| Abstract [eng] |
With current conflicts, upcoming recession, and green transition there are some disruptions in the European energy market. This brings a lot of uncertainty and may negatively affect individuals, especially those from the most socioeconomically vulnerable groups. Hence, understanding, measuring and tackling energy poverty is becoming more and more important. While a lot of complex indicators already exist, they often fail to take into account the changes in energy market, specifically the shift from traditional energy resources towards renewable ones. The goal of this study is to create a green energy poverty index that considers renewable energy and green transition in the assessment of energy poverty. Several already existing energy poverty indices were analysed to better understand what are the most suitable indicators and methods for computing the new index. The literature analysis also revealed that green transition can reduce energy poverty if the energy transition actions are implemented with a focus on improving affordability and efficiency of energy. However, if the green transition is premature, it may exacerbate energy poverty. Two methods are selected. Robust Principal Component Analysis is used to create a green energy poverty index that can be easily computed when the values of the selected indicators are available. Data envelopment analysis is used to evaluate efficiency of the countries. Data envelopment analysis evaluates whether the country is progressing in green transition with a focus on inclusivity and energy poverty reduction and provide the target values for energy poverty with the current use of renewable energy resources if they are used efficiency with such focus. The analysis covers 27 EU Member States. Five variables were selected for the index – inability to keep adequately warm, arrears on utility bills, use of renewables for electricity, use of renewables for heating and cooling, share of energy from renewable resources. Robust PCA is used to derive the weights for each of the variables in the index. After that, the green energy poverty index value for each country is calculated. DEA is used to determine which countries are most efficient, meaning they have lowest values of energy poverty indicators associated with the amount of renewable energy resources it has. The newly computed indices are validated using correlation analysis with relevant indicators. The study provides a closer look to the relation between green transition and energy poverty. The index constructed can be used to inform policy decision-making process. |
