ISETS Working Papers

ISETS Working Paper No. 22-0005

The impacts of climate policy uncertainty on the volatility and tail dependence of Chinese and US stock markets

Xin Xu, Shupei Huang, Brian M. Lucey, Haizhong An

Abstract: This paper measures China’s daily and monthly climate policy uncertainty (CPU) from Jan 2000 to Mar 2022 based on Chinese news data for the first time. Then, the nonlinear and lag impacts of the US CPU and China’s CPU on stock market volatilities in both countries are investigated by using GARCH (1,1) and the distribution lag nonlinear model (DLNM), respectively. Furthermore, the changes in mean correlation and low tail dependence between Chinese and US stock market volatilities caused by CPUs also are compared by adopting the copula function and DLNM method. The stock market data include the Shanghai Composite Index (SSCI) and NASDAQ from Jan 2000 to Mar 2022 from the Choice database, and the Shenzhen Composite Index (SCI) and S&P 500 are used for the robustness test. The empirical results indicate that (1) the growth trend of China’s CPU index is similar to that of the US. However, there are significant differences between the impacts of these two CPUs on the volatility, correlation and tail dependence of stock markets. (2) For China, only high climate policy uncertainty could increase stock volatility in the current period and reduce the low tail dependence, and the higher the CPU is, the stronger the reduction effect. Beyond that, this effect requires a lag of more than approximately two months to be observed. (3) For the US, under a low CPU level, lags of approximately two and six months increase stock market volatility. For a high CPU level, the effect diminishes to zero after a lag of more than 6 months. CPU does not improve the low tail correlation of Chinese and US stock market volatilities in the current period, but it has a significant positive effect after more than 2 months.