Board directors’ educational backgrounds and corporate default risk: Evidence from China

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Type of the article: Research Article

Abstract
Amid China’s accelerating financial development and heightened concerns over corporate debt, default risk has emerged as a central challenge for financial stability. This study investigates whether the educational attainment of board directors significantly reduces corporate default risk in the context of China’s listed firms. Using a panel dataset of 4,751 firms spanning 2003–2023, default risk is measured through Merton Distance to Default and the Z-Score, a widely used metric of financial distress constructed as a weighted linear combination of five financial ratios. Fixed-effects regression results show that higher educational attainment among board members significantly lowers default risk. A one-standard-deviation increase in board education leads to a 0.344-point increase in Z-Score, approximately 7% of its standard deviation. Notably, the mitigating effect of board education is more evident in non-state-owned enterprises, where weaker governmental support makes governance quality especially vital. The effect is also stronger in small firms, where limited internal controls heighten reliance on board oversight. Furthermore, in firms with weak institutional monitoring, better-educated boards appear more capable of navigating market pressures and reducing financial vulnerability. To address potential endogeneity, lagged variable analyses are conducted, which suggest that earlier levels of board education predict lower future default risk. Two-stage least squares regressions, using the industry-median board education as an instrument, further support the causal interpretation of the relationship. These findings underscore the strategic importance of board education in mitigating financial distress, strengthening risk management, and fostering sustainable corporate development in China’s evolving market environment.

Acknowledgment
This research was funded by the Wenzhou Association for Science and Technology—Service and Technology Innovation Program [jczc0254], the General Program of the Zhejiang Provincial Department of Education [Y202353438], the Wenzhou-Kean University International Collaborative Research Program [ICRP2023002], and the Wenzhou-Kean University Student Partnering with Faculty Research Program [WKUSPF202411].

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    • Table 1. Descriptive statistics
    • Table 2. Pairwise correlations
    • Table 3. Baseline regressions
    • Table 4. Effect of institutional monitoring
    • Table 5. SOEs vs. non-SOEs
    • Table 6. Small vs. large firms
    • Table 7. Lagged board education
    • Table 8. Two-stage least squares regressions
    • Conceptualization
      Keyi Wei
    • Data curation
      Keyi Wei
    • Formal Analysis
      Keyi Wei, Haozhe Qi, Cagri Berk Onuk, Jianing Zhang
    • Investigation
      Keyi Wei, Haozhe Qi, Cagri Berk Onuk, Jianing Zhang
    • Methodology
      Keyi Wei, Haozhe Qi, Cagri Berk Onuk, Jianing Zhang
    • Resources
      Keyi Wei
    • Software
      Keyi Wei
    • Validation
      Keyi Wei, Haozhe Qi, Cagri Berk Onuk, Jianing Zhang
    • Visualization
      Keyi Wei, Haozhe Qi, Cagri Berk Onuk, Jianing Zhang
    • Writing – original draft
      Keyi Wei
    • Writing – review & editing
      Haozhe Qi, Cagri Berk Onuk, Jianing Zhang
    • Project administration
      Cagri Berk Onuk, Jianing Zhang
    • Supervision
      Cagri Berk Onuk, Jianing Zhang
    • Funding acquisition
      Jianing Zhang