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Assessment and Forecast of Green Total Factor Energy Efficiency in the Yellow River Basin—A Perspective Distinguishing the Upper, Middle and Lower Stream

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  • Minglu Ma

    (School of Economics and Management, China University of Petroleum (East China), Qingdao 266580, China)

  • Qiang Wang

    (School of Economics and Management, China University of Petroleum (East China), Qingdao 266580, China)

Abstract

As the fifth-longest river globally, the Yellow River is of great importance to the world’s ecological protection. Due to its location as an essential ecological barrier and economic zone, it is imperative to balance energy support and ecological management in the basin. In this process, improving energy efficiency is crucial solution. Distinguished into upstream, midstream, and downstream, we measured the trajectory of green total factor energy efficiency over the past fifteen years using the Super-Epsilon-based model. Further, we identified the heterogeneity of energy efficiency within different river basins with the help of kernel density estimation. We used it to analyze the geographical and policy reasons affecting energy efficiency fluctuations. Finally, we constructed high, medium, and low GDP growth scenarios, and used a long short-term memory neural network model to predict energy efficiency forecasts in each scenario. The study results clarified that the overall energy efficiency showed an upward trend since 2013. Among them, the most significant improvement in energy efficiency was observed upstream, while the energy efficiency in the middle and lower stream showed a decreasing trend. Regarding future development trends, an economic growth rate of 6.5% was most favorable for energy efficiency compared to 6% and 7%. This finding reminded us to be alert to the ecological condition of the lower Yellow River basin. In addition, maintaining an appropriate economic growth rate is helpful for the balance between development and ecology.

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  • Minglu Ma & Qiang Wang, 2022. "Assessment and Forecast of Green Total Factor Energy Efficiency in the Yellow River Basin—A Perspective Distinguishing the Upper, Middle and Lower Stream," Sustainability, MDPI, vol. 14(5), pages 1-23, February.
    • Handle: RePEc:gam:jsusta:v:14:y:2022:i:5:p:2506-:d:755443
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    as
    1. Yu, Binbin, 2022. "The Impact of the Internet on Industrial Green Productivity: Evidence from China," Technological Forecasting and Social Change, Elsevier, vol. 177(C).
    2. Chai, Jian & Guo, Ju-E & Wang, Shou-Yang & Lai, Kin Keung, 2009. "Why does energy intensity fluctuate in China?," Energy Policy, Elsevier, vol. 37(12), pages 5717-5731, December.
    3. Tone, Kaoru & Tsutsui, Miki, 2009. "Network DEA: A slacks-based measure approach," European Journal of Operational Research, Elsevier, vol. 197(1), pages 243-252, August.
    4. Tomasz Szul & Krzysztof Nęcka & Stanisław Lis, 2021. "Application of the Takagi-Sugeno Fuzzy Modeling to Forecast Energy Efficiency in Real Buildings Undergoing Thermal Improvement," Energies, MDPI, vol. 14(7), pages 1-16, March.
    5. Voigt, Sebastian & De Cian, Enrica & Schymura, Michael & Verdolini, Elena, 2014. "Energy intensity developments in 40 major economies: Structural change or technology improvement?," Energy Economics, Elsevier, vol. 41(C), pages 47-62.
    6. Huang, Junbing & Lai, Yali & Hu, Hanlei, 2020. "The effect of technological factors and structural change on China's energy intensity: Evidence from dynamic panel models," China Economic Review, Elsevier, vol. 64(C).
    7. Frank Asche & Odd Bjarte Nilsen & Ragnar Tveteras, 2008. "Natural Gas Demand in the European Household Sector," The Energy Journal, International Association for Energy Economics, vol. 0(Number 3), pages 27-46.
    8. Borozan, Djula, 2018. "Technical and total factor energy efficiency of European regions: A two-stage approach," Energy, Elsevier, vol. 152(C), pages 521-532.
    9. Jones, M. C., 1990. "The performance of kernel density functions in kernel distribution function estimation," Statistics & Probability Letters, Elsevier, vol. 9(2), pages 129-132, February.
    10. Wu, Bao & Wang, Qi & Fang, Chevy-Hanqing & Tsai, Fu-Sheng & Xia, Yuanze, 2022. "Capital flight for family? Exploring the moderating effects of social connections on capital outflow of family business," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 77(C).
    11. Woo, Chungwon & Chung, Yanghon & Chun, Dongphil & Seo, Hangyeol & Hong, Sungjun, 2015. "The static and dynamic environmental efficiency of renewable energy: A Malmquist index analysis of OECD countries," Renewable and Sustainable Energy Reviews, Elsevier, vol. 47(C), pages 367-376.
    12. Jha Ritesh Kumar & Bhattarai Natasha & KC Suraj & Shrestha Arjun Kumar & Kadariya Manahar, 2019. "Rooftop Farming: An Alternative To Conventional Farming For Urban Sustainability," Malaysian Journal of Sustainable Agriculture (MJSA), Zibeline International Publishing, vol. 3(1), pages 39-43, May.
    13. Liimatainen, Heikki & Pöllänen, Markus, 2010. "Trends of energy efficiency in Finnish road freight transport 1995-2009 and forecast to 2016," Energy Policy, Elsevier, vol. 38(12), pages 7676-7686, December.
    14. Ramakrushna Panigrahi, 2021. "Returns to Growth in Indian Automobile Industry: A Non-Parametric Data Envelopment Analysis (DEA) Approach," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 19(4), pages 747-765, December.
    15. Charles R. Hulten, 2000. "Total Factor Productivity: A Short Biography," NBER Working Papers 7471, National Bureau of Economic Research, Inc.
    16. Adom, Philip K. & Kwakwa, Paul Adjei, 2014. "Effects of changing trade structure and technical characteristics of the manufacturing sector on energy intensity in Ghana," Renewable and Sustainable Energy Reviews, Elsevier, vol. 35(C), pages 475-483.
    17. Gilbert E. Metcalf, 2008. "An Empirical Analysis of Energy Intensity and Its Determinants at the State Level," The Energy Journal, International Association for Energy Economics, vol. 0(Number 3), pages 1-26.
    18. Jiuwen Sun & Shanshan Li, 2014. "Total Factor Energy Efficiency of Yangtze River Delta Region in China," ERSA conference papers ersa14p799, European Regional Science Association.
    19. Färe, Rolf & Grosskopf, Shawna & Pasurka, Carl A., 2007. "Environmental production functions and environmental directional distance functions," Energy, Elsevier, vol. 32(7), pages 1055-1066.
    20. Gilbert E. Metcalf, 2008. "An Empirical Analysis of Energy Intensity and Its Determinants at the State Level," The Energy Journal, International Association for Energy Economics, vol. 0(Number 3), pages 1-26.
    21. Hong Yao & Qingxiang Zhang & Guangyuan Niu & Huan Liu & Yuxi Yang, 2021. "Applying the GM(1,1) model to simulate and predict the ecological footprint values of Suzhou city, China," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 23(8), pages 11297-11309, August.
    22. Xiaoli, Zhao & Rui, Yang & Qian, Ma, 2014. "China's total factor energy efficiency of provincial industrial sectors," Energy, Elsevier, vol. 65(C), pages 52-61.
    23. 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.
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    Cited by:

    1. Xiaoyan Li & Yaxin Tan & Kang Tian, 2022. "The Impact of Environmental Regulation, Industrial Structure, and Interaction on the High-Quality Development Efficiency of the Yellow River Basin in China from the Perspective of the Threshold Effect," IJERPH, MDPI, vol. 19(22), pages 1-15, November.
    2. Ping Han & Ziyu Zhou, 2023. "The Harmonious Relationship between Energy Utilization Efficiency and Industrial Structure Development under Carbon Emission Constraints: Measurement, Quantification, and Identification," Sustainability, MDPI, vol. 15(14), pages 1-21, July.
    3. Zhu, Minglei & Huang, Haiyan & Ma, Weiwen, 2023. "Transformation of natural resource use: Moving towards sustainability through ICT-based improvements in green total factor energy efficiency," Resources Policy, Elsevier, vol. 80(C).

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