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EN
The funds provided by Member States of the European Union (EU) are the main source of supplies to the EU budget. The size of the payment depends on the Gross National Income (GNI) of each country. The EU funds are allocated for the implementation of common policies aimed at improving upon life of its citizens through the alignment of the economic, social and territorial disparities between the regions of the Union. The main aim of the research is to conduct statistical analysis of spatial-temporal differentiation of redistribution of EU GNI in 2004-2008. Additionally, the new research methodology differentiation of redistribution of EU GNI based on statistical data analysis methods is elaborated. The mentioned redistribution of EU GNI was based on the relationship between the participation of a given Member State in expenditure on a highlighted area of a common EU policy and the participation of the same country in the creation of the EU's GNI. The research period included the years of Polish membership in the EU. The new research methodology of spatial-temporal differentiation of redistribution of EU GNI was based on various statistical data analysis methods such as the coefficient of spatial potential, model for panel data and an analysis of correspondence.
EN
The article presents results of taxonomic analysis of euro area countries belonging to the European Union in terms of similarity of the structure of spending on areas of common EU policy in 2000–2010. In a situation of global economic crisis strongly affects the euro area countries, special attention is devoted to such countries as Greece, Italy, Spain, Portugal and Ireland. As expected, Greece, Spain, Portugal and Ireland were characterized by a different level of spending on areas of common EU policy in 2000-2010 than the other euro area countries belonging to the EU. Exception was Italy, which showed a similarity in this respect to the other countries that joined the EU before 2004. The study used cluster analysis methods such as the method of Ward and k-means.
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