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Socio-Economic Factors for Reading Performance in Pirls: Income Inequality and Segregation by Achievements

Author

Listed:
  • Tamara I. Petrova

    (National Research University Higher School of Economics.)

  • Daniel A. Alexandrov

    (National Research University Higher School of Economics.)

Abstract

This study examines the relationship between family and school characteristics, and student reading performance; and how these vary across countries with different levels of economic inequality and stratification. Economic inequality is measured with the Gini index and stratification by the distribution of students by reading achievements. Reading tests and questionnaire responses of 190,456 fourth-graders, their parents and 6,987 school administrators in 41 countries were analysed using multilevel analyses. Students with lack of early home literacy activities have better test scores in schools with higher average socioeconomic status (SES), and reading scores in countries with a high level of economic inequality. The higher the stratification level, the better student reading achievements, despite the stratification measure indicating the inequality of their distribution among schools

Suggested Citation

  • Tamara I. Petrova & Daniel A. Alexandrov, 2015. "Socio-Economic Factors for Reading Performance in Pirls: Income Inequality and Segregation by Achievements," HSE Working papers WP BRP 25/EDU/2015, National Research University Higher School of Economics.
    • Handle: RePEc:hig:wpaper:25edu2015
    as

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    File URL: http://www.hse.ru/data/2015/03/11/1093739928/25EDU2015.pdf
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    1. 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.
    2. Eric A. Hanushek & Ludger Wössmann, 2006. "Does Educational Tracking Affect Performance and Inequality? Differences- in-Differences Evidence Across Countries," Economic Journal, Royal Economic Society, vol. 116(510), pages 63-76, March.
    3. Thomas Fuchs & Ludger Wossmann, 2004. "Computers and student learning: bivariate and multivariate evidence on the availability and use of computers at home and at school," Brussels Economic Review, ULB -- Universite Libre de Bruxelles, vol. 47(3-4), pages 359-386.
    4. Ron W Zimmer & Eugenia F Toma, 2000. "Peer effects in private and public schools across countries," Journal of Policy Analysis and Management, John Wiley & Sons, Ltd., vol. 19(1), pages 75-92.
    5. Eric A. Hanushek, 1998. "Conclusions and controversies about the effectiveness of school resources," Economic Policy Review, Federal Reserve Bank of New York, vol. 4(Mar), pages 11-27.
    6. Ludger Wößmann, 2003. "Schooling Resources, Educational Institutions and Student Performance: the International Evidence," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 65(2), pages 117-170, May.
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    More about this item

    Keywords

    educational achievements; inequality; peer effects; PIRLS; school resources; segregation; socio-economic status;
    All these keywords.

    JEL classification:

    • I24 - Health, Education, and Welfare - - Education - - - Education and Inequality

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    This paper has been announced in the following NEP Reports:

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