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Is There a Digital Rebound in the Process of Urban Green Development? New Empirical Evidence Using Ensemble Learning Methods

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  • Ying Ping

    (College of Economics and Management, Shanghai Ocean University, Shanghai 201306, China)

  • Zhuolin Li

    (College of Economics and Management, Shanghai Ocean University, Shanghai 201306, China)

Abstract

The convergence of digitization and greening is an unavoidable path of modern economic progress. Nonetheless, the digital economy does not consistently align with the principles of green development, potentially leading to a rebound effect in urban digitalization initiatives. To investigate the correlation between the digital rebound effect and urban green development, this study utilizes panel data from Chinese prefecture-level cities spanning from 2011 to 2019. By examining the dual impact of the digital economy on green development, the paper posits a theoretical hypothesis regarding the nonlinear marginal effect of the digital economy. This research demonstrates an inverted U-shaped correlation between the digital economy and urban green development via empirical analyses employing the random forest algorithm and partial dependency plots. It supports the existence of a moderate digital resiliency effect, which eventually reaches a state of stability rather than greatly diminishing the degree of green development in urban areas. In addition, the heterogeneity analysis reveals that the positive effects of the digital economy are more popular in cities located in the eastern and central regions, as well as in the National Comprehensive Pilot Zone for Big Data. However, these effects do not vary significantly among different ranks of cities. The mechanism test found that the information effect and the capital allocation effect are the mechanisms by which the digital economy affects green development, and there is a “U-shaped” relationship between the digital economy and information asymmetry and capital mismatch. According to the study’s results, improving the digital economy’s governance structure continues to make more sense than merely increasing the number of digital inputs.

Suggested Citation

  • Ying Ping & Zhuolin Li, 2024. "Is There a Digital Rebound in the Process of Urban Green Development? New Empirical Evidence Using Ensemble Learning Methods," Sustainability, MDPI, vol. 16(10), pages 1-32, May.
  • Handle: RePEc:gam:jsusta:v:16:y:2024:i:10:p:4281-:d:1397584
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    References listed on IDEAS

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    1. Shuming Ren & Lianqing Li & Yueqi Han & Yu Hao & Haitao Wu, 2022. "The emerging driving force of inclusive green growth: Does digital economy agglomeration work?," Business Strategy and the Environment, Wiley Blackwell, vol. 31(4), pages 1656-1678, May.
    2. Pastor, Jesus T. & Lovell, C.A. Knox, 2005. "A global Malmquist productivity index," Economics Letters, Elsevier, vol. 88(2), pages 266-271, August.
    3. Dong-hyun Oh, 2010. "A global Malmquist-Luenberger productivity index," Journal of Productivity Analysis, Springer, vol. 34(3), pages 183-197, December.
    4. Avom, Désiré & Nkengfack, Hilaire & Fotio, Hervé Kaffo & Totouom, Armand, 2020. "ICT and environmental quality in Sub-Saharan Africa: Effects and transmission channels," Technological Forecasting and Social Change, Elsevier, vol. 155(C).
    5. Galvin, Ray, 2015. "The ICT/electronics question: Structural change and the rebound effect," Ecological Economics, Elsevier, vol. 120(C), pages 23-31.
    6. Lange, Steffen & Pohl, Johanna & Santarius, Tilman, 2020. "Digitalization and energy consumption. Does ICT reduce energy demand?," Ecological Economics, Elsevier, vol. 176(C).
    7. Daoping Wang & Kerui Du & Ning Zhang, 2022. "Measuring technical efficiency and total factor productivity change with undesirable outputs in Stata," Stata Journal, StataCorp LP, vol. 22(1), pages 103-124, March.
    Full references (including those not matched with items on IDEAS)

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