ERN: Other Econometrics: Applied Econometric Modeling in Microeconomics - Microeconometric Models of the Environment (Topic)最新文献

{"title":"Climate Regulatory Risks and Corporate Bonds","authors":"Leon E. Seltzer, L. Starks, Qifei Zhu","doi":"10.2139/ssrn.3563271","DOIUrl":"https://doi.org/10.2139/ssrn.3563271","url":null,"abstract":"Examining how climate and other environmental regulatory risks affect bond risk and pricing, we find that bond credit ratings and yield spreads appear to be influenced by a firm's environmental performance along with its regulatory conditions. Firms with poor environmental profiles tend to have lower credit ratings and higher yield spreads, particularly when the firm is located in a state with more stringent environmental regulations. Using the Paris Agreement as a shock to expected climate regulation, we provide evidence of a causal relation between climate regulatory risks and the credit ratings and yield spreads of bonds with problematic environmental profiles.","PeriodicalId":318600,"journal":{"name":"ERN: Other Econometrics: Applied Econometric Modeling in Microeconomics - Microeconometric Models of the Environment (Topic)","volume":"109 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-03-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124670908","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The Mist of Corporate Innovation","authors":"Xuechen Gao, Jinbo Luo","doi":"10.2139/ssrn.3610439","DOIUrl":"https://doi.org/10.2139/ssrn.3610439","url":null,"abstract":"This study investigates the impact of air pollution on corporate innovation. Using the satellite generated Particulate Matter 2.5 concentration data in 390 cities in China over the period of 2000-2015, we find that severe air pollution (haze pollution) in a region may deteriorate the innovative performance of companies in the same region. Our results are robust to different air pollution and innovation measures. We employ an instrument variable approach to alleviate potential endogeneity concerns. In addition, we identify two possible mechanisms, reduced funds availability and loss of innovative talents, to explain the negative impact of air pollution on innovation.","PeriodicalId":318600,"journal":{"name":"ERN: Other Econometrics: Applied Econometric Modeling in Microeconomics - Microeconometric Models of the Environment (Topic)","volume":"77 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-01-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124693938","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"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":"https://doi.org/10.2139/ssrn.3226286","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":0.0,"publicationDate":"2018-08-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114574749","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Supply Response of Corn Farmers in Quebec: Analyzing the Impact of Prices Volatility?","authors":"Bahareh Mosadegh Sedghy, L. Tamini, Rémy Lambert","doi":"10.2139/ssrn.3265470","DOIUrl":"https://doi.org/10.2139/ssrn.3265470","url":null,"abstract":"This study examines the supply response and the effect of price predictability of corn in the province of Quebec. A generalized autoregressive conditional heteroskedasticity (GARCH) process is used to model output price expectations and its volatility. The empirical results show that price predictability has a positive effect on producersO decisions. Estimation of supply elasticity illustrates that expected output price is the most important risk factor for corn producers in Quebec.As expected, we found that the Farm Income Stabilization Insurance (ASRA) in Quebec leads producers to be more sensitive to effective prices than to market prices. Our results also show that application of this program causes less sensitivity to input prices than to output prices. Reducing producersO risk aversion is another implication of this program.","PeriodicalId":318600,"journal":{"name":"ERN: Other Econometrics: Applied Econometric Modeling in Microeconomics - Microeconometric Models of the Environment (Topic)","volume":"45 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127181066","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Econometric Information Recovery in Behavioral Networks","authors":"G. Judge","doi":"10.2139/ssrn.2827776","DOIUrl":"https://doi.org/10.2139/ssrn.2827776","url":null,"abstract":"In this paper, we suggest an approach to recovering behavior-related, preference-choice network information from observational data. We model the process as a self-organized behavior based random exponential network-graph system. To address the unknown nature of the sampling model in recovering behavior related network information, we use the Cressie-Read (CR) family of divergence measures and the corresponding information theoretic entropy basis, for estimation, inference, model evaluation, and prediction. Examples are included to clarify how entropy based information theoretic methods are directly applicable to recovering the behavioral network probabilities in this fundamentally underdetermined ill posed inverse recovery problem.","PeriodicalId":318600,"journal":{"name":"ERN: Other Econometrics: Applied Econometric Modeling in Microeconomics - Microeconometric Models of the Environment (Topic)","volume":"10 6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-08-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132671106","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}