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Response Error in Earnings Functions for Nonblack Males

Author

Listed:
  • William T. Bielby

    (University of California-Santa Barbara)

  • Robert M. Hauser

    (University of Wisconsin-Madison)

Abstract

Biases due to measurement errors in an earnings function for nonblack males are assessed by estimating unobserved variable models with data from the Income Supplement Reinterview program of the March 1973 Current Population Survey and from the remeasurement program of the 1973 Occupational Changes in a Generation-II survey. We find that reports of social origins, educational and occupational attainments, labor supply, and earnings of nonblack males are subject to primarily random response errors. Logarithmic earnings is one of the most accurately measured indicators of socioeconomic success. Further, retrospective reports of status variables are as reliable as contemporaneous reports. When measurement errors are ignored for nonblacks, the total economic return to schooling is underestimated by about 16% and the effects of some background variables are underestimated by as much as 15%. The total effects offirst and current job status are underestimated by about 20% when measurement errors are ignored, as are the unmediated effects of current job status. Conflicting evidence is presented on whether respondents tend to understate the consistency between their earnings and educational attainments in the Current Population Survey. If there is such a tendency, unmediated effects of education are modestly understated when response errors are ignored, and they are overstated if no such tendency exists.

Suggested Citation

  • William T. Bielby & Robert M. Hauser, 1977. "Response Error in Earnings Functions for Nonblack Males," Sociological Methods & Research, , vol. 6(2), pages 241-280, November.
    • Handle: RePEc:sae:somere:v:6:y:1977:i:2:p:241-280
    DOI: 10.1177/004912417700600207
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    References listed on IDEAS

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    1. Alan S. Blinder, 1976. "On Dogmatism in Human Capital Theory," Journal of Human Resources, University of Wisconsin Press, vol. 11(1), pages 8-22.
    2. Bowles, Samuel, 1972. "Schooling and Inequality from Generation to Generation," Journal of Political Economy, University of Chicago Press, vol. 80(3), pages 219-251, Part II, .
    3. Mark R. Rosenzweig, 1976. "Nonlinear Earnings Functions, Age, and Experience: A Nondogmatic Reply and Some Additional Evidence," Journal of Human Resources, University of Wisconsin Press, vol. 11(1), pages 23-27.
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    1. Gary S. Becker & Nigel Tomes, 1994. "Human Capital and the Rise and Fall of Families," NBER Chapters, in: Human Capital: A Theoretical and Empirical Analysis with Special Reference to Education, Third Edition, pages 257-298, National Bureau of Economic Research, Inc.
    2. Sajid Amin Javed & Mohammad Irfan, 2014. "Intergenerational Mobility: Evidence from Pakistan Panel Household Survey," The Pakistan Development Review, Pakistan Institute of Development Economics, vol. 53(2), pages 175-203.
    3. Grawe, Nathan D., 2003. "Life Cycle Bias in the Estimation of Intergenerational Earnings Persistence," Analytical Studies Branch Research Paper Series 2003207e, Statistics Canada, Analytical Studies Branch.
    4. G. Warriner, 1991. "Accuracy of self-reports to the burdensome question: survey response and nonresponse error trade-offs," Quality & Quantity: International Journal of Methodology, Springer, vol. 25(3), pages 253-269, August.
    5. René Böheim & Christina Judmayr, 2014. "Chancengleichheit in Österreich," Working Paper Reihe der AK Wien - Materialien zu Wirtschaft und Gesellschaft 134, Kammer für Arbeiter und Angestellte für Wien, Abteilung Wirtschaftswissenschaft und Statistik.

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