The Relationship between Climate Risk, Climate Policy Uncertainty, and CO2 Emissions : Empirical Evidence from the US

This paper examines the relationship between climate risk and climate policy uncertainty and CO2 emissions in the US, with an aim to contribute to the better understanding of the drivers of emissions. We proxy for climate risk using the cost of natural disasters, and for policy uncertainty the Climate Policy Uncertainty (CPU) Index of Gavriilidis (2021). For the empirical analysis we employ a structural FactorAugmented Vector AutoRegression (FAVAR) model with a two-step principal component analysis, using a balanced panel of 117 monthly variables, to capture US economic conditions for the period 2000 to 2022. The results indicate that a significant percentage of the variance of CO2 emissions in the US, is explained by Natural Disasters Cost, which also seem to account for a significant percentage of the US Total Renewable Energy Consumption variance. Shocks to disaster costs seem to decrease all type of emissions significantly and also increase renewable energy use significantly. The occurrence of natural disasters increases the political disagreement among U.S. politicians, as well as, the climate policy uncertainty, highlighting the need for efficient policymaking and regulations. When we replace the climate risk proxies with the CPU Index, results are qualitatively similar; in addition, there is a strong impact of CPU on US Total Renewable Energy Consumption. In further results, we find that an increase in Partisan Conflict decreases emissions and explains a significant amount of renewable energy variance