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The Effects of School Quality and Family Functioning on Youth Math Scores: a Canadian Longitudinal Analysis

Author

Listed:
  • Pierre Lefebvre
  • Philip Merrigan
  • Matthieu Verstraete

Abstract

This paper tries to disentangle the relative importance of family and school inputs on a child's cognitive achievement as measured by her percentile score on a mathematics test. We replicate a study by Todd and Wolpin (2007) in the United States with Canadian data. In contrast to their work that uses state-level indicators of school quality, we estimate our model with data from Statistics Canada's National Longitudinal Survey of Children and Youth (NLSCY) which provides micro-level information on the family and school history of the child. The sample used for the analysis is based on the 7- to 15-year-old longitudinal children who have completed at least two consecutive math tests. As in Todd and Wolpin, we conclude that cognitive outcomes are determined by current and past family inputs. Contrary to them, who find no impact of school inputs, we find that the quality of schools has a positive impact on achievement in mathematics.

Suggested Citation

  • Pierre Lefebvre & Philip Merrigan & Matthieu Verstraete, 2008. "The Effects of School Quality and Family Functioning on Youth Math Scores: a Canadian Longitudinal Analysis," Cahiers de recherche 0822, CIRPEE.
    • Handle: RePEc:lvl:lacicr:0822
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    References listed on IDEAS

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    1. Steven G. Rivkin & Eric A. Hanushek & John F. Kain, 2005. "Teachers, Schools, and Academic Achievement," Econometrica, Econometric Society, vol. 73(2), pages 417-458, March.
    2. Stephen V. Cameron & James J. Heckman, 1998. "Life Cycle Schooling and Dynamic Selection Bias: Models and Evidence for Five Cohorts of American Males," Journal of Political Economy, University of Chicago Press, vol. 106(2), pages 262-333, April.
    3. Hansen, Karsten T. & Heckman, James J. & Mullen, K.J.Kathleen J., 2004. "The effect of schooling and ability on achievement test scores," Journal of Econometrics, Elsevier, vol. 121(1-2), pages 39-98.
    4. James Heckman & Flavio Cunha, 2007. "The Technology of Skill Formation," American Economic Review, American Economic Association, vol. 97(2), pages 31-47, May.
    5. Petra E. Todd & Kenneth I. Wolpin, 2007. "The Production of Cognitive Achievement in Children: Home, School, and Racial Test Score Gaps," Journal of Human Capital, University of Chicago Press, vol. 1(1), pages 91-136.
    6. Eric A. Hanushek & John F. Kain & Steven G. Rivkin & Daniel M. O'Brien, 2005. "The Market for Teacher Quality," Discussion Papers 04-025, Stanford Institute for Economic Policy Research.
    7. Daniel Aaronson & Lisa Barrow & William Sander, 2007. "Teachers and Student Achievement in the Chicago Public High Schools," Journal of Labor Economics, University of Chicago Press, vol. 25(1), pages 95-135.
    8. Flavio Cunha & James J. Heckman, 2008. "Formulating, Identifying and Estimating the Technology of Cognitive and Noncognitive Skill Formation," Journal of Human Resources, University of Wisconsin Press, vol. 43(4).
    9. James J. Heckman & Jora Stixrud & Sergio Urzua, 2006. "The Effects of Cognitive and Noncognitive Abilities on Labor Market Outcomes and Social Behavior," Journal of Labor Economics, University of Chicago Press, vol. 24(3), pages 411-482, July.
    10. Neal, Derek A & Johnson, William R, 1996. "The Role of Premarket Factors in Black-White Wage Differences," Journal of Political Economy, University of Chicago Press, vol. 104(5), pages 869-895, October.
    11. 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 3-33, February.
    12. Clotfelter, Charles T. & Ladd, Helen F. & Vigdor, Jacob, 2005. "Who teaches whom? Race and the distribution of novice teachers," Economics of Education Review, Elsevier, vol. 24(4), pages 377-392, August.
    13. Murnane, Richard J & Willett, John B & Levy, Frank, 1995. "The Growing Importance of Cognitive Skills in Wage Determination," The Review of Economics and Statistics, MIT Press, vol. 77(2), pages 251-266, May.
    14. Eric A. Hanushek, 1996. "Measuring Investment in Education," Journal of Economic Perspectives, American Economic Association, vol. 10(4), pages 9-30, Fall.
    15. Heather Rose & Julian R. Betts, 2004. "The Effect of High School Courses on Earnings," The Review of Economics and Statistics, MIT Press, vol. 86(2), pages 497-513, May.
    16. Alan B. Krueger, 2003. "Economic Considerations and Class Size," Economic Journal, Royal Economic Society, vol. 113(485), pages 34-63, February.
    17. Flavio Cunha & James J. HECKMAN, 2009. "Investing in our Young People," Rivista Internazionale di Scienze Sociali, Vita e Pensiero, Pubblicazioni dell'Universita' Cattolica del Sacro Cuore, vol. 117(3), pages 387-418.
    18. Cunha, Flavio & Heckman, James J. & Lochner, Lance, 2006. "Interpreting the Evidence on Life Cycle Skill Formation," Handbook of the Economics of Education, in: Erik Hanushek & F. Welch (ed.), Handbook of the Economics of Education, edition 1, volume 1, chapter 12, pages 697-812, Elsevier.
    19. Jonah E. Rockoff, 2004. "The Impact of Individual Teachers on Student Achievement: Evidence from Panel Data," American Economic Review, American Economic Association, vol. 94(2), pages 247-252, May.
    20. Stephen V. Cameron & James J. Heckman, 1998. "Life Cycle Schooling and Dynamic Selection Bias: Models and Evidence for Five Cohorts," NBER Working Papers 6385, National Bureau of Economic Research, Inc.
    21. Eric A. Hanushek, 2003. "The Failure of Input-Based Schooling Policies," Economic Journal, Royal Economic Society, vol. 113(485), pages 64-98, February.
    22. John M. Barron & Mark C. Berger & Dan A. Black, 2006. "Selective Counteroffers," Journal of Labor Economics, University of Chicago Press, vol. 24(3), pages 385-410, July.
    23. Roland G. Fryer & Steven D. Levitt, 2006. "The Black-White Test Score Gap Through Third Grade," American Law and Economics Review, Oxford University Press, vol. 8(2), pages 249-281.
    24. Roland G. Fryer & Steven D. Levitt, 2004. "Understanding the Black-White Test Score Gap in the First Two Years of School," The Review of Economics and Statistics, MIT Press, vol. 86(2), pages 447-464, May.
    25. Stephen V. Cameron & James J. Heckman, 2001. "The Dynamics of Educational Attainment for Black, Hispanic, and White Males," Journal of Political Economy, University of Chicago Press, vol. 109(3), pages 455-499, June.
    26. Hanushek, E.A.omson, W., 1996. "Assessing the Effects of School Resources on Student Performance : An Update," RCER Working Papers 424, University of Rochester - Center for Economic Research (RCER).
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    Cited by:

    1. Kelly Chen & Lars Osberg & Shelley Phipps, 2019. "Unequal opportunities and public policy: The impact of parental disability benefits on child postsecondary attendance," Canadian Journal of Economics/Revue canadienne d'économique, John Wiley & Sons, vol. 52(4), pages 1401-1432, November.

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    More about this item

    Keywords

    Math scores; human capital; child development; school and family inputs; panel data;
    All these keywords.

    JEL classification:

    • I21 - Health, Education, and Welfare - - Education - - - Analysis of Education
    • J13 - Labor and Demographic Economics - - Demographic Economics - - - Fertility; Family Planning; Child Care; Children; Youth
    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models

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