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Educational production in East Asia: The impact of family background and schooling policies on student performance

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  • Wößmann, Ludger

Abstract

East Asian students regularly take top positions in international league tables of educational performance. Using internationally comparable student-level data, I estimate how family background and schooling policies affect student performance in five high-performing East Asian economies. Family background is a strong predictor of student performance in Korea and Singapore, while Hong Kong and Thailand achieve more equalized outcomes. There is no evidence that smaller classes improve student performance in East Asia. But other schooling policies such as school autonomy over salaries and regular homework assignments are related to higher student performance in several of the considered countries.

Suggested Citation

  • Wößmann, Ludger, 2005. "Educational production in East Asia: The impact of family background and schooling policies on student performance," Munich Reprints in Economics 19657, University of Munich, Department of Economics.
    • Handle: RePEc:lmu:muenar:19657
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    Cited by:

    1. Jean‐Marie Viaene & Itzhak Zilcha, 2009. "Human Capital and Inequality Dynamics: The Role of Education Technology," Economica, London School of Economics and Political Science, vol. 76(304), pages 760-778, October.
    2. Jaime Andrés Sarmiento Espinel & Adriana Carolina Silva Arias, 2014. "La formación del economista en Colombia," Revista Facultad de Ciencias Económicas, Universidad Militar Nueva Granada, vol. 0(1), pages 231-262.
    3. Hojo, Masakazu & Oshio, Takashi & 小塩, 隆士 & オシオ, タカシ, 2010. "What factors determine student performance in East Asia? New evidence from TIMSS 2007," PIE/CIS Discussion Paper 494, Center for Intergenerational Studies, Institute of Economic Research, Hitotsubashi University.
    4. Ammermüller, Andreas, 2005. "Educational Opportunities and the Role of Institutions," ZEW Discussion Papers 05-44, ZEW - Leibniz Centre for European Economic Research.
    5. Ferraro, Simona & Põder, Kaire, 2018. "School-level policies and the efficiency and equity trade-off in education," Journal of Policy Modeling, Elsevier, vol. 40(5), pages 1022-1037.
    6. Yan Lau, 2019. "The dragon cohort of Hong Kong: traditional beliefs, demographics, and education," Journal of Population Economics, Springer;European Society for Population Economics, vol. 32(1), pages 219-246, January.
    7. Barrera-Osorio, F. & García-Moreno, V. & Patrinos, H., & Porta, E., 2011. "Using the Oaxaca-Blinder Decomposition Technique to Analyze Learning Outcomes Changes over Time: An Application to Indonesia’s Results in PISA Mathematics," Regional and Sectoral Economic Studies, Euro-American Association of Economic Development, vol. 11(3).
    8. Kenn Ariga & Giorgio Brunello, 2006. "Are Education and Training Always Complements? Evidence from Thailand," ILR Review, Cornell University, ILR School, vol. 59(4), pages 613-629, July.
    9. Ludger Wößmann, 2005. "Ursachenkomplexe der PISA-Ergebnisse: Untersuchungen auf Basis der internationalen Mikrodaten," ifo Working Paper Series 16, ifo Institute - Leibniz Institute for Economic Research at the University of Munich.
    10. Polcyn, Jan, 2017. "Edukacja jako dobro publiczne - próba kwantyfikacji [Education as a public good – an attempt at quantification]," MPRA Paper 76606, University Library of Munich, Germany, revised 2017.

    More about this item

    JEL classification:

    • O15 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - Economic Development: Human Resources; Human Development; Income Distribution; Migration
    • I20 - Health, Education, and Welfare - - Education - - - General
    • H52 - Public Economics - - National Government Expenditures and Related Policies - - - Government Expenditures and Education

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