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School choice, school switching, and optimal assignment

Author

Listed:
  • Hessel Oosterbeek

    (University of Amsterdam)

  • Tina Rozsos

    (Vrije Universiteit Amsterdam)

  • Bas van der Klaauw

    (Vrije Universiteit Amsterdam)

Abstract

Close to 20% of secondary school students in Amsterdam - and elsewhere - transfer between secondary schools at some point, even when initially placed in their most-preferred school. School switching is costly for the students involved and disrupts the learning environment of their former and new classmates. Using data from the Amsterdam secondary-school match linked to administrative registers, we show that switching can be predicted by hard-to-rationalize initial school choices. Over 60% of switchers can be correctly identified at the admission stage. Simulations indicate that encouraging predicted switchers to adjust their preference ranking of schools could reduce the switching rate by almost 15%.

Suggested Citation

  • Hessel Oosterbeek & Tina Rozsos & Bas van der Klaauw, 2025. "School choice, school switching, and optimal assignment," Tinbergen Institute Discussion Papers 25-066/V, Tinbergen Institute.
    • Handle: RePEc:tin:wpaper:20250066
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    References listed on IDEAS

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    1. Monique De Haan & Pieter A. Gautier & Hessel Oosterbeek & Bas van der Klaauw, 2023. "The Performance of School Assignment Mechanisms in Practice," Journal of Political Economy, University of Chicago Press, vol. 131(2), pages 388-455.
    2. Jeongdai Kim & Paul A. Jargowsky, 2009. "The GINI coefficient and segregation on a continuous variable," Research on Economic Inequality, in: Occupational and Residential Segregation, pages 57-70, Emerald Group Publishing Limited.
    3. Andrei Munteanu, 2024. "School Choice, Student Sorting and Academic Performance," Cahiers de recherche / Working Papers 2401, Chaire de recherche sur les enjeux économiques intergénérationnels / Research Chair in Intergenerational Economics.
    4. Olivier De Groote, 2025. "Dynamic Effort Choice in High School: Costs and Benefits of an Academic Track," Journal of Labor Economics, University of Chicago Press, vol. 43(2), pages 467-502.
    5. Tomás Larroucau & Ignacio A. Rios & Anaïs Fabre & Christopher Neilson, 2025. "College Application Mistakes and the Design of Information Policies at Scale," NBER Working Papers 34164, National Bureau of Economic Research, Inc.
    6. Oosterbeek, Hessel & Sóvágó, Sándor & van der Klaauw, Bas, 2021. "Preference heterogeneity and school segregation," Journal of Public Economics, Elsevier, vol. 197(C).
    7. Ketel, Nadine & Oosterbeek, Hessel & Sóvágó, Sándor & van der Klaauw, Bas, 2023. "The (un)importance of school assignment," CEPR Discussion Papers 18586, Centre for Economic Policy Research.
    8. Tom‡s Larroucau & Ignacio A. Rios & Ana•s Fabre & Christopher Neilson, 2025. "College Application Mistakes and the Design of Information Policies at Scale," Cowles Foundation Discussion Papers 2461, Cowles Foundation for Research in Economics, Yale University.
    9. Diether W Beuermann & C Kirabo Jackson & Laia Navarro-Sola & Francisco Pardo, 2023. "What is a Good School, and Can Parents Tell? Evidence on the Multidimensionality of School Output," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 90(1), pages 65-101.
    10. Atila Abdulkadiroğlu & Nikhil Agarwal & Parag A. Pathak, 2017. "The Welfare Effects of Coordinated Assignment: Evidence from the New York City High School Match," American Economic Review, American Economic Association, vol. 107(12), pages 3635-3689, December.
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    Keywords

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    JEL classification:

    • C35 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • I21 - Health, Education, and Welfare - - Education - - - Analysis of Education

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