Does climate risk affect the performance of companies in China?

大洪水 中国 台风 气象灾害 业务 山崩 气候变化 极端天气 财务 地理 气象学 农业 工程类 地质学 海洋学 岩土工程 考古
作者
Kun Guo,Liyuan Luan,Dayong Zhang,Qiang Ji
出处
期刊:Applied Economics Letters [Informa]
卷期号:: 1-7 被引量:2
标识
DOI:10.1080/13504851.2023.2289899
摘要

ABSTRACTClimate change has become the greatest challenge for humanity in the 21st century, and extreme climate risks not only cause substantial direct economic losses, but also affect the operations of micro-enterprises. Based on financial data for Chinese A-share listed companies and meteorological disaster-loss data, this study found that comprehensive meteorological disaster losses significantly reduce firm performance, with rainstorm induced flood (landslide and mud-rock flow) disasters, drought disasters, gale, hail and lightning disasters being the most obvious. Further analysis showed that underperforming and smaller companies are more affected by meteorological disasters and that companies with diversified business operations and more managerial climate attention are less affected by meteorological disasters.KEYWORDS: Climate riskmeteorological disasterbusiness performancediversificationJEL CLASSIFICATION: G30Q27Q54 Disclosure statementNo potential conflict of interest was reported by the author(s).Notes1 Eckstein, David, Vera Künzel, and Laura Schäfer. 2022. GLOBAL CLIMATE RISK INDEX 2021. Germanwatch e.V.2 In the text, meteorological disasters include five types of disasters: drought disasters; rainstorm induced flood (landslide and mud-rock flow) disasters; low-temperature and frost disasters; gale, hail and lightning disasters and typhoon disasters.3 In China, the location of the company’s operations and the location of its registration are basically adjacent to each other, so we focus on the climate risk of the location of the company’s registration, following the practice of Pirinsky and Wang (Citation2006). ST companies (companies with delisting risk for three or more consecutive years) with abnormal financial conditions and the financial sector are removed, together with 1% tailing of data containing outliers. Enterprise-level data are from the Wind database, and meteorological disaster-related data are from the China Meteorological Disaster Statistical Yearbook.Additional informationFundingThe work was supported by the National Natural Science Foundation of China [71974159, 71974181, 72022020, 72348003].
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