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Representativeness of the Low-Income Population in the Health and Retirement Study

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  • Erik Meijer

    (University of Southern California and RAND Corporation)

  • Lynn A. Karoly

    (RAND Corporation)

Abstract

We study to what extent the Health and Retirement Study (HRS) is representative of all income groups, but with a particular emphasis on low-income groups. To focus on the HRS sample composition and abstract from potential measurement issues associated with measures of income and program participation, we exploit the SSA administrative data matched to the HRS sample and compare their distribution against the distribution of the same variables for the same population in the SSA databases. We find that overall, for cohorts and years that can be most reliably compared, the distributions are very similar and conclude that the HRS is representative for the population it covers. However, for some subgroups in the low-income population (e.g., recipients of Supplemental Security Income, Medicaid beneficiaries), there are some differences and thus we caution against estimating population totals for such small subpopulations. The HRS samples for which restricted matched administrative data are available are often not representative of a broad population of interest, because not all HRS respondents were asked permission to match in any given year. Therefore, the restricted HRS datafiles are generally not suitable for estimating population distributions, although they are still very useful for modeling purposes.

Suggested Citation

  • Erik Meijer & Lynn A. Karoly, 2013. "Representativeness of the Low-Income Population in the Health and Retirement Study," Working Papers wp273, University of Michigan, Michigan Retirement Research Center.
  • Handle: RePEc:mrr:papers:wp273
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    References listed on IDEAS

    as
    1. F. Thomas Juster & Richard Suzman, 1995. "An Overview of the Health and Retirement Study," Journal of Human Resources, University of Wisconsin Press, vol. 30, pages 7-56.
    2. 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.
    3. David Card & Andrew K.G. Hildreth & Lara D. Shore-Sheppard, 2004. "The Measurement of Medicaid Coverage in the SIPP: Evidence From a Comparison of Matched Records," Journal of Business & Economic Statistics, American Statistical Association, vol. 22, pages 410-420, October.
    4. 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.
    5. repec:mpr:mprres:6195 is not listed on IDEAS
    6. Peter Adams & Michael D. Hurd & Daniel L. McFadden & Angela Merrill & Tiago Ribeiro, 2004. "Healthy, Wealthy, and Wise? Tests for Direct Causal Paths between Health and Socioeconomic Status," NBER Chapters, in: Perspectives on the Economics of Aging, pages 415-526, National Bureau of Economic Research, Inc.
    7. Haider, S. & Solon, G., 2000. "Nonrandom Selection in the HRS Social Security Earnings Sample," Papers 00-01, RAND - Labor and Population Program.
    8. Haider, S. & Solon, G., 2000. "Nonrandom Selection in the HRS Social Security Earnings Sample," Papers 00-01, RAND - Labor and Population Program.
    9. 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 743, RAND Corporation.
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    Cited by:

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