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School choice, school switching, and optimal assignment

Author

Listed:
  • Hessel Oosterbeek
  • Tina Rozsos
  • Bas van der Klaauw

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," RFBerlin Discussion Paper Series 25159, ROCKWOOL Foundation Berlin (RFBerlin).
  • Handle: RePEc:crm:wpaper:25159
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    JEL classification:

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

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