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Study on the Coupling Development of Industry, City and Population in the Yellow River Basin from the Perspective of Green Economy

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  • Xiangdong Cao

    (College of Economics, Shandong Normal University, Jinan 250358, China)

  • Fuyi Ci

    (College of Economics, Shandong Normal University, Jinan 250358, China)

Abstract

Based on the perspective of green economy, we established an index system to evaluate industry, city and population, and obtained data from 78 cities in the Yellow River Basin from 2011 to 2020. The entropy weight method, coupling model, kernel density analysis and exploratory data analysis methods were used to analyze the coupling coordination degree and spatio-temporal differentiation characteristics of industry, city and population in the Yellow River Basin. We constructed a Tobit model to analyze the influencing factors. The results show that from the perspective of green economy, the coupling coordination degree of industry, city and population in the Yellow River Basin has improved continuously. Among them, the coupling coordination degree of Shandong Peninsula and provincial capital cities is high, but the coupling coordination degree of some areas in the middle and upper reaches of the Yellow River is low due to human capital factors. The Yellow River Basin should strengthen environmental control, optimize government regulation, guide the inflow of foreign capital and develop green finance to promote the coupling development of industry, city and population.

Suggested Citation

  • Xiangdong Cao & Fuyi Ci, 2023. "Study on the Coupling Development of Industry, City and Population in the Yellow River Basin from the Perspective of Green Economy," Sustainability, MDPI, vol. 15(13), pages 1-13, June.
    • Handle: RePEc:gam:jsusta:v:15:y:2023:i:13:p:10029-:d:1178599
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    References listed on IDEAS

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    1. Stephan Heblich & Alex Trew & Yanos Zylberberg, 2021. "East-Side Story: Historical Pollution and Persistent Neighborhood Sorting," Journal of Political Economy, University of Chicago Press, vol. 129(5), pages 1508-1552.
    2. Yao, Yao & Ivanovski, Kris & Inekwe, John & Smyth, Russell, 2019. "Human capital and energy consumption: Evidence from OECD countries," Energy Economics, Elsevier, vol. 84(C).
    3. He, Lingyun & Liu, Rongyan & Zhong, Zhangqi & Wang, Deqing & Xia, Yufei, 2019. "Can green financial development promote renewable energy investment efficiency? A consideration of bank credit," Renewable Energy, Elsevier, vol. 143(C), pages 974-984.
    4. Andersen, Dana C., 2018. "Accounting for loss of variety and factor reallocations in the welfare cost of regulations," Journal of Environmental Economics and Management, Elsevier, vol. 88(C), pages 69-94.
    5. Pasquale Marcello Falcone, 2020. "Environmental regulation and green investments: the role of green finance," International Journal of Green Economics, Inderscience Enterprises Ltd, vol. 14(2), pages 159-173.
    6. Wen, Huwei & Lee, Chien-Chiang & Zhou, Fengxiu, 2021. "Green credit policy, credit allocation efficiency and upgrade of energy-intensive enterprises," Energy Economics, Elsevier, vol. 94(C).
    7. Wang, Xinyue & Wang, Qing, 2021. "Research on the impact of green finance on the upgrading of China's regional industrial structure from the perspective of sustainable development," Resources Policy, Elsevier, vol. 74(C).
    8. Khan, Zeeshan & Hossain, Mohammad Razib & Badeeb, Ramez Abubakr & Zhang, Changyong, 2023. "Aggregate and disaggregate impact of natural resources on economic performance: Role of green growth and human capital," Resources Policy, Elsevier, vol. 80(C).
    9. Sun, Xiuli & Li, Haizheng & Ghosal, Vivek, 2020. "Firm-level human capital and innovation: Evidence from China," China Economic Review, Elsevier, vol. 59(C).
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