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Incorporating health impacts into a differentiated pollution tax rate system: A case study in the Beijing-Tianjin-Hebei region in China

Robert Mendelsohn and 4 other contributors

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    Abstract

    This paper argues for an efficient pollution tax rate system that reflects the differentiation of marginal health damages of the individual emission sources. Although China is the first country in the world to launch a regionally differentiated pollution tax rate program, due to the absence of marginal damage estimation, whether this policy is efficient and equitable remains unknown. In this paper, we build an Integrated Assessment Model to measure the marginal damage of SO2, NOx and PM2.5 emitted from 38 coal-fired power plants in the Beijing-Tianjin-Hebei region, and evaluate the policy performance of tax rate systems with different differentiation magnitudes. Results show that the spatial variations are huge, the range of marginal health damages of coal-fired power plants in the BTH region between the lowest and highest emission source is $2375 to $33245 per ton for S02, $307 to $4984 per ton for NOx, and $11513 - $163126 per ton for PM2.5. Shifting from the uniform tax rate system to the current partially differentiated tax rate system will increase the total health benefits by 51.6% but with some regions worse-off than the uniform tax rate system. If we incorporate the source-specific variations of marginal health damages into the tax rate system, such a fully differentiated tax rate system will further increase the total health benefits of current partially differentiated tax rate system by 43.1% with every region better-off. Furthermore, even though the policy benefits of both differentiated tax rate systems are much more unequally distributed than uniform tax rates, their impacts on environmental inequalities are better than the uniform tax rate system. Because uniform tax rate systems do not offset the original inequalities of environmental health burdens while differentiated tax rate systems achieve this buy efficiently allocate mitigation targets among regions with different burdens.