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Journal Article

Choices which change life satisfaction: similar results for Australia, Britain and Germany


Publication date

Jul 2013


Using data from national socio-economic panel surveys in Australia, Britain and Germany, this paper analyzes the effects of individual preferences and choices on subjective well-being (SWB). It is shown that, in all three countries, preferences and choices relating to life goals/values, partner’s personality, hours of work, social participation and healthy lifestyle have substantial and similar effects on life satisfaction. The results have negative implications for a widely accepted theory of SWB, set-point theory. This theory holds that adult SWB is stable in the medium and long term, although temporary fluctuations occur due to life events. Set-point theory has come under increasing criticism in recent years, primarily due to unmistakable evidence in the German Socio-Economic Panel that, during the last 25 years, over a third of the population has recorded substantial and apparently permanent changes in life satisfaction (Fujita and Diener in J Pers Soc Psychol 88:158–64, 2005; Headey in Soc Indic Res 85:389–403, 2008a; Headey et al. in Proc Natl Acad Sci USA 107(42):17922–17926, 2010). It is becoming clear that the main challenge now for SWB researchers is to develop new explanations which can account for medium and long term change, and not merely stability in SWB. Set-point theory is limited precisely because it is purely a theory of stability. The paper is based on specially constructed panel survey files in which data are divided into multi-year periods in order to facilitate analysis of medium and long term change.

Published in

Social Indicators Research

Volume and page numbers

112 , 725 -748





Well Being and Life Course Analysis


Not held in Res Lib - bibliographic reference only

Related publications

  1. Choices which change life satisfaction: revising SWB theory to account for change

    Bruce Headey, Ruud J.A. Muffels, and Gert G. Wagner

    1. Well Being
    2. Life Course Analysis


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