Cost estimates for multiple pollutants: A maximum entropy approach

In this paper, we demonstrate the use of inequality restricted generalized maximum entropy estimation to calculate shadow prices of effluents in a distance function framework. We estimate the shadow prices of sulfur dioxide, nitrogen oxides, carbon dioxide and mercury emissions from a panel of 260 coal-fired U.S. electric power plants. This modeling procedure delivers results, which are consistent with existing abatement cost evidence produced with both deterministic approaches and forecasting models. Our results imply that it may not be possible to duplicate the remarkable success of the SO2 trading system for the other pollutants because of their greater industry abatement cost homogeneity.