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The Effect Heterogeneity of Central Exams: Evidence from TIMSS, TIMSS-Repeat and PISA

  • Ludger Woessmann

This paper uses extensive student-level micro databases of three international student achievement tests to estimate heterogeneity in the effect of external exit exams on student performance along three dimensions. First, quantile regressions show that the effect tends to increase with student ability. But it does not differ substantially for most measured family-background characteristics. Second, central exams have complementary effects to school autonomy. Third, the effect of central exit exams increases during the course of secondary education, and regular standardised examination exerts additional positive effects. Thus, there is substantial heterogeneity in the central exam effect along student, school and time dimensions.

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File URL: http://www.cesifo-group.de/portal/page/portal/DocBase_Content/WP/WP-CESifo_Working_Papers/wp-cesifo-2004/wp-cesifo-2004-11/cesifo1_wp1330.pdf
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Paper provided by CESifo Group Munich in its series CESifo Working Paper Series with number 1330.

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Date of creation: 2004
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Handle: RePEc:ces:ceswps:_1330
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  1. Bishop, J., 1997. "The Effect of national Standards and Curriculum-Based Exams on Achievement," Papers 97-01, Cornell - Center for Advanced Human Resource Studies.
  2. Ludger Woessmann, 2003. "Central Exams as the "Currency" of School Systems: International Evidence on the Complementarity of School Autonomy and Central Exams," CESifo DICE Report, Ifo Institute for Economic Research at the University of Munich, vol. 1(4), pages 46-56, 02.
  3. Wößmann, Ludger, 2003. "Schooling resources, educational institutions and student performance: The international evidence," Munich Reprints in Economics 19661, University of Munich, Department of Economics.
  4. 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).
  5. Hanushek, Eric A., 2002. "Publicly provided education," Handbook of Public Economics, in: A. J. Auerbach & M. Feldstein (ed.), Handbook of Public Economics, edition 1, volume 4, chapter 30, pages 2045-2141 Elsevier.
  6. Wooldridge, Jeffrey M., 2001. "Asymptotic Properties Of Weighted M-Estimators For Standard Stratified Samples," Econometric Theory, Cambridge University Press, vol. 17(02), pages 451-470, April.
  7. Hendrik Jürges & Kerstin Schneider & Felix Büchel, 2005. "The Effect Of Central Exit Examinations On Student Achievement: Quasi-Experimental Evidence From TIMSS Germany," Journal of the European Economic Association, MIT Press, vol. 3(5), pages 1134-1155, 09.
  8. Bishop, John H, 1997. "The Effect of National Standards and Curriculum-Based Exams on Achievement," American Economic Review, American Economic Association, vol. 87(2), pages 260-64, May.
  9. 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.
  10. Fuchs, Thomas & Wößmann, Ludger, 2007. "What accounts for international differences in student performance? A re-examination using PISA data," Munich Reprints in Economics 20303, University of Munich, Department of Economics.
  11. 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.
  12. Koenker, Roger W & Bassett, Gilbert, Jr, 1978. "Regression Quantiles," Econometrica, Econometric Society, vol. 46(1), pages 33-50, January.
  13. Bishop, John H. & Moriarty, Joan Y. & Mane, Ferran, 2000. "Diplomas for learning, not seat time: the impacts of New York Regents examinations," Economics of Education Review, Elsevier, vol. 19(4), pages 333-349, October.
  14. Moulton, Brent R., 1986. "Random group effects and the precision of regression estimates," Journal of Econometrics, Elsevier, vol. 32(3), pages 385-397, August.
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