The dynamic relationship between climate policy uncertainty and renewable energy in the US: Applying the novel Fourier augmented autoregressive distributed lags approach

Renewable energy consumption is deemed imperative to attain higher economic growth without affecting environmental degradation. Hence, probing its influencing factors is an indispensable field of research in the literature on energy economics. The existing literature discerns several influencing factors of renewable energy consumption, however, the dynamic relationship between climate policy uncertainty and renewable energy consumption remains ignored. Hence, we probe the dynamic impact of climate policy uncertainty on renewable energy consumption. Using monthly dataset for the US, the findings from the novel Fourier augmented autoregressive distributed lag model reveal that climate policy uncertainty plunges renewable energy consumption across the long-and short-run. Finally, the study proposes to reduce the uncertainty in climate policies to upsurge renewable energy consumption.

Automated summary

Renewable energy consumption is crucial for sustainable economic growth and research on its influencing factors is essential in the field of energy economics. While previous studies have identified various factors, the dynamic relationship between climate policy uncertainty and renewable energy consumption has been overlooked. Therefore, this study investigates the impact of climate policy uncertainty on renewable energy consumption using a novel Fourier augmented autoregressive distributed lag model. The findings reveal that climate policy uncertainty significantly decreases renewable energy consumption in both the long and short-term. The study concludes by suggesting the reduction of uncertainty in climate policies to promote renewable energy consumption.