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Digital economy and carbon rebound effect: Evidence from Chinese cities

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  • Zhu, Yuke
  • Lan, Mudan

Abstract

It is theoretical and practical significance to incorporate the digital economy (DE) into the measurement framework of carbon rebound effect (CRE) for the accurate measurement of the current CRE of Chinese cities. Based on Chinese city-level data from 2011 to 2019, this study innovatively incorporates DE as a driver of carbon emissions, measures the urban CRE in DE through an improved stochastic frontier (SFA) model of carbon emissions, and further explores the formation mechanism of DE to induce the CRE of Chinese cities. When the DE was integrated into the measurement framework of the CRE, the CRE of Chinese cities ranged from 40.7% to 99.1%, with a mean value of 58.4%, indicating that the actual carbon reduction in Chinese cities under the DE was only approximately 40% of that expected. Meanwhile, the CRE of Chinese cities is characterized by cyclical fluctuations and a spatial distribution pattern of “inland to coastal decreasing,” and the polarization effect gradually appears. It is worth noting that the DE significantly contributed to CRE. It will enhance energy efficiency and promote economic growth, which will increase energy consumption through the “substitution effect,” “income effect,” and “output effect,” thus inducing and expanding the urban CRE.

Suggested Citation

  • Zhu, Yuke & Lan, Mudan, 2023. "Digital economy and carbon rebound effect: Evidence from Chinese cities," Energy Economics, Elsevier, vol. 126(C).
    • Handle: RePEc:eee:eneeco:v:126:y:2023:i:c:s0140988323004553
    DOI: 10.1016/j.eneco.2023.106957
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    as
    1. Yin, Zhichao & Gong, Xue & Guo, Peiyao & Wu, Tao, 2019. "What Drives Entrepreneurship in Digital Economy? Evidence from China," Economic Modelling, Elsevier, vol. 82(C), pages 66-73.
    2. Llorca, Manuel & Jamasb, Tooraj, 2017. "Energy efficiency and rebound effect in European road freight transport," Transportation Research Part A: Policy and Practice, Elsevier, vol. 101(C), pages 98-110.
    3. Zhang, Xiaoqun, 2013. "Income disparity and digital divide: The Internet Consumption Model and cross-country empirical research," Telecommunications Policy, Elsevier, vol. 37(6), pages 515-529.
    4. Nathan Nunn & Nancy Qian, 2014. "US Food Aid and Civil Conflict," American Economic Review, American Economic Association, vol. 104(6), pages 1630-1666, June.
    5. Hamdi, Helmi & Sbia, Rashid & Shahbaz, Muhammad, 2014. "The nexus between electricity consumption and economic growth in Bahrain," Economic Modelling, Elsevier, vol. 38(C), pages 227-237.
    6. Kenneth A. Small & Kurt Van Dender, 2007. "Fuel Efficiency and Motor Vehicle Travel: The Declining Rebound Effect," The Energy Journal, International Association for Energy Economics, vol. 0(Number 1), pages 25-52.
    7. Morakinyo O. Adetutu, Anthony J. Glass, and Thomas G. Weyman-Jones, 2016. "Economy-wide Estimates of Rebound Effects: Evidence from Panel Data," The Energy Journal, International Association for Energy Economics, vol. 0(Number 3).
    8. Zhang, Zhaowen & Jiang, Yaohui, 2022. "Can green public procurement change energy efficiency? Evidence from a quasi-natural experiment in China," Energy Economics, Elsevier, vol. 113(C).
    9. Saunders, Harry D., 2000. "A view from the macro side: rebound, backfire, and Khazzoom-Brookes," Energy Policy, Elsevier, vol. 28(6-7), pages 439-449, June.
    10. Sorrell, Steve & Dimitropoulos, John, 2008. "The rebound effect: Microeconomic definitions, limitations and extensions," Ecological Economics, Elsevier, vol. 65(3), pages 636-649, April.
    11. Wang, Jianda & Dong, Xiucheng & Dong, Kangyin, 2022. "How does ICT agglomeration affect carbon emissions? The case of Yangtze River Delta urban agglomeration in China," Energy Economics, Elsevier, vol. 111(C).
    12. Gene M. Grossman & Alan B. Krueger, 1995. "Economic Growth and the Environment," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 110(2), pages 353-377.
    13. Sadorsky, Perry, 2012. "Information communication technology and electricity consumption in emerging economies," Energy Policy, Elsevier, vol. 48(C), pages 130-136.
    14. 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.
    15. Quah, Danny, 1997. "Empirics for Growth and Distribution: Stratification, Polarization, and Convergence Clubs," CEPR Discussion Papers 1586, C.E.P.R. Discussion Papers.
    16. Cho, Youngsang & Lee, Jongsu & Kim, Tai-Yoo, 2007. "The impact of ICT investment and energy price on industrial electricity demand: Dynamic growth model approach," Energy Policy, Elsevier, vol. 35(9), pages 4730-4738, September.
    17. A. Greening, Lorna & Greene, David L. & Difiglio, Carmen, 2000. "Energy efficiency and consumption -- the rebound effect -- a survey," Energy Policy, Elsevier, vol. 28(6-7), pages 389-401, June.
    18. Wei, Taoyuan, 2007. "Impact of energy efficiency gains on output and energy use with Cobb-Douglas production function," Energy Policy, Elsevier, vol. 35(4), pages 2023-2030, April.
    19. Wei, Taoyuan, 2010. "A general equilibrium view of global rebound effects," Energy Economics, Elsevier, vol. 32(3), pages 661-672, May.
    20. Shao, Shuai & Guo, Longfei & Yu, Mingliang & Yang, Lili & Guan, Dabo, 2019. "Does the rebound effect matter in energy import-dependent mega-cities? Evidence from Shanghai (China)," Applied Energy, Elsevier, vol. 241(C), pages 212-228.
    21. Chai, Jian & Du, Mengfan & Liang, Ting & Sun, Xiaojie Christine & Yu, Ji & Zhang, Zhe George, 2019. "Coal consumption in China: How to bend down the curve?," Energy Economics, Elsevier, vol. 80(C), pages 38-47.
    22. Chen, Zhe & Song, Pei & Wang, Baolu, 2021. "Carbon emissions trading scheme, energy efficiency and rebound effect – Evidence from China's provincial data," Energy Policy, Elsevier, vol. 157(C).
    23. Orea, Luis & Llorca, Manuel & Filippini, Massimo, 2015. "A new approach to measuring the rebound effect associated to energy efficiency improvements: An application to the US residential energy demand," Energy Economics, Elsevier, vol. 49(C), pages 599-609.
    24. Carl Dahlman & Sam Mealy & Martin Wermelinger, 2016. "Harnessing the digital economy for developing countries," OECD Development Centre Working Papers 334, OECD Publishing.
    25. Lin, Boqiang & Zhu, Penghu, 2021. "Measurement of the direct rebound effect of residential electricity consumption: An empirical study based on the China family panel studies," Applied Energy, Elsevier, vol. 301(C).
    26. Xie, Rui & Fang, Jiayu & Liu, Cenjie, 2017. "The effects of transportation infrastructure on urban carbon emissions," Applied Energy, Elsevier, vol. 196(C), pages 199-207.
    27. Yang, Zhenbing & Fan, Meiting & Shao, Shuai & Yang, Lili, 2017. "Does carbon intensity constraint policy improve industrial green production performance in China? A quasi-DID analysis," Energy Economics, Elsevier, vol. 68(C), pages 271-282.
    28. Lin, Boqiang & Chen, Yufang & Zhang, Guoliang, 2017. "Technological progress and rebound effect in China's nonferrous metals industry: An empirical study," Energy Policy, Elsevier, vol. 109(C), pages 520-529.
    29. Zha, Donglan & Chen, Qian & Wang, Lijun, 2022. "Exploring carbon rebound effects in Chinese households’ consumption: A simulation analysis based on a multi-regional input–output framework," Applied Energy, Elsevier, vol. 313(C).
    30. Druckman, Angela & Chitnis, Mona & Sorrell, Steve & Jackson, Tim, 2011. "Missing carbon reductions? Exploring rebound and backfire effects in UK households," Energy Policy, Elsevier, vol. 39(6), pages 3572-3581, June.
    31. Zhang, Yue-Jun & Liu, Zhao & Qin, Chang-Xiong & Tan, Tai-De, 2017. "The direct and indirect CO2 rebound effect for private cars in China," Energy Policy, Elsevier, vol. 100(C), pages 149-161.
    32. Quah, Danny T, 1997. "Empirics for Growth and Distribution: Stratification, Polarization, and Convergence Clubs," Journal of Economic Growth, Springer, vol. 2(1), pages 27-59, March.
    33. Yi, Ming & Liu, Yafen & Sheng, Mingyue Selena & Wen, Le, 2022. "Effects of digital economy on carbon emission reduction: New evidence from China," Energy Policy, Elsevier, vol. 171(C).
    34. Aigner, Dennis & Lovell, C. A. Knox & Schmidt, Peter, 1977. "Formulation and estimation of stochastic frontier production function models," Journal of Econometrics, Elsevier, vol. 6(1), pages 21-37, July.
    35. Moyer, Jonathan D. & Hughes, Barry B., 2012. "ICTs: Do they contribute to increased carbon emissions?," Technological Forecasting and Social Change, Elsevier, vol. 79(5), pages 919-931.
    36. Harty D. Saunders, 1992. "The Khazzoom-Brookes Postulate and Neoclassical Growth," The Energy Journal, International Association for Energy Economics, vol. 0(Number 4), pages 131-148.
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