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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)

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    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.

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    File URL: http://www.mitpressjournals.org/doi/pdf/10.1162/003465303322369731
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    Bibliographic Info

    Article provided by MIT Press in its journal Review of Economics and Statistics.

    Volume (Year): 85 (2003)
    Issue (Month): 3 (August)
    Pages: 578-585

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    Handle: RePEc:tpr:restat:v:85:y:2003:i:3:p:578-585

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    Web page: http://mitpress.mit.edu/journals/

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    Web: http://mitpress.mit.edu/journal-home.tcl?issn=00346535

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    Cited by:
    1. Jonathan Fisher & Christina Houseworth, 2012. "The reverse wage gap among educated White and Black women," Journal of Economic Inequality, Springer, vol. 10(4), pages 449-470, December.
    2. 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, Department of Economics, University of Kent.
    3. 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.
    4. Schofield, Lynne Steuerle, 2014. "Measurement error in the AFQT in the NLSY79," Economics Letters, Elsevier, vol. 123(3), pages 262-265.

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