Does emission trading system reduce mining cities’ pollution emissions? A quasi-natural experiment based on Chinese prefecture-level cities

Jun Shen, Pengcheng Tang, Hao Zeng, Jinhua Cheng and Xiuli Liu

Resources Policy, 2023, vol. 81, issue C

Abstract: The emissions trading system is the most crucial measure taken by the Chinese government to control environmental pollution, but its actual effects on mining cities remain unknown. Therefore, the data of Chinese prefecture-level cities from 2003 to 2018 were used to evaluate the actual emission reduction effects of the emissions trading system in mining cities through the difference-in-difference method. The empirical results provide convincing evidence: (1) The emissions trading system of Chinese government has reduced pollution emissions in mining cities by 22%, and achieved the policy effects of emission reduction. (2) Compared with the mining cities in western and eastern regions, the mining cities in the central region have shown better policy effects of emission reduction. At the same time, the emissions trading system can promote the pollutant emissions reduction in mining cities in old industrial bases, growing mining cities and regenerative mining cities. (3) Further analysis revealed that the emissions trading system mainly achieved pollutant emissions reduction in mining cities through marketization and technological innovation (especially the innovation of green technology). Carbon market policies that adapt to local conditions should be implemented by the Chinese government to enhance the level of marketization and technological innovation, and maximize the policy effect of the emissions trading system.

Keywords: Emission trading system; Mining city; Pollution emission; Difference in difference (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (11)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:jrpoli:v:81:y:2023:i:c:s0301420723000016

DOI: 10.1016/j.resourpol.2023.103293

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