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Experimental Estimates of the Impacts of Class Size on Test Scores: Robustness and Heterogeneity

Author

Listed:
  • Ding, Weili
  • Lehrer, Steven F.
Abstract
Proponents of class size reductions draw heavily on the results from Project STAR to support their initiatives. Adding to the political appeal of these initiative are reports that minority and economically disadvantaged students received the largest benefits from smaller classes. We extend this research in two directions. First, to address correlated outcomes from the same class size treatment, we account for the over-rejection of the Null hypotheses by using multiple inference procedures. Second, we conduct a more detailed examination of the heterogeneous impacts of class size reductions on measures of cognitive and noncognitive achievement using more flexible models. We find that students with higher test scores received greater benefits from class size reductions. Furthermore, we present evidence that the main effects of the small class treatment are robust to corrections for the multiple hypotheses being tested. However, these same corrections lead the differential impacts of smaller classes by race and freelunch status to become statistically insignificant.

Suggested Citation

  • Ding, Weili & Lehrer, Steven F., 2011. "Experimental Estimates of the Impacts of Class Size on Test Scores: Robustness and Heterogeneity," CLSSRN working papers clsrn_admin-2011-12, Vancouver School of Economics, revised 26 Jun 2011.
    • Handle: RePEc:ubc:clssrn:clsrn_admin-2011-12
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    File URL: http://www.clsrn.econ.ubc.ca/workingpapers/CLSRN%20Working%20Paper%20no.%2077%20-%20Ding%20and%20Lehrer.pdf
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    References listed on IDEAS

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    Cited by:

    1. Jeffrey Penney, 2023. "Cautions when normalizing the dependent variable in a regression as a z‐score," Economic Inquiry, Western Economic Association International, vol. 61(2), pages 402-412, April.
    2. Graham McKee & Katharine Sims & Steven Rivkin, 2015. "Disruption, learning, and the heterogeneous benefits of smaller classes," Empirical Economics, Springer, vol. 48(3), pages 1267-1286, May.
    3. Mueller, Steffen, 2013. "Teacher experience and the class size effect — Experimental evidence," Journal of Public Economics, Elsevier, vol. 98(C), pages 44-52.
    4. Weili Ding, 2020. "Laboratory experiments can pre-design to address power and selection issues," Journal of the Economic Science Association, Springer;Economic Science Association, vol. 6(2), pages 125-138, December.
    5. Michael J. Kottelenberg & Steven F. Lehrer, 2017. "Targeted or Universal Coverage? Assessing Heterogeneity in the Effects of Universal Child Care," Journal of Labor Economics, University of Chicago Press, vol. 35(3), pages 609-653.
    6. 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.
    7. Pål Schøne & Kristine von Simson & Marte Strøm, 2020. "Peer gender and educational choices," Empirical Economics, Springer, vol. 59(4), pages 1763-1797, October.
    8. Ding, Weili & Lehrer, Steven F., 2014. "Understanding the role of time-varying unobserved ability heterogeneity in education production," Economics of Education Review, Elsevier, vol. 40(C), pages 55-75.
    9. Jan Kluge & Michael Weber, 2015. "Decomposing the German East-West wage gap," ifo Working Paper Series 205, ifo Institute - Leibniz Institute for Economic Research at the University of Munich.
    10. Jeffrey Penney, 2017. "Racial Interaction Effects and Student Achievement," Education Finance and Policy, MIT Press, vol. 12(4), pages 447-467, Fall.
    11. Middleditch, Paul & Moindrot, Will & Rudkin, Simon, 2022. "Teaching with Twitter: An extension to the traditional learning environment," International Review of Economics Education, Elsevier, vol. 41(C).

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    More about this item

    Keywords

    class size; multiple inference; unconditional quantile regression; treatment effect heterogeneity; test score gaps; and education experiment;
    All these keywords.

    JEL classification:

    • I20 - Health, Education, and Welfare - - Education - - - General
    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • I24 - Health, Education, and Welfare - - Education - - - Education and Inequality

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