Water disclosure and firm risk: Empirical evidence from highly water‐sensitive industries in China
journal contributionposted on 05.07.2019, 14:32 by Huixiang Zeng, Tao Zhang, Zhifang Zhou, Yang Zhao, Xiaohong Chen
In this paper, we examine the relationship between water disclosure and firm risk. Specifically, based upon a panel dataset of 334 Chinese listed firms operating in highly water‐sensitive industries during 2010–2015, we use regression models to analyze the relationships between water disclosure and three types of firm risk (i.e., total risk, systematic risk, and idiosyncratic risk) and the moderating effects of media coverage on these relationships. Our empirical results show that (a) although there are no significant relationships between water disclosure and total risk and idiosyncratic risk, there is a significant negative relationship between water disclosure and systematic risk; (b) negative media coverage weakens the negative relationship between water disclosure and systematic risk, whereas nonnegative media coverage reinforces this negative relationship. Our cornerstone study examines the effect of a specific type of environmental disclosure (i.e., water disclosure) on firm risk, and our empirical findings are different from previous studies, which examined the effects of overall corporate social responsibility (CSR) disclosure on firm risk. We analyze the causes of the differences in detail. With this study, we make theoretical, empirical, and managerial contributions to CSR disclosure–firm risk research in business ethics literature.
Innovation Driven Program of Central South University, Grant/Award Number: 2015CX010; the Major Program of the National Social Science Foundation of China, Grant/Award Numbers: 11&ZD166 and 15ZDA020; the National Natural Science Foundation of China, Grant/Award Number: 71303263; the Research and Innovation Project for Postgraduates in Hunan Province of China, Grant/Award Number: CX2016B036; the State Key Program of the National Natural Science Foundation of China, Grant/Award Number: 71431006; the Project of Social Science Foundation in Hunan Province of China, Grant/Award Number: 18YBQ130.
- Loughborough University London