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Can We Trust Older People’s Statements on Their Childhood Circumstances? Evidence from SHARELIFE

Abstract

This paper analyzes the quality of subjective assessments related to childhood circumstances when provided by old-age individuals. Early life events are important for social scientists to predict individual outcomes later in life and because of data restrictions, retrospective assessments are often used. Nevertheless, there is widespread skepticism on the ability of old-age respondents to recall with good accuracy events occurred many years ago. Using data from the survey of health, aging and retirement in Europe (SHARE), we assess the internal and external consistency of some measures of childhood health and socio-economic status. Our study suggests that overall respondents seem to remember fairly well their health status and their living conditions between age 0–15. Applying a cross-country comparison (13 European countries), we analyse within survey responses with external historical data (e.g., GDP per capita in period 1926–1956) at a country and cohort level. Our results should mitigate some of the doubts on retrospective data collection and promote their use for research purposes.

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Notes

  1. 1.

    Self-reported health is measured on a 1–5 scale with 1 for excellent health and 5 for poor health and we use data from SHARELIFE (2008). For illustration purposes we recode it and define good health as “very good or excellent” and bad health as “good, fair or poor”.

  2. 2.

    An alternative explanation might be that the effect of memory disappears because memory is a function of age and education. However, as aforementioned, this variable has a very large support and we found evidence of substantial variation in the memory test also within age and education groups. In particular, we regressed the variable memory on a cubic polynomial in age, education and other baseline controls including country fixed effects (results are available upon request). As expected, we found that this large set of controls is able to explain less than 30 % of the total variation in the memory test.

  3. 3.

    The same test has been performed using the whole panel (respondents present in wave 1, 2 and 3). However, we decided to drop it from the analysis since selective attrition might influence the goodness of the test. In any case the Wald test for the equality of coefficients between W1–W2 and W1–W3 lead to the rejection of the null hypothesis for women, while the evidence is mixed for men. Results are available upon request.

References

  1. Auriat, N. (1991). Who forgets? An analysis of memory effects in a retrospective survey on migration history. European Journal of Population, 7, 311–342.

    Article  Google Scholar 

  2. Almond, D., & Currie, J. (2011). Human capital development before age five. Handbook of Labor Economics, 4(B), 1315–1486.

    Google Scholar 

  3. Almond, D., & Mazumder, B. (2005). The 1918 influenza pandemic and subsequent health outcomes: An analysis of SIPP data. American Economic Review, 95(2), 258–262.

    Article  Google Scholar 

  4. Barker, D. J. (1998). In utero programming of chronic diseases. Clinical Science, 95, 115–128.

    Article  Google Scholar 

  5. Barro, R., & Lee, J. W. (2013). A new data set of educational attainment in the world, 1950–2010. Journal of Development Economics, forthcoming. doi:10.1016/j.jdeveco.2012.10.001

  6. Beckett, M., Da Vanzo, J., Sastry, N., Panis, C., & Peterson, C. (2001). The quality of retrospective data: An examination of long-term recall in a developing country. Journal of Human Resources, 36(3), 593–625.

    Article  Google Scholar 

  7. Belli, R. (1998). The structure of autobiographical memory and the history calendar: Potential improvements in the quality of retrospective reports in surveys. Memory, 6(4), 383–407.

    Article  Google Scholar 

  8. Belli, R. (2005) The integration of a computer assisted interviewing event history calendar in the panel study of income dynamics. PSID Technical Series Paper #05-01.

  9. Berney, L., & Blane, D. (1998). Collecting retrospective data: Accuracy of recall after 50 years judged against historical records. Social Science and Medicine, 45(10), 1519–1525.

    Article  Google Scholar 

  10. Berney, L., & Blane, D. (2003). The lifegrid method of collecting retrospective information from people at older ages. Research Policy and Planning, 21(2), 13–22.

    Google Scholar 

  11. Blackwell, D., Hayward, M. D., & Crimmins, E. M. (2001). Does childhood health affect chronic morbidity later in life? Social Science and Medicine, 52(8), 1269–1284.

    Article  Google Scholar 

  12. Börsch-Supan, A., & Jürges, H. (2005). The survey of health, aging, and retirement in Europe. Methodology. Mannheim: Mannheim Research Institute for the Economics of Aging (MEA).

    Google Scholar 

  13. Börsch-Supan, A., & Schröder, M. (2011). Retrospective data collection in the survey of health, ageing and retirement in Europe. SHARELIFE methodology. In M. Schröder (Ed.), Retrospective data collection in the survey of health, ageing and retirement in Europe (pp. 5–10). Mannheim: Mannheim Research Institute for the Economics of Aging (MEA).

    Google Scholar 

  14. Bozzoli, C., Deaton, A., & Quintana-Domeneque, C. (2009). Adult height and childhood disease. Demography, 46(49), 647–669.

    Article  Google Scholar 

  15. Bound, J., Brown, C., & Mathiowetz, N. (2001). Measurement error in survey data. Handbook of Econometrics, 5(59), 3707–3833.

    Google Scholar 

  16. Case, A., Fertig, A., & Paxson, C. (2005). The lasting impact of childhood health and circumstance. Journal of Health Economics, 24(2), 365–389.

    Article  Google Scholar 

  17. Case, A., & Paxson, C. (2009). Early life health and cognitive function in old age. American Economic Review Papers and Proceedings, 99(2), 104–109.

    Article  Google Scholar 

  18. Currie, J. (2009). Healthy, wealthy, and wise? Socioeconomic status, poor health in childhood, and human capital development. Journal of Economic Literature, 47(1), 87–122.

    Article  Google Scholar 

  19. De Luca, G., & Peracchi, F. (2005). Survey participation in the first wave of SHARE. In A. Börsch-Supan & H. Jürges (Eds.), The survey of health, aging, and retirement in Europe—methodology. Mannheim: Mannheim Research Institute for the Economics of Aging (MEA).

    Google Scholar 

  20. De Luca, G., & Peracchi, F. (2012). Estimating Engel curves under unit and item nonresponse. Journal of Applied Econometrics, 27(7), 1076–1099.

    Article  Google Scholar 

  21. De Luca, G., & Rossetti, C. (2013). Weights. In SHARE release guide 1.1.1, wave 4.

  22. del Arco Blanco, M. A. (2010). Hunger and the consolidation of the francoist regime (1939–1951). European History Quarterly, 40(3), 458–483.

    Article  Google Scholar 

  23. Dex, S. (1995). The reliability of recall data: A literature review. Bulletin de Méthodologie Sociologique, 49, 58–89.

  24. Francesconi, M. (2005). An evaluation of the childhood family structure measures from the sixth wave of the British household panel survey. Journal of the Royal Statistical Society—Series A, 168, 539–566.

    Article  Google Scholar 

  25. Garrouste, C., & Paccagnella, O. (2010). Data quality: Three examples of consistency across SHARE and SHARELIFE. Mannheim: Mannheim Research Institute for the Economics of Aging (MEA).

    Google Scholar 

  26. Gluckman, P., & Hanson, M. (2005). The developmental origins of adult disease. Maternal and Child Nutrition, 1(3), 130–141.

    Article  Google Scholar 

  27. Haas, S. (2007). The long-term effects of poor childhood health: An assessment and application of retrospective reports. Demography, 44(1), 113–135.

    Article  Google Scholar 

  28. Haas, S., & Bishop, N. (2010). What do retrospective subjective reports of childhood health capture? Evidence from the WLS and the PSID. Research on Aging, 32(6), 698–714.

    Article  Google Scholar 

  29. Havari, E., & Peracchi, F. (2012). Childhood circumstances and adult outcomes: Evidence from SHARELIFE. Working paper 11–15, Einaudi Institute for Economics and Finance (EIEF), Rome.

  30. Jürges, H. (2007). Unemployment, life satisfaction and retrospective error. Journal of the Royal Statistical Society—Series A, 170, 43–61.

    Article  Google Scholar 

  31. Kesternich, I., Siflinger, B., Smith, J. P., & Winter, J. K. (2013). Individual behavior as a pathway between early-life shocks and adult health. Economic Journal (forthcoming)

  32. Krall, E. A., Valadian, I., Dwyer, J. T., & Gardner, J. (1988). Recall of childhood diseases. Journal of Clinical Epidemiology, 41, 1059–1064.

    Article  Google Scholar 

  33. Maddison, A. (2010). Statistics on world population, GDP and per capita GDP, 1–2008 AD. Retrieved April 17, 2013, from http://www.ggdc.net/MADDISON/Historical_Statistics/horizontal-file_02-2010.xls.

  34. Mazzonna, F. (2014). The long lasting effect of family background: A European cross-country comparison. Economics of Education Review, 40, 25–42.

    Article  Google Scholar 

  35. Mazzonna, F., & Peracchi, F. (2012). Ageing, cognitive abilities and retirement. European Economic Review, 56(4), 691–710.

    Article  Google Scholar 

  36. McArdle, J. J., Smith, J. P., & Willis, R. (2011). Cognition and economic outcomes in the health and retirement survey. In D. Wise (Ed.), Explorations in the economics of aging. Chicago: University of Chicago Press.

    Google Scholar 

  37. Pampel, F., & Pillai, V. (1986). Patterns and determinants of infant mortality in developed nations, 1950–1975. Demography, 23, 525–542.

    Article  Google Scholar 

  38. Raphael, K. (1987). Recall bias: A proposal for assessment and control. International Journal of Epidemiology, 16(2), 167–170.

    Article  Google Scholar 

  39. Schröder, M. (2011). Retrospective data collection in the survey of health, ageing and retirement in Europe. Mannheim: Mannheim Research Institute for the Economics of Aging (MEA).

    Google Scholar 

  40. Schröder, M., & Börsch-Supan, A. (2008). Retrospective data collection in Europe. Mannheim Research Institute for the Economics of Aging (MEA), Discussion paper no. 172–2008.

  41. Smith, J. (2009a). Reconstructing childhood health histories. Demography, 46(2), 387–403.

    Article  Google Scholar 

  42. Smith, J. (2009b). The impact of childhood health on adult labor market outcomes. The Review of Economics and Statistics, 91(3), 478–489.

    Article  Google Scholar 

  43. Smith, J., & Thomas, D. (2003). Remembrances of things past: Test–retest reliability of retrospective migration histories. Journal of the Royal Statistical Society—Series A, 166, 23–49.

    Article  Google Scholar 

  44. van den Berg, G. J., Doblhammer-Reiter, G., & Christensen, K. (2009). Exogenous determinants of early-life conditions, and mortality later in life. Social Science and Medicine, 68(9), 1591–1598.

    Article  Google Scholar 

  45. van den Berg, G. J., Pinger, P. R., & Schoch, J. (2012). Instrumental variable estimation of the causal effect of hunger early in life on health later in life. doi:10.1111/ecoj.12250.

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Acknowledgments

This paper uses data from SHARE release 2.3.1. SHARE data collection in 2004–2007 was primarily funded by the European Commission through its 5th and 6th framework programmes (project numbers QLK6-CT-2001- 00360; RII-CT- 2006-062193; CIT5-CT-2005-028857). Additional funding by the US National Institute on Aging (Grant No. U01 AG09740-13S2; P01 AG005842; P01 AG08291; P30 AG12815; Y1-AG-4553-01; OGHA 04-064; R21 AG025169) as well as by various national sources is gratefully acknowledged (see http://www.share-project.org for a full list of funding institutions).

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Correspondence to Fabrizio Mazzonna.

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Havari, E., Mazzonna, F. Can We Trust Older People’s Statements on Their Childhood Circumstances? Evidence from SHARELIFE. Eur J Population 31, 233–257 (2015). https://doi.org/10.1007/s10680-014-9332-y

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Keywords

  • Childhood
  • Europe
  • Health
  • Retrospective data
  • SHARE survey