Recent research on residential segregation has focused on defining trends in areas outside of traditional metropolitan areas, including so-called new destinations and established immigrant gateways. Moreover a trend of decreasing black-white segregation between 1970 and 2009 has been described by recent work by Iceland and colleagues. In this paper, we go beyond the approach used in this recent work to investigate the county-level patterns of change in residential segregation between 1990 and 2010 using the most recent decennial census data available. We consider both black-white and Hispanic-Non-Hispanic patterns of segregation using measures of three dimensions of segregation: Evenness, Exposure and spatial clustering. Furthermore, we use tools of exploratory spatial data analysis and Geographic Information System (GIS) visualization to highlight areas of the country experiencing the most change over this period. This will allow us to see sub-regional trends in the dynamics of segregation, and understand the nature of segregation beyond the traditional black-white dichotomy, especially in areas of recent Hispanic immigration.

1. C O R E Y S . S P A R K S
P . J O H N E L L E S P A R K S
D E P A R T M E N T O F D E M O G R A P H Y
T H E U N I V E R S I T Y O F T E X A S A T S A N
A N T O N I O
A Spatial Analysis of Changing
Segregation Patterns in the United
States Between 1990 and 2010

2. Introduction
 Between 1970 and 2009, black-white residential
segregation declined on average across the country
 Recently, Iceland and colleagues (2013) showed that
within this time period, the western region of the US
showed the greatest decline in black-white
segregation, while the Midwest showed the lowest
decline
 Generally, these trends are for metropolitan areas,
with no reference given to non-metro areas

3. Reasons for Regional Patterns of Residential
Segregation
 Iceland et al (2013) point out that the size of the minority
population itself is often associated with higher levels of
segregation
 Also size of the metro area
 This is especially seen in the NE and MW
 In other areas, more multi-ethnic populations may serve
as a buffer to black-white patterns of segregation
 Historic patterns of black population migration have also affected the
overall temporal trend in segregation
 Also, patterns of economic activity and growth in housing
markets have affected segregation patterns
 Government, military and higher education decrease segregation
 Suburbanization also decreases segregation

4. How segregation is measured
 MSA versus Place?
 Parisi and colleagues (2011) point out how racial segregation
can occur at many different levels of geography, not just the
MSA
 This is primarily because of recent trends of population
decentralization into small towns and metro-fringe areas
 Macro and micro segregation
 They go on to show how micro-segregation, or segregation
between areas within cities, only accounts for ~50% of the
variation in segregation, while macro, or between place
segregation is also important
 They go on to point out the importance of considering
segregation in smaller communities

5. Goals
 First, we go beyond the approach used in this recent
work to investigate the county-level patterns of
change in residential segregation between 1990 and
2010 using the most recent decennial census data.
 Secondly, we use tools of exploratory spatial data
analysis and Geographic Information System (GIS)
visualization to highlight areas of the country where
segregation has continued to persist, despite the
national trend.
 Thirdly, we consider non-metro, as well as metro
segregation in our analysis, and examine if the
described trends hold for these areas as well.

6. Data
 US Decennial Census
 Summary File 1
 1990, 2000, 2010
 Population tabulated by Race
 Census tract level
 NHGIS County Shapefile
 n=3109 counties, 3 time periods

7. Methods
 Calculate two indices of segregation
 Evenness – Dissimilarity Index
 Exposure – Interaction Index
 Apply Exploratory Spatial Analysis Methods
 Getis-Ord G* - Examine spatial clustering of high and low
values of segregation indices
 Examine persistence of clustering across time
 Examine spatial patterns of segregation change between 1990
and 2010

8. Spatial Trends in Segregation
Dissimilarity

9. Spatial Trends in Segregation
Dissimilarity

10. Spatial Trends in Segregation
Dissimilarity
2010 Dissimilarity G*

11. Spatial Trends in Segregation
Change in Dissimilarity

12. Spatial Trends in Segregation
Interaction

13. Spatial Trends in Segregation
Interaction

14. Spatial Trends in Segregation
Interaction

15. Spatial Trends in Segregation
Change in Interaction

16. Changes in Segregation Across the Urban-Rural
Continuum

17. Persistence in Segregation Across the Urban-
Rural Continuum

18. Conclusions
 Patterns of change
 Largest changes in segregation occurred in large metro areas
and small urban areas outside of metro counties
 Smallest changes occurred in most non-metro counties
 Large metros also were most likely to be persistently
segregated (D>.6) over 1990 to 2010
 Most nonmetro areas were most likely to change from
segregated to desegregated
 Results support propositions from Parisi and
colleagues
 Most pronounced changes are in areas outside of traditional
metro areas
 Micropolitan population changes