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Estimating the distributional effects of education reforms: A look at Project STAR

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  • Jackson, Erika
  • Page, Marianne E.

Abstract

Most evaluations of education policies focus on their mean impacts; when distributional effects are investigated it is usually by comparing mean impacts across demographic subgroups. We argue that such estimates may overlook important treatment effect heterogeneity; in order to appreciate the full extent of a policy's distributional impacts one should also exploit alternative methods. We demonstrate this using data from Project STAR, where we find evidence of substantial treatment effect heterogeneity across achievement quantiles. While all children appear to benefit from being placed in small classes, the largest test score gains are at the top of the achievement distribution. This result seems to be at odds with previous evidence that smaller classes benefit disadvantaged children most, but the discrepancy is reconciled by the fact that there are similar patterns of treatment effect heterogeneity within demographic groups, and that gains for disadvantaged students are larger throughout much of the achievement distribution.

Suggested Citation

  • Jackson, Erika & Page, Marianne E., 2013. "Estimating the distributional effects of education reforms: A look at Project STAR," Economics of Education Review, Elsevier, vol. 32(C), pages 92-103.
  • Handle: RePEc:eee:ecoedu:v:32:y:2013:i:c:p:92-103
    DOI: 10.1016/j.econedurev.2012.07.017
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    Cited by:

    1. Goldman, Matt & Kaplan, David M., 2018. "Comparing distributions by multiple testing across quantiles or CDF values," Journal of Econometrics, Elsevier, vol. 206(1), pages 143-166.
    2. Antecol, Heather & Eren, Ozkan & Ozbeklik, Serkan, 2013. "The effect of Teach for America on the distribution of student achievement in primary school: Evidence from a randomized experiment," Economics of Education Review, Elsevier, vol. 37(C), pages 113-125.
    3. Simone Balestra & Uschi Backes-Gellner, 2014. "Heterogeneous effects of pupil-to-teacher ratio policies - A look at class size reduction and teacher aide," Economics of Education Working Paper Series 0102, University of Zurich, Department of Business Administration (IBW), revised Apr 2017.
    4. Katherine Caves & Simone Balestra, 2018. "The impact of high school exit exams on graduation rates and achievement," The Journal of Educational Research, Taylor & Francis Journals, vol. 111(2), pages 186-200, March.
    5. Simone Balestra & Uschi Backes-Gellner, 2017. "Heterogeneous effects of pupil-to-teacher ratio policies - A look at class size reduction and teacher aide," Economics of Education Working Paper Series 0130, University of Zurich, Department of Business Administration (IBW).
    6. Kaplan, David M., 2015. "Improved quantile inference via fixed-smoothing asymptotics and Edgeworth expansion," Journal of Econometrics, Elsevier, vol. 185(1), pages 20-32.
    7. Goldman, Matt & Kaplan, David M., 2018. "Comparing distributions by multiple testing across quantiles or CDF values," Journal of Econometrics, Elsevier, vol. 206(1), pages 143-166.
    8. Marie Connolly & Catherine Haeck, 2018. "Le lien entre la taille des classes et les compétences cognitives et non cognitives," CIRANO Project Reports 2018rp-18, CIRANO.
    9. Xavier D’Haultfoeuille & Pauline Givord, 2014. "La régression quantile en pratique," Économie et Statistique, Programme National Persée, vol. 471(1), pages 85-111.
    10. Haeck, Catherine & Lefebvre, Pierre & Merrigan, Philip, 2014. "The distributional impacts of a universal school reform on mathematical achievements: A natural experiment from Canada," Economics of Education Review, Elsevier, vol. 41(C), pages 137-160.
    11. Denny, Kevin & Oppedisano, Veruska, 2013. "The surprising effect of larger class sizes: Evidence using two identification strategies," Labour Economics, Elsevier, vol. 23(C), pages 57-65.
    12. Jeffrey Penney, 2018. "Dynamic Treatment Effects Of Teacher'S Aides In An Experiment With Multiple Randomizations," Economic Inquiry, Western Economic Association International, vol. 56(2), pages 1244-1260, April.
    13. David M. Kaplan, 2014. "Nonparametric Inference on Quantile Marginal Effects," Working Papers 1413, Department of Economics, University of Missouri.

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    More about this item

    Keywords

    Class size; Heterogeneity; Project STAR;
    All these keywords.

    JEL classification:

    • I21 - Health, Education, and Welfare - - Education - - - Analysis of Education
    • I24 - Health, Education, and Welfare - - Education - - - Education and Inequality

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