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Improving Urban Ecological Welfare Performance: An ST-LMDI Approach to the Yangtze River Economic Belt

Author

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  • Jie Yang

    (Department of Economics, The Engineering & Technical College of Chengdu University of Technology, Leshan 614000, China
    College of Management Science, Chengdu University of Technology, Chengdu 610059, China)

  • Zhigang Li

    (College of Management Science, Chengdu University of Technology, Chengdu 610059, China
    Research Center for Protection Policy of Key Ecological Functional Areas in the Upper Reaches of the Yangtze River, Chengdu 610059, China)

Abstract

Enhancing urban ecological welfare performance is essential for achieving sustainable urban development and fostering a comprehensive regional green transformation. This study develops a quantitative assessment framework for urban ecological welfare performance, grounded in both the welfare of urban residents and their consumption of ecological resources. Employing the spatio-temporal Logarithmic Mean Divisia Index model to dissect the ecological welfare performance across 108 key prefecture-level cities within China’s Yangtze River Economic Belt, considering both temporal and spatial dimensions, the analysis reveals a “W”-shaped trajectory in the ecological welfare performance from 2006 to 2022, characterized by pronounced spatial disparities. Particularly in the downstream coastal regions and notably the Yangtze River Delta, advantages in social and economic structures, along with public fiscal outlays, contribute to a superior ecological welfare performance, exhibiting a notable spatial spillover effect. The study introduces six key factors—social benefit, economic benefit, population dispersion, population density in urban areas, urbanization scale, and ecological sustainability—to examine their influence on ecological welfare performance, uncovering substantial differences in the outcomes of temporal and spatial decomposition. Temporal decomposition indicates that economic benefit and urbanization scale are the primary drivers enhancing ecological welfare performance, whereas population dispersion is identified as the primary inhibitor. Spatial decomposition reveals that the determinants of above-average urban ecological welfare vary regionally and undergo dynamic shifts over time. Overall, a holistic understanding of the interplay among economic growth, ecological preservation, and the enhancement of residents’ welfare can inform the development and execution of tailored policies by local governments.

Suggested Citation

  • Jie Yang & Zhigang Li, 2024. "Improving Urban Ecological Welfare Performance: An ST-LMDI Approach to the Yangtze River Economic Belt," Land, MDPI, vol. 13(8), pages 1-21, August.
  • Handle: RePEc:gam:jlands:v:13:y:2024:i:8:p:1318-:d:1459933
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    References listed on IDEAS

    as
    1. Zhigang Li & Jie Yang & Jialong Zhong & Dong Zhang, 2022. "Assessment of Urban Agglomeration Ecological Sustainability and Identification of Influencing Factors: Based on the 3DEF Model and the Random Forest," IJERPH, MDPI, vol. 20(1), pages 1-15, December.
    2. Lingyan Bao & Xuhui Ding & Jingxian Zhang & Dingyi Ma, 2023. "Can New Urbanization Construction Improve Ecological Welfare Performance in the Yangtze River Economic Belt?," Sustainability, MDPI, vol. 15(11), pages 1-18, May.
    3. Chen, Youlin & Wang, Lei & Yu, Peiheng & Cheng, Changxu, 2024. "Linkages between digital economy and ecosystem services: Revealing the spatiotemporal relationship based on U-shaped effect," Technological Forecasting and Social Change, Elsevier, vol. 207(C).
    4. Shengyun Wang & Liancheng Duan & Shuwen Jiang, 2022. "Research on Spatial Differences and Driving Effects of Ecological Well-Being Performance in China," IJERPH, MDPI, vol. 19(15), pages 1-20, July.
    5. Xiaoling Xie & Qi Zhu, 2023. "Research on the Impact of Urban Expansion on Habitat Quality in Chengdu," Sustainability, MDPI, vol. 15(7), pages 1-16, April.
    6. Haoyang Lu & Jing Tong & Yajiao Tang, 2022. "Analysis of Green Credit and the Ecological Welfare Performance Based on Empirical Models and ARIMA(2,3,2): Taking China as an Example," Sustainability, MDPI, vol. 14(19), pages 1-15, September.
    7. Feng Lan & Zhao Hui & Jing Bian & Ying Wang & Wenxin Shen, 2022. "Ecological Well-Being Performance Evaluation and Spatio-Temporal Evolution Characteristics of Urban Agglomerations in the Yellow River Basin," Land, MDPI, vol. 11(11), pages 1-21, November.
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