IDEAS home Printed from https://ideas.repec.org/p/arx/papers/2106.11120.html
   My bibliography  Save this paper

Mechanism Design for Efficient Nash Equilibrium in Oligopolistic Markets

Author

Listed:
  • Kaiying Lin
  • Beibei Wang
  • Pengcheng You

Abstract

This paper investigates the efficiency loss in social cost caused by strategic bidding behavior of individual participants in a supply-demand balancing market, and proposes a mechanism to fully recover equilibrium social optimum via subsidization and taxation. We characterize the competition among supply-side firms to meet given inelastic demand, with linear supply function bidding and the proposed efficiency recovery mechanism. We show that the Nash equilibrium of such a game exists under mild conditions, and more importantly, it achieves the underlying efficient supply dispatch and the market clearing price that reflects the truthful system marginal production cost. Further, the mechanism can be tuned to guarantee self-sufficiency, i.e., taxes collected counterbalance subsidies needed. Extensive numerical case studies are run to validate the equilibrium analysis, and we employ individual net profit and a modified version of Lerner index as two metrics to evaluate the impact of the mechanism on market outcomes by varying its tuning parameter and firm heterogeneity.

Suggested Citation

  • Kaiying Lin & Beibei Wang & Pengcheng You, 2021. "Mechanism Design for Efficient Nash Equilibrium in Oligopolistic Markets," Papers 2106.11120, arXiv.org.
    • Handle: RePEc:arx:papers:2106.11120
    as

    Download full text from publisher

    File URL: http://arxiv.org/pdf/2106.11120
    File Function: Latest version
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Ramesh Johari & John N. Tsitsiklis, 2011. "Parameterized Supply Function Bidding: Equilibrium and Efficiency," Operations Research, INFORMS, vol. 59(5), pages 1079-1089, October.
    2. Daskalakis, George & Markellos, Raphael N., 2009. "Are electricity risk premia affected by emission allowance prices? Evidence from the EEX, Nord Pool and Powernext," Energy Policy, Elsevier, vol. 37(7), pages 2594-2604, July.
    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. Pietz, Matthäus, 2009. "Risk premia in electricity wholesale spot markets: empirical evidence from Germany," CEFS Working Paper Series 2009-11, Technische Universität München (TUM), Center for Entrepreneurial and Financial Studies (CEFS).
    2. Naeem, Muhammad Abubakr & Arfaoui, Nadia, 2023. "Exploring downside risk dependence across energy markets: Electricity, conventional energy, carbon, and clean energy during episodes of market crises," Energy Economics, Elsevier, vol. 127(PB).
    3. Bunn, Derek W. & Chen, Dipeng, 2013. "The forward premium in electricity futures," Journal of Empirical Finance, Elsevier, vol. 23(C), pages 173-186.
    4. Marc Gronwald & Janina Ketterer & Stefan Trück, 2011. "The Dependence Structure between Carbon Emission Allowances and Financial Markets - A Copula Analysis," CESifo Working Paper Series 3418, CESifo.
    5. Chia-Lin Chang & Michael McAleer, 2019. "Modeling Latent Carbon Emission Prices for Japan: Theory and Practice," Energies, MDPI, vol. 12(21), pages 1-21, November.
    6. Chia-Lin Chang & Te-Ke Mai & Michael Mcaleer, 2018. "Pricing Carbon Emissions In China," Annals of Financial Economics (AFE), World Scientific Publishing Co. Pte. Ltd., vol. 13(03), pages 1-37, September.
    7. George Daskalakis, Lazaros Symeonidis, Raphael N. Markellos, 2015. "Electricity futures prices in an emissions constrained economy: Evidence from European power markets," The Energy Journal, International Association for Energy Economics, vol. 0(Number 3).
    8. Wang, Yudong & Guo, Zhuangyue, 2018. "The dynamic spillover between carbon and energy markets: New evidence," Energy, Elsevier, vol. 149(C), pages 24-33.
    9. Mei, Tianhua & Liu, Jie & Guo, Jianming & Siano, Pierluigi & Jin, Xuanxuan, 2022. "Allocation of emission allowances considering strategic voting," Energy Economics, Elsevier, vol. 114(C).
    10. Eunyoung Kim & Youngcheul Ahn & Doojin Ryu, 2014. "Application of the Carbon Emission Pricing Model in the Korean Market," Energy & Environment, , vol. 25(1), pages 63-78, February.
    11. Carlos Pinho & Mara Madaleno, 2011. "Links between spot and futures allowances: ECX and EEX markets comparison," International Journal of Global Energy Issues, Inderscience Enterprises Ltd, vol. 35(2/3/4), pages 101-131.
    12. van Koten, Silvester, 2021. "The forward premium in electricity markets: An experimental study," Energy Economics, Elsevier, vol. 94(C).
    13. Yuexu Zhao & Weiqi Xu, 2023. "Measurement of risk spillover effect based on EV-Copula method," Palgrave Communications, Palgrave Macmillan, vol. 10(1), pages 1-10, December.
    14. Pawel Maryniak & Stefan Trueck & Rafal Weron, 2016. "Carbon pricing, forward risk premiums and pass-through rates in Australian electricity futures markets," HSC Research Reports HSC/16/10, Hugo Steinhaus Center, Wroclaw University of Technology.
    15. Reboredo, Juan C., 2014. "Volatility spillovers between the oil market and the European Union carbon emission market," Economic Modelling, Elsevier, vol. 36(C), pages 229-234.
    16. Yue-Jun Zhang, 2016. "Research on carbon emission trading mechanisms: current status and future possibilities," International Journal of Global Energy Issues, Inderscience Enterprises Ltd, vol. 39(1/2), pages 89-107.
    17. Kushlin, Valery & Ustenko, Viktoriya, 2017. "Modern World Practice of State Support of Perspective Scientific and Innovative Programs: Evaluation of the Developed Mechanisms of State Management of Innovation Development in the Context of Time Ch," Working Papers 041718, Russian Presidential Academy of National Economy and Public Administration.
    18. Rohlfs, Wilko & Madlener, Reinhard, 2010. "Valuation of CCS-Ready Coal-Fired Power Plants: A Multi-Dimensional Real Options Approach," FCN Working Papers 7/2010, E.ON Energy Research Center, Future Energy Consumer Needs and Behavior (FCN).
    19. Nur Sunar & John R. Birge, 2019. "Strategic Commitment to a Production Schedule with Uncertain Supply and Demand: Renewable Energy in Day-Ahead Electricity Markets," Management Science, INFORMS, vol. 65(2), pages 714-734, February.
    20. Brooks, Chris & Prokopczuk, Marcel & Wu, Yingying, 2013. "Commodity futures prices: More evidence on forecast power, risk premia and the theory of storage," The Quarterly Review of Economics and Finance, Elsevier, vol. 53(1), pages 73-85.

    More about this item

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    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:arx:papers:2106.11120. 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: arXiv administrators (email available below). General contact details of provider: http://arxiv.org/ .

    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.