Renewable energy plays a pivotal role in achieving the SDGs, particularly SDG 7 and SDG 13, by driving the transition toward a greener, more resilient economy. Thus, the current study explores the drivers of renewable energy consumption in the United States from 1980Q1 to 2022Q4. Utilising the novel multivariate wavelet quantile regression framework, the study explores these dynamics, allowing for a more comprehensive analysis by capturing the impact of the independent variable on the dependent variable while simultaneously accounting for the effects of other covariates. Furthermore, the study employed wavelet quantile co-integration to capture the long-run association across different quantiles and frequency bands. The findings reveal that inflation consistently reduces the use of renewable energy across all quantiles and time scales, with the strongest effects at higher consumption levels in the short run. While technological innovation and financial globalisation exhibit a positive but heterogeneous impact, especially at higher quantiles in the medium to long term, financial development displays mixed effects depending on the distributional characteristics. These findings highlight the importance of tailored policy tools and recommend inflation-indexed subsidies, targeted green finance mechanisms, and regulatory reforms that align international capital flows with clean energy goals. This study not only introduces a robust analytical approach but also contributes actionable insights into designing dynamic, distributionally sensitive renewable energy policies.
Adebayo et al. (Tue,) studied this question.
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