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The Spatial Differentiation and Driving Forces of Ecological Welfare Performance in the Yangtze River Economic Belt

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  • Ling Bai

    (School of Economics and Management, Nanchang University, Nanchang 330031, China
    Department of Geography and Environment, University of Lethbridge, 4401 University Drive West, Lethbridge, AB T1K 3M4, Canada)

  • Tianran Guo

    (School of Economics and Management, Nanchang University, Nanchang 330031, China)

  • Wei Xu

    (Department of Geography and Environment, University of Lethbridge, 4401 University Drive West, Lethbridge, AB T1K 3M4, Canada)

  • Kang Luo

    (School of Economics and Management, Nanchang University, Nanchang 330031, China)

Abstract

Ecological welfare performance contributes directly to human well-being and regional sustainable development. Improving the regional ecological welfare performance in the process of pursuing green and sustainable development demands theoretical innovation and empirical exploration. Based on the super-efficiency SBM model, this study evaluated the ecological welfare performance of 108 cities during the period of 2009 to 2019. The Dagum Gini coefficient decomposition and spatial convergence model were employed to analyze the differences in ecological welfare performance across and within the study area and explore the underlining causes of such spatial differentiation in the Yangtze River Economic Belt and the upper, middle and lower reaches. It can be seen from the results that: (1) the overall difference in the ecological welfare performance of the Yangtze River Economic Belt is associated with a fluctuating downward trend during the study period. Regional and inter-regional differences were revealed and hypervariable density was identified as the main source of the differences. (2) The ecological welfare performance of the Yangtze River Economic Belt has absolute and conditional β convergence, and the ecological welfare performance of each city-region and surrounding urban areas has a positive impact on each other. (3) The difference in the spatial-temporal differentiation trend is manifested by the difference in the convergence rate. The cities in the middle reaches of the Yangtze River have the fastest convergence rate, followed by the cities in the upper reaches, and the cities in the lower reaches are the slowest. This geographic difference is mainly driven by the combined effects of industrial structure, urban characteristics, environmental regulation, foreign direct investment, and transportation accessibility. Finally, it is proposed that future policies should focus on the imbalanced regional development in the study area, and each region needs to explore ways to improve local ecological welfare performance according to local conditions, and ultimately promote the overall green, coordinated and high-quality development in the Yangtze River Economic Belt.

Suggested Citation

  • Ling Bai & Tianran Guo & Wei Xu & Kang Luo, 2022. "The Spatial Differentiation and Driving Forces of Ecological Welfare Performance in the Yangtze River Economic Belt," IJERPH, MDPI, vol. 19(22), pages 1-21, November.
  • Handle: RePEc:gam:jijerp:v:19:y:2022:i:22:p:14801-:d:968785
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    References listed on IDEAS

    as
    1. Chen, Yu & Lin, Boqiang, 2021. "Understanding the green total factor energy efficiency gap between regional manufacturing—insight from infrastructure development," Energy, Elsevier, vol. 237(C).
    2. Yu, Nannan & de Roo, Gert & de Jong, Martin & Storm, Servaas, 2016. "Does the expansion of a motorway network lead to economic agglomeration? Evidence from China," Transport Policy, Elsevier, vol. 45(C), pages 218-227.
    3. Cole, Matthew A. & Elliott, Robert J.R. & Okubo, Toshihiro, 2010. "Trade, environmental regulations and industrial mobility: An industry-level study of Japan," Ecological Economics, Elsevier, vol. 69(10), pages 1995-2002, August.
    4. Charnes, A. & Cooper, W. W. & Rhodes, E., 1978. "Measuring the efficiency of decision making units," European Journal of Operational Research, Elsevier, vol. 2(6), pages 429-444, November.
    5. Shengyun Wang & Yaxin Zhang & Xingren Yao, 2021. "Research on Spatial Unbalance and Influencing Factors of Ecological Well-Being Performance in China," IJERPH, MDPI, vol. 18(17), pages 1-23, September.
    6. Andrew K. Jorgenson, 2014. "Economic development and the carbon intensity of human well-being," Nature Climate Change, Nature, vol. 4(3), pages 186-189, March.
    7. Meijuan Hu & Suleman Sarwar & Zaijun Li, 2021. "Spatio-Temporal Differentiation Mode and Threshold Effect of Yangtze River Delta Urban Ecological Well-Being Performance Based on Network DEA," Sustainability, MDPI, vol. 13(8), pages 1-19, April.
    8. Lindong Ma & Yuanxiao Hong & Xihui Chen, 2022. "Can Green Economy and Ecological Welfare Achieve Synergistic Development? The Perspective of the “Two Mountains” Theory," IJERPH, MDPI, vol. 19(11), pages 1-24, May.
    9. Common, Mick, 2007. "Measuring national economic performance without using prices," Ecological Economics, Elsevier, vol. 64(1), pages 92-102, October.
    10. Lampe, Hannes W. & Hilgers, Dennis, 2015. "Trajectories of efficiency measurement: A bibliometric analysis of DEA and SFA," European Journal of Operational Research, Elsevier, vol. 240(1), pages 1-21.
    11. Meng Sun & Yue Zhang & Yaqi Hu & Jiayi Zhang, 2022. "Spatial Convergence of Carbon Productivity: Theoretical Analysis and Chinese Experience," IJERPH, MDPI, vol. 19(8), pages 1-19, April.
    12. Liobikienė, Genovaitė & Butkus, Mindaugas, 2019. "Scale, composition, and technique effects through which the economic growth, foreign direct investment, urbanization, and trade affect greenhouse gas emissions," Renewable Energy, Elsevier, vol. 132(C), pages 1310-1322.
    13. Werner Antweiler & Brian R. Copeland & M. Scott Taylor, 2001. "Is Free Trade Good for the Environment?," American Economic Review, American Economic Association, vol. 91(4), pages 877-908, September.
    14. Abdallah, Saamah & Thompson, Sam & Marks, Nic, 2008. "Estimating worldwide life satisfaction," Ecological Economics, Elsevier, vol. 65(1), pages 35-47, March.
    15. J. Paul Elhorst, 2003. "Specification and Estimation of Spatial Panel Data Models," International Regional Science Review, , vol. 26(3), pages 244-268, July.
    16. Daly, Herman E, 1974. "The Economics of the Steady State," American Economic Review, American Economic Association, vol. 64(2), pages 15-21, May.
    17. J. Elhorst, 2010. "Applied Spatial Econometrics: Raising the Bar," Spatial Economic Analysis, Taylor & Francis Journals, vol. 5(1), pages 9-28.
    18. Tone, Kaoru, 2001. "A slacks-based measure of efficiency in data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 130(3), pages 498-509, May.
    19. Jing Bian & Feng Lan & Yulin Zhou & Zhenzhen Peng & Mingfang Dong, 2022. "Spatial and Temporal Evolution and Driving Factors of Urban Ecological Well-Being Performance in China," IJERPH, MDPI, vol. 19(16), pages 1-19, August.
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    2. Yang Yang & Simo Li & Zhaoxian Su & Hao Fu & Wenbin Wang & Yun Wang, 2023. "Research on the Ecological Innovation Efficiency of the Zhongyuan Urban Agglomeration: Measurement, Evaluation and Optimization," Sustainability, MDPI, vol. 15(19), pages 1-24, September.

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