The relationship between renewable energy consumption and economic growth attracts scientific interest. However, empirical results remain inconclusive, particularly for Sub-Saharan Africa (SSA), largely reflecting unobserved cross-country structural heterogeneity inadequately captured by conventional estimation methods. This article applies a Finite Mixture Model (FMM) to 44 SSA countries over 1990-2021, integrating human capital as a concomitant variable. Endogenous classification identifies four latent energy regimes: two conservation regimes (Classes 1 and 3), where renewable energy consumption negatively affects growth (Class 1 = -0.0798 and Class 3 = -0.198); and two growth regimes (Class 2: 59.38% of countries and Class 4: 29.18% of countries), where renewable energy consumption significantly stimulates economic growth (Class 2 = 0.0245 and Class 4 = 0.0484). A complementary panel threshold regression identifies a single critical human capital threshold of 1.309, beyond which economies develop the absorptive capacity necessary to turn the energy transition into a driver of productivity gains and growth. Estimates show that control of corruption catalyses green growth in Class 4, whereas digitalisation initially entails detrimental adoption costs in fragile regimes. These findings challenge uniform energy policies and advocate differentiated transition strategies centred on strengthening technological absorption capacities.
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Ouema et al. (2026) studied this question.
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