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Industrial Structure Adjustment and Regional Green Development from the Perspective of Mineral Resource Security

Author

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  • You Zheng

    (School of Economics and Management, China University of Geosciences, Wuhan 430074, China)

  • Jianzhong Xiao

    (School of Economics and Management, China University of Geosciences, Wuhan 430074, China)

  • Jinhua Cheng

    (School of Economics and Management, China University of Geosciences, Wuhan 430074, China)

Abstract

Mineral resource security is the premise and foundation of the regional green rise strategy. And the adjustment of industrial structure is an effective way to relieve the pressure of the current green economy transformation. Based on the Shift-share Method and the Spatial Durbin model, this paper takes 30 regions in China from 2006 to 2017 as examples to study the impact of industrial structure adjustment on China’s green development from the perspective of mineral resource security. The empirical results show that: China is still in the process of industrial transfer. The dynamic effect of industrial structure promotes green development from the perspective of mineral resource security, while its static effect inhibits green development from the perspective of mineral resource security. The spatial spillover effect of the industrial structure affecting green development from the perspective of mineral resource security is significant. The static structural effect of the tertiary industry promotes the green development of the region, and it has a significant negative impact on neighboring areas, while the secondary industry’s static structural effect has the opposite effect.

Suggested Citation

  • You Zheng & Jianzhong Xiao & Jinhua Cheng, 2020. "Industrial Structure Adjustment and Regional Green Development from the Perspective of Mineral Resource Security," IJERPH, MDPI, vol. 17(19), pages 1-18, September.
    • Handle: RePEc:gam:jijerp:v:17:y:2020:i:19:p:6978-:d:418300
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    References listed on IDEAS

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    1. Lin, Gang & Jiang, Dong & Fu, Jingying & Wang, Di & Li, Xiang, 2019. "A spatial shift-share decomposition of energy consumption changes in China," Energy Policy, Elsevier, vol. 135(C).
    2. Jing Xu & Min Zhou & Hailong Li, 2016. "ARDL-based research on the nexus among FDI, environmental regulation, and energy consumption in Shanghai (China)," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 84(1), pages 551-564, October.
    3. Yehua Dennis Wei & Wangming Li & Chunbin Wang, 2007. "Restructuring Industrial Districts, Scaling Up Regional Development: A Study of the Wenzhou Model, China," Economic Geography, Taylor & Francis Journals, vol. 83(4), pages 421-444, October.
    4. Bei Jin & Gang Li, 2013. "Green economic growth from a developmental perspective," China Finance and Economic Review, Springer, vol. 1(1), pages 1-7, December.
    5. Xiaobing Wang & Nick Weaver & Ning Xue, 2019. "Challenges for the Chinese economy in the new era of development," Journal of Chinese Economic and Business Studies, Taylor & Francis Journals, vol. 17(1), pages 1-7, January.
    6. Zhijun Feng & Wei Chen, 2018. "Environmental Regulation, Green Innovation, and Industrial Green Development: An Empirical Analysis Based on the Spatial Durbin Model," Sustainability, MDPI, vol. 10(1), pages 1-22, January.
    7. Lee, Lung-fei & Yu, Jihai, 2010. "Estimation of spatial autoregressive panel data models with fixed effects," Journal of Econometrics, Elsevier, vol. 154(2), pages 165-185, February.
    8. Zhu, Bangzhu & Zhang, Mengfan & Zhou, Yanhua & Wang, Ping & Sheng, Jichuan & He, Kaijian & Wei, Yi-Ming & Xie, Rui, 2019. "Exploring the effect of industrial structure adjustment on interprovincial green development efficiency in China: A novel integrated approach," Energy Policy, Elsevier, vol. 134(C).
    9. Cheng, Zhonghua & Li, Lianshui & Liu, Jun, 2018. "Industrial structure, technical progress and carbon intensity in China's provinces," Renewable and Sustainable Energy Reviews, Elsevier, vol. 81(P2), pages 2935-2946.
    10. Vu, K.M., 2017. "Structural change and economic growth: Empirical evidence and policy insights from Asian economies," Structural Change and Economic Dynamics, Elsevier, vol. 41(C), pages 64-77.
    11. Elhorst, J. Paul & Gross, Marco & Tereanu, Eugen, 2018. "Spillovers in space and time: where spatial econometrics and Global VAR models meet," Working Paper Series 2134, European Central Bank.
    12. Bego�a Cueto & Mat�as Mayor & Patricia Su�rez, 2015. "Entrepreneurship and unemployment in Spain: a regional analysis," Applied Economics Letters, Taylor & Francis Journals, vol. 22(15), pages 1230-1235, October.
    13. Seiford, Lawrence M. & Zhu, Joe, 2002. "Modeling undesirable factors in efficiency evaluation," European Journal of Operational Research, Elsevier, vol. 142(1), pages 16-20, October.
    14. Scheel, Holger, 2001. "Undesirable outputs in efficiency valuations," European Journal of Operational Research, Elsevier, vol. 132(2), pages 400-410, July.
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    Cited by:

    1. Ruxu Sheng & Rong Zhou & Ying Zhang & Zidi Wang, 2021. "Green Investment Changes in China: A Shift-Share Analysis," IJERPH, MDPI, vol. 18(12), pages 1-15, June.

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