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互动机制下低碳农业发展中政府与农户的行为选择--基于静态与演化博弈模型的检验
引用本文:陈祺琪.互动机制下低碳农业发展中政府与农户的行为选择--基于静态与演化博弈模型的检验[J].国土资源科技管理,2017,34(2):76-85.
作者姓名:陈祺琪
作者单位:中原工学院经济管理学院,河南郑州450007;系统与工业工程技术研究中心,河南郑州450007;华中农业大学湖北农村发展研究中心,湖北武汉430070
基金项目:国家自然科学基金重点项目,国家自然科学基金面上项目
摘    要:为有效促进我国低碳农业发展,考察低碳农业主体的行为选择及互动影响,从政府与农户的视角出发,构建了完全静态博弈模型与演化博弈模型,探讨了两个主体在低碳农业发展中的行为选择。研究结果表明:(1)基于完全信息静态博弈模型,引入激励机制有利于更好的引导农户采用低碳农业生产,进而取得帕累托最优均衡目标;(2)当政府增加采用低碳农业生产农户的补贴,同时加大对采用传统农业生产方式农户的约束力度,且农户采用低碳农业的综合收益逐渐增加及其成本不断减少时,演化博弈模型中局部均衡点最终演化为政府发展低碳农业,农户采用低碳农业生产这个稳定状态。基于此,分别从政府与农户角度提出了利于低碳农业发展的政策建议。

关 键 词:低碳农业  政府  农户  互动机制  博弈模型

Analysis on the Behavior Choice of the Government and Peasants in theDevelopment of Low Carbon Agriculture under the Interaction Mechanism:Based on the Test of Static Game Model and Evolutionary Game Model
Abstract:The paper built the static game model and the evolutionary game model between the government and the peasants and explored the game processes of their interaction behavior from the perspective of developing the low carbon agriculture in China and behavior selection and interaction of the low carbon agriculture development with regard to two models.The results showed:Firstly,based on the complete information static game model,by introducing the rewards and punishment mechanism,suggestions were made to guide the peasants to adopt low carbon agriculture methods and achieve the equilibrium goal of Pareto Optimum.Secondly,since the the government increased the subsidies for peasants who adopted low carbon agriculture methods while imposing constrains to peasants of the traditional agriculture methods,the partial equilibrium points in the evolutionary game tended to be the Pareto Optimum,i.e.the government is inclined to develop the low carbon agriculture while the peasants switch to low carbon agriculture methods due to increasing benefits and decreasing costs.Suggestions are proposed in this peper to develop low carbon agriculture from the perspective of governments and peasants.
Keywords:low carbon agriculture  government  peasants  interaction mechanism  game model
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