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Enhancing the Quality of Data on Income: Recent Innovations from the HRS

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  • Michael Hurd
  • F. Thomas Juster
  • James P. Smith

Abstract

This paper evaluates two survey innovations introduced in the HRS that aimed to improve income measurement. The innovations are (1) the integration of questions for income and wealth and (2) matching the periodicity over which income questions are asked to the typical way such income is received. Both innovations had significant impacts in improving the quality of income reports. For example, the integration of income questions into the asset module produced in HRS an across-wave 63 percent increase in the amount of income derived from financial assets, real estate investments and farm and business equity. Similarly, asking respondents to answer using a time interval consistent with how income is received substantially improved the quality of reports on social security income. Fortunately, we also suggest ways that these innovations can be introduced into other major social science surveys.

Suggested Citation

  • Michael Hurd & F. Thomas Juster & James P. Smith, 2003. "Enhancing the Quality of Data on Income: Recent Innovations from the HRS," Journal of Human Resources, University of Wisconsin Press, vol. 38(3).
    • Handle: RePEc:uwp:jhriss:v:38:y:2003:i:3:p758-772
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    Cited by:

    1. Michele Lalla & Maddalena Cavicchioli, 2020. "Nonresponse and measurement errors in income: matching individual survey data with administrative tax data," Department of Economics 0170, University of Modena and Reggio E., Faculty of Economics "Marco Biagi".
    2. Grafova, Irina B. & Freedman, Vicki A. & Lurie, Nicole & Kumar, Rizie & Rogowski, Jeannette, 2014. "The difference-in-difference method: Assessing the selection bias in the effects of neighborhood environment on health," Economics & Human Biology, Elsevier, vol. 13(C), pages 20-33.
    3. Bridget Hiedemann & Michelle Sovinsky & Steven Stern, 2018. "Will You Still Want Me Tomorrow?: The Dynamics of Families’ Long-Term Care Arrangements," Journal of Human Resources, University of Wisconsin Press, vol. 53(3), pages 663-716.
    4. Michael Hurd & Susann Rohwedder, 2006. "Consumption and Economic Well-Being at Older Ages: Income- and Consumption-Based Poverty Measures in the HRS," Working Papers wp110, University of Michigan, Michigan Retirement Research Center.
    5. Michael D. Hurd & Susann Rohwedder, 2013. "Wealth Dynamics and Active Saving at Older Ages," NBER Chapters, in: Improving the Measurement of Consumer Expenditures, pages 388-413, National Bureau of Economic Research, Inc.
    6. James P. Smith, 2003. "Trends and Projections in Income Replacement during Retirement," Journal of Labor Economics, University of Chicago Press, vol. 21(4), pages 755-782, October.
    7. Michelle Sovinsky & Steven Stern, 2016. "Dynamic modelling of long-term care decisions," Review of Economics of the Household, Springer, vol. 14(2), pages 463-488, June.
    8. Maddalena Cavicchioli & Michele Lalla, 2022. "Evidences from survey data and fiscal data: nonresponse and measurement errors in annual incomes," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 31(3), pages 587-615, September.
    9. F. Thomas Juster & Joseph P. Lupton & Honggao Cao, 2002. "Ensuring Time-Series Consistency in Estimates of Income and Wealth," Working Papers wp030, University of Michigan, Michigan Retirement Research Center.
    10. James Banks & Michael Marmot & Zoe Oldfield & James P. Smith, 2009. "The SES Health Gradient on Both Sides of the Atlantic," NBER Chapters, in: Developments in the Economics of Aging, pages 359-406, National Bureau of Economic Research, Inc.
    11. Duane F. Alwin & Kristina Zeiser & Don Gensimore, 2014. "Reliability of Self-reports of Financial Data in Surveys," Sociological Methods & Research, , vol. 43(1), pages 98-136, February.
    12. Essig, Lothar, 2005. "Methodological aspects of the SAVE data set," Papers 05-17, Sonderforschungsbreich 504.
    13. Michael D. Hurd & Susann Rohwedder, 2006. "Economic Well-Being at Older Ages: Income- and Consumption-Based Poverty Measures in the HRS," NBER Working Papers 12680, National Bureau of Economic Research, Inc.
    14. ChangHwan Kim & Christopher R. Tamborini, 2014. "Response Error in Earnings," Sociological Methods & Research, , vol. 43(1), pages 39-72, February.
    15. Thomas Juster & Honggao Cao & Mick Couper & Daniel Hill & Michael Hurd & Joseph Lupton & Michael Perry & James Smith, 2007. "Enhancing the Quality of Data on the Measurement of Income and Wealth," Working Papers wp151, University of Michigan, Michigan Retirement Research Center.
    16. Deborah S. DeGraff & Rebeca Wong & Karina Orozco-Rocha, 2018. "Dynamics of Economic Security Among the Aging in Mexico: 2001–2012," Population Research and Policy Review, Springer;Southern Demographic Association (SDA), vol. 37(1), pages 59-90, February.
    17. Julie Zissimopoulos & Lynn A. Karoly & Qian Gu, 2010. "Liquidity Constraints, Household Wealth, and Self-Employment The Case of Older Workers," Working Papers 725, RAND Corporation.
    18. Michael D. Hurd & Susann Rohwedder, 2006. "Economic Well-Being at Older Ages: Income- and Consumption-Based Poverty Measures in the HRS," NBER Working Papers 12680, National Bureau of Economic Research, Inc.
    19. Julie Zissimopoulos & Lynn A. Karoly & Qian Gu, 2010. "Liquidity Constraints, Household Wealth, and Self-Employment The Case of Older Workers," Working Papers WR-725, RAND Corporation.
    20. Michele Lalla & Patrizio Frederic & Daniela Mantovani, 2022. "The inextricable association of measurement errors and tax evasion as examined through a microanalysis of survey data matched with fiscal data: a case study," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 31(5), pages 1375-1401, December.
    21. Adam Bee & Irena Dushi & Joshua Mitchell & Brad Trenkamp, 2024. "Measuring Income of the Aged in Household Surveys: Evidence from Linked Administrative Records," Working Papers 24-32, Center for Economic Studies, U.S. Census Bureau.

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