IDEAS home Printed from https://ideas.repec.org/p/nbr/nberwo/8964.html
   My bibliography  Save this paper

Where the boys aren't: Non-cognitive skills, returns to school and the gender gap in higher education

Author

Listed:
  • Brian A. Jacob

Abstract

Nearly 60 percent of college students today are women. Using longitudinal data on a nationally representative cohort of eighth grade students in 1988, I examine two potential explanations for the differential attendance rates of men and women -- returns to schooling and non-cognitive skills. The attendance gap is roughly five percentage points for all high school graduates. Conditional on attendance, however, there are few differences in type of college, enrollment status or selectivity of institution. The majority of the attendance gap can be explained by differences in the characteristics of men and women, despite some gender differences in the determinants of college attendance. I find that higher non-cognitive skills and college premiums among women account for nearly 90 percent of the gender gap in higher education. Interestingly, non-cognitive factors continue to influence college enrollment after controlling for high school achievement.

Suggested Citation

  • Brian A. Jacob, 2002. "Where the boys aren't: Non-cognitive skills, returns to school and the gender gap in higher education," NBER Working Papers 8964, National Bureau of Economic Research, Inc.
    • Handle: RePEc:nbr:nberwo:8964
    Note: CH ED
    as

    Download full text from publisher

    File URL: http://www.nber.org/papers/w8964.pdf
    Download Restriction: no

    References listed on IDEAS

    as
    1. Kevin M. Murphy & Finis Welch, 1992. "The Structure of Wages," The Quarterly Journal of Economics, Oxford University Press, vol. 107(1), pages 285-326.
    2. F. L. Jones, 1983. "On Decomposing the Wage Gap: A Critical Comment on Blinder's Method," Journal of Human Resources, University of Wisconsin Press, vol. 18(1), pages 126-130.
    3. Oaxaca, Ronald, 1973. "Male-Female Wage Differentials in Urban Labor Markets," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 14(3), pages 693-709, October.
    4. Altonji, Joseph G, 1993. "The Demand for and Return to Education When Education Outcomes Are Uncertain," Journal of Labor Economics, University of Chicago Press, vol. 11(1), pages 48-83, January.
    5. Alan S. Blinder, 1973. "Wage Discrimination: Reduced Form and Structural Estimates," Journal of Human Resources, University of Wisconsin Press, vol. 8(4), pages 436-455.
    6. Ronald L. Oaxaca & Michael R. Ransom, 1999. "Identification in Detailed Wage Decompositions," The Review of Economics and Statistics, MIT Press, vol. 81(1), pages 154-157, February.
    7. Murnane, Richard J & Willett, John B & Levy, Frank, 1995. "The Growing Importance of Cognitive Skills in Wage Determination," The Review of Economics and Statistics, MIT Press, vol. 77(2), pages 251-266, May.
    8. Levy, Frank & Murnane, Richard J, 1992. "U.S. Earnings Levels and Earnings Inequality: A Review of Recent Trends and Proposed Explanations," Journal of Economic Literature, American Economic Association, vol. 30(3), pages 1333-1381, September.
    9. Cotton, Jeremiah, 1988. "On the Decomposition of Wage Differentials," The Review of Economics and Statistics, MIT Press, vol. 70(2), pages 236-243, May.
    10. Reimers, Cordelia W, 1983. "Labor Market Discrimination against Hispanic and Black Men," The Review of Economics and Statistics, MIT Press, vol. 65(4), pages 570-579, November.
    11. David Neumark, 1988. "Employers' Discriminatory Behavior and the Estimation of Wage Discrimination," Journal of Human Resources, University of Wisconsin Press, vol. 23(3), pages 279-295.
    12. Oaxaca, Ronald L. & Ransom, Michael R., 1994. "On discrimination and the decomposition of wage differentials," Journal of Econometrics, Elsevier, vol. 61(1), pages 5-21, March.
    Full references (including those not matched with items on IDEAS)

    More about this item

    JEL classification:

    • I20 - Health, Education, and Welfare - - Education - - - General
    • J16 - Labor and Demographic Economics - - Demographic Economics - - - Economics of Gender; Non-labor Discrimination

    NEP fields

    This paper has been announced in the following NEP Reports:

    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:nbr:nberwo:8964. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: () or (Joanne Lustig). General contact details of provider: http://edirc.repec.org/data/nberrus.html .

    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 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.

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

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.