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The effect of early tracking on participation in higher education

Author

Listed:
  • Roel van Elk

    (CPB Netherlands Bureau for Economic Policy Analysis)

  • Marc van der Steeg
  • Dinand Webbink

Abstract

This paper examines the impact of early tracking on enrollment in and completion of higher education. We compare pupils that are directly tracked in lower general secondary education (‘mavo’) to pupils that postpone their choice of education level by entering secondary education in a combined first-grade class. Potential self-selection problems are addressed in two ways. First of all, using micro data allows us to control for a large set of individual background characteristics including tests of cognitive ability. Second, we exploit differences in regional supply of particular school types.The estimates show that early tracking has a detrimental effect on enrollment in and completion of higher education for pupils who leave primary education with a mavo advice. In addition, we find no evidence that pupils who leave primary education with a higher general secondary education (‘havo’) advice would be negatively affected by being in a comprehensive class together with the mavo advice pupils.Enrollment in and completion of higher education can be increased by stimulating participation in combined first-grade classes that keep pupils with a mavo or havo advice together for an additional one or two years.

Suggested Citation

  • Roel van Elk & Marc van der Steeg & Dinand Webbink, 2009. "The effect of early tracking on participation in higher education," CPB Document 182, CPB Netherlands Bureau for Economic Policy Analysis.
    • Handle: RePEc:cpb:docmnt:182
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    References listed on IDEAS

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    1. Giorgio Brunello & Massimo Giannini, 2004. "Stratified or Comprehensive? The Economic Efficiency of School Design," Scottish Journal of Political Economy, Scottish Economic Society, vol. 51(2), pages 173-193, May.
    2. Laura M. Argys & Daniel I. Rees & Dominic J. Brewer, 1996. "Detracking America's schools: Equity at zero cost?," Journal of Policy Analysis and Management, John Wiley & Sons, Ltd., vol. 15(4), pages 623-645.
    3. Kenn Ariga & Giorgio Brunello, 2007. "Does Secondary School Tracking Affect Performance? Evidence from IALS," KIER Working Papers 630, Kyoto University, Institute of Economic Research.
    4. Joshua D. Angrist, 2004. "Treatment effect heterogeneity in theory and practice," Economic Journal, Royal Economic Society, vol. 114(494), pages 52-83, March.
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    Cited by:

    1. Eva Feron & Trudie Schils & Bas ter Weel, 2016. "Does the Teacher Beat the Test? The Value of the Teacher’s Assessment in Predicting Student Ability," De Economist, Springer, vol. 164(4), pages 391-418, December.
    2. Feron, Eva & Schils, Trudie & ter Weel, Bas, 2015. "Does the Teacher Beat the Test? The Additional Value of Teacher Assessment in Predicting Student Ability," IZA Discussion Papers 8768, Institute of Labor Economics (IZA).
    3. Bas ter Weel & Eva Feron & Trudie Schils, 2015. "Does the teacher beat the test? The additional value of teacher assessment in predicting student ability," CPB Discussion Paper 300, CPB Netherlands Bureau for Economic Policy Analysis.
    4. Betts, Julian R., 2011. "The Economics of Tracking in Education," Handbook of the Economics of Education, in: Erik Hanushek & Stephen Machin & Ludger Woessmann (ed.), Handbook of the Economics of Education, edition 1, volume 3, chapter 7, pages 341-381, Elsevier.
    5. Wiemer Salverda & Christina Haas & Marloes Graaf-zijl & Bram Lancee & Natascha Notten & Tahnee Ooms, 2013. "GINI Country Report: Growing Inequalities and their Impacts in the Netherlands," GINI Country Reports netherlands, AIAS, Amsterdam Institute for Advanced Labour Studies.

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    JEL classification:

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

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