IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v16y2024i6p2377-d1356206.html
   My bibliography  Save this article

The Sustainability of Corporate ESG Performance: An Empirical Study

Author

Listed:
  • Kezhi Yang

    (School of Business, Beijing Technology and Business University, Beijing 100048, China)

  • Tingting Zhang

    (School of Business, Beijing Technology and Business University, Beijing 100048, China)

  • Chenyun Ye

    (Accounting School, Shandong Management University, Jinan 250100, China)

Abstract

A company’s ESG (environmental, social, and government) performance is an indicator of its sustainable development. In practice, enterprises should focus on improving their governance structure and improving their governance level to achieve sustainable development and long-term value. Based on a sample of China’s A-share-listed companies from 2014 to 2022, this paper obtains data from the WIND and CSMAR databases and finally selects 14,757 observed values. With ESG performance as the explained variable and Pledge as the explanatory variable, the relationship between major shareholders’ equity pledges and ESG performance is explored using a regression analysis. The results show that the correlation coefficient, β1, between corporate ESG performance and the pledge ratio of major shareholders is −0.0167, which is significantly negative at the 1% level, indicating that the equity pledges of major shareholders will have a negative impact on corporate ESG performance, and ESG performance shows that the pressure of controlling shareholders’ equity pledges mainly reduces the performance of companies in the areas of social responsibility (S) and governance (G) and does not have a significant impact on environmental construction (E). Further research shows that under the same conditions, compared with state-owned enterprises, the equity pledge behavior of major shareholders of private enterprises has a more significant impact on corporate ESG performance. This study is a good attempt at examining the sustainability of corporate ESG performance.

Suggested Citation

  • Kezhi Yang & Tingting Zhang & Chenyun Ye, 2024. "The Sustainability of Corporate ESG Performance: An Empirical Study," Sustainability, MDPI, vol. 16(6), pages 1-19, March.
  • Handle: RePEc:gam:jsusta:v:16:y:2024:i:6:p:2377-:d:1356206
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/16/6/2377/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2071-1050/16/6/2377/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Fernando García & Jairo González-Bueno & Francisco Guijarro & Javier Oliver, 2020. "Forecasting the Environmental, Social, and Governance Rating of Firms by Using Corporate Financial Performance Variables: A Rough Set Approach," Sustainability, MDPI, vol. 12(8), pages 1-18, April.
    2. Xiaobei Huang & Xi Li & Senyo Tse & Jennifer Wu Tucker, 2018. "The effects of a mixed approach toward management earnings forecasts: Evidence from China," Journal of Business Finance & Accounting, Wiley Blackwell, vol. 45(3-4), pages 319-351, March.
    3. Jiang, Fuxiu & Xia, Xiaoxue & Zheng, Xiaojia, 2021. "Does controlling shareholders' share pledging raise suppliers' eyebrows?," Pacific-Basin Finance Journal, Elsevier, vol. 66(C).
    4. Wanlong Zhao & Wei Zhang & Xiong Xiong & Gaofeng Zou, 2019. "Share pledges, tone of earnings communication conferences, and market reaction: evidence from China," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 59(5), pages 2817-2853, December.
    5. Huang, Xiaobei & Li, Xi & Tse, Senyo & Tucker, Jennifer Wu, 2018. "The effects of a mixed approach toward management earnings forecasts: evidence from China," LSE Research Online Documents on Economics 87113, London School of Economics and Political Science, LSE Library.
    6. Liu, Hongxun & Zhang, Zihan, 2023. "The impact of managerial myopia on environmental, social and governance (ESG) engagement: Evidence from Chinese firms," Energy Economics, Elsevier, vol. 122(C).
    Full references (including those not matched with items on IDEAS)

    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. Qian Wang & Duowen Wu & Lina Yan, 2021. "Effect of positive tone in MD&A disclosure on capital structure adjustment speed: evidence from China," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 61(4), pages 5809-5845, December.
    2. Li, Shan & Mihaylov, George & Peranginangin, Yessy & Zurbruegg, Ralf, 2021. "Short selling patterns in cross-listed stocks," Global Finance Journal, Elsevier, vol. 48(C).
    3. Kun Tracy Wang & Nathan Zhenghang Zhu, 2023. "Conditional Mandates on Management Earnings Forecasts: The Impact on the Cost of Debt," Abacus, Accounting Foundation, University of Sydney, vol. 59(4), pages 901-953, December.
    4. Lu, Hai & Shin, Jee-Eun & Zhang, Mingyue, 2023. "Financial reporting and disclosure practices in China," Journal of Accounting and Economics, Elsevier, vol. 76(1).
    5. Ding, Xin & Tan, Wenhao & Kang, Yixuan, 2021. "The spillover effect of regulatory penalties on management and analysts’ earnings forecasts: Empirical evidence based on directors networks in China," International Review of Economics & Finance, Elsevier, vol. 76(C), pages 502-515.
    6. Xiao, MingFang & Cao, June & Chiang, Yao-Min, 2022. "Kiss the baby for the nurse's sake? - Guaranteeing employees' stock purchase against loss program," International Review of Financial Analysis, Elsevier, vol. 81(C).
    7. Nathan Zhenghang Zhu & Kun Tracy Wang & Mark Wilson, 2022. "The Effect of Conditional Management Earnings Forecast Mandates on Voluntary Disclosure and Analyst Forecast Properties," Abacus, Accounting Foundation, University of Sydney, vol. 58(3), pages 479-522, September.
    8. Liu, Beibei & Tan, Keqi & Wong, Sonia M.L. & Yip, Rita W.Y., 2022. "Intra-industry information transfer in emerging markets: Evidence from China," Journal of Banking & Finance, Elsevier, vol. 140(C).
    9. Hanwen Chen & Siyi Liu & Xin Liu & Jiani Wang, 2022. "Opportunistic timing of management earnings forecasts during the COVID‐19 crisis in China," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 62(S1), pages 1495-1533, April.
    10. Liu, Yurou, 2023. "Judicial independence and crash risk: Evidence from a natural experiment in China," Journal of Corporate Finance, Elsevier, vol. 83(C).
    11. Zhou, Zhongsheng & Li, Zhuo, 2023. "Corporate digital transformation and trade credit financing," Journal of Business Research, Elsevier, vol. 160(C).
    12. Nikunj Sachin & R. Rajesh, 2022. "An empirical study of supply chain sustainability with financial performances of Indian firms," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 24(5), pages 6577-6601, May.
    13. Valeria D’Amato & Rita D’Ecclesia & Susanna Levantesi, 2022. "ESG score prediction through random forest algorithm," Computational Management Science, Springer, vol. 19(2), pages 347-373, June.
    14. Chang, Jeffery (Jinfan) & Meng, Qingbin & Ni, Xiaoran, 2022. "A tale of riskiness: The real effects of share pledging on the Chinese stock market," Pacific-Basin Finance Journal, Elsevier, vol. 73(C).
    15. Li, Tangrong & Sun, Xuchu, 2023. "Is controlling shareholders' credit risk contagious to firms? — Evidence from China," Pacific-Basin Finance Journal, Elsevier, vol. 77(C).
    16. Zhou, Jingting & Li, Wanli & Yan, Ziqiao & Lyu, Huaili, 2021. "Controlling shareholder share pledging and stock price crash risk: Evidence from China," International Review of Financial Analysis, Elsevier, vol. 77(C).
    17. Qin, Xiao & Wang, Ze, 2023. "Share pledge financing network and systemic risks: Evidence from China," Journal of Banking & Finance, Elsevier, vol. 152(C).
    18. Runmei Luo & Yong Ye, 2024. "Pressure from words: The tone of investors in Chinese earnings communication conferences and managerial myopia," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 64(1), pages 833-868, March.
    19. Hsio-Yi Lin & Bin-Wei Hsu, 2023. "Empirical Study of ESG Score Prediction through Machine Learning—A Case of Non-Financial Companies in Taiwan," Sustainability, MDPI, vol. 15(19), pages 1-19, September.
    20. Baochen Yang & Yifang Liu & Yunpeng Su, 2023. "Earnings communication conferences and post‐earnings‐announcement drift: Evidence from China," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 63(2), pages 2145-2185, June.

    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:gam:jsusta:v:16:y:2024:i:6:p:2377-:d:1356206. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    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.