Impact of gender and education on corporate social responsibility: evidence from Taiwan

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This paper empirically studies the impact of female proportion and the background of the board on corporate social responsibility (CSR) disclosure of Taiwanese listed firms. The different groups of board size are detected by the structural break test, which is used as the threshold for dividing subsamples. The results show that the higher proportion of women and accounting background of board of directors, the more CSR disclosure for firms with more than 11 directors in the board, implying that women and accounting background directors can only promote their compassionate and reciprocal in CSR decision-making in large board firms. Overall, the empirical results poorly support the efficiency hypothesis suggesting that the board of directors is more powerful when it has high gender diversity. This study also confirms that the linear regression method may not be able to fully present the various possible relationships between the variables.

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    • Figure 1. The breakpoints of the board size
    • Table 1. Variables definitions
    • Table 2. Test for unknown structural breaks
    • Table 3. Descriptive statistics
    • Table 4. The impact of board gender and accounting background on CSR (probit regression analysis for the case of more than 11 board members)
    • Table 5. The impact of Board gender and Accounting background on CSR (probit regression analysis for the case of 9-11 board members)
    • Table 6. The impact of Board gender and Accounting background on CSR (probit regression analysis for the case of 7-8 board members)
    • Table 7. The impact of Board gender and Accounting background on CSR (probit regression analysis for the case of less than 7 board members)
    • Conceptualization
      T. Thanh Binh Nguyen
    • Formal Analysis
      T. Thanh Binh Nguyen
    • Methodology
      T. Thanh Binh Nguyen, Qi-Wen Huang
    • Supervision
      T. Thanh Binh Nguyen
    • Writing – review & editing
      T. Thanh Binh Nguyen
    • Data curation
      Qi-Wen Huang
    • Writing – original draft
      Qi-Wen Huang