Optimal Design of Permit Markets with an Ex Ante Pollution Target
研究在实现事前（期望值）污染目标时，如何设计许可证交易计划以最小化成本，发现最优许可证上限和交易比率与传统结论不同，且监管者需要企业减排成本信息。
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.