Nonlinear effects of financial development on energy infrastructure: Insights from nonlinear panel models

This study examines the impact of financial development on energy infrastructure needs in a sample of 85 countries over the period 2000–2023. The analysis combines linear panel estimators with advanced nonlinear methods, including Method of Moments Quantile Regression (MMQR), the Instrumental-Variable Partially Linear Functional-Coefficient model (IVPLFC), and the dose–response function. These methods allow us to examine heterogeneity, dynamic persistence, and nonlinear marginal effects. A key contribution of the study is the use of the Energy Infrastructure Needs index, which captures deficiencies across electricity generation, transmission, distribution, and storage, rather than relying on narrower traditional proxies. The results show that stronger financial development significantly reduces energy infrastructure needs. This effect is strongest at earlier stages of financial development, while diminishing marginal effects emerge as financial systems mature. The MMQR results reveal distributional differences across levels of energy infrastructure needs, while the IVPLFC and dose–response results confirm clear nonlinear effects. Overall, the findings show that financial development plays an important but uneven role in reducing energy infrastructure needs. Financially underdeveloped economies benefit most from expanding access to credit, strengthening banking intermediation, and improving liquidity, whereas more financially developed economies require complementary institutional and regulatory reforms to achieve further progress. © 2026 The Authors.