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Assessment of renewable electricity adoption in sub-Saharan Africa

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  • Iyabo Adeola Olanrele
  • José Alberto Fuinhas

Abstract

Most sub-Saharan African electricity generation is through renewable energy sources. However, the pace of renewable expansion is slow, mirrored by the region's low per capita electric power consumption and electricity access. The study examines the determinants of renewable electricity generation adoption in sub-Saharan Africa (SSA) countries using content description and a panel ARDL analysis. Findings from this study show that hydroelectric power is the long-standing renewable electricity source in the region. The deployment of non-hydro renewable electricity sources is slow despite its vast potential. In most evaluated countries, renewable electricity targets are below actual realization. Also, policies are ineffective in driving renewable electricity adoption, as indicated by the negative relationship between renewable electricity generation and policy enactments in SSA. Foreign direct investment and financial development significantly negatively impact renewable electricity adoption, suggesting that both factors do not expand renewable electricity generation. Feasible strategies for increasing non-hydro renewable electricity use include activating renewable energy support mechanisms and their uptake. In addition, governments in SSA should strengthen their legal and institutional frameworks and encourage lessening bottlenecks and bureaucracies associated with renewable electricity investment.

Suggested Citation

  • Iyabo Adeola Olanrele & José Alberto Fuinhas, 2024. "Assessment of renewable electricity adoption in sub-Saharan Africa," Energy & Environment, , vol. 35(2), pages 848-873, March.
    • Handle: RePEc:sae:engenv:v:35:y:2024:i:2:p:848-873
    DOI: 10.1177/0958305X221118878
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    Cited by:

    1. Yuanbo Hu & Weilun Huang & Aibi Dai & Xuemeng Zhao, 2024. "Determinants of Non-Hydro Renewable Energy Consumption in China’s Provincial Regions," Energies, MDPI, vol. 17(16), pages 1-43, August.
    2. Kanzari, Emna & Fazio, Gioacchino & Fricano, Stefano, 2024. "Analysing the energy landscape in Africa using cluster analysis: Drivers of renewable energy development," Energy Policy, Elsevier, vol. 195(C).

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    Keywords

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    JEL classification:

    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
    • Q42 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Alternative Energy Sources
    • Q48 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Government Policy
    • R58 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Regional Government Analysis - - - Regional Development Planning and Policy

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