MODELING AND COMPARATIVE ANALYSIS OF THE LABOR MARKET OF EU COUNTRIES IN MODERN CONDITIONS

Abstract

The article examines the features of the functioning and development of the labor market in the countries of the European Union based on the application of economic and mathematical modeling and comparative statistical analysis. The relevance of the study is driven by significant cross-country differences in socio-economic indicators characterizing the state of the labor market under the conditions of globalization, digital transformation, demographic shifts, and deepening economic integration. The aim of the study is to model and conduct a comparative analysis of the EU labor market, as well as to identify typological groups of countries according to the level of its development. The study employs a system of key indicators, including the unemployment rate, the share of the working-age population (15–64 years), the proportion of employees with higher education, the level of minimum wages, and the average annual income of the population. Based on statistical data for 2023, a comparative analysis was carried out, confirming substantial differentiation among EU countries across all selected indicators. The findings reveal that the most pronounced disparities are observed in economic indicators, particularly in income levels and minimum wages, reflecting uneven economic development across countries. To systematize the results, a cluster analysis was performed using Ward’s hierarchical method and Euclidean distance. Prior to clustering, the data were standardized to ensure the comparability of indicators. As a result, two clusters of countries were identified, differing in terms of labor market development. The first cluster includes countries with relatively lower socio-economic indicators, whereas the second cluster comprises economically advanced countries characterized by a more balanced labor market structure, higher income levels, and stronger human capital. The findings confirm the effectiveness of applying multivariate statistical methods in labor market research and allow for the identification of underlying patterns in its development. The practical significance of the study lies in the potential application of the results for improving socio-economic policy and forecasting labor market development under contemporary challenges.