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  4. Modeling the emission trading scheme from an agent-based perspective: System dynamics emerging from firms' coordination among abatement options
 
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2020
Journal Article
Title

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

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.
Author(s)
Yu, Song-min  orcid-logo
Fraunhofer-Institut für System- und Innovationsforschung ISI  
Fan, Ying
School of Economics and Management, Beihang Univ.
Zhu, Lei
School of Economics and Management, Beihang Univ.
Eichhammer, Wolfgang  orcid-logo
Fraunhofer-Institut für System- und Innovationsforschung ISI  
Journal
European Journal of Operational Research  
Open Access
DOI
10.1016/j.ejor.2020.03.080
Language
English
Fraunhofer-Institut für System- und Innovationsforschung ISI  
Keyword(s)
  • multi-agent Systems

  • heterogeneity

  • Bounded rationality

  • multiple-population

  • genetic algorithm

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