USING THE CLUSTER ANALYSIS METHOD: MACROECONOMIC ASPECT AND INTERNATIONAL COMPARISONS

Анотація

The article examines the application of the cluster analysis method in macroeconomic research and substantiates its relevance in the context of increasing volumes of heterogeneous statistical data and the growing need for their systematization. Cluster analysis is considered as an effective multivariate statistical procedure that enables grouping objects according to a set of features. The theoretical foundations of cluster analysis are explored, including its role in classification, verification of structural hypotheses, and construction of new typologies for insufficiently studied socio-economic phenomena. The paper characterizes hierarchical (agglomerative and divisive) and iterative methods, outlines the logic of forming dendrograms, and describes the use of distance measures for assessing similarity between objects in multidimensional space. The practical implementation of the method is demonstrated through the clustering of European Union countries based on four key macroeconomic indicators for 2024: gross domestic product, exports of goods and services, imports of goods and services, and foreign direct investment inflows. The empirical analysis was conducted using STATISTICA software. The results of the study allowed the identification of three relatively homogeneous clusters of EU countries. The first cluster includes the main centers of macroeconomic concentration, characterized by the highest average values of all selected indicators and representing system-forming economies within the EU. The second cluster comprises countries with intensive foreign economic interaction, distinguished by high trade openness and active participation in international capital flows. The third cluster unites economies with balanced macroeconomic dynamics and moderate values of the analyzed indicators, reflecting structural proportionality between GDP, trade turnover, and investment flows and demonstrating relative internal homogeneity. The research demonstrates that cluster analysis is an effective analytical tool for international comparisons, macroeconomic modeling, and evidence-based policy formulation in the context of complex, dynamic, and highly interconnected economic systems.

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