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Social Indicators Research

, Volume 129, Issue 2, pp 937–960 | Cite as

Towards a Theory of Medium Term Life Satisfaction: Two-Way Causation Partly Explains Persistent Satisfaction or Dissatisfaction

  • Bruce HeadeyEmail author
  • Ruud Muffels
Article

Abstract

Long term panel data enable researchers to construct trajectories of life satisfaction (LS) for individuals over time. In this paper we analyse the trajectories of respondents (N = 3689) in the German Socio-Economic Panel who recorded their LS for 20 consecutive years in 1991–2010. Previous research has shown that at least a quarter of these respondents recorded substantial long term changes in LS (Headey et al. in Proc Natl Acad Sci 107.42:17922–17926, 2010a, in Soc Indic Res 112:725–748, 2013). In this paper, graphs of LS trajectories, and subsequent statistical analysis, show that respondents tend to spend multiple consecutive years above and, in other periods, below their own 20-year mean level of LS. They experience extended ‘good times’ and extended ‘bad times’. These results are contrary to set-point theory which views LS as stable, except for short term fluctuations due to life events. In the later part of the paper we attempt to move towards a theory of medium term life satisfaction. We estimate structural equation models with two-way causation between LS and variables usually treated as causes of LS, including health, physical exercise, frequency of social activities, and satisfaction with work and leisure. Results are interpreted as showing positive feedback loops between these variables and LS, accounting for extended periods of high or low LS. The models are based on a modified concept of ‘Granger-causation’ (Granger in Econometrica 37:424–438, 1969). The main intuition behind Granger-causation is that if x can be shown to be statistically significantly related to y in a model which includes multiple lags of y, then it can be inferred that x is one cause of y.

Keywords

Life satisfaction trajectories Set-point theory Two-way causation Positive feedback loops Granger-causation 

References

  1. Allison, P. D. (2005). Fixed effects regression methods for longitudinal data using SAS. Cary, NC: SAS Institute.Google Scholar
  2. Andrews, F. M., & Withey, S. B. (1976). Social indicators of well-being. New York: Plenum.CrossRefGoogle Scholar
  3. Beck, N., & Katz, J. N. (2011). Modelling dynamics in time-series cross-section political economy data. Annual Review of Political Science, 14, 331–352.CrossRefGoogle Scholar
  4. Bentler, P. M. (1990). Comparative fit indices in structural models. Psychological Bulletin, 107, 238–246.CrossRefGoogle Scholar
  5. Bentler, P. M., & Freeman, E. H. (1983). Tests for stability in linear structural equation systems, Psychometrika, 48, 143–145.Google Scholar
  6. Bollen, K. A. (2010). A general panel model with random and fixed effects: A structural equation approach. Social Forces, 89, 1–34.CrossRefGoogle Scholar
  7. Brickman, P. D., & Campbell, D. T. (1971). Hedonic relativism and planning the good society. In M. H. Appley (Ed.), Adaptation level theory (pp. 287–302). New York: Academic Press.Google Scholar
  8. Browne, M. W., & Cudeck, R. (1993). Alternative ways of assessing model fit. In K. A. Bollen & J. S. Long (Eds.), Testing structural equation models (pp. 136–162). Newbury Park, CA: Sage.Google Scholar
  9. Coleman, J. S. (1968). The mathematical study of change. In H. Blalock & A. Blalock (Eds.), Methodology in social research (pp. 428–478). New York: McGraw Hill.Google Scholar
  10. Costa, P. T., & McCrae, R. R. (1980). Influences of extroversion and neuroticism on subjective well-being. Journal of Personality and Social Psychology, 38, 668–678.CrossRefGoogle Scholar
  11. Costa, P. T., & McCrae, R. R. (1991). NEO PI-R. Odessa, FL: PAR.Google Scholar
  12. Deeg, D., & van Zonneveld, R. J. (1989). Does happiness lengthen life? In R. Veenhoven (Ed.), How harmful is happiness? (pp. 29–43). Rotterdam: Erasmus University Press.Google Scholar
  13. Diener, E. (1984). Subjective well-being. Psychological Bulletin, 95, 542–575.CrossRefGoogle Scholar
  14. Diener, E., & Seligman, M. E. P. (2004). Beyond money: Toward an economy of well-being. Psychological Science in the Public Interest, 5, 1–31.CrossRefGoogle Scholar
  15. Diener, E., Suh, E. M., Lucas, R. E., & Smith, H. L. (1999). Subjective well-being: Three decades of progress. Psychological Bulletin, 25, 276–302.CrossRefGoogle Scholar
  16. Easterlin, R. A. (1974). Does economic growth improve the human lot? Some empirical evidence. In P. A. David & M. W. Reder (Eds.), Nations and households in economic growth (pp. 89–125). New York: Academic Press.CrossRefGoogle Scholar
  17. Easterlin, R. A. (2003). Explaining happiness. Proceedings of the National Academy of Sciences, 100.19, 11176–11183. doi: 10.1073/pnas.1633144100.
  18. Easterlin, R. A., & Angelescu, L. (2009). Happiness and growth the world over: Time series evidence on the happiness-income paradox. Discussion paper no. 4060 (Institute for the Study of Labor, Bonn). Available at http://ftp.iza.org/dp4060.pdf
  19. Finkel, S. E. (1995). Causal analysis with panel data. Thousand Oaks, CA: Sage.CrossRefGoogle Scholar
  20. Frey, B. S., & Stutzer, A. (2002). What can economists learn from happiness research? Journal of Economic Literature, 40, 402–435.CrossRefGoogle Scholar
  21. Frick, J. R., Schupp, J., & Wagner, G. G. (2007). Enhancing the power of the German Socio-Economic Panel Study (SOEP)—Evolution, scope and enhancements. Schmollers Jahrbuch, 127, 139–169.Google Scholar
  22. Fujita, F., & Diener, E. (2005). Life satisfaction set-point: Stability and change. Journal of Personality and Social Psychology, 88, 158–164.CrossRefGoogle Scholar
  23. Granger, C. W. J. (1969). Investigating causal relations by econometric models and cross-spectral methods. Econometrica, 37, 424–438.CrossRefGoogle Scholar
  24. Granger, C. W. J., & Newbold, P. (1974). Spurious regressions in econometrics. Journal of Econometrics, 2(2), 111–120.CrossRefGoogle Scholar
  25. Greenberg, D. F., & Kessler, R. C. (1982). Equilibrium and identification in linear panel models. Sociological Research and Methods, 10, 435–451.CrossRefGoogle Scholar
  26. Gremeaux, V., Gayda, M., Lepers, R., Sosner, P., Juneau, M., & Nigam, A. (2012). Exercise and longevity. Maturitas, 73, 312–317.CrossRefGoogle Scholar
  27. Headey, B. W. (2008a). The set-point theory of well-being: Negative results and consequent revisions. Social Indicators Research, 85, 389–403.CrossRefGoogle Scholar
  28. Headey, B. W. (2008b). Life goals matter to happiness: A revision of set-point theory. Social Indicators Research, 86, 213–231.CrossRefGoogle Scholar
  29. Headey, B. W., Hoehne, G., & Wagner, G. G. (2014). Does religion make you healthier and longer lived? Evidence for Germany, Social Indicators Research, 119, 1335–1361.CrossRefGoogle Scholar
  30. Headey, B. W., Muffels, R. J. A., & Wagner, G. G. (2010a). Long-running German panel survey shows that personal and economic choices, not just genes, matter for happiness. Proceedings of the National Academy of Sciences, 107(42), 17922–17926.CrossRefGoogle Scholar
  31. Headey, B. W., Muffels, R. J. A., & Wagner, G. G. (2013). Choices which change life satisfaction: Similar results for Australia. Britain and Germany, Social Indicators Research, 112, 725–748.CrossRefGoogle Scholar
  32. Headey, B. W., Schupp, J., Tucci, I., & Wagner, G. G. (2010b). Authentic happiness theory supported by impact of religion on life satisfaction: A longitudinal analysis with data for Germany. Journal of Positive Psychology, 5, 73–82.CrossRefGoogle Scholar
  33. Headey, B. W., Veenhoven, R., & Wearing, A. J. (1991). Top-down versus bottom-up theories of subjective well-being. Social Indicators Research, 24, 81–100.CrossRefGoogle Scholar
  34. Kessler, R. C., & Greenberg, D. F. (1981). Linear panel analysis. New York: Academic Press.Google Scholar
  35. Kline, R. B. (2010). Principles and practice of structural equation modelling (3rd ed.). New York: Guilford Press.Google Scholar
  36. Kuhn, T. S. (1962). The structure of scientific revolutions. Chicago: University of Chicago Press.Google Scholar
  37. Lucas, R. E. (2008). Personality and subjective well-being. In M. Eid & R. J. Larsen (Eds.), The science of subjective well-being (pp. 171–194). New York: Guilford Press.Google Scholar
  38. Lucas, R. E., Clark, A. E., Georgellis, Y., & Diener, E. (2003). Reexamining adaptation and the set point model of happiness: Reactions to change in marital status. Journal of Personality and Social Psychology, 84, 527–539.CrossRefGoogle Scholar
  39. Luhmann, M., & Eid, M. (2009). Does it really feel the same? Changes in life satisfaction following repeated life events. Journal of Personality and Social Psychology, 97, 363–381.CrossRefGoogle Scholar
  40. Luhmann, M., Hoffman, W., Eid, M., & Lucas, R. E. (2012). Subjective well-being and adaptation to life events: A meta-analysis. Journal of Personality and Social Psychology, 102, 592–615.CrossRefGoogle Scholar
  41. Lykken, D., & Tellegen, A. (1996). Happiness is a stochastic phenomenon. Psychological Science, 7, 186–189.CrossRefGoogle Scholar
  42. Lyubomirsky, S., Sheldon, K. M., & Schkade, D. (2005). Pursuing happiness: The architecture of sustainable change. Review of General Psychology, 9, 111–131.CrossRefGoogle Scholar
  43. Mackay, L. M., Oliver, M., & Schofield, G. M. (2011). Demographic variations in discrepancies between objective and subjective measures of physical activity. Open Journal of Preventive Medicine, 1, 13–19. Available at http://www.scirp.org/journal/OJPM/
  44. Mathison, L., Andersen, M. H., Veenstra, M., Wahl, A. K., Hanestad, B. R., & Fosse, E. (2007). Quality of life can both influence and be an outcome of general health perceptions after heart surgery. Health and Quality of Life Outcomes, 5, 27. doi: 10.1186/1477-7525-5-27.CrossRefGoogle Scholar
  45. Mehnert, T., Kraus, H. H., Nadler, R., & Boyd, M. (1990). Correlates of life satisfaction in those with a disabling condition. Rehabilitation Psychology, 35, 3–17.CrossRefGoogle Scholar
  46. Meier, S., & Stutzer, A. (2004). Is volunteering rewarding in itself? IZA discussion paper no. 1045, IZA, Bonn.Google Scholar
  47. Nagazato, N., Schimmack, U., & Oishi, S. (2011). Effect of changes in living conditions on well-being: A prospective top-down bottom-up model. Social Indicators Research, 100, 115–135.CrossRefGoogle Scholar
  48. Nickerson, C., Schwarz, N., Diener, E., & Kahneman, D. (2003). Zeroing in on the dark side of the American dream: A closer look at the negative consequences of the goal for financial success. Psychological Science, 14, 531–536.CrossRefGoogle Scholar
  49. Pearl, J. (2009). Causality: Models, reasoning and inference. Cambridge: Cambridge University Press.CrossRefGoogle Scholar
  50. Scherpenzeel, A., & Saris, W. E. (1996). Causal direction in a model of life satisfaction: The top-down/bottom-up controversy. Social Indicators Research, 38, 161–180.CrossRefGoogle Scholar
  51. Schwarze, J., Andersen, H., & Silke, A. (2000). Self-assessed health and changes in self-assessed health as predictors of mortality—First evidence from the German panel data. DIW discussion paper no. 203, Berlin, DIW.Google Scholar
  52. Sheldon, K. M., & Lucas, R. E. (Eds.). (2014). The stability of happiness. Amsterdam: Elsevier.Google Scholar
  53. StataCorp. (2013). Structural equation modelling reference manual, release 13. College Station, TX: Stata Press.Google Scholar
  54. Stevenson, B., & Wolfers, J. (2008). Economic growth and subjective well-being: Reassessing the Easterlin Paradox. Brookings Papers on Economic Activity, 39, 1–102.CrossRefGoogle Scholar
  55. Tuma, N., & Hannan, M. (1984). Social dynamics. New York: Academic Press.Google Scholar
  56. Wilkins, A. S. (2014). To lag or not to lag: Re-evaluating the use of lagged dependent variables in regression analysis. Working paper, Stanford University Department of Political Science. Downloaded July 4, 2014.Google Scholar
  57. Wilson, T. D., & Gilbert, T. D. (2008). Explaining away: A model of affective adaptation. Perspectives on Psychological Science, 3, 370–386.CrossRefGoogle Scholar
  58. Wooldridge, J. M. (2010). Econometric analysis of cross-section and panel data (2nd ed.). Cambridge, MA: MIT press.Google Scholar

Copyright information

© Springer Science+Business Media Dordrecht 2015

Authors and Affiliations

  1. 1.Melbourne Institute of Applied Economic and Social ResearchUniversity of MelbourneParkvilleAustralia
  2. 2.School of Social and Behavioral SciencesTilburg UniversityTilburgThe Netherlands

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