Can enhanced CSR quality reduce the cost of debt capital? An empirical analysis of CEO expertise and non-financial reporting practices in China

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This study aims to investigate whether stockholders and creditors place a positive value on corporate social responsibility (CSR) information disclosure when making decisions about providing financing to firms, thereby influencing their investment choices. Utilizing data from the China Stock Market & Accounting Research Database (CSMAR) and HEXUN, the study analyzes CSR disclosures and financial data of 7,123 firm-year observations of A-share listed companies on the Shanghai and Shenzhen stock exchanges from 2012 to 2020. A comprehensive methodology involving regression analysis was applied to assess the relationship between CSR quality and the cost of debt capital. Various robustness tests, including different model specifications and alternative variable measurements, were conducted to ensure the reliability and validity of the findings. The results obtained indicate that higher CSR quality significantly correlates with a lower cost of debt capital, supporting the hypothesis that improved CSR disclosure reduces perceived credit risk. However, CEO financial expertise shows a significantly positive relationship with the cost of debt capital. Furthermore, the study reveals that CSR assurance and engagement with Big 4 accounting firms do not noticeably affect the price of debt capital, whereas mandatory CSR reporting does. The findings underscore the importance of CSR quality in financial decision-making, offering valuable insights.

Acknowledgment
This paper is co-funded by the European Union through the European Education and Culture Executive Agency (EACEA) within the project “EU Best Practice of Life Cycle Assessment, Social, Environmental Accounting and Sustainability Reporting” – 101047667-ERASMUS-JMO-2021-MODULE https://jm.snau.edu.ua/en/eu-best-practice-of-life-cycle-assessment-social-environmental-accounting-and-sustainability-reporting/
Oleh Pasko expresses sincere gratitude for the support from the Kirkland Research Program, generously provided by the Leaders of Change Foundation established by the Polish-American Freedom Foundation.

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    • Table 1. Sample selection
    • Table 2. Descriptive statistics
    • Table 3. Correlations matrix
    • Table A1. Variables’ definition and proxies
    • Table A2. Regression analysis – І
    • Table A3. Regression analysis – ІІ
    • Table A4. Regression analysis – ІІІ
    • Table A5. Regression analysis – ІV
    • Table A6. Endogeneity test
    • Conceptualization
      Oleh Pasko, Nelia Proskurina, Vadym Sapych
    • Funding acquisition
      Oleh Pasko
    • Investigation
      Oleh Pasko, Yang Zhang, Nelia Proskurina, Vadym Sapych, Yelyzaveta Mykhailova
    • Methodology
      Oleh Pasko, Vadym Sapych
    • Project administration
      Oleh Pasko, Yang Zhang
    • Supervision
      Oleh Pasko
    • Visualization
      Oleh Pasko, Yang Zhang, Vadym Sapych, Yelyzaveta Mykhailova
    • Writing – original draft
      Oleh Pasko, Yang Zhang, Nelia Proskurina, Vadym Sapych, Yelyzaveta Mykhailova
    • Writing – review & editing
      Oleh Pasko
    • Data curation
      Yang Zhang, Vadym Sapych
    • Formal Analysis
      Yang Zhang, Nelia Proskurina, Yelyzaveta Mykhailova
    • Software
      Nelia Proskurina, Yelyzaveta Mykhailova
    • Validation
      Nelia Proskurina, Vadym Sapych, Yelyzaveta Mykhailova