Assessing the impact of nuclear energy on load capacity, economic growth, and innovation: A quantile-on-quantile analysis for Finland

This study explores the complex relationships between nuclear energy consumption, load capacity factor, economic growth, and innovation in Finland during 1990–2022 by employing a Quantile-on-Quantile (QQ) regression approach complemented by Kernel-based Regularized Least Squares (KRLS) estimation. The QQ method allows for a detailed analysis of how different quantiles of explanatory variables influence various quantiles of nuclear energy consumption, thus capturing nonlinear and asymmetric dependencies that traditional models often overlook. The findings indicate that GDP exerts the strongest and most consistent positive impact on nuclear energy use, particularly in higher quantiles, while the load capacity factor also shows a positive, albeit more heterogeneous, influence. In contrast, patent applications exert a limited and statistically insignificant effect across most quantile combinations. The KRLS model confirms these results, highlighting GDP as the dominant driver of nuclear energy consumption, followed by infrastructure efficiency, with innovation playing a marginal role. The study contributes to energy policy discourse by demonstrating that nuclear energy's role in the energy mix is highly contingent on economic performance and system efficiency, and only weakly linked to aggregate innovation activity. These insights are especially relevant for advanced economies aiming to optimize their low-carbon energy strategies under varying economic and technological conditions.