Low-carbon development has always been an important focus of China's economic transformation. In order to promote the development of low-carbon economy, this study used SBM-DEA model to evaluate China's provincial LCEE from 2005 to 2019, studied its temporal and spatial evolution law, used spatial autocorrelation to explore the correlation of China's provincial LCEE, and explored the key influencing factors of LCEE with Tobit model. The empirical results show that the LCEE of most provinces in China is declining, and there are significant differences among different regions in China. Because the eastern region of China can rely on its own human resources, capital environment, and economic foundation, the overall LCEE level is relatively high, while the central and western regions still have obvious deficiencies due to industrial conditions, geographical location, and other factors. LCEE has significant spatial correlation, and neighboring provinces have spillover effects on local LCEE. On this basis, the key factors that affect LCEE are determined. Urbanization level, traffic level, economic development level, financial development, investment in fixed assets, and energy consumption are the important factors that affect LCEE in China, but these influences vary from province to region. It is more reasonable for local governments to develop low-carbon economy according to their own conditions.
Keywords: Low-carbon economic efficiency; Slack-based measure-data envelopment analysis; Spatial autocorrelation; Tobit model.
© 2022. The Author(s), under exclusive licence to Springer Nature Switzerland AG.