Demographic Aging and Energy Transition in Sub-Saharan Africa: A Macroeconomic Analysis of Access to Clean Cooking Fuels and Technologies

Although sub-Saharan Africa (SSA) is experiencing a rapid transformation on its population age structure while remaining the global epicenter of the deficit in access to clean cooking, the nexus between demographic aging and energy transition remains largely overlooked. This study analyzes this structural paradox by employing an unbalanced panel of 48 SSA countries over the period 2000–2024 (WDI). We identify two inseparable dimensions of this demographic shift: socio‑cultural inertia dimension, captured by the share of the population aged 65+ (l), and the budgetary constraint measured by the old‑age dependency ratio (). We implement the Lind & Mehlum (2010) test, introduce interaction terms with urbanization, and mobilize several robustness checks (Driscoll‑Kraay, bootstrap, IV-2SLS with lagged instruments and Lewbel (2012) internal instruments). We uncover a robust inverted U‑shaped relationship between demographic aging and the energy transition. Critical tipping points are identified: beyond 4.03% of seniors (65+) (or 8.35 seniors per 100 working‑age individuals), aging initially a catalyst of the energy transition, becomes a structural barrier. The study also reveals the role of urbanization, which, although the most powerful direct lever for clean cooking access, accelerates the downward phase of the curve. In the absence of anticipatory policies, the expected tripling of seniors by 2050 (from 34.5 to 98.4 million) could jeopardize SDG 7. The results withstand demanding robustness tests (Westerlund cointegration, Driscoll‑Kraay, bootstrap). Policies makers must implement modulated subsidies according to household composition, couple energy and social protection, and differentiate urban and rural strategies. This dataset contains the full replication files for the empirical analysis presented in the above study. It includes the final cleaned unbalanced panel dataset covering 48 sub-Saharan African countries over the period 2000–2024, extracted from the World Development Indicators (WDI, World Bank, 2025). The replication package also provides the complete Stata/R do-files/scripts required to reproduce all regression results, including the quadratic fixed-effects models (Table 5), interaction effects with urbanization (Table 7), robustness checks (Driscoll-Kraay, Bootstrap, Appendix Tables 6-7), the Lind & Mehlum (2010) U-test (Appendix Table 5), and all figures presented in the manuscript