IDEAS home Printed from https://ideas.repec.org/a/eee/eneeco/v126y2023ics0140988323004553.html
   My bibliography  Save this article

Digital economy and carbon rebound effect: Evidence from Chinese cities

Author

Listed:
  • 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
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0140988323004553
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.eneco.2023.106957?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. 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).
    2. 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.
    3. Sorrell, Steve & Dimitropoulos, John, 2008. "The rebound effect: Microeconomic definitions, limitations and extensions," Ecological Economics, Elsevier, vol. 65(3), pages 636-649, April.
    4. 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.
    5. 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.
    6. 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.
    7. 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.
    8. 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).
    9. Wei, Taoyuan, 2010. "A general equilibrium view of global rebound effects," Energy Economics, Elsevier, vol. 32(3), pages 661-672, May.
    10. 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).
    11. 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.
    12. Carl Dahlman & Sam Mealy & Martin Wermelinger, 2016. "Harnessing the digital economy for developing countries," OECD Development Centre Working Papers 334, OECD Publishing.
    13. 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.
    14. 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.
    15. 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.
    16. 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.
    17. 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.
    18. 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).
    19. 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.
    20. 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.
    21. 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.
    22. Nathan Nunn & Nancy Qian, 2014. "US Food Aid and Civil Conflict," American Economic Review, American Economic Association, vol. 104(6), pages 1630-1666, June.
    23. 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.
    24. 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).
    25. Sadorsky, Perry, 2012. "Information communication technology and electricity consumption in emerging economies," Energy Policy, Elsevier, vol. 48(C), pages 130-136.
    26. 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.
    27. Quah, Danny, 1997. "Empirics for Growth and Distribution: Stratification, Polarization, and Convergence Clubs," CEPR Discussion Papers 1586, C.E.P.R. Discussion Papers.
    28. 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.
    29. 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.
    30. 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.
    31. 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.
    32. 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).
    33. 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).
    34. 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.
    35. 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.
    36. 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.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Guo, Yunxia & Yu, Mengyao & Xu, Mingchen & Tang, Ying & Huang, Jingran & Liu, Jia & Hao, Yu, 2023. "Productivity gains from green finance: A holistic and regional examination from China," Energy Economics, Elsevier, vol. 127(PA).
    2. Gao, Feng & He, Ziwen, 2024. "Digital economy, land resource misallocation and urban carbon emissions in Chinese resource-based cities," Resources Policy, Elsevier, vol. 91(C).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Karen Turner, 2013. ""Rebound" Effects from Increased Energy Efficiency: A Time to Pause and Reflect," The Energy Journal, International Association for Energy Economics, vol. 0(Number 4).
    2. Rocha, Felipe Freitas da & Almeida, Edmar Luiz Fagundes de, 2021. "A general equilibrium model of macroeconomic rebound effect: A broader view," Energy Economics, Elsevier, vol. 98(C).
    3. Thomas, Brinda A. & Azevedo, Inês L., 2013. "Estimating direct and indirect rebound effects for U.S. households with input–output analysis Part 1: Theoretical framework," Ecological Economics, Elsevier, vol. 86(C), pages 199-210.
    4. Li, Guohao & Niu, Miaomiao & Xiao, Jin & Wu, Jiaqian & Li, Jinkai, 2023. "The rebound effect of decarbonization in China’s power sector under the carbon trading scheme," Energy Policy, Elsevier, vol. 177(C).
    5. Ghoddusi, Hamed & Roy, Mandira, 2017. "Supply elasticity matters for the rebound effect and its impact on policy comparisons," Energy Economics, Elsevier, vol. 67(C), pages 111-120.
    6. 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.
    7. Taoyuan Wei & Xue Wang, 2020. "Rebound Effect from Income Savings Due to an Energy Efficiency Improvement by Households: An Input–Output Approach," Energies, MDPI, vol. 13(16), pages 1-10, August.
    8. Adha, Rishan & Hong, Cheng-Yih & Firmansyah, M. & Paranata, Ade, 2021. "Rebound effect with energy efficiency determinants: a two-stage analysis of residential electricity consumption in Indonesia," MPRA Paper 110444, University Library of Munich, Germany.
    9. Cansino, José M. & Ordóñez, Manuel & Prieto, Manuela, 2022. "Decomposition and measurement of the rebound effect: The case of energy efficiency improvements in Spain," Applied Energy, Elsevier, vol. 306(PA).
    10. Chen, Qian & Zha, Donglan & Wang, Lijun & Yang, Guanglei, 2022. "The direct CO2 rebound effect in households: Evidence from China's provinces," Renewable and Sustainable Energy Reviews, Elsevier, vol. 155(C).
    11. Ouyang, Xiaoling & Yang, Yuchuan & Du, Kerui & Cheng, Zhenyu, 2022. "How does residential electricity consumption respond to electricity efficiency improvement? Evidence from 287 prefecture-level cities in China," Energy Policy, Elsevier, vol. 171(C).
    12. Lemoine, Derek, 2020. "General equilibrium rebound from energy efficiency innovation," European Economic Review, Elsevier, vol. 125(C).
    13. 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.
    14. Maliyamu Abudureheman & Qingzhe Jiang & Xiucheng Dong & Cong Dong, 2022. "CO 2 Emissions in China: Does the Energy Rebound Matter?," Energies, MDPI, vol. 15(12), pages 1-25, June.
    15. Cansino, José M. & Román-Collado, Rocío & Merchán, José, 2019. "Do Spanish energy efficiency actions trigger JEVON’S paradox?," Energy, Elsevier, vol. 181(C), pages 760-770.
    16. Wei, Kai & Zhang, Zuopeng Justin & Lin, Boqiang, 2024. "Does news propaganda really affect residents’ electricity rebound effect: New evidence of non-price information," Energy, Elsevier, vol. 300(C).
    17. 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.
    18. Broberg, Thomas & Berg, Charlotte & Samakovlis, Eva, 2015. "The economy-wide rebound effect from improved energy efficiency in Swedish industries–A general equilibrium analysis," Energy Policy, Elsevier, vol. 83(C), pages 26-37.
    19. Orea, Luis & Llorca, Manuel & Filippini, Massimo, 2014. "Measuring energy efficiency and rebound effects using a stochastic demand frontier approach: the US residential energy demand," Efficiency Series Papers 2014/01, University of Oviedo, Department of Economics, Oviedo Efficiency Group (OEG).
    20. Bakry, Walid & Nghiem, Xuan-Hoa & Farouk, Sherine & Vo, Xuan Vinh, 2023. "Does it hurt or help? Revisiting the effects of ICT on economic growth and energy consumption: A nonlinear panel ARDL approach," Economic Analysis and Policy, Elsevier, vol. 78(C), pages 597-617.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:eneeco:v:126:y:2023:i:c:s0140988323004553. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/eneco .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.