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Commonalities and Disparities among the EU Candidate

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Author Info

  • Ivan Ungureanu, Clementina

    ()
    (Romanian National Statistical Institute, Institute for Economic Forecasting, Romanian Academy, EU international expert.)

  • Ersoz, Filiz

    ()
    (Turkish Military Academy Defence Sciences Institute, Ankara, Turkey.)

Abstract

One of the important challenges of the European Union (EU) at the beginning of the 21st century is its enlargement. After the integration of the 12 countries in 2005 and 2007, the EU continues its strategy for stability, security and prosperity in Europe. The new candidate countries, at different levels of development, are Western Balkan countries and Turkey. The objective of the paper is to investigate the differences among the EU candidate countries according to the current measures of welfare/sustainability and to find their similarities and differences. This analysis of the differences and the similitude between candidate countries is done by using multidimensional scaling method (MDS) and hierarchical cluster analysis of sustainability, which takes into account, at the same time, economic, health, standard of living, people and environmental variables, as part of the multivariate statistical analysis technique - one of the basic methods of multidimensional scaling. Furthermore, MDS method allows a standardized (transformed) analysis of the data collected in different scales. This study is based on the data standardized by means of Z score transformation. The main conclusions of the analysis light up the differences between candidate countries and could be an important tool for the policy makers to focus their efforts on the difficult goal to join the European Union.

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Bibliographic Info

Article provided by Institute for Economic Forecasting in its journal Romanian Journal for Economic Forecasting.

Volume (Year): (2010)
Issue (Month): 3 (September)
Pages: 173-186

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Handle: RePEc:rjr:romjef:v::y:2010:i:3:p:173-186

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Keywords: multidimensional scaling; hierarchical cluster analysis; statistical analysis;

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