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Racial Inequality and Segregation Measures: Some Evidence from the 2000 Census

Abstract

How much of the observed segregation between black and white Americans can be attributed to income disparities between the two groups? We adopt an approach to the decomposition of segregation measures that combines the method of indirect standardization with the idea that some degree of segregation is the outcome of purely random processes. Using the dissimilarity index as a measure of segregation and data on race and income from US metropolitan areas for 2000, we find that the role played by racial income inequality in accounting for segregation is modest but varies significantly across cities.

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Fig. 1

Notes

  1. 1.

    See also Kain (1976), Galster (1988), McKinney and Schnare (1989) and Ellen (2000) on the relative unimportance of income disparities in accounting for observed levels of segregation. The idea that relatively moderate preferences over neighborhood racial composition can give rise to extreme levels of segregation when households make decentralized location choices was developed in the influential work of Schelling (1971); Clark (1991) argues for the continuing relevance of the Schelling model. Evidence on racial steering in housing markets and differential access to mortgage credit in accounting for segregation may be found, for instance, in Yinger (1995).

  2. 2.

    The hypothetical city is constructed using data from all eight counties in the New York PMSA, although only Manhattan is depicted.

  3. 3.

    For evidence on the extent of racial income disparities in the New York metropolitan area, see the estimates below of β i (the share of black households in each of the sixteen income classes).

  4. 4.

    The values of β i in the table refer to the black share of total black plus non-Hispanic white households, excluding members of other groups.

  5. 5.

    Much of the literature on segregation uses census tracts rather than block groups, and we follow this tradition. Note, however, that tracts that seem integrated can be composed of blocks that are themselves racially homogenous. For instance, Ellen (2000, p. 78) finds that about a third of the block groups in a sample of integrated Washington D.C. census tracts are either predominantly black or predominantly white (integrated tracts are defined as those in which the black share of the total population is between 10% and 50%).

  6. 6.

    This facilitates comparison with Massey and Denton (1993), who focus on the thirty areas with the largest black populations in 1990. Due to changes in population sizes and area definitions, only 24 of the 30 areas on their list appear in ours. Buffalo, Columbus, Gary, Milwaukee, Pittsburgh and San Francisco have been replaced by Charlotte, Fort Lauderdale, Jacksonville, Oakland, Raleigh and Richmond.

  7. 7.

    Income distributions by race are available at the census tract level only for households, and only in the STF3 data set. Most segregation studies use STF1 data on persons, so conformity with our results cannot be exact. Our use of STF3 data also introduces sampling error into our estimates, but given the large number of households in each metropolitan area we expect this to be negligible.

  8. 8.

    A few MSAs span two census regions; these are assigned to the region in which the majority of the population resides.

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Correspondence to Rajiv Sethi.

Additional information

For comments on an earlier version we thank Dan O’Flaherty and an anonymous referee.

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Sethi, R., Somanathan, R. Racial Inequality and Segregation Measures: Some Evidence from the 2000 Census. Rev Black Polit Econ 36, 79–91 (2009). https://doi.org/10.1007/s12114-009-9042-6

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Keywords

  • Residential segregation
  • Racial income disparities
  • Dissimilarity index