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Math and Gender: Is Math a Route to a High-Powered Career?

Author

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  • Joensen, Juanna Schrøter

    () (University of Chicago)

  • Nielsen, Helena Skyt

    () (Aarhus University)

Abstract

There is a large gender gap in advanced math coursework in high school that many believe exists because girls are discouraged from taking math courses. In this paper, we exploit an institutional change that reduced the costs of acquiring advanced high school math to determine if access is, in fact, the mechanism – in particular for girls at the top of the math ability distribution. By estimating marginal treatment effects of acquiring advanced math qualifications, we document substantial beneficial wage effects from encouraging even more females to opt for these qualifications. Our analysis suggests that the beneficial effect comes from accelerating graduation and attracting females to high-paid or traditionally male-dominated career tracks and to CEO positions. Our results may be reconciled with experimental and empirical evidence suggesting there is a pool of unexploited math talent among high ability girls that may be retrieved by changing the institutional set-up of math teaching.

Suggested Citation

  • Joensen, Juanna Schrøter & Nielsen, Helena Skyt, 2013. "Math and Gender: Is Math a Route to a High-Powered Career?," IZA Discussion Papers 7164, Institute for the Study of Labor (IZA).
  • Handle: RePEc:iza:izadps:dp7164
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    References listed on IDEAS

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    1. Claudia Goldin & Lawrence F. Katz & Ilyana Kuziemko, 2006. "The Homecoming of American College Women: The Reversal of the College Gender Gap," Journal of Economic Perspectives, American Economic Association, vol. 20(4), pages 133-156, Fall.
    2. Muriel Niederle & Lise Vesterlund, 2010. "Explaining the Gender Gap in Math Test Scores: The Role of Competition," Journal of Economic Perspectives, American Economic Association, vol. 24(2), pages 129-144, Spring.
    3. Joseph G. Altonji & Erica Blom & Costas Meghir, 2012. "Heterogeneity in Human Capital Investments: High School Curriculum, College Major, and Careers," Annual Review of Economics, Annual Reviews, vol. 4(1), pages 185-223, July.
    4. Bedard, Kelly & Cho, Insook, 2010. "Early gender test score gaps across OECD countries," Economics of Education Review, Elsevier, vol. 29(3), pages 348-363, June.
    5. Muriel Niederle & Lise Vesterlund, 2007. "Do Women Shy Away From Competition? Do Men Compete Too Much?," The Quarterly Journal of Economics, Oxford University Press, vol. 122(3), pages 1067-1101.
    6. James J. Heckman & Sergio Urzua & Edward Vytlacil, 2006. "Understanding Instrumental Variables in Models with Essential Heterogeneity," The Review of Economics and Statistics, MIT Press, vol. 88(3), pages 389-432, August.
    7. Örs, Evren & Palomino, Frédéric & Peyrache, Eloïc, 2008. "Performance Gender-Gap: Does Competition Matter?," CEPR Discussion Papers 6891, C.E.P.R. Discussion Papers.
    8. Smith, Nina & Smith, Valdemar & Verner, Mette, 2011. "Why Are So Few Females Promoted into CEO and Vice-President Positions? Danish Empirical Evidence 1997-2007," IZA Discussion Papers 5961, Institute for the Study of Labor (IZA).
    9. Juanna Schrøter Joensen & Helena Skyt Nielsen, 2009. "Is there a Causal Effect of High School Math on Labor Market Outcomes?," Journal of Human Resources, University of Wisconsin Press, vol. 44(1).
    10. Marianne Bertrand & Claudia Goldin & Lawrence F. Katz, 2010. "Dynamics of the Gender Gap for Young Professionals in the Financial and Corporate Sectors," American Economic Journal: Applied Economics, American Economic Association, vol. 2(3), pages 228-255, July.
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    Cited by:

    1. Elena Mattana & Juanna Joensen, 2014. "Student Aid, Academic Achievement, and Labor Market Behavior: Grants or Loans?," 2014 Meeting Papers 707, Society for Economic Dynamics.
    2. Anna Dreber & Emma Essen & Eva Ranehill, 2014. "Gender and competition in adolescence: task matters," Experimental Economics, Springer;Economic Science Association, vol. 17(1), pages 154-172, March.

    More about this item

    Keywords

    math; instrumental variable; gender; career choice; high school curriculum;

    JEL classification:

    • I21 - Health, Education, and Welfare - - Education - - - Analysis of Education
    • J24 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Human Capital; Skills; Occupational Choice; Labor Productivity

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