Modeling the emission trading scheme from an agent-based perspective: System dynamics emerging from firms’ coordination among abatement options

排放交易 方案(数学) 透视图(图形) 温室气体 动力学(音乐) 系统动力学 运筹学 计算机科学 经济 业务 微观经济学 数学 物理 生物 人工智能 数学分析 声学 生态学
作者
Songmin Yu,Ying Fan,Lei Zhu,Wolfgang Eichhammer
出处
期刊:European Journal of Operational Research [Elsevier BV]
卷期号:286 (3): 1113-1128 被引量:51
标识
DOI:10.1016/j.ejor.2020.03.080
摘要

Though sharing a similar practice form, the emission trading scheme is distinguished from traditional financial markets: firms coordinate three abatement options at the micro level, including allowance trading, output adjustment, and low-carbon technology adoption. Then, at the macro level, this leads to dynamic interactions among allowance market, output market, and low-carbon technology diffusion. This is the fundamental characteristic of the emission trading scheme, and modeling the dynamics behind is a major difficulty for relevant studies, especially when following complexities are considered: (1) different planning horizons of the three abatement options, (2) heterogeneity among sectors and firms, and (3) details of firms’ production and optional low-carbon technologies. Aiming at this difficulty, we establish an agent-based model for the emission trading scheme, and within a novel multi-level time frame, the fundamental characteristic is reflected and the complexities are considered. Firms’ production and low-carbon technologies are discretely modeled at a process level from a bottom-up perspective, and based on European data, our model is calibrated to cover 5 industrial sectors, 11 emission-intensive products, 25 production processes, and 52 low-carbon technologies. With this model, the emergence properties and uncertainty of the system are captured, and the non-linear impact of the abatement target is reflected and discussed. We find that, after a certain level, higher target leads to lower allowance price uncertainty but stronger output impact, which is a trade-off for setting the abatement target.
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