Optimal Design of Permit Markets with an Ex Ante Pollution Target
In this paper, we examine the design of permit trading programs when the objective is to minimize the cost of achieving an ex ante pollution target, that is, one that is defined in expectation rather than an ex post deterministic value. We consider two potential sources of uncertainty, the presence of either of which can make our model appropriate: incomplete information on abatement costs and uncertain delivery coefficients. In such a setting, we find three distinct features that depart from the well-established results on permit trading: (1) the regulator's information on firms' abatement costs can matter; (2) the optimal permit cap is not necessarily equal to the ex ante pollution target; and (3) the optimal trading ratio is not necessarily equal to the delivery coefficient even when it is known with certainty. Intuitively, since the regulator is only required to meet a pollution target on average, she can set the trading ratio and total permit cap such that there will be more pollution when abatement costs are high and less pollution when abatement costs are low. Information on firms' abatement costs is important in order for the regulator to induce the optimal alignment between pollution level and abatement costs.
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- Richard D. Horan & James S. Shortle, 2005. "When Two Wrongs Make a Right: Second-Best Point-Nonpoint Trading Ratios," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 87(2), pages 340-352.
- Montgomery, W. David, 1972. "Markets in licenses and efficient pollution control programs," Journal of Economic Theory, Elsevier, vol. 5(3), pages 395-418, December.
- Segerson, Kathleen, 1988. "Uncertainty and incentives for nonpoint pollution control," Journal of Environmental Economics and Management, Elsevier, vol. 15(1), pages 87-98, March.
- Richard D. Horan, 2001. "Differences in Social and Public Risk Perceptions and Conflicting Impacts on Point/Nonpoint Trading Ratios," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 83(4), pages 934-941.
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