考虑各省经济人效应的我国省域碳排放权DEA分配
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摘要
国家应对气候变化规划(2014—2020年)》提出到2020年单位GDP二氧化碳排放量要在2005年基础上减少40%～45%。为实现减排目标,我国政府采取了碳排放交易等一系列措施,而这些措施的基础就是合理进行碳排放权分配。基于区域协同减排,综合考虑公平性、支付性、世袭性三大原则,建立考虑各省市经济人效应的集中DEA模型,进行优化分配,实现各省效率最大化。模型选择人口、资本存量、能源消耗量作为投入指标,选择GDP和二氧化碳排放量作为产出指标。其中,资本存量折算为2005年价格下的资本存量,并对2020年各省资本存量进行拟合预测;GDP折算为2005年价格下的GDP,并根据各省市"十三五"规划纲要进行预测;能源消耗量通过拟合进行预测;二氧化碳排放量根据IPCC算法算出。然后,将优化结果与国家减排政策目标进行对比,算出差值β。结果显示,北京等省市的β值为零,说明优化结果与国家减排指标一致;黑龙江等省份的β值为正,说明优化结果比国家减排指标大,国家应给予它们更多的碳排放权;河北等省份的β值为负,说明优化结果比国家减排指标小,国家可以给予它们更少的碳排放权。总体来说,东部地区的减排工作不能放松,但西部省份的减排工作也不可掉以轻心。
China has committed in its National Plan for Addressing Climate Change(2014-2020) to reducing carbon dioxide emissions per unit of GDP by 40%-45% by 2020 compared with the level of 2005.In order to achieve this emission reduction goal,the government has taken a series of measures including carbon emissions trading,and these measures are based on the rational allocation of carbon emissions rights.Considering the three principles of fairness,payment and heredity,a centralized DEA model,which considers the economic man effect of each province,was established based on regional coordinated emission reduction to optimize the allocation and maximize the efficiency of each province.This model selected population,capital stock and energy consumption as the input indicators and GDP and carbon dioxide emissions as the output indicators.Among them,the capital stock was translated into the capital stock under the 2005 price,and the capital stock of each province in 2020 was predicted by fitting.GDP was translated into the GDP under the 2005 price and predicted according to the 13 thFive-Year Plan of each province.Energy consumption was predicted by fitting,and carbon dioxide emissions were calculated using IPCC algorithm.Then the optimization results were com-pared with the national policy objectives of emission reduction,and the difference β was calculated.It was found that the β value of some provinces and cities including Beijing was zero,indicating that the optimization results are consistent with the national objectives of emission reduction.The β value of some provinces including Heilongjiang was positive,indicating that the optimization results are worse than the national objectives of emission reduction,so the government should allocate more carbon emission rights to them.The β value of some provinces including Hebei was negative,indicating that the optimization results are better than the national objectives of emission reduction,so the government can allocate fewer carbon emission rights to them.In general,while stepping up its emission reduction efforts in eastern China,the government should never take the emission reduction work in western China lightly.
China has committed in its National Plan for Addressing Climate Change(2014-2020) to reducing carbon dioxide emissions per unit of GDP by 40%-45% by 2020 compared with the level of 2005.In order to achieve this emission reduction goal,the government has taken a series of measures including carbon emissions trading,and these measures are based on the rational allocation of carbon emissions rights.Considering the three principles of fairness,payment and heredity,a centralized DEA model,which considers the economic man effect of each province,was established based on regional coordinated emission reduction to optimize the allocation and maximize the efficiency of each province.This model selected population,capital stock and energy consumption as the input indicators and GDP and carbon dioxide emissions as the output indicators.Among them,the capital stock was translated into the capital stock under the 2005 price,and the capital stock of each province in 2020 was predicted by fitting.GDP was translated into the GDP under the 2005 price and predicted according to the 13 thFive-Year Plan of each province.Energy consumption was predicted by fitting,and carbon dioxide emissions were calculated using IPCC algorithm.Then the optimization results were com-pared with the national policy objectives of emission reduction,and the difference β was calculated.It was found that the β value of some provinces and cities including Beijing was zero,indicating that the optimization results are consistent with the national objectives of emission reduction.The β value of some provinces including Heilongjiang was positive,indicating that the optimization results are worse than the national objectives of emission reduction,so the government should allocate more carbon emission rights to them.The β value of some provinces including Hebei was negative,indicating that the optimization results are better than the national objectives of emission reduction,so the government can allocate fewer carbon emission rights to them.In general,while stepping up its emission reduction efforts in eastern China,the government should never take the emission reduction work in western China lightly.
引文
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[13]国务院发展研究中心课题组.国内温室气体减排:基本框架设计[J].管理世界,2011(10):1-9.
[14]段茂盛,庞韬.全国统一碳排放权交易体系中的配额分配方式研究[J].武汉大学学报:哲学社会科学版,2014,67(5):5-12.
[15]郑立群.中国各省区碳减排责任分摊---基于零和收益DEA模型的研究[J].资源科学,2012,34(11):2087-2096.
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[18]曾诗鸿,徐妍.基于零和DEA模型的中国省级碳减排分配效率研究[J].管理现代化,2014,34(5):63-65.
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[21]杨庆亮.我国2020年碳减排目标省际分解研究---基于公平与效率视角[D].北京:中国矿业大学,2015.
[22]孙作人.效率分析视角下我国二氧化碳排放分解及分配研究[D].南京:南京航空航天大学,2013.
[23]WANG Qunwei,ZHOU Peng,ZHOU Dequn,et al.Dynamic Changes,Regional Differences,and Influencing Factors of CO2Emission Performance in China[J].Chinese Journal of Population Resources&Environment,2011,9(3):47-57.
[24]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[J].中国工业经济,2015(9):99-113.
[25]王荧.兼顾效率与公平的碳排放额分配的DEA建模与运用[J].资源科学,2015,37(7):1434-1443.
[26]宋杰鲲,牛丹平,曹子建,等.考虑碳转移的我国省域碳排放核算与初始分配[J].华东经济管理,2017,31(11):57-64.
[27]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[J].干旱区资源与环境,2017,31(5):7-13.
[28]阿荣.基于ZSG-DEA模型下的中国碳市场初始配额研究及区域政策分析[J].甘肃科学学报,2017,29(2):125-130.
[29]王敬敏,薛雨田.基于数据包络模型的电力行业碳排放权配额初始分配效率研究[J].中国电力,46(10):146-150.
[30]张军,吴桂英,张吉鹏.中国省际物质资本存量估算:1952-2000[J].经济研究,2004(10):35-44.
[31]张博,何明洋.基于全国统一碳市场下的中国各省市初始碳排放权分配方案研究[J].云南财经大学学报,2015(6):102-113.
[2]王凯,秦颖,王红春.中国现有碳排放权分配方式解构[J].中国人口·资源与环境,2014,24(增):10-12.
[3]陈华,诸大建,邹丽.全球主要国家的二氧化碳排放空间研究---基于生态-公平-效率模型[J].东北大学学报:社会科学版,2012,14(2):119-124.
[4]彭水军,张文城.国际碳减排合作公平性问题研究[J].厦门大学学报:哲学社会科学版,2012(1):109-117.
[5]刘春兰,蔡博峰,陈操操,等.中国碳减排目标的地区分解方法研究述评[J].地理科学,2013,33(9):1089-1096.
[6]孙耀华,仲伟周.国际温室气体减排方案及其公平性研究---基于罗尔斯正义论的视角[J].资源科学,2013,35(7):1430-1437.
[7]BLOK K,PHYLIPSEN D.Common and Coordinated Policies and Measures to Reduce Greenhouse Gas Emissions in the European Union[J].International Journal of Environment&Pollution,1998,10(3/4):393-402.
[8]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.
[9]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):850-853.
[10]DE VILLEMEUR E B,LEROUX J.Sharing the Cost of Global Warming[J].Scandinavian Journal of Economics,2011,113(4):758-783.
[11]赵雪,钟定胜,俞俏翠.基尼系数法在全球碳排放权分配中的应用研究[J].环境科学与技术,2015,38(1):195-204.
[12]F魧RE R,GROSSKOPF S,PASURKA C A,et al.Substitutability among Undesirable Outputs[J].Applied Economics,2012,44(1):39-47.
[13]国务院发展研究中心课题组.国内温室气体减排:基本框架设计[J].管理世界,2011(10):1-9.
[14]段茂盛,庞韬.全国统一碳排放权交易体系中的配额分配方式研究[J].武汉大学学报:哲学社会科学版,2014,67(5):5-12.
[15]郑立群.中国各省区碳减排责任分摊---基于零和收益DEA模型的研究[J].资源科学,2012,34(11):2087-2096.
[16]傅京燕,黄芬.中国碳交易市场CO2排放权地区间分配效率研究[J].中国人口·资源与环境,2016,26(2):1-9.
[17]WANG Q W,ZHOU P,SHEN N,et al.Measuring Carbon Dioxide Emission Performance in Chinese Provinces:A Parametric Approach[J].Renewable and Sustainable Energy Reviews,2013,21(5):324-330.
[18]曾诗鸿,徐妍.基于零和DEA模型的中国省级碳减排分配效率研究[J].管理现代化,2014,34(5):63-65.
[19]李小胜,宋马林.“十二五”时期我国碳排放额度分配评估及效率研究[J].经济科学,2015(5):58-69.
[20]王科,李默洁.碳排放配额分配的DEA建模与应用[J].北京理工大学学报:社会科学版,2013,15(4):7-13.
[21]杨庆亮.我国2020年碳减排目标省际分解研究---基于公平与效率视角[D].北京:中国矿业大学,2015.
[22]孙作人.效率分析视角下我国二氧化碳排放分解及分配研究[D].南京:南京航空航天大学,2013.
[23]WANG Qunwei,ZHOU Peng,ZHOU Dequn,et al.Dynamic Changes,Regional Differences,and Influencing Factors of CO2Emission Performance in China[J].Chinese Journal of Population Resources&Environment,2011,9(3):47-57.
[24]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[J].中国工业经济,2015(9):99-113.
[25]王荧.兼顾效率与公平的碳排放额分配的DEA建模与运用[J].资源科学,2015,37(7):1434-1443.
[26]宋杰鲲,牛丹平,曹子建,等.考虑碳转移的我国省域碳排放核算与初始分配[J].华东经济管理,2017,31(11):57-64.
[27]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[J].干旱区资源与环境,2017,31(5):7-13.
[28]阿荣.基于ZSG-DEA模型下的中国碳市场初始配额研究及区域政策分析[J].甘肃科学学报,2017,29(2):125-130.
[29]王敬敏,薛雨田.基于数据包络模型的电力行业碳排放权配额初始分配效率研究[J].中国电力,46(10):146-150.
[30]张军,吴桂英,张吉鹏.中国省际物质资本存量估算:1952-2000[J].经济研究,2004(10):35-44.
[31]张博,何明洋.基于全国统一碳市场下的中国各省市初始碳排放权分配方案研究[J].云南财经大学学报,2015(6):102-113.