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Rebound Effect of China’s Electric Power Demand in the Context of Technological Innovation

Author

Listed:
  • Yan Lu

    (School of Economics and Management, Harbin Engineering University, Harbin 150001, China
    CCCC Fourth Highway Engineering Co., Ltd., Beijing 100022, China)

  • Xu Yang

    (School of Economics and Management, Harbin Engineering University, Harbin 150001, China)

  • Yixiang Ma

    (School of Economics and Management, Beijing University of Chemical Technology, Beijing 100029, China)

  • Lean Yu

    (School of Economics and Management, Harbin Engineering University, Harbin 150001, China
    School of Economics and Management, Beijing University of Chemical Technology, Beijing 100029, China
    WQ-UCAS Graduate School of Business, Binzhou Institute of Technology, Binzhou 256600, China
    WQ-UCAS Joint Lab, University of Chinese Academy of Sciences, Beijing 100190, China)

Abstract

Technological innovations in the power industry can help reduce electricity consumption but may also have a negative result due to rebound effects. Estimation and refinement of electricity demand rebound effects are important for assessing the impact of technological innovations. For this purpose, this paper first constructs a Log Mean Divisia Index (LMDI) to measure the structural and technical effects. Secondly, a Data Envelopment Analysis (DEA)–Malmquist Productivity Index is used to calculate the change in the generalized rate of technological progress, narrow rate of technological progress, and technical use efficiency. Thirdly, the electric power demand rebound effect during the New Normal period is calculated to compare with the rebound effect of the overall energy. Finally, a vector auto-regressive (VAR) model and an impulse response function (IRF) are used to investigate the impact degree of electric power demand changes on other energy demand under the “electrical energy substitution” strategy. The empirical results indicate that the general technological progress rate of China’s electric power industry is increasing gradually in the New Normal period, and the variations in electric demand exhibit the characteristics of the backfire effect and partial rebound effect, respectively, in the context of generalized technological innovation and narrow technological innovation. Meanwhile, contrary to the changing trend of the overall energy demand intensity, electric power demand intensity increased continuously with the advancement of the “electrical energy substitution” strategy, which led to a continuous decline in other energy demands.

Suggested Citation

  • Yan Lu & Xu Yang & Yixiang Ma & Lean Yu, 2022. "Rebound Effect of China’s Electric Power Demand in the Context of Technological Innovation," Sustainability, MDPI, vol. 14(14), pages 1-18, July.
    • Handle: RePEc:gam:jsusta:v:14:y:2022:i:14:p:8263-:d:856869
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    as
    1. Li, Ke & Zhang, Ning & Liu, Yanchu, 2016. "The energy rebound effects across China’s industrial sectors: An output distance function approach," Applied Energy, Elsevier, vol. 184(C), pages 1165-1175.
    2. Wang, Xiaolei & Wen, Xiaohui & Xie, Chunping, 2018. "An evaluation of technical progress and energy rebound effects in China's iron & steel industry," Energy Policy, Elsevier, vol. 123(C), pages 259-265.
    3. Qingsong Wang & Zhenlei Gao & Hongrui Tang & Xueliang Yuan & Jian Zuo, 2018. "Exploring the Direct Rebound Effect of Energy Consumption: A Case Study," Sustainability, MDPI, vol. 10(1), pages 1-21, January.
    4. Green, Rikard & Larsson, Karl & Lunina, Veronika & Nilsson, Birger, 2018. "Cross-commodity news transmission and volatility spillovers in the German energy markets," Journal of Banking & Finance, Elsevier, vol. 95(C), pages 231-243.
    5. Lei Jin & Keran Duan & Xu Tang, 2018. "What Is the Relationship between Technological Innovation and Energy Consumption? Empirical Analysis Based on Provincial Panel Data from China," Sustainability, MDPI, vol. 10(1), pages 1-13, January.
    6. Amjadi, Golnaz & Lundgren, Tommy & Persson, Lars, 2018. "The Rebound Effect in Swedish Heavy Industry," Energy Economics, Elsevier, vol. 71(C), pages 140-148.
    7. Engle, Robert & Granger, Clive, 2015. "Co-integration and error correction: Representation, estimation, and testing," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 39(3), pages 106-135.
    8. Yu, Biying & Zhang, Junyi & Fujiwara, Akimasa, 2013. "Evaluating the direct and indirect rebound effects in household energy consumption behavior: A case study of Beijing," Energy Policy, Elsevier, vol. 57(C), pages 441-453.
    9. Li, Jianglong & Lin, Boqiang, 2017. "Rebound effect by incorporating endogenous energy efficiency: A comparison between heavy industry and light industry," Applied Energy, Elsevier, vol. 200(C), pages 347-357.
    10. Caves, Douglas W & Christensen, Laurits R & Diewert, W Erwin, 1982. "The Economic Theory of Index Numbers and the Measurement of Input, Output, and Productivity," Econometrica, Econometric Society, vol. 50(6), pages 1393-1414, November.
    11. Granger, C W J, 1969. "Investigating Causal Relations by Econometric Models and Cross-Spectral Methods," Econometrica, Econometric Society, vol. 37(3), pages 424-438, July.
    12. Su, Yu-Wen, 2019. "Residential electricity demand in Taiwan: Consumption behavior and rebound effect," Energy Policy, Elsevier, vol. 124(C), pages 36-45.
    13. Li, Yi & Sun, Linyan & Feng, Taiwen & Zhu, Chunyan, 2013. "How to reduce energy intensity in China: A regional comparison perspective," Energy Policy, Elsevier, vol. 61(C), pages 513-522.
    14. Qiang Du & Yi Li & Libiao Bai, 2017. "The Energy Rebound Effect for the Construction Industry: Empirical Evidence from China," Sustainability, MDPI, vol. 9(5), pages 1-11, May.
    15. Safarzadeh, Soroush & Rasti-Barzoki, Morteza, 2019. "A game theoretic approach for assessing residential energy-efficiency program considering rebound, consumer behavior, and government policies," Applied Energy, Elsevier, vol. 233, pages 44-61.
    16. Yang, Lisha & Li, Zhi, 2017. "Technology advance and the carbon dioxide emission in China – Empirical research based on the rebound effect," Energy Policy, Elsevier, vol. 101(C), pages 150-161.
    17. Ang, B. W. & Liu, F. L. & Chew, E. P., 2003. "Perfect decomposition techniques in energy and environmental analysis," Energy Policy, Elsevier, vol. 31(14), pages 1561-1566, November.
    18. Lin, Boqiang & Liu, Xia, 2012. "Dilemma between economic development and energy conservation: Energy rebound effect in China," Energy, Elsevier, vol. 45(1), pages 867-873.
    19. Ouyang, Xiaoling & Gao, Beiying & Du, Kerui & Du, Gang, 2018. "Industrial sectors' energy rebound effect: An empirical study of Yangtze River Delta urban agglomeration," Energy, Elsevier, vol. 145(C), pages 408-416.
    20. Guangyu Chen & Boqiang Lin & Bin Ye, 2018. "Is China’s Manufacturing Industry Efficient? Evidence from an Energy-Rebound Effect Perspective," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 54(10), pages 2245-2257, August.
    21. Zhou, Meifang & Liu, Yu & Feng, Shenghao & Liu, Yang & Lu, Yingying, 2018. "Decomposition of rebound effect: An energy-specific, general equilibrium analysis in the context of China," Applied Energy, Elsevier, vol. 221(C), pages 280-298.
    22. Safarzadeh, Soroush & Rasti-Barzoki, Morteza & Hejazi, Seyed Reza & Piran, Md Jalil, 2020. "A game theoretic approach for the duopoly pricing of energy-efficient appliances regarding innovation protection and social welfare," Energy, Elsevier, vol. 200(C).
    23. Cheng, Shulei & Wu, Yinyin & Chen, Hua & Chen, Jiandong & Song, Malin & Hou, Wenxuan, 2019. "Determinants of changes in electricity generation intensity among different power sectors," Energy Policy, Elsevier, vol. 130(C), pages 389-408.
    24. Safarzadeh, Soroush & Rasti-Barzoki, Morteza & Hejazi, Seyed Reza, 2020. "A review of optimal energy policy instruments on industrial energy efficiency programs, rebound effects, and government policies," Energy Policy, Elsevier, vol. 139(C).
    25. Milin Lu & Zhaohua Wang, 2017. "Rebound effects for residential electricity use in urban China: an aggregation analysis based E-I-O and scenario simulation," Annals of Operations Research, Springer, vol. 255(1), pages 525-546, August.
    26. Zhang, Jiangshan & Lin Lawell, C.-Y. Cynthia, 2017. "The macroeconomic rebound effect in China," Energy Economics, Elsevier, vol. 67(C), pages 202-212.
    27. Bataille, Chris & Melton, Noel, 2017. "Energy efficiency and economic growth: A retrospective CGE analysis for Canada from 2002 to 2012," Energy Economics, Elsevier, vol. 64(C), pages 118-130.
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