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Optimal Trading Ratios for Pollution Permit Markets

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  • Stephen Holland
  • Andrew J. Yates

Abstract

We analyze a novel method for improving the efficiency of pollution permit markets by optimizing the way in which emissions are exchanged through trade. Under full-information, it is optimal for emissions to exchange according to the ratio of marginal damages. However, under a canonical model with asymmetric information between the regulator and the sources of pollution, we show that these marginal damage trading ratios are generally not optimal, and we show how to modify them to improve efficiency. We calculate the optimal trading ratios for a global carbon market and for a regional nitrogen market. In these examples, 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 the structure of asymmetric information when designing permit markets.

Suggested Citation

  • Stephen Holland & Andrew J. Yates, 2014. "Optimal Trading Ratios for Pollution Permit Markets," NBER Working Papers 19780, National Bureau of Economic Research, Inc.
  • Handle: RePEc:nbr:nberwo:19780
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    References listed on IDEAS

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    1. repec:spt:admaec:v:8:y:2018:i:1:f:8_1_5 is not listed on IDEAS
    2. repec:ucp:jaerec:doi:10.1086/691975 is not listed on IDEAS
    3. 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.
    4. Baran Doda & Simon Quemin, 2018. "Linking Permit Markets Multilaterally," Working Papers 1804, Chaire Economie du climat.
    5. Simon Quemin & Christian de Perthuis, 2017. "Transitional Restricted Linkage between Emissions Trading Schemes," Working Papers 2017.31, FAERE - French Association of Environmental and Resource Economists.
    6. Werner Antweiler, 2017. "Emission trading for air pollution hot spots: getting the permit market right," Environmental Economics and Policy Studies, Springer;Society for Environmental Economics and Policy Studies - SEEPS, vol. 19(1), pages 35-58, January.

    More about this item

    JEL classification:

    • 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
    • Q53 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Air Pollution; Water Pollution; Noise; Hazardous Waste; Solid Waste; Recycling

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