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High School Grades and University Performance: A Case Study

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  • Philippe Cyrenne

    ()
    (Department of Economics, The University of Winnipeg)

  • Alan Chan

    ()

Abstract

A critical issue facing a number of colleges and universities is how to allocate first year places to incoming students. The decision to admit students if often based on a number of factors, but a key statistic is a student's high school grades. This paper reports on a case study of the subsequent performance at the University of Winnipeg of high school students from 84 Manitoba High Schools. By tracking the University performance of a set of students admitted for the years 1997-2002, we are able to estimate the likelihood of success of subsequent students based on their characteristics as well as their high school grades. In doing so, we use a number of alternative estimators including a Least Squares Dummy Variable Model and a Hierarchical Linear Model. The methodology should be of interest to admissions o±cers at other universities as an input into estimating the subsequent performance of first year students.

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File URL: http://economics.uwinnipeg.ca/RePEc/winwop/2010-02.pdf
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Bibliographic Info

Paper provided by The University of Winnipeg, Department of Economics in its series Departmental Working Papers with number 2010-02.

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Length: 44 pages
Date of creation: May 2010
Date of revision:
Handle: RePEc:win:winwop:2010-02

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References

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  1. Christopher F Baum, 2006. "An Introduction to Modern Econometrics using Stata," Stata Press books, StataCorp LP, number imeus, April.
  2. Naylor, Robin & Smith, Jeremy, 2002. "Schooling Effects On Subsequent University Performance : Evidence For The Uk University Population," The Warwick Economics Research Paper Series (TWERPS) 657, University of Warwick, Department of Economics.
  3. Joseph G. Altonji & Todd E. Elder & Christopher R. Taber, 2005. "Selection on Observed and Unobserved Variables: Assessing the Effectiveness of Catholic Schools," Journal of Political Economy, University of Chicago Press, vol. 113(1), pages 151-184, February.
  4. Ermisch, John & Francesconi, Marco, 2001. "Family Matters: Impacts of Family Background on Educational Attainments," Economica, London School of Economics and Political Science, vol. 68(270), pages 137-56, May.
  5. Julian R. Betts & Darlene Morell, 1999. "The Determinants of Undergraduate Grade Point Average: The Relative Importance of Family Background, High School Resources, and Peer Group Effects," Journal of Human Resources, University of Wisconsin Press, vol. 34(2), pages 268-293.
  6. Zimmerman, David J., 1999. "Peer Effects in Academic Outcomes: Evidence From a Natural Experiment," Williams Project on the Economics of Higher Education DP-52, Department of Economics, Williams College.
  7. Wayne A. Grove & Tim Wasserman, 2004. "The Life-Cycle Pattern of Collegiate GPA: Longitudinal Cohort Analysis and Grade Inflation," The Journal of Economic Education, Taylor & Francis Journals, vol. 35(2), pages 162-174, April.
  8. Hanushek, Eric A, 1986. "The Economics of Schooling: Production and Efficiency in Public Schools," Journal of Economic Literature, American Economic Association, vol. 24(3), pages 1141-77, September.
  9. Horowitz, John B. & Spector, Lee, 2005. "Is there a difference between private and public education on college performance?," Economics of Education Review, Elsevier, vol. 24(2), pages 189-195, April.
  10. Hakkinen, Iida & Kirjavainen, Tanja & Uusitalo, Roope, 2003. "School resources and student achievement revisited: new evidence from panel data," Economics of Education Review, Elsevier, vol. 22(3), pages 329-335, June.
  11. Cohn, Elchanan & Cohn, Sharon & Balch, Donald C. & Bradley, James Jr., 2004. "Determinants of undergraduate GPAs: SAT scores, high-school GPA and high-school rank," Economics of Education Review, Elsevier, vol. 23(6), pages 577-586, December.
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Cited by:
  1. Buly A. Cardak & Joe Vecci, 2013. "Catholic School Effectiveness in Australia: A Reassessment Using Selection on Observed and Unobserved Variables," Working Papers 2013.05, School of Economics, La Trobe University.
  2. Trappey, Amy J.C. & Trappey, Charles V. & Liu, Penny H.Y. & Lin, Lee-Cheng & Ou, Jerry J.R., 2013. "A hierarchical cost learning model for developing wind energy infrastructures," International Journal of Production Economics, Elsevier, vol. 146(2), pages 386-391.
  3. Sandra E. Black & Jane Arnold Lincove & Jenna Cullinane & Rachel Veron, 2014. "Can You Leave High School Behind?," NBER Working Papers 19842, National Bureau of Economic Research, Inc.

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