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PISA : what makes the difference?

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  • Andreas Ammermüller

    ()
    (Centre for European Economic Research)

Abstract

The huge difference in the level and variance of student performance in the 2000 PISA study between Finland and Germany motivates this paper. It analyses why Finnish students performed so much better by estimating educational production functions for both countries. The difference in the reading proficiency scores is assigned to different effects, using Oaxaca-Blinder and Juhn-Murphy-Pierce decomposition techniques. The analysis shows that German students have on average a more favorable background except for the lowest deciles, but experience much lower returns to these background characteristics in terms of test scores than Finnish students. The results imply that early streaming in Germany penalizes students in lower school types and leads to a greater inequality of educational achievement. It remains unclear, however, if this can be attributed to the effect of school types per se or student background and innate ability that determine the allocation process of students into school types. Overall, the variation in test scores can be explained much better by the observable characteristics in Germany than in Finland.

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Bibliographic Info

Paper provided by Research Group Heterogeneous Labor, University of Konstanz/ZEW Mannheim in its series Working Papers of the Research Group Heterogenous Labor with number 04-07.

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Length: 32 pages
Date of creation: 08 Mar 2004
Date of revision:
Handle: RePEc:knz:hetero:0407

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Keywords: Educational production ; PISA ; student performance;

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References

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  1. Lauer, Charlotte, 2000. "Gender wage gap in West Germany: how far do gender differences in human capital matter?," ZEW Discussion Papers 00-07, ZEW - Zentrum für Europäische Wirtschaftsforschung / Center for European Economic Research.
  2. West, Martin R. & Wößmann, Ludger, 2006. "Which school systems sort weaker students into smaller classes? International evidence," Munich Reprints in Economics 19694, University of Munich, Department of Economics.
  3. Bishop, John H. & Wößmann, Ludger, 2004. "Institutional effects in a simple model of educational production," Munich Reprints in Economics 20279, University of Munich, Department of Economics.
  4. Oaxaca, Ronald, 1973. "Male-Female Wage Differentials in Urban Labor Markets," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 14(3), pages 693-709, October.
  5. Hanushek, Eric A. & Luque, Javier A., 2003. "Efficiency and equity in schools around the world," Economics of Education Review, Elsevier, vol. 22(5), pages 481-502, October.
  6. Ben Jann, 2005. "Standard Errors for the Blinder-Oaxaca Decomposition," German Stata Users' Group Meetings 2005 03, Stata Users Group.
  7. Blau, Francine D & Kahn, Lawrence M, 1992. "The Gender Earnings Gap: Learning from International Comparisons," American Economic Review, American Economic Association, vol. 82(2), pages 533-38, May.
  8. Juhn, Chinhui & Murphy, Kevin M & Pierce, Brooks, 1993. "Wage Inequality and the Rise in Returns to Skill," Journal of Political Economy, University of Chicago Press, vol. 101(3), pages 410-42, June.
  9. Petra E. Todd & Kenneth I. Wolpin, 2003. "On The Specification and Estimation of The Production Function for Cognitive Achievement," Economic Journal, Royal Economic Society, vol. 113(485), pages F3-F33, February.
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Citations

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Cited by:
  1. Hanushek, Eric A. & Wößmann, Ludger, . "The Economics of International Differences in Educational Achievement," Chapters in Economics, University of Munich, Department of Economics.
  2. Ammermüller, Andreas, 2005. "Educational Opportunities and the Role of Institutions," ZEW Discussion Papers 05-44, ZEW - Zentrum für Europäische Wirtschaftsforschung / Center for European Economic Research.
  3. Marina Murat & Davide Ferrari & Patrizio Frederic, 2012. "Immigrant students and educational systems. Cross-country evidence from PISA 2006," Department of Economics 0683, University of Modena and Reggio E., Faculty of Economics "Marco Biagi".
  4. Anja Kuckulenz & Michael Maier, 2006. "Heterogeneous Returns to Training, An Analysis with German Data Using Local Instrumental Variables," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), Justus-Liebig University Giessen, Department of Statistics and Economics, vol. 226(1), pages 24-40, January.
  5. Baranov, Igor N., 2012. "Quality of Secondary Education in Russia: Between Soviet Legacy and Challenges of Global Competitiveness," Working Papers 538, Graduate School of Management, St. Petersburg State University.
  6. Marina Murat, 2011. "Do immigrant students succeed? Evidence from Italy and France based on PISA 2006," Department of Economics 0670, University of Modena and Reggio E., Faculty of Economics "Marco Biagi".
  7. 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.
  8. Ramos, Raul & Duque, Juan Carlos & Nieto, Sandra, 2012. "Decomposing the Rural-Urban Differential in Student Achievement in Colombia Using PISA Microdata," IZA Discussion Papers 6515, Institute for the Study of Labor (IZA).
  9. Amini, Chiara & Commander, Simon, 2012. "Educational scores: How does Russia fare?," Journal of Comparative Economics, Elsevier, vol. 40(3), pages 508-527.
  10. Wagstaff, Adam & Wang, L. Choon, 2011. "A hybrid approach to efficiency measurement with empirical illustrations from education and health," Policy Research Working Paper Series 5751, The World Bank.
  11. Murat Marina, 2012. "Do Immigrant Students Succeed? Evidence from Italy and France," Global Economy Journal, De Gruyter, vol. 12(3), pages 1-22, September.
  12. Kitae Sohn, 2012. "A New Insight Into The Gender Gap In Math," Bulletin of Economic Research, Wiley Blackwell, vol. 64(1), pages 135-155, 01.
  13. Alina Botezat & Ruben R. Seiberlich, 2013. "Educational performance gaps in Eastern Europe," The Economics of Transition, The European Bank for Reconstruction and Development, vol. 21(4), pages 731-756, October.
  14. Shiu-Sheng Chen & Ming-Ching Luoh, 2010. "Are Mathematics and Science Test Scores Good Indicators of Labor-Force Quality?," Social Indicators Research, Springer, vol. 96(1), pages 133-143, March.
  15. 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.
  16. Sakellariou, Chris, 2012. "Decomposing the increase in TIMSS Scores in Ghana : 2003-2007," Policy Research Working Paper Series 6084, The World Bank.

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