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Explaining the Gender Test Score Gap in Mathematics: The Role of Gender Inequality

Author

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  • Gevrek, Z. Eylem

    (Universidade Catolica Portuguesa, Porto)

  • Neumeier, Christian

    (University of Konstanz)

  • Gevrek, Deniz

    (Texas A&M University Corpus Christi)

Abstract

Using data from the 2012 PISA across 56 countries, this study examines the link between societal gender inequalities and the gender test score gap in mathematics. We employ a novel two-stage empirical strategy in which the first stage involves decomposing the gender mathematics gap into a part that is explained by gender differences in observable characteristics and a part that remains unexplained. We use a semiparametric Oaxaca-Blinder (OB) decomposition to analyze the gap in each country individually. In the second stage, we investigate whether the decomposition components of the gap are systematically related to country-level gender inequality measures. The results indicate that the gap is not statistically significantly associated with the indicators of gender inequality, but the unexplained part of the gap is. In more gender-equal countries, the unexplained part of the gap favoring boys appears smaller. Moreover, we find that the relationship between the unexplained part of the gap and the societal gender inequality varies within the test score distribution, and tends to become less pronounced at the upper end of the distribution.

Suggested Citation

  • Gevrek, Z. Eylem & Neumeier, Christian & Gevrek, Deniz, 2018. "Explaining the Gender Test Score Gap in Mathematics: The Role of Gender Inequality," IZA Discussion Papers 11260, Institute of Labor Economics (IZA).
  • Handle: RePEc:iza:izadps:dp11260
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    References listed on IDEAS

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    1. James J. Heckman & Hidehiko Ichimura & Petra E. Todd, 1997. "Matching As An Econometric Evaluation Estimator: Evidence from Evaluating a Job Training Programme," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 64(4), pages 605-654.
    2. A. Smith, Jeffrey & E. Todd, Petra, 2005. "Does matching overcome LaLonde's critique of nonexperimental estimators?," Journal of Econometrics, Elsevier, vol. 125(1-2), pages 305-353.
    3. Roland G. Fryer & Steven D. Levitt, 2010. "An Empirical Analysis of the Gender Gap in Mathematics," American Economic Journal: Applied Economics, American Economic Association, vol. 2(2), pages 210-240, April.
    4. Black, Dan A. & Smith, J.A.Jeffrey A., 2004. "How robust is the evidence on the effects of college quality? Evidence from matching," Journal of Econometrics, Elsevier, vol. 121(1-2), pages 99-124.
    5. Devin G. Pope & Justin R. Sydnor, 2010. "Geographic Variation in the Gender Differences in Test Scores," Journal of Economic Perspectives, American Economic Association, vol. 24(2), pages 95-108, Spring.
    6. Dickerson, Andy & McIntosh, Steven & Valente, Christine, 2015. "Do the maths: An analysis of the gender gap in mathematics in Africa," Economics of Education Review, Elsevier, vol. 46(C), pages 1-22.
    7. Alina Botezat & Ruben R. Seiberlich, 2013. "Educational performance gaps in Eastern Europe," The Economics of Transition, The European Bank for Reconstruction and Development, vol. 21(4), pages 731-756, October.
    8. Barbara Sianesi, 2004. "An Evaluation of the Swedish System of Active Labor Market Programs in the 1990s," The Review of Economics and Statistics, MIT Press, vol. 86(1), pages 133-155, February.
    9. Heckman, James J. & Lalonde, Robert J. & Smith, Jeffrey A., 1999. "The economics and econometrics of active labor market programs," Handbook of Labor Economics, in: O. Ashenfelter & D. Card (ed.), Handbook of Labor Economics, edition 1, volume 3, chapter 31, pages 1865-2097, Elsevier.
    10. Guido W. Imbens, 2004. "Nonparametric Estimation of Average Treatment Effects Under Exogeneity: A Review," The Review of Economics and Statistics, MIT Press, vol. 86(1), pages 4-29, February.
    11. Jinyong Hahn, 1998. "On the Role of the Propensity Score in Efficient Semiparametric Estimation of Average Treatment Effects," Econometrica, Econometric Society, vol. 66(2), pages 315-332, March.
    12. Gevrek, Z. Eylem & Seiberlich, Ruben R., 2014. "Semiparametric decomposition of the gender achievement gap: An application for Turkey," Labour Economics, Elsevier, vol. 31(C), pages 27-44.
    13. Michael Lechner, 2002. "Some practical issues in the evaluation of heterogeneous labour market programmes by matching methods," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 165(1), pages 59-82, February.
    14. Natalia Nollenberger & Núria Rodríguez-Planas & Almudena Sevilla, 2016. "The Math Gender Gap: The Role of Culture," American Economic Review, American Economic Association, vol. 106(5), pages 257-261, May.
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    Cited by:

    1. Ana Maria Munoz Boudet & Lourdes Rodriguez Chamussy & Christina Chiarella & Isil Oral Savonitto, 2021. "Women and STEM in Europe and Central Asia," World Bank Publications - Reports 35463, The World Bank Group.
    2. Graetz, Georg & Karimi, Arizo, 2022. "Gender gap variation across assessment types: Explanations and implications," Economics of Education Review, Elsevier, vol. 91(C).
    3. Paterson, Molly, 2021. "Gender and Disadvantage in the Evolution of Test Score Gaps," Warwick-Monash Economics Student Papers 06, Warwick Monash Economics Student Papers.
    4. Graetz, Georg & Karimi, Arizo, 2019. "Explaining gender gap variation across assessment forms," Working Paper Series 2019:8, IFAU - Institute for Evaluation of Labour Market and Education Policy.
    5. Long, Wenjin & Pang, Xiaopeng & Dong, Xiao-yuan & Zeng, Junxia, 2020. "Is rented accommodation a good choice for primary school students' academic performance? – Evidence from rural China," China Economic Review, Elsevier, vol. 62(C).

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    JEL classification:

    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • I24 - Health, Education, and Welfare - - Education - - - Education and Inequality
    • I25 - Health, Education, and Welfare - - Education - - - Education and Economic Development
    • J16 - Labor and Demographic Economics - - Demographic Economics - - - Economics of Gender; Non-labor Discrimination

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