The aim of this research is to evaluate economic efficiency by measuring how regional resources are reflected in the economic results. The analysis focuses on new member states of European Union that joined the EU in 2004. Regions of the Central and Eastern European Union and the Baltic States are analysed. These territories have a comparatively common experience of market and infrastructure development and could be evaluated as economically comparable units. As the EU Cohesion policy funds are distributed according to NUTS2 regional level, this regional level is selected for the analysis. Selected NUTS2 territorial units are of 800 thousand to 3 million population size. Because of this criteria, more densely populated areas form separate region, as Prague or Bratislava, that consist of capitals and are more economically developed than less urban territories. Overall, 40 regions are involved in the analysis of 8 countries: Estonia (EE), Latvia (LV), Lithuania (LT), Poland (PL), Czechia (CZ), Slovakia (SK), Slovenia (SL), Hungary (HU). Data is from the Eurostat database. The EU nomenclature of territorial units for statistics ensures harmonised standards in the collection and transmission of regional data, guarantees that published regional statistics are based on comparable data and enables the analysis and comparison of the socioeconomic situation of the regions.

Regional economic indicators: GDP - Gross domestic product, PPS (purchasing power standard) per inhabitant; HR_SC_TH - Persons employed in science and technology, per cent of total population; HR_TER - Persons with tertiary education, per cent of total population; R&D_EXP - Cumulative intramural research and development expenditure (during previous 5 years), PPS per inhabitant; PATENT - Patents (during previous 5 years), per capita; HTC_EMP - Employment in high-technology manufacturing and knowledge-intensive high-technology services, per cent of total employment; LMTC_EMP - Employment in low and medium technology manufacturing, per cent of total employment; AGR_EMP - Employment in agriculture, forestry and fishing; mining and quarrying, per cent of total employment; POP_DENS - Population density, inhabitants per square km; ROAD_DENS - Railway network density, total railway lines per thousand square km; TOUR_NGHT - Nights spent at tourist accommodation establishments, per thousand inhabitants.

Content: initial data matrix; matrix after normalization by z-score; correlation matrix R; matrix V for visual analysis of correlations.