Modeling the determinants of renewable energy consumption: Evidence from the five most populous nations in Africa

• Published in: Energy (Oxford) Vol. 206; p. 117992
• Main Authors: Akintande, Olalekan J., Olubusoye, Olusanya E., Adenikinju, Adeola F., Olanrewaju, Busayo T.
• Format: Journal Article
• Language: English
• Published: Oxford Elsevier Ltd 01.09.2020; Elsevier BV
• Subjects: Bayesian analysis; Bayesian Model Averaging (BMA); Bayesian theory; Carbon-dioxide emission; Climate change; Democratic Republic of the Congo; Egypt; Electric power; Electric power demand; Electric power generation; electricity; Electricity consumption; Electricity distribution; energy; Energy consumption; Energy demand; Energy security; energy use and consumption; Ethiopia; Five Most Populous African countries; Global warming; Human capital; macroeconomics; Nigeria; Organizational aspects; Population growth; Power consumption; Renewable energy; Renewable Energy Consumption; Renewable Energy Determinants; renewable energy sources; Renewable resources; Social factors; Socioeconomic factors; South Africa; uncertainty; urban population; Urban populations; Africa; South Africa; Democratic Republic of the Congo; Nigeria; Ethiopia; Egypt; Bayesian Model Averaging (BMA); Carbon-dioxide emission; Renewable Energy Consumption; Renewable Energy Determinants; Five Most Populous African countries
• ISSN: 0360-5442; 1873-6785
• DOI: 10.1016/j.energy.2020.117992

The increasing concern over global warming and energy security has rejuvenated the renewable energy option as the most vibrant option to sustaining future energy needs. This paper developed a renewable energy consumption model using annual data spanning between 1996 and 2016 in the five most populous countries (Ethiopia, South Africa, Nigeria, DR Congo, and Egypt) in Africa. Following the existing literature on the subject, the driving factors investigated were categorized into three broad areas. These include macroeconomic, socioeconomic, and institutional variables. Altogether, thirty-four predictor variables are analyzed. The study employed Bayesian Model Averaging (BMA) procedures to account for the uncertainty associated model choice and variable selection. The results of the analysis indicate that population growth, urban population, energy use, electric power consumption, human capital are the main determinants of renewable energy consumption in the selected countries. Also, an increase in any of these determinants (population growth, urban population, energy demand/use, electricity power demand/consumption) causes an increase in renewable energy consumption. •Investigate determinants of renewable energy consumption.•Employed Bayesian Model Averaging (BMA) procedures.•Key determinants are; urban population and growth.•As well as energy use, electricity consumption, human capital.•Increase in determinants cause increase in renewable consumption.