Affiliation:
1. Lum University Giuseppe Degennaro, Italy
Abstract
In this chapter, the authors investigate the role of “renewable energy consumption” in the context of circular economy. They assume that the consumption of renewable energy is a proxy for the development of circular economy. They use data from the environmental, social, and governance (ESG) dataset of the World Bank for 193 countries in the period 2011-2020. They perform several econometric techniques (i.e., panel data with fixed effects, panel data with random effects, pooled ordinary least squares [OLS], weighted least squares [WLS]). The results show that “renewable energy consumption” is positively associated among others to “cooling degree days” and “adjusted savings: net forest depletion” and negatively associated among others to “greenhouse gas (GHG) net emissions/removals by land use change and forestry (LUCF)” and “mean drought index.” Furthermore, they perform a cluster analysis with the application of the k-Means algorithm and find the presence of four clusters. Finally, they compare eight different machine-learning algorithms to predict the value of renewable energy consumption.