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Measurement Error in Human Capital and the Black-White Wage Gap

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  • Christopher R. Bollinger

    (University of Kentucky)

Abstract

Proxy variables are frequently used in economics to control for unavailable variables in a linear regression setting. For example, AFQT scores have been used to control for human capital accumulation in measuring black-white wage differentials. This practice may bias the coefficient estimates for the correctly measured variables as well. This paper models proxy variables as a measurement error process and derives bounds for the coefficients on the correctly measured variables under a variety of assumptions. The results show that the coefficient on race in a linear regression is an overstatement of the actual black-white wage gap. Sensitivity analysis suggests that if human capital could be correctly measured it would be unlikely that the coefficient on black would be negative. © 2003 President and Fellows of Harvard College and the Massachusetts Institute of Technology.

Suggested Citation

  • Christopher R. Bollinger, 2003. "Measurement Error in Human Capital and the Black-White Wage Gap," The Review of Economics and Statistics, MIT Press, vol. 85(3), pages 578-585, August.
    • Handle: RePEc:tpr:restat:v:85:y:2003:i:3:p:578-585
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    Citations

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    Cited by:

    1. Peter McHenry & Melissa McInerney, 2012. "Are Wage Premiums for Black Women Illusory? A Critical Examination," Working Papers 120, Department of Economics, College of William and Mary.
    2. Du, Shihan & Homrighausen, Pia & Wilke, Ralf A., 2018. "On omitted variables, proxies and unobserved effects in analysis of administrative labour market data," FDZ Methodenreport 201806_en, Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany].
    3. Chalak, Karim & Kim, Daniel & Miller, Megan & Pepper, John, 2022. "Reexamining the evidence on gun ownership and homicide using proxy measures of ownership," Journal of Public Economics, Elsevier, vol. 208(C).
    4. Elyakim Kislev, 2017. "Deciphering the ‘Ethnic Penalty’ of Immigrants in Western Europe: A Cross-Classified Multilevel Analysis," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 134(2), pages 725-745, November.
    5. Chalak, Karim & Kim, Daniel, 2020. "Measurement error in multiple equations: Tobin’s q and corporate investment, saving, and debt," Journal of Econometrics, Elsevier, vol. 214(2), pages 413-432.
    6. Brian Junker & Lynne Schofield & Lowell Taylor, 2012. "The use of cognitive ability measures as explanatory variables in regression analysis," IZA Journal of Labor Economics, Springer;Forschungsinstitut zur Zukunft der Arbeit GmbH (IZA), vol. 1(1), pages 1-19, December.
    7. Eirini-Christina Saloniki & Amanda Gosling, 2012. "Point identification in the presence of measurement error in discrete variables: application - wages and disability," Studies in Economics 1214, School of Economics, University of Kent.
    8. Aaron Chalfin & Justin McCrary, 2013. "The Effect of Police on Crime: New Evidence from U.S. Cities, 1960-2010," NBER Working Papers 18815, National Bureau of Economic Research, Inc.
    9. Rita Pető & Balázs Reizer, 2021. "Gender differences in the skill content of jobs," Journal of Population Economics, Springer;European Society for Population Economics, vol. 34(3), pages 825-864, July.
    10. Bělín, Matěj, 2020. "Time-invariant regressors under fixed effects: Simple identification via a proxy variable," Economics Letters, Elsevier, vol. 186(C).
    11. Schofield, Lynne Steuerle, 2014. "Measurement error in the AFQT in the NLSY79," Economics Letters, Elsevier, vol. 123(3), pages 262-265.
    12. Jonathan Fisher & Christina Houseworth, 2012. "The reverse wage gap among educated White and Black women," The Journal of Economic Inequality, Springer;Society for the Study of Economic Inequality, vol. 10(4), pages 449-470, December.
    13. Christopher R. Bollinger & Amitabh Chandra, 2005. "Iatrogenic Specification Error: A Cautionary Tale of Cleaning Data," Journal of Labor Economics, University of Chicago Press, vol. 23(2), pages 235-258, April.
    14. Jungmin Lee & Sokbae Lee, 2012. "Does it Matter WHO Responded to the Survey? Trends in the U.S. Gender Earnings Gap Revisited," ILR Review, Cornell University, ILR School, vol. 65(1), pages 148-160, January.
    15. Naven, Matthew, 2020. "Within-School Heterogeneity in Quality: Do Schools Provide Equal Value Added to All Students?," MPRA Paper 100123, University Library of Munich, Germany.
    16. Black Dan & Daniel Kermit & Smith Jeffrey, 2005. "College Quality and Wages in the United States," German Economic Review, De Gruyter, vol. 6(3), pages 415-443, August.
    17. Engzell, Per, 2017. "What Do Books in the Home Proxy For? A Cautionary Tale," Working Paper Series 1/2016, Stockholm University, Swedish Institute for Social Research.
    18. Nikolas Mittag, 2013. "A Method Of Correcting For Misreporting Applied To The Food Stamp Program," Working Papers 13-28, Center for Economic Studies, U.S. Census Bureau.
    19. Francis J. DiTraglia & Camilo Garcia-Jimeno, 2020. "A Framework for Eliciting, Incorporating, and Disciplining Identification Beliefs in Linear Models," Papers 2011.07276, arXiv.org.
    20. Zhang, Fan & Polyakov, Maksym & Fogarty, James & Pannell, David, 2016. "The Capitalized Value of Rainwater Tanks in the Property Market of Perth, Australia," Working Papers 246968, University of Western Australia, School of Agricultural and Resource Economics.
    21. repec:iab:iabfme:201806(en is not listed on IDEAS
    22. de New, Sonja C. & Schurer, Stefanie & Leung, Felix, 2015. "Testing the Validity of Item Non-Response as a Proxy for Cognitive and Non-Cognitive Skills," IZA Discussion Papers 8874, Institute of Labor Economics (IZA).
    23. Dan A. Black & Jeffrey A. Smith, 2006. "Estimating the Returns to College Quality with Multiple Proxies for Quality," Journal of Labor Economics, University of Chicago Press, vol. 24(3), pages 701-728, July.

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