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Country performance at the International Mathematical Olympiad

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  • Henseke, Golo

Abstract

This study seeks to explain country differences in the performance at the International Mathematical Olympiad. Hypotheses on the relationship between, on one hand, performance at the Olympiads and, on the other, population size and dynamics, economic resources, human capital, schooling quantity and quality, and the political regime are tested with a panel dataset of 97 countries over the period 1993-2006. The analysis distinguishes between crosscountry differences and intra-country differences. Results indicate that macro-conditions explain cross-country differences well but fail to predict changes in performance over time. Thus, long-term differences in country characteristics are associated with the average performance of Olympians.

Suggested Citation

  • Henseke, Golo, 2009. "Country performance at the International Mathematical Olympiad," Thuenen-Series of Applied Economic Theory 108, University of Rostock, Institute of Economics.
    • Handle: RePEc:zbw:roswps:108
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    1. Thomas Fuchs & Ludger Wößmann, 2008. "What accounts for international differences in student prformance? A re-examination using PISA data," Studies in Empirical Economics, in: Christian Dustmann & Bernd Fitzenberger & Stephen Machin (ed.), The Economics of Education and Training, pages 209-240, Springer.
    2. James Heckman & Flavio Cunha, 2007. "The Technology of Skill Formation," American Economic Review, American Economic Association, vol. 97(2), pages 31-47, May.
    3. Robert Hoffmann & Lee Chew Ging & Bala Ramasamy, 2002. "The Socio-Economic Determinants of International Soccer Performance," Journal of Applied Economics, Universidad del CEMA, vol. 5, pages 253-272, November.
    4. Gary S. Becker & H. Gregg Lewis, 1974. "Interaction between Quantity and Quality of Children," NBER Chapters, in: Economics of the Family: Marriage, Children, and Human Capital, pages 81-90, National Bureau of Economic Research, Inc.
    5. Michael A. Leeds & Eva Marikova Leeds, 2009. "International Soccer Success and National Institutions," Journal of Sports Economics, , vol. 10(4), pages 369-390, August.
    6. Eric A. Hanushek, 2003. "The Failure of Input-Based Schooling Policies," Economic Journal, Royal Economic Society, vol. 113(485), pages 64-98, February.
    7. Mundlak, Yair, 1978. "On the Pooling of Time Series and Cross Section Data," Econometrica, Econometric Society, vol. 46(1), pages 69-85, January.
    8. Narin, Francis & Breitzman, Anthony, 1995. "Inventive productivity," Research Policy, Elsevier, vol. 24(4), pages 507-519, July.
    9. Kevin M. Murphy & Andrei Shleifer & Robert W. Vishny, 1991. "The Allocation of Talent: Implications for Growth," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 106(2), pages 503-530.
    10. Richard Easterlin, 1978. "What will 1984 be like? Socioeconomic implications of recent twists in age structure," Demography, Springer;Population Association of America (PAA), vol. 15(4), pages 397-432, November.
    11. Pirotte, Alain, 1999. "Convergence of the static estimation toward the long run effects of dynamic panel data models," Economics Letters, Elsevier, vol. 63(2), pages 151-158, May.
    12. Austin Nichols, 2007. "Causal inference with observational data," Stata Journal, StataCorp LP, vol. 7(4), pages 507-541, December.
    13. Peter Macmillan & Ian Smith, 2007. "Explaining International Soccer Rankings," Journal of Sports Economics, , vol. 8(2), pages 202-213, May.
    14. Hon‐Kwong Lui & Wing Suen, 2008. "Men, Money, And Medals: An Econometric Analysis Of The Olympic Games," Pacific Economic Review, Wiley Blackwell, vol. 13(1), pages 1-16, February.
    15. Per O. Seglen, 1992. "The skewness of science," Journal of the American Society for Information Science, Association for Information Science & Technology, vol. 43(9), pages 628-638, October.
    16. Daniel K. N. Johnson & Ayfer Ali, 2004. "A Tale of Two Seasons: Participation and Medal Counts at the Summer and Winter Olympic Games," Social Science Quarterly, Southwestern Social Science Association, vol. 85(4), pages 974-993, December.
    17. Andrew B. Bernard & Meghan R. Busse, 2004. "Who Wins the Olympic Games: Economic Resources and Medal Totals," The Review of Economics and Statistics, MIT Press, vol. 86(1), pages 413-417, February.
    18. Rosen, Sherwin, 1981. "The Economics of Superstars," American Economic Review, American Economic Association, vol. 71(5), pages 845-858, December.
    19. Wolfgang Lutz & Anne Goujon & Samir K.C. & Warren Sanderson, 2007. "Reconstruction of population by age, sex and level of educational attainment of 120 countries for 1970-2000," Vienna Yearbook of Population Research, Vienna Institute of Demography (VID) of the Austrian Academy of Sciences in Vienna, vol. 5(1), pages 193-235.
    20. Hanushek, Eric A, 1992. "The Trade-Off between Child Quantity and Quality," Journal of Political Economy, University of Chicago Press, vol. 100(1), pages 84-117, February.
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    More about this item

    Keywords

    Science Olympiads; Talent in mathematics; Country panel; PISA;
    All these keywords.

    JEL classification:

    • I21 - Health, Education, and Welfare - - Education - - - Analysis of Education
    • H52 - Public Economics - - National Government Expenditures and Related Policies - - - Government Expenditures and Education
    • J24 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Human Capital; Skills; Occupational Choice; Labor Productivity

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