Abstract
This paper studies the initial emission permits auction problem from the perspective of government’ activities. In the traditional auction models, the basic assumption is that the government, i.e., the auctioneer, only pursues the maximum economic revenue. In this paper, we consider a hybrid auction-bargaining model, which gives new insights on how the government’s economic and social goals effect the equilibrium strategies. For this model, we find a symmetric bidding strategy equilibrium for the firms in a sealed bid auction form, which is closely related to the classical results in the auction. Our most important finding is that, compared with the classical auction mechanism, the final trading price is based on not only firm’s bidding strategy, but also the application quality of emission permits in the energy consumption market. The results also show that this auction-bargaining mechanism can alleviate distortion by excessive allowance in initial emission permits auction market and promote the social goals in both auction market and consumption market.
Access provided by Autonomous University of Puebla. Download to read the full chapter text
Chapter PDF
Similar content being viewed by others
References
Montgomery, W.D.: Markets in Licenses and Efficient Pollution Control Programs. Journal of Economic Theory 5(3), 395–418 (1972)
Rao, C.J., Zhao, Y., Li, C.F.: Asymmetric Nash Equilibrium in Emission Rights Auctions. Technological Forecasting & Social Change 79, 429–435 (2012)
Benz, E., Loschel, A., Sturm, B.: Auctioning of CO 2 Emission Allowances in Phase 3 of the EU Emissions Trading Scheme. Climate Policy 10(6), 705–718 (2010)
Porter, D., Rassenti, S., Shobe, W.: The Design, Testing and Implementation of Virginias NOx Allowance Auction. Journal of Economic Behavior & Organization 69(2), 190–200 (2009)
Genc, T.S.: Discriminatory Versus Uniform-price Electricity Auctions with Supply Function Equilibrium. J. Optim. Theory Appl. 140, 9–31 (2009)
Cramton, P., Kerr, S.: Tradeable Carbon Permit Auctions: How and Why to Auction not Grandfather. Energy Policy 30(4), 333–345 (2002)
Betz, R., Seifert, S., Cramton, P., Kerr, S.: Auctioning Greenhous Gas Emissions Permits in Australia. Aust. J. Agric. Resour. Econ. 54(2), 219–238 (2010)
Lai, Y.B.: Auctions or Grandfathering: the Political Economy of Tradable Emission Permits. Public Choice 136(1-2), 181–200 (2008)
Ausubel, L.M.: An Efficient Ascending-bid Auction for Multiple Objects. The American Economic Review 94(5), 1452–1475 (2004)
Mougeot, M., Naegelen, F., Pelloux, B., et al.: Breaking Collusion in Auctions through Speculation: An Experiment on CO2 Emission Permit Markets. Journal of Public Economic Theory 13(5), 829–856 (2011)
Yu, Y.: An Optimal Ad Valorem Tax/Subsidy with an Output-Based Refunded Emission Payment for Permits Auction in an Oligopoly Market. Environmental and Resource Economics 52(2), 235–248 (2012)
Sunnevag, K.J.: Auction Design for the Allocation of Emission Permits in the Presence of Market Power. Environmental and Resource Economics 26(3), 385–400 (2003)
Goeree, J.K., Palmer, K., Holt, C.A.: An Experimental Study of Auctions versus Grandfathering to Assign Pollution Permits. Journal of the European Economic Association 8(2-3), 514–525 (2010)
Jensen, S.G., Skytte, K.: Simultaneous Attainment of Energy Goals by Means of Green Certificates and Emission Permits. Energy Policy 31(1), 63–71 (2003)
Harstad, B., Eskeland, G.S.: Trading for the Future: Signaling in Permit Markets. Energy Policy 94(9), 749–760 (2010)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2014 Springer International Publishing Switzerland
About this paper
Cite this paper
Ding, L., Wang, X., Kang, W. (2014). An Auction-Bargaining Model for Initial Emission Permits. In: Gu, Q., Hell, P., Yang, B. (eds) Algorithmic Aspects in Information and Management. AAIM 2014. Lecture Notes in Computer Science, vol 8546. Springer, Cham. https://doi.org/10.1007/978-3-319-07956-1_30
Download citation
DOI: https://doi.org/10.1007/978-3-319-07956-1_30
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-07955-4
Online ISBN: 978-3-319-07956-1
eBook Packages: Computer ScienceComputer Science (R0)