公平与效率协调视角下的中国碳减排潜力与路径
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摘要
在碳排放公平原则和效率原则协调的基础上计算区域碳减排潜力并设计碳减排路径,对于我国更科学地测算区域碳减排潜力以及更合理地制定区域碳减排路径,从而更好地促进绿色低碳经济发展具有重要意义。选取了1997-2015年29个省级地区数据,通过Super-SBM模型测算了碳排放效率,并以人均碳排放量衡量区域碳排放公平;基于Markov链框架测算了碳排放公平和效率的俱乐部趋同指数,以分析公平和效率原则在考察我国碳减排潜力中的重要性以及在制定碳减排政策时的侧重点,进而在碳排放公平与效率协调的视角下重新测算出各省份的碳减排潜力;在碳排放公平和效率二维矩阵图基础上,基于二者协调的视角设计了碳减排路径。研究发现:(1)我国碳排放公平与碳排放效率的俱乐部趋同程度(固化程度)具有显著差异,碳排放的"长期低效率"比"长期不公平"固化问题更严重。(2)相比于公平与效率相等原则,基于协调原则下的各地区碳减排潜力指数存在变化,这将影响我国碳减排目标地区的划分,进而影响国家碳权分配以及减排责任的分摊。(3)基于各省碳减排的公平性与效率性差异,中国大陆29个省级行政区域可划分为四大类型地区。我国公平效率协调的减排路径是:重点支持"低效低排"型地区,提高其碳排放效率,实施碳排放公平和效率动态协调的碳减排策略。
Studying the Chinese provincial carbon emission reduction potential and the path of emission reduction based on the coordinated perspective of fairness and efficiency is most significant to measuring the regional potential of carbon emission reduction and to formulating the regional carbon emission reduction path for China, so as to better promote the development of green low carbon economy. First, we measure the carbon reduction efficiency by the SuperSBM model, and measure the equity of regional carbon emissions by per capita carbon emissions. Then we calculate the carbon club convergence index of efficiency and fairness based on Markov model frame so as to analyze the importance of carbon reduction potential in China and the emphasis in carbon emissions. Then we recalculate the carbon emission potential of each province based on the coordinated principle of fairness and efficiency. Finally, the carbon emission reduction path is designed on the basis of the two dimensional matrix diagram of carbon emission fairness and efficiency based on the coordinated principle. The results show that:(1) The carbon club convergence degree of China's regional carbon emission efficiency is higher, and the curing problem of "long-term low efficiency" of carbon emissions is more serious than the "long-term unfair".(2) China's carbon emission potential is underestimated,which will affect the country's allocation of carbon rights and the sharing of emission reduction responsibility.(3) Based on the coordinated perspective of fairness and efficiency in carbon emissions, the 29 provincial-level administrative districts in the mainland of China fall into four categories. Policymakers should focus on supporting the regions of "low-efficiency & lowemission" type and improve the efficiency of their carbon emissions, so as to achieve carbon emission reduction under the coordinated perspective of fairness and efficiency.
Studying the Chinese provincial carbon emission reduction potential and the path of emission reduction based on the coordinated perspective of fairness and efficiency is most significant to measuring the regional potential of carbon emission reduction and to formulating the regional carbon emission reduction path for China, so as to better promote the development of green low carbon economy. First, we measure the carbon reduction efficiency by the SuperSBM model, and measure the equity of regional carbon emissions by per capita carbon emissions. Then we calculate the carbon club convergence index of efficiency and fairness based on Markov model frame so as to analyze the importance of carbon reduction potential in China and the emphasis in carbon emissions. Then we recalculate the carbon emission potential of each province based on the coordinated principle of fairness and efficiency. Finally, the carbon emission reduction path is designed on the basis of the two dimensional matrix diagram of carbon emission fairness and efficiency based on the coordinated principle. The results show that:(1) The carbon club convergence degree of China's regional carbon emission efficiency is higher, and the curing problem of "long-term low efficiency" of carbon emissions is more serious than the "long-term unfair".(2) China's carbon emission potential is underestimated,which will affect the country's allocation of carbon rights and the sharing of emission reduction responsibility.(3) Based on the coordinated perspective of fairness and efficiency in carbon emissions, the 29 provincial-level administrative districts in the mainland of China fall into four categories. Policymakers should focus on supporting the regions of "low-efficiency & lowemission" type and improve the efficiency of their carbon emissions, so as to achieve carbon emission reduction under the coordinated perspective of fairness and efficiency.
引文
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[2] STERN N. Key elements of a global deal on climate change. London School of Economics and Political Science, London, UK, 2008.
[3]邓吉祥,刘晓,王铮.中国碳排放的区域差异及演变特征分析与因素分解.自然资源学报, 2014, 29(2):189-200.[DENG J X, LIU X, WANG Z. Characteristics analysis and factor decomposition based on the regional difference chang
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[10]刘亦文,胡宗义.中国碳排放效率区域差异性研究:基于三阶段DEA模型和超效率DEA模型的分析.山西财经大学学报, 2015, 37(2):23-34.[LIU Y W, HU Z Y. Research on regional difference about carbon emission efficiency in China:Based on three stage DEA. Journal of Shanxi University of Finance and Economics, 2015, 37(2):23-34.]
[11] YAN D, LEI Y L, LI L, et al. Carbon emission efficiency and spatial clustering analyses in China's thermal power industry:Evidence from the provincial level. Journal of Cleaner Production, 2017, 156:518-527.
[12]傅京燕,原宗琳,曾翩.中国区域生态效率的测度及其影响因素分析.产经评论, 2016, 7(6):85-97.[FU J Y, YUAN Z L, ZENG P. Research on regional ecological efficiency in China:Measurement and determinants. Industrial Economic Review, 2016, 7(6):85-97.]
[13]宋杰鲲,张凯新,曹子建.省域碳排放配额分配—融合公平和效率的研究.干旱区资源与环境, 2017, 31(5):7-13.[SONG J K, ZHANG K X, CAO Z J. Provincial allocation of carbon emission quotas-under the fusion of fairness and efficiency. Journal of Arid Land Resources and Environment, 2017, 31(5):7-13.]
[14] WEI C, NI J L, DU L M. Regional allocation of carbon dioxide abatement in China. China Economic Review, 2012,23(3):552-565.
[15]吴贤荣,张俊飚,田云,等.基于公平与效率双重视角的中国农业碳减排潜力分析.自然资源学报, 2015, 30(7):1172-1182.[WU X R, ZHANG J B, TIAN Y, et al. Analysis on China's agricultural carbon abatement capacity from the perspective of both equity and efficiency. Journal of Natural Resources, 2015, 30(7):1172-1182.]
[16]冯冬,李健.京津冀区域城市二氧化碳排放效率及减排潜力研究.资源科学, 2017, 39(5):978-986.[FENG D, LI J.Research of the carbon dioxide emission efficiency and reduction potential of cities in the Beijing-Tianjin-Hebei region.Resources Science, 2017, 39(5):978-986.]
[17] TONE K. A slacks-based measure of efficiency in data envelopment analysis. European Journal of Operational Research, 2001, 130(3):498-509.
[18] TONE K. A slacks-based measure of super-efficiency in data envelopment analysis. European Journal of Operational Research, 2002, 143(1):32-41.
[19] TONE K. Dealing with Undesirable Outputs in DEA:A Slacks based Measure(SBM)Approach. GRIPS Research Report Seires, 2003-0005.
[20]周迪,程慧平.中国农业现代化发展水平时空格局及趋同演变.华南农业大学学报:社会科学版, 2015, 14(1):25-35.[ZHOU D, CHENG H P. Evolvement of convergence and spatial patterns of agricultural modernization in China.Journal of South China Agricultural University:Social Science Edition, 2015, 14(1):25-35.]
[21] PAN X F, LIU Q, PENG X X. Spatial club convergence of regional energy efficiency in China. Ecological Indicators,2015, 51:25-30.
[22]杨明海,张红霞,孙亚男.七大城市群创新能力的区域差距及其分布动态演进.数量经济技术经济研究, 2017, 34(3):21-39.[YANG M H, ZHANG H X, SUN Y N. Regional disparity and distributional dynamic evolution of the innovation ability in seven Chinese megalopolises. The Journal of Quantitative&Technical Economics, 2017, 34(3):21-39.]
[23] GALLO J L. Space-time analysis of GDP disparities among European regions:A Markov chain approach. International Regional Science Review, 2001, 27(2):138-163.
[24]单豪杰.中国资本存量K的再估算:1952-2006年.数量经济技术经济研究, 2008, 25(10):17-31.[SHAN H J. Reestimating the capital stock of China:1952-2006. The Journal of Quantitative&Technical Economics, 2008, 25(10):17-31.]
[25]杜立民.我国二氧化碳排放的影响因素:基于省级面板数据的研究.南方经济, 2010,(11):20-33.[DU L M. Impact factors of China's carbon dioxide emissions:Provincial panel data analysis. South China Journal of Economics, 2010,(11):20-33.]
(1)为节约篇幅,具体计算结果没有给出,需要的读者可以向作者索取。
(2)为节约篇幅,具体检验结果没有给出,需要的读者可以向作者索取。
[2] STERN N. Key elements of a global deal on climate change. London School of Economics and Political Science, London, UK, 2008.
[3]邓吉祥,刘晓,王铮.中国碳排放的区域差异及演变特征分析与因素分解.自然资源学报, 2014, 29(2):189-200.[DENG J X, LIU X, WANG Z. Characteristics analysis and factor decomposition based on the regional difference chang
[9]李小胜,宋马林.“十二五”时期中国碳排放额度分配评估:基于效率视角的比较分析.中国工业经济, 2015,(9):99-113.[LI X S, SONG M L. Regional allocation of CO2emissions allowance during the"Twelfth Five-Year Plan"in China:From the perspective of efficiency comparative analysis. China Industrial Economics, 2015,(9):99-113.]
[10]刘亦文,胡宗义.中国碳排放效率区域差异性研究:基于三阶段DEA模型和超效率DEA模型的分析.山西财经大学学报, 2015, 37(2):23-34.[LIU Y W, HU Z Y. Research on regional difference about carbon emission efficiency in China:Based on three stage DEA. Journal of Shanxi University of Finance and Economics, 2015, 37(2):23-34.]
[11] YAN D, LEI Y L, LI L, et al. Carbon emission efficiency and spatial clustering analyses in China's thermal power industry:Evidence from the provincial level. Journal of Cleaner Production, 2017, 156:518-527.
[12]傅京燕,原宗琳,曾翩.中国区域生态效率的测度及其影响因素分析.产经评论, 2016, 7(6):85-97.[FU J Y, YUAN Z L, ZENG P. Research on regional ecological efficiency in China:Measurement and determinants. Industrial Economic Review, 2016, 7(6):85-97.]
[13]宋杰鲲,张凯新,曹子建.省域碳排放配额分配—融合公平和效率的研究.干旱区资源与环境, 2017, 31(5):7-13.[SONG J K, ZHANG K X, CAO Z J. Provincial allocation of carbon emission quotas-under the fusion of fairness and efficiency. Journal of Arid Land Resources and Environment, 2017, 31(5):7-13.]
[14] WEI C, NI J L, DU L M. Regional allocation of carbon dioxide abatement in China. China Economic Review, 2012,23(3):552-565.
[15]吴贤荣,张俊飚,田云,等.基于公平与效率双重视角的中国农业碳减排潜力分析.自然资源学报, 2015, 30(7):1172-1182.[WU X R, ZHANG J B, TIAN Y, et al. Analysis on China's agricultural carbon abatement capacity from the perspective of both equity and efficiency. Journal of Natural Resources, 2015, 30(7):1172-1182.]
[16]冯冬,李健.京津冀区域城市二氧化碳排放效率及减排潜力研究.资源科学, 2017, 39(5):978-986.[FENG D, LI J.Research of the carbon dioxide emission efficiency and reduction potential of cities in the Beijing-Tianjin-Hebei region.Resources Science, 2017, 39(5):978-986.]
[17] TONE K. A slacks-based measure of efficiency in data envelopment analysis. European Journal of Operational Research, 2001, 130(3):498-509.
[18] TONE K. A slacks-based measure of super-efficiency in data envelopment analysis. European Journal of Operational Research, 2002, 143(1):32-41.
[19] TONE K. Dealing with Undesirable Outputs in DEA:A Slacks based Measure(SBM)Approach. GRIPS Research Report Seires, 2003-0005.
[20]周迪,程慧平.中国农业现代化发展水平时空格局及趋同演变.华南农业大学学报:社会科学版, 2015, 14(1):25-35.[ZHOU D, CHENG H P. Evolvement of convergence and spatial patterns of agricultural modernization in China.Journal of South China Agricultural University:Social Science Edition, 2015, 14(1):25-35.]
[21] PAN X F, LIU Q, PENG X X. Spatial club convergence of regional energy efficiency in China. Ecological Indicators,2015, 51:25-30.
[22]杨明海,张红霞,孙亚男.七大城市群创新能力的区域差距及其分布动态演进.数量经济技术经济研究, 2017, 34(3):21-39.[YANG M H, ZHANG H X, SUN Y N. Regional disparity and distributional dynamic evolution of the innovation ability in seven Chinese megalopolises. The Journal of Quantitative&Technical Economics, 2017, 34(3):21-39.]
[23] GALLO J L. Space-time analysis of GDP disparities among European regions:A Markov chain approach. International Regional Science Review, 2001, 27(2):138-163.
[24]单豪杰.中国资本存量K的再估算:1952-2006年.数量经济技术经济研究, 2008, 25(10):17-31.[SHAN H J. Reestimating the capital stock of China:1952-2006. The Journal of Quantitative&Technical Economics, 2008, 25(10):17-31.]
[25]杜立民.我国二氧化碳排放的影响因素:基于省级面板数据的研究.南方经济, 2010,(11):20-33.[DU L M. Impact factors of China's carbon dioxide emissions:Provincial panel data analysis. South China Journal of Economics, 2010,(11):20-33.]
(1)为节约篇幅,具体计算结果没有给出,需要的读者可以向作者索取。
(2)为节约篇幅,具体检验结果没有给出,需要的读者可以向作者索取。
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