黄河流域城市能源综合效率时空分异与影响因素研究  

Spatio-temporal distribution and influencing factors of urban comprehensive energy efficiency in the Yellow River Basin

作　　者：岳立[1] 任婉瑜 Yue Li;Ren Wanyu(School of Economics,Lanzhou University,Lanzhou 730000,Gansu,China)

机构地区：[1]兰州大学经济学院,甘肃兰州730000

出　　处：《地理科学》2024年第4期630-639,共10页Scientia Geographica Sinica

基　　金：国家社会科学基金项目(21BJY163)资助。

摘　　要：经济发展和环境保护的双重压力下,能源效率成为反映一国经济发展质量的关键指标,不断提升能源效率是必然的趋势。本文使用非参数的super-SBM模型、地理信息系统空间分析法、面板Tobit回归和地理加权回归(GWR)模型对黄河流域2007—2018年城市能源综合效率的时空格局和影响因素进行分析。结果表明:①研究期内,城市能源综合效率基本保持平稳,但有下降趋势。效率分布的区域差异有所缩小,且呈现出明显的连片分布特征,具体来说上游城市多处于低效、中低效率区间,中下游城市多位于中低和中高效率区间;②影响因素的Tobit回归结果表明,经济发展水平和绿色创新对城市能源综合效率具有显著正向影响,碳排放水平、产业结构和环境规制对城市能源综合效率具有显著的负向影响,区域异质性回归结果也基本保持不变;③地理加权回归结果表明,各影响因素作用的空间异质性存在并且具有一定分布规律。研究结论为促进黄河流域城市能源综合效率提供思路。Under the confluence of economic advancement and ecological preservation imperatives,the imperative to enhance energy efficiency has crystallized as a pivotal metric encapsulating a nation’s developmental prowess.This research delves into the intricate spatial and temporal dynamics,as well as the underlying determinants,of urban energy efficiency within the Yellow River Basin spanning the years 2007 to 2018.Employing a multifaceted analytical approach comprising the non-parametric super-SBM model,geographic information system spatial analysis,panel Tobit regression,and geographically weighted regression(GWR)model,this study unravels compelling insights.Firstly,it elucidates the trajectory of urban comprehensive energy efficiency over the study duration,revealing a nuanced narrative of relative stability juxtaposed with a discernible downward trajectory.Moreover,the study unearths a trend of diminishing regional differentials in efficiency distribution,accompanied by the emergence of a conspicuous patchy distribution paradigm.Notably,cities situated upstream evinced tendencies towards lower and medium-low efficiency levels,in stark contrast to their midstream and downstream counterparts,which predominantly exhibited medium-low to medium-high efficiency ranges.Furthermore,the Tobit regression analyses illuminate the pivotal role played by economic development levels and green innovation in bolstering urban comprehensive energy efficiency,underscored by their significant positive impacts.Conversely,the deleterious effects of carbon emissions,industrial structure,and environmental regulations manifest as significant negative influencers on urban comprehensive energy efficiency.Importantly,the findings from regional heterogeneity regression lend credence to the consistency of these discerned impacts across diverse geographical locales within the Yellow River Basin.Additionally,the application of geographically weighted regression(GWR)unfurls a tapestry of spatial heterogeneity in the influence exerted by various fac

关 键 词：城市能源综合效率 面板Tobit回归模型 GWR模型 黄河流域城市 

分 类 号：F062.2[经济管理—政治经济学]