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Estimation of Class-Size Effects, Using 'Maimonides' Rule': The Case of French Junior High Schools

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  • Gary-Bobo, Robert J.
  • Mahjoub, Mohamed Badrane

Abstract

Using a rich sample of students from French junior high schools with a panel structure, we obtain small but significant and negative effects of class size on probabilities of educational success, in grades 6 and 7. An 8 to 10 student reduction of class size puts the child of a non-educated mother on an equal footing with the child of a college-educated mother. These effects vanish in grades 8 and 9. We use Angrist and Lavy's (1999) theoretical class size (i.e., "Maimonides' rule") as an instrument for observed class size. This is possible, due to availability of total high school and total grade enrollment in each year, in our exceptional data set. We control for father occupation, mother education and other variables. Using a Probit framework to model transitions from one grade to another (and thus grade repetitions), we simultaneously estimate the student's probabilities of success over 4 years in junior high school. This is done while allowing a general covariance structure of the error terms that affect latent student-performance variables and class-size auxiliary equations.

Suggested Citation

  • Gary-Bobo, Robert J. & Mahjoub, Mohamed Badrane, 2006. "Estimation of Class-Size Effects, Using 'Maimonides' Rule': The Case of French Junior High Schools," CEPR Discussion Papers 5754, C.E.P.R. Discussion Papers.
  • Handle: RePEc:cpr:ceprdp:5754
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    Cited by:

    1. Peter Fredriksson & Björn Öckert & Hessel Oosterbeek, 2013. "Long-Term Effects of Class Size," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 128(1), pages 249-285.
    2. Hægeland, Torbjørn & Raaum, Oddbjørn & Salvanes, Kjell G., 2012. "Pennies from heaven? Using exogenous tax variation to identify effects of school resources on pupil achievement," Economics of Education Review, Elsevier, vol. 31(5), pages 601-614.
    3. Mike Gilraine & Hugh Macartney & Rob McMillan, 2018. "Education Reform in General Equilibrium: Evidence from California's Class Size Reduction," Working Papers tecipa-594, University of Toronto, Department of Economics.
    4. Argaw, Bethlehem A. & Puhani, Patrick A., 2018. "Does class size matter for school tracking outcomes after elementary school? Quasi-experimental evidence using administrative panel data from Germany," Economics of Education Review, Elsevier, vol. 65(C), pages 48-57.
    5. Joshua D. Angrist & Erich Battistin & Daniela Vuri, 2014. "In a Small Moment: Class Size and Moral Hazard in the Mezzogiorno," FBK-IRVAPP Working Papers 2014-04, Research Institute for the Evaluation of Public Policies (IRVAPP), Bruno Kessler Foundation.
    6. Michael Gilraine & Hugh Macartney & Robert McMillan, 2018. "Estimating the Direct and Indirect Effects of Major Education Reforms," NBER Working Papers 24191, National Bureau of Economic Research, Inc.
    7. Joshua D. Angrist & Victor Lavy & Jetson Leder-Luis & Adi Shany, 2019. "Maimonides' Rule Redux," American Economic Review: Insights, American Economic Association, vol. 1(3), pages 309-324, December.
    8. Joshua D. Angrist & Erich Battistin & Daniela Vuri, 2014. "In a Small Moment: Class Size and Moral Hazard in the Mezzogiorno," NBER Working Papers 20173, National Bureau of Economic Research, Inc.
    9. Edwin Leuven & Hessel Oosterbeek & Marte Rønning, 2008. "Quasi‐experimental Estimates of the Effect of Class Size on Achievement in Norway," Scandinavian Journal of Economics, Wiley Blackwell, vol. 110(4), pages 663-693, December.
    10. 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.
    11. Stephen Gibbons & Sandra McNally, 2013. "The Effects of Resources Across School Phases: A Summary of Recent Evidence," CEP Discussion Papers dp1226, Centre for Economic Performance, LSE.

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    More about this item

    Keywords

    Education; Class size; Econometrics; Instrumental variables; Junior high school;
    All these keywords.

    JEL classification:

    • C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models
    • C35 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions
    • I20 - Health, Education, and Welfare - - Education - - - General

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