Business groups are industry exemplars whose investment decisions and social responsibility commitments are important for future sustainable development. We use data from China’s listed firms from 2012 to 2018 to investigate the effects of ESG-related disclosure on corporate investment efficiency by comparing the heterogeneity in ESG-related disclosure between group-affiliated firms and standalone firms, as well as between member firms within groups at different pyramid levels. We find that (1) group-affiliated firms are more willing to disclose ESG information than independent ones, and compared with lower-level pyramid member firms, higher-level pyramid member firms have a higher propensity of ESG disclosure; (2) over-investment for group-affiliated firms and under-investment for higher-level pyramid member firms are all moderated by their higher propensity for ESG disclosure. That is, corporate disclosure of ESG information significantly promotes investment efficiency; (3) by grouping the sample firms according to analyst attention and industry external financing dependence, respectively, we find that the promotion effect of ESG disclosure on corporate investment efficiency is more significant when the firms are followed by fewer analysts, or when firms belong to industries with higher external financing dependence. Our findings suggest that ESG disclosure plays an important role in driving a firm’s investment toward desirable levels.
We take the “Environmental Information Disclosure Measures (Trial)” implemented in China as a quasi-natural experiment and use the difference-in-difference (DID) method to identify the impact of environmental information disclosure (EID) on local exports. Additionally, we further investigate the impact of fiscal decentralization on local governments’ performance of this centrally mandated environmental information disclosure policy. Our results suggest that EID significantly hinders local exports, and such an inhibition effect exhibits obvious regional and stringency heterogeneity. Furthermore, the degree of fiscal decentralization is positively related to the enthusiasm of local governments in implementing the EID policy, thus strengthening EID’s inhibitory impact on local exports. As for the mechanisms behind, we verify that EID activates the “cost effect” and increases the cost of local pollution control. However, it cannot stimulate local innovation at the same time, and the “innovation effect” does not work, which ultimately results in a decrease in local exports; for cities with a high degree of fiscal decentralization, local governments tend to actively implement the centrally-mandated environmental protection policy by increasing investments in environmental pollution control and stimulating the innovation vitality of local enterprises. But the benefits from the innovation improvement cannot fully offset the negative impact of the increase in environmental costs in the short term, and local exports are further reduced.
This paper examines the effects of imports and exports on China's PM2.5 pollution using data from 31 provinces during the period 2001–2016. At the aggregate level, our analysis shows that exports have a pollution‐generating effect while imports have a pollution‐shifting effect on provincial PM2.5 pollution. Cross‐sectional analysis reveals that imports and exports exhibit opposite effects on manufacturing and high‐tech industries, but demonstrate the same pollution‐generating effect for the heavy industry sector. At the regional level, the effects are similar to those at the aggregate level. We also examine the impacts of other factors on PM2.5 pollution. Our empirical evidence shows that PM2.5 pollution is positively correlated with domestic sales, population density, economic growth, urbanization rate, and transportation, but negatively correlated with energy efficiency and industry structure. This paper suggests that reducing exports and increasing imports will help to reduce PM2.5 pollution.
Purpose: The establishment of environmental courts in China provides a good opportunity to explores the economic effects of environmental justice reform. This paper investigates how the environmental justice reform can influence corporate green transformation from the perspective of green technology innovation and explores the potential mechanisms of how the environmental courts affect green technology innovation. The heterogeneous effects of environmental courts are also considered.Methodology: Using the establishment of environmental courts in China as a quasi-natural experiment, this paper adopts a difference-in-difference (DID) method to conduct empirical test based on data on Chinese listed A-shared firms from 2004 to 2019. Moreover, this paper use propensity score matching (PSM), tobit and negative binomial regression method to address possible estimation bias.Findings: The establishment of environmental courts significantly enhances green technology innovation among enterprises. The more effective judicial enforcement and better public awareness of the environment brought by the environmental courts will increase the cost of illegality and external supervision pressure for firms, which will lead firms to innovate in green technology. Furthermore, the positive and significant effect of environmental courts on green technology innovation is more pronounced in state-owned enterprises (SOEs) and enterprises located in regions where local protectionism is more serious or regions with more ideal environmental legal system.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
Copyright © 2025 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.