业务
公司治理
执行
环境治理
产业组织
政府(语言学)
稳健性(进化)
污染
环境经济学
经济
财务
基因
生物
哲学
生物化学
化学
法学
语言学
生态学
政治学
作者
Daqian Shi,Caiqi Bu,Xue Hui-yuan
标识
DOI:10.1016/j.eneco.2021.105680
摘要
Few firm-level empirical studies have been conducted to test whether environmental information disclosure (EID) policy remains effective in pollution control and improving environmental performance. We treat the release of the Pollutant Information Transparency Index (PITI) in 2008 as a quasi-natural experiment, using matched data from the Chinese industrial firm database and the Chinese industrial firm pollution database from 2003 to 2012 and adopting the difference-in-differences (DID) method to estimate the emission reduction effect and mechanism of EID on SO2 emissions of firms. The results show that there is a significant emission reduction effect of EID on industrial firms and it still holds after a series of robustness checks. The heterogeneity analysis suggests that EID has a superior pollution emission reduction effect on private firms, large-scale firms and firms in the western region. To gain a more in-depth understanding of how emerging environmental regulations such as EID can affect the pollution emission behavior of firms, we further conduct mechanism tests and find that EID may induce non-compliant firms to reduce emissions by both improving the energy structure of firms and restructuring capital factors. In addition, this study verifies the moderating effect of local government environmental governance in the emission reduction process of EID. Local government can strengthen the enforcement of environmental regulations in order to improve the disclosed information content and send green signals, which in turn promotes firms to reduce emissions. This is conducive to further regularizing the disclosure content of EID and exerting the environmental governance effect of EID. It provides new support for local governments to better use the power of disclosure in the information age to encourage non-compliant firms to control pollution.
科研通智能强力驱动
Strongly Powered by AbleSci AI