Climate policy uncertainty through production networks: Evidence from the stock market

Abstract

This thesis provides a deeper insight into quantifying the part of the production network in explaining spillovers of climate policy uncertainty (CPU) shocks to stock returns. By introducing world input–output data into the spatial vector autoregression (SAR) model, we distinguish the direct impact of CPU and the indirect impact occurring through the production network. The results show that more than 60 % of CPU’ effect on the stock market can be explained by the spillovers induced by the production network. In addition, the indirect effect is more obvious in the long term than in the short term.