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The Role of Background Factors for Reading Literacy: Straight National Scores in the PISA 2000 Study

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Author Info

  • Fertig, Michael

    ()
    (ISG, Cologne)

  • Schmidt, Christoph M.

    ()
    (RWI)

Abstract

Based on the individual-level data of the PISA 2000 study, this note 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.

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Bibliographic Info

Paper provided by Institute for the Study of Labor (IZA) in its series IZA Discussion Papers with number 545.

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Length: 20 pages
Date of creation: Aug 2002
Date of revision:
Handle: RePEc:iza:izadps:dp545

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Keywords: reading literacy; school resources; quantile regression;

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Cited by:
  1. Michael Fertig & Robert E. Wright, 2003. "School Quality, Educational Attainment and Aggregation Bias," RWI Discussion Papers 0009, Rheinisch-Westfälisches Institut für Wirtschaftsforschung.
  2. 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, 08.
  3. Entorf, Horst & Minoiu, Nicoleta, 2004. "What a Difference Immigration Law Makes: PISA results, migration background, socioeconomic status and social mobility in Europe and traditional countries of immigration," Darmstadt Discussion Papers in Economics 37288, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute of Economics (VWL).
  4. Natalia Zinovyeva & Florentino Felgueroso & Pablo Vazquez Vega, 2008. "Immigration and Students' Achievement in Spain," Working Papers 2008-37, FEDEA.
  5. Paul Rodríguez Lesmes & José Trujillo & Daniel Valderrama, 2013. "Más allá de la infraestructura: el impacto de las bibliotecas públicas en la calidad de la educación," DOCUMENTOS DE TRABAJO 010499, UNIVERSIDAD DEL ROSARIO.
  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 for Economic Research at the University of Munich, vol. 59(09), pages 03-21, 05.
  7. 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.
  8. 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.

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