Regulation of stock externalities with correlated abatement cost

We study a dynamic regulation model where firms' actions contribute to a stock externality. The regulator and firms have asymmetric information about serially correlated abatement costs. With price-based policies such as taxes, or if firms trade quotas efficiently, the regulator learns about the evolution of both the stock and costs. This ability to learn about costs is important in determining the ranking of taxes and quotas, and in determining the value of a feedback rather than an open-loop policy. For a range of parameter values commonly used in global warming studies, taxes dominate quotas, regardless of whether the regulator uses an open-loop or a feedback policy, and regardless of the extent of cost correlation.