IDEAS home Printed from https://ideas.repec.org/a/ucp/jlabec/v24y2006i3p661-700.html
   My bibliography  Save this article

Bias-Corrected Estimates of GED Returns

Author

Listed:
  • James J. Heckman

    (University of Chicago and American Bar Foundation)

  • Paul A. LaFontaine

    (Center for Social Program Evaluation, American Bar Foundation)

Abstract

Using three sources of data, this article examines the direct economic return to General Educational Development (GED) certification for both native and immigrant high school dropouts. One data source—the Current Population Survey (CPS)—is plagued by nonresponse and allocation bias from the hot deck procedure that biases the estimated return to the GED upward. 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 both native-born and immigrant populations.

Suggested Citation

  • James J. Heckman & Paul A. LaFontaine, 2006. "Bias-Corrected Estimates of GED Returns," Journal of Labor Economics, University of Chicago Press, vol. 24(3), pages 661-700, July.
  • Handle: RePEc:ucp:jlabec:v:24:y:2006:i:3:p:661-700
    DOI: 10.1086/504278
    as

    Download full text from publisher

    File URL: http://dx.doi.org/10.1086/504278
    File Function: main text
    Download Restriction: Access to the online full text or PDF requires a subscription.

    File URL: https://libkey.io/10.1086/504278?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to look for a different version below or search for a different version of it.

    Other versions of this item:

    References listed on IDEAS

    as
    1. 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.
    2. 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, Institute of Labor Economics (IZA).
    3. 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.
    4. 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.
    5. Heckman, James, 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.
    6. 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.
    7. 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.
    8. 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.
    9. 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.
    10. 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.
    11. 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.
    12. 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.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Bonhomme, Stphane & Robin, Jean-Marc, 2009. "Consistent noisy independent component analysis," Journal of Econometrics, Elsevier, vol. 149(1), pages 12-25, April.
    2. Heckman, James J. & Urzúa, Sergio, 2010. "Comparing IV with structural models: What simple IV can and cannot identify," Journal of Econometrics, Elsevier, vol. 156(1), pages 27-37, May.
    3. Jaap Abbring & James Heckman, 2008. "Dynamic policy analysis," CeMMAP working papers CWP05/08, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    4. Seki, Mai, 2014. "Heterogeneous Returns to U.S. College Selectivity and the Value of Graduate Degree Attainment," CLSSRN working papers clsrn_admin-2014-53, Vancouver School of Economics, revised 25 Nov 2014.
    5. Conti, Gabriella & Frühwirth-Schnatter, Sylvia & Heckman, James J. & Piatek, Rémi, 2014. "Bayesian exploratory factor analysis," Journal of Econometrics, Elsevier, vol. 183(1), pages 31-57.
    6. Pablo Lavado & Nelson Oviedo & Hernán Ruffo, 2016. "Destruction of Cognitive and Noncognitive Skills in Adulthood," Working Papers 16-07, Centro de Investigación, Universidad del Pacífico.
    7. Heckman, James J. & Humphries, John Eric & Veramendi, Gregory & Urzua, Sergio, 2014. "Education, Health and Wages," IZA Discussion Papers 8027, Institute of Labor Economics (IZA).
    8. Sarafidis, Vasilis & Yamagata, Takashi, 2010. "Instrumental Variable Estimation of Dynamic Linear Panel Data Models with Defactored Regressors under Cross-sectional Dependence," MPRA Paper 25182, University Library of Munich, Germany.
    9. Peter A. Savelyev & Kegon T. K. Tan, 2019. "Socioemotional Skills, Education, and Health-Related Outcomes of High-Ability Individuals," American Journal of Health Economics, MIT Press, vol. 5(2), pages 250-280, Spring.
    10. Anirban Basu & James J. Heckman & Salvador Navarro-Lozano & Sergio Urzua, 2007. "Use of instrumental variables in the presence of heterogeneity and self-selection: an application to treatments of breast cancer patients," Health Economics, John Wiley & Sons, Ltd., vol. 16(11), pages 1133-1157.
    11. James J. Heckman, 2008. "Econometric Causality," International Statistical Review, International Statistical Institute, vol. 76(1), pages 1-27, April.
    12. Hansen, Karsten T. & Heckman, James J. & Mullen, K.J.Kathleen J., 2004. "The effect of schooling and ability on achievement test scores," Journal of Econometrics, Elsevier, vol. 121(1-2), pages 39-98.
    13. Norkutė, Milda & Sarafidis, Vasilis & Yamagata, Takashi & Cui, Guowei, 2021. "Instrumental variable estimation of dynamic linear panel data models with defactored regressors and a multifactor error structure," Journal of Econometrics, Elsevier, vol. 220(2), pages 416-446.
    14. Bernal, Pedro & Mittag, Nikolas & Qureshi, Javaeria A., 2016. "Estimating effects of school quality using multiple proxies," Labour Economics, Elsevier, vol. 39(C), pages 1-10.
    15. Flavio Cunha & James J. Heckman & Susanne M. Schennach, 2010. "Estimating the Technology of Cognitive and Noncognitive Skill Formation," Econometrica, Econometric Society, vol. 78(3), pages 883-931, May.
    16. Anna Thum-Thysen, 2016. "Employment chances of immigrants and their children in Germany: does sense of personal control matter?," IZA Journal of Migration and Development, Springer;Forschungsinstitut zur Zukunft der Arbeit GmbH (IZA), vol. 5(1), pages 1-25, December.
    17. repec:diw:diwwpp:dp1240 is not listed on IDEAS
    18. Thomas Andren & Daniela Andren, 2006. "Assessing the employment effects of vocational training using a one-factor model," Applied Economics, Taylor & Francis Journals, vol. 38(21), pages 2469-2486.
    19. Heckman, James J. & Navarro, Salvador, 2007. "Dynamic discrete choice and dynamic treatment effects," Journal of Econometrics, Elsevier, vol. 136(2), pages 341-396, February.
    20. David Bravo Urrutia & Claudia Sanhueza & sergio Urzúa, 2007. "Ability, Schooling Choices And Gender Labor Market Discrimination: Evidence For Chile," Working Papers wp265, University of Chile, Department of Economics.
    21. Edwards, Rebecca & Gibson, Rachael & Harmon, Colm & Schurer, Stefanie, 2022. "First-in-their-family students at university: Can non-cognitive skills compensate for social origin?," Economics of Education Review, Elsevier, vol. 91(C).

    More about this item

    JEL classification:

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

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:ucp:jlabec:v:24:y:2006:i:3:p:661-700. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Journals Division (email available below). General contact details of provider: https://www.journals.uchicago.edu/JOLE .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.