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Gender stereotypes in the family

Author

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  • Cheti Nicoletti
  • Almudena Sevilla
  • Valentina Tonei

Abstract

We study whether and why parents have gender-stereotyped beliefs when they assess their child's skills. Exploiting systematic differences in parental beliefs about a child's skills and blindly graded standardized test scores, we find that parents overestimate boys' skills more so than girls' in mathematics (a male-stereotyped subject), whereas there are no gender differences for reading. Consistent with an information friction hypothesis, we find that the parental gender bias disappears for parents who are interviewed after receiving information on their child's test scores. We further show that the parental gender bias in detriment of girls contributes to explain the widening of the gender gap in mathematical skills later in childhood, supporting the hypothesis that exposure to gender biases negatively influence girls' ability to achieve their full potential.

Suggested Citation

  • Cheti Nicoletti & Almudena Sevilla & Valentina Tonei, 2022. "Gender stereotypes in the family," CEP Discussion Papers dp1891, Centre for Economic Performance, LSE.
  • Handle: RePEc:cep:cepdps:dp1891
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    Cited by:

    1. Adamecz-Völgyi, Anna & Jerrim, John & Pingault, Jean-Baptiste & Shure, Nikki, 2023. "Overconfident Boys: The Gender Gap in Mathematics Self-Assessment," IZA Discussion Papers 16180, Institute of Labor Economics (IZA).

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    More about this item

    Keywords

    parental beliefs; gender bias; stereotypes; school performance; standardized scores;
    All these keywords.

    JEL classification:

    • J13 - Labor and Demographic Economics - - Demographic Economics - - - Fertility; Family Planning; Child Care; Children; Youth
    • D13 - Microeconomics - - Household Behavior - - - Household Production and Intrahouse Allocation
    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
    • C20 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - General

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