Spatiotemporal differentiation and evolution trend of green and low-carbon development performance in the National Major Strategic Regions

Abstract

[Objective] The purpose of this study was to evaluate the performance of green and low-carbon development in the Major Strategic Regions of China, analyze its spatiotemporal differentiation characteristics and dynamic change, and provide a scientific basis and decision-making reference for promoting high-quality regional development in a coordinated manner. [Methods] Based on the Global-Luenberger index of the super-efficiency EBM model, this study scientifically evaluated the green and low-carbon development performance of China’s Major Strategic Regions from 2012 to 2020. Dagum Gini coefficient, variance decomposition, and traditional and spatial kernel density estimation were used to reveal the spatiotemporal differentiation, dynamic change, and long-term transfer trend. [Results] (1) During the sample study period, the performance of green and low-carbon development in the Major Strategic Regions has been improved, showing the regional disequilibrium characteristics of Guangdong-Hong Kong-Macao Greater Bay Area > Chengdu-Chongqing > Beijing-Tianjin-Hebei > Yangtze River Delta > Yellow River Basin > the middle reaches of the Yangtze River. (2) The spatial difference of green and low-carbon development performance in the Major Strategic Regions was small, showing a trend of decline and then rising over time. Supervariable density difference was the main source of spatial difference. Structural differences mainly depended on technological progress differences, input factors, and undesired output productivity differences. Further subdividing the factors, environmental pollution control productivity differences and net carbon emission reduction productivity differences were the main driving forces for regional disparities in green and low-carbon development performance. (3) The green and low-carbon development performance of the Major Strategic Regions was generally high, but there was a trend of spatial polarization. The green and low-carbon development of all regions was manifested as low-performing cities moved upward, medium-performing cities showed sustainability, and high-performing cities moved downward, and the overall distribution characteristics were reversed. When considering the spatial conditions, the positive spillover effect of neighboring cities in the Yellow River Basin, the middle reaches of the Yangtze River Delta, and the Yangtze River Economic Belt was significant, but the spatial spillover effect of the Guangdong-Hong Kong-Macao Greater Bay Area and Chengdu-Chongqing was not obvious, and the “beggar-thy-neighbor” phenomenon existed in the Beijing-Tianjin-Hebei. [Conclusion] In order to establish a new pattern of green and low-carbon development led by the Major Strategic Regions, it is necessary to rationally optimize the spatial layout and scientifically understand the structural differences to jointly improve green and low-carbon development performance, while giving full play to the spatial spillover effect to form a joint force for improving green and low-carbon development performance.

Keywords

• green and low-carbon development|global-luenberger index|dagum gini coefficient|kernel density estimation|major strategic regions