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The puzzle of missing female engineers: Academic preparation, ability beliefs, and preferences

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  • Shi, Ying

Abstract

This paper uses administrative North Carolina data linked from high school to college and national surveys to characterize the largest contributor to the STEM gender gap: engineering. Disparities are the result of differential entry during high school or earlier rather than postsecondary exit. Differences in pre-college academic preparation account for 5 to 7% of the gap. Females’ relative lack of academic self-confidence explains 8%, while other-regarding preferences and professional goals capture a further 14%. Empirical evidence using identifying variation in the gender composition of twins in North Carolina shows that opposite-sex pairs are more likely to pursue gender-stereotypical majors.

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  • Shi, Ying, 2018. "The puzzle of missing female engineers: Academic preparation, ability beliefs, and preferences," Economics of Education Review, Elsevier, vol. 64(C), pages 129-143.
    • Handle: RePEc:eee:ecoedu:v:64:y:2018:i:c:p:129-143
    DOI: 10.1016/j.econedurev.2018.04.005
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    Cited by:

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    2. Grosch, Kerstin & Häckl, Simone & Kocher, Martin G., 2022. "Closing the gender STEM gap," Department of Economics Working Paper Series 329, WU Vienna University of Economics and Business.
    3. Izaskun Zuazu, 2020. "Graduates’ Opium? Cultural Values, Religiosity and Gender Segregation by Field of Study," Social Sciences, MDPI, vol. 9(8), pages 1-27, July.
    4. Delaney, Judith M. & Devereux, Paul J., 2023. "Gender Differences in Teacher Judgement of Comparative Advantage," IZA Discussion Papers 16635, Institute of Labor Economics (IZA).
    5. Biewen, Martin & Schwerter, Jakob, 2019. "Does More Math in High School Increase the Share of Female STEM Workers? Evidence from a Curriculum Reform," IZA Discussion Papers 12236, Institute of Labor Economics (IZA).
    6. Kerstin Grosch & Simone Haeckl & Martin G. Kocher, 2022. "Closing the Gender STEM Gap - A Large-Scale Randomized-Controlled Trial in Elementary Schools," CESifo Working Paper Series 9907, CESifo.
    7. Mcnally, Sandra, 2020. "Gender differences in tertiary education: what explains STEM participation," LSE Research Online Documents on Economics 108232, London School of Economics and Political Science, LSE Library.
    8. C. Judson King, 2020. "A Liberal Undergraduate Education for Engineers," Sustainability, MDPI, vol. 12(16), pages 1-6, August.
    9. Bi, Sharon & Buontempo, Jenny & DiSalvo, Richard W., 2022. "The effects of accelerated mathematics on self-efficacy and growth mindset," Economics of Education Review, Elsevier, vol. 90(C).
    10. Tao, Hung-Lin & Cheng, Hui-Pei, 2022. "Parental and sibling influence on study field choice: Gender-stereotypical or field preference transmission," Journal of Asian Economics, Elsevier, vol. 82(C).
    11. Maria Inmaculada Tazo & Ana Boyano & Unai Fernandez-Gámiz & Amaia Calleja-Ochoa, 2020. "The Gender Perspective of Professional Competencies in Industrial Engineering Studies," Sustainability, MDPI, vol. 12(7), pages 1-16, April.
    12. Chiara Cavaglia & Stephen Machin & Sandra McNally & Jenifer Ruiz-Valenzuela, 2020. "Gender, achievement, and subject choice in English education," CVER Research Papers 032, Centre for Vocational Education Research.
    13. Zuazu-Bermejo, Izaskun, 2020. "Graduates’ opium? Cultural values, religiosity and gender segregation by field of study," OSF Preprints yn23j, Center for Open Science.

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    More about this item

    Keywords

    Economics of gender; Human capital; Occupational choice;
    All these keywords.

    JEL classification:

    • J16 - Labor and Demographic Economics - - Demographic Economics - - - Economics of Gender; Non-labor Discrimination
    • J24 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Human Capital; Skills; Occupational Choice; Labor Productivity
    • I23 - Health, Education, and Welfare - - Education - - - Higher Education; Research Institutions

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