Identification of Macroeconomic Clusters in the European Union Before and After 2020

Macroeconomic indicators of European Union member states are essential for analyzing patterns of comparative economic development, identifying structural differences, and designing policies aimed at reducing regional disparities. This study applies cluster and discriminant analysis to group countries according to selected indicators and to determine the variables that contribute most to differentiating more developed and less developed member states. Principal component analysis (PCA) was employed to reduce data dimensionality and identify latent structures among countries, while factor analysis provides exploratory evidence consistent with the role of selected variables in shaping economic profiles. The results reveal the existence of a stable core of countries with high GDP and favourable fiscal positions, whereas Southern and Eastern European countries exhibit greater internal differences, particularly in inflation rates, unemployment, and public debt. Cluster and factor patterns indicate the consistency of country typologies across both periods, and PCA highlights more complex latent structures and potential convergence processes among certain country groups. These findings provide a solid foundation for understanding the dynamics of macroeconomic processes and planning future comparative analyses and policies, including guidance for targeted economic interventions and strategies to reduce regional inequalities, for both academic research and policy formulation. Measured as an annual rate rather than a price-level index, inflation is shown to diverge markedly after 2020, whereas real convergence in GDP per capita and unemployment continues; endogenous structural-break tests support a break around 2020, and internal validation indices support a stable three-cluster typology.