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Bias Corrected Estimates of GED Returns

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  • James J. Heckman
  • Paul LaFontaine

Abstract

Using three sources of data, this paper examines the direct economic return to GED certification for both native and immigrant high school dropouts. One data source - the CPS - is plagued by non-response and allocation bias from the hot-deck procedure that biases upward the estimated return to the GED. Correcting for allocation bias and ability bias, there is no direct economic return to GED certification. An apparent return to GED certification with age found in the raw CPS data is due to dropouts becoming more skilled over time. These results apply to native born as well as immigrant populations.

Suggested Citation

  • James J. Heckman & Paul LaFontaine, 2006. "Bias Corrected Estimates of GED Returns," NBER Working Papers 12018, National Bureau of Economic Research, Inc.
    • Handle: RePEc:nbr:nberwo:12018
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    References listed on IDEAS

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    1. Melissa Clark & David Jaeger, 2006. "Natives, the foreign-born and high school equivalents: new evidence on the returns to the GED," Journal of Population Economics, Springer;European Society for Population Economics, vol. 19(4), pages 769-793, October.
    2. Pedro Carneiro & Karsten T. Hansen & James J. Heckman, 2003. "Estimating Distributions of Treatment Effects with an Application to the Returns to Schooling and Measurement of the Effects of Uncertainty on College," NBER Working Papers 9546, National Bureau of Economic Research, Inc.
    3. Angrist, Joshua D. & Krueger, Alan B., 1999. "Empirical strategies in labor economics," Handbook of Labor Economics, in: O. Ashenfelter & D. Card (ed.), Handbook of Labor Economics, edition 1, volume 3, chapter 23, pages 1277-1366, Elsevier.
    4. Carneiro, Pedro & Hansen, Karsten T. & Heckman, James J., 2003. "Estimating Distributions of Treatment Effects with an Application to the Returns to Schooling and Measurement of the Effects of Uncertainty on College Choice," IZA Discussion Papers 767, IZA Network @ LISER.
    5. Barry T. Hirsch & Edward J. Schumacher, 2004. "Match Bias in Wage Gap Estimates Due to Earnings Imputation," Journal of Labor Economics, University of Chicago Press, vol. 22(3), pages 689-722, July.
    6. James Heckman, 2013. "Sample selection bias as a specification error," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 31(3), pages 129-137.
    7. John M. Barron & Mark C. Berger & Dan A. Black, 2006. "Selective Counteroffers," Journal of Labor Economics, University of Chicago Press, vol. 24(3), pages 385-410, July.
    8. Marco Manacorda, 2004. "Can the Scala Mobile Explain the Fall and Rise of Earnings Inequality in Italy? A Semiparametric Analysis, 19771993," Journal of Labor Economics, University of Chicago Press, vol. 22(3), pages 585-614, July.
    9. Pedro Carneiro & Karsten T. Hansen & James J. Heckman, 2003. "2001 Lawrence R. Klein Lecture Estimating Distributions of Treatment Effects with an Application to the Returns to Schooling and Measurement of the Effects of Uncertainty on College Choice," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 44(2), pages 361-422, May.
    10. James J. Heckman & Jora Stixrud & Sergio Urzua, 2006. "The Effects of Cognitive and Noncognitive Abilities on Labor Market Outcomes and Social Behavior," Journal of Labor Economics, University of Chicago Press, vol. 24(3), pages 411-482, July.
    11. Richard J. Murnane & John B. Willett & Kathryn Parker Boudett, 1999. "Do Male Dropouts Benefit from Obtaining a GED, Postsecondary Education, and Training?," Evaluation Review, , vol. 23(5), pages 475-503, October.
    12. Cameron, Stephen V & Heckman, James J, 1993. "The Nonequivalence of High School Equivalents," Journal of Labor Economics, University of Chicago Press, vol. 11(1), pages 1-47, January.
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    JEL classification:

    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis

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