碳交易政策下区域合作减排收益分配研究
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摘要
科学合理的区域合作减排收益分配方案,能够持续地促进集聚空间内区域主体合作减排,有效降低碳排放负外部性影响。本文基于不对称纳什谈判合作收益分配模型,确定谈判后的合作收益最佳折扣方案,给出各地方政府的减排收益分配系数及初始收益分配矩阵。综合考虑各地方政府在合作减排中的重要程度,风险分担程度以及地方政府减排绩效等影响收益分配的要素,利用客观指标数据和主观评价数据对影响要素进行测算,以此构建修正的合作减排收益分配方案。最后,以京津冀合作减排系统为对象对所设计的收益分配方案进行例证,研究发现修正后的方案更符合成员所承担的风险越大,减排绩效越好,其获得收益也应该越多的前提假设,能够大幅提高地方政府减排投入产出的有效性及风险承担能力,提高了合作关系稳定性。
A scientific and reasonable regional cooperative emission reduction interest distribution scheme can continuously promote the emission-reducing willingness of players in an agglomeration space, and effectively reduce the bad influence of the externality of carbon emission. Based on the model of interest distributions of asymmetric Nash negotiations, this paper solves the best discount coefficient of cooperative interest after negotiation, determines the distribution coefficient of local governments' emission reduction and the initial income distribution matrix. Taking into account the important factors of the local governments in the cooperative emission reduction, the degree of risk sharing and the local government emission reduction performance and other factors affecting the distribution of interest, this paper uses objective data and subjective evaluation data to calculate the influencing factors in order to build a revised regional cooperative emission reduction interest distribution program. Finally, the Beijing-Tianjin-Hebei cooperation emission reduction system as the object of the design of the interest distribution programs are exemplified and the result shows that the revised program is more in line with the premise that the greater the risks of members and the better the performance of the reduction, the more interests should be. The revised interest distribution strategy can greatly improve the effectiveness and risk-taking capacity of the local government's emission reduction and enhance the stability of the cooperative relationship.
A scientific and reasonable regional cooperative emission reduction interest distribution scheme can continuously promote the emission-reducing willingness of players in an agglomeration space, and effectively reduce the bad influence of the externality of carbon emission. Based on the model of interest distributions of asymmetric Nash negotiations, this paper solves the best discount coefficient of cooperative interest after negotiation, determines the distribution coefficient of local governments' emission reduction and the initial income distribution matrix. Taking into account the important factors of the local governments in the cooperative emission reduction, the degree of risk sharing and the local government emission reduction performance and other factors affecting the distribution of interest, this paper uses objective data and subjective evaluation data to calculate the influencing factors in order to build a revised regional cooperative emission reduction interest distribution program. Finally, the Beijing-Tianjin-Hebei cooperation emission reduction system as the object of the design of the interest distribution programs are exemplified and the result shows that the revised program is more in line with the premise that the greater the risks of members and the better the performance of the reduction, the more interests should be. The revised interest distribution strategy can greatly improve the effectiveness and risk-taking capacity of the local government's emission reduction and enhance the stability of the cooperative relationship.
引文
[1] Yu L., Tan X. J., Yu Y., et al. Assessment of Impacts of Hubei Pilot Emission Trading Schemes in China——A CGE-analysis Using Term CO2 Model[J]. Applied Energy, 2017,189:762-769
[2] Edenhofer O., Pichs-Madruga R., Sokona Y., et al. IPCC Special Report on Renewable Energy Sources and Climate Change Mitigation[M]. Cambridge, UK: Cambridge University Press, 2011
[3] Quire C. L., Moriarty R., Andrew R. M., et al. Global Carbon Budget 2014[J]. Earth System Science Data Discussions, 2015,7(2):521-610
[4] 傅京燕. 碳交易试点市场建设的中国经验[N]. 中国社会科学报, 2016-11-04(006)
[5] Jiang M. X., Yang D. X., Chen Z. Y., et al. Market Power in Auction and Efficiency in Emission Permits Allocation[J]. Journal of Environmental Management, 2016,183(Pt 3):576
[6] 孙慧,刘媛媛. 中国区际碳排放差异与损益偏离现象分析[J]. 管理评论, 2016,28(10):89-96
[7] 林伯强,黄光晓. 梯度发展模式下中国区域碳排放的演化趋势——基于空间分析的视角[J]. 金融研究, 2011,(12):35-46
[8] 苑清敏,李想. 基于产业梯度的京津冀合作减排分析[J]. 科技管理研究, 2015,(16):225-229
[9] 李炫榆,宋海清. 区域减排合作路径探寻——基于结构效应与二氧化碳排放的空间面板数据实证分析[J]. 福建师范大学学报(哲学社会科学版), 2015,(1):29-35
[10] 邢华. 我国区域合作的纵向嵌入式治理机制研究:基于交易成本的视角[J]. 中国行政管理, 2015,(10):80-84
[11] Uddin N., Taplin R. Regional Cooperation in Widening Energy Access and Mitigating Climate Change: Current Programs and Future Potential[J]. Global Environmental Change, 2015,35:497-504
[12] 王金南,宁淼,孙亚梅. 区域大气污染联防联控的理论与方法分析[J]. 环境与可持续发展, 2012,37(5):5-10
[13] Wang Y. A Game Pattern Analysis of the Cooperation and Competition of Global Carbon Emission Reduction[J]. Advanced Materials Research, 2012,524-527:2352-2355
[14] Zhang B., Wang Z., Yin J., et al. CO2, Emission Reduction within Chinese Iron & Steel Industry: Practices, Determinants and Performance[J]. Journal of Cleaner Production, 2012,33:167-178
[15] Pan X. Y., Zhao D., Wu C. X. Enterprises’ Emission Reduction Cooperation in Carbon Supply Chain[J]. Open Cybernetics & Systemics Journal, 2014,8(1):931-937
[16] Nash J. Two-person Cooperative Games[J]. Econometrical, 1953,21(1):128-140
[17] 曹霞,于娟,张路蓬. 不同联盟规模下产学研联盟稳定性影响因素及演化研究[J]. 管理评论, 2016,28(2):3-14
[18] Chen S. H. Driving Factors of External Funding and Funding Effects on Academic Innovation Performance in University-industry-government Linkages[J]. Centimetric, 2013,94(3):1077-1098
[19] 谢晶晶,窦祥胜. 基于合作博弈的碳配额交易价格形成机制研究[J]. 管理评论, 2016,28(2):15-24
[20] 王奇,吴华峰,李明全. 基于博弈分析的区域环境合作及收益分配研究[J]. 中国人口·资源与环境, 2014,24(10):11-16
[21] 陈忠全,徐雨森,杨海峰. 基于Shapley分配的排污权交易联盟博弈[J]. 系统工程, 2016,34(1):34-40
[22] 薛俭,谢婉林,李常敏. 京津冀大气污染治理省际合作博弈模型[J]. 系统工程理论与实践, 2014,34(3):810-816
[23] Dinar A., Howitt R. E. Mechanisms for Allocation of Environmental Control Cost: Empirical Tests of Acceptability and Stability[J]. Journal of Environmental Management, 1997,49(2):183-203
[24] Iill P. E. B., Coombs J. E. Equity Alliance, Stages of Product Development and Alliance Instability[J]. Journal of Engineering and Technology Management, 2004,21(3):191-214
[25] 孙东川,叶飞. 动态联盟利益分配的Nash谈判模型研究[J]. 科研管理, 2001,(3):91-95
[26] Petros Jan L., Accouri G. Time-consistent Shapley Value Allocation of Pollution Cost Reduction[J]. Journal of Economic Dynamics & Control, 2003,27(3):381-398
[27] 李柏洲,罗小芳. 基于Shapley值法的产学研合作型企业原始创新收益分配研究[J]. 运筹与管理, 2013,22(4):220-224
[28] 时茜茜,朱建波,盛昭瀚. 重大工程供应链协同合作利益分配研究[J]. 中国管理科学, 2017,25(5):42-51
[29] Webster M., Santen N., Parpas P. An Approximate Dynamic Programming Framework for Modeling Global Climate Policy under Decision-dependent Uncertainty[J]. Computational Management Science, 2012,9(3):339-362
[30] 陈文颖,高鹏飞,何建坤. 二氧化碳减排对中国未来GDP增长的影响[J]. 清华大学学报(自然科学版), 2004,(6):744-747
[31] 王明喜,王明荣,汪寿阳,等. 最优减排策略及其实施的理论分析[J]. 管理评论, 2010,22(6):42-47
[32] 董保民. 合作博弈论[M]. 北京: 中国市场出版社, 2008
[33] 杨怀珍,霍玉龙,董迎,等. 随机需求时上游段VMI模式利益分配模型研究[J]. 工业工程与管理, 2015,20(2):74-78
[34] Kyparisis J. On Uniqueness of Kuhn-Tucker Multipliers in Nonlinear Programming[J]. Mathematical Programming, 1985,32(2):242-246
[35] 郝艳丽. 物流企业动态联盟的构建及收益分配契约设计研究[D]. 天津大学硕士学位论文, 2009
[36] 程启月. 评测指标权重确定的结构熵权法[J]. 系统工程理论与实践, 2010,30(7):1225-1228
[37] 王苏生,胡王江,付波航. 新常态下的区域协调发展与区域合作——第二十届全国经济地理研究会年会观点综述[J]. 区域经济评论, 2017,(4):140-146
[38] Zhou H., Wang J., Qiu Y. Application of the Cross Entropy Method to the Credit Risk Assessment in an Early Warning System[C]//International Symposiums on Information Processing. IEEE Computer Society, 2008
[39] 葛秋萍,汪明月. 产学研协同创新技术转移风险评价研究——基于层次分析法和模糊综合评价法[J]. 科技进步与对策, 2015,(10):107-113
[40] 张道武,汤书昆,徐旭初. 合作创新联盟成员绩效评估的综合分析机制[J]. 系统工程理论方法应用, 2004,13(2):100-105
[41] Al-Harbi A. S. Application of the AHP in Project Management[J]. International Journal of Project Management, 2001,19(1):19-27
[42] 王春嬉,杨水利. 基于成果转化贡献的科研团队成员收益分配研究[J]. 运筹与管理, 2017,26(5):184-188
[43] 姚奕,倪勤. 各地区碳减排能力综合评价研究——基于投影寻踪分类模型[J]. 运筹与管理, 2012,(5):193-199
[44] 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
[45] 薛俊宁. 高技术产业与碳排放强度——中国省际面板数据分析[J]. 工业技术经济, 2013,(7):117-123
[46] Webster M., Santen N., Parpas P. An Approximate Dynamic Programming Framework for Modeling Global Climate Policy under Decision-dependent Uncertainty[J]. Computational Management Science, 2012,9(3):339-362
[2] Edenhofer O., Pichs-Madruga R., Sokona Y., et al. IPCC Special Report on Renewable Energy Sources and Climate Change Mitigation[M]. Cambridge, UK: Cambridge University Press, 2011
[3] Quire C. L., Moriarty R., Andrew R. M., et al. Global Carbon Budget 2014[J]. Earth System Science Data Discussions, 2015,7(2):521-610
[4] 傅京燕. 碳交易试点市场建设的中国经验[N]. 中国社会科学报, 2016-11-04(006)
[5] Jiang M. X., Yang D. X., Chen Z. Y., et al. Market Power in Auction and Efficiency in Emission Permits Allocation[J]. Journal of Environmental Management, 2016,183(Pt 3):576
[6] 孙慧,刘媛媛. 中国区际碳排放差异与损益偏离现象分析[J]. 管理评论, 2016,28(10):89-96
[7] 林伯强,黄光晓. 梯度发展模式下中国区域碳排放的演化趋势——基于空间分析的视角[J]. 金融研究, 2011,(12):35-46
[8] 苑清敏,李想. 基于产业梯度的京津冀合作减排分析[J]. 科技管理研究, 2015,(16):225-229
[9] 李炫榆,宋海清. 区域减排合作路径探寻——基于结构效应与二氧化碳排放的空间面板数据实证分析[J]. 福建师范大学学报(哲学社会科学版), 2015,(1):29-35
[10] 邢华. 我国区域合作的纵向嵌入式治理机制研究:基于交易成本的视角[J]. 中国行政管理, 2015,(10):80-84
[11] Uddin N., Taplin R. Regional Cooperation in Widening Energy Access and Mitigating Climate Change: Current Programs and Future Potential[J]. Global Environmental Change, 2015,35:497-504
[12] 王金南,宁淼,孙亚梅. 区域大气污染联防联控的理论与方法分析[J]. 环境与可持续发展, 2012,37(5):5-10
[13] Wang Y. A Game Pattern Analysis of the Cooperation and Competition of Global Carbon Emission Reduction[J]. Advanced Materials Research, 2012,524-527:2352-2355
[14] Zhang B., Wang Z., Yin J., et al. CO2, Emission Reduction within Chinese Iron & Steel Industry: Practices, Determinants and Performance[J]. Journal of Cleaner Production, 2012,33:167-178
[15] Pan X. Y., Zhao D., Wu C. X. Enterprises’ Emission Reduction Cooperation in Carbon Supply Chain[J]. Open Cybernetics & Systemics Journal, 2014,8(1):931-937
[16] Nash J. Two-person Cooperative Games[J]. Econometrical, 1953,21(1):128-140
[17] 曹霞,于娟,张路蓬. 不同联盟规模下产学研联盟稳定性影响因素及演化研究[J]. 管理评论, 2016,28(2):3-14
[18] Chen S. H. Driving Factors of External Funding and Funding Effects on Academic Innovation Performance in University-industry-government Linkages[J]. Centimetric, 2013,94(3):1077-1098
[19] 谢晶晶,窦祥胜. 基于合作博弈的碳配额交易价格形成机制研究[J]. 管理评论, 2016,28(2):15-24
[20] 王奇,吴华峰,李明全. 基于博弈分析的区域环境合作及收益分配研究[J]. 中国人口·资源与环境, 2014,24(10):11-16
[21] 陈忠全,徐雨森,杨海峰. 基于Shapley分配的排污权交易联盟博弈[J]. 系统工程, 2016,34(1):34-40
[22] 薛俭,谢婉林,李常敏. 京津冀大气污染治理省际合作博弈模型[J]. 系统工程理论与实践, 2014,34(3):810-816
[23] Dinar A., Howitt R. E. Mechanisms for Allocation of Environmental Control Cost: Empirical Tests of Acceptability and Stability[J]. Journal of Environmental Management, 1997,49(2):183-203
[24] Iill P. E. B., Coombs J. E. Equity Alliance, Stages of Product Development and Alliance Instability[J]. Journal of Engineering and Technology Management, 2004,21(3):191-214
[25] 孙东川,叶飞. 动态联盟利益分配的Nash谈判模型研究[J]. 科研管理, 2001,(3):91-95
[26] Petros Jan L., Accouri G. Time-consistent Shapley Value Allocation of Pollution Cost Reduction[J]. Journal of Economic Dynamics & Control, 2003,27(3):381-398
[27] 李柏洲,罗小芳. 基于Shapley值法的产学研合作型企业原始创新收益分配研究[J]. 运筹与管理, 2013,22(4):220-224
[28] 时茜茜,朱建波,盛昭瀚. 重大工程供应链协同合作利益分配研究[J]. 中国管理科学, 2017,25(5):42-51
[29] Webster M., Santen N., Parpas P. An Approximate Dynamic Programming Framework for Modeling Global Climate Policy under Decision-dependent Uncertainty[J]. Computational Management Science, 2012,9(3):339-362
[30] 陈文颖,高鹏飞,何建坤. 二氧化碳减排对中国未来GDP增长的影响[J]. 清华大学学报(自然科学版), 2004,(6):744-747
[31] 王明喜,王明荣,汪寿阳,等. 最优减排策略及其实施的理论分析[J]. 管理评论, 2010,22(6):42-47
[32] 董保民. 合作博弈论[M]. 北京: 中国市场出版社, 2008
[33] 杨怀珍,霍玉龙,董迎,等. 随机需求时上游段VMI模式利益分配模型研究[J]. 工业工程与管理, 2015,20(2):74-78
[34] Kyparisis J. On Uniqueness of Kuhn-Tucker Multipliers in Nonlinear Programming[J]. Mathematical Programming, 1985,32(2):242-246
[35] 郝艳丽. 物流企业动态联盟的构建及收益分配契约设计研究[D]. 天津大学硕士学位论文, 2009
[36] 程启月. 评测指标权重确定的结构熵权法[J]. 系统工程理论与实践, 2010,30(7):1225-1228
[37] 王苏生,胡王江,付波航. 新常态下的区域协调发展与区域合作——第二十届全国经济地理研究会年会观点综述[J]. 区域经济评论, 2017,(4):140-146
[38] Zhou H., Wang J., Qiu Y. Application of the Cross Entropy Method to the Credit Risk Assessment in an Early Warning System[C]//International Symposiums on Information Processing. IEEE Computer Society, 2008
[39] 葛秋萍,汪明月. 产学研协同创新技术转移风险评价研究——基于层次分析法和模糊综合评价法[J]. 科技进步与对策, 2015,(10):107-113
[40] 张道武,汤书昆,徐旭初. 合作创新联盟成员绩效评估的综合分析机制[J]. 系统工程理论方法应用, 2004,13(2):100-105
[41] Al-Harbi A. S. Application of the AHP in Project Management[J]. International Journal of Project Management, 2001,19(1):19-27
[42] 王春嬉,杨水利. 基于成果转化贡献的科研团队成员收益分配研究[J]. 运筹与管理, 2017,26(5):184-188
[43] 姚奕,倪勤. 各地区碳减排能力综合评价研究——基于投影寻踪分类模型[J]. 运筹与管理, 2012,(5):193-199
[44] 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
[45] 薛俊宁. 高技术产业与碳排放强度——中国省际面板数据分析[J]. 工业技术经济, 2013,(7):117-123
[46] Webster M., Santen N., Parpas P. An Approximate Dynamic Programming Framework for Modeling Global Climate Policy under Decision-dependent Uncertainty[J]. Computational Management Science, 2012,9(3):339-362