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Measurement Error in Long-term Retrospective Recall Surveys Of Earnings


  • John Gibson

    () (University of Waikato)

  • Bonggeun Kim

    (University of Waikato and Sungkyunkwan University, Korea)


Several recent studies in labour and population economics use retrospective surveys to substitute for the high cost and limited availability of longitudinal survey data. Although a single interview can obtain a lifetime history, inaccurate long-term recall could make such retrospective surveys a poor substitute for longitudinal surveys, especially if it induces non-classical error that makes conventional statistical corrections less effective. In this paper, we use the unique Panel Study of Income Dynamics Validation Study to assess the accuracy of long-term recall data. We find underreporting of transitory events. This recall error creates a non-classical measurement error problem. A limited cost-benefit analysis is also conducted, showing how savings from using a cheaper retrospective recall survey might be compared with the cost of applying the less accurate recall data to a specific policy objective such as designing transfers to reduce chronic poverty.

Suggested Citation

  • John Gibson & Bonggeun Kim, 2007. "Measurement Error in Long-term Retrospective Recall Surveys Of Earnings," Working Papers in Economics 07/03, University of Waikato.
  • Handle: RePEc:wai:econwp:07/03

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    References listed on IDEAS

    1. Megan Beckett & Julie Da Vanzo & Narayan Sastry & Constantijn Panis & Christine Peterson, 2001. "The Quality of Retrospective Data: An Examination of Long-Term Recall in a Developing Country," Journal of Human Resources, University of Wisconsin Press, vol. 36(3), pages 593-625.
    2. Chaudhuri, Shubham & Ravallion, Martin, 1994. "How well do static indicators identify the chronically poor?," Journal of Public Economics, Elsevier, vol. 53(3), pages 367-394, March.
    3. Luttmer,Erzo F.P., 2001. "Measuring poverty dynamics and inequality in transition economies - disentangling real events from noisy data," Policy Research Working Paper Series 2549, The World Bank.
    4. 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.
    5. Pischke, Jorn-Steffen, 1995. "Measurement Error and Earnings Dynamics: Some Estimates from the PSID Validation Study," Journal of Business & Economic Statistics, American Statistical Association, vol. 13(3), pages 305-314, July.
    6. H. Elizabeth Peters, 1988. "Retrospective Versus Panel Data in Analyzing Lifecycle Events," Journal of Human Resources, University of Wisconsin Press, vol. 23(4), pages 488-513.
    7. James P. Smith & Duncan Thomas, 2003. "Remembrances of things past: test-retest reliability of retrospective migration histories," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 166(1), pages 23-49.
    8. Gillian Paull, 2002. "Biases in the reporting of labour market dynamics," IFS Working Papers W02/10, Institute for Fiscal Studies.
    9. Bonggeun Kim & Gary Solon, 2005. "Implications of Mean-Reverting Measurement Error for Longitudinal Studies of Wages and Employment," The Review of Economics and Statistics, MIT Press, vol. 87(1), pages 193-196, February.
    10. Bound, John, et al, 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.
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    Cited by:

    1. Le Wang, 2013. "How Does Education Affect the Earnings Distribution in Urban China?," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 75(3), pages 435-454, June.

    More about this item


    longitudinal data; measurement error; retrospective surveys;

    JEL classification:

    • C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models
    • J64 - Labor and Demographic Economics - - Mobility, Unemployment, Vacancies, and Immigrant Workers - - - Unemployment: Models, Duration, Incidence, and Job Search

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