International Review of Economics

, Volume 59, Issue 4, pp 409–430 | Cite as

Mapping patterns of well-being and quality of life in extended Europe

  • Jenny AssiEmail author
  • Mario Lucchini
  • Amedeo Spagnolo


In this paper, we have applied a powerful clustering procedure (the two-step cluster analysis or BIRCH algorithm) to a set of non-monetary indicators of well-being and quality of life taken from the first four waves of the European Social Survey. By employing this technique, we have identified nine clusters of people characterized by different forms of well-being and quality of life, while preserving as much as possible the multidimensional information contained in the preselected indicators. We then analyzed the distribution of the clusters among the various European countries, finding significant differences among the groups of Nordic countries, Continental European countries, Mediterranean European countries and Eastern European countries in the chances of belonging to the nine forms of well-being and quality of life previously identified. On average, citizens of the Nordic countries, but also those of Switzerland and Luxembourg, have a higher chance of belonging to cumulative clusters of well-being than countries in Continental Europe and Eastern Europe. In very concise terms, the former appear to be somewhat protected from the risk of incurring the more severe forms of material deprivation, distrust of others and of institutions, poor health and relational isolation. In contrast, Eastern Europeans are characterized by particularly pronounced levels of deprivation across multiple dimensions.


Well-being Quality of life Two-step cluster analysis European social survey 

JEL Classification



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Copyright information

© Springer-Verlag 2012

Authors and Affiliations

  1. 1.Department of Business and Social Sciences (DSAS)University of Applied Sciences and Arts of Southern Switzerland (SUPSI)MannoSwitzerland
  2. 2.Istituto per lo Sviluppo della Formazione Professionale dei Lavoratori (ISFOL)RomeItaly

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