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A comprehensive analysis of the spatiotemporal dynamics and determinants of carbon emission efficiency in China's
1School of Management, Chongqing University of Technology, Chongqing, 400054, China.
Abstract:
As the mainstay of China's national economy, the development model of high carbon emissions in the manufacturing sector not only poses the greatest challenge to China's achievement of its "Dual Carbon" goals, but also significantly threatens global ecological security and sustainable development. Therefore, improving carbon emission efficiency (CEE) and reducing carbon emissions are key to realizing China's "Dual Carbon" goals and global sustainable development. This study uses panel data from 30 Chinese provinces from 2005 to 2022 and CO2 emissions equivalents from the manufacturing sector provided by China Emission Accounts and Datasets (CEADS). The Super-EBM model, which allows for in-depth analysis of extreme efficiency, is employed to accurately measure carbon emission efficiency of China's manufacturing sector (CEECMS). Additionally, frontier exploratory spatiotemporal data analysis is applied to investigate the spatiotemporal evolution of CEECMS, while spatial econometric models are used to assess the influencing factors of CEE. The study finds that: (1) The spatial geographical location has a significant impact on the CEECMS. The provinces with the highest average efficiency are Beijing, Guangdong, and Fujian, all of which have relative efficiency values greater than 1. (2) The CEECMS exhibits strong spatial correlation, with an overall increase in spatial fluctuations, but spatial cohesion tends to stabilize. (3) The improvement of CEECMS requires a focus on foreign trade as a driving force, promoting regional coordinated development based on the "Chengdu-Chongqing Economic Circle" model, and continuously deepening supply-side structural reforms.

