中国
面板数据
温室气体
业务
Boosting(机器学习)
自然资源经济学
环境经济学
经济增长
经济
地理
计算机科学
生态学
考古
机器学习
计量经济学
生物
作者
Lulu Liu,Yanyin Lv,Da Gao,Xinlin Mo
标识
DOI:10.1177/0958305x231217646
摘要
The pursuit of a low-carbon transition is central to achieving green development worldwide, and China has embraced carbon emissions trading (CET) with the aim of achieving high-quality economic development. Despite its critical policy importance, the question of whether and how CET promotes carbon efficiency remains unclear. Using unique panel data covering prefecture-level cities in China from 2007 to 2020, this study first fills this gap by constructing the Global-EBM model and taking carbon dioxide as an undesirable output to innovatively evaluate the total factor carbon emission efficiency (TFCEE) of China's cities. Second, as an extension of the existing provincial evidence, we treat the carbon trading scheme in urban China as a quasi-natural experiment and confirm the boosting effect of CET on TFCEE in the pilot cities. Third, the mediating roles of both green technology innovation and industrial structure upgrading in the process of promoting carbon efficiency are identified, further demonstrating the channel influences. Finally, the heterogeneous impact of the CET policy is further investigated and found to be stronger in eastern and developed cities. Our findings have important policy implications for China's green transition.
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