Mapping the Association Between Energy Use and ESG Dimensions: Evidence from Panel Econometrics, Clustering, and Machine Learning

This article examines the statistical relationships between ENUS, defined as per capita energy use, and Environmental, Social, and Governance variables, with particular emphasis on the Environmental dimension and its connections with national energy systems. The study investigates whether systematic associations exist between ESG indicators and the cross-country and temporal variation in ENUS as per capita energy use, and to what extent machine learning methods can contribute to the description and interpretation of these relationships in comparison with panel econometric models. The analysis is based on a large World Bank dataset covering approximately 161 countries over the period 2004–2023 and follows a three-step methodological strategy. First, fixed-effects, random-effects, and Weighted Least Squares panel models are estimated to explore the statistical associations between a broad set of ESG variables and ENUS as per capita energy use, while controlling for unobserved country-level heterogeneity. Second, clustering techniques are applied to identify groups of countries with similar joint patterns in multidimensional variables related to energy systems, emissions, climate conditions, and natural resource use. Third, several machine learning models are implemented, with particular attention to the performance of the K-Nearest Neighbors algorithm evaluated through normalized measures of predictive accuracy and goodness of fit. Model interpretability is enhanced using dropout loss and additive explanation methods to assess the contribution of ESG variables to the prediction of ENUS as per capita energy use. Overall, the results reveal a rich and multidimensional structure of relationships between ESG indicators and ENUS expressed as per capita energy use. In particular, the evidence indicates a close association between ENUS and key environmental variables such as emissions intensity, energy intensity as a control variable, and the use of natural resources, together with Social and Governance factors related to development, institutional quality, and economic structure. These findings suggest that cross-country differences in ENUS as per capita energy use correspond to distinct environmental, social, and governance profiles within the ESG framework.