Constructing social and economic indicators for EU countries using dynamic classification: Case studies

Abstract

This paper presents applications of the dynamic classification algorithm (DCA) described in Gertsbakh and Yatskiv (Dynamic Classification: Economic Welfare Growth in EU During 1995-2004. Proceedings of International Conference Data Mining 2006, 11-13 July 2006, Prague. WIT Press. 2006, p.53-62) to the development of three socio-economic indicators: National Health Index (NHI), Population Mobility Index (PMI) and Logistic Performance Index (LPI). In each of these three cases we work with the respective data for EU-25 countries. The essence of the DCA is to transform a multidimensional vector to a scalar on the basis of combining cluster and discriminant analysis. In Gertsbakh and Yatskiv, the DCA was used for obtaining a measure of socio-economic welfare and its dynamics for EU-25 countries over the period 1995-2004. The output of DCA is a collection of time series (graphs) representing the dynamics and the pattern of the scalar socio-economic indicator for each country in the considered time period.