2000115-Strengthening-Communities-with-Neighborhood-Data

326 Strengthening Communities with Neighborhood Data
the percentage of single-family homes, homeownership rates, residential
land use, and median income. The second group includes a number of
indicators typically associated with neighborhood distress: vacancy rates
(both vacant land and vacant housing units), percentage of single-parent
households, social capital, and industrial land use. The third group has
to do with the concentration of retail and services in the neighborhood,
indicators that also tend to be associated with the presence of a younger
and more mobile population.
The hierarchical structure of the typology yields a potentially very large
number of neighborhood types, as we can keep refining each grouping
until we reach the individual neighborhoods at the bottom of the tree. To
make this information useful and accessible, however, a manageable number
of distinct neighborhood types should be identified, while at the same
time preserving enough differentiation between types to see real differences
in characteristics and drivers of change. To achieve this balance, the project
focused on two layers of the typology, deriving nine broad neighborhood
types that were then further divided into several distinct subtypes. 10
Figure 7.1.2 summarizes these two key layers of the typology, displaying
the nine types and 33 subtypes of neighborhoods identified with
this system. The broad neighborhood types are ordered based on their
median income and numbered from 1 to 9. Within each type, the subtypes
are ordered based on their median income and assigned a letter.
Therefore, type 1-A (single parents) is the lowest income segment, while
type 9-C (exclusive enclaves) is the wealthiest. 11
While only 23 variables were used to construct the typology, many more
variables can be used to profile each neighborhood type. For instance, it is
possible to describe each type by its location, racial composition, residents’
occupations, or even foreclosure or crime rates, even though none of these
factors were used to define the type in the first place. By and large, the types
are well differentiated based on these other descriptive features as well,
lending validity to the final classification. 12 For instance, while race was
not included as a defining variable, neighborhoods with a distinct racial
makeup tended to fall into several distinct neighborhood types.
Similarly, while the typology was constructed by pooling all neighborhoods
in the four cities, not all types are found everywhere. For example,
none of the three poorest types are found in Seattle, where incomes are
generally higher than in the other three cities. Conversely, Coming Attractions
neighborhoods are found primarily in Dallas and Seattle; very few
neighborhoods in Chicago, and none in Cleveland, match this profile.