Role of board indexes on corporate social responsibility (CSR) and shareholders’ wealth
Journal of Cleaner Production
Corporate governance plays a vital role in supporting the moral obligation of social responsibility and wealth maximization to facilitate stakeholders. The core purpose of the study is to investigate the impact of corporate governance indexes on social responsibility and Shareholders' wealth maximization in the US firms. The current study employs a sample of 286 non-financial S&P 1500 listed firms from the year 2010–2020. The panel data for S&P 1500 index firms were collected from the Eikone data stream professional service terminal. Panel regression models with fixed and random effects were employed to investigate the proposed hypotheses. In addition, the problem of endogeneity was addressed by the dynamic GMM model. This study constructed an index score for the very first time to address CSR and shareholders' wealth. The results of the study revealed that board composition and board diversity support community development (CSR), but negatively impact global sustainability development (CSR index). However, the audit committee was found to have no impact on both CSR funds and Index. Moreover, the audit committee index (AC) and board diversity index (BC) were also found to significantly contribute to shareholders' wealth maximization, but the audit committee index does not support community development. Shareholder wealth was found to have a very weak relationship with the audit committee index. Our findings have significant implications especially for developed countries. The policymakers and legislators are suggested to employ diverse boards of directors with a balanced composition to enhance human welfare and community development. In addition, regulatory bodies should appoint skilled audit committee members and directors with diverse cultural backgrounds, qualifications and experience to protect common shareholders' interest.
Board indexes, corporate social responsibility (CSR), shareholders’ wealth, dynamic GMM model, panel regression models.