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. Author manuscript; available in PMC: 2014 Oct 1.
Published in final edited form as: Demography. 2013 Oct;50(5):1873–1896. doi: 10.1007/s13524-012-0177-x

Residential Integration on the New Frontier: Immigrant Segregation in Established and New Destinations

Matthew Hall 1,
PMCID: PMC4151043  NIHMSID: NIHMS589556  PMID: 23192394

Abstract

This article explores patterns and determinants of immigrant segregation for 10 immigrant groups in established, new, and minor destination areas. Using a group-specific typology of metropolitan destinations, this study finds that without controls for immigrant-group and metropolitan-level characteristics, immigrants in new destinations are more segregated and immigrants in minor destinations considerably more segregated than their counterparts in established destinations. Neither controls for immigrant-group acculturation or socioeconomic status nor those for demographic, housing, and economic features of metropolitan areas can fully account for the heightened levels of segregation observed in new and minor destinations. Overall, the results offer support for arguments that a diverse set of immigrant groups face challenges to residential incorporation in the new areas of settlement.

Keywords: Segregation, Immigration, New Destinations

Introduction

The rapid rise in America’s immigrant population has ushered in a new era of demographic change in which one in four Americans is either an immigrant or the child of immigrants.1 However, just as important as the increase in the immigrant population is their geographic dispersion out of a handful of major gateways and into communities throughout the country. Consider, for example, that in 1970, nearly one-quarter of all immigrants to America lived in just one of three U.S. cities (New York City, Los Angeles, or Chicago), but by 2010, this share had shrunk to just 13 %. Even more striking, the relative size of the immigrant population soared during this period—often by factors of 1,000 % or more—in U.S. metropolitan areas throughout the Great Plains, Midwest, and Southern Atlantic (Singer 2005, 2009).

The redistribution of America’s immigrants has been a broad-scale exercise in regional deconcentration—one that shifted millions of foreign-born persons from long-standing engines of immigrant integration into communities with little prior history of incorporating newcomers. Yet, this process of deconcentration at the regional level is not necessarily occurring at the local level—in the neighborhoods of these new areas where immigrants live. This is an important consideration because residential separation serves as an important benchmark for gauging immigrant incorporation and the scope of racial/ethnic inequality (Charles 2003; Iceland 2009; Massey and Denton 1993; White and Glick 2009), and can help to contextualize the growth of local policies regarding immigrants (Capps et al. 2011).

Existing research on residential sorting in new destinations has reached mixed conclusions: Park and Iceland (2011) found that immigrants in newer destinations are more residentially integrated with natives than their counterparts in immigrant gateways. By contrast, Lichter et al. (2010) found that Latino segregation from native whites is significantly higher in new destinations than in established gateways, and that the difference cannot be explained by structural characteristics of metropolitan areas nor by income inequality between whites and Hispanics living in these areas. Although prior research is informative and raises a number of important issues about the prospects for residential integration on the new settlement frontier, it is limited by the standard practice of combining groups from various countries into broad panethnic categories, such as Hispanic or Asian. This may be an erroneous decision if the groups that populate these panethnic populations are socially, economically, or otherwise distinct. This panethnic convention poses a specific challenge to residential research because immigrant groups often have diverse settlement patterns (e.g., Filipinos to California, Indians to New York). In prior work addressing these issues, the focus has typically been on a single group or single community.

The goal of this article is to provide an account of how immigrant dispersion away from traditional U.S. destinations is shaping residential integration while overcoming some of the shortcomings of previous work by focusing on 10 of the largest new immigrant groups: five from Asia (Chinese, Indians, Koreans, Filipinos, and Vietnamese) and five from Latin American and the Caribbean (Dominicans, Haitians, Mexicans, Jamaicans, and Salvadorans). With historical settlement data for each group, I create a group-specific destination typology for the 100 largest metropolitan areas, where the overwhelming majority of American immigrants live, that recognizes that a new destination for one group may be an established destination for another. This work is guided by three main questions: (1) Do differences exist in immigrant-group segregation from native-born, non-Latino whites among established, new, and minor destinations?; (2) Can differences in segregation between destination types be explained by characteristics of immigrant groups and/or structural features of the metropolitan areas?; and (3) Does the association between destination type and segregation vary by immigrant group?

Background

The dispersion of immigrant groups from traditional destinations and into communities with little prior history of immigration has been the source of great scholarly attention (Massey 2008; McConnell 2008; Singer 2005, 2009; Zúñiga and Hernández-León 2005), prompting some to claim that a “contemporary diaspora” is underway (Reis 2004). Despite the range of scholarship on issues related to immigrant redistribution, relatively little is known about how residential processes play out in these new areas of settlement and whether residential integration follows from regional deconcentration.

Two general theoretical perspectives have been developed to understand how residential segregation varies across places: spatial assimilation and place stratification. The spatial assimilation model argues that upon initial entry into the host country, immigrants will congregate in ethnic enclaves where information on employment, housing, and other functional requirements is accessible and plentiful, and that provide a social environment rich in ethnic and linguistic resources that help ease the transition into the new land. According to the spatial assimilation perspective, after accumulating economic resources and becoming more familiar with American institutions, norms, and values, immigrants will become less reliant on the security of enclaves and seek non-ethnic neighborhoods where the quality of housing, schools, and public services is better (see Massey 1985; Rosenbaum and Friedman 2007). Empirically, the assimilation model holds that groups living in metropolitan areas with better language skills, longer durations in the United States, and higher earnings will be less segregated than their counterparts possessing less beneficial characteristics.

Although the place stratification perspective recognizes that language, socioeconomic status, and other assimilation characteristics advance residential incorporation, it points to persistent barriers that immigrants and minorities face in navigating American housing markets. Included here are the discriminatory practices of banks and mortgage lenders, realtors, and federal policies (Massey and Denton 1993; Ross and Yinger 2002). Equally as important is the aversion of whites toward living in neighborhoods with even moderately minority populations (Charles 2000, 2006; Farley et al. 1997; Krysan 2002) and the “flight” of whites in the face of growing minority or immigrant populations (Crowder et al. 2011; Pais et al. 2009).

Although the insights gleaned from these two perspectives are generally not applied to broad population shifts across regions, some have argued that the immigrant dispersion now underway is a scaled-up process of spatial assimilation and that immigrants moving from traditional to nontraditional areas are undergoing a move akin to one from a central city enclave to a suburban bedroom community (Frey and Liaw 2005). Others have been quick to point out that immigrants are increasingly settling directly in nontraditional locales from their sending countries, such that internal migrants are a minority of immigrants living in these new destinations (Lichter and Johnson 2009; Singer 2005). Moreover, this simple assimilation argument ignores that the entrance of new groups potentially disturbs the fragile social fabric and racial structures of existing communities, arousing competition and potentially jeopardizing the position of majority group members.

Whether the redistribution of the immigrant population has resulted in greater residential incorporation is the source of an ongoing scholarly debate. Frey and Liaw (2005:212) were explicit in making the link from a regional process of diffusion to a local one, arguing that “minorities undergoing spatially assimilating long-distance migration will be residing in more integrated neighborhoods locally.” However, support for this argument has been limited. Park and Iceland (2011), on the one hand, found evidence that Latino and non-Latino white, black, and Asian immigrants are less segregated from native whites in new than in traditional immigrant destinations. Similarly, Alba and colleagues (2010) found that exposure of Latino children to non-Latino whites is considerably higher in new destinations than in established gateways. On the other hand, Lichter et al. (2010) found that dissimilarity of Latinos from native whites is significantly higher in new destinations than in established gateways and that the difference cannot be explained by structural characteristics of metropolitan areas or by income inequality between whites and Latinos. Similarly, Fischer and Tienda (2006) found that Latino immigrants are more segregated from other groups in emerging Latino destinations than in traditional ones and that Latino immigrant segregation is especially high in “other” destinations with relatively small Latino populations. These suggestions of heightened segregation in new versus traditional destinations are buttressed by mobility research showing that recent increases in local immigrant populations are tied to native out-migration (Crowder et al. 2011).

Part of the reason for the unevenness of this previous work stems from the way destination types have been defined. Large-scale studies of immigrant incorporation in new destinations typically rely on destination typologies that consider the historical settlement of all immigrants (Singer 2005, 2009) or panethnic immigrant populations (Kandel and Cromartie 2004; Kuk and Lichter 2011; Lichter et al. 2010; Suro and Singer 2003). There are several important drawbacks to these approaches for understanding processes of residential incorporation. First, combining immigrant subgroups into common categories creates an implicit assumption of homogeneity—that the experiences of each group within the broader panethnic population are equivalent. Yet, demographic, socioeconomic, political, and cultural differences between specific groups are considerable (Waters and Ueda 2007). Race scholars have also been quick to note that simple labels like “Asian” and “Hispanic” ignore differences in how groups adopt panethnic identities (Kibria 1998; Masuoka 2006), understate the role of the state in creating these classifications (Itzigsohn 2004; Okamoto 2003; Yanow 2003), and overlook conflicts between groups within the same panethnic category (Espiritu 1993). In the context of segregation, Kim and White (2010) demonstrated that while panethnicity remains relevant, there is a considerable amount of residential separation between the groups that make up panethnic categories.

A consequence of this convention is that specific groups’ unique settlement histories are ignored. Certainly, many immigrants are drawn to long-standing ports of entry (e.g., New York City and Los Angeles), but even among the major gateways, substantial variation exists in the size and recency of immigrant group populations. The uneven attraction of metropolitan areas is due to a variety of factors, including group differences in socioeconomic and linguistic resources (Gurak and Kritz 2000; Nogle 1997), distance to origin country and strength of coethnic social networks (Bartel 1989; Ellis and Goodwin-White 2006; Kritz and Nogle 1994), and the extent to which housing and labor conditions match needs (Fang and Brown 1999; Kritz and Nogle 1994; Leach and Bean 2008; Ley 2007). Given the diversity in the sociodemographic profiles of immigrant groups and historical and geographical factors that attract immigrants to different regions of the United States, it follows that what is a “traditional” destination for one immigrant group may well be a “new” destination for another.

This issue is illustrated by considering the immigrant experience in New York City (NYC). This city has long been a primary port of entry into America, but Mexican migration there has been more recent. Although numerous factors have historically limited the migration of Mexicans to NYC, increased demands for low-skill labor and the saturation of labor pools in traditional southwestern strongholds resulted in substantial growth in NYC’s Mexican population. The emergence of NYC as a new Mexican destination has attracted a good deal of scholarship (e.g., Cortina and Gendreau 2003; Jones-Correa 1998; Smith 1996, 2001). A common theme is that although NYC has a long history of turning immigrants into Americans, its social and institutional arrangements that aid in the integration of established immigrants groups (Levitt 2007; Kim and Kim 2001; Min 1992) may be less equipped to aid newer immigrant groups, such as Mexicans. The larger question then is not simply whether—in line with the assimilation perspective—new immigrants are more residentially separated from majority groups than settled ones, but whether the broader context of a group’s migration history into particular places alters the incorporation process. The situation of Mexicans in NYC is just one example of the potential importance of recognizing the distinct settlement patterns of specific groups.

Broadly speaking, immigrant segregation is maintained via two processes: the extent to which immigrants band together in coethnic neighborhoods and the residential responses of the native-born. Following the spatial assimilation perspective, immigrants living in nontraditional areas may have settled there partially because they are less reliant on the protection and resources offered by ethnic neighborhoods and therefore less likely to cluster in dense enclaves than their counterparts in traditional destinations. Yet, because migration streams to new areas draw not only from secondary (internal) migrants but also from primary migrants coming directly from origin countries, one might expect destination-type differences to be small. Either way, the argument implies that any differences in ethnic clustering are due to compositional differences in local group populations. An alternative argument is that broader group processes alter the tendency to self-segregate. Immigrants in new areas, for example, may be more likely congregated in order to concentrate and expand the availability of ethnic goods and services. In traditional destination areas, by contrast, immigrants may be able to tap into the organizational resources and services of ethnic communities without actually living there. This process of “heterolocalism” (Wright and Ellis 2000; Zelinsky and Lee 1998) has been observed for several groups in established settlement areas, including Chinese immigrants in New York City (Zhou 1992), Vietnamese immigrants in Portland (Hardwick and Meacham 2008), Hatian immigrants in Chicago (Zelinsky and Lee 1998), and Salvadorans in Washington DC (Price et al. 2005).

Immigrant segregation is also generated by the actions of the native-born. Research has shown that native-born residents have heightened odds of neighborhood out-migration when local immigration increases (Crowder et al. 2011), and related work reveals not only that this migratory response to the presence of immigrants is stronger in nontraditional areas but also that the neighborhood destinations of native movers have substantially fewer immigrants than the ones they left (Hall et al. 2010). This work, however, has not determined which immigrant groups—for example, Mexicans, Indians, or Canadians—natives are fleeing from. An argument could certainly be made that native out-migrants are simply reluctant to share neighborhoods with racial “others,” but particular groups’ settlement histories may play an added role. Native attitudes toward and perceptions of ethnic groups may be especially sensitive to the kinds of rapid neighborhood change that define the in-migration patterns of immigrant groups who are newer to a region.2 The flip side is that natives may have developed some sense of comfortableness with more-settled immigrant groups, and their presence is therefore less likely to induce out migration or shape neighborhood selection.

Thus, group settlement profiles—not just the history of immigration to places—potentially matter for understanding residential incorporation. Accordingly, I track the size and growth of 10 immigrant groups into the 100 largest metropolitan areas of the United States to develop a group-specific destination typology that recognizes the diversity in the settlement patterns of specific groups and allows the same metropolitan area to serve as an established destination for one group but a new destination for another.

Data and Methods

This analysis relies on data from Summary File 3 of Census 2000.3 Using these files, I extract data on all 39,525 census tracts in the 100 largest metropolitan areas (as of 2000). Although the rise in immigration to smaller metropolitan and rural areas is an important trend (Lichter and Johnson 2006), a significant majority (83.6 %) of American immigrants resides in the top 100 metropolises.4 The 10 immigrant groups that form the focus of this analysis were chosen based on overall size and recent growth, and have the added benefit of being equally split between those from Asia and from Latin American and the Caribbean (LAC).5 In this analysis, I treat census tracts as proxies for neighborhoods. Although they are imperfect operationalizations of neighborhoods, they are defined by local committees of data users and public officials and are assumed to better approximate the usual conception of neighborhood than any other spatial unit provided by the Census Bureau (Jargowsky 1997; White 1987). To prevent sampling bias due to small populations, I exclude 459 tracts with fewer than 250 residents; to avoid confounding by institutional settings, 368 tracts with group-quarters populations greater than 25 % of the total population are deleted. In total, my database comprises 38,719 census tracts.

I use the mainstay of segregation analysis—the Index of Dissimilarity (D)—to measure residential segregation:

D=12t=1T|ptjPjptkPk|, (1)

where t refers to tracts within a metropolitan statistical area (MSA), j and k refer to population groups, ptj is the population of group j in tract t, and Pj is the population of group j in the metropolitan area. The index ranges from 0 (no segregation) to 1 (total segregation) and can be interpreted as the proportion of one group that would have to relocate in order to achieve an identical neighborhood distribution to that of the other group. In this analysis, and consistent with previous segregation work, the reference group (k) is native-born non-Hispanic whites (hereafter called “native whites”). To facilitate interpretation, D scores are multiplied by 100. To prevent bias associated with sampling error for small population groups, I calculate D scores only for metropolitan areas containing an immigrant group population of 1,000 or more (Cutler et al. 2008; Iceland and Scopilliti 2008; Park and Iceland 2011).

To define metropolitan destination types, I use census data to examine each immigrant group’s size, population share, and growth from 1970 to 2000 and then assign destinations to one of three types: established, new, or minor.6 “Established” destinations are defined as metropolitan areas where a group’s percentage of the total metropolitan population in 1970 or 1980 exceeded the corresponding mean across all metropolitan areas and where the group’s absolute metropolitan population exceeded the metropolitan average. “New” destinations are non-established areas in which a group’s percentage of the total population in 1990 or 2000 was larger than the metropolitan average for the group and in which the group’s growth rate during the 1980s or 1990s was at least two times the corresponding metropolitan mean. “Minor” destinations refer to metropolitan areas where neither set of conditions is met. This method for determining destination type results in 111 established, 272 new, and 239 minor destinations.7 Generally speaking, established destinations are areas where a group was heavily represented, in terms of both size and population share, by 1980; new destinations are those that experienced rapid immigrant-group population growth during the 1980s or 1990s; and minor destinations do not meet either condition, corresponding instead to “old” destinations with modestly sized group populations but little recent growth and to “developing” destinations with small group populations but modest signs of growth.

Table 1 shows a breakdown of the percentage of immigrant group members residing in each destination type and the total number of metropolitan areas (in parentheses) considered to be established, new, and minor. (A full list of the destination types by metropolitan area and immigrant group is shown in Online Resource 1, Table S1. In accordance with my earlier example, New York is an established destination for Chinese, Dominican, Haitian, Indian, Jamaican, and Korean immigrants, but a new destination for Filipinos, Mexicans, and Salvadorans, and a minor destination for the Vietnamese. Likewise, Portland, often regarded as a major “emerging” immigrant gateway (Hardwick and Meacham 2008; Singer 2005), is a new destination for Mexicans and Indians, but represents an established destination for Chinese, Korean, Salvadoran, and Vietnamese immigrants. It is also important to recognize the group variability in the distribution of group members across destination types. Although a majority of each group resides in established destinations, some groups (e.g., Filipinos and Vietnamese) are considerably less concentrated than others (e.g., Dominicans and Jamaicans).

Table 1.

Distribution of immigrant groups across destination types

Immigrant Group Established
New
Minor
Total MSAs for Group
% (MSAs) % (MSAs) % (MSAs)
Chinese 61 (10) 24 (43) 15 (34) (87)
Filipinos 58 (12) 28 (17) 14 (44) (73)
Indians 63 (22) 25 (33) 12 (32) (87)
Vietnamese 50 (17) 40 (43) 10 (19) (79)
Koreans 63 (14) 26 (34) 11 (29) (77)
Mexicans 68 (15) 28 (40)   4 (38) (93)
Salvadorans 59   (5) 35 (26)   6 (19) (50)
Dominicans 67   (2) 29 (12)   5   (9) (23)
Jamaicans 78   (9) 16 (14)   6 (10) (33)
Haitians 64   (5) 32 (10)   4   (5) (20)

Notes: The number of metropolitan areas is shown in parentheses. A full list of group-specific destination types is in Online Resource 1, Table S1.

Several destination-specific characteristics of immigrant groups are included in the models: group size (immigrant-group population (in 10,000s)); recent arrivals (percentage of group members arriving between 1995 and 2000); English ability (percentage of group members who speak English “only,” “very well,” or “well”); white income parity, which is the ratio of a group’s median family income to the native, non-Latino white population’s median family income (multiplied by 100); and homeowners, which refers to the percentage of housing units headed by group members that are owner-occupied.8 Following the spatial assimilation perspective, immigrant groups with higher levels of English proficiency and homeownership, with median incomes that are closer to whites’, and with fewer recent arrivals are expected to have reduced segregation. To the extent that these characteristics are distributed unevenly across destination types, these factors should partially attenuate differences in segregation between new and established destinations.

An extensive literature indicates that racial segregation is related to regional location, population size and composition, housing market conditions, and industrial mix (Farley and Frey 1994; Iceland and Nelson 2008; Logan et al. 2004; Timberlake and Iceland 2007). Thus, I include controls for census region, metropolitan total population (logged), percentage immigrant, percentage black, and percentage elderly. Because segregation may vary according to the breadth of its immigrant population, I include the number of new immigrant groups (of the 10 analyzed here) with populations of 1,000 or greater. Similarly, because long-standing immigrant gateways may have unique histories of integrating immigrants, a dummy variable captures the five metropolitan areas with the largest immigrant populations (Chicago, Houston, Los Angeles, Miami, and New York City).9 Three housing characteristics are incorporated: suburbanization (percentage of the metropolitan population living outside the central city), vacancy rate (share of housing units that are unoccupied), and new construction (percentage of the housing supply built during the 1990s). Characteristics of the following industries in which immigrants congregate are also included: science and technology, low-skill service, and manufacturing, as well as the percentage of the labor force in the military.10 Overall means and means by destination type, along with zero-order correlations, are shown for these variables in Online Resource 1, Table S3 in the appendix.

Multivariate models follow the framework described by Iceland and Scopilliti (2008) and Massey and Denton (1989) that combines segregation scores for all groups in a metropolitan area in which the 1,000 group size threshold is met (N = 622). To adjust for the non-independence of observations within metropolitan areas, I analyze these data using generalized linear models with robust standard errors that take the general form11:

Yjm=β0+β1Destinationjm+β2Groupjm+β3Structuraljm+ejm, (2)

where Yjm is the dissimilarity score for immigrant group j in metropolitan area m; Destinationjm is a set of group-specific destination-type dummy variables (with established areas as the referent); Groupjm is a vector of group-specific demographic and acculturation characteristics for group j in metropolitan area m; and Structuraljm is a set of metropolitan population, housing, and economic characteristics for metropolitan area m.12

Results

Immigrant-Group Segregation by Destination Type

Mean immigrant-group dissimilarity from native whites is shown in Table 2. The table shows both weighted (by metropolitan immigrant-group population) and unweighted means, with the former providing a useful indicator of the residential experience of the typical group member, and the latter representing the segregation experience in the typical destination area. Because the goal of this analysis is to evaluate variation in segregation across destination, I focus on the unweighted scores. Nevertheless, it is important to note that because most immigrant groups are concentrated in established areas, the “typical” group member is likely to experience residential patterns exhibited there.13

Table 2.

Dissimilarity of immigrant groups from native whites, by destination type, 2000

Unweighted
Weighted
Established New Minor Established New Minor
Chinese .59 .61 .62 .63 .55 .60
Filipinos .58 .54 .59 .59 .52 .57
Indians .58 .62 .66 .58 .57 .65
Vietnamese .65 .70 .72 .66 .67 .74
Koreans .54 .59 .62 .59 .56 .62
Mexicans .62 .64 .70 .65 .65 .71
Salvadorans .68 .73 .79 .71 .72 .79
Dominicans .70 .72 .85 .82 .71 .83
Jamaicans .75 .71 .80 .78 .68 .81
Haitians .83 .80 .86 .82 .72 .86

Notes: Includes only MSAs with at least 1,000 immigrant group members. Weighted means are weighted by group metropolitan area population.

The unweighted means in Table 2 indicate that for all but Filipinos, Jamaicans, and Haitians, immigrant-group segregation from native whites is higher in new destinations than in established areas. The magnitude of the differences is modest for most groups but is consistent with existing research suggesting that segregation in traditional immigrant points of entry is being re-created in nontraditional settlement areas. More striking is that new immigrant groups in minor destinations are considerably more segregated from native whites than those in either established or new destination areas—a pattern that holds for all groups evaluated. Although the heightened segregation in these minor areas has been observed before (Fischer and Tienda 2006), it has received little attention.14

Multivariate Models of Immigrant Segregation

Results from models predicting immigrant-group dissimilarity from native whites are shown in Table 3. The first model shows group differences in dissimilarity from white natives (with Chinese immigrant segregation serving as the referent) and the effects of destination type. The results indicate that that without controls for group acculturation/SES or metropolitan characteristics, immigrants in new and minor destinations are significantly more segregated from natives whites than are those in established areas. In line with the large body of work on racial residential segregation, there is a racial/ethnic hierarchy to the results: Asian immigrant groups are less segregated from native whites than are LAC groups. Perhaps surprisingly, Mexican immigrants represent one of the two exceptions to this pattern, being much less segregated than any of the other LAC groups. The other exception is Vietnamese immigrants, whose history as refugees and participation in governmental settlement programs may have led to heightened levels of segregation. Together, these origin-group and destination-type differences explain nearly one-half (R2 = .47) of the variation in immigrant-group segregation across destinations.

Table 3.

Regressions of immigrant group dissimilarity from native whites, 2000

Variable (1) (2) (3)
Destination Type
  Established (omitted)
  New   2.25 (1.12)*   1.41 (0.70)*   2.31 (1.00)*
  Minor   6.35 (0.99)***   5.69 (0.99)***   4.74 (1.01)***
Immigrant Groups
  Chinese (omitted)
  Filipino −3.87 (0.96)***   0.42 (1.38)   1.12 (1.39)
  Indian   1.95 (0.70)** −0.09 (1.25)   1.63 (1.16)
  Vietnamese   9.40 (0.89)*** 11.84 (1.59)***   9.54 (1.42)***
  Korean −1.77 (0.88)* −0.73 (1.20) −1.55 (1.07)
  Mexican   5.00 (1.12)** −5.87 (2.71)* −4.67 (2.64)
  Salvadoran 14.13 (1.23)*** 12.35 (2.19)*** 11.70 (1.87)***
  Dominican 15.80 (2.46)*** 14.74 (2.93)*** 12.47 (2.73)***
  Jamaican 14.56 (1.74)*** 21.17 (2.25)*** 19.02 (2.26)***
  Haitian 21.81 (1.60)*** 24.20 (2.45)*** 22.40 (2.23)***
Group Characteristics
  Group size (in 10,000s)   0.12 (0.03)***   0.05 (0.02)*
  Recent arrivals   0.15 (0.06)**   0.09 (0.05)
  English ability −0.19 (0.05)*** −0.18 (0.05)***
  White income paritya   0.12 (0.13)   0.06 (0.03)
  Homeownersa −0.21 (0.05)*** −0.16 (0.03)***
Region
  Northeast (omitted)
  Midwest   0.79 (1.07)
  West −0.98 (1.05)
  South −0.18 (0.78)
Demographics
  Total population (ln)   2.89 (0.69)***
  Percent immigrant −0.24 (0.04)***
  New immigrant groups −0.13 (0.24)
  Top-5 immigrant gateway   2.05 (1.01)*
  Percentage black   0.00 (0.03)
  Percentage elderly   0.18 (0.16)
Housing Supply
  Suburbanization −0.02 (0.01)
  Vacancy rate −0.12 (0.18)
  New construction −0.21 0.07)***
Economic Structure
  Science and technology −0.04 (0.17)
  Low-skill service   0.56 (0.23)*
  Manufacturing   0.30 (0.10)**
  Military −0.38 (0.13)**
Intercept 57.42 (1.14)*** 79.00 (7.32)*** 37.64 (11.49)**
R2     .47     .56     .66

Notes: N = 622 group destinations (number of metropolitan areas = 98). Robust standard errors are shown in parentheses. Includes only MSAs with at least 1,000 group members.

a

Refers to characteristics of foreign- and native-born members of ethnic origin group.

*

p < .05;

**

p < .01;

***

p < .001

Characteristics of the groups living in these different destinations are added to the equation in the second column of Table 3. When these acculturation and socioeconomic factors of groups are equalized, the coefficient for new destinations is reduced by 37 %. This attenuation is due mostly to immigrants in new destinations being less likely to speak English proficiently and own homes, factors that tend to reduce segregation between immigrants and native whites. Along similar lines, the minor destination effect declines by about one-tenth when group characteristics are added. Here, the reduction is largely attributable to the high share of recent arrivals who live in minor destinations. However, despite their newer arrival, immigrants in these areas also tend to have better English skills and higher earnings than those in other areas, which partially suppresses higher levels of segregation. Thus, part of the explanation for the higher segregation in new and minor destinations is simply compositional: immigrants in these areas hold different sets of characteristics that make them less likely to live alongside whites.

The coefficients on the group characteristics indicate that immigrant segregation from native whites is significantly higher where group populations are larger or shares of recent arrivals higher,15 and significantly lower where groups have greater English proficiency or where a larger percentage of their members own homes. However, SES, as measured by income parity with native whites, has a positive albeit nonsignificant effect on segregation.16 Thus, the results are mostly consistent with the spatial assimilation model: better-acculturated immigrant groups with more-established U.S. roots are less segregated from native whites than others, although new immigrant groups do not appear to be converting financial capital into greater residential proximity with native whites.

The third model in the table incorporates metropolitan demographic, housing, and economic variables. This full model evaluates group differences in segregation given similar acculturation, socioeconomic, settlement, and ecological contexts and indicates that immigrant segregation in new and minor destinations remains significantly higher than in established destinations.17 The net destination-type differences in segregation are relatively modest but stand in contrast to arguments that the dispersion of immigrants away from traditional areas is leading to residential integration (Alba et al. 2010; Frey and Liaw 2005; Park and Iceland 2011). At a minimum, a conservative interpretation of the results is that segregation is being reproduced in new and minor destinations, and there are signs—certainly in the case of minor destinations—of underlying processes that amplify immigrant segregation.

The coefficients on the metropolitan factors are consistent with past research: immigrant segregation is higher in larger metropolitan areas and in those with large low-skill service and manufacturing sectors, but lower in areas with newer housing stocks and a large military presence. The results also indicate that immigrant segregation is lower in metropolitan areas where all immigrants compose a greater share of the total population, but higher in the five largest immigrant gateways. Although these may seem to be contradictory findings, the positive effect for the top five immigrant gateways highlights the unique residential experiences of immigrants living in these long-standing immigrant metropolises.18 This finding also uncovers one possible source of the disagreement in prior research by showing that the five major ports of entry have distinctively high levels of immigrant segregation.

Lastly, it is striking that even with the complete set of group and metropolitan controls, there are substantial differences in segregation between the 10 immigrant groups. These differences tend to cut along racial/ethnic lines, with Asian immigrant groups generally being less segregated from native whites than LAC immigrant groups, thus providing some support for the standard practice to combine groups into broader panethnic categories. Again, however, Vietnamese and Mexican immigrants stand out: the former are much more segregated than any other Asian immigrant group, and the latter are less segregated from native whites than most other groups.19

Group-Specific Models of Immigrant Segregation

Although these combined-group models are informative, they are potentially problematic if specific immigrant groups exhibit distinct patterns of residential sorting, a possibility evident in their patterns of dispersal across destination types and segregation levels. Small sample sizes preclude separate multivariate models for each of the 10 immigrant groups but selectively trimmed models for the larger ones—Chinese, Indian, Vietnamese, Korean, and Mexican immigrants (i.e., groups for which segregation scores are estimated in at least 75 metropolitan areas)—are possible to estimate. Variables included in these reduced models were selected based on their theoretical and empirical relevance, and include group factors (arrival recency, language ability, and income parity) and metropolitan factors (region, population size, housing market conditions, and industrial mix).20 In the results shown in Table 4, three models are shown for each group: an unadjusted model describing differences in segregation by destination type, a model that adds in group-specific characteristics, and a model that incorporates metropolitan-level controls.

Table 4.

Group-specific regressions of immigrant group dissimilarity from native whites

Variable Chinese Indians Vietnamese Koreans Mexicans
Destination Type
  Established (omitted)   ––
  New   2.10 −1.26 4.94   4.48   2.09   2.56   5.77   5.32   4.59   4.97   4.39   5.48   1.82   1.21   3.30
  Minor   2.58   0.87 −3.53   8.04   5.84   3.58   7.82   8.04   6.16   7.75   7.85   6.34   7.57   6.68   2.83
Group Characteristics
  Recent arrivals   0.56   0.32   0.21   0.22   0.02 −0.04   0.33   0.40   0.15   0.11
  English ability 0.42 0.24 0.32 0.29 −0.29 −0.22 0.31 0.28 0.24 0.25
  White income paritya   0.06   0.01   0.17   0.10 −0.02 −0.08   0.19   0.14 0.18 0.10
Region
  Northeast (omitted)
  Midwest   2.45 −2.45   3.21   2.81 5.11
  West −1.06 −0.34 −2.72 −1.54 9.42
  South   4.37   0.76   2.06   5.24 8.47
Demographics
  Total population (ln)   1.35   1.81   1.62   3.08   3.17
  % immigrant 0.25 0.22 −0.13 −0.12 0.24
Housing Supply
  New construction −0.15 −0.03 0.41 0.35 0.48
Economic Structure
  Low-skill service   1.46   2.49   1.17   1.31   0.72
  Manufacturing   0.91   0.74   0.29   0.42 0.41
  Military 0.26   0.17 −0.77 −0.33 −0.51
Intercept 58.70 58.26 30.41 57.90 60.59 16.51 64.55 65.18 34.75 53.93 43.11   6.02 62.11 76.03 59.54
Number of metropolitan areas 87 87 87 87 87 87 79 79 79 77 77 77 93 93 93
Adjusted R2 .01 .38 .63 .18 .37 .73 .12 .17 .46 .12 .27 .47 .13 .25 .66

Notes: Bolded coefficients are significant at p < .05. Includes only MSAs with at least 1,000 group members.

a

Refers to characteristics of foreign- and native-born members of ethnic origin group.

The first model indicates that without controls, all immigrant groups are more segregated in new and minor destinations than in established ones, although significantly so for only three of the five. Group acculturation and socioeconomic characteristics are added in the second column for each group. With these characteristics held constant, Vietnamese and Korean immigrants in new destinations remain significantly more segregated, and all but Chinese immigrants experience significantly higher segregation in minor destinations than in established ones. Among the group-specific variables, the most consistent effect is English ability, highlighting the importance of language skills in the residential attainment process. By contrast, the income effect varies greatly across groups. For Mexicans, where incomes (relative to whites) are higher, segregation is lower. This finding is in line with the spatial assimilation perspective suggesting that Mexican immigrants are translating economic resources into residential proximity to native whites. Segregation of Chinese and Vietnamese immigrants appears to be unaffected by income. Conversely, the income effect is significantly positive for Indian and Korean immigrants.21 This may seem like a peculiar finding, but the presence of affluent Indian and Korean enclaves as well as “ethnoburbs” in communities such as Silicon Valley and the Dallas suburb of Las Colinas offers some clues into its association with segregation (Li 2006, 2009; Skop 2012; Teaford 2007; Wen et al. 2009).

In the final model for each group, metropolitan characteristics are added. There are some interesting differences in the effects of metropolitan characteristics, including region, metropolitan population, new housing construction, and industrial mix. Most importantly, however, segregation from native whites is significantly higher in new destinations for Mexicans, Koreans, and Vietnamese immigrants, even when group-level and metropolitan-level characteristics are held constant. Indian immigrant segregation from native whites in new destinations is also higher, but the coefficient just fails to reach statistical significance (p = .07). Conversely, Chinese immigrants are significantly less segregated in new than in established destinations. The same holds for Chinese immigrants in minor destinations, although not significantly so (p = .10).22 Thus, while the select set of group-specific results shown here mostly upholds the finding from the pooled models that immigrant segregation from natives whites is slightly higher in new and minor destinations, important differences exist across specific groups on this and other factors.23 Lastly, it is worth noting adjusted R2 values indicate that the selected variables explain a substantial portion of group segregation from whites for Chinese, Indians, and Mexicans, but not for Vietnamese or Korean immigrants. This could be due to a different a set of processes generating segregation or, for Vietnamese, to large refugee populations.24

Conclusion

The diffusion of immigrants across the country is one of the most prolific features of America’s new demography. Although long-standing ports of entry continue to attract large numbers of new arrivals, immigrants are increasingly settling in nontraditional areas with little prior history of immigration. The redistribution of America’s foreign-born population is, on one level, cause for celebration: it brings new opportunities for immigrants to fulfill the American Dream and increases the possibility that natives will enjoy the benefits of diversity and immigration in their communities. However, immigrants’ dispersion also raises concerns about how they are faring on the new frontier and what their prospects for incorporation are.

Spatial incorporation has long been seen as a proxy for social incorporation, and thus the guiding empirical question of this study has been whether the broad-scale deconcentration of America’s immigrants is also underway in the neighborhoods of the communities these newcomers are occupying. To answer this question, I used data from Census 2000 to compare patterns of residential segregation in established, new, and minor destinations for 10 specific immigrant groups in the 100 largest metropolitan areas. Overall, the results are consistent with Lichter et al. (2010) and point to signs that the dispersion of immigrants is not leading to greater residential integration. More specifically, for 7 of the 10 groups that I analyzed, immigrant dissimilarity from native whites is higher in new destinations than in established ones. Patterns in minor destinations—metropolitan areas with small and slow-growing immigrant group populations—are especially alarming with all groups being much more segregated in these areas than elsewhere.

Results indicate that part of the explanation for the higher levels of segregation in new destinations is compositional: immigrants who live in new areas tend to be recent arrivals with poor English skills and low earnings, which, in line with spatial assimilation, are negatively related to residence in white neighborhoods. However, even controlling for these group characteristics, immigrants’ new destinations remain more segregated than established ones, and this compositional argument is even less applicable to the high levels of segregation observed in minor areas. Likewise, while demographic, housing, and economic features of metropolitan areas are important correlates of immigrant segregation, they fail to explain the elevated levels of immigrant segregation in new and minor destinations. Subsequent analyses demonstrate that although differences across immigrant groups exist, the heightened levels of segregation in new and minor destinations characterize the residential experience of several specific groups, including Mexicans. The difference in segregation between new and established areas is fairly modest (about 2 points), but finding that immigrant segregation in new destinations is not any lower than in established destinations—often characterized by high levels of segregation—might serve as a cause for concern that the outlook for integration is limited as immigration expands across the nation.

Although all immigrants undergo a difficult process of acclimating to their new homes, immigrants in nontraditional destinations may face unique hurdles. Groups who are relatively new to areas often lack the communal and institutional resources, such as ethnic churches, sports clubs, and advocacy groups, that aid immigrants in established areas. The density of these resources in traditional immigrant gateways facilitates incorporation directly, through job, housing, and medical assistance, but also indirectly by serving as an anchor for group members who may disperse residentially but still access a rich supply of ethnic goods and services. Where these institutional supports are lacking, immigrants may compensate by being more likely to band together in coethnic neighborhoods.

Immigrant segregation is generated through the migratory behaviors of natives. Where an immigrant group’s settlement history is more established, native populations may be more accepting of, or at least more accustomed to, the distinctiveness of the group than they are toward groups whose arrival is more recent. The entrance of newer groups may also trigger fears of declining housing values or concerns about the future of neighborhoods (Ellen 2000). These anxieties with newcomers may make natives more likely to flee in the face of swelling immigrant populations or to alter decisions about which neighborhoods to settle in. Regardless of whether natives in traditional destinations are more tolerant of immigrants, there are many reports that immigrants are not being welcomed warmly in newer destinations. Fennelly (2008), for example, described the ambivalent but often negative feelings that native Minnesotans harbor toward newly arrived Mexican immigrants, expressing concerns about their impact on cultural cohesion, local crime, and school quality. Other work has documented political backlash to rapidly growing immigrant populations, including policies that require landlords to verify immigration status, place limits on household occupancy, declare English as the official language, penalize employers who hire undocumented workers, or deputize police officers into immigration control agents (Capps et al. 2011; Esbenshade 2007; Ramakrishnan and Lewis 2005). Restrictive policies along these lines may act to further divide natives and immigrants and lead to greater residential separation between the groups.

Arguably, both of these issues—the tendency for immigrants to self-segregate and natives’ sensitivity to local immigrant populations—are intensified in minor destination areas where immigrant populations are small but have nevertheless been growing steadily. Perhaps it is in these areas where the entrance of new and unknown immigrant groups incites native out-migration (see Hall et al. 2010). Alternatively, there may exist unmeasured place-specific factors—history of racial exclusion or industrial decline—that characterize exclusively minor destination metros (e.g., Buffalo, Cleveland, and St. Louis). Clearly, better understanding the patterns of segregation in these destinations should be the focus of future research.

In addition to exploring patterns of segregation across destination types, this analysis also differs from existing research by focusing on specific immigrant groups rather than on panethnic groups that assume homogeneity in residential experiences. Doing so not only provides for a more fine-grained evaluation of immigrant groups’ unique settlement histories but also uncovers some exceptional cases: the comparatively low levels of segregation among Mexicans, the high levels among Vietnamese, the opposing results for Chinese immigrants (who are most segregated in established destinations), and the finding that more-advantaged Indian and Korean immigrants are more segregated than less-advantaged ones. Yet, the results also confirm the salience of race/ethnicity in structuring residential patterns, with Asian immigrant groups tending to be more highly segregated than Latin American groups, and Caribbean groups experiencing especially high levels of segregation. Thus, although the distinctions within panethnic categories are important and interesting, they cannot minimize the continued significance of racial/ethnic divisions.

The possibility that exposure and tolerance are locked in a cycle—each one breeding more of the other—bodes well for the long-term hopes of integration in emerging immigrant destinations. In the short-run, however, policy analysts and social scientists should continue to explore the challenges immigrants face in these areas. Particularly relevant to this research is exploring the mechanisms that re-create or amplify segregation in new destinations: Do natives express greater hostility toward immigrants in these areas, and are they converting these attitudes into action by seeking out neighborhoods with fewer immigrants? Are immigrants to new destinations segregating in ethnic enclaves because of the ethnic and linguistic goods and services they provide or as a way to buffer themselves from native populations? Future work should also consider the roles of undocumented migration and local policy contexts in the residential sorting process, and should further expand the scope of both groups (to include some of the newest groups, such as Colombians; and older ones, such as Cubans) and destinations (including rural and micropolitan areas).

Supplementary Material

1
NIHMS589556-supplement-1.pdf (1,015.8KB, pdf)

Acknowledgments

This article acknowledges support from the Penn State University Alumni Association and the Population Research Institute at Penn State, which receives core funding from the National Institute of Child Health and Human Development (Grant R24-HD041025). I am thankful to Editor Tolnay and three anonymous reviewers for their thoughtful comments, as well as to Gordon De Jong, Glenn Firebaugh, Anastasia Gorodzeisky, Deb Graefe, John Iceland, Barry Lee, and Audrey Singer for comments on earlier versions of the manuscript.

Footnotes

Electronic supplementary material The online version of this article (doi:10.1007/s13524-012-0177-x) contains supplementary material, which is available to authorized users.

1

In 2010, 13.6 % of Americans were foreign-born, and another 11.2 % had at least one parent who was born abroad.

2

The “group threat” literature almost exclusively focuses on the stock of ethnic/racial groups (e.g., Hood and Morris 1997; McDermott 2011; Oliver and Wong 2003; Quillian 1996; Rocha and Espino 2009; Taylor 1998) rather than recent changes in their populations posited here to influence perceptions and migration behavior (but see Hopkins 2010, 2011).

3

This analysis is not possible with recent American Community Survey data. Although dissimilarity scores for each of these groups can be estimated, most of the group-specific characteristics used in the analysis are unavailable. Table S2 in Online Resource 1 shows dissimilarity scores, by destination type, for the 10 groups from in 2005–2009, generally showing the same patterns as seen in 2000, although the levels are in some cases modestly different. I estimated models that regress 2000–2009 change in dissimilarity on 2000 group-level and metropolitan-level variables. These models yielded substantively similar results, showing that net of group and metropolitan characteristics, immigrant dissimilarity from native whites increased significantly more rapidly in new (b = 1.25, SE = .49) and minor (b = 2.35, SE = .50) destinations than in established areas.

4

In addition to including a relatively small (albeit growing) share of U.S. immigrants, smaller metropolitan and nonmetropolitan areas have too few tracts to capture residential spatial patterns. Lichter et al. (2010) bypassed this issue by using block data, a level of geographic detail not possible here because of suppression of place-of-birth data at that more-refined level. Research has shown, however, that although levels of segregation tend to be higher at lower geographic levels, metropolitan estimates based on tracts, block groups, and blocks are highly correlated (Iceland and Steinmetz 2003).

5

These groups are not necessarily representative of all American immigrants, but they are a broad cross-section of the foreign-born population, constituting 56 % of all immigrants in 2000 and making up 77 % of all foreign-born growth between 1990 and 2000.

6

Data for 1980 to 2000 come from county-level summary files of decennial censuses. Because the 1970 summary tables do not include information on eight of the groups (all but Chinese and Mexican immigrants), the 1970 Public Use Microdata Sample (PUMS) was used to generate group populations in each of the top 100 metropolitan areas. This procedure presumably produces estimates more prone to sampling error; however, for Chinese and Mexican immigrants, the correlation between this PUMS–based approach and the summary-table approach is very high (r = .98), and both methods produce the same set of destination types.

7

In supplemental analysis, I tested several alternative destination-type operationalizations that either increased or decreased the stringency of being an established or new destination, including group-size restrictions and relaxing/increasing the extent to which population shares or growth exceed metropolitan averages. Although the size of the destination-type effects varies slightly depending on the approach used, the general interpretation is consistent and the magnitude of the coefficients shown here approximates the midpoint of all considered specifications.

8

Census 2000 does not tabulate income or housing tenure by country of birth. To circumvent this issue, I draw on metropolitan-level ethnic-group data (from Summary File 4). These data are imperfect because the subpopulations represent those identifying with specific ethnic groups on race, Hispanic origin, or (for Jamaicans and Haitians) ancestry questions, and thus include both the U.S.-born and foreign-born. What is essential is that these variables capture the variability in demographic, economic, and acculturation characteristics across immigrant groups and metropolitan areas. Correlation analyses suggest that they do: at the national level, the ethnic-origin data used here is strongly related to estimates specific only to immigrant-group members (white income parity, r = .99; homeowners, r = .98). Nevertheless, the percentage of each ethnic group that is foreign-born is included as an additional control.

9

Supplemental models explored the use of a destination typology based on the total immigrant population (i.e., “place-based”) rather than the group-based one employed here. When included alone or alongside the group-based typology, there were no significant differences between place-based established and non-established destinations, and this variable’s inclusion does not alter the statistical or substantive interpretation of the group-based destination-type coefficients. The interactions between the group-placed and place-based dummy variables do, however, indicate a somewhat heightened impact of being a new group in a non-established place, but these models also exhibit major signs of collinearity and instability, and are thus not shown. Complete results are available on request.

10

In additional analyses, I considered occupational concentration in four other sectors of labor markets: health, sales, construction, and government. The coefficients on each of these in the full model were small and nonsignificant.

11

Although these measures can take values anywhere between 0 and 100, their truncated range makes a linear model technically inappropriate. However, residual plots reveals no major violations of regression assumptions due to truncation, and skewness/kurtosis statistics suggest that the D values approximate a normal distribution (s = 0.31, k = 2.78).

12

Fixed-effects models that account for metropolitan characteristics that do not vary across groups produce results that are substantively similar to those presented here. The coefficients for new destinations (b = 2.44; SE = 0.93) and minor destinations (b = 4.77; SE = 0.95) under the fixed-effects approach are nearly identical to those shown in Table 3.

13

The substantive interpretation of the unweighted and weighted models is similar. In the full regression model with weights, the new destination coefficient is smaller than that in the unweighted models but remains positive and significant (b = 1.57; SE = 0.78); the coefficient for minor destinations is larger in the weighted results (b = 5.87; SE = 0.97) than the unweighted ones.

14

One possible explanation for the higher levels of segregation in minor destinations is increased sampling error associated with the calculation of D for small groups. However, even when metropolitan areas with fewer than 5,000 group members are excluded, segregation in minor destinations remains higher than in established and new destinations.

15

Modifying recent arrivals to include immigrants who entered the country between 1990 and 1994 does not change the interpretation of the results (arrived 1990–2000, Model 2: b = 0.14, SE = 0.05; Model 3: b = 0.09, SE = 0.04).

16

Substituting a measure of a group’s family does not alter the interpretation of the results (family income, in $1,000s, Model 2: b = 0.04, SE = 0.06; Model 3: b = 0.02, SE = 0.04).

17

The suppression of the new destinations coefficient between Models 2 and 3 is due mostly to the positive effect of metropolitan population size on segregation. The zero-order correlation between the two variables is r = −.21.

18

When entered separately, both coefficients are significantly negative (percentage immigrant b = −0.21; SE = .04; top 5 gateway b = −1.69; SE = 1.29). Importantly, their inclusion does not alter the results of the group-specific destination-types in any meaningful way. With both excluded from the analysis, segregation in new (b = 2.53; SE = 1.05) and minor (b = 5.21; SE = 1.01) destinations remains significantly higher than in established areas.

19

Setting Mexicans as the referent in these models indicates that their adjusted level of segregation from native whites is significantly lower than all groups except Koreans (b = 3.12; SE = 2.82) and Chinese (b = 4.67; SE = 2.64).

20

Results generated partially from a forward-stepwise approach lead to similar conclusions.

21

Differences in the effect of income parity are statistically significant (at p < .05) between Mexican immigrants and all others but Vietnamese immigrants, and between Vietnamese and both Korean and Indian immigrants.

22

Differences in the effects of destination type (both new and minor destinations) are significant only between Chinese immigrants and all other groups.

23

In supplemental analyses, I explored models that pool Jamaicans and Haitians and estimate the reduced set of variables in Table 4 on dissimilarity from native whites. The results show that these groups are no more nor less segregated from native whites in new destinations (b = .82, SE = 3.12) yet more segregated in minor areas, although not significantly (b = 1.78, SE = 2.63), than in established areas. However, the small N of 53, even when these groups are pooled, may contribute to model instability; thus, I do not present these estimates.

24

Supplemental models for Koreans reveal the importance of metropolitan black and retirement populations, both of which significantly increase segregation.

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