Abstract
The study presents the results of grouping EU NUTS 2 regions based on the share of employment in particular sectors (knowledge‑intensive high‑technology services, knowledge‑intensive market services and other knowledge‑intensive services), as well as GDP per capita, in 2008 and 2018. The grouping of regions was done by clustering methods (for structure data), including Ward’s method to determine the number of groups and the k‑means for the final partition. GDP groups were defined using a sample mean and one standard deviation. To assess the similarity of the classifications and, consequently, to evaluate correlations between the employment structures and the level and pace of economic development, the similarity measure for partitions proposed by Sokołowski was used.
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