ESG ratings and stock performance in the internet industry

  • Received November 29, 2023;
    Accepted January 12, 2024;
    Published January 17, 2024
  • Author(s)
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  • Article Info
    Volume 21 2024, Issue #1, pp. 38-50
  • Cited by
    2 articles

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This work is licensed under a Creative Commons Attribution 4.0 International License

Amidst the escalating emphasis on sustainable development, numerous corporations and organizations have intensified their environmental, social, and governance (ESG) efforts. The internet sector, intrinsically linked to the ESG domain, has consequently garnered amplified scrutiny. This study delves into the correlation between ESG ratings and the stock performance of publicly listed Chinese companies in the internet sector from 2016 to 2020. The findings reveal that initiatives in the ESG sphere significantly and negatively influence stock performance in these firms, assessed through raw stock returns, stock excess returns relative to the market index, Jensen’s one-factor alpha, and the Fama-French three-factor alpha. This inverse correlation between ESG ratings and stock performance is nonlinear and convex, indicating a lessening negative impact at elevated ESG levels. Moreover, this adverse effect is more pronounced in value stocks compared to growth stocks. Predominantly manifesting before 2018, this negative trend diminishes amidst the COVID-19 period. The reverse causality analysis employing lagged ESG ratings suggests that higher ESG ratings precipitate reduced stock performance, as opposed to vice versa. This study bridges a gap in the existing literature concerning ESG and stock performance specific to the Chinese internet industry and proposes recommendations for its sustainable evolution.

This research was supported by the Department of Education of Zhejiang Province General Program (Y202249981, Y202353438), the Wenzhou Association for Science and Technology – Service and Technology Innovation Program (jczc0254), the Wenzhou-Kean University Student Partnering with Faculty Research Program (WKUSPF2023004), the Wenzhou-Kean University International Collaborative Research Program (ICRP2023002, ICRP2023004), and the Wenzhou-Kean University Internal Research Support Program (IRSPG202205, IRSPG202206).

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    • Table 1. Descriptive statistics
    • Table 2. Pairwise correlations between variables
    • Table 3. Baseline regressions
    • Table 4. Nonlinear quadratic regressions
    • Table 5. Moderating effects of control variables
    • Table 6. Subperiod analysis
    • Table 7. Reverse causality analysis
    • Conceptualization
      Lan Wang, Jianing Zhang
    • Data curation
      Lan Wang
    • Formal Analysis
      Lan Wang, Zhenyuan Weng, Chunxiao Xue, Jianing Zhang
    • Investigation
      Lan Wang, Zhenyuan Weng, Chunxiao Xue, Jianing Zhang
    • Methodology
      Lan Wang, Zhenyuan Weng, Chunxiao Xue, Jianing Zhang
    • Resources
      Lan Wang
    • Software
      Lan Wang, Zhenyuan Weng
    • Visualization
      Lan Wang
    • Writing – original draft
      Lan Wang
    • Validation
      Zhenyuan Weng, Chunxiao Xue, Jianing Zhang
    • Writing – review & editing
      Zhenyuan Weng, Chunxiao Xue, Jianing Zhang
    • Funding acquisition
      Chunxiao Xue, Jianing Zhang
    • Project administration
      Chunxiao Xue, Jianing Zhang
    • Supervision
      Chunxiao Xue, Jianing Zhang