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Does an aptitude test affect socioeconomic and gender gaps in attendance at an elite university?

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  • Jake Anders

    (Department of Quantitative Social Science, Institute of Education, University of London)

Abstract

The increasing use of aptitude tests as part of the admissions processes at elite English universities potentially has significant implications for fair access to these institutions. I attempt to isolate the impact of the introduction of one such test on the proportion of successful applicants by school type (as a proxy for socioeconomic status) and by gender using a difference in differences approach and administrative data from the University of Oxford. The introduction of the test coincided with the implementation of a guideline number of interviews per available place, significantly reducing the proportion of applicants offered an interview (by 14 percentage points) and, hence, increasing the proportion of interviewees offered places (by 3.6 percentage points). By gender, I find some evidence that these changes may be having differing effects at different stages of the admissions process, but not on each group's overall chances of securing an offer. I do not find any evidence that the policy has negative side effects on the chances of applicants from less advantaged socioeconomic backgrounds at any stage of the process.

Suggested Citation

  • Jake Anders, 2014. "Does an aptitude test affect socioeconomic and gender gaps in attendance at an elite university?," DoQSS Working Papers 14-07, Quantitative Social Science - UCL Social Research Institute, University College London.
    • Handle: RePEc:qss:dqsswp:1407
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    File URL: https://repec.ucl.ac.uk/REPEc/pdf/qsswp1407.pdf
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    References listed on IDEAS

    as
    1. Jake Anders, 2012. "Using the Longitudinal Study of Young People in England for research into Higher Education access," DoQSS Working Papers 12-13, Quantitative Social Science - UCL Social Research Institute, University College London.
    2. Jake Anders, 2012. "The Link between Household Income, University Applications and University Attendance," Fiscal Studies, Institute for Fiscal Studies, vol. 33(2), pages 185-210, June.
    3. Parente Paulo M.D.C. & Santos Silva João M.C., 2016. "Quantile Regression with Clustered Data," Journal of Econometric Methods, De Gruyter, vol. 5(1), pages 1-15, January.
    4. David Card, 1992. "Using Regional Variation in Wages to Measure the Effects of the Federal Minimum Wage," ILR Review, Cornell University, ILR School, vol. 46(1), pages 22-37, October.
    5. repec:esx:essedp:728 is not listed on IDEAS
    6. A. Colin Cameron & Jonah B. Gelbach & Douglas L. Miller, 2008. "Bootstrap-Based Improvements for Inference with Clustered Errors," The Review of Economics and Statistics, MIT Press, vol. 90(3), pages 414-427, August.
    7. repec:cdl:cshedu:qt8kd4q096 is not listed on IDEAS
    8. Koenker, Roger W & Bassett, Gilbert, Jr, 1978. "Regression Quantiles," Econometrica, Econometric Society, vol. 46(1), pages 33-50, January.
    9. Rothstein, J.M.Jesse M., 2004. "College performance predictions and the SAT," Journal of Econometrics, Elsevier, vol. 121(1-2), pages 297-317.
    Full references (including those not matched with items on IDEAS)

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    Cited by:

    1. Claire Crawford, 2014. "Socio-economic differences in university outcomes in the UK: drop-out, degree completion and degree class," IFS Working Papers W14/31, Institute for Fiscal Studies.

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    JEL classification:

    • I23 - Health, Education, and Welfare - - Education - - - Higher Education; Research Institutions
    • I24 - Health, Education, and Welfare - - Education - - - Education and Inequality

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