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Gender differences in the intention to study math increase with math performance

Author

Listed:
  • Thomas Breda

    (PSE - Paris School of Economics - UP1 - Université Paris 1 Panthéon-Sorbonne - ENS-PSL - École normale supérieure - Paris - PSL - Université Paris Sciences et Lettres - EHESS - École des hautes études en sciences sociales - ENPC - École nationale des ponts et chaussées - CNRS - Centre National de la Recherche Scientifique - INRAE - Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement, PJSE - Paris Jourdan Sciences Economiques - UP1 - Université Paris 1 Panthéon-Sorbonne - ENS-PSL - École normale supérieure - Paris - PSL - Université Paris Sciences et Lettres - EHESS - École des hautes études en sciences sociales - ENPC - École nationale des ponts et chaussées - CNRS - Centre National de la Recherche Scientifique - INRAE - Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement)

  • Elyès Jouini

    (Université Paris Dauphine-PSL - PSL - Université Paris Sciences et Lettres, CEREMADE - CEntre de REcherches en MAthématiques de la DEcision - Université Paris Dauphine-PSL - PSL - Université Paris Sciences et Lettres - CNRS - Centre National de la Recherche Scientifique)

  • Clotilde Napp

    (Université Paris Dauphine-PSL - PSL - Université Paris Sciences et Lettres, DRM - Dauphine Recherches en Management - Université Paris Dauphine-PSL - PSL - Université Paris Sciences et Lettres - CNRS - Centre National de la Recherche Scientifique)

Abstract

Even though females currently outnumber males in higher education, they remain largely underrepresented in math-related fields of study, with no sign of improvement during the past decades. To better understand which students drive this underrepresentation, we use PISA 2012 data on 251,120 15-year-old students in 61 countries to analyse boys' and girls' educational intentions along the ability distribution on math assessment tests. We analyze the percentages of boys and girls intending to pursue math-related studies or careers as a function of math performance. First, we show that for both boys and girls, there is a positive and linear relation between the probability of intending to pursue math and math performance. Second, the positive relation is stronger among boys than among girls. In particular, the gender gap in student intentions to pursue math-related studies or careers is close to zero among the poorest performers in math and increases steadily with math performance. Third, as a consequence, the gender gap in math performance, to the detriment of girls, is larger among students intending to pursue math than in the general student population.

Suggested Citation

  • Thomas Breda & Elyès Jouini & Clotilde Napp, 2023. "Gender differences in the intention to study math increase with math performance," Post-Print halshs-04155403, HAL.
    • Handle: RePEc:hal:journl:halshs-04155403
    DOI: 10.1038/s41467-023-39079-z
    Note: View the original document on HAL open archive server: https://shs.hal.science/halshs-04155403v1
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    References listed on IDEAS

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    1. Delaney, Judith M. & Devereux, Paul J., 2019. "It's Not Just for Boys! Understanding Gender Differences in STEM," IZA Discussion Papers 12176, Institute of Labor Economics (IZA).
    2. Breda, Thomas & Grenet, Julien & Monnet, Marion & Van Effenterre, Clémentine, 2020. "Do Female Role Models Reduce the Gender Gap in Science? Evidence from French High Schools," IZA Discussion Papers 13163, Institute of Labor Economics (IZA).
    3. Francine D. Blau & Lawrence M. Kahn, 2017. "The Gender Wage Gap: Extent, Trends, and Explanations," Journal of Economic Literature, American Economic Association, vol. 55(3), pages 789-865, September.
    4. Clotilde Napp & Thomas Breda, 2022. "The stereotype that girls lack talent: A worldwide investigation," Post-Print hal-03911361, HAL.
    5. Clotilde Napp & Thomas Breda, 2022. "The stereotype that girls lack talent: A worldwide investigation," Post-Print halshs-03672465, HAL.
    6. Michela Carlana, 2019. "Implicit Stereotypes: Evidence from Teachers’ Gender Bias," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 134(3), pages 1163-1224.
    7. Dan A. Black & Amelia M. Haviland & Seth G. Sanders & Lowell J. Taylor, 2008. "Gender Wage Disparities among the Highly Educated," Journal of Human Resources, University of Wisconsin Press, vol. 43(3), pages 630-659.
    8. Brown, Charles & Corcoran, Mary, 1997. "Sex-Based Differences in School Content and the Male-Female Wage Gap," Journal of Labor Economics, University of Chicago Press, vol. 15(3), pages 431-465, July.
    9. Delaney, Judith M. & Devereux, Paul J., 2019. "Understanding gender differences in STEM: Evidence from college applications✰," Economics of Education Review, Elsevier, vol. 72(C), pages 219-238.
    10. Justman, Moshe & Méndez, Susan J., 2018. "Gendered choices of STEM subjects for matriculation are not driven by prior differences in mathematical achievement," Economics of Education Review, Elsevier, vol. 64(C), pages 282-297.
    11. Clotilde Napp & Thomas Breda, 2022. "The stereotype that girls lack talent: A worldwide investigation," PSE-Ecole d'économie de Paris (Postprint) hal-03911361, HAL.
    12. Thomas Breda & Elyès Jouini & Clotilde Napp & Georgia Thebault, 2020. "Gender stereotypes can explain the gender-equality paradox," Proceedings of the National Academy of Sciences, Proceedings of the National Academy of Sciences, vol. 117(49), pages 31063-31069, December.
    13. Devereux, Paul J. & Delaney, Judith, 2019. "Understanding Gender Differences in STEM: Evidence from College Applications," CEPR Discussion Papers 13558, C.E.P.R. Discussion Papers.
    14. Shulamit Kahn & Donna Ginther, 2017. "Women and STEM," NBER Working Papers 23525, National Bureau of Economic Research, Inc.
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    Cited by:

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    2. Kaziya Kadonsi, 2025. "Addressing Gender Disparities in Mathematics Achievement: A Case Study of Rural Schools in Kalomo District, Zambia," International Journal of Research and Innovation in Social Science, International Journal of Research and Innovation in Social Science (IJRISS), vol. 9(4), pages 3282-3309, April.
    3. Gladys Njideka Okpalanwa & Chika C. Ugwuanyi & Ann O. Ugwuda, 2025. "Motivation as Correlate of Slow Learners’ Achievement in Modular Arithmetic in Senior Secondary School Mathematics," International Journal of Research and Scientific Innovation, International Journal of Research and Scientific Innovation (IJRSI), vol. 12(15), pages 862-870, May.
    4. Naomi Friedman-Sokuler & Claudia Senik, 2025. "From pink collar to lab coat: cultural persistence and diffusion of socialist gender norms," Journal of Population Economics, Springer;European Society for Population Economics, vol. 38(1), pages 1-34, March.

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