Centro Journal ISSN: 1538-6279 centro-journal@hunter.cuny.edu The City University of New York Estados Unidos Vélez, William; Martin, Michael E.; Mendez, Edgar Segregation Patterns in Metro Areas: Latinos and African Americans in 2000 Centro Journal, vol. XXI, núm. 1, 2009, pp. 119-137 The City University of New York New York, Estados Unidos Available in: http://www.redalyc.org/articulo.oa?id=37721248006 How to cite Complete issue More information about this article Journal's homepage in redalyc.org Scientific Information System Network of Scientific Journals from Latin America, the Caribbean, Spain and Portugal Non-profit academic project, developed under the open access initiative
Seg La A
Massive Latino immigration and changes in the American economy are affecting the nature of residential segregation of Latinos in the United States. Historically, residential segregation of immigrants has been viewed as a system of voluntary social and economic isolation in inner-city residential neighborhoods. As the second and third generations experience socioeconomic mobility, there is geographical dispersion and movement into the mainstream (Park 1926: Lieberson 1980). This model has been found to work best for immigrant groups who have European origins, but has been inadequate when dealing with the unique problem of racial exclusion faced by African Americans and Latinos of African origin (Myrdal 1944; Jackson 1985; Massey and Denton 1993). Although there is no generally accepted theory of Latino residential segregation, it has generally been compared to the spatial assimilation model and is not seen as related to structural inequalities (Massey and Denton 1987). Massive increases in Latino immigration and the restructuring and globalization of the American economy confound traditional explanations and justify the need to develop a residential segregation theory that relates specifically to Latinos and Latino subgroups. Residential segregation plays a crucial role in perpetuating urban poverty and racial injustice in the United States (Massey and Denton 1993). Residential segregation has been linked to a host of social ills, including increased health risks factors, educational disadvantages, concentrated urban poverty, economic disinvestments, crime, social disorder, and housing inequalities (Settles 1996; Kasarda 1993; Massey and Denton 1993; Brookings Institute 2001). Racial segregation is also an important factor in the development of urban ghettos, barrios, and slums (Jargowsky 1997). There is strong evidence that immigration patterns and economic restructuring are producing structural patterns of residential segregation for Latinos (Suro and Tafoya 2004). This paper addresses the central issue of whether the residential segregation of Latinos, Latino subgroups, and African Americans in 2000 is consistent with the spatial assimilation model or with the place stratification model. This paper tests the adequacy of the spatial assimilation model (Charles 2003) in explaining Latino and African-American residential segregation. We divide the model s predictors into two categories: human capital/acculturation and group incorporation. The model assumes Latino and Black segregation will decline as [ 120 ]
their socioeconomic characteristics improve. In other words, as Latinos acquire more education, earn higher incomes, increase their rates of homeownership, and move to the suburbs, they will become less residentially isolated from Anglos. Assimilation is also related to the increasing presence of second- and thirdgeneration Latinos, so that as the proportion of foreign-born immigrants declines, residential isolation also decreases. Group incorporation variables are based on measuring the relative disadvantage faced by Latinos (and African Americans) vis-a-vis Anglos in different metropolitan areas. Rather than looking at straight measures of socioeconomic well-being, we argue that because of distant and recent historical developments in specific labor and housing markets, Latinos have fallen behind Anglos in disproportionately high levels. For example, different levels of documented workers and different mixes of industries might make opportunities for advancement more available in the Southeast than the Northeast (Courtney-Smith 2008). It is the proportional intensity of structural inequalities embedded in specific metropolitan areas that explains Latino/Anglo segregation. For example, it is the ratio of Latino median household incomes relative to those of Anglo households that is a better measure of structural inequality than using the variation of Latino median incomes across metropolitan areas to measure their relative economic standing. Similarly, differential wage levels vis-a-vis Whites also reflect the level of group incorporation across metropolitan areas. We also test the adequacy of the place stratification model by calculating the effects of discrimination in the home mortgage market on the residential segregation of Blacks and Latinos. Historical Background of Latino Settlements Like the Southern-Eastern-Central (SEC) European immigrants (1880 1910), and African-American migrants (1910 1970), many Latinos are coming to different metropolitan areas in the United States to find work. The employment opportunities for all these immigrant and migrant groups have traditionally been confined to unskilled and semiskilled jobs (Warner 1972; Lieberson 1980). European immigrants used manufacturing employment to get a foothold in the economy and move up the economic ladder, thus offering themselves and future generations economic and spatial mobility. Structural barriers and racism in the housing and employment markets prevented African Americans from obtaining the same opportunities as SEC Europeans, thus limiting economic and spatial mobility (Lieberson 1980). Although Latinos have a history of unequal treatment and racism, the nature of structural inequality facing Latinos is fundamentally different from what earlier European immigrants experienced. Latinos have a long history of being occupationally niched into low-wage, flexible-type labor (Sánchez-Korrol 1983; Suro 1998). The U.S. federal government sponsored a contract labor program, known as the Bracero Program, that brought flexible, low-wage workers, primarily from Mexico, into the United States between 1942 and 1964. The number of Latinos allowed into the United States was strictly regulated by the demand for low-wage agricultural, manufacturing, and railroad labor. When demand was high, more Latinos were allowed in to the country; when demand shrunk, Latinos were deported. All together, 4.5 million Latinos participated in the Bracero Program and were employed mainly in the Southwest and California, but also as far away as [ 121 ]
Michigan and Ohio. The Bracero Program gave many Latinos an opportunity to gain a degree of familiarity with the United States (Suro 1998). In addition to a history of exploitation in the secondary labor market, Latinos have been negatively affected by economic restructuring. The globalization and deindustrialization of the United States economy has eliminated millions of low-skilled, high-wage jobs replacing them with low-skill, low-wage servicesector jobs (Carruthers and Babb 2000). These new low-skill, low-wage service jobs represent a new, segmented labor market for immigrants that often acts as an occupational mobility trap (Ortiz 1996). Segmented low-skill, low-wage labor has helped keep per capita average income for Latinos below per capita average income for Blacks in New York and Los Angeles. This has accounted for the fact that increases in median household income between 1990 and 2000 are lower for Latinos than Blacks and Whites for all metropolitan areas (Lewis Mumford Center 2002). This is because wages are rising faster at the high ends of the labor market as the demand for these workers is exceeding supply, while the reverse is happening at the low ends of the labor market. Latinos are hurt by collapsing demand for less educated workers, especially in manufacturing. During the 1990s the restructuring of food processing industries fueled Latino growth in nonmetropolitan areas in the South and the Midwest, while increasing numbers of Latinos moved to Orlando to work in the tourist and service industry (Vásquez, Seales, and Friedmann-Marquardt 2008). The globalization and deindustrialization of the United States economy has eliminated millions of low-skilled, high-wage jobs replacing them with low-skill, low-wage servicesector jobs. The timing of America s deindustrialization had an exceptionally negative effect on Latinos. The 1970s were the beginning of market globalization in the manufacturing industry and the start of segmentation of immigrant labor for industries that stayed in the United States (Lamphere, Stepick, and Grenier 1994). The 1970s were also the first full decade after the passage of the Immigration and Nationality Act, which eliminated the European bias in immigration laws. The Immigration and Nationality Act of 1964 started the beginning of the current Latino migration wave, and changed the demographic make-up of America and its work force. While many Latino immigrants, especially Mexicans, used to settle in rural areas, in more recent decades Latino immigrants and migrants are moving overwhelmingly to urban areas. Between the years 1995 and 2000 about 3 million Latinos came to the United States from abroad (Saenz 2004). This immigration [ 122 ]
wave is particularly important to the discussion of residential segregation given the history of residential segregation of the previous two large immigrant and migrant waves (SEC Europeans and African Americans). In addition to dealing with low levels of availability and higher housing cost burdens in places like New York City and Los Angeles, Latinos also face higher levels of overcrowding than whites (Diaz McConnell, 2008). High levels of immigration are associated with the declining quality of Latino neighborhoods between 1990 and 2000 and higher levels of ethnic isolation, when compared to non-hispanic whites (Lewis Mumford Center, 2002). Every metropolitan area in the United States experienced an increase in Latinos between 1990 2000 (Lewis Mumford Center 2002). Currently, 90.9 percent of all Latinos live in metropolitan areas within the United States. Of the 32.1 million Latinos who live in metropolitan areas, 9.1 million (28.3 percent) live in metropolitan areas where they experience high levels of segregation (Lewis Mumford Center 2002). This represents an increase of more than 250 percent since 1980. The Spatial Assimilation Model The vast majority of the academic literature concerning residential segregation has dealt with two models: (1) the spatial assimilation model, and (2) the place stratification model (Charles 2003). The spatial assimilation model was developed in response to the phenomenon of immigrants spatially concentrating into residential enclaves during an initial period that usually includes the first two generations, followed by a process of spatial mobility due to acculturation and entrance into the economic mainstream (Park 1926). Traditionally, newly arriving migrants and immigrants have settled in declining neighborhoods near their workplace. Migrants and immigrants choose declining neighborhoods because of economic factors, mainly the lower cost of housing and transportation (Warner 1972). The spatial and social isolation of these neighborhoods provides economic opportunity and shelter from the dominant culture, but also provide an opportunity for exploitation by fellow ethnics (Portes and Stepick 1993). The level of segregation within the inner-city enclaves intensifies in proportion to the size of the immigrant group (Lieberson 1980). Gradually, migrants and immigrants become acculturated to the dominant society and start the process of entering mainstream culture and economy. Second- and third-generation immigrants become more comfortable with the dominant culture, speak the language, and become integrated into the economy and the community. Although some SEC European immigrants did experience unequal treatment in housing opportunities outside of the enclave and in society, initial SEC European segregation was mostly a function of cultural dissimilarity, population size, and socioeconomic status, not of structural inequality or intentional discrimination (Lieberson 1980). The process of acculturation and subsequent increased socioeconomic status reduced social and spatial isolation of the ethnic enclave and increases residential mobility (Lieberson 1980; Massey and Denton 1993). The spatial assimilation model was developed based on the experiences of European immigrants. Current immigration trends are different, however. More recently, immigrants are bypassing cities altogether to settle in both innerring and outer-ring ring suburbs (Vásquez, Seales, and Friedmann-Marquardt 2008). This trend might place a dampening effect on the predictive power of the spatial assimilation model. For example, Anglos might feel threatened by the rapid influx of minority groups and react with greater discrimination against the latter, [ 123 ]
thus negating the effects of household prosperity on residential improvement. However, a study of neighborhood integration in five large metropolitan areas concluded that the effects of spatial assimilation variables (including suburban residence) on Latinos were consistent between 1980 and 1990 (Alba, Logan, and Stults 2000). It can be argued that the spatial assimilation model is limited to measuring the impact of human capital variables on socioeconomic outcomes like neighborhood location. The model in fact ignores how racialized an ethnic group might be in a specific location. In other words, the returns to education or income for an ethnic group might be lower if for some historical reason it has been treated disproportionately worse by the dominant group or has experienced a very negative event or process in a specific area. For example, Puerto Ricans in New York City experienced high levels of arson and urban renewal in the 1960s and 1970s; these events displaced them from their thriving barrios with consequent negative effects (Suro 1998). That is why we have chosen to augment the spatial assimilation model by including group-incorporation variables. The group incorporation variables predict a decline in segregation scores as African Americans and Latinos approach parity or close the gap with Anglos in suburbanization levels, household income, and housing equity. They capture how successful a particular racial/ethnic group has been in competing against Anglos in a metropolitan area. It is important to remember that this study is focused on testing models at the metropolitan level, while previous studies have usually looked at intra-metropolitan samples. For example, Alba, Logan, and Stults (2000) selected neighborhoods in Chicago, Los Angeles, Miami, New York, and San Francisco to test their locationalattainment models. The advantage of using metropolitan areas as the unit of analysis is that it allows us to test different models while capturing a bigger proportion of the populations under study. Place Stratification Model The place stratification model focuses on the structural obstacles that have reinforced abnormally high levels of racial segregation for African Americans. It argues that historical institutional racism in housing markets favored dominant culture and segregated Blacks in order to maintain Anglo neighborhood homogeneity. Added to historical racism, current structural obstacles keep Black incomes and housing values lower than Anglos and prevent Blacks from getting equal housing equity and moving to more lucrative housing values in suburban areas. In other words, racism created Black residential segregation, and current systems of inequality maintain residential segregation. Historically, institutional practices severely limited where Blacks could live. Racism in the form of exclusionary zoning, racially restrictive covenants, blockbusting, and unfair lending practices legally denied Blacks the opportunity to live in desirable neighborhoods or outside traditionally Black areas (Squires 1994). In addition, government housing programs often aided segregation by redlining Black homeowners and central city areas, and local governments often used redevelopment as a way to buffer White neighborhoods from Black neighborhoods (Hays 1985). Fair Housing Laws, enacted since 1968, have made institutional racism in housing markets illegal, but the legacy of institutional racism is that Black neighborhoods are in parts of the city with the least potential for housing equity, a situation that has severely limited Black families from gaining wealth through homeownership. [ 124 ]
Like housing markets, employment has a history of institutional racism. After World War I, Blacks from the Deep South began moving to Northern cities for jobs in manufacturing and the service sectors. The jobs filled by Blacks in Northern industrial cities were those at the bottom of the labor queue and offered little or no opportunity for advancement. Racism in the form of prejudicial hiring practices, occupational segregation, lack of unionization, and unequal salaries created structural barriers to entry into the labor market and limited the earning power of Blacks compared to Anglos. Income inequality limited housing options for Blacks and assisted in segregating Blacks within lower income communities. After the passage of the Civil Rights Act of 1964, many institutional racist employment practices were made illegal, but Blacks still face institutional barriers to equal wages. Deindustrialization has eliminated many of the high-wage, low-skill jobs held by Blacks, and economic restructuring replaced those high-wage manufacturing jobs with low-wage service sector jobs. Income inequality has created a structural obstacle for Blacks trying to purchase homes outside of the Black community and has reinforced current levels of segregation. There is ample evidence that Latinos, like Blacks, were victims of institutional practices that limited where they could live. Blacks have faced structural problems in their opportunities to purchase homes in the suburbs and outside of Black communities. Traditionally, SEC Europeans were able to gain equity in the housing market and to purchase more expensive housing in suburban areas, where schools are better, housing values increase more quickly, and are in general seen as more desirable than areas in the traditional inner-city enclave. Unequal housing values have limited the ability for Blacks to purchase more expensive housing in suburban areas and have limited Black spatial mobility. Limited spatial mobility had a two-prong effect. First, unequal housing values reinforced Black segregation because Blacks faced structural problems in moving beyond their first home or starter home. Second, it limited the options of the few Blacks who were able to suburbanize. Suburban areas are not all the same. Traditionally, inner-ring suburbs are less desirable and are less expensive than outer-ring suburbs. Unequal housing values have forced Blacks to move to innerring suburbs. This has reinforced residential segregation because those Blacks who could suburbanize were limited to the same suburbs, and those suburbs were often contiguous to the traditional Black neighborhoods. For the purposes of this paper, blatant racism in housing markets will be tested by analyzing the effects of mortgage loan denial rates on the residential segregation rates experienced by Blacks and Latinos. We assume blatant racism still exists for Blacks and Latinos in housing and labor markets; and that conditions existing before the Fair Housing Act and Civil Rights Act still affect minority residential segregation (Diaz 2005; Friedman and Squires 2005). [ 125 ]
There is ample evidence that Latinos, like Blacks, were victims of institutional practices that limited where they could live. Issues of historical importance to Latinos include legal segregation of Mexicans in Texas (Montejano 1987), de facto segregation of migrant farm workers in railroad colonies (Valdes 2000), and blatant housing discrimination in urban barrios (Sánchez Korrol 1983). Recent studies continue to show high levels of inequality in the United States for Latinos and recent immigrants. Puerto Ricans in New York still experience many structural barriers in that housing market (Rosenbaum 1992), and Mexicans in Chicago are often victims of racist and illegal real estate practices (Betancur 1996). California has denied government resources to legal immigrants during the immigration boom in the 1990s (Suro 1998). A study sponsored by the U.S. Department of Housing in 2000 concluded that about a quarter of all real estate encounters for Latinos seeking a rental unit will involve discriminatory behavior, and that discrimination against Latino renters had remained essentially unchanged since 1989 (Austin-Turner, Ross, Galster, and Yinger 2002). And residential segregation leads to school segregation, so that in the academic year 2002 03 more than three-quarters (77 percent) of Latino students were attending majority minority schools (Orfield and Lee 2005). Thus, evidence of structural inequalities supports the notion that Latino residential segregation is based on more than just acculturation, demographics, and low economic status. The foundations of Latino residential segregation theory are closely linked to a series of papers published by Douglas Massey and colleagues, leading up to the publication of the groundbreaking work of racial residential segregation American Apartheid: Segregation and the Making of the Urban Underclass by Douglas Massey and Nancy Denton (1993). They were the first to do a comparative study of Mexican, Cuban, and Puerto Rican segregation. Their findings suggested Puerto Ricans were more segregated from Whites, and less segregated from Blacks than the other Latino groups (Massey and Denton 1989). In this and in another comparative study (Massey and Bitterman 1985), Massey and his co-authors attempted to explain the Puerto Rican disadvantage vis-a-vis other Latino groups to being poorer and blacker. But the argument for Puerto Ricans being darker than other Latinos has been questioned by other researchers (see Baker 2002). In looking at the more recent 1980 90 period, Jargowski (1997) concluded that neighborhood poverty among Latinos was explained more by income and income inequality than by residential segregation. But his study only included a relatively small number of metropolitan areas. We test the place stratification model by looking at the effects of the denial rate for conventional mortgage loans for Blacks and Latinos for the year 2004. Conventional loans offer the best interest rates and have lower costs (i.e, frontend fees) than loans obtained in the so-called subprime market (Apgar and Calder 2005). Recent research has unveiled the development of a dual market structure where minorities, even those having higher incomes, have lower access to conventional prime loans than White borrowers (Joint Center for Housing Studies 2004). The geographical discriminatory practice of mortgage redlining has been linked to producing and maintaining the high levels of segregation that exist in most U.S. metropolitan areas (Friedman and Squires 2005; Bond and Williams 2007). And studies of the lending patterns of both prime and subprime lenders consistently establish the presence of high denial rates for minorities even after accounting for financial reasons like credit worthiness and employment history (Ross and Yinger 1999; Ezeala-Harrison and Glover 2008). Finally, it has already been established in [ 126 ]
the literature that increasing levels of lending to black homeowners contributes to neighborhood racial integration (Bond and Williams 2007). We considered but rejected the idea of using subprime loan levels (often called predatory lending ) for metropolitan areas because there is not a generally accepted definition of what constitutes a subprime loan at this time and also because a significant proportion of these loans are not reported to federal agencies (Squires 2004). A recent study of home loan denial rates found that Blacks were denied home loans more frequently than Whites by both prime and subprime lenders (Ezeala-Harrison and Glover 2008). In comparing the effects of conventional loans and subprime lending on residential segregation, Bond and Williams (2007) concluded that only increases in traditional lending to black homebuyers decreases black-white segregation. Sources of Data and Methodology Our study is based on geographical data from the 332 U.S. Census defined metropolitan areas or MSAs (U.S. Census 1990, 2000, 2002). Data were collected for four racial/ethnic categories: Blacks, Latinos and two Latino sub-groups (Mexican and Puerto Rican). We also collected data on Anglos (Whites) to create the Anglo-differential ratios (see below). Since MSAs with small racial/ethnic populations skew the data, population minimums were set at 5,000 for Latinos and Blacks, and 2,000 for Latino subgroups. The decennial census offers the most in-depth survey of population, socioeconomic, and housing data available. The U.S. Census Department recognizes 16 different measures of segregation clustered into five key dimensions: evenness, exposure, concentration, centralization, and clustering. The vast majority of segregation studies have relied on one of these statistics, the Index of Dissimilarity (evenness). The Index of Dissimilarity or (D) score, is a measure of how evenly two groups are spatially distributed. Conceptually, the (D) score measures what percentage of a population would have to relocate, within a geographic unit, to achieve an even distribution. The dependent variable for this paper is the (D) score for the year 2000. The source of data for the dependent variable is the Lewis Mumford Center for Urban and Regional Research, which is based on the full-count PL-794 and SF1 files. The independent variables were obtained from the 2000 U.S. Census SF-4 files. The following formula was used to generate segregation scores. Scores were generated from U.S. Census data at the tract level: The example given here is for White/Black indices, but the same formulas may be used for all group combinations. The (D) scores were downloaded from the website: http://mumford1.dyndns.org/cen2000/data.html. For the purposes of this research work, all (D) scores will compare minority groups against Anglos. The authors will operationalize the spatial assimilation model by measuring the number and percentage of Latinos and Latino subgroups who are foreign born in each metropolitan area. We also include measures for median family income, college graduation rates, unemployment levels, and owner occupancy rates. [ 127 ]
According to the ethnic assimilation model, residential segregation from Anglos will decline as the income and educational levels of our targeted groups (Latinos, Blacks, Mexican Americans, and Puerto Ricans) increase. Similarly, increasing rates of homeownership will lead to decreases in housing segregation from Anglos. Also, rising unemployment rates and rising proportions of the foreign born in metropolitan areas will cause the dissimilarity scores to increase. The group incorporation variables predict a decline in segregation scores as the targeted groups approach parity or close the gap with Anglos in suburbanization levels, household income, and housing equity (as expressed in median housing values). The authors will regress (D) scores for Blacks, Latinos, and Latino subgroups to a subset of independent variables. These variables will be measured separately for each racial/ethnic group. In addition, a measure called the Anglo Differential (AD) will be determined for all four racial/ethnic groups. The AD is a ratio of a specific independent variable for Latinos compared to Anglos. For example, a metropolitan area with a median household income for Latinos of $30,000, and for Anglos at $40,000, would have a household income AD of.750 or $30,000/$40,000. The AD will measure disparities between Latinos and Anglos and will highlight possible structural issues in racial/ethnic residential segregation. Data for Latinos and Blacks will incorporate (D) scores from 1990 2000 and for Latino subgroups for 1990 and 2000 to present changes over time. Only the data on (D) scores for 2000 will be used in the multivariate analyses. We operationalize the place stratification model by including the denial rate for conventional mortgage loans for Blacks and Latinos for the year 2004. The data on loans were provided by the Federal Financial Institutions Examination Council as part of the Home Mortgage Disclosure Act. Unfortunately, HMDA data does not break down Latino applicants into national origin groups, so we can only test the full model on Blacks and Latinos. Our analyses also call for controlling for the effects of demographic trends amongst Latinos and African Americans; these effects include population size, percent of the population, and population growth. Previous studies suggest that a groups size and sudden and large increases in immigration can disrupt housing markets and cause temporary rises in housing segregation (Lieberson 1980). The variables for the overall regression model were: 1. Number of Persons in 2000; 2. Percent of Persons in 2000; 3. Percentage Growth 1990 2000; 4. Percent Foreign Born in 2000; 5. Suburbanization AD in 2000; 6. Median Household Income; 7. Household Income AD in 2000; 8. College Graduation Rate; 9. House Value AD in 2000; 10. Owner Occupancy Rate; 11. Unemployment Rate; 12. HMDA Loan Denial Rate; and 13. HMDA Loan Denial Rate AD. RESULTS (D) Score Analysis Our analysis shows that Latinos were segregated from Anglos at a moderate rate (Weighted Mean (D) Score=51.7). 1 Of the 234 metropolitan areas used in this survey, 19 were highly segregated, with a (D) score of above 60.0. In those highly segregated metropolitan areas 9,282,757 Latinos reside (28 percent of all Latinos in SMSAs). Latino segregation has increased between 1990 and 2000. The weighted mean (D) increased by 0.8 points between 1990 and 2000. In addition, the number of highly segregated metropolitan areas (those with a (D) score of.60 or higher) increased [ 128 ]
TABLE 1: Weighted Mean (D) Scores by Racial/Ethnic Group in Metropolitan Areas (D) Score 1990 2000 Latino/Anglo (N=234) Black/Anglo (N=254) 50.9 69.0 51.7 65.0 Mexican/Anglo (N=235) Puerto Rican/Anglo (N=129) 51.6 62.2 53.2 57.3 Gap between Black/Anglo and Latino/Anglo (D) scores 18.1 13.3 Latinos and Blacks: Metropolitan Areas with More Than 5,000. Mexicans and Puerto Ricans: Metropolitan Areas with More Than 2,000. by 4 from 15 to 19. Lastly, the number of Latinos living in a highly segregated metropolitan area increased from 6,804,251 in 1990 to 9,282,757 in 2000. Latino increases in segregation compare with Black decreases in segregation. The weighted mean (D) score for Blacks was 69.0 in 1990 and decreased by 4.0 points to 65.0 in 2000. Although Blacks remain more segregated than Latinos, the difference in their weighted mean (D) scores decreased from 18.1 points to 13.1. When analyzing Latino subgroups, Puerto Ricans are more segregated than Mexicans, but Puerto Rican segregation is decreasing and Mexican segregation is increasing. The Puerto Rican segregation rate in 2000 is 57.3. This is a 4.9 point decrease from the (D) score of 62.2 in 1990. The Mexican segregation rate in 2000 is 53.2. This is a 1.6 point increase from the (D) score of 51.6 in 1990. Testing the Spatial Assimilation Model-Mexicans and Puerto Ricans The results for the Mexican-origin population reveal that the following predictors explain segregation from Anglos: Suburbanization AD in 2000; Percent Foreign Born in 2000; Median Household Income; Household Income AD in 2000; and House Value AD in 2000. Metropolitan areas with a larger proportion of foreign-born Mexicans experience higher levels of residential segregation. In areas where the Mexican-origin population has incomes and home values that are similar to those of Anglos, segregation is lower. Similarly, in areas where Mexicans and Anglos enjoy similar levels of suburbanization, the segregation scores trend lower. One unexpected finding is that higher Mexican incomes lead to increasing levels of segregation. This finding contradicts the spatial assimilation model. Thus, three group incorporation predictors support the spatial assimilation model, while one human capital/acculturation variable supported the model and another contradicted it. These findings suggest that for Mexicans achieving socioeconomic parity with Anglos is a crucial requirement for attaining residential integration with the dominant group. For Puerto Ricans the significant predictors of segregation are Number of Persons in 2000, Suburbanization AD in 2000, Household Income AD in 2000, and House Value AD in 2000. The results of the multivariate analysis suggest metropolitan areas where Puerto Ricans and Anglos have similar levels of suburbanization experienced significantly lower levels of segregation. As the number of Puerto Ricans goes up, their segregation from Anglos also increases. The results for income show that as the gap in the household income distribution between Puerto Ricans [ 129 ]
TABLE 2: Means and Standard Deviations of Independent Variables Independent Variables Number of Persons in 2000 in thousands Percent of Persons in 2000 Suburbanization AD in 2000 Percent - Foreign Born in 2000i Percentage Growth 1990 2000 Median Household Income in thousands Household Income AD in 2000 College Graduation Rate Unemployment Rate Owner Occupancy Rate House Value AD in 2000 HMDA Loan Denial Rate HMDA Loan Denial Rate AD Black N=255 118.417 243.937 13.6 10.6.522.266 4.6 6.6 29.7 24.0 33.238 7.014.722.092 17.230 6.020 10.266 3.528 53.043 7.804.691.127 24.0 5.2 1.783.407 Latino N=234 135.936 373.652 13.2 15.8.724.278 13.3 9.8 123.3 132.4 38.116 6.749.811.099 19.634 6.889 7.900 2.735 56.751 9.173.787.133 20.8 4.0 1.590.348 Mexican N=235 85.941 269.334 9.5 14.7.783.277 35.8 16.1 191.9 230.0 33.997 5.829.735.088 10.035 5.750 8.927 3.691 41.838 12.916.771.143 N.A. N.A. Puerto Rican N=129 26.245 81.159 2.2 2.5.692.296 37.2 9.5 75.0 51.3 34.257 9.546.684.167 16.481 9.679 9.298 3.759 41.871 13.080.823.155 N.A. N.A. Note: Numbers on top are means, and numbers in italics are standards deviations. i For Puerto Ricans, the FB percent relates to Puerto Ricans born on the island of Puerto Rico. Metropolitan Areas used in this model must have over 5,000 for Blacks and Latinos. Metropolitan Areas used in this model must have over 2,000 for Mexicans and Puerto Ricans. and Anglos closes, their residential segregation goes down. Similarly, as the gap in owner-occupied housing values between Anglos and Puerto Ricans narrows, their residential segregation declines. Only group incorporation variables supported the spatial assimilation model (Suburbanization AD in 2000, Household Income AD in 2000, and House Value AD in 2000). Full Regression Model-Blacks and Latinos The addition of two variables using HMDA data on conventional mortgage loans (HMDA Loan Denial Rate and HMDA Loan Denial Rate AD) allowed us to compare the relative explanatory power of the spatial assimilation model and the place stratification model in explaining the housing segregation of African Americans and Latinos (see Table 3). In looking at the spatial assimilation model, the results for Blacks show that seven variables have significant effects on housing segregation: Number of Persons in 2000, Percent of Persons in 2000, Percent Foreign Born in 2000, [ 130 ]
TABLE 3: Coefficients of Residential Segregation from Whites at Metropolitan Level Independent Variables Number of Persons in 2000 Percent of Persons in 2000 Suburbanization AD in 2000 Percent - Foreign Born in 2000i Percentage Growth 1990-2000 Median Household Income Household Income AD in 2000 College Graduation Rate Unemployment Rate Owner Occupancy Rate House Value AD in 2000 HMDA Loan Denial Rate HMDA Loan Denial Rate AD Constant Multiple Square R Adjusted Multiple Square R Black N=236 2.930*** (.473) -.179*** (.051) -4.128* (1.952).221** (.791) -0.728 (2.098) 0.065 (3.441) 60.420*** (9.143) -0.099 (.093) 0.621*** (.171) 0.117 (.074) -12.490* (5.240).145 (9.456) -0.906 (1.202) 87.119 0.867 0.752 Latino N=216 1.437** (.488) -.144*** (.0424) -3.205 (2.048).290*** (.752) 1.529*** (.320) 0.156 (3.574) -65.733*** (7.518) -0.346*** (.075) -0.052 (.231) 0.017 (.071) -12.332** (4.078) -.434 (11.014) 3.282* (1.494) 98.94 0.891 0.794 Mexican N=235 0.384 (.518) -.021 (.054) -4.467* (1.916).415*** (.522) -0.340 (.311) 11.318** (3.931) 34.272*** (7.064) -0.163 (.109) 0.131 (.144) 0.037 (.068) -21.002*** (4.590) N.A. N.A. 33.106 0.644 0.627 Puerto Rican N=129 2.563** (.768) -.166 (3.76) -13.749*** (3.075).054 (.808) -0.899 (1.415) -3.833 (4.659) -13.782 (7.486) -0.121 (.098) 0.138 (.265) @ -18.793*** (5.705) N.A. N.A. 87.067 0.756 0.736 Note: Numbers in parenthesis are standard errors. i For Puerto Ricans, the FB percent relates to Puerto Ricans born on the island of Puerto Rico. @ Variable is multi-collinear so it has been excluded from the regression model. * p<.05, **p<.01, ***p<.001 (two-tailed test). Metropolitan Areas used in this model must have over 5,000 for Blacks and Latinos & 2,000 for Mexicans & Puerto Ricans. Suburbanization AD in 2000, Household Income AD in 2000, House Value AD in 2000, and Unemployment Rate. Metropolitan areas with the largest population of African Americans experienced higher levels of segregation. In contrast, a proportionally larger Black population is linked to lower levels of isolation from Anglos, a counterintuitive finding that might be linked to political strength (see discussion on Latinos below). Metropolitan areas with proportionally more foreign-born Blacks experienced higher levels of segregation. The results also suggest that areas where Black incomes are closer to Anglo incomes have lower segregation scores. Similarly, where the values of homes owned by Blacks are similar to those owned by Anglos levels of segregation tend to be lower. Also, higher rates of unemployment among Blacks are linked to increasing [ 131 ]
segregation levels. Finally, the results of the multivariate analysis suggest that metropolitan areas where Blacks and Anglos have similar levels of suburbanization experienced significantly lower levels of segregation. While three of the group incorporation factors are significantly related to segregation in the expected direction (Household Income AD in 2000, Suburbanization AD in 2000, and House Value AD in 2000), two predictors linked to human capital/acculturation impacted segregation in the hypothesized direction (percent foreign born and unemployment rate). The importance of the place stratification model amongst Blacks is rejected as our findings fail to confirm that higher denial rates for conventional loans result in increasing segregation levels from Anglos. In testing the spatial assimilation model the following variables had significant effects on Latino residential segregation: Number of Persons in 2000, Percent of Persons in 2000, Percent Foreign Born in 2000, Household Income AD in 2000, House Value AD in 2000, Percentage Growth 1990 2000, and College Graduation Rate. These results suggest that areas where Latino incomes are closer to Anglo incomes have lower segregation scores. In addition, segregation increases in areas experiencing higher Latino population growth and in areas with higher proportions of foreign-born Latinos. Higher proportions of college-educated Latinos are associated with lower levels of Latino/Anglo segregation. In metropolitan areas where Latinos own homes closer in value to those of Anglos there are lower levels of residential segregation. The only counterintuitive finding is that higher proportions of Latinos are associated with declining segregation scores. Perhaps once you control for the size of the foreign born and population increases, a larger Latino composition reflects political strength or some similar factor that translates into lower isolation from Anglos. A similar argument can be used to explain why larger proportions of African Americans led to declines in neighborhood segregation. Our overall regression model indicates that two human capital/acculturation variables (percent foreign born and college graduation rate) were statistically significant, compared to two group incorporation variables (income and house value differentials). In addition, one of the group incorporation variables, Income Differential, had the largest effects on Latino residential segregation. The place stratification model is also important in explaining housing segregation amongst Latinos. In areas where the loan denial rates for Latinos are similar or lower than those experienced by Anglos, their segregation scores are lower. Put differently, as Latino denial rates exceed Anglo denial rates, their housing segregation increases. 2 TABLE 4: Comparing Explanatory Strength of Three Types of Predictors Across Ethnic/Racial Groups Ethnic Group # Variables Support Human Capital/Group Composition 1 0 2 2 # Variables Support Local Incorporation # Variables Support Place Stratification Model N.A. N.A. 0 1 Mexicans Puerto Ricans African Americans Latinos 3 3 3 2 [ 132 ]
Summary and Conclusions Puerto Ricans are the most segregated Latino ethnic group with Anglos, while Mexicans were the least segregated. Between 1990 2000 segregation scores for Puerto Ricans declined, while those of Mexicans increased. This finding suggests that aggregating Latino subgroups obscures important distinctions in the residential experiences of these ethnic groups. Indeed, segregation of Mexicans and Puerto Ricans is greater than Latinos, which means that other Latino subgroups are less segregated from Anglos. Blacks have the highest segregation, but the gap between Blacks and Latinos (in relation to their segregation from Anglos) is declining over time. The results of the multivariate analysis suggest metropolitan areas with the largest number of Puerto Ricans and Blacks experienced significantly high levels of segregation, as the population size of these groups (and percentage growth for Latinos) was positively related to increases in residential segregation from Anglos. This finding indicates that high-growth Latino metropolitan areas and Latino hub areas like Los Angeles and Chicago experience high levels of residential segregation. This finding suggests that aggregating Latino subgroups obscures important distinctions in the residential experiences of these ethnic groups. As expected, an increasing equality in suburbanization rates between Mexicans and Anglos, and between Puerto Ricans and Anglos, was associated with declining levels of residential segregation. This finding supports the spatial assimilation model and its emphasis on the workings of institutional barriers to group incorporation operating in specific metropolitan markets. A look at socioeconomic indicators shows that as the Latino-Anglo income differential is reduced, residential segregation declines. This was true for the disaggregated Latino groups and African-Americans also. Similarly, as the proportion of Latinos (which included Cubans, Central, and South Americans) with a college degree increases, their residential segregation goes down. This finding was not significant for Puerto Ricans or for Mexicans, highlighting the importance of specifying Latino subgroups when testing sociological models. The spatial assimilation model is also confirmed by the findings on percent foreign born among Latinos, Blacks, and Mexicans, which suggests that the presence of large numbers of immigrants increases residential isolation. This model is contradicted by the significant but negative results of income within the Mexican population, challenging the assumption that increasing economic resources leads to higher levels of residential integration. In testing the place stratification model we found that in metropolitan areas where the Latino denial rates exceed the Anglo denial rates, residential segregation [ 133 ]
increases. However, conventional loan denial rates for African Americans were not causally related to residential segregation. In comparing the impact of our two types of independent variables (within the spatial assimilation model) for explaining housing segregation, our results show that group incorporation best explains Puerto Rican segregation from Anglos at the metropolitan level. The results for Mexicans reflect a strong validation of the group incorporation approach, and mixed support for the human capital/acculturation variables. In overall terms, our findings suggest that the spatial assimilation model explains housing segregation reasonably well. For Latinos we found support for both the spatial assimilation and the place stratification models. The findings on loan denial rates suggest that for Latino borrowers, lack of access to mortgages plays a role in preventing neighborhood integration with Anglos. It is very likely that many rejected applicants ended up in the subprime loan market, causing them to pay higher fees and interest rates and suffer the increased likelihood of losing their homes to foreclosure (Apgar and Calder 2005). Given the recent re-structuring of the American economy, with its emphasis on a downgraded manufacturing sector, the opportunities for advancement available to immigrants today are not as plentiful as they were for immigrants from earlier periods. The very strong effects of income inequality on segregation suggests that the opportunity structures for Latinos and African Americans are more equitable in some metropolitan areas of the country and that perhaps some discriminatory processes are operating in other metropolitan areas. Given the recent re-structuring of the American economy, with its emphasis on a downgraded manufacturing sector, the opportunities for advancement available to immigrants today are not as plentiful as they were for immigrants from earlier periods. The situation is particularly bleak for Mexican Americans, who continue to experience high rates of immigration, and in areas like Los Angeles have relatively low levels of human capital (Ortiz 1996). The road to residential integration for Latinos appears to be based on increasing their number of college-educated workers, and closing the income gap between them and the majority Anglo population. And our findings also suggest, that at least for Latinos, ensuring equal access to mortgage credit must remain as a crucial public policy if we are to pursue neighborhood integration as a societal goal. [ 134 ]
notes 1 The (D) score for univariate analyses is weighted to account for the very large differences in Latino populations across the country. It assigns more importance to large metropolitan areas like Los Angeles when computing scores. The dependent variable in the regression equation is not weighted. 2 Although we only present the results for the full regression model, separate analyses not presented here suggest the addition of the place stratification variables increases the variance explained in a small but significant way. References Alba, Richard D, John Logan, and Brian J Stults. 2000. The Changing Neighborhood Contexts of the Immigrant Population. Social Forces 79: 587 621. Apgar, William and Allegra Calder. 2005. The Dual Mortgage Market: The Persistence of Discrimination in Mortgage Lending. In The Geography of Opportunity: Race and Housing Choice in Metropolitan America, ed. Xavier de Souza Briggs. 101 23. Washington, DC: The Brookings Institution. Austin Turner, Margery, Stephen L. Ross, George C. Galster, and John Yinger. 2002. Discrimination in Metropolitan Housing Markets: National Results from Phase I HDS 2000. Final Report. U.S. Department of Housing and Urban Development. Online. http://www.huduser.org/publications/pdf/phase1_report.pdf. Baker, Susan S. 2002. Understanding Mainland Puerto Rican Poverty. Philadelphia: Temple Unversity Press. Betancur, John. 1996. The Settlement Experience of Latinos in Chicago: Segregation, Speculation, and the Ecology Model. Social Forces 74: 1299 324. Bond, Carolyn and Richard Williams. 2007. Residential Segregation and the Transformation of Home Mortgage Lending. Social Forces 85: 671 98. Brookings Institute. 2001. The Segregation Tax : The Cost of Racial Segregation to Black Homeowners. Brookings Institution Survey Series 10: 1 14. Charles, Camille Zubrinski. 2003. The Dynamics of Racial Residential Segregation. Annual Review of Sociology 29: 167 207. Carruthers, Bruce G and Sarah L. Babb. 2000. Economy/Society: Markets, Meanings, and Social Structure. Thousand Oaks, CA: Pine Forge Press. Courtney-Smith, Robert. 2008. Latino Incorporation in the United States in Local and Transnational Contexts. In Latinas/os on the United States: Changing the Face of America, eds. Havidan Rodriguez, Rogelio Saenz and Cecilia Menjivar. 36 53. New York: Springer. Diaz, D. R. 2005. Barrio Urbanism: Chicanos, Planning, and American Cities. New York: Routledge. Diaz McConnell, Eileen. 2008. U.S. Latinos/as and the American Dream : Diverse Populations and Unique Challenges in Housing. In Latinas/os on the United States: Changing the Face of America, eds. Havidan Rodriguez, Rogelio Saenz, and Cecilia Menjivar. 87 100. New York: Springer. Ezeala-Harrison, Fidel and Glenda B. Glover. 2008. Determinants of Housing Loan Patterns Toward Minority Borrowers in Mississippi. Journal of Economic Issues 42: 75 96. Friedman, Samantha and Gregory D. Squires. 2005. Does the Community Reinvestment Act Help Minorities Access Traditionally Inaccessible Neighborhoods? Social Problems 52: 209 31. Hays, R. Allen. 1985. The Federal Government and Urban Housing: Ideology and Change in Urban Policy. Albany: SUNY Press. [ 135 ]