Improvements and Spatial Dependencies in Energy Transition Measures

Abstract

This article aims to improve one of the newest energy transition measures—the World Economic Forum WEF Energy Transition Index (ETI) and find its driving forces. This paper proposes a new approach to correct the ETI structure, i.e., sensitivity analysis, which allows assessing the accuracy of variable weights. Moreover, the novelty of the paper is the use the spatial error models to estimate determinants of the energy transition on different continents. The results show that ETI is unbalanced and includes many variables of marginal importance for the shape of the final ranking. The variables with the highest weights in ETI did not turn out to be its most important determinants, which means that they differentiate the analysed countries well; nonetheless, they do not have sufficient properties of approximating the values of the ETI components. The most important components of ETI (with the highest information load) belong to the CO2 emissions per capita, the innovative business environment, household electricity prices, or renewable capacity buildout. Moreover, we identified the clustering of both ETI and its two main pillars in Europe, which is not observed in America and Asia. The identified positive spatial effects showing that European countries need much deeper cooperation to reach a successful energy transition.