IDEAS home Printed from https://ideas.repec.org/p/iza/izadps/dp4566.html
   My bibliography  Save this paper

How Consistent Are Class Size Effects?

Author

Listed:
  • Konstantopoulos, Spyros

    (Michigan State University)

Abstract

Evidence from Project STAR has suggested that on average small classes increase student achievement. However, thus far researchers have focused on computing mean differences in student achievement between smaller and larger classes. In this study I focus on the distribution of the small class effects at the school level and compute the inconsistency of the treatment effects across schools. I use data from Project STAR and estimated small class effects for each school on mathematics and reading scores from kindergarten through third grade. The results revealed that school-specific small class effects are both positive and negative and that although students benefit considerably from being in small classes in some schools, in other schools being in small classes is a disadvantage. Small class effects were inconsistent and varied significantly across schools. Full time teacher aide effects were also inconsistent across schools and in some schools students benefit considerably from being in regular classes with a full time aide, while in other schools being in these classes is a disadvantage.

Suggested Citation

  • Konstantopoulos, Spyros, 2009. "How Consistent Are Class Size Effects?," IZA Discussion Papers 4566, Institute of Labor Economics (IZA).
  • Handle: RePEc:iza:izadps:dp4566
    as

    Download full text from publisher

    File URL: https://docs.iza.org/dp4566.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Alan B. Krueger, 1999. "Experimental Estimates of Education Production Functions," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 114(2), pages 497-532.
    Full references (including those not matched with items on IDEAS)

    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. Andersson, Christian, 2007. "Teacher density and student achievement in Swedish compulsory schools," Working Paper Series 2007:4, IFAU - Institute for Evaluation of Labour Market and Education Policy.
    2. Ma, Lingjie & Koenker, Roger, 2006. "Quantile regression methods for recursive structural equation models," Journal of Econometrics, Elsevier, vol. 134(2), pages 471-506, October.
    3. Giacomo De Giorgi & Michele Pellizzari & William Gui Woolston, 2012. "Class Size And Class Heterogeneity," Journal of the European Economic Association, European Economic Association, vol. 10(4), pages 795-830, August.
    4. Martin Schlotter & Guido Schwerdt & Ludger Woessmann, 2011. "Econometric methods for causal evaluation of education policies and practices: a non-technical guide," Education Economics, Taylor & Francis Journals, vol. 19(2), pages 109-137.
    5. Alan B. Krueger, 2002. "Inequality, Too Much of a Good Thing," Working Papers 845, Princeton University, Department of Economics, Industrial Relations Section..
    6. Holla,Alaka & Bendini,Maria Magdalena & Dinarte Diaz,Lelys Ileana & Trako,Iva, 2021. "Is Investment in Preprimary Education Too Low ? Lessons from (Quasi) ExperimentalEvidence across Countries," Policy Research Working Paper Series 9723, The World Bank.
    7. Jesús M. Carro & Pedro Gallardo, 2024. "Effect of class size on student achievement in the COVID‐19 “new normal”," Bulletin of Economic Research, Wiley Blackwell, vol. 76(2), pages 303-318, April.
    8. Gregory A. Gilpin & Anton Bekkerman, 2012. "Cost-effective hiring in US high schools: estimating optimal teacher quantity and quality decisions," Applied Economics Letters, Taylor & Francis Journals, vol. 19(14), pages 1421-1424, September.
    9. John Bishop & Ludger Wossmann, 2004. "Institutional Effects in a Simple Model of Educational Production," Education Economics, Taylor & Francis Journals, vol. 12(1), pages 17-38.
    10. Stephen Machin & Sandra McNally, 2012. "The Evaluation of English Education Policies," National Institute Economic Review, National Institute of Economic and Social Research, vol. 219(1), pages 15-25, January.
    11. Stephen Machin & Sandra McNally & Martina Viarengo, 2018. "Changing How Literacy Is Taught: Evidence on Synthetic Phonics," American Economic Journal: Economic Policy, American Economic Association, vol. 10(2), pages 217-241, May.
    12. Victor Lavy & Analia Schlosser, 2005. "Targeted Remedial Education for Underperforming Teenagers: Costs and Benefits," Journal of Labor Economics, University of Chicago Press, vol. 23(4), pages 839-874, October.
    13. Pekkarinen, Tuomas, 2012. "Gender Differences in Education," IZA Discussion Papers 6390, Institute of Labor Economics (IZA).
    14. Masakazu Hojo, 2011. "Education Production Function and Class-Size Effects in Japanese Public Schools," Global COE Hi-Stat Discussion Paper Series gd11-194, Institute of Economic Research, Hitotsubashi University.
    15. Stephen Machin & Sandra McNally & Costas Meghir, 2010. "Resources and Standards in Urban Schools," Journal of Human Capital, University of Chicago Press, vol. 4(4), pages 365-393.
    16. Alex Hollingsworth & Mike Huang & Ivan J. Rudik & Nicholas J. Sanders, 2020. "A Thousand Cuts: Cumulative Lead Exposure Reduces Academic Achievement," NBER Working Papers 28250, National Bureau of Economic Research, Inc.
    17. David N. Figlio & Cassandra M.D. Hart & Krzysztof Karbownik, 2020. "Effects of Scaling Up Private School Choice Programs on Public School Students," NBER Working Papers 26758, National Bureau of Economic Research, Inc.
    18. H. Naci Mocan & Deborah Viola, 1997. "The Determinants of Child Care Workers' Wages and Compensation: Sectoral Differences, Human Capital, Race, Insiders and Outsiders," NBER Working Papers 6328, National Bureau of Economic Research, Inc.
    19. Roland G. Fryer, Jr & Tanaya Devi & Richard T. Holden, 2012. "Vertical versus Horizontal Incentives in Education: Evidence from Randomized Trials," NBER Working Papers 17752, National Bureau of Economic Research, Inc.
    20. Facundo Albornoz & Samuel Berlinski & Antonio Cabrales, 2016. "Motivation, Resources and the Organization of the School System," IDB Publications (Working Papers) 94958, Inter-American Development Bank.

    More about this item

    Keywords

    small classes; treatment variability; meta-analysis;
    All these keywords.

    JEL classification:

    • I20 - Health, Education, and Welfare - - Education - - - General

    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:dp4566. 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.