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A pathway to coordinated regional development: Energy utilization efficiency and green development - Evidence from China's major national strategic zones

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  • Luo, Kang
  • Lee, Chien-Chiang
  • Zhuo, Chong

Abstract

According to the new economic geography hypothesis, this study establishes an analytical framework to assess the efficiency of energy use and the progress of green development. The framework is based on panel data collected from 254 cities at the prefecture level in China. The spatial Durbin model is employed to examine the influence and spatial spillover effect of energy utilization efficiency on green development in major national strategic zones. The results show that: improving energy utilization efficiency promotes green development in major national strategic regions, with a stronger intra-regional transfer effect than inter-regional. This is confirmed by robustness and endogeneity analyses. The spillover intensity of energy utilization efficiency on green development varies across regions. It shows an inverted U-shape curve in the Yangtze River Economic Belt, a U-shape curve in the Yellow River Basin and Yangtze River Delta region, a diminishing margin in the Beijing-Tianjin-Hebei region, and a growing margin in the Guangdong-Hong Kong-Macao Greater Bay Area. There is significant spatial heterogeneity within these regions. Different mediating mechanisms affect green development in different regions. The knowledge spillover effect mediates energy utilization efficiency's impact on green development in the Guangdong-Hong Kong-Macao Greater Bay Area, the industry linkage effect in the Yangtze River Economic Belt and Beijing-Tianjin-Hebei region, the environmental improvement effect in the Yellow River Basin, and the market linkage effect in the Yangtze River Delta region. To promote regional coordinated development with energy utilization efficiency, the country should not only consider differences between national strategic areas but also focus on the effects of different paths to realize the complementarity between energy utilization efficiency and green development.

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  • Luo, Kang & Lee, Chien-Chiang & Zhuo, Chong, 2024. "A pathway to coordinated regional development: Energy utilization efficiency and green development - Evidence from China's major national strategic zones," Energy Economics, Elsevier, vol. 131(C).
    • Handle: RePEc:eee:eneeco:v:131:y:2024:i:c:s0140988324001105
    DOI: 10.1016/j.eneco.2024.107402
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    References listed on IDEAS

    as
    1. Zhang, Xiaoming & Tian, Yiming & Lee, Chien-Chiang, 2024. "Enforcement actions and systemic risk," Emerging Markets Review, Elsevier, vol. 59(C).
    2. Luo, Kang & Liu, Yaobin & Chen, Pei-Fen & Zeng, Mingli, 2022. "Assessing the impact of digital economy on green development efficiency in the Yangtze River Economic Belt," Energy Economics, Elsevier, vol. 112(C).
    3. 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).
    4. Ramli, Noor Asiah & Munisamy, Susila, 2015. "Eco-efficiency in greenhouse emissions among manufacturing industries: A range adjusted measure," Economic Modelling, Elsevier, vol. 47(C), pages 219-227.
    5. Moon, Hana & Min, Daiki, 2017. "Assessing energy efficiency and the related policy implications for energy-intensive firms in Korea: DEA approach," Energy, Elsevier, vol. 133(C), pages 23-34.
    6. Ghanem, Dalia & Zhang, Junjie, 2014. "‘Effortless Perfection:’ Do Chinese cities manipulate air pollution data?," Journal of Environmental Economics and Management, Elsevier, vol. 68(2), pages 203-225.
    7. Chang, Chun-Ping & Wen, Jun & Zheng, Mingbo & Dong, Minyi & Hao, Yu, 2018. "Is higher government efficiency conducive to improving energy use efficiency? Evidence from OECD countries," Economic Modelling, Elsevier, vol. 72(C), pages 65-77.
    8. Jia, Ruining & Shao, Shuai & Yang, Lili, 2021. "High-speed rail and CO2 emissions in urban China: A spatial difference-in-differences approach," Energy Economics, Elsevier, vol. 99(C).
    9. Fujita, Masahisa & Krugman, Paul & Mori, Tomoya, 1999. "On the evolution of hierarchical urban systems1," European Economic Review, Elsevier, vol. 43(2), pages 209-251, February.
    10. Lee, Chien-Chiang & Wang, Chih-Wei & Thinh, Bui Tien, 2023. "Green development, climate risks, and cash flow: International evidence," Pacific-Basin Finance Journal, Elsevier, vol. 79(C).
    11. Pan, Yinghao & Zhang, Chao-Chao & Lee, Chien-Chiang & Lv, Suxiang, 2024. "Environmental performance evaluation of electric enterprises during a power crisis: Evidence from DEA methods and AI prediction algorithms," Energy Economics, Elsevier, vol. 130(C).
    12. Lee, Chien-Chiang & Yuan, Zihao, 2024. "Impact of energy poverty on public health: A non-linear study from an international perspective," World Development, Elsevier, vol. 174(C).
    13. Yahya, Farzan & Lee, Chien-Chiang, 2023. "Disentangling the asymmetric effect of financialization on the green output gap," Energy Economics, Elsevier, vol. 125(C).
    14. Ray, Subhash C. & Ghose, Arpita, 2014. "Production efficiency in Indian agriculture: An assessment of the post green revolution years," Omega, Elsevier, vol. 44(C), pages 58-69.
    15. J. Paul Elhorst, 2014. "Dynamic Spatial Panels: Models, Methods and Inferences," SpringerBriefs in Regional Science, in: Spatial Econometrics, edition 127, chapter 0, pages 95-119, Springer.
    16. Zhang, Yixiang & Xiong, Yali & Li, Feng & Cheng, Jinhua & Yue, Xiaochen, 2020. "Environmental regulation, capital output and energy efficiency in China: An empirical research based on integrated energy prices," Energy Policy, Elsevier, vol. 146(C).
    17. Borozan, Djula, 2018. "Technical and total factor energy efficiency of European regions: A two-stage approach," Energy, Elsevier, vol. 152(C), pages 521-532.
    18. Bertoldi, Paolo & Mosconi, Rocco, 2020. "Do energy efficiency policies save energy? A new approach based on energy policy indicators (in the EU Member States)," Energy Policy, Elsevier, vol. 139(C).
    19. Song, Malin & Zhang, Jie & Wang, Shuhong, 2015. "Review of the network environmental efficiencies of listed petroleum enterprises in China," Renewable and Sustainable Energy Reviews, Elsevier, vol. 43(C), pages 65-71.
    20. Lin, Boqiang & Wang, Miao, 2021. "What drives energy intensity fall in China? Evidence from a meta-frontier approach," Applied Energy, Elsevier, vol. 281(C).
    21. Guo, Xiaoying & Lu, Ching-Cheng & Lee, Jen-Hui & Chiu, Yung-Ho, 2017. "Applying the dynamic DEA model to evaluate the energy efficiency of OECD countries and China," Energy, Elsevier, vol. 134(C), pages 392-399.
    22. Wang, Qiao & Yi, Hongtao, 2021. "New energy demonstration program and China's urban green economic growth: Do regional characteristics make a difference?," Energy Policy, Elsevier, vol. 151(C).
    23. Lee, Chien-Chiang & Xing, Wenwu & Lee, Chi-Chuan, 2022. "The impact of energy security on income inequality: The key role of economic development," Energy, Elsevier, vol. 248(C).
    24. Lou, Zhaohui & Xie, Qizhuo & Shen, Jim Huangnan & Lee, Chien-Chiang, 2024. "Does Supply Chain Finance (SCF) alleviate funding constraints of SMEs? Evidence from China," Research in International Business and Finance, Elsevier, vol. 67(PA).
    25. Yao, Xin & Zhou, Hongchen & Zhang, Aizhen & Li, Aijun, 2015. "Regional energy efficiency, carbon emission performance and technology gaps in China: A meta-frontier non-radial directional distance function analysis," Energy Policy, Elsevier, vol. 84(C), pages 142-154.
    26. Liu, Jia-Bao & Zheng, Ya-Qian & Lee, Chien-Chiang, 2024. "Statistical analysis of the regional air quality index of Yangtze River Delta based on complex network theory," Applied Energy, Elsevier, vol. 357(C).
    27. Lee, Chien-Chiang & Qin, Shuai & Li, Yaya, 2022. "Does industrial robot application promote green technology innovation in the manufacturing industry?," Technological Forecasting and Social Change, Elsevier, vol. 183(C).
    28. Özkara, Yücel & Atak, Mehmet, 2015. "Regional total-factor energy efficiency and electricity saving potential of manufacturing industry in Turkey," Energy, Elsevier, vol. 93(P1), pages 495-510.
    29. Lee, Chien-Chiang & Yan, Jingyang & Wang, Fuhao, 2024. "Impact of population aging on food security in the context of artificial intelligence: Evidence from China," Technological Forecasting and Social Change, Elsevier, vol. 199(C).
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