Analysis of spatial correlation characteristics and key factors of regional environmental governance efficiency in China

Youbin Zhu (), Hui Hou (), Minglang Zhang () and Shilin Hou ()
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Youbin Zhu: Northeastern University
Hui Hou: Northeastern University
Minglang Zhang: National University of Singapore
Shilin Hou: PriceWaterhouseCoopers LLP Singapore

Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, 2025, vol. 27, issue 2, No 53, 3989-4016

Abstract: Abstract Based on panel data spanning from 2008 to 2021, this study employs the super-efficiency SBM-DEA model to quantify the efficiency of regional environmental governance in China. Through the utilization of Social Network Analysis, we investigate the spatial correlation characteristics within the network of environmental governance efficiency. Furthermore, a spatial econometric model is employed to conduct an empirical analysis of the key factors influencing regional environmental governance efficiency. The findings reveal noticeable spatial disparities in regional environmental governance efficiency across China, with an overall efficiency that remains in the low-efficiency stage. The spatial correlation of the network gradually increases and transitions from polarization to convergence. Moreover, population size, economic development level, and fiscal autonomy demonstrate negative effects on regional environmental governance efficiency. Conversely, factors such as industrial structure upgrading, investment in industrial pollution control, local government competition, and the intensity of environmental regulation have a positive impact on regional environmental governance efficiency. Consequently, in order to enhance regional environmental governance efficiency, it is imperative for the government to consider not only economic and social factors but also focus on government behavior factors.

Keywords: Regional environmental governance efficiency; Super-efficiency SBM-DEA model; Social Network Analysis; Spatial correlation characteristics; Spatial econometric model; Spatial correlation (search for similar items in EconPapers)
Date: 2025
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DOI: 10.1007/s10668-023-04057-4

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