Temporal and spatial evolution and influencing factors of urban ecological total factor productivity in the Yellow River basin under strong sustainable development

被引:4
|
作者
Yang, Wan-Ping [1 ]
Zhang, Zhen-Ya [1 ]
Luo, Ping-Ping [2 ,3 ,4 ]
Wang, Ya-Juan [5 ]
机构
[1] Xi An Jiao Tong Univ, Sch Econ & Finance, Xian 710064, Peoples R China
[2] Changan Univ, Key Lab Subsurface Hydrol & Ecol Effects Arid Reg, Minist Educ, Xian 710064, Peoples R China
[3] Changan Univ, Xian Monitoring Modelling & Early Warning Watershe, Xian, Peoples R China
[4] Changan Univ, Sch Water & Environm, Xian, Peoples R China
[5] Fudan Univ, Sch Management, Shanghai 200433, Peoples R China
关键词
Strong sustainable development; Yellow River basin; ecological total factor productivity; spatial panel model; influencing factors; CARBON EMISSIONS; DEA APPROACH; EFFICIENCY; CONSUMPTION; ENERGY; IMPACT;
D O I
10.1177/00368504231152742
中图分类号
G40 [教育学];
学科分类号
040101 ; 120403 ;
摘要
A growing consensus worldwide has indicated the need to protect the ecological environment and achieve sustainable development. Ensuring ecological protection and high-quality development of the Yellow River basin have become China's major national strategy. We reviewed extant literature, summarised government reports and guidance documents on the Yellow River basin, and proposed introducing a strong sustainable development theory into the study of total factor productivity (TFP). The spatial-temporal evolution and influencing factors of urban ecological TFP in the Yellow River basin are of great practical significance. We proposed a new ecological TFP indicator: the modified input-oriented Luenberger productivity indicator (MIL). Using panel data from 78 cities in the Yellow River basin during 2003-2019, we measured the urban ecological TFP. We adopted the geographic information system tool and kernel density estimation to analyse the temporal and spatial evolution of the indicator, as well as its spatial effects and influencing factors, using the global Moran's I index and dynamic spatial Durbin model (SDM). Our results show that, during the sample period, our indicator increased in cities in the region with an average annual growth rate of 0.627%, driven by technological progress. The average annual growth rate in urban areas showed a decreasing distribution of 'downstream-midstream-upstream'. Fiscal decentralisation (FD), industrial structure (IND), financial development (FIN), urbanisation level (URB) and research and development (RD) investment improved growth rates in this and the adjacent regions through direct and indirect effects. However, environmental regulation (ER), opening level (OPEN) of cities and population density (POP) were obstacles to TFP growth.
引用
收藏
页数:33
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