From Hydropower Diffusion to Its Determinants: An Analysis of Innovation Diffusion Parameters Using Country-Level Indicators

Hydropower remains one of the most important renewable energy sources worldwide, yet its long-term development has followed different trajectories across countries. This thesis examines long-term hydropower diffusion across 51 countries over the period 1965--2024 by combining innovation diffusion modeling with country-level explanatory analysis. In the first stage, the Bass diffusion model is fitted to national hydropower generation trajectories to estimate the innovation coefficient (p), imitation coefficient (q), and market-potential parameter (m). While m describes the fitted scale of each country's hydropower trajectory, the subsequent analysis focuses on p and q as indicators of innovation-driven and imitation-driven diffusion dynamics. The estimated diffusion parameters are linked to a consolidated dataset of economic, social, environmental, climatic, energy-related, institutional, and technological indicators. Bivariate analysis, Ordinary Least Squares (OLS) regression with HC3 inference, Akaike Information Criterion (AIC) comparison, Elastic Net stability checks, Explainable Boosting Machine (EBM) models, and Leave-One-Out Cross-Validation (LOOCV) are used to evaluate which indicators remain informative across model specifications. The results show moderate but consistent explanatory patterns. The innovation coefficient p is most robustly associated with institutional quality, technological capacity, and economic development, especially the Worldwide Governance Indicators (WGI), Patent Applications, and GDP. The imitation coefficient q is more strongly associated with demographic and development-gradient variables, especially higher Population Growth and lower GDP and WGI, with additional evidence for CO₂ Emissions in selected specifications. Overall, the findings suggest that hydropower diffusion cannot be explained only by physical resource availability or fitted market potential. Cross-country differences in diffusion dynamics are also linked to broader institutional, technological, economic, demographic, and energy-system conditions. The results provide a structured empirical framework for connecting Bass diffusion parameters with country-level indicators in the study of renewable energy technology diffusion.