This study analyzes the interactions between various sources of energy generation and climate variables in Colombia, using Vector Autoregressive Models (VAR) and Generalized Additive Models (GAM). The main objective is to understand the dynamics and complementarity between fossil, hydroelectric, solar and wind energy sources, as well as their relationship with critical climate factors. The results of the VAR model reveal a strong interdependence between fossil and hydroelectric generation. Impulse-response functions show that a shock to fossil generation has a significant and sustained impact on hydropower generation and vice versa, highlighting the role of fossil generation as a backup during periods of water stress. Additionally, patterns of interdependence are observed between fossil generation and renewable sources, especially solar, which is beginning to have a more notable impact on fossil generation. GAM analysis complements these findings by providing a nonlinear perspective on the relationships between variables. Hydroelectric generation is found to be strongly influenced by fossil generation, with a significant negative relationship, suggesting that as hydroelectric generation increases, the need for fossil generation decreases. Furthermore, climatic variables such as solar radiation and water reserves have significant relationships with hydroelectric generation, underlining the dependence of the energy system on climatic conditions. Colombia's energy matrix depends 70 % on hydroelectric generation, which, although sustainable under normal conditions, can become critical during periods of drought. In such scenarios, fossil generation becomes an essential backup. The incorporation of non-conventional renewable energy sources, such as solar and wind, is crucial to diversify the energy matrix and improve the resilience of the system.

Electricity tariffs in emerging economies are often influenced by macroeconomic volatility and regulatory design, affecting both affordability and system stability. Understanding these interactions is crucial for anticipating price fluctuations and ensuring sustainable energy policy. This paper examines the influence of macroeconomic conditions on electricity tariff dynamics in Colombia by integrating econometric and machine learning approaches. Using monthly data from 2009 to 2024 and a set of 153 macroeconomic indicators condensed via principal component analysis (PCA), we assess the predictive performance of vector autoregressive (VAR), SARIMAX, and XGBoost models, as well as a hybrid VAR–XGBoost specification. Impulse-response analysis reveals that tariff components exhibit limited sensitivity to macroeconomic shocks, underscoring the buffering role of regulation and sector-specific drivers. However, forecasting exercises demonstrate that accuracy is highly component-specific: SARIMAX performs best for transmission and restrictions, and VAR dominates for distribution and losses, while the hybrid model outperforms for generation and commercialization. These findings highlight that although macroeconomic pass-through into tariffs is weak, hybrid approaches that combine structural econometric dynamics with nonlinear learning can deliver tangible forecasting gains. The study contributes to the literature on electricity pricing in emerging economies and offers practical insights for regulators and policymakers concerned with tariff predictability and energy affordability.

This study assesses energy productivity changes in 26 European countries from 2005 to 2019 using a Metafrontier Malmquist-Luenberger Productivity Index (MML), incorporating both desirable outputs and undesirable outputs. By distinguishing between European regions, the analysis reveals structural heterogeneity in energy transitions. The inclusion of energy poverty offers a more equitable framework to evaluate not only technical efficiency but also social performance. Results show mixed productivity trends: while some countries achieve efficiency and technological gains, others display stagnation or regression when equity dimensions are included. Eastern Europe, despite lower average productivity under the joint orientation (MML = 0.9899), demonstrates improvement when the focus shifts to energy poverty (MML = 1.0351), suggesting that equity-focused policies can yield meaningful outcomes even in less efficient systems. In contrast, Western Europe shows relatively lower productivity under the baseline joint orientation (MML = 0.9049), with only a slight improvement when energy poverty is prioritized (MML = 0.9164), highlighting persistent challenges in addressing distributive aspects despite stronger technological capabilities. Overall, the findings underscore the importance of integrating equity considerations into energy efficiency assessments, showing that technological progress alone does not guarantee socially inclusive energy transitions.