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On the Measurement of Segregation

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  • Federico Echenique
  • Roland G. Fryer, Jr.

Abstract

This paper develops a measure of segregation based on two premises: (1) a measure of segregation should disaggregate to the level of individuals, and (2) an individual is more segregated the more segregated are the agents with whom she interacts. Developing three desirable axioms that any segregation measure should satisfy, we prove that one and only one segregation index satisfies our three axioms, and the two aims mentioned above; which we coin the Spectral Segregation Index. We apply the index to two well-studied social phenomena: residential and school segregation. We calculate the extent of residential segregation across major US cities using data from the 2000 US Census. The correlation between the Spectral index and the commonly-used dissimilarity index is .42. Using detailed data on friendship networks, available in the National Longitudinal Study of Adolescent Health, we calculate the prevalence of within-school racial segregation. The results suggests that the percent of minority students within a school, commonly used as a substitute for a measure of in-school segregation, is a poor proxy for social interactions.

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Bibliographic Info

Paper provided by National Bureau of Economic Research, Inc in its series NBER Working Papers with number 11258.

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Date of creation: Apr 2005
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Handle: RePEc:nbr:nberwo:11258

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  1. Borjas, George J, 1995. "Ethnicity, Neighborhoods, and Human-Capital Externalities," American Economic Review, American Economic Association, American Economic Association, vol. 85(3), pages 365-90, June.
  2. Lawrence F. Katz & Jeffrey R. Kling & Jeffrey B. Liebman, 2000. "Moving to Opportunity in Boston: Early Results of a Randomized Mobility Experiment," NBER Working Papers 7973, National Bureau of Economic Research, Inc.
  3. Jan K. Brueckner & Oleg Smirnov, 2004. "Workings of the Melting Pot: Social Networks and the Evolution of Population Attributes," CESifo Working Paper Series 1320, CESifo Group Munich.
  4. Jonathan Guryan, 2001. "Desegregation and Black Dropout Rates," NBER Working Papers 8345, National Bureau of Economic Research, Inc.
  5. Philipson Tomas, 1993. "Social Welfare and Measurement of Segregation," Journal of Economic Theory, Elsevier, Elsevier, vol. 60(2), pages 322-334, August.
  6. Roland G. Fryer & Steven D. Levitt, 2004. "The Causes and Consequences of Distinctively Black Names," The Quarterly Journal of Economics, MIT Press, MIT Press, vol. 119(3), pages 767-805, August.
  7. Jeffrey R. Kling & Jeffrey B. Liebman & Lawrence F. Katz, 2005. "Experimental Analysis of Neighborhood Effects," NBER Working Papers 11577, National Bureau of Economic Research, Inc.
  8. Edward P. Lazear, 1995. "Culture and Language," NBER Working Papers 5249, National Bureau of Economic Research, Inc.
  9. David Frankel & Oscar Volij, 2005. "Measuring Segregation," Economic theory and game theory, Oscar Volij 017, Oscar Volij.
  10. Cutler, David M & Glaeser, Edward L, 1997. "Are Ghettos Good or Bad?," The Quarterly Journal of Economics, MIT Press, MIT Press, vol. 112(3), pages 827-72, August.
  11. Cutler, David & Vigdor, Jacob & Glaeser, Edward, 1999. "The Rise and Decline of the American Ghetto," Scholarly Articles 2770033, Harvard University Department of Economics.
  12. Case, A.C. & Katz, L.F., 1991. "The Company You Keep: The Effects Of Family And Neighborhood On Disadvantaged Younths," Harvard Institute of Economic Research Working Papers, Harvard - Institute of Economic Research 1555, Harvard - Institute of Economic Research.
  13. Ignacio Palacios-Huerta & Oscar Volij, 2004. "The Measurement of Intellectual Influence," Econometrica, Econometric Society, Econometric Society, vol. 72(3), pages 963-977, 05.
  14. Hutchens, Robert, 2001. "Numerical measures of segregation: desirable properties and their implications," Mathematical Social Sciences, Elsevier, Elsevier, vol. 42(1), pages 13-29, July.
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