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Optimal trading ratios for pollution permit markets

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  • Holland, Stephen P.
  • Yates, Andrew J.

Abstract

We demonstrate a novel method for improving the efficiency of pollution permit markets by optimizing the exchange of emissions through trade. Under full-information, it is optimal for emissions to exchange according to the ratio of marginal damages. Under asymmetric information, we derive necessary conditions for the marginal damage trading ratios to be optimal, illustrate that the marginal damage trading ratios are generally not optimal, and show how to improve efficiency using optimal trading ratios. We calculate the optimal trading ratios for a global carbon market. The gains from using optimal trading ratios rather than marginal damage trading ratios range from substantial to trivial, which suggests the need for careful consideration of asymmetric information when designing permit markets.

Suggested Citation

  • Holland, Stephen P. & Yates, Andrew J., 2015. "Optimal trading ratios for pollution permit markets," Journal of Public Economics, Elsevier, vol. 125(C), pages 16-27.
    • Handle: RePEc:eee:pubeco:v:125:y:2015:i:c:p:16-27
    DOI: 10.1016/j.jpubeco.2015.03.005
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    3. Heijmans, Roweno J.R.K. & Engström, Max, 2024. "Time Horizons and Emissions Trading," Discussion Papers 2024/2, Norwegian School of Economics, Department of Business and Management Science.
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    9. Baran Doda & Luca Taschini, 2017. "Carbon Dating: When Is It Beneficial to Link ETSs?," Journal of the Association of Environmental and Resource Economists, University of Chicago Press, vol. 4(3), pages 701-730.
    10. Daniel Leppert, 2023. "“No fences make bad neighbors” but markets make better ones: cap-and-trade reduces cross-border SO2 in a natural experiment," Environmental Economics and Policy Studies, Springer;Society for Environmental Economics and Policy Studies - SEEPS, vol. 25(3), pages 407-433, July.
    11. Simon Quemin & Christian Perthuis, 2019. "Transitional Restricted Linkage Between Emissions Trading Schemes," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 74(1), pages 1-32, September.
    12. Wang, Zhiyu, 2018. "Permit trading with flow pollution and stock pollution," Journal of Environmental Economics and Management, Elsevier, vol. 91(C), pages 118-132.
    13. Jay S. Coggins & Andrew L. Goodkind & Jason Nguyen & Zhiyu Wang, 2019. "Price Effects, Inefficient Environmental Policy, and Windfall Profits," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 72(3), pages 637-656, March.
    14. Zhang, Da & Peng, Hantang & Zhang, Lin, 2023. "Share of polluting input as a sufficient statistic for burden sharing," Energy Economics, Elsevier, vol. 121(C).
    15. Maogang Tang & Ruihan Zhang & Zhen Li & Baijun Wu, 2021. "Assessing the impact of tradable discharge permit on pollution reduction and innovation: micro-evidence from Chinese industrial enterprises," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 23(11), pages 16911-16933, November.
    16. Xiaoyan Wang & Minggao Xue & Lu Xing, 2018. "Market-based pollution regulations with damages Varying across space: When the adoption of clean Technology is socially optimal," Advances in Management and Applied Economics, SCIENPRESS Ltd, vol. 8(1), pages 1-5.
    17. Hagen, Martin, 2022. "Tradable immigration quotas revisited," Journal of Public Economics, Elsevier, vol. 208(C).
    18. Chan, H. Ron & Chupp, B. Andrew & Cropper, Maureen L. & Muller, Nicholas Z., 2018. "The impact of trading on the costs and benefits of the Acid Rain Program," Journal of Environmental Economics and Management, Elsevier, vol. 88(C), pages 180-209.
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    21. Xiaoyan Wang & Weiwei Zhang, 2022. "Taxes Versus Tradable Permits Considering Public Environmental Awareness," Economics of Disasters and Climate Change, Springer, vol. 6(2), pages 293-315, July.

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    More about this item

    Keywords

    Pollution markets; Asymmetric information; Trading ratios;
    All these keywords.

    JEL classification:

    • Q53 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Air Pollution; Water Pollution; Noise; Hazardous Waste; Solid Waste; Recycling
    • D82 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Asymmetric and Private Information; Mechanism Design
    • H23 - Public Economics - - Taxation, Subsidies, and Revenue - - - Externalities; Redistributive Effects; Environmental Taxes and Subsidies

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