Renewable electricity generation proposed pathways for the US and China

Bismark Ameyaw, Yao Li, Yongkai Ma, Joy Korang Agyeman, Jamal Appiah-Kubi and Augustine Annan

Renewable Energy, 2021, vol. 170, issue C, 212-223

Abstract: In this study, we investigate the direction of the causal relationship between renewable electricity generation (REG) and economic growth for the US and China. The results show a unidirectional causality running from REG to economic growth for the US and China. Furthermore, a bi-directional long short-term (Bi-LSTM) algorithm is formulated to propose REG pathways based on four scenarios. First, we allow the Bi-LSTM network to make business-as-usual (BAU) predictions. The results show that the US and China’s REG as a percentage of total electricity output will hit ∼17.769 and ∼34.688 by 2030, respectively. Second, we set a 30% incremental target and estimate that the US and China REG will hit ∼17.198 and ∼31.105 by 2030, respectively. Third, the results from setting an incremental target of 50% depicts that the US and China REG will hit ∼19.844 and ∼35.891 by 2030, respectively. Finally, the 100% incremental target from the 2015 generation shows that the US and China REG are expected to hit ∼26.458 and ∼47.854 by 2030, respectively. As a policy implication, if investments in renewable electricity generation are not intensified, the US and China stand a risk of not meeting the pathway targets proposed.

Keywords: Renewable electricity generation; Bi-directional long short-term memory; Forecasting; Forecast evaluation; Economic growth (search for similar items in EconPapers)
Date: 2021
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Citations: View citations in EconPapers (6)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:renene:v:170:y:2021:i:c:p:212-223

DOI: 10.1016/j.renene.2021.01.119

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