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Regulatory game model of carbon leakage collusion: Prospect theory and verification agency dynamics

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  • Xing, Qingsong
  • Yan, Yanlin
  • Deng, Fumin
  • Wang, Peng

Abstract

The compliance of carbon data quality is a key factor that concerns national image, market stability, and policy-making, and has always been one of the hot issues widely concerned by all sectors of society. As an important tool for promoting corporate environmental, social, and governance (ESG) behaviors, the Emission Trading System (ETS) plays a significant role in achieving carbon emission reduction targets. This study introduces prospect theory to construct a regulatory game model of carbon leakage collusion behavior involving both passive and active participation of verification institutions, and discusses the collusion conditions of various participants under different model parameters. Through numerical simulation, the study explores the impact of key factors such as collusion benefits on the shift in the collusion behavior of verification institutions and on the collusion situation of multiple behavior subjects under different model parameters. The main conclusions are as follows: 1) The choice of collusion method by the actors of carbon verification institutions is influenced by their subjective perception of the probability of successful government supervision and the benefits of collusion; 2) The behavior subjects are more sensitive to changes in the degree of loss aversion coefficient than to changes in the degree of marginal sensitivity coefficient.

Suggested Citation

  • Xing, Qingsong & Yan, Yanlin & Deng, Fumin & Wang, Peng, 2025. "Regulatory game model of carbon leakage collusion: Prospect theory and verification agency dynamics," Energy Economics, Elsevier, vol. 150(C).
    • Handle: RePEc:eee:eneeco:v:150:y:2025:i:c:s0140988325007017
    DOI: 10.1016/j.eneco.2025.108874
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    References listed on IDEAS

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    1. Yin, Chuanzhong & Zhang, Zi-Ang & Fu, Xiaowen & Ge, Ying-En, 2024. "A low-carbon transportation network: Collaborative effects of a rail freight subsidy and carbon trading mechanism," Transportation Research Part A: Policy and Practice, Elsevier, vol. 184(C).
    2. Tversky, Amos & Kahneman, Daniel, 1992. "Advances in Prospect Theory: Cumulative Representation of Uncertainty," Journal of Risk and Uncertainty, Springer, vol. 5(4), pages 297-323, October.
    3. Pan, Yanchun & Yang, Wen & Ma, Nan & Chen, Zhimin & Zhou, Ming & Xiong, Yi, 2019. "Game analysis of carbon emission verification: A case study from Shenzhen's cap-and-trade system in China," Energy Policy, Elsevier, vol. 130(C), pages 418-428.
    4. Liao, Feimei & Sun, Yinghao & Xu, Shulin, 2023. "Financial report comment letters and greenwashing in environmental, social and governance disclosures: Evidence from China," Energy Economics, Elsevier, vol. 127(PB).
    5. Ximin (Natalie) Huang & Tarkan Tan & L. Beril Toktay, 2021. "Carbon Leakage: The Impact of Asymmetric Regulation on Carbon‐Emitting Production," Production and Operations Management, Production and Operations Management Society, vol. 30(6), pages 1886-1903, June.
    6. Li, Xiaosheng & Wang, Ruirui & Shen, Zhiyang & Song, Malin, 2024. "Government environmental signals, government–Enterprise collusion and corporate pollution transfer," Energy Economics, Elsevier, vol. 139(C).
    7. Lionel Fontagné & Katheline Schubert, 2023. "The Economics of Border Carbon Adjustment: Rationale and Impacts of Compensating for Carbon at the Border," Annual Review of Economics, Annual Reviews, vol. 15(1), pages 389-424, September.
    8. Daniel Kahneman & Amos Tversky, 2013. "Prospect Theory: An Analysis of Decision Under Risk," World Scientific Book Chapters, in: Leonard C MacLean & William T Ziemba (ed.), HANDBOOK OF THE FUNDAMENTALS OF FINANCIAL DECISION MAKING Part I, chapter 6, pages 99-127, World Scientific Publishing Co. Pte. Ltd..
    9. Joseph S Shapiro, 2021. "The Environmental Bias of Trade Policy," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 136(2), pages 831-886.
    10. Meredith L. Fowlie & Mar Reguant, 2022. "Mitigating Emissions Leakage in Incomplete Carbon Markets," Journal of the Association of Environmental and Resource Economists, University of Chicago Press, vol. 9(2), pages 307-343.
    11. Dechezleprêtre, Antoine & Gennaioli, Caterina & Martin, Ralf & Muûls, Mirabelle & Stoerk, Thomas, 2022. "Searching for carbon leaks in multinational companies," Journal of Environmental Economics and Management, Elsevier, vol. 112(C).
    12. Wang, Xiao-Qing & Su, Chi-Wei & Lobonţ, Oana-Ramona & Li, Hao & Nicoleta-Claudia, Moldovan, 2022. "Is China's carbon trading market efficient? Evidence from emissions trading scheme pilots," Energy, Elsevier, vol. 245(C).
    13. Li, Yanbin & Liu, Chang & Wang, Jiani & Wang, Yuan & Yang, Xiuqi & Li, Yun, 2024. "Data fraud in the carbon emissions trading market: A tripartite evolutionary game analysis from China," Utilities Policy, Elsevier, vol. 91(C).
    14. Yu, Ziling & Wang, Zhe & Ma, Mengjuan & Ma, Lili, 2024. "The impact of carbon leakage from energy-saving targets: A moderating effect based on new-energy model cities," Applied Energy, Elsevier, vol. 375(C).
    15. Gao, Yuning & Li, Meng & Xue, Jinjun & Liu, Yu, 2020. "Evaluation of effectiveness of China's carbon emissions trading scheme in carbon mitigation," Energy Economics, Elsevier, vol. 90(C).
    16. Krishnan S. Anand & François C. Giraud-Carrier, 2020. "Pollution Regulation of Competitive Markets," Management Science, INFORMS, vol. 66(9), pages 4193-4206, September.
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