Energy poverty in the European Union Cross-country patterns and vulnerability
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- Master Thesis 
This thesis is a quantitative study based on the data gathered from Eurostat. The thesis investigates energy poverty by observing several sides of the problem: geographical distribution in the European Union, cross-country pattern similarities in the EU, and vulnerability of European households to energy poverty, especially when energy prices are unprecedentedly high. The analysis is performed with the help of such statistical methods as Principal Component Analysis (PCA) and Hierarchical Clustering (HC). According to PCA, the first four Principal Components out of fourteen are sufficient for the analysis since they explain 79% of the variance in the data. Later, HC is applied to those four identified Principal Components, showing that it is optimal to divide the EU countries into seven categories by their predisposition and susceptibility to risks associated with energy poverty. Further, the translog regression approach, along with the HC, is adopted to make a model with an interaction term comprised of the cluster and household electricity price variables to assess the electricity price elasticity of household energy consumption. This thesis is inspired by similar studies conducted by Recalde et al. (2019) and Chai et al. (2021). However, the paper proposes a different way of tracking energy poverty across Europe, based on social, economic, environmental and energy indicators. The findings of this thesis suggest that the neighboring counties' sensitivity to energy poverty tends to be similar, and southern European states are noticeably more vulnerable to the severe effects of energy poverty.