Climate Policy Uncertainty and Its Implications for Non-Renewable Energy: A Dynamic Analysis of the US Economy Across Time and Quantiles

The US is the leading carbon emitter globally, and it has been confronting significant environmental issues. The fundamental reason behind these issues is massive non-renewable energy consumption. Therefore, energy management is required to curb environmental degradation. In order to reshape energy management policies, understanding the influencing factors of non-renewable energy is inevitable. Thus, the current study aims to explore the relationship between climate policy uncertainty and non-renewable energy consumption in the US by applying the novel wavelet quantile correlation framework. Additionally, using the augmented ARDL model, the study examines two transmission channels - energy pricing and clean technology - that link climate policy uncertainty to non-renewable energy consumption. For the core empirical analysis, a monthly time series dataset is used covering the period January 1990 to December 2019. The findings suggest that climate policy uncertainty initially decreases non-renewable energy consumption in the short run, but it also has a positive effect in the medium and long run. The analysis of transmission channels reveals that climate policy uncertainty can influence non-renewable energy consumption both positively, through the clean technology channel, and negatively, through the energy pricing channel. The findings from robustness analysis are consistent with baseline outcomes. As a result, the study recommends a set of policy implications, such as stabilizing climate policies in the US, protecting clean technology investments from fluctuations caused by CPU, potentially through mechanisms such as green bonds, loan guarantees, or tax incentives aimed at research and development in low-carbon technologies.