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The Role of Background Factors for Reading Literacy: Straight National scores in the Pisa 2000 Study

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  • Fertig, Michael
  • Schmidt, Christoph M

Abstract

Based on the individual-level data of the PISA 2000 study, this Paper provides a detailed econometric analysis of the way that reading test scores are associated with individual and family background information, and with characteristics of the school and class of the 15 to 16 year old respondents to the survey. Based on our quantile regressions, we interpret the national performance scores conditional on these observable characteristics, as the reflection of different education systems. Our findings suggest that US students, particularly those in the lower quantiles, are served relatively unsatisfactorily by their system of education. Moreover, part of the potential for improvement seems to involve measurable aspects, which could be altered and monitored easily.

Suggested Citation

  • Fertig, Michael & Schmidt, Christoph M, 2002. "The Role of Background Factors for Reading Literacy: Straight National scores in the Pisa 2000 Study," CEPR Discussion Papers 3544, C.E.P.R. Discussion Papers.
  • Handle: RePEc:cpr:ceprdp:3544
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    References listed on IDEAS

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    1. Lee, Jong-Wha & Barro, Robert J, 2001. "Schooling Quality in a Cross-Section of Countries," Economica, London School of Economics and Political Science, vol. 68(272), pages 465-488, November.
    2. Borjas, George J, 1985. "Assimilation, Changes in Cohort Quality, and the Earnings of Immigrants," Journal of Labor Economics, University of Chicago Press, vol. 3(4), pages 463-489, October.
    3. Card, David & Krueger, Alan B, 1992. "Does School Quality Matter? Returns to Education and the Characteristics of Public Schools in the United States," Journal of Political Economy, University of Chicago Press, vol. 100(1), pages 1-40, February.
    4. Thomas Warm, 1989. "Weighted likelihood estimation of ability in item response theory," Psychometrika, Springer;The Psychometric Society, vol. 54(3), pages 427-450, September.
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    Cited by:

    1. Fertig, Michael & Wright, Robert E., 2005. "School quality, educational attainment and aggregation bias," Economics Letters, Elsevier, vol. 88(1), pages 109-114, July.
    2. Jhorland Ayala Garcia & Shirly Marrugo Llorente & Bernardo Saray Ricardo, 2011. "Antecedentes Familiares y Rendimiento Académico en los Colegios Oficiales de Cartagena," REVISTA ECONOMÍA & REGIÓN, UNIVERSIDAD TECNOLÓGICA DE BOLÍVAR, December.
    3. Martins, Lurdes & Veiga, Paula, 2010. "Do inequalities in parents' education play an important role in PISA students' mathematics achievement test score disparities?," Economics of Education Review, Elsevier, vol. 29(6), pages 1016-1033, December.
    4. Paul Rodríguez-Lesmes & José D. Trujillo & Daniel Valderrama, 2015. "Are Public Libraries Improving Quality of Education? When the Provision of Public Goods is not Enough," REVISTA DESARROLLO Y SOCIEDAD, UNIVERSIDAD DE LOS ANDES-CEDE, December.
    5. Oecd, 2011. "The Impact of the 1999 Education Reform in Poland," OECD Education Working Papers 49, OECD Publishing.
    6. Christa Stewens & Malte Ristau & Reiner Klingholz & Bertram Wiest & Stefan Schaible & Christian Böllhoff & Christel Humme, 2006. "Familienpolitik: Förderung von Familien - nach welchem Konzept?," ifo Schnelldienst, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 59(09), pages 03-21, May.
    7. Guillermo Jopen & Walter Gómez & Herbert Olivera, 2014. " Sistema educativo peruano: balance y agenda pendiente," Documentos de Trabajo / Working Papers 2014-379, Departamento de Economía - Pontificia Universidad Católica del Perú.
    8. repec:zbw:rwidps:0009 is not listed on IDEAS
    9. Giambona, Francesca & Porcu, Mariano, 2015. "Student background determinants of reading achievement in Italy. A quantile regression analysis," International Journal of Educational Development, Elsevier, vol. 44(C), pages 95-107.
    10. Zoltan Hermann & Daniel Horn, 2011. "How inequality of opportunity and mean student performance are related? - A quantile regression approach using PISA data," IEHAS Discussion Papers 1124, Institute of Economics, Centre for Economic and Regional Studies, Hungarian Academy of Sciences.
    11. Geovanny Castro Aristizabal & Marcela Diaz Rosero & Jairo Tobar Bedoya, 2016. "Causas de las diferencias en desempeño escolar entre los colegios públicos y privados: Colombia en las pruebas SABER11 2014," Working Papers 26, Faculty of Economics and Management, Pontificia Universidad Javeriana Cali.
    12. Natalia Zinovyeva & Florentino Felgueroso & Pablo Vazquez Vega, 2008. "Immigration and Students' Achievement in Spain," Working Papers 2008-37, FEDEA.
    13. Stephen Machin & Patrick A. Puhani, 2005. "Special Issue on the Economics of Education - Policies and Empirical Evidence: Editorial," German Economic Review, Verein für Socialpolitik, vol. 6(3), pages 259-267, August.
    14. Michael Fertig & Robert E. Wright, 2003. "School Quality, Educational Attainment and Aggregation Bias," RWI Discussion Papers 0009, Rheinisch-Westfälisches Institut für Wirtschaftsforschung.

    More about this item

    Keywords

    quantile regression; reading literacy; school resources;

    JEL classification:

    • I21 - Health, Education, and Welfare - - Education - - - Analysis of Education
    • I28 - Health, Education, and Welfare - - Education - - - Government Policy

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