Climate Change Concerns and the Performance of Green vs. Brown Stocks

被引:197
作者
Ardia, David [1 ,2 ]
Bluteau, Keven [3 ]
Boudt, Kris [4 ,5 ,6 ]
Inghelbrecht, Koen [5 ]
机构
[1] Ecole Hautes Etud Commerciales HEC Montreal, Grp Etud & Rech Anal Decis GERAD, Montreal, PQ H3T 2A7, Canada
[2] Ecole Hautes Etud Commerciales HEC Montreal, Dept Decis Sci, Montreal, PQ H3T 2A7, Canada
[3] Univ Sherbrooke, Dept Finance, Sherbrooke, PQ J1K 2R1, Canada
[4] Vrije Univ Brussel, Solvay Business Sch, B-1050 Brussels, Belgium
[5] Univ Ghent, Dept Econ, B-9000 Ghent, Belgium
[6] Vrije Univ Amsterdam, Sch Business & Econ, NL-1081 Amsterdam, Netherlands
基金
加拿大自然科学与工程研究理事会;
关键词
asset pricing; climate change; sustainable investing; ESG; greenhouse gas emissions; sentometrics; textual analysis; MEDIA; NEWS;
D O I
10.1287/mnsc.2022.4636
中图分类号
C93 [管理学];
学科分类号
12 ; 1201 ; 1202 ; 120202 ;
摘要
We empirically test the prediction of Pa ' stor et al. (2021) that green firms outperform brown firms when concerns about climate change increase unexpectedly, using data for S&P 500 companies from January 2010 to June 2018. To capture unexpected increases in climate change concerns, we construct a daily Media Climate Change Concerns index using news about climate change published by major U.S. newspapers and newswires. We find that on days with an unexpected increase in climate change concerns, the green firms' stock prices tend to increase, whereas brown firms' prices decrease. Furthermore, using topic modeling, we conclude that this effect holds for concerns about both transition and physical climate change risk. Finally, we decompose returns into cash flow and discount rate news components and find that an unexpected increase in climate change concerns is associated with an increase (decrease) in the discount rate of brown (green) firms.
引用
收藏
页码:7607 / 7632
页数:27
相关论文
共 61 条
[1]  
Alekseev G, 2022, QUANTITY BASED APPRO
[2]  
[Anonymous], Guide for supervisors, integrating climate-related and environmental risks into prudential supervision
[3]   Questioning the news about economic growth: Sparse forecasting using thousands of news-based sentiment values [J].
Ardia, David ;
Bluteau, Keven ;
Boudt, Kris .
INTERNATIONAL JOURNAL OF FORECASTING, 2019, 35 (04) :1370-1386
[4]   Flights to Safety [J].
Baele, Lieven ;
Bekaert, Geert ;
Inghelbrecht, Koen ;
Wei, Min .
REVIEW OF FINANCIAL STUDIES, 2020, 33 (02) :689-746
[5]   Measuring Economic Policy Uncertainty [J].
Baker, Scott R. ;
Bloom, Nicholas ;
Davis, Steven J. .
QUARTERLY JOURNAL OF ECONOMICS, 2016, 131 (04) :1593-1636
[6]  
Ballinari D, 2021, PREPRINT, DOI [10.2139/ssrn.3964819, DOI 10.2139/SSRN.3964819]
[7]   DEPENDENCY MODEL OF MASS-MEDIA EFFECTS [J].
BALLROKEACH, SJ ;
DEFLEUR, ML .
COMMUNICATION RESEARCH, 1976, 3 (01) :3-21
[8]   Socially Responsible Investing in Good and Bad Times [J].
Bansal, Ravi ;
Wu, Di ;
Yaron, Amir .
REVIEW OF FINANCIAL STUDIES, 2022, 35 (04) :2067-2099
[9]   Aggregate Confusion: The Divergence of ESG Ratings* [J].
Berg, Florian ;
Kolbel, Julian F. ;
Rigobon, Roberto .
REVIEW OF FINANCE, 2022, 26 (06) :1315-1344
[10]  
Bertolotti A., 2019, Climate risk in the US electric utility sector: a case study, DOI 10.2139/ssrn.3347746