Evaluation of the European Union countries' system of indicators for measuring income inequality and poverty level among the population

Abstract

This research analyzes the European Union countries’ system of indicators used to measure income inequality and poverty level among the population. Income disparities within the EU are significant, however, the disparities are stark between member states. The Gini coefficient for income inequality stood at 29.6% in 2023, indicating moderate inequality. For example, Bulgaria and Lithuania have the highest levels of inequality, with Gini coefficients that exceed 35%, while for Slovakia, Slovenia, Belgium, and Czechia the levels are much lower, with coefficients below 25%. A substantial portion of the EU population is at risk of poverty or social exclusion. In 2023, approximately 21.4% of EU citizens, or nearly 95 million individuals, faced this risk. This figure includes those below the poverty threshold, those experiencing severe material deprivation, and those in low work-intensity households. Romania, Bulgaria, and Greece exhibit particularly high percentages of individuals at risk, especially in rural areas where there are limited job opportunities and services. In general, the system of indicators for measuring income inequality includes many different indicators, the most important of which are: the Gini coefficient (the most common indicator), the Lorenz curve (a graphical illustration of income distribution), the decile coefficient (the ratio of the income of the richest 10% to the poorest 10%), and indicators reflecting the share of certain population groups in total income. European Union countries use the Gini coefficient as the main indicator for measuring income inequality, which reflects the degree of income stratification in society. At the EU level, the ratio of the incomes of the richest 20% to the poorest 20% (S80/S20) is also used to assess the level of inequality. Comparing the Gini coefficient of the Republic of Moldova with that of neighboring countries reveals certain differences in the level of income inequality. Eastern European countries such as Romania and Ukraine also face inequality issues, but the dynamics of changes in the coefficient in these countries may differ. These differences reflect the overall socioeconomic status of the countries and the effectiveness of their social and economic policies. Analysis of neighboring countries allows Moldova to assess its achievements and shortcomings in the context of regional development.