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The Segmentation of the Argentine Education System: Evidence from PISA 2009

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  • Krüger, N.

Abstract

For decades, one of the main goals for policy makers throughout the world has been to provide equal educational opportunities. Nevertheless, many countries still face great challenges in this respect, especially considering equality in the distribution of resources. Since the early eighties, Argentina has focused the fact that the education system is segmented, i.e., divided into groups of institutions of differential quality in which students are distributed according to their socio-economic background. This means that schooling reproduces and reinforces existing patterns of social inequality. The purpose of this article is to contribute to the comprehension and the diagnosis of the current relevance of this phenomenon. Based on information from the PISA 2009 survey, the aim is to establish the degree of educational segmentation, evaluating the distribution of the schools physical, human, and social capitals, as well as the interaction of these resources with student characteristics. A cluster analysis is performed for visualising how these factors lead to the configuration of different school profiles. This may be a useful tool to assist in designing strategies to level the most disadvantaged schools, thus better mediating the impact of socio-economic background on educational success.

Suggested Citation

  • Krüger, N., 2011. "The Segmentation of the Argentine Education System: Evidence from PISA 2009," Regional and Sectoral Economic Studies, Euro-American Association of Economic Development, vol. 11(3).
  • Handle: RePEc:eaa:eerese:v:11:y2011:i:3_3
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    File URL: http://www.usc.es/economet/reviews/eers1133.pdf
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    References listed on IDEAS

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    1. Robert Hutchens, 2004. "One Measure of Segregation," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 45(2), pages 555-578, May.
    2. Jacob M. Markman & Eric A. Hanushek & John F. Kain & Steven G. Rivkin, 2003. "Does peer ability affect student achievement?," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 18(5), pages 527-544.
    3. Mª Jesús Mancebón Torrubia & Domingo Pérez-Ximénez de Embún, 2007. "Conciertos educativos y selección académica y social del alumnado," Hacienda Pública Española / Review of Public Economics, IEF, vol. 180(1), pages 77-108, March.
    4. MANCEBÓN TORRUBIA, María Jesús & PÉREZ XIMÉNEZ-DE-EMBÚN, Domingo, 2010. "Una Valoracion Del Grado De Segregación Socioeconómica Existente En El Sistema Educativo Español. Un Analisis Por Comunidades Autonómas A Partir De Pisa 2006," Regional and Sectoral Economic Studies, Euro-American Association of Economic Development, vol. 10(3).
    5. Oecd, 2011. "Private schools: Who Benefits?," PISA in Focus 7, OECD Publishing.
    6. Iatarola, P. & Stiefel, L., 2003. "Intradistrict equity of public education resources and performance," Economics of Education Review, Elsevier, vol. 22(1), pages 69-78, February.
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    Cited by:

    1. Susana Faria & Maria Conceição Portela, 2016. "Student Performance in Mathematics using PISA-2009 data for Portugal," Working Papers de Gestão (Management Working Papers) 01, Católica Porto Business School, Universidade Católica Portuguesa.

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    More about this item

    Keywords

    equality; educational resources; clusters;
    All these keywords.

    JEL classification:

    • I21 - Health, Education, and Welfare - - Education - - - Analysis of Education
    • H41 - Public Economics - - Publicly Provided Goods - - - Public Goods
    • C38 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Classification Methdos; Cluster Analysis; Principal Components; Factor Analysis

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