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The Gender Gap in Mathematics Achievement: Evidence from Italian Data

Author

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  • Di Tommaso, Maria Laura

    () (University of Turin)

  • Mendolia, Silvia

    () (University of Wollongong)

  • Contini, Dalit

    () (University of Turin)

Abstract

Gender differences in the STEM (Science Technology Engineering and Mathematics) disciplines are widespread in most OECD countries and mathematics is the only subject where typically girls tend to underperform with respect to boys. This paper describes the gender gap in math test scores in Italy, which is one of the countries displaying the largest differential between boys and girls according to the Programme for International Student Assessment (PISA), we use data from an Italian national level learning assessment, involving children in selected grades from second to tenth. We first analyse the magnitude of the gender gap using OLS regression and school fixed-effect models for each grade separately. Our results show that girls systematically underperform boys, even after controlling for an array of individual and family background characteristics, and that the average gap increases with children's age. We then study the gender gap throughout the test scores distribution, using quantile regression and metric-free methods, and find that the differential is small at the lowest percentiles of the grade distribution, but large among top performing children. Finally, we estimate dynamic models relating math performance at two consecutive assessments. Lacking longitudinal data, we use a pseudo panel technique and find that girls' average test scores are consistently lower than those of boys at all school years, even conditional on previous scores.

Suggested Citation

  • Di Tommaso, Maria Laura & Mendolia, Silvia & Contini, Dalit, 2016. "The Gender Gap in Mathematics Achievement: Evidence from Italian Data," IZA Discussion Papers 10053, Institute of Labor Economics (IZA).
  • Handle: RePEc:iza:izadps:dp10053
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    References listed on IDEAS

    as
    1. Brunello, Giorgio & Checchi, Daniele, 2005. "School quality and family background in Italy," Economics of Education Review, Elsevier, vol. 24(5), pages 563-577, October.
    2. James J. Heckman & Stefano Mosso, 2014. "The Economics of Human Development and Social Mobility," Annual Review of Economics, Annual Reviews, vol. 6(1), pages 689-733, August.
    3. Verbeek, Marno & Vella, Francis, 2005. "Estimating dynamic models from repeated cross-sections," Journal of Econometrics, Elsevier, vol. 127(1), pages 83-102, July.
    4. Daniela Del Boca & Christopher Flinn & Matthew Wiswall, 2014. "Household Choices and Child Development," Review of Economic Studies, Oxford University Press, vol. 81(1), pages 137-185.
    5. Silvia Mendolia & Ian Walker, 2014. "The effect of personality traits on subject choice and performance in high school," Working Papers 64907361, Lancaster University Management School, Economics Department.
    6. Heckman, James J. & Kautz, Tim, 2012. "Hard evidence on soft skills," Labour Economics, Elsevier, vol. 19(4), pages 451-464.
    7. Christopher Cornwell & David B. Mustard & Jessica Van Parys, 2013. "Noncognitive Skills and the Gender Disparities in Test Scores and Teacher Assessments: Evidence from Primary School," Journal of Human Resources, University of Wisconsin Press, vol. 48(1), pages 236-264.
    8. Ylenia Brilli & Daniela Boca & Chiara Pronzato, 2016. "Does child care availability play a role in maternal employment and children’s development? Evidence from Italy," Review of Economics of the Household, Springer, vol. 14(1), pages 27-51, March.
    9. Mendolia, Silvia & Walker, Ian, 2014. "The effect of personality traits on subject choice and performance in high school: Evidence from an English cohort," Economics of Education Review, Elsevier, vol. 43(C), pages 47-65.
    10. Ylenia Brilli & Daniela Boca & Chiara Pronzato, 2016. "Does child care availability play a role in maternal employment and children’s development? Evidence from Italy," Review of Economics of the Household, Springer, vol. 14(1), pages 27-51, March.
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    Cited by:

    1. Daniela Piazzalunga, 2018. "The Gender Wage Gap Among College Graduates in Italy," Italian Economic Journal: A Continuation of Rivista Italiana degli Economisti and Giornale degli Economisti, Springer;Società Italiana degli Economisti (Italian Economic Association), vol. 4(1), pages 33-90, March.
    2. Di Tommaso, Maria Laura & Maccagnan, Anna & Mendolia, Silvia, 2018. "The Gender Gap in Attitudes and Test Scores: a new construct of the mathematical capability," Department of Economics and Statistics Cognetti de Martiis. Working Papers 201815, University of Turin.
    3. Di Tommaso, Maria Laura & Maccagnan, Anna & Mendolia, Silvia, 2018. "The Gender Gap in Attitudes and Test Scores: A New Construct of the Mathematical Capability," IZA Discussion Papers 11843, Institute of Labor Economics (IZA).
    4. Daniel Montolio & Pere A. Taberner, 2018. "Gender differences under test pressure and their impact on academic performance: a quasi-experimental design," Working Papers 2018/21, Institut d'Economia de Barcelona (IEB).

    More about this item

    Keywords

    math gender gap; education; school achievement; inequalities; cross-sectional data; pseudo panel estimation; quantile regression;

    JEL classification:

    • J16 - Labor and Demographic Economics - - Demographic Economics - - - Economics of Gender; Non-labor Discrimination
    • I24 - Health, Education, and Welfare - - Education - - - Education and Inequality
    • 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

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