{"title":"环境管理体系认证和企业ESG绿色化","authors":"Zhonghua Cheng, Xueqin Yan","doi":"10.1016/j.eneco.2025.108800","DOIUrl":null,"url":null,"abstract":"<div><div>Environmental management system certification (EMSC) has been widely recognized for its effectiveness in enhancing corporate environmental management performance and alleviating environmental pollution. However, it may concurrently facilitate corporate ESG greenwashing through opportunistic behavior. Leveraging the distinct strengths of double machine learning in both variable selection and model estimation, we analyze data from Chinese listed firms during 2012 to 2022 to examine the effects and mechanisms of environmental management system certification on corporate ESG greenwashing within the double machine learning framework. The empirical results reveal that: (1) Environmental management system certification significantly suppresses corporate ESG greenwashing, and this finding holds consistently across various endogeneity and robustness tests. (2) Mechanism analysis indicates that environmental management system certification can affect firms' internal governance and external stakeholder attention, thereby constraining earnings management, enhancing stakeholder supervision, and reducing inefficient investment, thus mitigating corporate ESG greenwashing. (3) Heterogeneity analysis suggests that the impact of environmental management system certification in curbing ESG greenwashing is more pronounced for small-scale firms, private firms, and firms in clean industries.</div></div>","PeriodicalId":11665,"journal":{"name":"Energy Economics","volume":"149 ","pages":"Article 108800"},"PeriodicalIF":14.2000,"publicationDate":"2025-07-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Environmental management system certification and corporate ESG greenwashing\",\"authors\":\"Zhonghua Cheng, Xueqin Yan\",\"doi\":\"10.1016/j.eneco.2025.108800\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>Environmental management system certification (EMSC) has been widely recognized for its effectiveness in enhancing corporate environmental management performance and alleviating environmental pollution. However, it may concurrently facilitate corporate ESG greenwashing through opportunistic behavior. Leveraging the distinct strengths of double machine learning in both variable selection and model estimation, we analyze data from Chinese listed firms during 2012 to 2022 to examine the effects and mechanisms of environmental management system certification on corporate ESG greenwashing within the double machine learning framework. The empirical results reveal that: (1) Environmental management system certification significantly suppresses corporate ESG greenwashing, and this finding holds consistently across various endogeneity and robustness tests. (2) Mechanism analysis indicates that environmental management system certification can affect firms' internal governance and external stakeholder attention, thereby constraining earnings management, enhancing stakeholder supervision, and reducing inefficient investment, thus mitigating corporate ESG greenwashing. (3) Heterogeneity analysis suggests that the impact of environmental management system certification in curbing ESG greenwashing is more pronounced for small-scale firms, private firms, and firms in clean industries.</div></div>\",\"PeriodicalId\":11665,\"journal\":{\"name\":\"Energy Economics\",\"volume\":\"149 \",\"pages\":\"Article 108800\"},\"PeriodicalIF\":14.2000,\"publicationDate\":\"2025-07-30\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Energy Economics\",\"FirstCategoryId\":\"96\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0140988325006279\",\"RegionNum\":2,\"RegionCategory\":\"经济学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"ECONOMICS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Energy Economics","FirstCategoryId":"96","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0140988325006279","RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ECONOMICS","Score":null,"Total":0}
Environmental management system certification and corporate ESG greenwashing
Environmental management system certification (EMSC) has been widely recognized for its effectiveness in enhancing corporate environmental management performance and alleviating environmental pollution. However, it may concurrently facilitate corporate ESG greenwashing through opportunistic behavior. Leveraging the distinct strengths of double machine learning in both variable selection and model estimation, we analyze data from Chinese listed firms during 2012 to 2022 to examine the effects and mechanisms of environmental management system certification on corporate ESG greenwashing within the double machine learning framework. The empirical results reveal that: (1) Environmental management system certification significantly suppresses corporate ESG greenwashing, and this finding holds consistently across various endogeneity and robustness tests. (2) Mechanism analysis indicates that environmental management system certification can affect firms' internal governance and external stakeholder attention, thereby constraining earnings management, enhancing stakeholder supervision, and reducing inefficient investment, thus mitigating corporate ESG greenwashing. (3) Heterogeneity analysis suggests that the impact of environmental management system certification in curbing ESG greenwashing is more pronounced for small-scale firms, private firms, and firms in clean industries.
期刊介绍:
Energy Economics is a field journal that focuses on energy economics and energy finance. It covers various themes including the exploitation, conversion, and use of energy, markets for energy commodities and derivatives, regulation and taxation, forecasting, environment and climate, international trade, development, and monetary policy. The journal welcomes contributions that utilize diverse methods such as experiments, surveys, econometrics, decomposition, simulation models, equilibrium models, optimization models, and analytical models. It publishes a combination of papers employing different methods to explore a wide range of topics. The journal's replication policy encourages the submission of replication studies, wherein researchers reproduce and extend the key results of original studies while explaining any differences. Energy Economics is indexed and abstracted in several databases including Environmental Abstracts, Fuel and Energy Abstracts, Social Sciences Citation Index, GEOBASE, Social & Behavioral Sciences, Journal of Economic Literature, INSPEC, and more.