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Mixing versus sorting in schooling: Evidence from the equalization policy in South Korea

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  • Kim, Taejong
  • Lee, Ju-Ho
  • Lee, Young

Abstract

This paper employs the difference-in-differences empirical strategy and quantile regressions to analyze the effects of sorting and mixing on the academic performance of high school students in South Korea. In Korea, about half of high schools are subject to the equalization policy (EP), and must therefore passively accept students randomly assigned to them. On the other hand, about half of high schools are in non-EP areas, so students are sorted among schools based on students' ability levels. Two main results emerge from this study. First, sorting raises test scores of students outside the EP areas by roughly 0.3 standard deviations, relative to mixing. Second, more surprisingly, quantile regression results reveal that sorting helps students above the median in the ability distribution, and does no harm to those below the median.

Suggested Citation

  • Kim, Taejong & Lee, Ju-Ho & Lee, Young, 2008. "Mixing versus sorting in schooling: Evidence from the equalization policy in South Korea," Economics of Education Review, Elsevier, vol. 27(6), pages 697-711, December.
  • Handle: RePEc:eee:ecoedu:v:27:y:2008:i:6:p:697-711
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    Cited by:

    1. Salvador Contreras & Frank Badua & Mitchell Adrian, 2012. "Peer Effects on Undergraduate Business Student Performance," International Review of Economic Education, Economics Network, University of Bristol, vol. 11(1), pages 57-66.
    2. Susanne Link, 2012. "Single-Sex Schooling and Student Performance: Quasi-Experimental Evidence from South Korea," ifo Working Paper Series 146, ifo Institute - Leibniz Institute for Economic Research at the University of Munich.
    3. Rodrigues, Clarissa Guimarães & Rios-Neto, Eduardo Luiz Gonçalves & de Xavier Pinto, Cristine Campos, 2013. "Changes in test scores distribution for students of the fourth grade in Brazil: A relative distribution analysis for the years 1997–2005," Economics of Education Review, Elsevier, vol. 34(C), pages 227-242.
    4. Nam, Kigon, 2014. "Until when does the effect of age on academic achievement persist? Evidence from Korean data," Economics of Education Review, Elsevier, vol. 40(C), pages 106-122.
    5. Marisa Hidalgo Hidalgo, 2009. "Tracking can be more equitable than mixing: peer effects and college attendance," Working Papers 09.04, Universidad Pablo de Olavide, Department of Economics, revised Jul 2012.
    6. Eleanor Jawon Choi & Hyungsik Roger Moon & Geert Ridder, 2014. "Estimation of an Education Production Function under Random Assignment with Selection," American Economic Review, American Economic Association, vol. 104(5), pages 206-211, May.
    7. Liang Choon Wang, 2016. "The effect of high-stakes testing on suicidal ideation of teenagers with reference-dependent preferences," Journal of Population Economics, Springer;European Society for Population Economics, vol. 29(2), pages 345-364, April.
    8. Agnes Baeker & Mario Mechtel, 2015. "Peer Settings Induce Cheating on Task Performance," IAAEU Discussion Papers 201506, Institute of Labour Law and Industrial Relations in the European Union (IAAEU).
    9. Mechtel, Mario & Bäker, Agnes, 2015. "Peer Effects in Cheating on Task Performance," Annual Conference 2015 (Muenster): Economic Development - Theory and Policy 113093, Verein für Socialpolitik / German Economic Association.
    10. Wang, Liang Choon, 2015. "All work and no play? The effects of ability sorting on students’ non-school inputs, time use, and grade anxiety," Economics of Education Review, Elsevier, vol. 44(C), pages 29-41.
    11. Agnes Baeker & Mario Mechtel, 2013. "The Role of Task Meaning on Output in Groups: Experimental Evidence," IAAEU Discussion Papers 201308, Institute of Labour Law and Industrial Relations in the European Union (IAAEU).
    12. Murguia Baysse, Juan Manuel, 2013. "Essays on agricultural, financial economics and education," ISU General Staff Papers 201301010800004458, Iowa State University, Department of Economics.

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