撞车
溢出效应
业务
公司治理
库存(枪支)
计量经济学
边距(机器学习)
精算学
经济
财务
工程类
计算机科学
微观经济学
机械工程
机器学习
程序设计语言
作者
Linyu Wang,Yifan Ji,Zhongxin Ni
标识
DOI:10.1016/j.irfa.2023.102768
摘要
This study measures the static and dynamic crash risk connections across ESG networks from 2015 to 2020, using the generalized vector autoregressive framework. In particular, it highlights the mixed results of the crash risk connections across ESG three pillars and the different spillover performance when firms with different ownership structures and qualification of margin-trading and short-selling. Our results reveal that stocks with higher ESG ratings display more negative net spillover effects, which is consistent with the ideas that stock groups with good ESG performance experience lower crash risk, and thus transmitting smaller crash risk to other ESG levels. Among the three ESG pillars, good social performance (S) significantly lowers the total crash risk connections. In contrast, firms with well environment performance (E) do not transmit lower crash risk. Moreover, SOEs and firms with qualification of margin-trading and short-selling have lower total crash risk connections among ESG ratings. Using propensity score matching to match companies with high ESG and low ESG quarterly, we find the results are still robust. When dividing the sample according to the outbreak of COVID-19, we find the crash risk connections across ESG networks are stronger during crisis.
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