Analysis of Spatial Differences and the Influencing Factors in Eco-Efficiency of Urban Agglomerations in China

Danyu Liu () and Ke Zhang
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Danyu Liu: School of Economics, Zhongnan University of Economics and Law, Wuhan 430073, China
Ke Zhang: School of Economics, Zhongnan University of Economics and Law, Wuhan 430073, China

Sustainability, 2022, vol. 14, issue 19, 1-21

Abstract: In the context of climate change, studying the ecological efficiency (EE) of urban agglomerations is of great significance in promoting sustainable development. First, night light data are used as the expected output to build an evaluation index system based on the five major urban agglomerations, namely, the Yangtze River Delta, Pearl River Delta, Beijing–Tianjin–Hebei, the middle reaches of the Yangtze River, and Chengdu–Chongqing urban agglomerations. Second, the super-efficient Epsilon-based (super-EBM) model and the input–output redundancy rates are used to measure the EE of the five major urban agglomerations from 2006 to 2018. Then, their spatial differences are explored with the help of the Gini coefficient. Finally, the spatial differences in the EE drivers of urban agglomerations are analyzed using Geodetector. The results reveal the following. (1) The EE of the five major urban agglomerations present the decline fluctuation trend of “∧”. However, this trend has slowed down. From the perspective of urban agglomeration, Beijing–Tianjin–Hebei > The Pearl River Delta > Chengdu–Chongqing > Yangtze River Delta > the middle reaches of the Yangtze River. The lowest efficiency of the Yangtze River’s middle reaches has “high investment, low output, and high pollution” characteristics. (2) The EE of the five major urban agglomerations had weak synergistic development and noticeable spatial differences. The primary sources are inter-group differences and hypervariable density. (3) From the perspective of influencing, the difference in technological innovation levels (TEC) is the single leading factor in the differences in the EE space of urban agglomerations. In addition, the interaction combination of industrial structure upgrades (IDS) and traffic infrastructure (TRAF) is a crucial combination driver. However, the core influencing factors of spatial differences in EE in five urban agglomerations are heterogeneous. Among them, the nature-influencing factors of the EE space differences in the Beijing–Tianjin–Hebei and the Chengdu–Chongqing urban agglomerations are environmental regulations (ER). Meanwhile, the influencing factor in the Yangtze River Delta urban agglomeration is the development of urbanization (URB). Moreover, the prominent factor in the middle reaches of the Yangtze River and the Pearl River Delta urban agglomerations is foreign direct investment (FDI). On this basis, this study aims to promote ecological civilization construction in urban agglomerations and optimize regional integrated spatial patterns.

Keywords: urban agglomerations; EE; super-efficient EBM; night-time light data; input-output analysis; Gini coefficient; Geodetector (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

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