我国工业源碳减排的博弈分析

Game Analysis of Carbon Emission Reduction of China's Industrial Source

碳排放量逐年上升、全球气候变暖等已成为不争的事实。人类进行工业活动被看作是主要原因。工业源在节能减排和碳汇决策中的行为方式关系到我国能否实现2020年单位GDP二氧化碳排放要比2005年下降40%～45%的目标。基于此,文章从博弈理论视角,建立博弈模型探究工业源碳减排,分析了完全信息下均作为"理性经济人"的工业协会与工业企业之间、工业源企业之间采取不同的策略对工业源碳减排的效果。研究结果表明:工业协会的监管、工业源之间的相互合作以及工业协会与工业源之间相互协作可以对工业源碳减排发挥很大的作用,实现效用最大化;其次,工业源生产收益越高、减排成本越小、减排获得的企业形象收益越高、工业协会对减排一方补贴越高、工业协会对不减排惩罚度越高时,工业源选择进行碳减排的概率很大。最后,基于研究结论提出促进工业源碳减排的政策建议,以期为相关部门提供现实意义的参考。

Carbon emissions＇ rising and global warming has become an indisputable fact in the world. Human industrial activities are looked as the main reason to cause them. And the behavior of industrial sources in the decision-making of energy conservation and carbon sequestration related to whether our ability to achieve the target of carbon dioxide emissions per unit GDP decreased by 40% to 45% in 2020 than in 2005 or not. Based On this, from the perspective of game theory, the research sets up game model to explore carbon emission reduction of the industrial source, and analyzes the effect of industrial associations and industrial enterprises, among industrial sources as ＂rational economic man＂ to adopt different strategy to reduce carbon emission. The results show that： the supervision of the Industry Association, the mutual cooperation between the industrial sources and their effective integration can play a significant role in carbon emission reduction of the industrial source, and achieve utility maximization; when the higher productivity gains of industrial source, the smaller cost of reduction row, the higher corporate image obtained by the reduction proceeds, and the higher degree of punishing not to reduce carbon emission, the probability of the industrial source selects to reduce carbon emission are all higher. Finally, based on the conclusions of this study, the paper puts forward policy recommendations to promote carbon emission reduction of industrial source, and in order to provide the reference of practical significance for the relevant departments.