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STEM graduates and secondary school curriculum: does early exposure to science matter?

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  • Marta De Philippis

Abstract

Increasing the number of Science, Technology, Engineering and Math (STEM) university graduates is considered a key element for long-term productivity and competitiveness in the global economy. Still, little is known about what actually drives and shapes students' choices. This paper focusses on secondary school students at the very top of the ability distribution and explores the effect of more exposure to science on enrolment and persistence in STEM degrees at the university and on the quality of the university attended. The paper overcomes the standard endogeneity problems by exploiting the different timing in the implementation of a reform that induced secondary schools in the UK to offer more science to high ability 14 year-old children. Taking more science in secondary school increases the probability of enrolling in a STEM degree by 1.5 percentage point and the probability of graduating in these degrees by 3 percentage points. The results mask substantial gender heterogeneity: while girls are as willing as boys to take advanced science in secondary school - when offered -, the effect on STEM degrees is entirely driven by boys. Girls are induced to choose more challenging subjects, but still the most female-dominated ones.

Suggested Citation

  • Marta De Philippis, 2016. "STEM graduates and secondary school curriculum: does early exposure to science matter?," CEP Discussion Papers dp1443, Centre for Economic Performance, LSE.
  • Handle: RePEc:cep:cepdps:dp1443
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    Cited by:

    1. Black, Sandra E. & Muller, Chandra & Spitz-Oener, Alexandra & He, Ziwei & Hung, Koit & Warren, John Robert, 2021. "The importance of STEM: High school knowledge, skills and occupations in an era of growing inequality," Research Policy, Elsevier, vol. 50(7).
    2. Chise Diana & Fort Margherita & Monfardini Chiara, 2021. "On the Intergenerational Transmission of STEM Education among Graduate Students," The B.E. Journal of Economic Analysis & Policy, De Gruyter, vol. 21(1), pages 115-145, January.
    3. Delaney, Judith & Devereux, Paul, 2019. "It's not just for boys! Understanding gender differences in STEM," Papers WP617, Economic and Social Research Institute (ESRI).
    4. 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.
    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. Judith M. Delaney & Paul J. Devereux, 2021. "Gender and Educational Achievement: Stylized Facts and Causal Evidence," Working Papers 202103, School of Economics, University College Dublin.
    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. Chise, Diana & Fort, Margherita & Monfardini, Chiara, 2019. "Scientifico! like Dad: On the Intergenerational Transmission of STEM Education in Italy," IZA Discussion Papers 12688, Institute of Labor Economics (IZA).
    9. Shulamit Kahn & Donna Ginther, 2017. "Women and STEM," NBER Working Papers 23525, National Bureau of Economic Research, Inc.
    10. Diana Chise & Margherita Fort & Chiara Monfardini, 2020. "Scientifico! like Dad: On the Intergenerational Transmission of STEM Education," FBK-IRVAPP Working Papers 2020-01, Research Institute for the Evaluation of Public Policies (IRVAPP), Bruno Kessler Foundation.
    11. 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.

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    More about this item

    Keywords

    university education; education; high school curriculum; STEM;
    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
    • I28 - Health, Education, and Welfare - - Education - - - Government Policy
    • I21 - Health, Education, and Welfare - - Education - - - Analysis of Education

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