基于实验经济学仿真构建碳排放交易的多代理模型

Translated title of the contribution: Modeling Multi-agent in Carbon Emission Market Based on Experimental Economics Simulations

Jiang Chao, Xue Yusheng, Huang Jie, Qiuwei Wu, Guangya Yang

Research output: Contribution to journalJournal articleResearchpeer-review

Abstract

The market efficiency and regulation effects of carbon emission trading strongly depend on decisions made by different kinds of participants in the carbon emission market. Therefore, the participants, especially the policy designers and regulators, should understand the participants' trading behaviors and their underlying mechanisms. Experimental economics can reflect participants' "bounded rationality" characteristic through humans' participating in experiments. However, the scale of experiment is limited due to the difficulty to have enough qualified human participants, and the comparability among the multi-scenario experiments is also limited due to the variations of human participants' concentration level. This paper adopts a hybrid interactive simulation methodology. Human-subjected experiments with a small group of human participants are conducted. Major driving factors and their influencing rules on human participants' uncertain behaviors are extracted, which can aid the construction of multi-agent stochastic models with the same distribution characteristics. In this way, only a small group of humans are needed to represent the special decision makers, who can interact with large numbers of multi-agents constructed by the aforementioned method. The methodology discussed can overcome the scale limitations and meanwhile maintain the merits of experimental economics.
Translated title of the contributionModeling Multi-agent in Carbon Emission Market Based on Experimental Economics Simulations
Original languageChinese
JournalDianli Xitong Zidonghua
Volume38
Issue number17
Pages (from-to)80-86
ISSN1000-1026
DOIs
Publication statusPublished - 2014

Keywords

  • Carbon emission trading
  • Experimental economics
  • Stochastic multi-agent modeling
  • Computational economics
  • Hybrid interactive simulation

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