Shadow prices and abatement cost of soil erosion in Shaanxi Province, China: Convex expectile regression approach

Abstract

Since 1999, the Sloping Land Conversion Program (SLCP) in China, regarded as one of the largest payments for ecosystem services (PES) programs worldwide, was carried out for the alleviation of soil erosion. The high economic cost of the SLCP has attracted considerable attention to its ecological and economic effects during the past decades. However, reliable evidence about abatement alternatives and abatement costs of soil erosion remains scant. Using panel data of 83 counties observed in Shaanxi Province from 2000 to 2015, the marginal abatement cost (MAC) of soil erosion is accurately evaluated by a directional distance function with convex expectile regression. Besides, we explore how external variables affect shadow prices and the choice of abatement solutions. Our main findings are the following: First, this novel data-driven approach could alleviate the bias from the interference of noise and inefficiency; second, incorporating the investment of the SLCP into the production process allows to find the most cost-efficient abatement solution from both the input side (i.e., increasing the SLCP investment) and the output side (i.e., downscaling the primary industry or downscaling the non-primary industries); third, the temporal-spatial distribution of abatement costs shows that the abatement potential from the SLCP has shrunk gradually, which implies that there might be cost-inefficiency in some counties if the SLCP continues; finally, we recognize that natural conditions, like wind speed and vegetation quality, could influence the input-side abatement cost and output-side abatement cost differently. These results have profound policy implications, asking for more cost-efficient abatement strategies in the future.