An Index For Measuring Income Segregation

This academic journal article proposes a new index that that can be used to relate income segregation on the spatial arrangement of neighborhoods, and uses examples from Baltimore, Maryland.

2 minute read

May 24, 2007, 1:00 PM PDT

By Chris Steins @planetizen


"Recent urban and regional policy debates have emphasized the need to eliminate the spatial concentration of poverty within US metropolitan areas. Despite growing evidence linking residential location to economic inequality, there is still a dearth of information on the severity of poverty concentration and the spatial pattern of household income distributions within US metropolitan areas.

...This paper proposes a new spatial ordering index that can be used to quantify the dependence of a given pattern of income segregation on the spatial arrangement of neighborhoods."

From the article's conclusion:

"The relationship between the spatial ordering index and the covariance provides an intuitive interpretation of the spatial ordering index as a correlation measure which quantifies the association between the neighborhood per capita income distribution and a spatial reordering of the neighborhood income distribution. As the Baltimore, Maryland, case study illustrates, the values of calculated spatial ordering indices are largely consistent with expectations regarding the observed spatial pattern of neighborhood income segregation."

[Editor's note: A free 30-day subscription to the Journal of Regional Science for 30 days is available to Planetizen readers. Included in this trial is access to the special theme issue, Environmental Economics and Regional Science, guest edited by Matthew E. Kahn, Professor of Economics, Tufts University.

Use this web address to activate your free trial before May 31, 2007:
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If you are not able to use the link as displayed here, manual instructions for access token "JORSetrial2007" are available online at http://www.blackwellpublishing.com/freetrial/ .]

Saturday, May 19, 2007 in Journal Of Regional Science

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