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Social Indicators Research

, Volume 96, Issue 2, pp 339–361 | Cite as

Economic Disparities and Life Satisfaction in European Regions

  • M. Grazia PittauEmail author
  • Roberto Zelli
  • Andrew Gelman
Article

Abstract

This paper investigates the role of economic variables in predicting regional disparities in reported life satisfaction of European Union (EU) citizens. European subnational units (regions) are defined according to the first-level EU nomenclature of territorial units. We use multilevel modeling to explicitly account for the hierarchical nature of our data, respondents within regions and countries, and for understanding patterns of variation within and between regions. Main findings are that personal income matters more in poor regions than in rich regions, a pattern that still holds for regions within the same country. Being unemployed is negatively associated with life satisfaction even after controlled for income variation. Living in high unemployment regions does not alleviate the unhappiness of being out of work. After controlling for individual characteristics and modeling interactions, regional differences in life satisfaction still remain, confirming that regional dimension is relevant for life satisfaction.

Keywords

Life satisfaction Regional disparities Multilevel models 

Notes

Acknowledgments

The authors thank the Columbia University, Applied Statistics Center, and the National Science Foundation and National Institutes of Health for financial support. They also acknowledge Sapienza, University of Rome, for financial assistance under grant number C26F07R754. They would like to thank an anonymous reviewer and participants of the XXX IARIW conference, Portoroz, Slovenia, August 2008, for their precious comments and suggestions.

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Copyright information

© Springer Science+Business Media B.V. 2009

Authors and Affiliations

  • M. Grazia Pittau
    • 1
    • 2
    Email author
  • Roberto Zelli
    • 1
  • Andrew Gelman
    • 2
  1. 1.DSPSASapienza Università di RomaRomeItaly
  2. 2.Department of StatisticsColumbia UniversityNew YorkUSA

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