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Sorting and inequality in Canadian schools

  • Jane Friesen

    (Simon Fraser University)

  • Brian Krauth

    (Simon Fraser University)

Researchers and educators often argue that a student's peers strongly influence his or her educational outcomes. If so, an unequal distribution of advantaged and disadvantaged students across schools in a community will leave many students doubly disadvantaged and amplify existing inequalities. We explore the relationship between the degree of sorting by socioeconomic characteristics, ethnicity and language across schools within a community and inequality as measured by the variance of standardized high school exam scores within the community. Simple cross- sectional estimates suggest a direct relationship between sorting by ethnicity and the variance of test scores, but no direct relationship between sorting by income or primary parent's education and the variance of test scores. We then implement a fixed effects estimator to control for endogeneity in the extent of sorting: the results indicate that sorting by ethnicity does not affect the variance of test scores, but that sorting by home language and primary parent's education does.

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File URL: http://128.118.178.162/eps/hew/papers/0408/0408001.pdf
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Paper provided by EconWPA in its series HEW with number 0408001.

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Length: 32 pages
Date of creation: 03 Aug 2004
Date of revision:
Handle: RePEc:wpa:wuwphe:0408001
Note: Type of Document - pdf; pages: 32
Contact details of provider: Web page: http://128.118.178.162

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  1. Durlauf, S.N., 1992. "A Theory of Persistent Income Inequality," Papers 47, Stanford - Institute for Thoretical Economics.
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  11. Fernandez, Raquel & Rogerson, Richard, 1996. "Income Distribution, Communities, and the Quality of Public Education," The Quarterly Journal of Economics, MIT Press, vol. 111(1), pages 135-64, February.
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  13. Michael A. Boozer & Stephen E. Cacciola, 2001. "Inside the 'Black Box' of Project STAR: Estimation of Peer Effects Using Experimental Data," Working Papers 832, Economic Growth Center, Yale University.
  14. Edward E. Glaeser & Bruce Sacerdote & Jose A. Scheinkman, 1995. "Crime and Social Interactions," Harvard Institute of Economic Research Working Papers 1738, Harvard - Institute of Economic Research.
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  16. Hansen, Lars Peter, 1982. "Large Sample Properties of Generalized Method of Moments Estimators," Econometrica, Econometric Society, vol. 50(4), pages 1029-54, July.
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  18. M Arellano & O Bover, 1990. "Another Look at the Instrumental Variable Estimation of Error-Components Models," CEP Discussion Papers dp0007, Centre for Economic Performance, LSE.
  19. Cragg, John G. & Donald, Stephen G., 1993. "Testing Identifiability and Specification in Instrumental Variable Models," Econometric Theory, Cambridge University Press, vol. 9(02), pages 222-240, April.
  20. Miguel Urquiola, 2005. "Does School Choice Lead to Sorting? Evidence from Tiebout Variation," American Economic Review, American Economic Association, vol. 95(4), pages 1310-1326, September.
  21. Kelly Bedard & William O. Brown, Jr. & Eric Helland, . "School Size and the Distribution of Test Scores," Claremont Colleges Working Papers 1999-11, Claremont Colleges.
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