Advertisement

Social Indicators Research

, Volume 117, Issue 1, pp 235–255 | Cite as

Panel Conditioning and Subjective Well-being

  • Mark WoodenEmail author
  • Ning Li
Article

Abstract

The importance of panel, or longitudinal, survey data for analyzing subjective wellbeing, and especially its dynamics, is increasingly recognized. Analyses of such data, however, have to deal with two potential problems: (1) non-random attrition; and (2) panel conditioning. The former is a much researched topic. In contrast, panel conditioning has received much less attention from the research community. In this analysis, longitudinal survey data collected from members of a large national probability sample of households are used to examine whether self-reported measures of psychological well-being exhibit any tendency to change over time in a way that might reflect panel conditioning. Regression models are estimated that control for all time invariant influences as well as a set of time-varying influences. We find very little evidence that mean life satisfaction scores vary with length of time in the panel, especially once non-random attrition is controlled for. In contrast, scores on a measure of mental health do vary with time, and surprisingly men and women exhibit opposing patterns. For men, scores decline over time (though the estimates are not statistically robust), whereas for women the effects are both large and rise with time. Further, for both outcome measures there is a clear narrowing in the dispersion of reported scores over the first few waves of participation. The findings have implications for empirical research employing longitudinal data.

Keywords

HILDA Survey Life satisfaction Longitudinal data Mental health Panel conditioning 

Notes

Acknowledgments

The research reported on in this paper was supported by an Australian Research Council Discovery Grant (#DP1095497). The paper uses unit record data from the Household, Income and Labour Dynamics in Australia (HILDA) Survey. The HILDA Survey Project was initiated and is funded by the Australian Government Department of Families, Housing, Community Services and Indigenous Affairs (FaHCSIA) and is managed by the Melbourne Institute of Applied Economic and Social Research (Melbourne Institute). The authors also thank Robert Cummins and Nicole Watson for helpful advice and comments on an earlier version of this paper. The findings and views reported in this paper, however, are those of the authors and should not be attributed to any of the aforementioned.

References

  1. Australian Bureau of Statistics. (1997). 1995 National Health Survey: SF-36 Population Norms, Australia (ABS cat. No. 4399.0). Canberra: Australian Bureau of Statistics.Google Scholar
  2. Bailar, B. A. (1975). The effects of the rotation group bias on estimates from panel surveys. Journal of the American Statistical Association, 70(349), 23–30.CrossRefGoogle Scholar
  3. Blanchflower, D. G., & Oswald, A. J. (2008). Is well-being U-shaped over the life cycle? Social Science and Medicine, 66(8), 1733–1749.CrossRefGoogle Scholar
  4. Corder, L.S., & Horvitz, D. G. (1989). Panel effects in the National Medical Care Utilization and Expenditure Survey. In D. Kasprzyk, G. Duncan, G Kalton, & M. P. Singh (Eds.), Panel Surveys (pp. 304–318). New York: Wiley.Google Scholar
  5. Das, M., Toepoel, V., & van Soest, A. (2011). Nonparametric tests of panel conditioning and attrition bias in panel surveys. Sociological Methods and Research, 40(1), 32–56.CrossRefGoogle Scholar
  6. Diener, E., Suh, E. M., Lucas, R. E., & Smith, H. L. (1999). Subjective well-being: Three decades of progress. Psychological Bulletin, 125(2), 276–302.CrossRefGoogle Scholar
  7. Ferrer-i-Carbonell, A., & Frijters, P. (2004). How important is methodology for the estimates of the determinants of happiness? Economic Journal, 114(497), 521–530.CrossRefGoogle Scholar
  8. Frick, J. R., Goebel, J., Schechtman, E., Wagner, G. G., & Yitzhaki, S. (2006). Using analysis of gini (ANOGI) for detecting whether two subsamples represent the same universe: The German Socio-Economic Panel Study (SOEP) experience. Sociological Methods and Research, 34(4), 427–468.CrossRefGoogle Scholar
  9. Frijters, P., & Beatton, T. (2012). The mystery of the U-shaped relationship between happiness and age. Journal of Economic Behavior and Organization, 82(2–3), 525–542.CrossRefGoogle Scholar
  10. Frijters, P., Haisken-DeNew, J. P., & Shields, M. A. (2004). Investigating the patterns and determinants of life satisfaction in Germany following reunification. Journal of Human Resources, 39(3), 649–674.CrossRefGoogle Scholar
  11. Headey, B., Muffels, R., & Wagner, G. (2010). 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
  12. Headey, B., Muffels, R., & Wooden, M. (2008). Money doesn’t buy happiness: Or does it? a reassessment based on the combined effects of wealth, income and consumption. Social Indicators Research, 87(1), 65–82.CrossRefGoogle Scholar
  13. Hoeymans, N., Garssen, A. A., Westert, G. P., & Verhaak, P. F. (2004). Measuring mental health of the Dutch population: A comparison of the GHQ-12 and the MHI-5. Health and Quality of Life Outcomes, 2. Article No 23. [Available from: www.hqlo.com].
  14. Kalton, G., Kasprzyk, D., & McMillen, D. B. (1989). Nonsampling errors in panel surveys. In D. Kasprzyk, G. Duncan, G Kalton & M. P. Singh (Eds.), Panel Surveys (pp. 249–270). New York: Wiley.Google Scholar
  15. Kassenboehmer, S. C., & Haisken-DeNew, J. P. (2012). Heresy or enlightenment? The well-being age U-shape effect is flat. Economics Letters, 117(1), 235–238.CrossRefGoogle Scholar
  16. Klein, D. N., & Rubovits, D. R. (1987). The reliability of subjects’ reports on stressful life events inventories: A longitudinal study. Journal of Behavioral Medicine, 10(5), 501–512.CrossRefGoogle Scholar
  17. Landua, D. (1993). Changes in reports of satisfaction in panel surveys: An analysis of some unintentional effects of the longitudinal design. Kolner Zeitschrift fur Soziologie und Sozialpsychologie, 45(3), 553–571.Google Scholar
  18. Lazarsfeld, P. (1940). Panel studies. Public Opinion Quarterly, 4(1), 122–128.CrossRefGoogle Scholar
  19. Lynn, P. (2009). Methods for longitudinal surveys. In P. Lynn (Ed.), Methodology of Longitudinal Surveys (pp. 1–19). Chichester, UK: Wiley.CrossRefGoogle Scholar
  20. Paulhus, D. L. (1991). Measurement and control of response bias. In J. P. Robinson, P. R. Shaver, & L. S. Wrightsman (Eds.), Measures of personality and social psychological attitudes (pp. 17–40). San Diego, CA: Academic Press.CrossRefGoogle Scholar
  21. Pennell, S., & Lepkowski, J. (1992). Panel conditioning effects in the Survey of Income and Program Participation. Proceedings of the Survey Research Methods Section of the American Statistical Association, 566–571.Google Scholar
  22. Rumpf, H.-J., Meyer, C., Hapke, U., & John, U. (2001). Screening for mental health: Validity of the MHI-5 using DSM-IV Axis I psychiatric disorders as gold standard. Psychiatry Research, 105(3), 243–253.CrossRefGoogle Scholar
  23. Silberstein, A. R., & Jacobs, C. A. (1989). Symptoms of repeated interview effects in the Consumer Expenditure Interview Survey. In D. Kasprzyk, G. Duncan, G Kalton, & M. P. Singh (Eds.), Panel Surveys (pp. 289–303). New York: Wiley.Google Scholar
  24. Sobol, M. G. (1959). Panel mortality and panel bias. Journal of the American Statistical Association, 54(285), 52–68.CrossRefGoogle Scholar
  25. Strand, B. H., Dalgard, O. D., Tambs, K., & Rognerud, M. (2003). Measuring the mental health status of the Norwegian population: A comparison of the instruments SCL-25, SCL-10, SCL-5 and MHI-5 (SF-36). Nordic Journal of Psychiatry, 57(2), 113–118.CrossRefGoogle Scholar
  26. Sturgis, P., Allum, N., & Brunton-Smith, I. (2009). Attitudes over time: The psychology of panel conditioning. In P. Lynn (Ed.), Methodology of Longitudinal Surveys (pp. 113–126). Chichester, UK: Wiley.CrossRefGoogle Scholar
  27. Summerfield, M., Freidin, S., Hahn, M., Ittak, P., Li, N., Macalalad, N., et al. (2012). HILDA User Manual – Release 11. Melbourne: Melbourne Institute of Applied Economic and Social Research, University of Melbourne.Google Scholar
  28. Toepoel, V., Das, M., & van Soest, A. (2009). Relating question type to panel conditioning; Comparing trained and fresh respondents. Survey Methods Research, 3(2), 73–80.Google Scholar
  29. Torche, F., Warren, J. R., Halpern-Manners, A., & Valenzuela, E. (2012). Panel conditioning in a study of adolescents’ substance use: Evidence from an experiment. Social Forces, 90(3), 891.CrossRefGoogle Scholar
  30. Traugott, M. W., & Katosh, J. P. (1979). Response validity in surveys of voter behavior. Public Opinion Quarterly, 43(3), 359–377.CrossRefGoogle Scholar
  31. Van Landeghem, B. (2012). Panel conditioning and self-reported satisfaction: Evidence from International panel data and repeated cross-sections. SOEPpapers (on Multidisciplinary Panel Data Research) no. 484. Berlin: DIW.Google Scholar
  32. Verbeek, M., & Nijman, T. (1992). Testing for selectivity bias in panel data models. International Economic Review, 33(3), 681–703.CrossRefGoogle Scholar
  33. Veroff, J., Hatchett, S., & Douvan, E. (1992). Consequences of participating in a longitudinal study of marriage. Public Opinion Quarterly, 56(3), 315–327.CrossRefGoogle Scholar
  34. Ware, J. E., Kosinski, M., Bjorner, J. B., Turner-Bowker, D. M., Gandek, B., & Maruish, M. E. (2000). Users’s Manual for the SF-36v2 Health Survey (2nd ed.). Lincoln, RI: QualityMetric Inc.Google Scholar
  35. Ware, J. E., Snow, K. K., Kosinski, M., & Gandek, B. (2007). SF-36 Health Survey: Manual and Interpretation Guide. Lincoln, RI: QualityMetric Inc.Google Scholar
  36. Waterton, J., & Lievesley, J. (1989). Evidence of conditioning effects in the British Social Attitudes. In D. Kasprzyk, G. Duncan, G Kalton, & M. P. Singh (Eds.), Panel Surveys (pp. 319–339). New York: Wiley.Google Scholar
  37. Watson, N., & Wooden, M. (2009). Identifying factors affecting longitudinal survey response. In P. Lynn (Ed.), Methodology of Longitudinal Surveys (pp. 157–182). Chichester, UK: Wiley.CrossRefGoogle Scholar
  38. Watson, N., & Wooden, M. (2012). The HILDA Survey: A case study in the design and development of a successful household panel study. Longitudinal and Life Course Studies, 3(3), 369–381.Google Scholar
  39. Watson, N. & Wooden, M. (2013). Adding a top-up sample to the HILDA Survey. The Australian Economic Review, 46(4), forthcoming.Google Scholar
  40. Watson, N., & Wooden, M. (forthcoming). Re-engaging with survey non-respondents: Evidence from three household panels. Journal of the Royal Statistical Society: Series A (Statistics in Society).Google Scholar
  41. Wilson, S. E., & Howell, B. L. (2005). Do panel surveys make people sick? US arthritis trends in the Health and Retirement Study. Social Science and Medicine, 60(11), 2623–2627.CrossRefGoogle Scholar
  42. Wooden, M., Freidin, S., & Watson, N. (2002). The Household, Income and Labour Dynamics in Australia (HILDA) Survey: Wave 1. The Australian Economic Review, 35(3), 339–348.CrossRefGoogle Scholar
  43. Wooden, M., Warren, D., & Drago, R. (2009). Working time mismatch and subjective well-being. British Journal of Industrial Relations, 47(1), 147–179.CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media Dordrecht 2013

Authors and Affiliations

  1. 1.Melbourne Institute of Applied Economic and Social ResearchUniversity of MelbourneMelbourneAustralia

Personalised recommendations