IDEAS home Printed from https://ideas.repec.org/a/eee/jocoma/v35y2024ics2405851324000382.html
   My bibliography  Save this article

Nash equilibria in greenhouse gas offset credit markets

Author

Listed:
  • Welsh, Liam
  • Jaimungal, Sebastian

Abstract

One approach to reducing greenhouse gas (GHG) emissions is to incentivise carbon capturing and carbon reducing projects while simultaneously penalising excess GHG output. In this work, we present a novel market framework and characterise the optimal behaviour of GHG offset credit (OC) market participants in both single-player and two-player settings. The single player setting is posed as an optimal stopping and control problem, while the two-player setting is posed as optimal stopping and mixed-Nash equilibria problem. We demonstrate the importance of acting optimally using numerical solutions and Monte Carlo simulations and explore the differences between the homogeneous and heterogeneous players. In both settings, we find that market participants benefit from optimal OC trading and OC generation.

Suggested Citation

  • Welsh, Liam & Jaimungal, Sebastian, 2024. "Nash equilibria in greenhouse gas offset credit markets," Journal of Commodity Markets, Elsevier, vol. 35(C).
    • Handle: RePEc:eee:jocoma:v:35:y:2024:i:c:s2405851324000382
    DOI: 10.1016/j.jcomm.2024.100419
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S2405851324000382
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.jcomm.2024.100419?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Eirik Amundsen & Fridrik Baldursson & Jørgen Mortensen, 2006. "Price Volatility and Banking in Green Certificate Markets," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 35(4), pages 259-287, December.
    2. Arvind Shrivats & Sebastian Jaimungal, 2020. "Optimal Generation and Trading in Solar Renewable Energy Certificate (SREC) Markets," Applied Mathematical Finance, Taylor & Francis Journals, vol. 27(1-2), pages 99-131, July.
    3. Liu, Yue & Sun, Huaping & Meng, Bo & Jin, Shunlin & Chen, Bin, 2023. "How to purchase carbon emission right optimally for energy-consuming enterprises? Analysis based on optimal stopping model," Energy Economics, Elsevier, vol. 124(C).
    4. Martin J. Osborne & Ariel Rubinstein, 1994. "A Course in Game Theory," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262650401, December.
    5. Philippe Casgrain & Brian Ning & Sebastian Jaimungal, 2022. "Deep Q-Learning for Nash Equilibria: Nash-DQN," Applied Mathematical Finance, Taylor & Francis Journals, vol. 29(1), pages 62-78, January.
    6. Seifert, Jan & Uhrig-Homburg, Marliese & Wagner, Michael, 2008. "Dynamic behavior of CO2 spot prices," Journal of Environmental Economics and Management, Elsevier, vol. 56(2), pages 180-194, September.
    7. Hitzemann, Steffen & Uhrig-Homburg, Marliese, 2018. "Equilibrium Price Dynamics of Emission Permits," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 53(4), pages 1653-1678, August.
    8. Steven Campbell & Yichao Chen & Arvind Shrivats & Sebastian Jaimungal, 2021. "Deep Learning for Principal-Agent Mean Field Games," Papers 2110.01127, arXiv.org.
    9. René Carmona & Gökçe Dayanıklı & Mathieu Laurière, 2022. "Mean Field Models to Regulate Carbon Emissions in Electricity Production," Dynamic Games and Applications, Springer, vol. 12(3), pages 897-928, September.
    10. Arvind V. Shrivats & Dena Firoozi & Sebastian Jaimungal, 2022. "A mean‐field game approach to equilibrium pricing in solar renewable energy certificate markets," Mathematical Finance, Wiley Blackwell, vol. 32(3), pages 779-824, July.
    11. Hustveit, Magne & Frogner, Jens Sveen & Fleten, Stein-Erik, 2017. "Tradable green certificates for renewable support: The role of expectations and uncertainty," Energy, Elsevier, vol. 141(C), pages 1717-1727.
    12. Philippe Casgrain & Brian Ning & Sebastian Jaimungal, 2019. "Deep Q-Learning for Nash Equilibria: Nash-DQN," Papers 1904.10554, arXiv.org, revised Oct 2022.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Dena Firoozi & Arvind V Shrivats & Sebastian Jaimungal, 2021. "Principal agent mean field games in REC markets," Papers 2112.11963, arXiv.org, revised Jun 2022.
    2. Liam Welsh & Sebastian Jaimungal, 2024. "Nash Equilibria in Greenhouse Gas Offset Credit Markets," Papers 2401.01427, arXiv.org, revised Jun 2024.
    3. Arvind Shrivats & Dena Firoozi & Sebastian Jaimungal, 2020. "A Mean-Field Game Approach to Equilibrium Pricing in Solar Renewable Energy Certificate Markets," Papers 2003.04938, arXiv.org, revised Aug 2021.
    4. Arvind V. Shrivats & Dena Firoozi & Sebastian Jaimungal, 2022. "A mean‐field game approach to equilibrium pricing in solar renewable energy certificate markets," Mathematical Finance, Wiley Blackwell, vol. 32(3), pages 779-824, July.
    5. Arvind Shrivats & Sebastian Jaimungal, 2019. "Optimal Behaviour in Solar Renewable Energy Certificate (SREC) Markets," Papers 1904.06337, arXiv.org, revised Apr 2020.
    6. Estelle Cantillon & Aurélie Slechten, 2018. "Information Aggregation in Emissions Markets with Abatement," Annals of Economics and Statistics, GENES, issue 132, pages 53-79.
    7. St'ephane Cr'epey & Mekonnen Tadese & Gauthier Vermandel, 2024. "Sensitivity Analysis of emissions Markets: A Discrete-Time Radner Equilibrium Approach," Papers 2411.06185, arXiv.org.
    8. Coulon, Michael & Khazaei, Javad & Powell, Warren B., 2015. "SMART-SREC: A stochastic model of the New Jersey solar renewable energy certificate market," Journal of Environmental Economics and Management, Elsevier, vol. 73(C), pages 13-31.
    9. Sebastian Jaimungal, 2022. "Reinforcement learning and stochastic optimisation," Finance and Stochastics, Springer, vol. 26(1), pages 103-129, January.
    10. Huang, Zhehao & Dong, Hao & Jia, Shuaishuai, 2022. "Equilibrium pricing for carbon emission in response to the target of carbon emission peaking," Energy Economics, Elsevier, vol. 112(C).
    11. Steven Campbell & Yichao Chen & Arvind Shrivats & Sebastian Jaimungal, 2021. "Deep Learning for Principal-Agent Mean Field Games," Papers 2110.01127, arXiv.org.
    12. Xin-gang, Zhao & Yi, Zuo & Hui, Wang & Zhen, Wang, 2022. "How can the cost and effectiveness of renewable portfolio standards be coordinated? Incentive mechanism design from the coevolution perspective," Renewable and Sustainable Energy Reviews, Elsevier, vol. 158(C).
    13. Wegener, Christoph & Kruse-Becher, Robinson & Klein, Tony, 2024. "EU ETS Market Expectations and Rational Bubbles," VfS Annual Conference 2024 (Berlin): Upcoming Labor Market Challenges 302359, Verein für Socialpolitik / German Economic Association.
    14. Hui, Wang & Xin-gang, Zhao & Ling-zhi, Ren & Fan, Lu, 2021. "An agent-based modeling approach for analyzing the influence of market participants’ strategic behavior on green certificate trading," Energy, Elsevier, vol. 218(C).
    15. Carè, Rosella & Cumming, Douglas, 2024. "Technology and automation in financial trading: A bibliometric review," Research in International Business and Finance, Elsevier, vol. 71(C).
    16. Steffen Hitzemann & Marliese Uhrig-Homburg, 2019. "Empirical performance of reduced-form models for emission permit prices," Review of Derivatives Research, Springer, vol. 22(3), pages 389-418, October.
    17. Battigalli, Pierpaolo & Bonanno, Giacomo, 1997. "The Logic of Belief Persistence," Economics and Philosophy, Cambridge University Press, vol. 13(1), pages 39-59, April.
    18. Szabó, György & Borsos, István & Szombati, Edit, 2019. "Games, graphs and Kirchhoff laws," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 521(C), pages 416-423.
    19. Grüll, Georg & Taschini, Luca, 2011. "Cap-and-trade properties under different hybrid scheme designs," Journal of Environmental Economics and Management, Elsevier, vol. 61(1), pages 107-118, January.
    20. Shi, Yi & Deng, Yawen & Wang, Guoan & Xu, Jiuping, 2020. "Stackelberg equilibrium-based eco-economic approach for sustainable development of kitchen waste disposal with subsidy policy: A case study from China," Energy, Elsevier, vol. 196(C).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:jocoma:v:35:y:2024:i:c:s2405851324000382. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/jcomm .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.