多目标条件下企业碳配额分配和政府公平——基于(p,α)比例公平的视角
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  • 英文篇名:Optimal Allocation of Corporate Carbon Quotas and Government's Fairness under Multi-objective Decisions—From the Perspective of(p,α)Proportional Fairness
  • 作者:夏晖 ; 王思逸 ; 蔡强
  • 英文作者:XIA Hui;WANG Si-yi;CAI Qiang;School of Management and Economics,University of Electronic Science and Technology of China;Macro Economy and Finance Research Center,Sichuan Radio and TV University;
  • 关键词:(p ; α)比例公平 ; 主从博弈 ; 多目标决策 ; 碳配额分配 ; 遗传算法
  • 英文关键词:(p,α)proportional fairness;;leader-followers game;;multi-objective decisions;;carbon quota allocation;;genetic algorithm
  • 中文刊名:ZGGK
  • 英文刊名:Chinese Journal of Management Science
  • 机构:电子科技大学经济与管理学院;四川广播电视大学宏观经济与金融研究中心;
  • 出版日期:2019-04-30 15:24
  • 出版单位:中国管理科学
  • 年:2019
  • 期:v.27;No.174
  • 基金:国家自然科学基金面上项目(71473031);; 教育部人文社会科学研究项目(14YJA790062)
  • 语种:中文;
  • 页:ZGGK201904005
  • 页数:8
  • CN:04
  • ISSN:11-2835/G3
  • 分类号:51-58
摘要
本文在企业和政府主从博弈框架下,研究政府兼顾社会福利和减排成本的多目标条件下企业最优碳配额分配方式,并采用(p,α)比例公平建立了最优分配与政府公平态度之间的对应关系,进一步分析企业间减排效率差异对碳配额最优分配以及政府所持公平态度的影响。采用遗传算法模拟结果显示,在政府最大化社会福利和最小化减排总成本的多目标下,政府始终给予高效率减排企业更多的配额,在企业间减排效率差异较小和较大的行业,减排效率对最优配额分配和政府所持公平态度的影响是完全不同的。当行业内企业减排效率差异较小时,随减排效率差异的增加,低效率企业所得配额逐渐减少,政府公平性逐渐降低;当企业减排效率差异较大时,情况刚好相反,低效率企业的配额逐渐增加,政府变得越来越注重公平。除此之外,政府公平性并不意味着低效率企业得到更多的碳配额,当企业间减排效率差异增加到某一区间,随减排效率差异的增加,低效率企业所得配额逐渐减小,而政府公平逐渐增加。我们的结论为相关部门多目标下的最优碳配额分配决策以及分析政府的公平性提供了有益参考。
        For government,there are several certain goals considered when distributing carbon quota.For instance,to maximize the total welfare of the society and to minimize the reduction cost.Meanwhile,a certain blue print of distribution reflects government's attitude towards fairness,and it also influences enterprises' production decision,especially between enterprises with different efficiency in reduction.In this paper,under the frame of leader-followers game,the optimal carbon quota allocation strategy when the government realizes multi-objective optimization under taking account of both social welfare and emission reduction costs is studied.We use(p,α)-proportional fairness is used to establish the corresponding relationship between the optimal allocation and the government's attitude towards fairness.And then how enterprises' differences on reduction efficiency influences government's attitude towards fairness is analyzed.Genetic algorithm simulation results show that the government always gives greater quota to high efficiency enterprise when government wants to minimize the reduction cost and to maximize the social welfare.The results also show that how the differences in the efficiency of emission reduction influence the optimal allocation and government's attitude towards fairness will change completely differently within industries with differences between the efficiency of enterprises.When there is a small difference in the efficiency of emission reduction,with the increase of the difference of emission reduction efficiency,the quota of inefficient enterprises gradually decreased,and the government attitude towards fairness is getting smaller and smaller.When the difference in efficiency is larger,the situation is just the opposite.The government paid more attention to fairness,while low-efficiency enterprises get more carbon.Meanwhile,government's attitude towards fairness doesn't mean the low-efficiency enterprise obtain greater quota.As the difference in efficiency in a certain range,the increase in the difference will lead to smaller quota to the low-efficiency enterprise and a higher fairness in allocation.The above-mentioned results provide a useful reference and uncover the superiority of base line method in multi-objective optimization within industry with difference in reduction efficiency.And industries with different reduction efficiency apply to different distribution policy.
引文
[1]Heilmayr R,Bradbury J A.Effective,efficient or equitable:Using allowance allocations to mitigate emissions leakage[J].Climate Policy,2011,11(4):1113-1130.
    [2]王倩,高翠云,王硕.基于不同原则下的碳权分配与中国的选择[J].当代经济研究,2014,(4):30-36.
    [3]Howard R J,Tallontire A,Stringer L,et al.Unraveling the notion of“fair carbon”:Key challenges for standards development[J].World development,2015,70:343-356.
    [4]Shi H,Prasad R V,Onur E,et al.Fairness in wireless networks:Issues,measures andchallenges[J].IEEECommunications Surveys&Tutorials,2014,16(1):5-24.
    [5]Soumis F,Zaccour G,Hoanga l N.Measuring unfairness feeling in allocation problems[J].Omega,2016,65:138-147.
    [6]Howard R J,Tallontire A M,Stringer L C,et al.Which“fairness”,for whom,and why?An empirical analysis of plural notions of fairness in Fairtrade Carbon Projects,using Q methodology[J].Environmental Science&Policy,2016,56:100-109.
    [7]Hammar H,Jagers S C.What is a fair CO2tax increase?On fair emission reductions in the transport sector[J].Ecological Economics,2007,61(2):377-387.
    [8]Wang Qiuxian,Gao Zhiqiang,Ning Jicai,et al.The research on the fairness of carbon emissions for China's energy based on GIS[C]//Wei Gao,Jackson T J,Remote Sensing and Modeling of Ecosystems for Sustainability X(8869).Proceedings of SPIE,2013:1-6.
    [9]Pan Xunzhang,Teng Fei,Ha Yuejiao.Equitable access to sustainable development:Based on the comparative study of carbon emission rights allocation schemes[J].Applied Energy,2014,130(5):632-640.
    [10]Lan Tian,Kao D,Chiang M,et al.An axiomatic theory of fairness in network resource allocation[C]//Proceedings of the 29th conference on Information communications.San Diego,March 14-19,IEEE Press,2010:1343-1351.
    [11]Wu Huaqing,Du Shaofu,Liang Liang,et al.A DEA-based approach for fair reduction and reallocation of emission permits[J].Mathematical and Computer Modelling,2013,58(5):1095-1101.
    [12]Liao Zhenliang,Zhu Xiaolong,et al.Case study on initial allocation of Shanghai carbon emission trading based on Shapley value[J].Journal of Cleaner Production,2015,(103):338-344.
    [13]Joe-Wong C,Sen S,Lan T,et al.Multi-resource allocation:Fairness-efficiency tradeoffs in a unifying framework[J].IEEE/ACM Transactions on Networking(TON),2013,21(6):1785-1798.
    [14]Boche H,Schubert M.Nash bargaining and proportional fairness for wireless systems[J].IEEE/ACMTransactions on Networking(TON),2009,17(5):1453-1466.
    [15]Zhou Peng,Wang Mei.Carbon dioxide emissions allocation:A review[J].Ecological Economics,2016,(125):47-59.
    [16]令狐大智,叶飞.基于历史排放参照的碳配额分配机制研究[J].中国管理科学,2015,23(6):65-72.
    [17]陆敏,方习年.考虑不同分配方式的碳交易市场博弈分析[J].中国管理科学,2015,23(S1):807-811.
    [18]Kelly F P,Maulloo A K,Tan D K H.Rate control for communication networks:Shadow prices,proportional fairness and stability[J].Journal of the Operational Research Society,1998,49(3):237-252.
    [19]Mo J,Walrand J.Fair end-to-end window-based congestion control[J].IEEE/ACM Transactionson Networking,2000,8(5):556-567.
    [20]B9hringer C,Rosendahl K E.Strategic partitioning of emission allowances under the EU Emission Trading Scheme[J].Resource&Energy Economics,2008,31(3):182-197.
    [21]卓金武.MATLAB在数学建模中的应用[M].北京:北京航空航天大学出版社,2014.
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