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基于集体行动逻辑的京津冀雾霾合作治理演化博弈分析
引用本文:初钊鹏,刘昌新,朱婧.基于集体行动逻辑的京津冀雾霾合作治理演化博弈分析[J].中国人口.资源与环境,2017(9):56-65.
作者姓名:初钊鹏  刘昌新  朱婧
作者单位:1. 东北大学工商管理学院,辽宁沈阳110819;东北大学秦皇岛分校经济学院,河北秦皇岛066004;2. 中国科学院科技战略咨询研究院,北京,100190;3. 东北大学秦皇岛分校经济学院,河北秦皇岛,066004
基金项目:国家社会科学基金项目“空间正义视阈下京津冀协同发展的城市群治理研究”(17BJY054),河北省自然科学基金项目“基于情景分析的河北省碳减排环境效应与碳市场路径研究”(D2016501095)
摘    要:当前京津冀地区在雾霾问题上面临环境外部性困扰和集体行动困境,其根源在于地方政府作为雾霾合作治理集体成员的收益是不对称的,而割裂集体行动中收益与损失之间的联系是一种纠正环境外部性市场失灵的政府失灵。奥尔森集体行动的逻辑在京津冀三地政府执行雾霾合作治理规制行为上表现为私人理性与集体理性的动态重复博弈。针对京津冀地区大气污染联防联控执行状况,基于集体行动的逻辑视角,借助演化经济学研究工具,构建京津冀三地政府在雾霾合作治理执行策略的猎鹿模型、拓展模型的演化、随机和动态的博弈过程,探究地方政府执行雾霾合作治理集体行动的行为特征及其影响因素。根据复制动态方程探讨博弈主体行为演化特征和演化稳定策略,采用数值仿真方法分析不同情形下系统演化轨迹及演化均衡状态,考察随机因素对系统演化均衡状态的影响以及实现区域环境合作联盟的动态演化均衡机制。研究发现,京津冀三地政府在雾霾合作治理执行过程中的动态演化,很大程度上取决于本地区在区域整体中的环境偏好系数和搭便车收益与集体行动收益的比值。因此,中央政府要健全跨区域环境治理的制度建设,为京津冀地区建立一致的区域环境质量标准,有效降低地方政府在合作治理雾霾集体行动中的搭便车收益,以立法的形式对约束地方政府承担环境治理责任的强制和选择性激励措施加以确定。此外,将雾霾造成的经济损失作为重要指标纳入地方官员政绩考核体系,加强对地方政府雾霾治理执行情况的监管力度,实现合作治理雾霾集体行动责任落实的帕累托改进。

关 键 词:集体行动  演化博弈  猎鹿模型  数值仿真

Evolutionary game analysis on cooperative governance of haze in Beijing-Tianjin-Hebei based on the logic of collective action
CHU Zhao-peng,LIU Chang-xin,ZHU Jing.Evolutionary game analysis on cooperative governance of haze in Beijing-Tianjin-Hebei based on the logic of collective action[J].China Polulation.Resources and Environment,2017(9):56-65.
Authors:CHU Zhao-peng  LIU Chang-xin  ZHU Jing
Abstract:At present,Beijing-Tianjin-Hebei is facing the plight of environmental externalities and collective action on the haze control problem.The root of the problem lies in the fact that as a member of the haze cooperative governance,the benefit of local government is asymmetrical.Fragmented the link between benefits and losses of collection action to correct the environmental externality is a kind of market failure replaced by government failure.The logic of Olsen's collective action is manifested as a dynamic repetitive game of private rationality and collective rationality in the implementation of the haze cooperative governance in Beijing-Tianjin-Hebei.In view of the collective action of air pollution joint control in Beijing-Tianjin-Hebei,this paper constructs stag hunt model to study government's implementation strategy of haze cooperation governance by means of evolutionary research tools.The game process is divided into evolutionary,stochastic and dynamic three stages,which explores the behavioral characteristics and influencing factors of local governments in collective action of Haze control.According to the replicator of dynamic equation,the evolution of participant's behavior and evolutionary stable strategy are discussed.The numerical simulation method is used to analyze the evolutionary trends and evolution equilibrium of the system under different situations.Model estimates indicate that the evolutionary equilibrium state of the system influenced by stochastic factors and the dynamic equilibrium mechanism achieve the multiregional environmental cooperation alliance.A general finding is that the dynamic evolution of Beijing-Tianjin-Hebei in the implementation of haze cooperative governance is largely dependent on the ratio of free rid income to collective action income and the environmental preference coefficient of the district in the region as a whole.Therefore,it is necessary for central government to improve the cross-regional environmental law system,establish a consistent regional environmental quality standard,and reduce the gain of local government's free ride.More importandy,the coercive and selective incentives thatconstrain local government to take responsibility of environmental governance should be determined in the form of legislation.In addition,the economic losses caused by haze should be bringing into the local officials' performance appraisal system.The central government should strengthen the supervision when local governments conductair pollution control in order to achievethe Pareto improvement of collective action during the course of haze cooperative governance.
Keywords:collective action  evolutionary game  stag hunt model  numerical simulation
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