Re‐Assessing Environmental Sustainability in Africa: Accounting for Synergy and Heterogeneity in the Relationship Between Renewable Energy and Democracy

ABSTRACT

Mitigating the ecological footprint is essential for attaining global environmental sustainability, driving significant research into the factors that shape this broad measure of human demand on natural resources. Although previous studies have identified multiple determinants of ecological footprint, the combined effects and potential synergy between democratic governance and renewable energy consumption (REC) remain underexplored. This study fills this gap by investigating how democratic institutions and renewable energy adoption together influence ecological footprint across 31 African nations from 1996 to 2024, employing Driscoll‐Kraay standard errors, IV‐GMM estimators, and panel causality tests. Results reveal that renewable energy consumption significantly reduces ecological footprint, while democracy's direct effect is conditional: it is positive at low renewable penetration but turns negative as clean energy expands. The central contribution is a negative and significant interaction term, indicating that democratic institutions enhance the environmental benefits of renewable energy. At the highest democracy levels, a 1% increase in renewable energy reduces the footprint by approximately 0.50%, compared to only 0.12% at the lowest democracy levels—a fourfold amplification. The Environmental Kuznets Curve hypothesis is validated by a turning point at a GDP per capita by approximately $11,850 GDP, where most African nations remain on the upward slope. A bidirectional causality links renewable energy and ecological footprint is found. These findings imply that simultaneous investment in renewable infrastructure and democratic governance is essential, with renewable expansion requirements varying depending on institutional quality. Policy strategies should therefore couple clean energy deployment with transparency and accountability mechanisms to maximise environmental returns.