Carbon emission trading system and stock price crash risk of heavily polluting listed companies in China: based on analyst coverage mechanism

Abstract

This study reveals the inconsistencies between the negative externalities of carbon emissions and the recognition condition of accounting statements. Hence, the study identifies that heavily polluting enterprises in China have severe off-balance sheet carbon reduction risks before implementing the carbon emission trading system (CETS). Through the staggered difference-in-difference (DID) model and the propensity score matching-DID model, the impact of CETS on reducing the risk of stock price crashes is examined using data from China’s A-share heavily polluting listed companies from 2007 to 2019. The results of this study are as follows: (1) CETS can significantly reduce the risk of stock price crashes for heavily polluting companies in the pilot areas. Specifically, CETS reduces the skewness (negative conditional skewness) and down-to-up volatility of the firm-specific weekly returns by 8.7% and 7.6%, respectively. (2) Heterogeneity analysis further shows that the impacts of CETS on the risk of stock price crashes are more significant for heavily polluting enterprises with the bear market condition, short-sighted management, and intensive air pollution. (3) Mechanism tests show that CETS can reduce analysts’ coverage of heavy polluters, reducing the risk of stock price crashes. This study reveals the role of CETS from the stock price crash risk perspective and helps to clarify the relationship between climatic risk and corporate financial risk.