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PISA: What makes the difference?

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  • Andreas Ammermueller

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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

Article provided by Springer in its journal Empirical Economics.

Volume (Year): 33 (2007)
Issue (Month): 2 (September)
Pages: 263-287

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Handle: RePEc:spr:empeco:v:33:y:2007:i:2:p:263-287

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Keywords: Educational production; PISA; Student performance; Decomposition; I21; H52;

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References

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  1. Ben Jann, 2005. "Standard Errors for the Blinder-Oaxaca Decomposition," German Stata Users' Group Meetings 2005, Stata Users Group 03, Stata Users Group.
  2. 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.
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  5. Bishop, John H. & Woessmann, Ludger, 2002. "Institutional Effects in a Simple Model of Educational Production," IZA Discussion Papers 484, Institute for the Study of Labor (IZA).
  6. Petra E. Todd & Kenneth I. Wolpin, 2003. "On The Specification and Estimation of The Production Function for Cognitive Achievement," Economic Journal, Royal Economic Society, Royal Economic Society, vol. 113(485), pages F3-F33, February.
  7. West, Martin R. & Woessmann, Ludger, 2006. "Which school systems sort weaker students into smaller classes? International evidence," European Journal of Political Economy, Elsevier, vol. 22(4), pages 944-968, December.
  8. 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.
  9. 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.
  10. 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, University of Chicago Press, vol. 101(3), pages 410-42, June.
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Cited by:
  1. 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.
  2. 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.
  3. Eric A. Hanushek & Ludger Woessmann, 2010. "The Economics of International Differences in Educational Achievement," CESifo Working Paper Series 3037, CESifo Group Munich.
  4. Sakellariou, Chris, 2012. "Decomposing the increase in TIMSS Scores in Ghana : 2003-2007," Policy Research Working Paper Series 6084, The World Bank.
  5. Shiu-Sheng Chen & Ming-Ching Luoh, 2010. "Are Mathematics and Science Test Scores Good Indicators of Labor-Force Quality?," Social Indicators Research, Springer, Springer, vol. 96(1), pages 133-143, March.
  6. Marina Murat & Davide Ferrari & Patrizio Frederic, 2012. "Immigrant students and educational systems. Cross-country evidence from PISA 2006," Center for Economic Research (RECent), University of Modena and Reggio E., Dept. of Economics 080, University of Modena and Reggio E., Dept. of Economics.
  7. Amini, Chiara & Commander, Simon, 2012. "Educational scores: How does Russia fare?," Journal of Comparative Economics, Elsevier, vol. 40(3), pages 508-527.
  8. 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.
  9. 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.
  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. 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.
  12. 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, Elsevier, vol. 29(6), pages 1016-1033, December.
  13. Marina Murat, 2011. "Do immigrant students succeed? Evidence from Italy and France based on PISA 2006," Department of Economics, University of Modena and Reggio E., Faculty of Economics "Marco Biagi" 0670, University of Modena and Reggio E., Faculty of Economics "Marco Biagi".
  14. Raul Ramos & Juan Carlos Duque & Sandra Nieto, 2013. "“Decomposing the Rural-Urban Differential in Student Achievement in Colombia Using PISA Microdata”," IREA Working Papers 201223, University of Barcelona, Research Institute of Applied Economics, revised Mar 2013.
  15. Murat Marina, 2012. "Do Immigrant Students Succeed? Evidence from Italy and France," Global Economy Journal, De Gruyter, De Gruyter, vol. 12(3), pages 1-22, September.
  16. 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, Justus-Liebig University Giessen, Department of Statistics and Economics, vol. 226(1), pages 24-40, January.

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