Trading, storage, or penalty? Uncovering firms' decision-making behavior in the Shanghai emissions trading scheme: Insights from agent-based modeling
Gang Kou and
Energy Economics, 2023, vol. 117, issue C
The emissions trading scheme (ETS) has become a flagship climatic initiative for regulating greenhouse gas (GHG) emissions. Under an ETS, the emitting firm must simultaneously deal with changing carbon prices and the number of permits and the trade-off between permit trading (if one should buy, sell, or reserve) and permit-consuming production. This study characterizes the different compliance strategies' trade-offs, logic, and options among regulated emitting firms under an ETS. Consequently, this study provides firm-level evidence of regulated firms' strategic responses under the Shanghai ETS, considering detailed firm information, heterogeneous industry characteristics, and ETS architects. The proposed model simulated the trading interactions among diversified firms to portray the firms' decision-making process, and the emergent effects on the ETS market were identified. The results indicate that: 1) the carbon price experiences a non-monotonic “L-shaped” trend, which maintains an initial low level and increases sharply after crossing a threshold; 2) with increasing carbon prices, the trading in ETS becomes more active, especially among the low-emission firms; 3) the current ETS penalty is too limited and generic, which inadequately induces technological development and carbon reduction among firms. Finally, policy suggestions are provided for future optimization of the ETS mechanism. Overall, this study contributes to operation management literature by evaluating decision-making behaviors in a dynamic environment. Our findings have global implications for policymakers and managers in the private sector.
Keywords: Decision support systems; Emissions trading scheme (ETS); Compliance strategies; Agent-based model; Firm-level evidence (search for similar items in EconPapers)
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Persistent link: https://EconPapers.repec.org/RePEc:eee:eneeco:v:117:y:2023:i:c:s0140988322005928
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