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

被引:53
作者
Yu, Song-min [1 ]
Fan, Ying [2 ]
Zhu, Lei [2 ]
Eichhammer, Wolfgang [1 ,3 ]
机构
[1] Fraunhofer Inst Syst & Innovat Res, Breslauer Str 48, D-76139 Karlsruhe, Germany
[2] Beihang Univ, Sch Econ & Management, 37 Xueyuan Rd, Beijing, Peoples R China
[3] Univ Utrecht, Copernicus Inst Sustainable Dev, NL-3584 CB Utrecht, Netherlands
基金
中国国家自然科学基金;
关键词
Multi-agent systems; Heterogeneity; Bounded rationality; Multiple-population Genetic Algorithm; TECHNOLOGICAL-INNOVATION; POLICY; INDUSTRY; CHINA; COMPETITIVENESS; SIMULATION; MARKETS; LEAKAGE; DEMAND; SECTOR;
D O I
10.1016/j.ejor.2020.03.080
中图分类号
C93 [管理学];
学科分类号
12 ; 1201 ; 1202 ; 120202 ;
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. (C) 2020 Elsevier B.V. All rights reserved.
引用
收藏
页码:1113 / 1128
页数:16
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