Designing a double auction mechanism for the re-allocation of emission permits

S.I.: RealCaseOR
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Abstract

This paper employs and extends the auction method for the re-allocation of emission permits (RAEP) at the China Beijing Environment Exchange (CBEE) to meet pollution reduction targets. An optimization method is first proposed to calculate the optimal production quantity and emission permit demand/supply volume for firms with high/low pollution abatement cost. Then, the double auction method is adopted and extended to construct the RAEP double auction mechanism based on the principle of maximizing the total social welfare utility. To further explain this auction method, three matching mechanisms are proposed. Each mechanism achieves a balance between supply and demand of emission permits. Finally, a computational analysis of the real CBEE case is used to verify both the validity and practicability of the mechanism. The results show that the extended auction method presented in this paper could effectively increase the number of traded participants, improve the auction transaction efficiency, and increase the utilities of trading participants, compared to the auction method currently used in the CBEE; the extended method is always applicable regardless of the size of the permit market; the method could effectively realize the incentive compatibility, thus encouraging each firm to provide a real bid price.

Keywords

Re-allocation of emission permits (RAEP) Double auction Emission permit trading Cap-and-trade system 

Notes

Acknowledgements

The authors sincerely thank the editors and anonymous reviewers for their insightful comments and suggestions. This research is partially supported by the National Natural Science Foundation of China under the grant nos. 71501139, 91746110, 71372019, 71521002, 71642004; the National Science Fund of China for Distinguished Young Scholars under the grant no. 71625003; the Joint Development Program of Beijing Municipal Commission of Education; Natural Science Funds of Jiangsu Province (No. BK20150307).

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Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Research Center for Smarter Supply Chain, School of BusinessSoochow UniversitySuzhouChina
  2. 2.School of Management and EconomicsBeijing Institute of TechnologyBeijingChina
  3. 3.Center for Energy and Environmental Policy ResearchBeijing Institute of TechnologyBeijingChina
  4. 4.Sustainable Development Research Institute for Economy and Society of BeijingBeijingChina

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