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

  • Ding, Weili
  • Lehrer, Steven F.

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.

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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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Paper provided by Vancouver School of Economics in its series CLSSRN working papers with number clsrn_admin-2011-12.

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Length: 38 pages
Date of creation: 26 Jun 2011
Date of revision: 26 Jun 2011
Handle: RePEc:ubc:clssrn:clsrn_admin-2011-12
Contact details of provider: Web page: http://www.clsrn.econ.ubc.ca/

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  1. Lex Borghans & Bas ter Weel & Bruce A. Weinberg, 2008. "Interpersonal Styles and Labor Market Outcomes," Journal of Human Resources, University of Wisconsin Press, vol. 43(4).
  2. Ding, Weili & Lehrer, Steven F., 2009. "Estimating Treatment Effects from Contaminated Multi-Period Education Experiments: The Dynamic Impacts of Class Size Reductions," CLSSRN working papers clsrn_admin-2009-43, Vancouver School of Economics, revised 22 Jul 2009.
  3. Flavio Cunha & James J. Heckman & Susanne M. Schennach, 2010. "Estimating the Technology of Cognitive and Noncognitive Skill Formation," Econometrica, Econometric Society, vol. 78(3), pages 883-931, 05.
  4. Willard G. Manning & John Mullahy, 1999. "Estimating Log Models: To Transform or Not to Transform?," NBER Technical Working Papers 0246, National Bureau of Economic Research, Inc.
  5. Anderson, Michael L., 2008. "Multiple Inference and Gender Differences in the Effects of Early Intervention: A Reevaluation of the Abecedarian, Perry Preschool, and Early Training Projects," Journal of the American Statistical Association, American Statistical Association, vol. 103(484), pages 1481-1495.
  6. Bandiera, Oriana & Larcinese, Valentino & Rasul, Imran, 2009. "Heterogeneous Class Size Effects: New Evidence from a Panel of University Students," IZA Discussion Papers 4496, Institute for the Study of Labor (IZA).
  7. Alan B. Krueger, 1997. "Experimental Estimates of Education Production Functions," NBER Working Papers 6051, National Bureau of Economic Research, Inc.
  8. James Marshall & Michael Peters (ed.), 1999. "Education Policy," Books, Edward Elgar Publishing, number 1657, April.
  9. Jesse Rothstein, 2010. "Teacher Quality in Educational Production: Tracking, Decay, and Student Achievement," The Quarterly Journal of Economics, Oxford University Press, vol. 125(1), pages 175-214.
  10. James J. Heckman & Jora Stixrud & Sergio Urzua, 2006. "The Effects of Cognitive and Noncognitive Abilities on Labor Market Outcomes and Social Behavior," NBER Working Papers 12006, National Bureau of Economic Research, Inc.
  11. Sergio Firpo & Nicole M. Fortin & Thomas Lemieux, 2007. "Unconditional Quantile Regressions," NBER Technical Working Papers 0339, National Bureau of Economic Research, Inc.
  12. Weili Ding & Steven Lehrer, 2005. "Class Size and Student Achievement: Experimental Estimates of Who Benefits and Who Loses from Reductions," Working Papers 1046, Queen's University, Department of Economics.
  13. Yona Rubinstein & James J. Heckman, 2001. "The Importance of Noncognitive Skills: Lessons from the GED Testing Program," American Economic Review, American Economic Association, vol. 91(2), pages 145-149, May.
  14. Yoav Benjamini & Abba M. Krieger & Daniel Yekutieli, 2006. "Adaptive linear step-up procedures that control the false discovery rate," Biometrika, Biometrika Trust, vol. 93(3), pages 491-507, September.
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