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

  • Arie Kapteyn
  • Pierre-Carl Michaud
  • James P. Smith
  • Arthur van Soest

The authors 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. They 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, they 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. They 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.

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File URL: http://www.rand.org/content/dam/rand/pubs/working_papers/2006/RAND_WR407.pdf
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Paper provided by RAND Corporation Publications Department in its series Working Papers with number 407.

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Length: 42 pages
Date of creation: Jul 2006
Date of revision:
Handle: RePEc:ran:wpaper:407
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  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, J.L. & Manski, C.F., 1995. "Censoring of Outcomes and Regressors Due to Survey Nonresponse: Identification and estimation Using Weights and Imputations," Working Papers 95-12, University of Iowa, Department of Economics.
  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 455-73, March.
  5. O. Attanasio & H. W. Hoynes, . "Differential mortality and wealth accumulation," Institute for Research on Poverty Discussion Papers 1079-96, University of Wisconsin Institute for Research on Poverty.
  6. Haider, S. & Solon, G., 2000. "Nonrandom Selection in the HRS Social Security Earnings Sample," Papers 00-01, RAND - Labor and Population Program.
  7. 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.
  8. Lee A. Lillard & Constantijn W. A. Panis, 1998. "Panel Attrition from the Panel Study of Income Dynamics: Household Income, Marital Status, and Mortality," Journal of Human Resources, University of Wisconsin Press, vol. 33(2), pages 437-457.
  9. 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.
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