Buffering Effects for Negative Life Events: The Role of Material, Social, Religious and Personal Resources


The changes in subjective wellbeing experienced following negative life events can be buffered by various types of resources. In the present article, we compare the influences of material, religious, social and personality resources using the Swiss Household Panel in a unified framework. Fixed effects regression models are estimated for four negative life events: separation, death of a closely related person, unemployment and disability. Buffering effects are estimated by interacting time since the event with the amount of resources. Religious resources show the strongest buffering whereas material resources do not seem to buffer consequences of negative life events. Social and personality resources present mixed results.

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Fig. 1

Source: SHP 1999–2016

Fig. 2

Source: SHP 1999–2016

Fig. 3

Source: SHP 1999–2016

Fig. 4

Source: SHP 1999–2016


  1. 1.

    As commonly seen in the literature (see e.g. Diener et al. 2003) we use happiness, life satisfaction and SWB interchangeably.

  2. 2.

    Martikainen and Valkonen (1998) studied the mortality of widows after experiencing bereavement and found no clear buffering effect of income.

  3. 3.

    Some studies have covered non-discrete events. Lechner et al. (2013) found that both religious attendance and subjective religiosity buffered the impact of work-related demands on depressive symptoms but not on life satisfaction or work satisfaction.

  4. 4.

    For social support and stressors, see e.g. Cummins (1990) for job stressors, Laudet et al. (2006) for drug addiction, Mueller (2006) for couple difficulties.

  5. 5.

    Among personality traits, extraversion and neuroticism are usually found to predict happiness best.

  6. 6.

    There has been a change in the questionnaire. The yearly questions on relatives (available from 1999 to 2010) has been replaced by separate questions for children, father, mother, siblings and other relatives every 3 years (in 2013 and 2016). This is why we selected friends as indicators. However, using an alternative measure for the entire network gives similar empirical results. The change in the questionnaire concerns also the measure of emotional support (see online Appendix).

  7. 7.

    If there are multiple events, the buffer variable may vary between events.

  8. 8.

    In case of multiple events, we exclude some observations between two events. This concerns observations that are 1 or 2 years after an event and, at the same time, 1 year before the next event.

  9. 9.

    Although conceptually internal, personality includes in addition to an internal component (intra-individual components, i.e. openness, conscientiousness and neuroticism) a rather external component (interindividual components, i.e. agreeableness and extraversion).

  10. 10.

    The buffering variables are stable for each event. In cases with multiple events per individual, the buffer variables might change over time for the same individual. These models include not only an interaction, but also a main effect for the buffering variable.

  11. 11.

    The Benjamini–Hochberg procedure controls the proportion of significant results that are misleadingly positive. For the analysis, we defined 13 repeated measures and a false discovery rate of 0.2 following the recommendations by McDonald (2014). Three aggravating effects, that are significant at a 0.05 p value, are not significant according to the Benjamini–Hochberg procedure. In contrast, two additional aggravating effects become significant. Both methods identify the same significant buffering effects.

  12. 12.

    Due to our coding, we only analyze individuals who become unable to work for reasons of disabilities. Disabilities, where individuals remain economically active are not captured. Still, income could buffer this drop and this is not the case.

  13. 13.

    However, two years after separation, individuals with frequent religious attendance do not suffer significantly more from separation than individuals without or with rare religious attendance.


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This study has been realized using the data collected by the Swiss Household Panel (SHP), which is based at the Swiss Centre of Expertise in the Social Sciences FORS. The project is financed by the Swiss National Science Foundation. The research was supported by the Swiss National Science Foundation (Project FNS—D-A-CH-10001AL_166319). The authors wish to thank Laura Ravazzini, Jehane Simona and Justus Veenman as well as the anonymous reviewers for their valuable comments.

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Correspondence to Ursina Kuhn.

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Kuhn, U., Brulé, G. Buffering Effects for Negative Life Events: The Role of Material, Social, Religious and Personal Resources. J Happiness Stud 20, 1397–1417 (2019) doi:10.1007/s10902-018-9995-x

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  • Subjective well-being
  • Life event
  • Buffer
  • Panel data
  • Religion
  • Personality