Social Indicators Research

, Volume 130, Issue 1, pp 107–127 | Cite as

Long Term Trends in Life Satisfaction, 1973–2012: Flanders in Europe

  • Marc CallensEmail author


In this paper we focus on temporal heterogeneity of overall life satisfaction. Using repeated Eurobarometer Surveys from the period 1973–2012 and multilevel hierarchical age period cohort regression, trend, life-cycle and cohort effects are disentangled. In Flanders, the trend fluctuations are stronger than the life-cycle effects and there are hardly any generation effects. In other countries, by contrast, there are few or no trend fluctuations, but rather signs of a generational change. The international heterogeneity is particularly large and these international differences are stronger than the temporal ones. It remains unclear what factors from the macro-context lie at the basis of the observed international differences.


Overall life satisfaction Eurobarometer 1973–2012 Multilevel hierarchical age period cohort regression Long term trend Flanders Europe 


  1. Blanchflower, D., & Oswald, A. (2004). Well-being over time in Britain and the USA. Journal of Public Economics, 88, 1359–1386.CrossRefGoogle Scholar
  2. Callens, M., & Croux, C. (2005). Performance of likelihood-based estimation methods for multilevel binary regression models. Journal of Statistical Computation and Simulation, 75(12), 1003–1017.CrossRefGoogle Scholar
  3. Commission of the European Communities. (2009). GDP and beyond. Measuring progress in a changing world. Communication from the Commission to the Council and the European Parliament. Brussels: Commission of the European CommunitiesGoogle Scholar
  4. Corijn, M. (2010). Als we maar gezond zijn!? Het belang en de betekenis van de gezondheidsbeleving in Vlaanderen. In D. Verlet, & M. Callens (Eds.), De kwaliteit van het leven, een mozaïek van het dagelijks leven. Brussel: Studiedienst van de Vlaamse Regering.Google Scholar
  5. Davis, J. (1984). New money, an old man/lady and ‘Two’s company’: Subjective Welfare in the NORC General Social Surveys, 1972–1982. Social Indicators Research, 15, 319–350.CrossRefGoogle Scholar
  6. Easterlin, R. (1987). Birth and fortune: The impact of numbers on personal welfare. Chicago: University of Chicago.Google Scholar
  7. Easterlin, R. (1995). Will raising the income of all increase the happiness of all? Journal of Economic Behaviour and Organisation, 27, 35–48.CrossRefGoogle Scholar
  8. Elder, R. (1974). Children of the great depression: Social change in life experience. Chicago: The University of Chicago Press.Google Scholar
  9. Ferrer-i-Carbonell, A., & Frijters, P. (2004). How important is methodology for the estimates of the determinants of happiness? Economic Journal, 114, 641–659.CrossRefGoogle Scholar
  10. Goldstein, H. (2003). Multilevel statistical models. New York: Wiley.Google Scholar
  11. Gove, W., Ortega, S., & Style, C. (1989). The maturational and role perspectives on aging and self through the adult years: An empirical evaluation. Americal Journal of Sociology, 94, 1117–1145.CrossRefGoogle Scholar
  12. Hall, J., Giovannini, E., Morrone, A., & Ranuzzi, G. (2010). A framework to measure the progress of societies. OECD Statistics Directorate working paper no. 34. Paris: OECD.Google Scholar
  13. Huebner, E., & Dew, D. (1996). The interrelationships of positive affect, negative effect and life satisfaction in an adolescent sample. Social Indicators Research, 38(2), 129–137.CrossRefGoogle Scholar
  14. Li, B., Lingsma, H. F., Steyerberg, E. W., & Lesaffre, E. (2011). Logistic random effects regression models: A comparison of statistical packages for binary and ordinal outcomes. BMC Medical Research Methodology. doi: 10.1186/1471-2288-11-77.Google Scholar
  15. Pittau, M., Zelli, R., & Gelman, A. (2010). Economic disparities and life satisfaction in European regions. Social Indiactors Research, 96(2), 339–361.CrossRefGoogle Scholar
  16. Raudenbush, S., & Bryk, A. (2002). Hierarchical linear models: Applications and data analysis methods. Thousand Oaks: Sage.Google Scholar
  17. Rodgers, W. (1982). Trends in reported happiness within demographically defined subgroups, 1957–78. Social Forces, 60, 826–842.CrossRefGoogle Scholar
  18. Ryder, N. B. (1965). The cohort as a concept in the study of social change. American Sociological Review, 30, 843–861.CrossRefGoogle Scholar
  19. Schmitt, H., Scholz, E., Leim, I., & Moschner, M. (2008). The Mannheim Eurobarometer Trend File 19702002 (ed. 2.00). European Commission [Principal investigator]. Cologne: GESIS Data Archive. ZA3521 Data file Version 2.0.1. doi: 10.4232/1.10074.
  20. Schmitt, H., Scholz, E., Leim, I., & Moschner, M. (2009). The Mannheim Eurobarometer Trendfile 19702002. Data Set Edition 2.01. Codebook and unweighted frequency distributions. Updated Version. Cologne: GESIS Data Archive.Google Scholar
  21. Schmotkin, D. (1990). Subjective well-being is a function of age and gender: A multivariate look for differentiated trends. Social Indicators Research, 23, 201–230.CrossRefGoogle Scholar
  22. Snijders, T., & Bosker, R. (1999). Multilevel analysis: An introduction to basic and advanced multilevel modeling. London: Sage Publishers.Google Scholar
  23. Stiglitz, J. E., Sen, A. & Fitoussi, J. (2009). Report by the commission on the measurement of economic performance and social progress.
  24. Van den Noortgate, W., De Boeck, P., & Meulders, M. (2003). Cross-classification multilevel logistic models in psychometrics. Journal of Educational and Behavioral Statistics, 28(4), 369–386.CrossRefGoogle Scholar
  25. Veenhoven, R. (1984). Conditions of happiness. Dordrecht: Kluwer Academic.CrossRefGoogle Scholar
  26. Veenhoven, R. (1996). Developments in satisfaction research. Social Indicators Research, 37(1), 1–46.Google Scholar
  27. Veenhoven, R. (2002). Het grootste geluk voor het grootste aantal. Sociale Wetenschappen, 4, 1–43.Google Scholar
  28. Veenhoven, R. (2004). World database of happiness: Continuous register of subjective appreciation of life. In W. Glatzer, S. VonBelow, & M. Stoffregen (eds.), Challenges for quality of life in the contemporary world: Advances in quality-of-life studies, theory and research. Social indicators research series, 24. Dordrecht: Kluwer Academic Publishers.Google Scholar
  29. Veenhoven, R. (2005). Trend average happiness in nations 19462004: How much people like the life they live. World Database of Happiness. Trend Report 2005-1d.Google Scholar
  30. Veenhoven, R. (2009). Trends inequality-adjusted happiness in nations 19462008: How well nations combine a high level of happiness with an equitable distribution. World database of happiness. Trend Report 2009-4.
  31. Verlet, D., & Callens, M. (2010a). De kwaliteit van het leven in het vizier van het beleid. Een inleidende situering. In D. Verlet, & M. Callens (Eds.), De kwaliteit van het leven, een mozaïek van het dagelijks leven. Brussel: Studiedienst van de Vlaamse Regering.Google Scholar
  32. Verlet, D., & Callens, M. (2010b). De contente Vlaming. Algemene levenstevredenheid bij de doorsnee bevolking in Vlaanderen. In D. Verlet, & M. Callens (Eds.), De kwaliteit van het leven, een mozaïek van het dagelijks leven. Brussel: Studiedienst van de Vlaamse Regering.Google Scholar
  33. Yang, Y. (2008). Social inequalities in happiness in the United States, 1972 to 2004: An age–period–cohort analysis. American Sociological Review, 73, 204–226.CrossRefGoogle Scholar
  34. Yang, Y., & Land, K. (2006). A mixed models approach to the age–period–cohort analysis of repeated cross-section surveys, with an application to data on trends in verbal test scores. Sociological Methodology, 36, 75–97.CrossRefGoogle Scholar
  35. Yang, Y., & Land, K. (2008). Age–period–cohort analysis of repeated cross-section surveys: Fixed or random effects? Sociological Methods and Research, 36, 297–326.CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media Dordrecht 2015

Authors and Affiliations

  1. 1.Research Centre of the Flemish GovernmentBrusselsBelgium

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