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Revealing Gender-Specific Costs of STEM in an Extended Roy Model of Major Choice

Author

Listed:
  • Marc Henry
  • Romuald Meango
  • Ismael Mourifié

    (University of Toronto)

Abstract

We derive sharp bounds on the non consumption utility component in an extended Roy model of sector selection. We interpret this non consumption utility component as a compensating wage differential. The bounds are derived under the assumption that potential wages in each sector are (jointly) stochastically monotone with respect to an observed selection shifter. The lower bound can also be interpreted as the minimum cost subsidy necessary to change sector choices and make them observationally indistinguishable from choices made under the classical Roy model of sorting on potential wages only. The research is motivated by the analysis of women's choice of university major and their under-representation in mathematics intensive fields. With data from a German graduate survey, and using the proportion of women on the STEM faculty at the time of major choice as our selection shifter, we find high costs of choosing the STEM sector for women from the former West Germany, especially for low realized incomes and low proportion of women on the STEM faculty, interpreted as a scarce presence of role models.

Suggested Citation

  • Marc Henry & Romuald Meango & Ismael Mourifié, 2020. "Revealing Gender-Specific Costs of STEM in an Extended Roy Model of Major Choice," Working Papers 2020-035, Human Capital and Economic Opportunity Working Group.
    • Handle: RePEc:hka:wpaper:2020-035
    Note: ECI
    as

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    File URL: http://humcap.uchicago.edu/RePEc/hka/wpaper/Henry_Meango_Mouriifie_2020_gender-specific-costs-stem.pdf
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    References listed on IDEAS

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    Cited by:

    1. Shuowen Chen & Hiroaki Kaido, 2022. "Robust Tests of Model Incompleteness in the Presence of Nuisance Parameters," Papers 2208.11281, arXiv.org, revised Sep 2023.

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    More about this item

    Keywords

    Roy model; partial identification; stochastic monotonicity; women in STEM;
    All these keywords.

    JEL classification:

    • C31 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models; Quantile Regressions; Social Interaction Models
    • C34 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Truncated and Censored Models; Switching Regression Models
    • 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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