This paper introduces model uncertainty into the empirical study of the determinants of renewable energy generation at the regional level. The Bayesian Model Averaging (BMA) approach applied to the panel data of West African Economic and Monetary Union (WAEMU) countries, spanning the period of 1990–2017. The results suggest that, among the considered regressors, those reflecting countries’ socioeconomic and financial conditions as well as internal environmental prospects tend to receive high posterior inclusion probabilities. Then, the study explores the relationship between these regressors and renewable energy production by employing the Fully Modified Ordinary Least Squares (FMOLS) and Dynamic Ordinary Least Squares (DOLS) long-run estimators. The findings reveal that renewable energy consumption, real GDP per capita, investment in energy, urbanization, and unemployment spur renewable energy production, whereas CO2 emissions and energy imports inhibit renewable energy production. Findings from this study have important policy implications for WAEMU countries with regard to achieving the 7th objective of the Sustainable Development Goals (SDGs), which advocates the access to affordable, reliable, sustainable, and modern energy for all.
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Bayale et al. (2021) studied this question.
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