Spatio-temporal patterns of energy efficiency in Chinese prefecture cities under green low-carbon transition

The green and low-carbon economy has become a pivotal direction for global development, representing both an imperative response to climate change and an intrinsic requirement for economic structural transformation. China’s economic development currently occupies a critical phase of structural transition, yet research on the impact of energy efficiency measurement across prefecture-level cities in low-carbon economic development remains scarce. Addressing this gap, this paper conducts an empirical examination of China’s energy efficiency and green low-carbon economic development levels based on data from 285 prefecture-level cities spanning 2012 to 2022. Specifically, the Systemic Behavioural Modelling (SBM) approach is employed to systematically measure energy efficiency and low-carbon economic development levels (measurement values are presented in Appendices 1 and 2). Furthermore, the Dagum Gini coefficient and kernel density estimation are utilised to analyse and interpret the characteristics of energy efficiency disparities and their spatio-temporal distribution. Finally, the empirical investigation examines the impact of low-carbon economic development on energy efficiency. The findings reveal: Firstly, national energy efficiency exhibits an overall upward trend, manifested by a sustained growth rate exceeding 1 since 2013, with the fastest increase occurring in 2021 at 1.184. Concurrently, the overall Gini coefficient declined from 0.164 in 2013 to 0.108 in 2022, indicating significant inter-regional disparities. Both intra-regional and inter-regional variations, alongside hyper-dispersion differences, exert substantial influence on energy efficiency inequality. Secondly, a positive correlation exists in the spatial distribution of energy efficiency. Specifically, the highest regional density of energy efficiency is observed around 1.2, indicating that energy efficiency is concentrated within this range in most years, exhibiting a tendency towards spatial clustering. Finally, the research conclusions and policy implications proposed herein offer implementation pathways for enhancing China’s energy efficiency and developing a green, low-carbon economy, providing directional guidance and theoretical reference for advancing China’s green productive forces in the new era.