The term environmental, social and governance (ESG) has gained momentum in recent years. Thus, understanding its underlying driving mechanisms has become increasingly intriguing. In this study, we examine the effects of economic policy uncertainty (EPU), climate policy uncertainty (CPU) and geopolitical risk (GPR) on firms’ ESG disclosure.
To achieve the paper’s goal, we use the mixed data sampling (MIDAS) regression model on a sample of 500 firms from the US stock market.
The results indicate that EPU and GPR have significant adverse effects on ESG performance, whereas the CPU index exhibits a positive impact. However, the significant associations of CPU and GPR with ESG score observed in the whole sample do not hold consistently across industries. This suggests that, while overarching trends might exist, individual sector characteristics and varying external influences can shape the relationship between uncertainty factors and ESG performance. This highlights the importance of context when analyzing ESG practices across different industries. Furthermore, we identified a range of influential financial parameters that drive ESG practices.
The findings of our study have significant implications for many parties including policymakers, managers, governments, investors and shareholders. Additionally, sector-specific policies may be needed to encourage sustainable practices, particularly in industries sensitive to environmental and geopolitical risks.
The paper’s originality lies in its examination of the combined impact of EPU, CPU, and GPR on ESG disclosure – a relationship rarely explored in existing literature. Using the MIDAS model, it provides a more refined analysis by integrating both high- and low-frequency data. The study also offers industry-specific insights, revealing how these external uncertainties affect ESG disclosure differently across sectors. By incorporating financial drivers and offering policy implications, this research presents a novel and comprehensive approach to understanding ESG disclosure under increasing global uncertainties.
