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Academic Aptitude Signals and STEM field participation: A Regression Discontinuity Approach

Author

Listed:
  • Marcos Agurto

    (Universidad de Piura)

  • Sandra Buzinsky

    (Universidad de Piura)

  • Siddharth Hari

    (The World Bank)

  • Valeria Quevedo

    (Universidad de Piura)

  • Sudipta Sarangi

    (Virginia Tech)

  • Susana Vegas

    (Universidad de Piura)

Abstract

Gender disparities in STEM field participation at all levels are wide and persistent. In this paper we explore whether external signals about academic aptitude can influence female participation in STEM fields. We analyze 10 years of data on aptitude tests administered by a private university in Peru taken by 3,000 high school students each year. Prior to the test, students are asked to state their (non-binding) preferences over college majors. Admission into majors is determined on the basis of cut-off scores on the exam, which has a math and a verbal component. Using a regression discontinuity design, we find that among students whose preferred major was other than engineering, making the engineering cut-off increases the likelihood of enrolling in engineering by 10-12 percentage points. These effects are driven entirely by female students, and no effect is seen for males. We also find that women with higher scores on the verbal component are less likely to make this switch, reinforcing the idea that external signals about aptitude matter for choice of college majors. These results highlight the importance of external validation in influencing career choices in a context where social norms discourage female participation in STEM fields, and have important policy implications.

Suggested Citation

  • Marcos Agurto & Sandra Buzinsky & Siddharth Hari & Valeria Quevedo & Sudipta Sarangi & Susana Vegas, 2020. "Academic Aptitude Signals and STEM field participation: A Regression Discontinuity Approach," Working Papers 2020-08, Lima School of Economics.
  • Handle: RePEc:ima:wpaper:2020-008
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    References listed on IDEAS

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    1. Glenn Ellison & Ashley Swanson, 2010. "The Gender Gap in Secondary School Mathematics at High Achievement Levels: Evidence from the American Mathematics Competitions," Journal of Economic Perspectives, American Economic Association, vol. 24(2), pages 109-128, Spring.
    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. Arcidiacono, Peter, 2004. "Ability sorting and the returns to college major," Journal of Econometrics, Elsevier, vol. 121(1-2), pages 343-375.
    4. Christopher Avery & Oded Gurantz & Michael Hurwitz & Jonathan Smith, 2018. "Shifting College Majors in Response to Advanced Placement Exam Scores," Journal of Human Resources, University of Wisconsin Press, vol. 53(4), pages 918-956.
    5. Natalia Nollenberger & Núria Rodríguez-Planas & Almudena Sevilla, 2016. "The Math Gender Gap: The Role of Culture," American Economic Review, American Economic Association, vol. 106(5), pages 257-261, May.
    6. Andrew Gelman & Guido Imbens, 2019. "Why High-Order Polynomials Should Not Be Used in Regression Discontinuity Designs," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 37(3), pages 447-456, July.
    7. David Card & A. Abigail Payne, 2021. "High School Choices And The Gender Gap In Stem," Economic Inquiry, Western Economic Association International, vol. 59(1), pages 9-28, January.
    8. 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.
    9. Sebastian Calonico & Matias D. Cattaneo & Max H. Farrell & Roc ́ıo Titiunik, 2017. "rdrobust: Software for regression-discontinuity designs," Stata Journal, StataCorp LP, vol. 17(2), pages 372-404, June.
    10. Devin G. Pope & Justin R. Sydnor, 2010. "Geographic Variation in the Gender Differences in Test Scores," Journal of Economic Perspectives, American Economic Association, vol. 24(2), pages 95-108, Spring.
    11. United Nations Educational, Scientific and Cultura UNESCO, 2017. "Cracking the Code: Girls’ and Women’s Education in Science, Technology, Engineering and Mathematics (STEM)," Working Papers id:12246, eSocialSciences.
    12. Chang‐Tai Hsieh & Erik Hurst & Charles I. Jones & Peter J. Klenow, 2019. "The Allocation of Talent and U.S. Economic Growth," Econometrica, Econometric Society, vol. 87(5), pages 1439-1474, September.
    13. Shulamit Kahn & Donna Ginther, 2017. "Women and STEM," NBER Working Papers 23525, National Bureau of Economic Research, Inc.
    14. Matthew Wiswall & Basit Zafar, 2011. "Belief updating among college students: evidence from experimental variation in information," Staff Reports 516, Federal Reserve Bank of New York.
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    More about this item

    Keywords

    STEM; Gender Gap; Academic Aptitude Signals; RD; Peru;
    All these keywords.

    JEL classification:

    • I3 - Health, Education, and Welfare - - Welfare, Well-Being, and Poverty
    • I32 - Health, Education, and Welfare - - Welfare, Well-Being, and Poverty - - - Measurement and Analysis of Poverty
    • D63 - Microeconomics - - Welfare Economics - - - Equity, Justice, Inequality, and Other Normative Criteria and Measurement
    • O1 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development
    • H1 - Public Economics - - Structure and Scope of Government

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