Is Non-Hydro Renewable Electricity Associated with Longer Life Expectancy? Quantile and Machine-Learning Evidence from Fifteen Leading Adopter Economies, 1990–2021

Replacing fossil-fuel combustion with renewable electricity is widely expected to lengthen lives, yet the evidence comes mainly from countries early in the energy transition. This study asks whether renewable penetration remains associated with longevity where the transition is advanced, using a balanced panel of the fifteen countries with the highest 2021 shares of non-hydro renewable electricity over the period 1990–2021. Because several regressors are integrated and not cointegrated, the principal specifications are estimated in first differences using two-way fixed effects with Driscoll–Kraay standard errors and Method of Moments Quantile Regression with a moving-block bootstrap that preserves cross-country dependence. Level specifications, mean-group estimators and panel-aware machine learning with out-of-fold SHAP attribution provide sensitivity evidence. We do not detect an association between renewable penetration and life expectancy: the first-difference estimate is small and insignificant (p = 0.379), the quantile estimates are flat across the distribution, and formal tests find no quantile gradient or high-penetration threshold. Significantly negative lagged level coefficients appear to be driven by the post-Soviet mortality crisis in Lithuania and Estonia; excluding those countries removes them. Several estimates are sensitive to sample composition, and naive persistence outperforms every machine-learning model out of time. The study does not detect domestic health co-benefits of further renewable deployment; given limited power and unmeasured pollution pathways, this is not evidence that such benefits are absent.