Evolution of Racial and Ethnic Segregation:
Pace and Place of Neighborhood Change∗
Michael D. M. Bader
Robert Wood Johnson Foundation Health & Society Scholar
University of Pennsylvania
September 2010
This is a draft manuscript. Please do not distribute or cite without contacting the
author.
Abstract
Sociological research identifies racial segregation as a primary factor that perpetuates racial
inequality. The continued influence of racial segregation depends on the patterns of neighborhood racial and ethnic change that evolve in the present multicultural, post-Civil Rights era. I
argue that exploring the pace of neighborhood change and the places where change occurs links
individual-level processes to metropolitan level changes in racial and ethnic segregation. To
study the pace and place of emerging types of neighborhood change, I present novel graphical
and statistical methods – ternary plots and growth mixture models – that allow me to reduce the
complexity of measuring continuous levels of long-term change in composition among multiple
groups. Using the Chicago metropolitan area as a case-study, I show that the pace of neighborhood change slows considerably after the 1970s and that contemporary patterns of neighborhood
change evolve over multiple decades with specific spatial patterns. Uncovering the location of
change in time and space explains the evolution of racial and ethnic segregation through black
diffusion from traditionally black neighborhoods, Latino dispersion to new suburban enclaves,
and white divergence into gentrifying areas and the distant suburbs.
∗
Correspondence: Michael D. M. Bader, Robert Wood Johnson Foundation Health & Society Scholars Program,
3641 Locust Walk, Third Floor, Philadelphia, PA 19104. An earlier version of this paper was presented at the
2010 Annual Meeting of the Population Association of American in Dallas, TX and has benefited greatly from the
comments provided by Stew Tolnay at that meeting. In addition, the author would like to thank Jeffrey Morenoff,
Jim House, Maria Krysan, Karyn Lacy, Jennifer Ailshire, Laura Tach, and Jooyoung Lee for their comments on an
earlier draft of this paper as well as the comments and statistical help provided by Michael Elliott. The author thanks
the Robert Wood Johnson Foundation Health & Society Scholars program for its financial support.
1
Evolution of Segregation
Bader 2
To think of the neighborhood or community in isolation from the city is to disregard the
biggest fact about the city.
Ernest Burgess, The City, 1925 p. 148
The racial residential segregation of neighborhoods represents one of the most enduring
legacies of racial subjugation in contemporary American society (Massey and Denton,
1993). For much of the twentieth century sociologists demonstrated that the consequence of segregating cities by race was the maintenance of an oppressive racial order
that perpetuated racial inequality (DuBois, [1899]1996; Drake and Cayton, 1993; Massey
and Denton, 1993). In this light, the declining levels of black-white segregation are heralded while the growing levels of Latino-white and Asian-white segregation are cause
for concern (Logan et al., 2004; Timberlake and Iceland, 2007).
What is unclear from existing research is how the processes of neighborhood change
unfold over time and space to create metropolitan-level shifts in segregation. The
growing multiethnic diversity of the American population and reduced racial antipathy among whites makes the old model of neighborhood racial change – the process of
invasion and succession – obsolete (Logan and Zhang, 2010). The changing context of
race and ethnicity in contemporary American metropolitan areas means that it is no
longer possible to think of neighborhood racial change in binary terms (Waldinger, 1989;
Zubrinsky and Bobo, 1996); and, even where blacks and whites share neighborhoods
without other racial or ethnic groups, the contemporary patterns of change likely differ from the traditional model due to thawing racial attitudes among whites (Schuman
et al., 1997; Ellen, 2000). Yet the increased complexity introduced by this new racial and
ethnic context of metropolitan areas makes studying patterns of neighborhood racial
and ethnic change difficult. In turn, this difficulty presents formidable challenges for
researchers assessing the consequences of racial and ethnic segregation for contemporary
racial and ethnic inequality.
Assessing the influence of racial and ethnic segregation in the contemporary context
requires linking the emerging micro-level processes that create neighborhood change to
levels of metropolitan segregation, as the Chicago School sociologists did when they
Evolution of Segregation
Bader 3
developed their human ecological model (Park and Burgess, [1925]1984). While some
existing studies started overcoming challenges to describe contemporary patterns of
neighborhood change, they devote insufficient attention to the location of neighborhood
change in space and time (Alba et al., 1995; Friedman, 2008; Logan and Zhang, 2010). In
this paper, I argue that exploring the pace and place of neighborhood racial and ethnic
change makes explicit the link between individual-level actions and metropolitan levels
of segregation, and allows researchers to develop a firmer grasp on evolving patterns of
racial and ethnic segregation. Through this exploration, I highlight the shortcomings of
existing methods used to study neighborhood change due to their conceptualization of
change as rapid transitions between states of relative stability. In contrast, I argue that
contemporary influences on neighborhood change lead to gradual, continuous change
that is not captured using traditional methods of modeling neighborhood change.
Developing a complete picture of the pace and place of neighborhood change requires new methods to reduce the complexity of neighborhood change in a multiethnic
context. Building from Abbott’s (1997) idea of an “area career” that follows the incremental change of a neighborhood over a long period, I show how an innovative statistical
method called growth mixture modeling can empirically identify “neighborhood careers”
of racial and ethnic change. I also introduce a graphical tool, the ternary plot, that facilitates the interpretation of neighborhood composition distributions among three racial
and groups simultaneously. I demonstrate the usefulness of this approach by exploring
patterns of neighborhood change in the Chicago metropolitan area from 1970 to 2000 as
a case study. I find evidence of long-term, spatially dependent changes since the 1970s
that explain the evolution of neighborhood racial and ethnic segregation among blacks,
whites, and Latinos and explain evolving metropolitan segregation through slowing
black diffusion, increasing Latino dispersion, and white spatial divergence.
1
Segregation, Diversity, and Metropolitan Inequality
Throughout the twentieth century, racial residential segregation created and perpetuated racial inequality in the United States. Even after the Civil Rights Movement and
Evolution of Segregation
Bader 4
passage of the Fair Housing Act in 1968, racial residential segregation persisted and constrained opportunities for social and economic advancement among blacks (Massey and
Denton, 1993; Charles, 2003; Adelman and Gocker, 2007). Absent the legal ability of
whites to maintain segregated neighborhoods, researchers studied patterns of residential
mobility to undersand neighborhood racial change, and largely blamed the persistence
of segregation on whites’ racial antipathy towards living with blacks: whites would resist, often violently, the entrance – or “invasion” – of blacks to their neighborhoods;
but, after the successful entry of a few black neighbors, whites would flee leading to a
rapid “succession” of the neighborhood to become predominantly black (Duncan and
Duncan, 1957). The mathematical formalization of this “invasion/succession” model
showed that small levels of racial antipathy of whites towards blacks leads to the rapid
“tipping” of a neighborhood from white to black (Schelling, 1971).
Survey data supported the main assumptions of the invasion/succession model and
patterns of neighborhood change showed that the model largely described neighborhood change (Taeuber and Taeuber, 1965; Farley et al., 1978; Lee and Wood, 1990;
Clark, 1991). Although researchers pointed to stable integrated neighborhoods, and
highlighted the contingent factors that supported racial succession to rightfully criticize
the inevitability of racial transition implied by the model (Nyden et al., 1998; Taub
et al., 1984; Lee and Wood, 1991; Ellen, 2000), it remained a relatively useful heuristic.
Yet the growing multiethnic diversity of the country, fueled largely by immigration from
Latin America and Asia, challenges the usefulness of this biracial model in a multethnic
context (Waldinger, 1989). Additionally, the increasing racial tolerance of whites reduces the explanatory power of the model by dampening one of the mechanisms driving
change (Ellen, 2000). Developing new models that can incorporate multiethnic patterns of change and the different influence of race on residential mobility is a crucial
step to determine the prevalence and consequences of contemporary racial and ethnic
segregation.
Studying patterns of neighborhood change is more difficult in this new context,
in large part because multiethnic diversity substantially increases the complexity of
studying neighborhood change. Researchers are now required to simultaneously mea-
Evolution of Segregation
Bader 5
sure changes among multiple racial and ethnic groups rather than just two (Zubrinsky
and Bobo, 1996). However, there are a handful of studies that overcome the challenges to investigate patterns of multiethnic neighborhood change (Alba et al., 1995;
Friedman, 2008; Swaroop, 2005). These studies examine the transitions between categories of racial and ethnic composition, defined as having some minimum number or
proportion of members in each group, over several decades. These transition matrices
reveal an increasing integration of minorities into previously all-white communities, but
low levels of integration among minority neighborhoods, particularly black and Latino
neighborhoods. These studies suggest that minority entrance to previously all-white
neighborhoods reduces racial and ethnic segregation while the stable segregation of
minority neighborhoods perpetuates it.
Logan and Zhang’s (2010) recent and innovative analysis of nationwide neighborhood
racial and change begins exploring this question and goes the furthest in describing
emerging patterns of change. Their study is unique because they follow paths of neighborhood change by examining the sequence of transitions from 1980 to 1990 and then
from 1990 to 2000 rather than comparing only two points in time. With this unique
method, Logan and Zhang (2010) find that neighborhoods with a white presence tend
to gain the presence of one minority group, largely Asians or Latinos, and in a subsequent decade add additional minority groups. This “incremental addition” (Logan
and Zhang, 2010, 1092) of minorities leads to what they term “global neighborhoods”
– neighborhoods shared among multiple racial and ethnic groups – that are relatively
stable. At the same time, they find very few instances where neighborhoods become
all-white after attaining integration with at least one minority group. From this evidence, Logan and Zhang (2010) argue that multiethnic populations buffer the effects
of minority integration that previously led to racial succession while at the same time
finding that minority neighborhoods, particularly black neighborhoods, remain starkly
segregated.
Evolution of Segregation
2
Bader 6
Pace and Place of Neighborhood Change
Logan and Zhang’s (2010) attention to the paths of neighborhood change allows them
not only to describe what changes occurred, but how those changes occurred and draws
attention to the process of neighborhood change. Despite Logan and Zhang’s (2010)
considerable innovation, what their analysis is limited in what it can tell us about the
pace at which neighborhood change occurs as well as the places where different types
of change occur. With only limited knowledge of these factors, it is difficult to assess
what the implications of neighborhood racial and ethnic change are for the continuing
legacy of racial segregation and inequality.
2.1
Pace of Neighborhood Change
When considering the consequences of segregation on racial and ethnic inequality, the
pace at which a neighborhood changes is an important factor because it can affect the
economic stability of the neighborhood as well as the prospects for sustained racial integration. Ellen (2000) highlights the pace of racial change as a primary factor contributing to neighborhood stability. Rapid racial change in a neighborhood can lead to fears
of racial transition and cause an existing resident to move out or a potential resident
not to move in (Ellen, 2000; Crowder, 2000). These fears would led to a self-fulfilling
prophecy of racial succession that also destabilize the neighborhood economically.
Considering factors that influence in- versus out-migration is important in light of
contemporary patterns of residential mobility. In the traditional model of invasion/
succession, particularly its mathematical form, out-migration was as consequential for
neighborhood change as in-migration. While evidence exists demonstrating the influence of neighborhood minority concentration on white out-mobility, the effect is relatively small at low levels of minority composition and dependent on other factors of
neighborhood context (Crowder, 2000; Harris, 1999).1 Although racial composition has
a small effect on whether a white resident moves, it has a substantial effect on where
1
It is important to note that this research was largely conducted using data from the 1970s and early 1980s.
In light of changing racial attitudes among whites (Schuman et al., 1997), the effect of racial composition on outmigration is likely lower today.
Evolution of Segregation
Bader 7
that resident prefers to move and actually moves since whites almost exlusively consider neighborhoods that are overwhelmingly white (Farley et al., 1994; Emerson et al.,
2001; Krysan and Bader, 2007; South and Crowder, 1998; Quillian, 2002). Others argue that members of all racial and ethnic groups desire living with members of their
group and that this ethnocentrism leads to racial and ethnic segregation (Clark, 1992;
Fossett, 2006), or that the unwillingness of minorities to be the first to move to an allwhite neighborhood perpetuates segregation (Ellen, 2000). In sum, these factors point
to in-migration as the primary factor driving contemporary racial and ethnic change,
rather than a joint process of in- and out-migration as the invasion/succession model
presupposes.
The shifts in residential mobility, particularly the reduced influence of racial composition on out-mobility, suggest patterns of gradual, continuous neighborhood racial
and ethnic change rather than rapid changes between relatively stable neighborhood
compositions. Yet the dominant method of examining neighborhood change is to use
transition matrices built on the very assumption that neighborhood change is effectively
summarized by transitions between relatively stable states of neighborhood composition. Even Logan and Zhang’s (2010) improvement on traditional models by studying
paths of neighborhood change is problematic. Although they criticize the dated nature of the invasion/succession model, by modeling neighborhood change as a series
of transitions, they rely on a concept of change that is more adept at describing the
process of invasion/succession than patterns of gradual change that likely emerge with
contemporary patterns of residential mobility.
As neighborhood change occurs over longer periods of time, demographic transitions
become an additional factor that could contribute to gradual patterns of neighborhood
change. While we typically associate neighborhood in- and out-migration with residential mobility, residents can be “born into” or “die out of” a neighborhood as well. To the
degree that age differs by race or ethnicity within a neighborhood, then interracial differences in fertility and mortality would also lead to changes in the composition of neighborhood racial and ethnic change. Quantitative research finds a considerable amount of
segregation by household type, which is associated with age (Iceland et al., 2010; Marsh
Evolution of Segregation
Bader 8
and Iceland, 2010), and neighborhood ethnographers note the racial implications of
what Harvey Molotch (1969) calls “racial change in a stable community” (Wilson and
Taub, 2007; Deener, 2010; Hunter, 1974). Reductions in residential mobility-induced
change might substantially increase this type of long-term neighborhood change in contemporary metropolitan areas.
2.2
Place of Neighborhood Change
Segregation is an explicitly spatial phenomenon and a growing sociological literature
highlights the importance of a neighborhood’s spatial context on its residents’ wellbeing (Pattillo-McCoy, 1999; Morenoff, 2003; Adelman, 2004). Indeed, in Massey and
Denton’s (1993) seminal work on the segregation of American neighborhoods, three of
the five measures that contributed to their assessment of hypersegregation were explicitly spatial. However, researchers typically study neighborhood change in an aspatial
context (for exceptions, see Ellen, 2000; Morenoff and Tienda, 1997).
Additionally, since neighborhoods develop in relation to one another, as Burgess’
quote at the beginning of the manuscript alludes, then the type of change one neighborhood experiences could preclude or precondition the change experienced by other
neighborhoods (Hunter, 1974). Residents might view changes to an adjacent neighborhood as a precursor to change in their own neighborhoods and prompt them to move
(Crowder and South, 2008). When people move, regardless of the reason, search costs
tend to be lower in proximal areas compared to more distant ones (Clark and Smith,
1979). To the extent that existing racial and ethnic segregation leads residents of the
same race or ethnicity to live near one another, then residents might be more likely to
search in neighborhoods inhabited by members of their own race or ethnicity. Racial and
ethnic differences in search strategies and the influence of racial composition on community knowledge likely exaggerate this segregating influence (Krysan, 2008; Krysan
and Bader, 2009).
Immigration serves as another force that creates place-specific consequences for
neighborhood change. Immigration is based largely on personal networks as immigrants
frequently rely on previous immigrants to help them find housing and get situated in
Evolution of Segregation
Bader 9
the United States (Massey and Espinosa, 1997). Tight housing markets, which can
be created by an influx of immigration, create conditions that lead to racial or ethnic transition (Taeuber and Taeuber, 1965; Denton and Massey, 1991). In addition,
excess housing demand can spill over and create new patterns of change in adjacent
neighborhoods.
Contemporary changes to the metropolitan context also necessitate the need to map
where different types of racial and ethnic change occur. Metropolitan areas surrounding major cities continue to expand and this expansion led to the incorporation and
development of smaller satellite cities, or “edge cities” (Garreau, 1992), that challenge
traditional models of monocentric development patterns such as Burgess’ ([1925]1984)
concentric rings. At the same time, gentrification of urban neighborhoods led to the
redevelopment and racial turnover of many central city neighborhoods (Wyly and Hammel, 2004). Finally, drastic changes to federal housing policy from project-based housing, which had been so consequential for the development of racial segregation (Hunter,
1974; Hirsch, 1983; Massey and Denton, 1993), to mixed-income and voucher-based assistance could shift the largely minority population out of central cities to surrounding
suburbs. While these factors likely challenge the traditional conception of “chocolate
cities, vanilla suburbs” posited by Farley and colleagues (1978; 1993), understanding
what patterns emerge requires knowing where different types of neighborhood change
occur.
3
Evolving Patterns of Neighborhood Change
The factors that I describe above point to gradual, place-specific changes in neighborhood racial and ethnic composition that, in aggregate, create metropolitan segregation
or integration among racial and ethnic groups. Examining the pace and place of neighborhood change recalls the urban sociological tradition of the Chicago School’s human
ecological tradition Park and Burgess ([1925]1984). Abbott (1997), in discussing the
contributions of the early Chicago School sociologists, highlights the focus on both
temporal and spatial patterns as the primary and unique contribution of the Chicago
Evolution of Segregation
Bader 10
School. “[T]he cornerstone of the Chicago vision was location,” Abbott (1997, 1158)
argues, “for location in social time and space channeled the play of reciprocal determination.” Through their focus on the location of events in time and space, the Chicago
School sociologists saw neighborhood change as “a structure in process” that could
bridge both analytical scales from individuals to societal structures and empirical work
to sociological theory (Abbott, 1997, 1158).
Just as analyzing the process of neighborhood change helped the Chicago School
comprehend the implications of industrialization on residents, I argue that studying the
process of neighborhood racial and ethnic change provides substantial insight into the
ongoing evolution of metropolitan racial and ethnic segregation. Studying the pace of
this change resembles the approach that Abbott (1997) identifies as the “area career,”
signifying incremental changes that can be observed in a single area, in this case a
neighborhood, by following changes over a long period. Investigating the evolution of
neighborhood racial and ethnic change, including the pace and place of “neighborhood
careers,” presents methodological challenges. Some researchers have examined the pace
of racial change by measuring the change in the level of racial or ethnic composition
over time (Denton and Massey, 1991). Yet investigating neighborhood change in this
manner only allows one to examine the growth or decline of a single racial or ethnic
group and provides no information about how the simultaneous changes in composition
of other groups. These limitations reveal the tension inherent in identifying careers
of neighborhood change: on the one hand one wants to capture the full variation in
the rates of racial and ethnic change while, on the other, one needs to simultaneously
reduce that variation to an analytically meaningful set of common neighborhood racial
and ethnic careers.
In the following section, I describe analytical tools that can overcome these methodological challenges and reduce the complexity inherent in studying multiethnic neighborhood change. These include a graphical tool, the ternary plot, that helps summarize
continuous levels of composition among multiple racial and ethnic groups, and a statistical method, called growth mixture modeling, that empirically identifies careers of
neighborhood racial and ethnic change. To demonstrate the evolutionary approach that
Evolution of Segregation
Bader 11
I advocate, I study patterns of neighborhood racial and ethnic change in the Chicago
metropolitan area from 1970 to 2000. I use growth mixture models to empirically determine the nine careers of neighborhood racial and ethnic change and estimate the pace
of change for each career. I then map where the careers occur to demonstrate the when
and where racial and ethnic evolution is occurring.
Examining spatial patterns of neighborhood change requires focusing on a single
metropolitan area, and Chicago presents unique advantages for this investigation. Chicago is the subject of a number of influential studies of neighborhood racial and ethnic
change (e.g., Park and Burgess, [1925]1984; Duncan and Duncan, 1957; Hunter, 1974;
Morenoff and Tienda, 1997). Examining contemporary patterns of neighborhood racial
and ethnic change provides an additional observation in this series of studies and provides opportunities to compare to previous patterns of change. Some criticize urban
sociology’s over-reliance on the experiences of Chicago to develop urban theory (Dear
and Flusty, 1998; Dear, 2001); while there is truth to this claim, I would argue that the
same argument could be made of understanding multiethnic change from cities with
long histories of multiethnic populations, such as New York and Los Angeles. The
multiethnic diversity of Chicago grew substantially over this period and, by studying
neighborhood changes at the same time, I can uncover how this growing diversity affected patterns of neighborhood change. Thus, I approach the investigation of Chicago
as providing an interesting case study to examine the changing dynamic of racial and
ethnic segregation.
4
4.1
Data and Methods
Data Source and Study Region
Data for this study come from the Neighborhood Change Database (NCDB) created
by the Urban Institute and published by Geolytics, Inc. (Tatian, 2003). The NCDB
takes data from the tabulated United States Census long form for the 1970, 1980, 1990,
and 2000 decennial censuses, and normalizes the data from each decade to 2000 census
tract boundaries using geographical apportionment (for details, see Tatian, 2003). This
Evolution of Segregation
Bader 12
process yields data across three decades and four censuses for tracts defined with geographically constant boundaries. Using these data and accepting tract boundaries as
reasonable approximations of neighborhoods makes the NCDB well-suited to investigate
changes in neighborhood racial and ethnic composition over this span of time.
I use all tracts from the Chicago metropolitan area, which I define as any tract
in the Chicago-Gary-Kenosha, IL-IN-WI Consolidated Metropolitan Statistical Area
(CMSA). I choose to use the more expansive definition of consolidated metropolitan
area as opposed to the Chicago, IL Primary Metropolitan Statistical Area because, as I
note above, the expanding metropolitan area and housing market factors are potentially
associated with patterns of racial and ethnic change. Since a substantial portion of the
Chicago housing market has expanded into the “Chicagoland” area to the city’s south
and past the state line to Wisconsin in the north, the CMSA that was used because it
best captures this area. Therefore, a tract was included if it was in any of the counties
defined in the 1999 definition of the Chicago-Gary-Kenosha, IL-IN-WI CMSA.2
4.2
Description of Racial and Ethnic Composition Measures
Racial and ethnic composition was measured as the proportion of residents that identify
as non-Latino whites, non-Latino blacks, and Latinos of any race. Together, these three
racial and ethnic groups comprised 98.4, 97.9, 96.7, and 95.0 percent of all residents
in 1970, 1980, 1990, and 2000, respectively. Because these three groups represent the
overwhelming proportion of residents in the Chicago metropolitan area, analyses were
only conducted among these groups. Therefore, the proportion of each group in a
neighborhood is defined as the number in that group divided by the sum of whites,
blacks, and Latinos. In order to insure that the racial composition measures were
reliable, I only included tracts with a population of blacks, whites, and Latinos combined
greater than 100.
Creating these categories was somewhat problematic because the Census Bureau did
not start tabulating Latinos by race until 1980, meaning that Latinos are included in
2
The counties in Illinois are: Cook, DeKalb, DuPage, Grundy, Kane, Kankakee, Kendall, Lake, McHenry, and
Will; the counties in Indiana are: Lake and Porter; and the county in Wisconsin is: Kenosha.
Evolution of Segregation
Bader 13
the 1970 counts of whites and blacks. I employed the same strategy that Timberlake
and Iceland (2007) used and allocated Latinos to racial categories in 1970 based on the
proportion of Latinos identifying by each race in the same tract in 1980. This will have
the potential effect of understating the level of change between proportions Latinos and
whites and blacks in the 1970s and potentially overstate the level of stability.
4.3
Analytic Methods
Visualizing Neighborhood Racial and Ethnic Change.
I begin examining pat-
terns of neighborhood change by creating a transition matrix that examines changes
between categories of racial and ethnic composition from 1970 to 2000. I start with the
transition matrix because, as I note above, most studies explore neighborhood racial
and ethnic change using transition matrices. I examine the period from 1970 to 2000
rather than over a single decade because I want to capture the change as the Chicago
metropolitan area becomes more multiethnically diverse. To build the transition matrix, I break down tracts into categories based on a ten percent cut-off meaning that
that there are seven categories of racial composition: all white (< 10% black and < 10%
Latino), all black (< 10% white and < 10% Latino), all Latino (< 10% white and < 10%
black), white-black mixed (> 10% white and > 10% black), white-Latino mixed (> 10%
white and > 10% Latino), black-Latino mixed (> 10% black and > 10% Latino) and
white-black-Latino mixed (> 10% of all three groups). Using the transition matrix, I
can examine what patterns of changes between racial/ethnic categories tracts undergo
between 1970 and 2000.
Starting with the transition matrix also provides me the opportunity to compare
what is available from standard methods of neighborhood change and what might be
missed by using the other methods that I present in this paper. To begin this comparison, I examine the same racial and ethnic composition data from 1970 to 2000 are
“ternary plots.” These plots summarize the overall distribution of racial and ethnic
compositions of neighborhoods among three groups simultaneously. Points are plotted
for each tract and the plot can be read by locating where a point falls relative to three
axes on a triangle (for all of the plots in this paper, percent Latino will be plotted on
Evolution of Segregation
Bader 14
the left axis, percent white on the right axis, and percent black on the bottom axis).
Reading a ternary plot to obtain the proportion of residents identifying as one of the
three racial or ethnic groups requires that one draw a line that extends parallel to the
side counter-clockwise of the axis measuring the race of interest. Where this line crosses
the axis for the race or ethnicity of interest indicates the percentage of residents of that
race or ethnicity in the tract. For example, since Latinos will always be presented on the
left axis in this paper, the percentage of Latinos in a tract can be obtained by tracing
a line parallel to the bottom of the page from the plotted point to the left side of the
graph (since the bottom of the triangle is counter-clockwise to the Latino axis, which
on the left).
Beyond plotting individual points, it is also valuable to describe the general intuition
behind these plots. First, the closer to a vertex that a point falls, the more the tract
is dominated by a single race or ethnicity. For the plots in this paper, points near the
left vertex represent tracts that are predominantly black, those near the top represent
predominantly Latino tracts, and those near the right represent predominantly white
tracts. Second, points falling on a side of the triangle are composed of solely two
groups: tracts represented by points falling on the left side are mixed black-Latino (i.e.,
no whites), points falling on the right side are mixed Latino-white (i.e., no blacks), and
those falling on the bottom side are mixed black-white (i.e., no Latinos). The closer
a point is plotted to one of the sides, the greater the proportion of residents in the
tract that come from those two groups and, consequently, the fewer that come from the
third. Finally, the closer a point falls to the middle of the plot, the more equally blacks,
Latinos, and whites are represented.
Modeling Neighborhood Racial and Ethnic Change. In the following step, I
formally model and empirically identify patterns of neighborhood racial and ethnic
change in neighborhoods. Growth mixture models, a recent innovation in statistical
models of change, are designed for such a task. Growth mixture models build from two
separate traditions that treat variation in change over time in different ways (Kreuter
and Muthén, 2008). The first, latent growth models, assume that change follows a single
Evolution of Segregation
Bader 15
path but that individual tracts vary around that single path in a random fashion (Raudenbush and Bryk, 2002; Singer and Willett, 2003). The additional benefit of latent
growth models is that, in addition to random variation attributable to a single tract,
they account for randomness at each measurement point that is due to either measurement error or within-tract variation. The second approach, latent growth trajectory
analysis, assumes that variations in the change tracts experience come from belonging
to different underlying classes of tracts that all undergo the same path of change (Nagin, 2010). Once the analyst can assign the tract to a particular class that undergoes
a specific type of change, then the analyst can account for the variation between the
paths of change taken by different tracts.
The advantage of growth mixture models for studying patterns of neighborhood
racial and ethnic change is that combines the advantages of both methods and, by
doing so, minimizes some of the problems inherent with each. For example, previous
research has found that an integrated tract tends to remain integrated (Ellen, 2000);
however, the change components derived from a latent growth analysis designed to test
this hypothesis might overlook the potential heterogeneity in the types of neighborhood
change that could emerge from integrated neighborhoods. While a substantial proportion of integrated tracts might retain long-term, stably integrated populations, it is also
possible that, for another significant number of tracts, the level of integration marks
a period at the midpoint of the invasion/succession process. The components from a
latent growth analysis would be the mean of these two distinct trajectories and hide
the underlying heterogeneity. On the other hand, a latent growth trajectory analysis
designed to test this same hypothesis would assume that all of the variation between
tracts can be explained by its membership in one of these two trajectories meaning
that there is no differences to be explained between tracts following the same pattern
of change. This is equally undesirable because the process of neighborhood change includes a substantial degree of variation from non-deterministic forces and cannot be
explained by simple classifications.
The goal for the present analysis is to empirically identify the distinct patterns of
neighborhood racial and ethnic change that Chicago metropolitan neighborhoods have
Evolution of Segregation
Bader 16
undergone since 1970. Doing so requires predicting the initial racial and ethnic composition in 1970, the change of racial and ethnic group percentages from 1970 to 2000,
and the rate of change from 1970 to 2000 for each tract. These three components can
be mapped to the intercept, growth term, and quadratic growth term in a latent growth
model, respectively, and provide a reasonable estimation of the pace of neighborhood
racial and ethnic change. For a pre-specified number of classes, the growth mixture
model will predict the value of these three terms for two of the three racial groups (i.e.,
six terms total). I only estimate two of the three racial and ethnic groups (specifically,
blacks and Latinos) because the outcome is the proportion of the tract’s population
are members of the racial or ethnic group; thus, the remainder of the population from
the model for two of the three racial ethnic groups will be the proportion of the tract’s
composition that is a member of the third group.3 Since there is no theoretical guidance
pertaining to the number of distinct classes of neighborhood racial or ethnic change that
we should expect, I use the standard technique of comparing the Bayesian information
criterion (BIC) across models with successive numbers of classes. The BIC assesses
the trade-off between increased model fit versus the complexity of adding additional
parameters to the model, so the ideal number of classes can be determined by finding
the model with the number of classes where the BIC is minimized.
Mplus version 5.2 was used to predict the growth mixture models (Muthén and
Muthén, 2007). The remaining analyses were conducted in Stata version 10.2. The
ternary plots were constructed using Nicholas J. Cox’s triplot program created for
Stata (available at http://ideas.repec.org/c/boc/cocode/s342401.html). The program was modified slightly by the author for plotting lines on the ternary plot. The
modified version of the program is available from the author.
3
Technically, the outcome of the model
is a transformation of the proportion of the tract’s population that belongs
1/2
to the racial or ethnic group, arcsin pr
, where pr is the proportion of people that identify as race or ethnicity r
in a the tract. Because I am modeling a proportion as an outcome, the variance is determined by the mean and the
transformation is required to break the dependence of the variance on the mean. Ideally, a multinomial modeling
strategy would be employed in this situation; however, the computational demands of the multinomial model make
it infeasible in practice. The author would like to thank Michael Elliott (personal communication) for this advice.
Evolution of Segregation
5
Bader 17
Results
5.1
Tract-Level Composition in a Growing Multiethnic Context
I first examine the changing distribution of tracts in broad racial and ethnic categories
for each decade from 1970 to 2000 to assess how overall patterns of racial and ethnic
composition changed during this period. These results are presented in Table 1 and
echo findings from other studies that white neighborhoods become more diverse while
minority tracts remain segregated.4 There is a substantial decline in all-white tracts
from 1,366 in 1970 to 747 by 2000; this means that all-white tracts still represent the
modal category of tract in 2000, but now represent only about a third of all tracts
rather than a substantial majority. Meanwhile, the number of all-black tracts expanded
in absolute and relative terms during the three decades from 231 tracts in 1970 (12
percent of all tracts) to 353 tracts in 2000 (17 percent of all tracts). The largest
jump occurred in the 1970s, when all-black tracts went from 213 tracts to 315 tracts,
representing a four percentage point increase. Finally, the number of all-Latino tracts
differs somewhat from previous studies of neighborhood change (e.g., Alba et al., 1995)
in that there were no all-Latino tracts in 1970 and only 42 tracts in 2000, representing
just over two percent of tracts.
[Insert Table 1 about here]
Each of the mixed-race/ethnicity categories grew over this period, though the majority of the growth came from tracts mixed between whites and Latinos. This category
represented 196 tracts in 1970, almost ten percent, and grew steadily through 1990
when it represented 353, or 17 percent, of tracts; however, the pace of growth doubled
between 1990 and 2000, when this category grew by over six percentage points and
represented nearly a quarter of all tracts in the Chicago metropolitan area. This was
substantially larger than the growth in tracts shared between whites and blacks (134
to 174, with less than two percentage points growth) or blacks and Latinos (two to 64
4
Note that the total number of tracts changes from decade to decade; this is because neighborhoods with fewer
than 100 residents identifying as white, black, or Latino were not included in analyses. The increase in the number of
neighborhoods over this period represents the growth in the metropolitan area as more tracts were included at each
successive decade.
Evolution of Segregation
Bader 18
tracts, with about a three percent point growth). The final category, neighborhoods
mixed between whites, blacks, and Latinos – the “global neighborhood” type identified
by Logan and Zhang (2010) – grew from 50 tracts in 1970 to 185 by 2000, representing
nine percent of all metropolitan Chicago tracts.
Ternary plots of the same distribution of tracts can be found in Figure 1. These
plots describe the same broad patterns described in Table 1, but also reveal a great deal
more information about the diversity of neighborhoods. The predominance of all-white
and all-black tracts in 1970 can be seen in the clustering of points on the left and right
vertices. The growing diversity of all-white tracts can be seen by the dispersion of points
around the right vertex by 2000 in contrast to the segregation of all-black tracts shown
by the stable clustering of points near the left vertex. The growth of white-Latino
neighborhoods can be seen by the increase in points along the right axis in successive
decades. Finally, the increasing frequency of points in the center of plots is evidence of
the growing racial and ethnic diversity in Chicago metropolitan neighborhoods.
[Insert Figure 1 about here]
While the ternary plots echo the findings of the changing neighborhood composition
traced in Table 1, they also reveal a substantial degree of heterogeneity within the broad
racial and ethnic categories that is hidden by the broad categories in Table 1. For
example, the plots show a bifurcation of tracts within the black-white mixed category
in 1970: tracts are generally over 60 percent black (with strong clustering towards 100)
or under 40 (with stronger clustering towards 0), with the exception of a small cluster
of tracts split evenly between whites and blacks. Living in neighborhoods on different
sides of this bifurcation likely alters the experience of racial isolation in black/white
mixed communities, is hidden using standard categories. The ternary plots reveal a
growing Latino presence in mixed black/white communities over successive decades,
which can be seen by the increasing distance of points from the bottom axis of the plot
in later decades. Furthermore, the plots show that when Latinos live as a minority in
tracts split mostly between whites and blacks, they do so in tracts with greater white
populations.
Evolution of Segregation
Bader 19
The ternary plots show a different, though equally hidden, pattern in neighborhoods
shared between whites and Latinos. The Latino share of white/Latino mixed neighborhoods increased from 1970 to 2000, which can be seen by the increasing concentration
of points toward the top vertex. The increasing black presence in white/Latino neighborhoods over time is also evident from the growing distance from the right side axis;
however, there remain a sizable number of neighborhoods that fall on (or close to) the
right axis of the plot meaning that there are no (or few) blacks present. This is a sharp
contrast from the paucity of neighborhoods that fall on the bottom axis.
5.2
Neighborhood Racial and Ethnic Change
The results from the previous section show changes in the distribution of tracts by racial
and ethnic composition; however, they do not reveal how individual neighborhoods
changed over time. To do that, I first turn to the traditional method examining a
transition matrix of neighborhood racial and ethnic composition between 1970 and 2000,
presented in Table 2. The rows of Table 2 represent the initial racial and ethnic category
in 1970 and the columns represent the destination. A neighborhood represented on the
diagonal of the matrix indicates a tract with the same initial and destination racial and
ethnic category. The row marginals (the column labeled “Total”) report the number of
tracts of each row category in 1970 and the column marginals (the row labeled “Total”)
report the number of tracts in each column category in 2000.5 Row proportions are
also reported indicating the proportion of tracts with an initial category in 1970 that
became the column category in 2000.
[Insert Table 2 about here]
The first row of the transition matrix again demonstrates the remarkable decline in
all-white tracts over the 30-year period. Of the 1,364 tracts that start out as all-white
in 1970, only 666 (49 percent) remained all-white by 2000. Of those that did not remain
5
The values fro the marginals in this table do not exactly correspond to the number of tracts reported in Table 1.
There are 86 tracts that were not included in Table 2 because tracts with a population of fewer than 100 residents
that identify as either black, white, or Latino were dropped from the analysis. Among the 86 tracts, 77 were not
included because they were removed due to their 1970 population and 10 were removed due to their 2000 population;
there was one overlapping tract that was removed in both decades.
Evolution of Segregation
Bader 20
all-white, the majority (387 tracts) became integrated with Latinos while a substantial
number also became integrated with blacks (118 tracts) and multiracially integrated
(111 tracts). In contrast, nearly all of the all-black neighborhoods remained all-black in
2000. Among mixed white/black neighborhoods in 1970, almost half became all-black
by 2000, which represents about half of the growth in all-black neighborhoods. The
other substantial portion of all-black growth came from all-white neighborhoods, which
suggest that a fair amount of racial succession could still be observed, though it is impossible to assess how quickly that change happens in this matrix. At the same time, many
neighborhoods retained integration over the period. A quarter of mixed white/black
tracts in 1970 remained mixed in 2000 and an additional 14 percent became multiethnically integrated. Integration in mixed white/Latino tracts also persists, with almost
40 percent retaining white/Latino integration and 17 percent becoming multiethnically
integrated; however, in contrast to blacks, only 15 percent became all-Latino while 11
percent became integrated between blacks and Latinos.
The final trend apparent in Table 2 is the growth of neighborhoods mixed with
Latinos. By 2000, 715 of the tracts measured in 1970 had enough Latinos to be considered mixed while only 42 had enough to be considered all-Latino. The expanding
number of tracts considered to be mixed white/Latino from those that were all-white
in 1970 is largely responsible for this growth. This single cell represents 387 tracts, or
about 20 percent of all Chicago metropolitan neighborhoods measured in both 1970
and 2000. Transitions from all-white tracts also represent a significant portion of tracts
that become multiethnically integrated, with the remainder largely the result of white
integration with a single minority becoming multiethnically integrated. These results
confirm previous studies of neighborhood transition finding a growth in diversity among
previously all-white tracts and persistence of segregation in all-black tracts, while showing that Chicago is unique in that multiethnic growth comes largely from integration
between whites and Latinos rather than Latinos and blacks (Lee and Wood, 1991; Alba
et al., 1995)
Just as the table of changing racial and ethnic composition masked much of the
diversity within racial and ethnic categories, so too does the transition matrix mask the
Evolution of Segregation
Bader 21
trajectories of neighborhood change. Once again, I use ternary plots to demonstrate the
underlying diversity of change. Figure 2 plots the levels of whites, blacks, and Latinos
in tracts for 1970, 1980, 1990, and 2000 and then, for each tract, connects the point
plotted at each decade with a line. I plot these trends by racial and ethnic category of
tracts in 1970 (there were no all-Latino tracts in 1970). The changing racial and ethnic
composition of a tract can be traced by following the lines in the graph.6
[Insert Figure 2 about here]
Figure 2 displays the wide diversity of paths of neighborhood racial and ethnic change
found among Chicago metropolitan neighborhoods. Among all-white neighborhoods,
we see that a large number of all-white tracts become mixed with either Latinos or
blacks by 2000; however, the pace and completeness of that change differs by race.
Few neighborhoods become all-Latino, and those that grow in the proportion Latino
also tend to grow in percent black particularly after Latinos become a majority. Many
neighborhoods become all-black and some do so very quickly. Neighborhoods gaining
blacks tend to also gain Latinos until blacks reach about 60 percent of the population,
after which there is less diversity as neighborhoods tend to become all-black. In contrast
to all-white neighborhoods, there is very little change in all-black tracts from 1970 to
2000.
Mixed white/black neighborhoods more closely follow a single trajectory and gain
a larger proportion black over the three decades. In this category, there are some
neighborhoods that maintain the level of black residents and gain a greater proportion of
Latino residents, though they are rarer than neighborhoods that increase in proportion
black and decrease in proportion white. Conversely, mixed white/Latino neighborhoods
had a large increase in proportion black over the time period. Interestingly, for most
tracts, the increase in proportion black came as the proportion of Latinos grew in a
tract. This echoes findings of white loss in mixed white/minority neighborhoods found
by Logan and Zhang (2010), and could suggest that whites flee or become unwilling
6
Due to limitations in the software, only 98 trends can be plotted at a time. Accordingly, I plotted a random
sample of 98 plots for the all-white, all-black, mixed white/black, and mixed white/Latino plots. The plots shown
are representative of the trajectories within each category. A further limitation of the software is the inability to
place arrows indicating where a trajectory moves.
Evolution of Segregation
Bader 22
to move to neighborhoods that become increasingly Latino at the same time that they
become more attractive to blacks. Finally, neighborhoods shared by all three groups
demonstrate the least systematic patterns of neighborhood change. Most gain either in
proportion black or proportion Latino, but some gain in both to become split between
blacks and Latinos while decreasing in proportion white.
5.3
“Careers” of Neighborhood Racial and Ethnic Change
Table 3 reports the results of the growth mixture models identifying the unique trajectories – or “careers” – of neighborhood racial and ethnic change. Nine trajectories
minimized the BIC, meaning that nine is likely the optimal number of neighborhood
careers that describe racial and ethnic composition change in the Chicago metropolitan
area. The top row of Table 3 contains a the name of the career and the second row
reports the percentage of tracts best described by that career, which was determined by
assigning a neighborhood to a career based on the highest posterior probability of membership. The next group of rows reports the coefficients of the black and Latino growth
factors predicted for each growth factor transformed to percentage-point units.7 The
following two groups of rows report the predicted percentage of blacks and Latinos, respectively, at each decade for the tracts identified in the career. I group the nine careers
into three overall patterns of change, and discuss each in more detail below: racially
stable neighborhoods, black growth neighborhoods, and Latino growth neighborhoods.
[Insert Table 3 about here]
In addition to the estimates reported in Table 3, I also plotted the observed racial
composition by decade for the tracts in each career. Again, I used the posterior probabilities of career membership, predicted from the growth mixture model, and then
plotted the observed racial and ethnic composition of tracts by career for each decade
on ternary plots. A matrix of these plots can be viewed in Figure 3. Each of the nine
1/2
As mentioned previously, the model was estimated using the transformation arcsin pr
, where pr is the
proportion of the tract composed of race r. The coefficients reported in Table 3 are transformed by taking the sine
of the growth factor coefficient, βf r , estimated for growth factor f of race r, squaring the result, and retaining the
sign of the coefficient; i.e., p∗βr = sin (βf r )2 × sign (βf r ).
7
Evolution of Segregation
Bader 23
rows, one for each of the nine different careers, contains four plots for each decade from
1970 to 2000. The matrix of plots can be read across the rows to view changes in the
observed racial and ethnic composition of neighborhoods. It is worth noting as well
that overlaying the plots down each column would create the overall ternary plots by
decade shown in Figure 1.
[Insert Figure 3 about here]
Racially stable neighborhoods.
The two most abundant types of neighborhoods
in the Chicago metropolitan area are racially stable white and black neighborhoods.
Neighborhoods that follow a stable white career are by far the most common and comprise a majority (53 percent) of neighborhoods. The model predicts these tracts contain
essentially no blacks and very few Latinos with virtually no growth in either minority
group from 1970 to 2000. Although the model predicts almost no growth in the minority population in stable white neighborhoods, the first row of plots in Figure 3 reveals
that many all-white tracts in this trajectory became more diverse in subsequent decades
so that many are no longer strictly all-white. The majority of neighborhoods in this
category, however, still have a very small proportion of minority residents.8 This plot
suggests that some of the transitions from all-white to white/Latino and white/black
neighborhoods, as well as multiethnically integrated “global neighborhoods,” evident in
Table 2 are the result of very slow growth that inches neighborhoods into racially or
ethnically integrated compositions. Neighborhoods following the stable black career are
the next most abundant type with 14 percent of neighborhoods falling in this category.
The model predicts that these neighborhoods are 94 percent black in 1970 and grow to
98 percent black across the three decades, a finding largely confirmed by the plots in
Figure 3 and replicating the stability of all-black neighborhoods reported in Table 2.
The final stable career of neighborhood racial and ethnic composition is stable multiethnic integration. This is a much smaller category, as just over four percent of neighborhoods in the Chicago metropolitan area predicted to follow this trajectory. While it
8
It is important to remember that the ternary plots stack points on top of one another, and the majority of stable
white neighborhoods are clustered toward the right vertex.
Evolution of Segregation
Bader 24
is fair to call these neighborhoods “stable,” it is important to note that more racial and
ethnic change occurs in these neighborhoods than the preceding two trajectories. These
neighborhoods are predicted to have a large proportion of blacks and smaller level of
blacks with little average change in either; however, the observed distributions of racial
and ethnic composition reveal that this average estimate of no change is the result of
Latinos and blacks are increasing as a percentage of the population in some tracts and
decreasing in many others.
Black growth neighborhoods. I group two racial and ethnic careers into the “black
growth” category because they both start with nearly all-white populations in 1970
and then experience growth in the black share of the population. However, these two
careers follow very different paths and highlight the importance of studying the pace of
neighborhood change. The first black growth career, all-white to all-black succession,
follows the racial succession pattern described by the Duncans (1957). In the nearly
four percent of neighborhoods that follow this career, blacks represent a very small
percentage of the composition in 1970 and represent nearly all of the neighborhoods by
2000. In fact, the model estimates a pace of change so fast that it predicts population of
more than 100 percent black by 1990. Although this prediction highlights one problem
of using a continuous approximation to represent proportions, the rapid pace of change
is confirmed by the observed racial and ethnic composition in Figure 3.
The second type of black growth, all-white to majority black, occurs more slowly.
While the model predicts black growth to result in an average 14 percent black population by 2000, the ternary plots reveal a substantially larger proportion black by 2000.
They also reveal that much of this growth occurred in the 1990s, after many tracts
had grown slowly in the percent black during the 1970s and 1980s. This pattern could
reflect the increasing probability of white out-mobility as the percentage of blacks increases found by South and Crowder (1998) using individual-level mobility data. The
fact that the neighborhood did not completely transition, however, suggests that even
if white-flight occurs and is driving this pattern, that the process of change is much
more gradual than in previous decades. Since most of these tracts would remain in the
Evolution of Segregation
Bader 25
black/white integrated category of the transition matrix, even into 2000, it is important
to note that this pattern would be impossible to uncover using only transition matrices.
Latino growth neighborhoods.
The final four careers of neighborhood racial and
ethnic change represent areas with growing proportions of Latino residents and describe
the dramatic growth of the mixed white/Latino category found in Table 2. The first
three careers trace the entrance of Latinos into neighborhoods as their proportion of
the metropolitan population grew over the three decades under study. The first career, integrated white/Latino to all-Latino, were relatively integrated between whites
and Latinos in 1970, predicted to be just over half Latino by the growth mixture model
(Table 3), and become predominantly Latino by 2000. Blacks remain, as predicted
by the model, a small proportion of the neighborhood composition, though the black
population grows substantially in some neighborhoods in the 1990s. The second Latino
growth career traces neighborhoods that gained a Latino population in the 1970s. These
mostly white to majority Latino neighborhoods undergo a predicted growth in Latino
population from 12 percent in 1970 to 48 percent in 2000; however, just as in neighborhoods undergoing gradual transition from white to majority black, a substantial jump
towards an increasingly Latino population occurs in the 1990s. Yet unlike mostly white
to majority black neighborhoods, the proportion of blacks decreases in the 1990s. This
might suggest that immigration to ethnic enclaves that grew in the 1970s and 1980s is
responsible for this concentration of Latinos, as previous analyses suggest (Denton and
Massey, 1991).
The third career in this category are neighborhoods experiencing late Latino growth.
Although the model predicts these neighborhoods start with approximately two percent Latino 1970 and grow to about six percent Latino by 2000, the plots in Figure 3
show that this only describes the pace of change through 1990. In the 1990s, these
neighborhoods experienced dramatic Latino growth, leaving no tracts with more than
an 80 percent white population. Blacks experienced very little growth in these neighborhoods, as a large number of the exclusively white/Latino mixed neighborhoods that
were plotted along the right axis and highlighted in the discussion of Figure 1 come
Evolution of Segregation
Bader 26
from this career of racial and ethnic change.
The final Latino growth career describes neighborhoods that undergo Latino growth
followed by displacement. We can see this pattern by looking at Figure 3. The model
predicts continuous, but slowed, Latino growth from 1970 to 1990. However, in the
1990s almost all neighborhoods following this career regain significant white populations, many enough to be considered all-white. Overall, we see a growth in the black
population in these neighborhoods, though the percentage of black residents appears to
moderately decline along with the percentage of Latinos in the 1990s. While Logan and
Zhang (2010) find reversal toward white growth rare, I find that 4.5 percent of tracts in
the Chicago metropolitan area follow this trend. Because much of the change in neighborhood ethnic composition occurs within what would be considered the white/Latino
mixed neighborhoods, this kind of trajectory is invisible if one only studies transitions
between categories.
5.4
Geography of Racial and Ethnic Change
Examining the development of gradual racial and ethnic change provides valuable information about contemporary types of neighborhood change. However, a significant
amount of context regarding patterns of neighborhood change can be obtained by examining where racial and ethnic changes occur in respect to changes occurring in other
neighborhoods. Therefore, Figure 4 maps the location of each career of racial and ethnic
change in the metropolitan area.9 Mapping the location of the careers of change, which
represent temporal patterns of change, allows us to develop a picture of the dynamic of
neighborhood change over time and space.
[Insert Figure 4 about here]
Black growth patterns reveal a pattern of diffusion from the traditionally black neighborhoods. The neighborhoods surrounding traditional “black belt” of Chicago, as well
as longstanding black areas in the west side of Chicago; in the western suburb of May9
In order to provide sufficient detail, some outlying areas of the CMSA to the south and west are not depicted.
Largely, stable white neighborhoods comprise these areas; however, there are a few exceptions and a full map can be
obtained from the author upon request
Evolution of Segregation
Bader 27
wood; and Harvey and Gary to the south, experienced rapid succession from all-white
to all-black. The neighborhoods surrounding this transitional zone then experienced
long-term change from all-white to a black majority. This pattern suggests a process of
diffusion, with rapid outward expansion that slowed over time.
Latino growth patterns followed a similar pattern for neighborhoods surrounding
traditional immigrant enclaves, which are largely represented by neighborhoods following the integrated white/Latino to all-Latino career. It is important to recall that the
Latino presence in these communities in 1970 was far less complete than the black
presence in traditional black neighborhoods in 1970. The Latino populations in neighborhoods surrounding traditional enclaves followed the mostly white to majority Latino
career with Latino populations that grew in the 1980s. Several outlying cities and suburbs also saw the development of new enclaves in the 1990s including Melrose Park,
Elgin, and Aurora to the west; Joliet, Chicago Heights, and Harvey to the south; and
Waukegan and North Chicago to the north. In the 1990s, Latino populations diffused
to neighborhoods surrounding expanded enclaves in Chicago as well as neighborhoods
surrounding the new enclaves that developed in the 1980s. In addition, neighborhoods
that experienced late Latino growth are found in newer suburban communities, typically
along major transportation lines to the north and west of the city. Overall, patterns
of Latino growth point to a process of Latino dispersion from traditional enclaves to
outlying areas that mark the development of new suburban enclaves.
Stable white neighborhoods are, unsurprisingly, found largely in the suburban expanses of the Chicago metropolitan area. The white population of suburbs adjacent to
Chicago and other urban areas declined, particularly in the 1990s as near-in suburbs
follow the late Latino growth or growing black majority careers. On the other hand,
all of the Latino displacement neighborhoods are located in Chicago. The location of
these neighborhoods in Chicago’s gentrifying areas (e.g., Logan Square, Wicker Park,
and north side neighborhoods near the shore of Lake Michigan) suggest that increasing
housing values might lead to the displacement of Latinos by whites. White neighborhoods follow divergent patterns of stable segregation in outlying suburban areas and
increasing integration into urban, gentrifying neighborhoods in Chicago.
Evolution of Segregation
Bader 28
As previous research suggests, many of the stably integrated neighborhoods in the
city of Chicago are in neighborhoods that surround major universities or neighborhoods
that reaped substantial municipal investment such as Bridgeport (Taub et al., 1984;
Ellen, 2000). At the same time, stable integration can be found in neighborhoods
on the outskirts of satellite cities such as Joliet, Harvey, and North Chicago. This
integration might partially reflect the large geographic area of tracts in these areas and
not indicate integration on geographic scales comparable to integrated neighborhoods
found in Chicago (Lee et al., 2008). However, this could also reflect growing patterns
of increasing suburban diversity hidden by the aspatial nature of most neighborhood
change analyses.
6
Discussion
In this paper, I trace how patterns of neighborhood racial and ethnic change unfold over
space and time in the Chicago metropolitan area. I build on Logan and Zhang’s (2010)
recent analysis identifying paths of neighborhood racial and ethnic change; however,
rather than studying neighborhood change as a series of transitions between broad racial
and ethnic categories, I study the continuous changes in racial and ethnic change using
ternary plots and growth mixture models. I identify nine “careers” of neighborhood
racial and ethnic change and map the geographic location of these careers. Doing
so provides new insight regarding the pace of neighborhood change and the places
where different types of change occur that help explain contemporary racial and ethnic
segregation.
Examining the pace of change reveals patterns of neighborhood change that cannot be observed by studying neighborhood change as a series of transitions. While
this investigation confirms the general trends of neighborhood change found in previous studies, studying the the process of gradual change through neighborhood careers
reveals significant patterns of change undetectable by studying neighborhood change as
a series of transitions. Among the careers identified through growth mixture models,
we see the growth of integrated neighborhoods, especially neighborhoods transitioning
Evolution of Segregation
Bader 29
from all-white to mixed white/Latino compositions, as well as the stability of all-black
neighborhoods. However, studying careers of change also reveals the reduced pace of
racial change in black growth neighborhoods as well as the increased pace of change
in neighborhoods that began Latino growth around 1990 compared to neighborhoods
where growth started earlier. Additionally, I uncover the displacement of Latinos by
whites during the 1990s in over four percent of metropolitan neighborhoods. Because
the majority of change occurs within broad racial and ethnic categories, rather than between these categories, these trends are only identifiable by studying the gradual course
of neighborhood change.
Mapping neighborhood change careers unveils the importance of place and spatial
relationships in the interpretation of neighborhood change, and underscores the importance of understanding neighborhood change in relation to other changes occurring
throughout the metropolitan area (Burgess, [1925]1984; Hunter, 1974). In the Chicago
metropolitan area, black growth diffused out from large areas of black concentration in
central cities to surrounding neighborhoods, first rapidly and then slowing considerably
after the 1970s. Neighborhoods experiencing Latino growth initially diffused from traditional ethnic enclaves; however, after the 1980s Latino growth dispersed to satellite
cities and, especially in the 1990s, distant suburban communities. This pattern of dispersion within the metropolitan area reflects national patterns of Latino dispersion to
new immigrant destinations (Lichter and Johnson, 2006). Predominantly white neighborhoods spatially diverge: stable white neighborhoods are located in the suburban
expanse of the metropolitan area while a growing white population lives in gentrifying
neighborhoods of Chicago.
6.1
Evolution of Metropolitan Segregation
Identifying the pace of change and mapping this information to the places where change
occurs links micro-level processes that drive neighborhood change to the macro-level
patterns and consequences of metropolitan segregation. Metaphorically, mapping the
pace and place of neighborhood change develops an archaeological record documenting
the evolution of metropolitan racial and ethnic composition that recalls the Chicago
Evolution of Segregation
Bader 30
School’s human ecological model (Park, 1936). This record provides a context in which
the residential mobility decisions of individuals can be understood. For example, the
acceleration of white decline in neighborhoods as the minority share of neighborhoods
grows provides some support for the continued importance of white flight (South and
Crowder, 1998; Crowder, 2000). Additionally, the spatial pattern of black diffusion,
particularly of rapid change in the 1970s, support the contention that out-mobility is
influenced by the racial composition of surrounding neighborhoods (Crowder and South,
2008). The growing diversity of predominantly white neighborhoods suggest that minority residents “pioneer” into these tracts – the ternary plots show an increasing minority
presence even in neighborhoods classified as “all white” in the transition matrix. This
evidence counters arguments that ethnocentrism or a fear of being the only minority
perpetuates segregation (Clark, 1992; Ellen, 2000).
At the same time, this archaeological record illuminates evolution of metropolitan
racial and ethnic segregation (Logan et al., 2004; Timberlake and Iceland, 2007). The
rapid growth of Latinos in outlying suburbs and satellite cities help explain the increasing segregation of Latinos in recent decades, but the spatial pattern of this growth
simultaneously reveals that segregation differs from black segregation. Where black
segregation started from large, contiguous areas of concentration almost exclusively in
Chicago or Gary, Latino segregation is resulting from dispersion to outlying suburbs.
For blacks, the reduced pace – though not elimination – of neighborhood racial transition in predominantly black areas after the 1970s explains both the relative reduction
of black/white segregation and the maintenance of high absolute levels.
The evolution of neighborhood racial and ethnic change also supplies hints of potential future patterns of neighborhood change. Although current Latino segregation
results from spatial dispersion to new ethnic enclaves, the Latino spatial diffusion from
these new enclaves over successive decades in the 1980s and 1990s represents a credible
risk that future Latino segregation will develop in a manner similar to black segregation. Among the five forms of segregation used by Massey and Denton (1993) to
classify hypersegregation, the spatial diffusion of black neighborhoods and the unidirectional pattern of racial suggests that three will remain high: unevenness, isolation, and
Evolution of Segregation
Bader 31
clustering. The centripetal pattern of diffusion indicate both a reduced concentration
and centralization of black neighborhoods.
When considering the future of neighborhood change, it is important to consider the
role of housing policy. The role of federal housing policy, and local implementation,
on the segregation of American cities is well documented (Hunter, 1974; Hirsch, 1983;
Massey and Denton, 1993). Future studies should consider the role of the dramatic
shift in housing policy away from project based public housing to scattered-site and
voucher based programs, like HOPE VI and Section 8, on patterns of change. Existing
evidence suggests that these programs, which rely on the residential mobility of recipients, will contribute to existing diffusion of black neighborhoods (Kingsley et al., 2003;
Clampet-Lundquist, 2004). Furthermore, this analysis suggests that policies designed
to affirmatively attenuate racial and ethnic segregation by encouraging whites to move
to racially integrated neighborhoods might be the most effective if they target areas on
the outskirts of existing enclaves, including new suburban enclaves for Latinos.
6.2
Limitations
Despite the lessons that can be learned from this analysis, there are a few limitations
that are worth noting. First, this analysis only describes patterns in the Chicago metropolitan area, and thus the results should not be generalized to other metropolitan areas
without confirming that similar trends exist in those other cities. While this study only
encompasses a single metropolitan area, examining spatial patterns requires investigating a specific geography. Although the trends identified in this analysis are specific to
Chicago, the importance of studying the pace and place of neighborhood change to understand the evolution of metropolitan racial and ethnic segregation is likely universal.
Thus, future studies should investigate how patterns of neighborhood change evolve
over time and space in different ways across metropolitan areas.
The present analyses only presents results among three racial and ethnic groups.
While whites, blacks, and Latinos comprise an overwhelming majority of the Chicago
metropolitan population, extending the ternary plots to four groups for metropolitan
areas such as Los Angeles presents some challenges. Methods that use a similar tech-
Evolution of Segregation
Bader 32
nique to plot the composition of four groups using three-dimensional models have been
developed (e.g., Torres-Roldan et al., 2000). At worst, ternary plots can be sorted by
categories of composition for one racial or ethnic group, for example the least prevalent or most evenly distributed. Although the method loses some of the advantages
of investigating the continuous composition of all racial and ethnic groups, investigating continuous patterns for all but one group is desirable to investigating categorical
breakdowns for all groups.
Growth mixture models do not suffer the same limitations on the number of groups;
however, as I noted above, it would be more desirable to model counts or multinomial
logits of racial and ethnic composition. The computational expense of modeling the
outcome in this manner, which substantially increases for each racial and ethnic group
included, makes this method infeasible for the current analysis. Thus, it is possible
that some of the classes identified by the growth mixture model result from violations
of distributional assumptions in the model (Bauer and Curran, 2003). As software and
hardware capabilities improve, researchers should test whether distributional assumptions affect the outcome or interpretation of results.
Beyond the methodological concerns noted above, the limited focus of this paper on
neighborhood racial and ethnic composition leads to substantive questions for future
research. Perhaps most importantly, future studies should examine the pace and place
of changes in neighborhood socioeconomic status and investigate the overlap between
racial/ethnic and socioeconomic change. Many of the negative consequences associated
with racial segregation stem from its influence on economic investment and access to opportunity; studying the strength of the link between the evolution of racial and socioeconomic segregation can reveal the implications for metropolitan inequality. Additionally,
this analysis only describes changes in the quantitative integration of neighborhoods.
Recent innovative ethnographic studies examine the consequences of racial and ethnic
change for residents’ lived experiences (e.g., Pattillo, 2007; Deener, 2010; Katz, 2010).
Increasingly, these studies incorporate the role of larger geographic areas and historical
patterns of change that can both be informed by and inform analyses of neighborhood
change such as those presented here.
Evolution of Segregation
7
Bader 33
Conclusion
Viewing segregation as a structure in process that evolves through the reciprocal changes
in neighborhood racial and ethnic composition links micro-level patterns of mobility
to the larger structural evolution of metropolitan racial and ethnic segregation. This
analysis highlights the advantages of examining the pace of neighborhood change and
the places where changes occur in the evolution of racial and ethnic segregation. In
particular, micro-level processes that contribute to contemporary neighborhood change
leads to gradual, incremental change rather than rapid succession with strong spatial
patterns. The black diffusion, Latino dispersion, and white divergence found in the
Chicago metropolitan area from 1970 to 2000 helps explain patterns of racial and ethnic
segregation in a manner that would be difficult, if not impossible, without investigating
the pace and place of neighborhood racial and ethnic change.
Evolution of Segregation
8
Bader 34
Tables and Figures
Table 1: Count of tracts by racial and ethnic composition, 1970-2000
1970
Racial/Ethnic Composition
All white
All black
All Latino
W-B Mix
W-L Mix
B-L Mix
W-B-L Mix
Total
1980
N
%
1990
N
%
2000
N
%
N
%
1366
231
0
134
196
2
50
69.02
11.67
0
6.77
9.9
0.1
2.53
1127
315
10
161
276
19
102
56.07
15.67
0.5
8.01
13.73
0.95
5.07
965
329
26
191
353
40
136
47.3
16.13
1.27
9.36
17.3
1.96
6.67
747
353
42
174
481
64
185
36.51
17.25
2.05
8.5
23.51
3.13
9.04
1979
100
2010
100
2040
100
2046
100
Note: See text for definition of racial/ethnic categories
Source: Neighborhood Change Database, Geolytics, Inc.
0
(0.00)
n/a
n/a
5
(0.04)
27
(0.14)
0
(0.00)
2
(0.04)
700
(0.36)
(2) All black
(3) All Latino
(4) W-B Mix
(5) W-L Mix
(6) B-L Mix
(7) W-B-L Mix
Total
349
(0.18)
6
(0.12)
1
(0.50)
5
(0.03)
62
(0.47)
n/a
n/a
219
(0.96)
56
(0.04)
(2)
42
(0.02)
3
(0.06)
0
(0.00)
29
(0.15)
0
(0.00)
n/a
n/a
0
(0.00)
10
(0.01)
(3)
164
(0.08)
3
(0.06)
1
(0.50)
4
(0.02)
33
(0.25)
n/a
n/a
5
(0.02)
118
(0.09)
(4)
473
(0.24)
7
(0.14)
0
(0.00)
75
(0.38)
4
(0.03)
n/a
n/a
0
(0.00)
387
(0.28)
(5)
64
(0.03)
14
0.29
0
(0.00)
22
(0.11)
9
(0.07)
n/a
n/a
3
(0.01)
16
(0.01)
(6)
178
(0.09)
14
(0.29)
0
(0.00)
34
(0.17)
19
(0.14)
n/a
n/a
0
(0.00)
111
(0.08)
(7)
1,970
(1.00)
49
(1.00)
2
(1.00)
196
(1.00)
132
(1.00)
n/a
n/a
227
(1.00)
1,364
(1.00)
Total
Notes: Row proportions in parentheses; no tracts were all-Latino in 1970; see text for description of racial/ethnic categories
666
(0.49)
(1)
(1) All white
Racial/Ethnic
Composition
Table 2: Matrix of transitions from racial categories 1970-2000
Evolution of Segregation
Bader 35
0.18
0.28
0.38
0.49
Black
Black
Black
Black
Latino
Latino
Latino
Latino
%
%
%
%
%
%
%
%
1970
1980
1990
2000
1.58
1.60
1.66
1.74
0.18
0.10
0.00
1.58
0.01
0.01
Percent black
Linear change in percent black
Quadratic change in pct. black
Percent Latino
Linear change in percent Latino
Quadratic change in pct. Latino
1970
1980
1990
2000
52.50
Percent of tracts
Stable
white
0.90
0.79
0.71
0.64
94.22
95.73
97.04
98.17
94.22
1.60
-0.10
0.90
-0.12
0.01
14.27
Stable
black
7.27
7.36
7.44
7.54
32.44
34.81
36.96
38.89
32.44
2.48
-0.11
7.27
0.08
0.00
4.16
Stable
multiethnic
integration
Racially Stable
3.79
3.78
3.77
3.76
3.64
71.61
130.32
179.75
3.64
72.61
-4.64
3.79
-0.01
0.00
3.86
Allwhite to
all-black
succession
2.03
3.23
4.34
5.34
0.04
4.30
8.79
13.51
0.04
4.14
0.12
2.03
1.25
-0.05
3.84
Allwhite to
multiethnic
integration
Black Growth
51.36
59.53
66.70
72.86
2.23
2.33
2.44
2.55
2.23
0.10
0.00
51.36
8.68
-0.50
3.60
Integrated
whiteLatino
to allLatino
11.50
24.21
36.46
48.26
0.62
1.62
2.59
3.52
0.62
1.02
-0.02
11.50
12.94
-0.23
3.92
Mostly
white to
majority
Latino
2.54
3.14
4.33
6.10
0.15
0.20
0.28
0.39
0.15
0.04
0.01
2.54
0.31
0.29
9.39
Late
Latino
growth
Latino Growth
18.37
23.22
26.82
29.17
1.02
2.98
4.75
6.33
1.02
2.06
-0.10
18.37
5.47
-0.62
4.46
Latino
growth
followed
by
displacement
Table 3: Transformed coefficients of latent growth trajectories and predicted values of tract proportion black and
Latino populations in Chicago metropolitan tracts
Evolution of Segregation
Bader 36
Evolution of Segregation
Bader 37
Figure 1: Ternary plots of non-Latino white, non-Latino black, and Latino tract racial
and ethnic composition in 1970, 1980, 1990, and 2000 in the Chicago-Gary-Kenosha,
IL-IN-WI CMSA
Evolution of Segregation
Bader 38
Figure 2: Ternary plots showing trend in decadal racial and ethnic change from 1970
to 2000, by racial and ethnic composition in 1970
Evolution of Segregation
1970
% Latino
1980
% white
% Latino
% black
% Latino
% black
% Latino
% black
% Latino
% black
% Latino
% black
% white
% Latino
% black
% Latino
% black
% white
% Latino
% black
% Latino
% black
% white
% black
% Latino
% black
% white
Mostly white to
predominantly
Latino
% Latino
% white
Late Latino
growth
% black
% white
% black
Integrated
white-Latino to
all-Latino
% black
% white
% Latino
% white
% Latino
% black
% white
All-white to
predominantly
black
% black
% white
% Latino
% white
% Latino
% black
% white
All-white to
all-black
succession
% black
% white
% Latino
% white
% Latino
% black
% white
Stable
multiethnic
integration
% black
% white
% Latino
% white
% Latino
% black
% white
Stable black
% black
% white
% Latino
% white
% Latino
% black
% white
Stable white
% black
% white
% Latino
% black
% white
% Latino
% black
% white
% white
% black
% white
% Latino
% black
% white
% Latino
% black
% white
% Latino
% white
% Latino
% black
% white
2000
% black
% white
% Latino
% black
% Latino
% Latino
% black
% white
% Latino
% white
% Latino
% black
% Latino
1990
% black
% white
% Latino
Bader 39
% Latino
% white
Latino growth
followed by
displacement
% black
Figure 3: Ternary plots of observed racial and ethnic compositions in 1970, 1980, 1990,
and 2000 by latent growth trajectory class
Evolution of Segregation
Bader 40
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Figure 4: Map of neighborhood racial and ethnic careers in the Chicago CMSA
Evolution of Segregation
Bader 41
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