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Spatial–Temporal Evolution of Interprovincial Ecological Efficiency and Its Determinants in China: A Super-Efficiency SBM Model Approach

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  • Ying Liu

    (China Institute of Geo-Environment Monitoring, Beijing 100081, China
    Key Laboratory of Mine Ecological Effects and Systematic Restoration, Ministry of Natural Resources, Beijing 100081, China
    China Association for Geological Disaster Prevention and Ecological Restoration, Beijing 100043, China)

  • Lei Tian

    (China Institute of Geo-Environment Monitoring, Beijing 100081, China
    Key Laboratory of Mine Ecological Effects and Systematic Restoration, Ministry of Natural Resources, Beijing 100081, China)

  • Zhiyi Wang

    (China Institute of Geo-Environment Monitoring, Beijing 100081, China
    Key Laboratory of Mine Ecological Effects and Systematic Restoration, Ministry of Natural Resources, Beijing 100081, China)

  • Peiyong He

    (China Institute of Geo-Environment Monitoring, Beijing 100081, China
    Key Laboratory of Mine Ecological Effects and Systematic Restoration, Ministry of Natural Resources, Beijing 100081, China)

  • Meng Li

    (China Association for Geological Disaster Prevention and Ecological Restoration, Beijing 100043, China)

  • Na Wang

    (China Institute of Geo-Environment Monitoring, Beijing 100081, China
    Key Laboratory of Mine Ecological Effects and Systematic Restoration, Ministry of Natural Resources, Beijing 100081, China)

  • Yang Yu

    (China Institute of Geo-Environment Monitoring, Beijing 100081, China
    Key Laboratory of Mine Ecological Effects and Systematic Restoration, Ministry of Natural Resources, Beijing 100081, China)

Abstract

This study delves into the temporal–spatial variations and influencing factors of interprovincial ecological efficiency in China, aiming to provide vital guidance for sustainable development and ecological equilibrium. Employing the super-efficiency SBM model, we compute ecological efficiency indices for 31 Chinese provinces from 2005 to 2021. Furthermore, utilizing Geodetectors, we conduct an in-depth analysis of the impact of key dimensions—economic factors, efficiency elements, environmental governance, pollution determinants, input factors, and natural components—consisting of 30 specific indicators of ecological efficiency. The findings unveil several significant insights. Firstly, interprovincial ecological efficiency in China has experienced undulating declines since 2005. Additionally, notable spatial agglomeration exists, with economically developed regions demonstrating elevated ecological efficiency, while less-developed areas exhibit lower levels. Moreover, among the influencing factors, (1) economic aspects hold a dominant role, where optimizing industrial structure and enhancing resource utilization efficiency can partially alleviate environmental pressure; (2) efficiency elements exhibit a progressive enhancement trend; (3) the impacts of environmental governance and pollution factors manifest complex dynamics, necessitating continuous policy support and comprehensive remediation; (4) despite the relatively weaker influence of natural components, vigilance remains imperative due to intensifying climate change and natural disasters; and (5) while input factors exert limited effects on ecological efficiency, their significance in resource allocation and sustainable development persists.

Suggested Citation

  • Ying Liu & Lei Tian & Zhiyi Wang & Peiyong He & Meng Li & Na Wang & Yang Yu, 2023. "Spatial–Temporal Evolution of Interprovincial Ecological Efficiency and Its Determinants in China: A Super-Efficiency SBM Model Approach," Sustainability, MDPI, vol. 15(18), pages 1-19, September.
    • Handle: RePEc:gam:jsusta:v:15:y:2023:i:18:p:13864-:d:1242375
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    1. Yuxuan Xu & Fengjiao Qiang & Wenchun Luo, 2024. "Investigating the Impact of Heterogeneous Environmental Regulation on the Ecological Efficiency of Industrial Enterprises: A Multivariate Adjustment Approach Using the CLAD Spatial Durbin Model," Sustainability, MDPI, vol. 16(6), pages 1-37, March.

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