The Nonlinear Nexus of Climate Policy Uncertainty and Renewable Energy Consumption in the United States of America: A Markov-Switching Approach

Abstract

We employ a Markov-Switching regression model using monthly US data from April 1987 to August 2022 to investigate the effect of climate policy uncertainty (CPU) on renewable energy consumption (REC). The main findings suggest the presence of a nonlinear relationship between CPU and REC. The baseline analysis using the CPU index reveals an adverse effect in regimes characterized by high levels of uncertainty. However, the effect is not statistically significant in a low uncertainty regime. To account for potential variations in the results, we perform a robustness analysis that considers the effect of CPU on REC, which may fluctuate based on the authorities' contextual perspectives (i.e., being in favor or against climate policy) and also the effect of CPU on REC by household. In addition, we incorporate a robustness check by utilizing the environmental policy uncertainty index developed by Noailly et al. (2022). The robustness test results confirm the results obtained from the baseline estimation.

Keywords

• Climate Policy Uncertainty, Environmental Policy Uncertainty, Renewable Energy Demand, Markov-Switching Regression