Automatic air pollution monitoring and corporate environmental disclosure: a quasi-natural experiment from China

Purpose - This study aims to investigate the role of regional environmental transparency on corporate environmental disclosure. Design/methodology/approach - This study uses the introduction of a nationwide automated air pollution monitoring network in China as a quasi-natural experiment and employs regression analysis. Robustness checks, including parallel trend test and placebo test, are performed to test the robustness of the results. Findings - Sharing air pollution data with the public can improve corporate environmental disclosure. Firms with poorer environmental, social and governance (ESG) performance prefer to disclose less informative information after the automated network is implemented compared with firms with better ESG performance. The relationship between information sharing and corporate environmental transparency is more pronounced when local air pollution is severer, firms face stronger investor scrutiny and firms are from heavily polluting industries. The mechanism tests suggest the automated system can draw public environmental attention and improve governments’ aspiration for environmental governance. Finally, corporate environmental disclosure can reduce stock price crash risk and cost of equity. Practical implications - Real-time pollution data reporting is an important solution to raising public environmental awareness and then enhancing the effectiveness of pollution control. Social implications - This study has implications for policy-making regarding environmental governance and environmental disclosure. Originality/value - This study confirms that pollution information transparency can motivate firms to increase environmental disclosure.