputs are undesirable: a nonparametric approach[J].The Review of Economics andStatistics,1989,71(2):90-98.
    [54]F re R, Grosskopf S, Hernandez-Sancho F. Environmental performance: an index numberapproach[J].Resource and Energy Economics,2004,26(4):343-352.
    [55]Tyteca D.On the measurement of the environmental performance of firms: a literaturereview and productive efficiency perspective[J].Journal of EnvironmentalManagement,1996,46(3):281-308.
    [56]Zhou P, Ang B W. Linear programming models for measuring economy-wide energyefficiency performance[J].Energy Policy,2008,36(8):2911-2916.
    [57]F re R, Grosskopf S, Lovell C A K, et al. Deviation of shadow prices for undesirableoutputs: a distance function approach[J].The Review of Economics andStatistics,1993,75(2):374-380.
    [58]F re R, Grosskopf S, Noh D W, et al. Characteristics of a polluting technology:theory and practice[J].Journal of Econometrics,2005,126(2):469-492.
    [59]Chung Y H, F re R, Grosskopf S. Productivity and undesirable outputs: A directionaldistance function Approach[J].Journal of Environmental Management,1997,51(3):229-240.
    [60]Zhou P, Ang B W, Poh K L. Slacks-based efficiency measures for modelingenvironmental performance[J].Ecological Economics,2006,60(1):111-118.
    [61]Zhou P, Poh K L, Ang B W.A non-radial DEA approach to measuring environmentalperformance[J].European Journal of Operational Research,2007,178(1):1-9.
    [62]Zhou P, Ang B W, Poh K L.A survey of data envelopment analysis in energy andenvironmental studies[J]. European Journal of Operational Research,2008a,189(1):1-8.
    [63]Farrell M J. The measurement of productive efficiency [J].Journal of RoyalStatistical Society Series,1957,120(3):253-290.
    [64]Charnes A, Cooper W W, Rhodes E. Measuring the efficiency of decision-makingunits[J].European Journal of Operational Research,1978,6(2):429-444.
    [65]魏权龄.评价相对有效的DEA方法[M].北京:中国人民大学出版社,1988.
    [66]魏权龄,卢刚.DEA方法与模型的应用——数据包络分析(三)[J].系统工程理论与实践,1989,(5):67-75.
    [67]马占新.数据包络分析方法的研究进展[J]系统工程与电子技术,2002,24(3):33-37.
    [68]Banker R D, Charnes A, Cooper W W. Some Models for Estimating Technical and ScaleInefficiencies in Data Envelopment Analysis[J].Management Science,1984,30(9):1078-1092.
    [69]Hu J L, Wang S C. Total-factor Energy Efficiency of Regions in China[J]. EnergyPolicy,2006,34(17):3206-3217.
    [70]Hu J L, Kao C H. Efficient energy-saving targets for APEC economies[J]. EnergyPolicy,2007,35(1):373-382.
    [71]王群伟,周德群.中国全要素能源效率变动的实证研究[J].系统工程,2008,26(7):74-80.
    [72]师博,沈坤荣.市场分割下的中国全要素能源效率:基于超效率DEA方法的经验分析[J].世界经济,2008(9):49-59.
    [73]魏楚,杜立民,沈满洪.中国能否实现节能减排目标:基于DEA方法的评价与模拟[J].世界经济,2010,(3):141-160.
    [74]Cook W D, Kress M. Characterizing an equitable allocation of shared costs: A DEAapproach[J]. European Journal of Operational Research,1999,119:652-661.
    [75]Cook W D, Zhu J. Allocation of shared costs among decision making units: A DEAapproach[J]. Computers and Operations Research,2005,32:2171-2178.
    [76]Beasley J E. Allocating fixed costs and resources via data envelopment analysis[J].European Journal of Operational Research,2003,147:198-216.
    [77]Lins M P E, Gomes E G, Soares D M, et al. Olympic ranking based on a zero sum gainsDEA model[J]. European Journal of Operational Research,2003,148:312-322.
    [78]Lozano S A, Villa G. Centralized resource allocation using data envelopmentanalysis[J]. Journal of Productivity Analysis,2004,22:143-161.
    [79]Lozano S A, Villa G, Adenso-Diaz B.Centralized target setting for regionalrecycling operations using DEA[J].Omega,2004,32:101-110.
    [80]Asmild M, Paradi J C, Pastor J T. Centralized resource allocation BCC models[J].Omega,2009,37:40-49.
    [81]Lozano S A, Villa G. Centralized DEA models with the possibility of downsizingsource[J]. Journal of the Operational Research Society,2005,56(4):357-364.
    [82]Avellar J V G, Milioni A Z, Rabello T N.Spherical frontier DEA model based on aconstant sum of inputs[J]. Journal of the Operational Research Society,2009,58:1246-1251.
    [83]Guedes E C C, Freitas G M, Avellar J V G, et al. On the allocation of new inputsand outputs with DEA[J].Engevista,2009,11(1):4-7.
    [84]Milioni A Z, Avellar J V G, Gomes E G, et al.An ellipsoidal frontiermodel:Allocating input via parametric DEA[J]. European Journal of OperationalResearch,2011,209(2011):113-121.
    [85]Milioni A Z, Avellar J V G, Rabello T N, et al. On a fair distribution of an outputin DEA models[J]. Journal of the Operational Research Society,2010,doi:10.1057/jors.2010.24.
    [86]杨锋,杨琛琛,梁樑,等.各国奥运会参赛效率评价与排序研究[J].中国软科学,2009,(3):166-173.
    [87]杨锋,翟笃俊,梁樑,等.基于竞争决策单元的数据包络分析模型[J].系统管理学报,2009,18(3):332-337.
    [88]吴华清,梁樑,杨锋,等.一类基于投入约束的资源配置DEA博弈模型[J].系统工程,2009,27(10):104-107.
    [89]毕功兵,梁樑,杨锋.资源约束型两阶段生产系统的DEA效率评价模型[J].中国管理科学,2009,17(2):71-75.
    [90]Gomes E G,Lins, M P E. Modelling undesirable outputs with zero gains DEA models[J].Journal of the Operational Research Society,2008,59(5):616-623.
    [91]Gomes E G, Soares de Mello, J C C B,Angulo M L. Large discreet resource allocation:a hybrid approach based on DEA efficiency measurement[J]. PesquisaOperacional,2008,28(3):597-608.
    [92]Fonseca A B M, Soares de mello J C C B, Gomes E G, et al L. Uniformization of frontiersin non-radial ZSG-DEA models:an application to airport revenues[J]. PesquisaOperacional,2010,30:175-193.
    [93]Gomes E G, Souza G S. Allocating financial resource for competitive projects usinga zero sum gains DEA model[J].ENGEVISTA,2010,12(1):4-9.
    [94]Hu J L, Fang C Y. Do market share and efficiency matter for each other? An applicationof the zero-sum gains data envelopment analysis[J]. Journal of the OperationalResearch Society,2010,61:647-657.
    [95]林坦,宁俊飞.基于零和DEA模型的欧盟国家碳排放权分配效率研究[J].数量经济技术经济研究.2011,(3):36-50.
    [96]孙作人,周德群,周鹏,等.基于基于环境生产技术的ZSG效率分配模型的我国省区节能指标分配研究[J].系统工程,2012,(1):84-90.
    [97]Berg S A, Forsund F R, Jansen E S. Malmquist indices of productivity growth duringthe deregulation of Norwegian Banking1980-89[J]. Scandinavian Journal ofEconomics,1992,94(3):211-228.
    [98]Hailu A, Veeman T.Non-parametric productivity analysis with undesirable outputs:an application to Canadian pulp and paper industry [J]. American Journal ofAgricultural Economics,2000,83(3):605-616.
    [99]Mohtadi H. Environment, growth, and optimal policy design[J].Journal of PublicEconomics,1996,63:119-40.
    [100]F re G, Grosskopf S, Pasurka Jr C A. Environmental production functions andenvironmental directional distance functions [J].Energy,2007,32(7):1055-1066.
    [101]Zhou P, Ang B W, Poh K L.Measuring environmental performance under differentenvironmental DEA technologies[J].Energy Economics,2008,30(1):1-14.
    [102]王群伟,全要素视角下的能源利用和二氧化碳排放效率测度研究[D].南京航空航天大学,2011.
    [103]Zaim O. Measuring environmental performance of state manufacturing throughchanges in pollution intensities: a DEA framework[J]. Ecological Economics,2004,48(1):37-47.
    [104]Arcelus F J,Arocena P.Productivity differences across OECD countries in thepresence of environmental constraints[J].Journal of the Operational ResearchSociety,2005,56(12):1352-1362.
    [105]Pasurka Jr C A.Decomposing electric power plant emissions within a jointproduction framework[J].Energy Economics,2006,28(1):26-43.
    [106]王群伟,周鹏,周德群.中国二氧化碳排放绩效的动态变化、区域差异及影响因素[J].中国工业经济,2010,(1):45-54.
    [107]苗壮,周鹏,李向民.我国“十二·五”时期省级碳强度约束指标效率分配研究-基于基于环境生产技术的ZSG效率分配模型[J].经济管理,2012,(9):25-36.
    [108]乔晓楠,段小刚.总量控制、区际排污指标分配与经济绩效[J].经济研究,2012,(10):121-133.
    [109]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,(4):4-54.
    [110]单豪杰.中国资本存量K的再估:1952-2006年[J].数量经济技术经济研究,2008,(10):17-32.
    [111]袁晓玲,张宝山,杨万平.基于环境污染的中国全要素能源效率研究[J].中国工业经济,2009,(2):76-86.
    [112]Fan Y,Liu L C,Wang G,Hsien T T and Wei Y M.Changes in Carbon Intensity in China:Empirical Findings from1980-2003[J].Ecological Economics,2007,62:3-4.
    [113]Wei Y M,Liao H and Fan Y.An Empirical Analysis of Energy Efficiency in China’sIron and Steel Sector[J].Energy,2007,32.
    [114]王锋,冯根福.优化能源结构对实现中国碳强度目标的贡献潜力评估[J].北京:中国工业经济,2011,(4):127-137.
    [115]杜官印,蔡运龙,李双成.1997-2007年中国分省化石能源碳排放强度变化趋势分析[J].石家庄:地理与地理信息科学,2010,26(5):76-81.
    [116]吴殿廷,吴昊,姜晔.碳排放强度及其变化—基于截面数据定量分析的初步推断[J].北京:地理研究,2011,(4):579-589.
    [117]Zhang Y G.Structural Decomposition Analysis of Sources of Decarbonizing EconomicDevelopment in China:1992-2006[J].Ecological Economics,2009,68:8-9.
    [118]岳超,胡雪洋,贺灿飞,等.1995-2007年我国省区碳排放及碳强度的分析—碳排放与社会发展[J].北京大学学报:自然科学版,2010,46(4):510-516.
    [119]张友国.经济发展方式变化对中国碳排放强度的影响[J].北京:经济研究,2010,(4):120-133.
    [120]李善同,侯永志,刘云中,等.中国经济增长潜力与经济增长前景分析[J].北京:管理世界,2005,(9):7-20.
    [121]林伯强,孙传旺.如何在保障中国经济增长前提下完成碳减排目标[J].北京:中国社会科学,2011,(1):64-76.
    [122]Ang B W. Decomposition analysis for policymaking in energy: which is the preferredmethod?[J]. Energy Policy,2004,32(9):1131-1139.
    [123]高振宇,王益.我国生产用能源消费变动的分解分析[J].统计研究,2007,24(3):52-57.
    [124]邱寿丰.中国能源强度变化的区域影响分析[J].数量经济技术经济研究,2008,(12):37-48.
    [125]Fisher-Vanden K.What is driving China’s decline in energy intensity [J].Resourceand Energy Economics,2004,26(1):77-97.
    [126]冯泰文,孙林岩,何哲.技术进步对中国能源强度调节效应的实证研究[J].科学学研究,2008,26(10):987-993.
    [127]Feng T W,Sun L Y,Zhang Y.The relationship between energy consumption structure,economic structure and energy intensity in China[J].EnergyPolicy,2009,37(12):5475-5483.
    [128]Karl Y X,Chen Z C.Government expenditure and energy intensity in China [J].EnergyPolicy,2010,38(2):691-694.
    [129]Wu Y R. Energy intensity and its determinants in China's regional economics[J].Energy Policy,2012,41(2):703-711.
    [130]何建坤,张希良.我国“十一五”期间能源强度下降趋势分析—如何实现能源强度下降20%的目标[J].中国软科学,2006,(4):33-38.
    [131]Zheng Y M,Qi J H,Chen X L.The effect of increasing exports on industrial energyintensity in China [J].Energy Policy,2011,39(5):2688-2698.
    [132]Wang X. On China's energy intensity statistics: toward a comprehensive andtransparent indicator [J].Energy Policy,2011,39(11):7284-7289.
    [133]Krause F, Bach W, Koomey J. Energy policy in the greenhouse[M]. John Wiley Sons,New York (United States),1989.
    [134]Kverndokk S.Global CO2agreements: a cost-effective approach[J].the EnergyJournal,1993,14(2):91-112.
    [135]Janssen M. Modelling global change: the art of integrated assessment modelling,advances in ecological economics [M].Edward Elgar Publishing Ltd, Cheltenham(United Kingdom),1998.

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