{"title":"中国环境违法行为:长期影响评估与未来违法行为预测","authors":"C. Lo, Christopher S. Tang, Yi Zhou","doi":"10.2139/ssrn.3226286","DOIUrl":null,"url":null,"abstract":"We take a business analytic approach to examine ways to reduce environmental incidents committed by Chinese manufacturers. We first perform descriptive analysis to examine the long-term impact of environmental incidents on a firm’s performance that is measured in terms of Returns On Assets (ROA). By considering all 1542 environmental incidents occurred between 2004 and 2013 committed by 418 public Chinese manufacturing firms listed on Shanghai/Shenzhen Stock Exchange, we find empirical evidence that, relative to comparable firms without (any exposed) environmental incidents, firms with (exposed) environmental incidents have a lower ROA in consecutive years “only after” they were exposed. Despite the negative financial returns for being exposed, we speculate that low probability of being selected for inspection can be one of the key reasons for unethical Chinese manufacturers to violate environmental regulations. This speculation motivates us to use publicly available financial data to identify factors (e.g., age of the firm, total assets, percentage of government ownership, past environmental incidents) that one can use to predict which firm is more likely to violate environmental regulations. By using our training samples (from 2004-2012), we first develop our predictive model. Then we develop a scoring system to characterize the likelihood of a Chinese firm violating environmental regulations in 2013. By using these risk scores, we show the government can expose over 71% of the environmental violations in 2013 by inspecting only 21.5% of the firms with risk scores above the top 80 percentile. Therefore, our analytical approach has the potential to be used as a building block for the Chinese government to develop a more effective mechanism to select firms for inspection to expose non-compliance firms. With a higher chance of getting caught along with a harsher penalty imposed by the Chinese government since 2014, the number of environmental incidents in China is more likely to decline.","PeriodicalId":318600,"journal":{"name":"ERN: Other Econometrics: Applied Econometric Modeling in Microeconomics - Microeconometric Models of the Environment (Topic)","volume":"215 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-08-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Environmental Violations in China: Evaluating Their Long-Term Impact and Predicting Future Violations\",\"authors\":\"C. Lo, Christopher S. Tang, Yi Zhou\",\"doi\":\"10.2139/ssrn.3226286\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"We take a business analytic approach to examine ways to reduce environmental incidents committed by Chinese manufacturers. We first perform descriptive analysis to examine the long-term impact of environmental incidents on a firm’s performance that is measured in terms of Returns On Assets (ROA). By considering all 1542 environmental incidents occurred between 2004 and 2013 committed by 418 public Chinese manufacturing firms listed on Shanghai/Shenzhen Stock Exchange, we find empirical evidence that, relative to comparable firms without (any exposed) environmental incidents, firms with (exposed) environmental incidents have a lower ROA in consecutive years “only after” they were exposed. Despite the negative financial returns for being exposed, we speculate that low probability of being selected for inspection can be one of the key reasons for unethical Chinese manufacturers to violate environmental regulations. This speculation motivates us to use publicly available financial data to identify factors (e.g., age of the firm, total assets, percentage of government ownership, past environmental incidents) that one can use to predict which firm is more likely to violate environmental regulations. By using our training samples (from 2004-2012), we first develop our predictive model. Then we develop a scoring system to characterize the likelihood of a Chinese firm violating environmental regulations in 2013. By using these risk scores, we show the government can expose over 71% of the environmental violations in 2013 by inspecting only 21.5% of the firms with risk scores above the top 80 percentile. Therefore, our analytical approach has the potential to be used as a building block for the Chinese government to develop a more effective mechanism to select firms for inspection to expose non-compliance firms. With a higher chance of getting caught along with a harsher penalty imposed by the Chinese government since 2014, the number of environmental incidents in China is more likely to decline.\",\"PeriodicalId\":318600,\"journal\":{\"name\":\"ERN: Other Econometrics: Applied Econometric Modeling in Microeconomics - Microeconometric Models of the Environment (Topic)\",\"volume\":\"215 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-08-04\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"ERN: Other Econometrics: Applied Econometric Modeling in Microeconomics - Microeconometric Models of the Environment (Topic)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.2139/ssrn.3226286\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"ERN: Other Econometrics: Applied Econometric Modeling in Microeconomics - Microeconometric Models of the Environment (Topic)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2139/ssrn.3226286","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Environmental Violations in China: Evaluating Their Long-Term Impact and Predicting Future Violations
We take a business analytic approach to examine ways to reduce environmental incidents committed by Chinese manufacturers. We first perform descriptive analysis to examine the long-term impact of environmental incidents on a firm’s performance that is measured in terms of Returns On Assets (ROA). By considering all 1542 environmental incidents occurred between 2004 and 2013 committed by 418 public Chinese manufacturing firms listed on Shanghai/Shenzhen Stock Exchange, we find empirical evidence that, relative to comparable firms without (any exposed) environmental incidents, firms with (exposed) environmental incidents have a lower ROA in consecutive years “only after” they were exposed. Despite the negative financial returns for being exposed, we speculate that low probability of being selected for inspection can be one of the key reasons for unethical Chinese manufacturers to violate environmental regulations. This speculation motivates us to use publicly available financial data to identify factors (e.g., age of the firm, total assets, percentage of government ownership, past environmental incidents) that one can use to predict which firm is more likely to violate environmental regulations. By using our training samples (from 2004-2012), we first develop our predictive model. Then we develop a scoring system to characterize the likelihood of a Chinese firm violating environmental regulations in 2013. By using these risk scores, we show the government can expose over 71% of the environmental violations in 2013 by inspecting only 21.5% of the firms with risk scores above the top 80 percentile. Therefore, our analytical approach has the potential to be used as a building block for the Chinese government to develop a more effective mechanism to select firms for inspection to expose non-compliance firms. With a higher chance of getting caught along with a harsher penalty imposed by the Chinese government since 2014, the number of environmental incidents in China is more likely to decline.