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Does gender matter? The effect of high performing peers on academic performances

Author

Listed:
  • Francesca Modena

    (Bank of Italy)

  • Enrico Rettore

    (Department of Economics and Management, University of Padova and FBK-IRVAPP)

  • Giulia Martina Tanzi

    (Bank of Italy)

Abstract

This paper exploits student-level administrative data on the population of Italian university students, from 2006 to 2014, to analyse the effects of high performing (HP) male or female peers on individual academic performance, according to the gender of the student. The identification strategy is based on quasi-random variation in the exposure to HP peers across cohorts, within the same university and the same degree programme. The impact of HP students, proxied by their final high school grade, is heterogeneous. We found that female HP peers have stronger positive effects than HP males, in particular with peers of the same gender. Moreover, there is evidence that exposure to HP males can even be negative, especially for female students in competitive environments, such as the STEM fields of study, and for low ability students of both genders.

Suggested Citation

  • Francesca Modena & Enrico Rettore & Giulia Martina Tanzi, 2021. "Does gender matter? The effect of high performing peers on academic performances," Temi di discussione (Economic working papers) 1356, Bank of Italy, Economic Research and International Relations Area.
    • Handle: RePEc:bdi:wptemi:td_1356_21
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    1. Chesney, Alexander J., 2022. "Should I get a master’s degree?," Economics of Education Review, Elsevier, vol. 91(C).

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    More about this item

    Keywords

    Higher education; University performance; Gender; Peers.;
    All these keywords.

    JEL classification:

    • I22 - Health, Education, and Welfare - - Education - - - Educational Finance; Financial Aid
    • I23 - Health, Education, and Welfare - - Education - - - Higher Education; Research Institutions
    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • C35 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions

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