LAUSR

Abstract Marginal emission abatement costs play an important role in the emission trading market and in the allocation of emission reduction allowances. The traditional methods for estimating marginal emission abatement costs do not account for technological heterogeneity, which leads to biased results. To solve this problem, an improved method that combines the clustering method with a parametric output directional distance function is proposed in this paper. This method integrates the economic proximity of each examined province into its assessment of the environmental production technology of the province and takes multiple pollutants (CO2, SO2 and NOX) into consideration. Based on this method, in this paper, the environmental performance of 30 provinces in China from 2006 to 2017 is measured, the marginal emission abatement cost of CO2 is estimated, and a nonlinear programming method is used to study the optimal allocation of emission reduction in China. The results indicate the following: First, categorizing the provinces according to their economic proximity results in groups that differ greatly from geographically based groups. Second, the average inefficiency of these 30 Chinese provinces is 2.551%, which is less than that estimated by the methods that do not consider heterogeneity. Third, China’s average marginal CO2 abatement cost is 797.79 CNY/ton, and it exhibits a growing trend. Finally, compared to the grandfathering rule, the optimal quota allocation proposed by this paper can save approximately 797.793 billion CNY.