The Interaction of Ownership Concentration, Board Diversity, and Environmental Governance on Investment Efficiency and Financial Bankruptcy Risk

In the current context, where sustainability and environmental responsibilities have become key criteria for evaluating companies, understanding how governance mechanisms interact with financial performance is of critical importance for policymakers and investors. Particularly in emerging markets with concentrated ownership structures, identifying the moderating role of green governance and board diversity can offer effective solutions for mitigating risk and enhancing efficiency. To this end, the present study investigates the interaction effects of ownership concentration, board diversity, and environmental governance on investment efficiency and financial bankruptcy risk in 121 companies listed on the Tehran Stock Exchange during the years 2018 to 2024. By employing the dynamic Generalized Method of Moments (GMM), Panel Vector Error Correction Model (PVECM), and Granger causality test, short-run, long-run, and causal relationships between the variables are analyzed. Statistical findings indicate high ownership concentration (mean of 68.4%), moderate board diversity (Blau index of 0.341), and a limited level of environmental governance (mean of 0.412). The results show that although ownership concentration alone has a positive effect on reducing bankruptcy risk, it reduces investment efficiency when interacting with weak environmental governance. In contrast, board diversity plays a positive moderating role and neutralizes the negative effects of ownership concentration. The PVECM model confirms stronger long-run relationships and identifies environmental governance as a key factor for sustainability. The Granger causality test also indicates a causal direction from environmental governance towards investment efficiency and bankruptcy risk. This study fills the existing gap in the literature regarding the interaction of these factors in the Iranian capital market by presenting a comprehensive and dynamic model.