首页|国家重大战略区域绿色低碳发展绩效时空分异与演进趋势

国家重大战略区域绿色低碳发展绩效时空分异与演进趋势

扫码查看
[目的]本文旨在评价国家重大战略区域绿色低碳发展绩效,探析其时空分异特征及动态演进趋势,为协同促进区域高质量发展提供科学依据和决策参考。[方法]基于超效率EBM模型的Global-Luenberger指数对2012-2020年重大战略区域绿色低碳发展绩效进行科学评价,运用Dagum基尼系数、方差分解、传统与空间Kernel密度估计等方法揭示其时空分异特征、动态演进规律以及长期转移趋势。[结果]①样本考察期内,重大战略区域绿色低碳发展绩效均得到提升,整体表现出"粤港澳">"成渝">"京津冀">"长三角">"黄河流域">"长江中游"的区域非均衡特征。②重大战略区域绿色低碳发展绩效的空间差异较小,随时间推移呈现先下降再上升趋势。超变密度差异是主要空间差异来源;结构差异主要取决于技术进步差异、投入要素和非期望产出生产率差异,进一步细分要素,环境污染治理生产率差异和净碳减排生产率差异是绿色低碳发展绩效地区差距的主要驱动力。③重大战略区域绿色低碳发展绩效总体向好但存在空间极化趋势。各区域绿色低碳发展均表现为"低绩效城市向上转移、中间绩效城市持续性较强、高绩效城市向下转移",总体呈现出逆转的分布特征。考虑空间条件时,黄河流域、长江中游、长三角的正向溢出效应显著,粤港澳、成渝的空间溢出效应不明显,京津冀存在"以邻为壑"现象。[结论]为建立以重大战略区域为引领的绿色低碳发展新格局,应合理优化空间布局并科学把握结构差异以协同提升绿色低碳发展绩效,同时充分发挥空间溢出效应,形成绿色低碳发展绩效提升合力。
Spatiotemporal differentiation and evolution trend of green and low-carbon development performance in the National Major Strategic Regions
[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 differentia-tion characteristics and dynamic change,and provide a scientific basis and decision-making refer-ence 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 evalu-ated 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 re-gional disequilibrium characteristics of Guangdong-Hong Kong-Macao Greater Bay Area>Cheng-du-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 per-formance 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 differ-ences mainly depended on technological progress differences,input factors,and undesired output productivity differences.Further subdividing the factors,environmental pollution control productiv-ity 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 sustainabili-ty,and high-performing cities moved downward,and the overall distribution characteristics were re-versed.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-Ma-cao 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 ratio-nally 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 spill-over effect to form a joint force for improving green and low-carbon development performance.

green and low-carbon developmentGlobal-Luenberger indexDagum Gini coeffi-cientkernel density estimationMajor Strategic Regions

陈明华、史楠、张边秀、谢琳霄

展开 >

山东财经大学经济学院,济南 250014

绿色低碳发展 Global-Luenberger指数 Dagum基尼系数 Kernel密度估计 重大战略区域

2024

资源科学
中国科学院地理科学与资源研究所 中国自然资源学会

资源科学

CSTPCDCSSCICHSSCD北大核心
影响因子:2.408
ISSN:1007-7588
年,卷(期):2024.46(11)