Space and Change in the Measurement of Poverty Concentration: Detroit in the 1990s.
Joe Grengs, University of Michigan.
Standard measures of poverty concentration may not accurately reflect neighborhood conditions because they offer a weak link to the underlying geography of a neighborhood. Changes in the spatial configuration within a census tract can have the effect of increasing or decreasing the density of poverty, and the cities that showed the most dramatic improvement in census tract rates simultaneously faced substantial and potentially damaging shifts in land use. This paper uses a dasymetric mapping technique in a raster GIS environment to intersect population data in a block group layer with land-use categories from a land-use layer. I produce poverty counts and rates at a much finer spatial resolution than a block group, with an explicit spatial relationship between population and surrounding neighborhood characteristics. I illustrate the technique for the City of Detroit by measuring poverty concentration change between 1990 and 2000. I find that (a) a substantially larger share of poor people in 2000 lived in places that exceeded the standard 40-percent threshold than is calculated by the aspatial census-tract approach; (b) poverty became more concentrated in space during the 1990s counter to the reports of diminishing poverty concentration that are based on the share of poor people in high-poverty tracts; and
(c) poverty improved where neighboring land-use conditions also improved.
Poverty Trends and Measurement, Urban Poverty