Impact of climate change on dynamic tail-risk connectedness among stock market social sectors: Evidence from the US, Europe, and China

Abstract

This paper studies the impact of climate change risk (including physical and transition risk) on the tail-risk connectedness among ten stock market social sectors in the US, Europe and China. To this end, we first combine ARMA-GJR-GARCH models with a time-varying parameter autoregression (TVP-VAR) approach to examine the transmission of tail-risk among sectors. Then, we use predictive regression models to examine the contribution of climate change to tail-risk spillovers. Over the sample period from January 2013 to September 2023, we obtain two main results. First, the COVID-19 epidemic has resulted in significantly greater losses for social sectors in the US and Europe than for those in China. Additionally, the industrial sector is a common source of tail-risk shocks across all three economies. Second, physical risk contributes to higher overall and directional tail-risk connectedness, while an increase in transition risk has the opposite effect on both. However, the impact of physical and transition risk on the net tail-risk connectedness for each sector shows both positive and negative effects. Our findings indicate that physical and transition risk have different effects on tail-risk connectedness among social sectors.