This project aims to measure the consequences of gender stereotypes of secondary school teachers on the decisions and trajectories of their students during high school and after graduation in Peru. The researcher will measure the influence of teachers’ stereotypes on short-term indicators (e.g. grades obtained by students), medium-term indicators (e.g. preferences for post-secondary work paths or higher education and careers), and long-term (e.g. the application decision and admission to a higher education institution). This study aims to estimate the long-term effects of teachers’ stereotypes on school attainment, college attendance, and labor market outcomes. A second contribution relates a measure of gender stereotypes with score-based measures of gender bias. This allows characterizing two dimensions of bias exerted implicitly and explicitly through students’ assessments. Finally, the third contribution of this study consists of examining the relationship between the gender bias of teachers’ and students’ preferences for higher education fields.
Through a partnership with the Ministry of Education and the Ministry of Labor of Peru, the research team will analyze a rich set of information on teachers, students, and labor market outcomes. The research team will connect this information with primary data gathered on teachers’ implicit gender stereotypes using a psychology measure, the Implicit Association Test (Alessina 2019, Carlana 2019, Glover, Pallais, & Pariente, 2017 Greenwald et al. 1998, 2003).
The research team documented that teachers’ gender attitudes predicted subject-specific assessment bias in the sample: math teachers who believed boys were better than girls in mathematics and scientific disciplines gave boys better grades than the blindly-graded test scores, while language arts teachers who believed girls were better than boys at humanities gave girls better grades. Using enrollment, college, and matched employer-employee data on 1.7 million public high school students who graduated between 2015 and 2019 in Peru, the research team found that female students assigned to more biased teachers were less likely to complete high school and apply to college than male students. Moreover, female students assigned to more biased teachers were less likely to hold a job in the formal sector after graduation and more likely to have lower monthly earnings and fewer paid working hours relative to their male classmates. Mathematics teachers’ assessment bias had the most detrimental impact on female students, although the effects of language arts and science teachers’ bias were also significant.
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