Cluster Analysis and Macroeconomic Indicators and Their Effects on the Evolution of the Use of Clean Energies

Abstract

The aim of this research is to relate clean energies, CO2 emissions, and economic variables. Relationships can be generated that characterize countries that manage to relate the use of clean energy with GDP, economic openness, and economic growth. We employ a quantitative methodology that utilizes clustering techniques to identify distinct groups of countries based on their susceptibility to climate change impacts. Subsequently, we employ a generalized linear model approach to estimate the investment behaviors of these country groups in alternative energy sources in relation to CO2 emissions and macroeconomic variables. The clusters reveal that the countries grouped in each cluster exhibit significantly distinct behaviors among the clusters. This differentiation is grounded in the countries under analysis, showing the evolution of the countries in terms of the use of clean energy and the emission of CO2 in relation to macroeconomic variables. According to the conducted research, there are different groups with differentiated behavior in terms of energy consumption and CO2 emissions, which implies the implementation of policies consistent with the development characteristics of the countries and how they cope with climate risk. Moreover, as a result of this research, a recommendation for policy makers could be that sustainable and clean development countries are based in three different sustainability dimensions: environmental, economic, and social.

Keywords

• CO₂ emissions
• GDP
• clean energy
• macroeconomic variables
• cluster analysis
• econometric models