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Measurement Error in Earnings Data in the Health and Retirement Study

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  • Jesse Bricker
  • Gary V. Engelhardt

    (Center for Retirement Research, Boston College)

Abstract

We provide new evidence on the extent of measurement error in respondent-reported earnings data by exploiting detailed W-2 records matched to older workers in the Health and Retirement Study (HRS). Our empirical findings are qualitatively consistent with the findings of previous studies. Mean measurement error in the 1991 HRS earnings data for men is somewhat larger than what has been found in other validation studies, but is still modest, averaging about 0.059 log points, approximately 5.9 percent, or $1,500. For women in 1991, it is 0.067 log points, approximately 6.7 percent, or $916. We find a negative correlation between the measurement error and the true value of earnings as measured by the W-2 records, which indicates the presence of non-classical measurement error. For men and women, this error shows little correlation with a standard set of cross-sectional earnings determinants. The one exception is that the measurement error rises with reported education. The bias on the OLS parameter estimate of the impact of having a college degree or higher (relative to a high school drop-out) from using the respondent-reported rather than the W-2 earnings is positive and estimated to be 0.071 log points, or roughly a bias of 7 percent.

Suggested Citation

  • Jesse Bricker & Gary V. Engelhardt, 2007. "Measurement Error in Earnings Data in the Health and Retirement Study," Working Papers, Center for Retirement Research at Boston College wp2007-16, Center for Retirement Research, revised Oct 2007.
    • Handle: RePEc:crr:crrwps:wp2007-16
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    References listed on IDEAS

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    1. Bollinger, Christopher R, 1998. "Measurement Error in the Current Population Survey: A Nonparametric Look," Journal of Labor Economics, University of Chicago Press, vol. 16(3), pages 576-594, July.
    2. Duncan, Greg J & Hill, Daniel H, 1985. "An Investigation of the Extent and Consequences of Measurement Error in Labor-Economic Survey Data," Journal of Labor Economics, University of Chicago Press, vol. 3(4), pages 508-532, October.
    3. Steven Haider & Gary Solon, 2006. "Life-Cycle Variation in the Association between Current and Lifetime Earnings," American Economic Review, American Economic Association, vol. 96(4), pages 1308-1320, September.
    4. Thomas J. Kane & Cecilia E. Rouse & Douglas Staiger, 1999. "Estimating Returns to Schooling When Schooling is Misreported," Working Papers 798, Princeton University, Department of Economics, Industrial Relations Section..
    5. Leora Friedberg, 2000. "The Labor Supply Effects of the Social Security Earnings Test," The Review of Economics and Statistics, MIT Press, vol. 82(1), pages 48-63, February.
    6. Richard Disney & Sarah Smith, 2002. "The Labour Supply Effect of the Abolition of the Earnings Rule for Older Workers in the United Kingdom," Economic Journal, Royal Economic Society, vol. 112(478), pages 136-152, March.
    7. Bound, John & Brown, Charles & Mathiowetz, Nancy, 2001. "Measurement error in survey data," Handbook of Econometrics, in: J.J. Heckman & E.E. Leamer (ed.), Handbook of Econometrics, edition 1, volume 5, chapter 59, pages 3705-3843, Elsevier.
    8. Bound, John & Krueger, Alan B, 1991. "The Extent of Measurement Error in Longitudinal Earnings Data: Do Two Wrongs Make a Right?," Journal of Labor Economics, University of Chicago Press, vol. 9(1), pages 1-24, January.
    9. Gruber, Jonathan & Orszag, Peter, 2003. "Does the Social Security Earnings Test Affect Labor Supply and Benefits Receipt?," National Tax Journal, National Tax Association;National Tax Journal, vol. 56(4), pages 755-773, December.
    10. Griliches, Zvi & Hausman, Jerry A., 1986. "Errors in variables in panel data," Journal of Econometrics, Elsevier, vol. 31(1), pages 93-118, February.
    11. Cunningham, Christopher R. & Engelhardt, Gary V., 2002. "Federal Tax Policy, Employer Matching, and 401(K) Saving: Evidence From HRS W-2 Records," National Tax Journal, National Tax Association;National Tax Journal, vol. 55(3), pages 617-645, September.
    12. Arie Kapteyn & Jelmer Y. Ypma, 2007. "Measurement Error and Misclassification: A Comparison of Survey and Administrative Data," Journal of Labor Economics, University of Chicago Press, vol. 25(3), pages 513-551.
    13. Christopher D. Carroll & Andrew A. Samwick, 1998. "How Important Is Precautionary Saving?," The Review of Economics and Statistics, MIT Press, vol. 80(3), pages 410-419, August.
    14. Engelhardt, Gary V. & Kumar, Anil, 2009. "The repeal of the retirement earnings test and the labor supply of older men," Journal of Pension Economics and Finance, Cambridge University Press, vol. 8(4), pages 429-450, October.
    15. Leora Friedberg & Anthony Webb, 2006. "Persistence in Labor Supply and the Response to the Social Security Earnings Test," Working Papers, Center for Retirement Research at Boston College wp2006-27, Center for Retirement Research, revised Dec 2006.
    16. Thomas J. Kane & Cecilia Rouse & Douglas Staiger, 1999. "Estimating Returns to Schooling When Schooling is Misreported," Working Papers 798, Princeton University, Department of Economics, Industrial Relations Section..
    17. Marilyn Moon & F. Thomas Juster, 1995. "Economic Status Measures in the Health and Retirement Study," Journal of Human Resources, University of Wisconsin Press, vol. 30, pages 138-157.
    18. Richard Blundell & Ian Preston, 1998. "Consumption Inequality and Income Uncertainty," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 113(2), pages 603-640.
    19. Baker, Michael & Benjamin, Dwayne, 1999. "How do retirement tests affect the labour supply of older men?," Journal of Public Economics, Elsevier, vol. 71(1), pages 27-51, January.
    20. Haider, S. & Solon, G., 2000. "Nonrandom Selection in the HRS Social Security Earnings Sample," Papers 00-01, RAND - Labor and Population Program.
    21. Bound, John & Brown, Charles & Duncan, Greg J & Rodgers, Willard L, 1994. "Evidence on the Validity of Cross-Sectional and Longitudinal Labor Market Data," Journal of Labor Economics, University of Chicago Press, vol. 12(3), pages 345-368, July.
    22. Baker, Michael, 1997. "Growth-Rate Heterogeneity and the Covariance Structure of Life-Cycle Earnings," Journal of Labor Economics, University of Chicago Press, vol. 15(2), pages 338-375, April.
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    2. Vani Borooah & John Mangan, 2008. "Education, occupational class, and unemployment in the regions of the United Kingdom," Education Economics, Taylor & Francis Journals, vol. 16(4), pages 351-370.
    3. Gutknecht, Daniel, 2011. "Nonclassical Measurement Error in a Nonlinear (Duration) Model," Economic Research Papers 270763, University of Warwick - Department of Economics.
    4. Marjorie Honig & Irena Dushi, 2011. "How much do respondents in the health and retirement study know about their tax-deferred contribution plans? A cross-cohort comparison," Economics Working Paper Archive at Hunter College 431, Hunter College Department of Economics.

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