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Semiparametric Decomposition of the Gender Achievement Gap: An Application for Turkey

Author

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  • Z. Eylem Gevrek

    (Department of Economics, University of Konstanz, Germany)

  • Ruben R. Seiberlich

    (Department of Economics, University of Konstanz, Germany)

Abstract
Using the data from the 2006 Programme for International Student Assessment (PISA), this study sheds light on the gender gap in mathematics and science achievement of 15-year-olds in Turkey. We apply a semiparametric Oaxaca-Blinder (OB) decomposition to investigate the gap. This technique relaxes the parametric assumptions of the standard OB decomposition, accounts for the possible violation of the common support assumption and allows us to explore the gender test score gap not only at the mean but also across the entire distribution of test scores. Our findings provide evidence that the failure to recognize the common support problem leads to the underestimation of the part of the gap attributable to observable characteristics. We find that girls outperform boys in science while the gap is not statistically significant in math. School characteristics are the most important observable characteristics in explaining the gap. We also find that the gender test score gap changes across the distribution

Suggested Citation

  • Z. Eylem Gevrek & Ruben R. Seiberlich, 2012. "Semiparametric Decomposition of the Gender Achievement Gap: An Application for Turkey," Working Paper Series of the Department of Economics, University of Konstanz 2012-32, Department of Economics, University of Konstanz.
    • Handle: RePEc:knz:dpteco:1232
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    Cited by:

    1. Gevrek, Z. Eylem & Gevrek, Deniz & Neumeier, Christian, 2020. "Explaining the gender gaps in mathematics achievement and attitudes: The role of societal gender equality," Economics of Education Review, Elsevier, vol. 76(C).
    2. Munir, Farzana & Winter-Ebmer, Rudolf, 2018. "Decomposing international gender test score differences," Journal for Labour Market Research, Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany], vol. 52(1), pages 1-12.
    3. Huong Thu Le & Ha Trong Nguyen, 2018. "The evolution of the gender test score gap through seventh grade: new insights from Australia using unconditional quantile regression and decomposition," IZA Journal of Labor Economics, Springer;Forschungsinstitut zur Zukunft der Arbeit GmbH (IZA), vol. 7(1), pages 1-42, December.
    4. Muñoz, Juan Sebastián, 2018. "The economics behind the math gender gap: Colombian evidence on the role of sample selection," Journal of Development Economics, Elsevier, vol. 135(C), pages 368-391.
    5. 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).
    6. Farzana Munir & Rudolf Winter-Ebmer, 2018. "Decomposing international gender test score differences," Journal for Labour Market Research, Springer;Institute for Employment Research/ Institut für Arbeitsmarkt- und Berufsforschung (IAB), vol. 52(1), pages 1-17, December.
    7. Ha Trong Nguyen, 2015. "The evolution of the gender test score gap through seventh grade: New insights from Australia using quantile regression and decomposition," Bankwest Curtin Economics Centre Working Paper series WP1507, Bankwest Curtin Economics Centre (BCEC), Curtin Business School.
    8. Romuald Foueka, 2020. "Analyse du différentiel de performances scolaires dans les pays PASEC sur la base de la régression quantile contrefactuelle," African Development Review, African Development Bank, vol. 32(4), pages 605-618, December.
    9. repec:iab:iabjlr:v:52:i:1:p:art.12 is not listed on IDEAS
    10. Dries Lens & François Levrau, 2020. "Can Pre-entry Characteristics Account for the Ethnic Attainment Gap? An Analysis of a Flemish University," Research in Higher Education, Springer;Association for Institutional Research, vol. 61(1), pages 26-50, February.

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    More about this item

    Keywords

    Gender test score gap; semiparametric decomposition; propensity score matching;
    All these keywords.

    JEL classification:

    • I21 - Health, Education, and Welfare - - Education - - - Analysis of Education
    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General

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