IDEAS home Printed from https://ideas.repec.org/p/iza/izadps/dp11260.html
   My bibliography  Save this paper

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

Author

Listed:
  • 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
    as

    Download full text from publisher

    File URL: https://docs.iza.org/dp11260.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. 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.
    2. 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.
    3. 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.
    4. 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.
    5. 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.
    6. 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.
    7. 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.
    8. 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.
    9. 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.
    10. 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.
    11. 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.
    12. 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.
    13. 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.
    14. 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.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    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).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    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. 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.
    3. Carlos A. Flores & Oscar A. Mitnik, 2009. "Evaluating Nonexperimental Estimators for Multiple Treatments: Evidence from Experimental Data," Working Papers 2010-10, University of Miami, Department of Economics.
    4. Dettmann, E. & Becker, C. & Schmeißer, C., 2011. "Distance functions for matching in small samples," Computational Statistics & Data Analysis, Elsevier, vol. 55(5), pages 1942-1960, May.
    5. Frölich, Markus & Michaelowa, Katharina, 2004. "Peer effects and textbooks in primary education: Evidence from francophone sub-Saharan Africa," HWWA Discussion Papers 311, Hamburg Institute of International Economics (HWWA).
    6. Richard K. Crump & V. Joseph Hotz & Guido W. Imbens & Oscar A. Mitnik, 2006. "Moving the Goalposts: Addressing Limited Overlap in the Estimation of Average Treatment Effects by Changing the Estimand," NBER Technical Working Papers 0330, National Bureau of Economic Research, Inc.
    7. Dettmann, Eva & Becker, Claudia & Schmeißer, Christian, 2010. "Is there a Superior Distance Function for Matching in Small Samples?," IWH Discussion Papers 3/2010, Halle Institute for Economic Research (IWH).
    8. Guido W. Imbens & Jeffrey M. Wooldridge, 2009. "Recent Developments in the Econometrics of Program Evaluation," Journal of Economic Literature, American Economic Association, vol. 47(1), pages 5-86, March.
    9. Marco Caliendo & Sabine Kopeinig, 2008. "Some Practical Guidance For The Implementation Of Propensity Score Matching," Journal of Economic Surveys, Wiley Blackwell, vol. 22(1), pages 31-72, February.
    10. repec:jku:cdlwps:2015_07 is not listed on IDEAS
    11. Bernhard Schmidpeter, 2015. "The Fatal Consequences of Grief," Economics working papers 2015-06, Department of Economics, Johannes Kepler University Linz, Austria.
    12. Bernhard Schmidpeter, 2015. "The Fatal Consequences of Grief," CDL Aging, Health, Labor working papers 2015-07, The Christian Doppler (CD) Laboratory Aging, Health, and the Labor Market, Johannes Kepler University Linz, Austria.
    13. Eva Dettmann & Jutta Günther, 2013. "Subsidized Vocational Training: Stepping Stone or Trap? Assessing Empirical Effects Using Matching Techniques," Swiss Journal of Economics and Statistics (SJES), Swiss Society of Economics and Statistics (SSES), vol. 149(IV), pages 405-443, December.
    14. Eliasson, Kent, 2006. "The Role of Ability in Estimating the Returns to College Choice: New Swedish Evidence," Umeå Economic Studies 691, Umeå University, Department of Economics.
    15. Jochen Kluve & Boris Augurzky, 2007. "Assessing the performance of matching algorithms when selection into treatment is strong," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 22(3), pages 533-557.
    16. Eliasson, Kent, 2006. "How Robust is the Evidence on the Returns to College Choice? Results Using Swedish Administrative Data," Umeå Economic Studies 692, Umeå University, Department of Economics.
    17. Peter R. Mueser & Kenneth R. Troske & Alexey Gorislavsky, 2007. "Using State Administrative Data to Measure Program Performance," The Review of Economics and Statistics, MIT Press, vol. 89(4), pages 761-783, November.
    18. Richard Blundell & Lorraine Dearden & Barbara Sianesi, 2003. "Evaluating the impact of education on earnings in the UK: Models, methods and results from the NCDS," IFS Working Papers W03/20, Institute for Fiscal Studies.
    19. John C. Ham & Xianghong Li & Patricia B. Reagan, 2004. "Propensity Score Matching, a Distance-Based Measure of Migration, and the Wage Growth of Young Men," Working Papers 2004_3, York University, Department of Economics.
    20. Winterhager, Henrik & Heinze, Anja & Spermann, Alexander, 2006. "Deregulating job placement in Europe: A microeconometric evaluation of an innovative voucher scheme in Germany," Labour Economics, Elsevier, vol. 13(4), pages 505-517, August.
    21. Loi, Massimo & Rodrigues, Margarida, 2012. "A note on the impact evaluation of public policies: the counterfactual analysis," MPRA Paper 42444, University Library of Munich, Germany.

    More about this item

    Keywords

    Semiparametric Oaxaca Blinder decomposition; gender math gap; culture;
    All these keywords.

    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

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:iza:izadps:dp11260. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Holger Hinte (email available below). General contact details of provider: https://edirc.repec.org/data/izaaade.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.