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Effects of Attrition and Non-Response in the Health and Retirement Study


  • Kapteyn, Arie

    () (University of Southern California)

  • Michaud, Pierre-Carl

    () (HEC Montreal)

  • Smith, James P.

    () (RAND)

  • van Soest, Arthur

    () (Tilburg University)


We study the effect of attrition and other forms of non-response on the representativity over time of the Health and Retirement Study (HRS) sample born 1931-1941; the sample was initially drawn in 1992. Although some baseline characteristics of respondents do appear correlated with non-response over time, the 2002 sample of respondents does not appear to suffer significantly from selection on observables, except for race and ethnicity; for these two observables, longitudinal weights based on the Current Population Survey (CPS) can be used and are provided with the data set. We attribute this lack of selection to the fact that attritors who differ most eventually come back to the survey in waves prior to 2002. Although this allows cross-sections to remain fairly representative in later waves, it suggests that longitudinal analysis should use the unbalanced sample rather than the balanced sample of those interviewed in all waves. Individuals who attrit but who are recruited back into the survey are very different from those who are permanent attritors to the HRS. Finally, we investigate the selective nature of the decision of respondents to grant HRS permission to access their Social Security records and of the non-response introduced by employers of pension policyholders not providing HRS with worker’s Summary Plan Descriptions. We find that subsamples for which such information is available are selective on a number of dimensions, such as education and other socioeconomic status (SES) outcomes.

Suggested Citation

  • Kapteyn, Arie & Michaud, Pierre-Carl & Smith, James P. & van Soest, Arthur, 2006. "Effects of Attrition and Non-Response in the Health and Retirement Study," IZA Discussion Papers 2246, Institute for the Study of Labor (IZA).
  • Handle: RePEc:iza:izadps:dp2246

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    References listed on IDEAS

    1. John Fitzgerald & Peter Gottschalk & Robert Moffitt, 1998. "An Analysis of Sample Attrition in Panel Data: The Michigan Panel Study of Income Dynamics," Journal of Human Resources, University of Wisconsin Press, vol. 33(2), pages 251-299.
    2. Horowitz, Joel L. & Manski, Charles F., 1998. "Censoring of outcomes and regressors due to survey nonresponse: Identification and estimation using weights and imputations," Journal of Econometrics, Elsevier, vol. 84(1), pages 37-58, May.
    3. Keisuke Hirano & Guido W. Imbens & Geert Ridder & Donald B. Rubin, 2001. "Combining Panel Data Sets with Attrition and Refreshment Samples," Econometrica, Econometric Society, vol. 69(6), pages 1645-1659, November.
    4. Hausman, Jerry A & Wise, David A, 1979. "Attrition Bias in Experimental and Panel Data: The Gary Income Maintenance Experiment," Econometrica, Econometric Society, vol. 47(2), pages 455-473, March.
    5. Orazio P. Attanasio & Hilary Williamson Hoynes, 2000. "Differential Mortality and Wealth Accumulation," Journal of Human Resources, University of Wisconsin Press, vol. 35(1), pages 1-29.
    6. Juster, F. Thomas & Smith, James P. & Stafford, Frank, 1999. "The measurement and structure of household wealth," Labour Economics, Elsevier, vol. 6(2), pages 253-275, June.
    7. Daniel H. Hill & Robert J. Willis, 2001. "Reducing Panel Attrition: A Search for Effective Policy Instruments," Journal of Human Resources, University of Wisconsin Press, vol. 36(3), pages 416-438.
    8. Haider, S. & Solon, G., 2000. "Nonrandom Selection in the HRS Social Security Earnings Sample," Papers 00-01, RAND - Labor and Population Program.
    9. Haider, S. & Solon, G., 2000. "Nonrandom Selection in the HRS Social Security Earnings Sample," Papers 00-01, RAND - Labor and Population Program.
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    Cited by:

    1. Pierre-Carl Michaud & Dana Goldman & Darius Lakdawalla & Adam Gailey & Yuhui Zheng, 2009. "International Differences in Longevity and Health and their Economic Consequences," NBER Working Papers 15235, National Bureau of Economic Research, Inc.
    2. Slade, Alexander N., 2012. "Health investment decisions in response to diabetes information in older Americans," Journal of Health Economics, Elsevier, vol. 31(3), pages 502-520.
    3. Tobias Stucki, 2009. "How long do external capital constraints matter?," KOF Working papers 09-241, KOF Swiss Economic Institute, ETH Zurich.
    4. Dave, Dhaval & Saffer, Henry, 2008. "Alcohol demand and risk preference," Journal of Economic Psychology, Elsevier, vol. 29(6), pages 810-831, December.
    5. Erik Meijer & Lynn A. Karoly & Pierre-Carl Michaud, 2010. "Using Matched Survey and Administrative Data to Estimate Eligibility for the Medicare Part D Low Income Subsidy Program," Working Papers WR-743, RAND Corporation.
    6. John L. Czajka & Gabrielle Denmead, "undated". "Income Data for Policy Analysis: A Comparative Assessment of Eight Surveys," Mathematica Policy Research Reports 19724257b78544bdbd55f15be, Mathematica Policy Research.

    More about this item


    economics of aging; non-response; administrative records; attrition;

    JEL classification:

    • C42 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Survey Methods
    • C80 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - General
    • I10 - Health, Education, and Welfare - - Health - - - General
    • J26 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Retirement; Retirement Policies

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