The environmental Kuznets Curve and renewable energy in East Africa 1994 to 2022 a panel analysis

This study examines the relationships among economic growth, carbon emissions, renewable energy, and forest dynamics in East Africa using a balanced panel of eight countries over 29 years (1994–2022), yielding 232 observations. Missing values were imputed using linear interpolation separately by country and variable to produce a complete balanced panel. The Environmental Kuznets Curve (EKC) hypothesis is tested using fixed-effects, system GMM, and decoupling elasticity estimations. The Lind–Mehlum test for an inverted U-shape rejects the null of monotonicity at the 5% level (t = 1.95, p = 0.029), providing formal support for the EKC. The results provide conditional evidence of an inverted U-shaped relationship between GDP per capita and CO₂ emissions in fixed-effects models, with a turning point of approximately 2,846 USD (95% CI: 2,100–4,200). However, the wide confidence interval indicates substantial uncertainty, and the evidence is not robust across all specifications. Renewable energy consumption is negatively associated with emissions (β = −0.018, p < 0.01), but this coefficient should be interpreted cautiously because WDI data classify traditional biomass as renewable; sensitivity analysis excluding biomass-dominated countries yields a larger coefficient (β = −0.026, p < 0.01), suggesting that the aggregate coefficient understates the association with modern renewables. Decoupling analysis reveals heterogeneous country-level elasticities ranging from − 0.42 (Ethiopia) to 0.79 (Kenya). System GMM estimates indicate significant emissions persistence (ρ = 0.58, p < 0.01), which is consistent with but does not prove carbon lock-in. These findings provide partial, model-dependent support for the EKC hypothesis in East Africa. Policy implications include targeted modern renewable energy investments, forest carbon stock governance reforms, and development strategies tailored to country-specific decoupling patterns. Clinical trial number: Not applicable.