Revisiting the literature on the dynamic Environmental Kuznets Curves using a latent structure approach

Theories of the association between environmental degradation and economic growth are not new and are very important under current global conditions to understand and tackle challenges like decarbonisation and the circular economy among others. Countries must balance growth with environmental degradation, and in the extensive literature that deals with this association, applied economists have largely used the environmental Kuznets curve (EKC) setting, with different empirical methodologies in various data settings. However, under a panel data framework, researchers often assume that countries are similar when dealing with unobservable heterogeneity. The papers exploits one of the methodologies to unveil heterogeneity to determine groupings from the data. We consider the countries that account for nearly 80% of global carbon dioxide emissions and apply the EKC setting. Using a Classifier Lasso framework that applies latent group methodologies to address unobservable heterogeneity, we find for two distinct groups substantial heterogeneity in types of energy consumption (renewable and total) with both positive and negative effects observed in the data. The results provide a new perspective on potential impacts illustrated in the EKC literature that might be relevant to policy makers.