The impact of climate policy uncertainty on tail risk of energy companies: Evidence from China

Abstract

Against the backdrop of the accelerated advancement of the "dual-carbon" goals, climate policy uncertainty (CPU) has emerged as a critical driver behind the evolution of extreme risks for energy enterprises. Accurately identifying its operational mechanisms holds significant strategic importance for safeguarding national energy security and facilitating green transformation. To unravel the intrinsic mechanisms and potential impacts through which CPU exacerbates extreme risks for energy enterprises, this study employs a two-way fixed effects model to systematically evaluate the pathways through which CPU affects the tail risks of energy enterprises, thereby providing a basis for risk early warning. Using Chinese energy-listed companies as the sample, with data spanning from April 2010 to December 2022, this paper measures the level of tail risks by applying the GARCH-VaR model. The findings reveal that CPU induces extreme risks for enterprises and significantly elevates their tail risk levels. Mechanism tests indicate that CPU increases enterprises' tail risks by undermining investor confidence and constraining corporate green innovation. Furthermore, the partial mediating role played by the level of corporate green innovation exhibits a "suppression effect." In addition, non-state-owned enterprises and those with high analyst attention are more vulnerable to the impact of CPU in terms of tail risks. There are also significant regional disparities in the impact of CPU on the tail risks of energy enterprises across eastern, central, and western China. The results of this study provide certain policy implications for addressing the impact of CPU and preventing extreme losses.