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Who's to Blame? The Determinants of German Students' Achievement in the PISA 2000 Study

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  • Fertig, Michael

Abstract

The publication of the OECD report on the PISA 2000 study induced a public outcry in Germany.On average,German students participating in this standardized test performed considerably below the OECD average and substantially worse than those of other European countries,like Finland or Ireland.However,the results presented by the report consist mainly of country averages which do not take into account any other covariates of individual student achievement.This paper provides a comprehensive econometric analysis of the association of the individual-level reading test scores of German students with individual and family background information and with characteristics of the school and class of the 15 to 16 year old respondents in Germany to the survey.The results of several quantile regression analyses demonstrate that many popular explanations,like too much regulation of schools or the substantial share of non-citizens among the participating students,are by no means supported by the data.Rather results point towards a considerable impact of schools aiming at a more homogenous body of students in terms of their educational achievement.

Suggested Citation

  • Fertig, Michael, 2003. "Who's to Blame? The Determinants of German Students' Achievement in the PISA 2000 Study," RWI Discussion Papers 4, RWI - Leibniz-Institut für Wirtschaftsforschung.
  • Handle: RePEc:zbw:rwidps:4
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    1. repec:fth:prinin:357 is not listed on IDEAS
    2. Fertig, Michael & Schmidt, Christoph M., 2002. "The Role of Background Factors for Reading Literacy: Straight National Scores in the PISA 2000 Study," IZA Discussion Papers 545, Institute of Labor Economics (IZA).
    3. Sims,Christopher A. (ed.), 1994. "Advances in Econometrics," Cambridge Books, Cambridge University Press, number 9780521444606.
    4. Entorf, Horst & Gollac, Michel & Kramarz, Francis, 1999. "New Technologies, Wages, and Worker Selection," Journal of Labor Economics, University of Chicago Press, vol. 17(3), pages 464-491, July.
    5. Miller, Paul & Mulvey, Charles & Martin, Nick, 1997. "Family Characteristics and the Returns to Schooling: Evidence on Gender Differences from a Sample of Australian Twins," Economica, London School of Economics and Political Science, vol. 64(253), pages 119-136, February.
    6. 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.
    7. Jesse Levin, 2001. "For whom the reductions count: A quantile regression analysis of class size and peer effects on scholastic achievement," Empirical Economics, Springer, vol. 26(1), pages 221-246.
    8. David Card & Alan Krueger, 1996. "Labor Market Effects of School Quality: Theory and Evidence," Working Papers 736, Princeton University, Department of Economics, Industrial Relations Section..
    9. Sims,Christopher A. (ed.), 1994. "Advances in Econometrics," Cambridge Books, Cambridge University Press, number 9780521444590.
    10. David Card & Alan B. Krueger, 1996. "Labor Market Effects of School Quality: Theory and Evidence," NBER Working Papers 5450, National Bureau of Economic Research, Inc.
    11. Alan B. Krueger, 1993. "How Computers Have Changed the Wage Structure: Evidence from Microdata, 1984–1989," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 108(1), pages 33-60.
    12. John E. DiNardo & Jörn-Steffen Pischke, 1997. "The Returns to Computer Use Revisited: Have Pencils Changed the Wage Structure Too?," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 112(1), pages 291-303.
    13. Joshua Angrist & Victor Lavy, 2002. "New Evidence on Classroom Computers and Pupil Learning," Economic Journal, Royal Economic Society, vol. 112(482), pages 735-765, October.
    14. de New, John & Schmidt, Christoph M., 1999. "Money for Nothing and Your Chips for Free? The Anatomy of the PC Wage Differential," IZA Discussion Papers 86, Institute of Labor Economics (IZA).
    15. Thomas Warm, 1989. "Weighted likelihood estimation of ability in item response theory," Psychometrika, Springer;The Psychometric Society, vol. 54(3), pages 427-450, September.
    16. Eide, Eric & Showalter, Mark H., 1998. "The effect of school quality on student performance: A quantile regression approach," Economics Letters, Elsevier, vol. 58(3), pages 345-350, March.
    17. Wolter, Stefan C. & Coradi Vellacott, Maja, 2002. "Sibling Rivalry: A Look at Switzerland with PISA Data," IZA Discussion Papers 594, Institute of Labor Economics (IZA).
    18. Hanushek, Eric A, 1986. "The Economics of Schooling: Production and Efficiency in Public Schools," Journal of Economic Literature, American Economic Association, vol. 24(3), pages 1141-1177, September.
    19. Koenker, Roger W & Bassett, Gilbert, Jr, 1978. "Regression Quantiles," Econometrica, Econometric Society, vol. 46(1), pages 33-50, January.
    20. repec:zbw:rwidps:0002 is not listed on IDEAS
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    3. Entorf, Horst & Lauk, Martina, 2006. "Peer Effects, Social Multipliers and Migrants at School: An International Comparison," IZA Discussion Papers 2182, Institute of Labor Economics (IZA).
    4. Oecd, 2011. "The Impact of the 1999 Education Reform in Poland," OECD Education Working Papers 49, OECD Publishing.
    5. Abdul-Hamid, Husein & Abu-Lebdeh, Khattab M. & Patrinos, Harry Anthony, 2011. "Assessment testing can be used to inform policy decisions : the case of Jordan," Policy Research Working Paper Series 5890, The World Bank.
    6. Luciano Canova & Alessandro Vaglio, 2011. "Why do educated mothers matter? A model of parental help," Working Papers 2011/3, Institut d'Economia de Barcelona (IEB).
    7. Ludger Wößmann, 2003. "European education production functions: what makes a difference for student achievement in Europe?," European Economy - Economic Papers 2008 - 2015 190, Directorate General Economic and Financial Affairs (DG ECFIN), European Commission.
    8. Elisa Rose Birch & Paul W. Miller, 2006. "Student Outcomes At University In Australia: A Quantile Regression Approach," Australian Economic Papers, Wiley Blackwell, vol. 45(1), pages 1-17, March.
    9. 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," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 22606, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
    10. Carmo Seabra & Marta Rosado, 2015. "Public and Private school management systems: A Comparative analysis," Investigaciones de Economía de la Educación volume 10, in: Marta Rahona López & Jennifer Graves (ed.), Investigaciones de Economía de la Educación 10, edition 1, volume 10, chapter 19, pages 375-394, Asociación de Economía de la Educación.
    11. Natalia Zinovyeva & Florentino Felgueroso & Pablo Vazquez Vega, 2008. "Immigration and Students' Achievement in Spain," Working Papers 2008-37, FEDEA.
    12. Gokce Uysal & M. Alper Dincer, 2009. "Determinants of Student Achievement in Turkey," Working Papers 002, Bahcesehir University, Betam.
    13. Entorf, Horst & Lauk, Martina, 2006. "Peer effects, social multipliers and migration at school: An international comparison," HWWI Research Papers 3-3, Hamburg Institute of International Economics (HWWI).
    14. Raul Ramos & Juan Carlos Duque & Sandra Nieto, 2012. "“Decomposing the Rural-Urban Differential in Student Achievement in Colombia Using PISA Microdata”," AQR Working Papers 201210, University of Barcelona, Regional Quantitative Analysis Group, revised Mar 2013.
    15. Amini, Chiara & Commander, Simon, 2011. "Educational Scores: How Does Russia Fare?," IZA Discussion Papers 6033, Institute of Labor Economics (IZA).
    16. Hynsjö, Disa & Damon, Amy, 2016. "Bilingual education in Peru: Evidence on how Quechua-medium education affects indigenous children's academic achievement," Economics of Education Review, Elsevier, vol. 53(C), pages 116-132.
    17. Josep-Oriol Escardíbul & Toni Mora, 2013. "Teacher gender and student performance in mathematics. Evidence from Catalonia," Working Papers 2013/7, Institut d'Economia de Barcelona (IEB).
    18. Justina A.V. Fischer, 2005. "The Impact of Direct Democracy on Public Education: Performance of Swiss Students in Reading," University of St. Gallen Department of Economics working paper series 2005 2005-10, Department of Economics, University of St. Gallen.
    19. Zoltan Hermann & Daniel Horn, 2011. "How inequality of opportunity and mean student performance are related? - A quantile regression approach using PISA data," CERS-IE WORKING PAPERS 1124, Institute of Economics, Centre for Economic and Regional Studies.

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    More about this item

    Keywords

    Student Achievement; School Quality; Quantile Regression;
    All these keywords.

    JEL classification:

    • I21 - Health, Education, and Welfare - - Education - - - Analysis of Education

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