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

Song min Yu, Ying Fan, Lei Zhu*, Wolfgang Eichhammer

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

Abstract

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.

Original languageEnglish
Pages (from-to)1113-1128
Number of pages16
JournalEuropean Journal of Operational Research
Volume286
Issue number3
DOIs
Publication statusPublished - 1 Nov 2020

Funding

The authors would like to thank two anonymous referees, for their constructive suggestions and detailed comments, which helped us to improve the paper. The authors also appreciate the weekly joint seminars at CEEP in Beihang University and CAS, from where the earlier draft of the paper was improved. Support from the National Natural Science Foundation of China (Grant Nos. 71673019 , 71690245 ) and the National Key Research and Development Program of China (Grant No. 2017YFE0101800) is acknowledged. The first author is supported by the CSC-DAAD postdoc scholarship project.

Keywords

  • Bounded rationality
  • Heterogeneity
  • Multi-agent systems
  • Multiple-population Genetic Algorithm

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