The Neighborhood Attainment of Mixed-Race Couples across the Black/White Spectrum

Abstract

With the removal of legal barriers to mixed-race marriage, there has been a consistent increase in the number of Black-White couples. This has coincided with growth in the number of Black-White individuals who have formed couples with a Black or White partner. Little is known, however, about how these couples function within a key area of stratification—neighborhood attainment. We use data from the Home Mortgage Disclosure Act and the U.S. Census to investigate the percentage of Whites and the average income in the neighborhoods of home-purchasing couples defined by their levels of Black and White representation. These couples being White couples, Black-White individuals with White partners, Black-White couples, Black-White individuals with Black partners, and Black couples. Findings reveal that the percentage of Whites and average income in the neighborhoods of couples decrease as couples increase in Black representation. These results have implications for our understanding of the contemporary color line.

Keywords

neighborhood attainment mixed-race couples stratification

Introduction

Scholars have long investigated the Black/White divide in neighborhood attainment in the United States (Fischer and Lowe 2015; Logan and Alba 1993; Massey, Gross, and Shibuya 1994; Pais, South, and Crowder 2012). This scholarship consistently finds that Blacks tend to reside in neighborhoods with lower shares of Whites and socioeconomic status than their White counterparts. These patterns of neighborhood attainment are associated with stark differences in exposure to deleterious environments. In particular, neighborhoods with lower shares of Whites and socioeconomic status are often marked by higher crime (Peterson and Krivo 2009), environmental pollution (Evans and Kantrowitz 2002), and limited employment opportunities (Mouw 2000). We have, however, begun to see meaningful changes in the demographic composition of the U.S. population that invites the exploration of the neighborhood attainment of emerging groups. In 2015, approximately 10 percent of all marriages were between individuals of different races and ethnicities (Livingston and Brown 2017). This is associated with an increasing number of Black-White couples forming in the United States where 11 percent of all mixed-race marriages in 2015 consisted of Black-White unions (Livingston and Brown 2017). The demographic increase in Black-White couples has coincided with growth in the number of Black-White multiracial individuals. In 2018, one in five multiracial individuals aged 18 and older were Black-White (Ruggles et al. 2020) and many of these individuals have formed couples with monoracial Blacks or Whites.

Due to the relatively recent growth in the number of mixed-race couples and individuals identifying as multiracial, we have yet to fully understand how the expanding population of Black-White couples and Black-White individuals who form couples with monoracial Blacks or Whites fit within the enduring racial order that has, for generations, advantaged Whites and disadvantaged Blacks in neighborhood attainment (Hall et al. 2017; Rothstein 2017; Rugh 2020). Up to this point, there has been relatively limited research on the neighborhood attainment of Black-White couples and no research on Black-White multiracial individuals who form couples with monoracial Blacks or Whites. The research that has been conducted on the neighborhood attainment of Black-White couples tends to observe that they occupy a middle position between their monoracial Black and White couple counterparts, indicating that the rigid racial order that has separated Blacks and Whites is partially flexible through the combined racial status of individuals within interracial unions (Gabriel 2018a; Wright, Ellis, and Holloway 2011; Wright, Holloway, and Ellis 2013).

As it relates to Black-White individuals with monoracial Black or White partners, assessing the neighborhood attainment of these couples allows us to gauge the flexibility of neighborhood attainment outcomes that potentially occurs for couples with multiracial individuals. The potential flexibility in the neighborhood attainment outcomes of couples with one Black-White individual might occur because these multiracial individuals possess a more varied set of exposures to differing neighborhoods throughout their life course relative to monoracial individuals. The increased variation in exposures to differing neighborhoods for Black-White individuals likely happens because they have kith and kin networks that reside in separate metropolitan neighborhoods due to historical patterns of residential segregation that have sharply delineated the social and spatial spheres of Blacks and Whites (Krivo et al. 2013). This pattern may lead Black-White individuals with monoracial Black or White partners to have increased knowledge of, and comfort with, a more varied set of neighborhoods defined by race and socioeconomic status than their monoracial couple counterparts.

Therefore, in this study, we assess the percentage of Whites and the average income in the neighborhoods of couples across a spectrum of increasing Black representation starting with Black-White individuals with monoracial White partners, followed by Black-White couples consisting of monoracial Black and monoracial White individuals, Black-White individuals with monoracial Black partners, and monoracial Black couples, with monoracial White couples serving as the reference group. To investigate the neighborhood attainment of these couples, we apply unique data from the Home Mortgage Disclosure Act (HMDA) Loan Application Register from 2005 to 2015 that catalogs every mortgaged home purchase in the United States during that period in combination with multiple population censuses. This analysis is facilitated by the considerable size of the HMDA data which provides, for the first time, the opportunity to not only assess the neighborhood attainment of couples across a spectrum of increasing Black representation throughout the United States, but to conceptualize, operationalize, and investigate Black representation in this way. Our analysis also evaluates the potential role of economic resources in explaining the variation in neighborhood attainment between these couples while accounting for the possible influence of theoretically derived household, contextual, and temporal characteristics. In sum, exploring the neighborhood attainment of these couples illustrates how a growing diverse population may help reshape U.S. neighborhoods (Clark, Andersson, and Malmberg 2018) and, in turn, aid in reshaping the racial order that has long separated Blacks and Whites.

Background and Theory

During the Jim Crow era, social taboos and legal proscriptions against Black-White couples were strongly embedded throughout American culture. The firm and often violent reaction to Black-White couples (Finnegan 2013) occurred because these unions were perceived as a threat to the racial order that situated Whites on top and Blacks at the bottom in all areas of American life (Emirbayer and Desmond 2015). In addition to the violent actions related to Black-White unions, Whites crafted the one-drop rule to fortify the bulwarks of the racial order, which decreed that an individual with any Black ancestry would be treated as Black (Perlmann and Waters 2002). The one-drop rule largely functioned as designed—it effectively disincentivized Black-White racial mixing and limited Black-White individuals’ access to the social, political, and economic benefits of Whiteness.

But, with a swell of legal actions against various racially discriminatory institutions (Patterson 2001), combined with energetic civil disobedience (Garrow 1986), the 1960s began to usher in greater legal structural equality between Blacks and Whites (Massey 2015). One of the many discriminatory statutes that was defeated during this period were laws banning mixed-race marriage. Although a majority of states had already removed legal proscriptions against mixed-race marriage, almost all of the states in the South persisted in blocking these unions during this decade. However, in 1967, the Supreme Court struck down legal barriers to interracial relationships, helping to spark the dramatic increase in contemporary racial and ethnic diversity (Lee and Bean 2010).

In response to these social and demographic changes, there has been a small but growing focus on the neighborhood attainment of mixed-race couples (Gabriel 2016, 2018a, 2018b; Holloway et al. 2005; Wright et al. 2011; Wright et al. 2013). This research tends to observe that Black-White couples are more integrated into Whiter and higher-income neighborhoods than their monoracial Black couple counterparts (Gabriel 2018b; Wright et al. 2011). Counter to the growing research on mixed-race couples, minimal research has been conducted on the neighborhood attainment of multiracial individuals (Bennett 2011). The lack of understanding of the neighborhood attainment of multiracial individuals is partly due to the limited number of publicly available datasets that allow respondents to identify themselves as more than one race (Bratter 2018). In a creative response to this limitation, some scholars have focused on multiracial children whose racial status can be determined through their parents’ combined racial status (Brunsma 2005; Qian 2004). However beneficial this approach, it has led to limited scholarship on how the growing population of adult multiracial individuals function in the housing market (Bratter 2018), specifically, Black-White individuals who have monoracial Black or White partners.

Of the limited research on multiracial individuals, scholars tend to find their neighborhood attainment differs from monoracial individuals in unique ways. For instance, William A. V. Clark et al. (2018) reveal that multiracial individuals in San Francisco and Los Angeles are likely to live in neighborhoods that are relatively racially and ethnically diverse and in areas that are, on average, considered higher socioeconomic status neighborhoods. William H. Frey and Dowell Myers (2002) find that Black-White individuals are more likely to live in neighborhoods that have greater percentages of Whites than their monoracial Black counterparts but fewer Whites than monoracial White individuals. Pamela Bennett (2011) corroborates these findings by observing that Black-White individuals experience lower levels of segregation—as measured by the index of dissimilarity—from Whites relative to Blacks. Nevertheless, the collective findings from these studies on the neighborhood location of multiracial individuals come from survey data that contain counts of multiracial children living with their mixed-race parents. Multiracial children, however, are not the primary decision makers in selecting where a family lives, so these prior studies provide a limited understanding of the neighborhood attainment of adult multiracial individuals. Therefore, what is needed to help ameliorate previous data limitations is to use a prospective approach that assesses the neighborhood selection of adult multiracial individuals and, in our case, adult Black-White individuals coupled with monoracial Black or White partners.

Another challenge with studying the neighborhood attainment of Black-White individuals with monoracial Black or White partners and Black-White couples is that the theoretical frameworks surrounding these populations are rather nascent. Because of that, we turn to established theories that have explicated the forces that have contributed to differential neighborhood attainment patterns for Blacks and Whites, which can provide an initial framework to understand the neighborhood attainment of Black-White individuals with Black or White partners and Black-White couples. Standing out among the collection of forces that have received considerable treatment in influencing racial residential stratification is the role of economic resources. Known as the spatial assimilation theory (Logan and Alba 1993), this perspective asserts that minority and majority groups convert increased economic resources across the life course into higher-status neighborhoods. For Black-White couples, there is some support for the spatial assimilation argument in recent studies of the topic. Steven R. Holloway et al. (2005) observe that high-income Black-White couples are more apt to reside in neighborhoods with higher concentrations of Whites. Similarly, Ryan Gabriel (2018b) finds that higher-income Black-White couples are likely to live in lower-poverty neighborhoods than their Black-White couple counterparts with fewer economic resources. For Black-White individuals with monoracial Black or White partners, however, no research has examined their ability to convert economic resources into neighborhoods with greater concentrations of Whites and higher average incomes. Thus, the spatial assimilation theory would predict that Black-White individuals with Black or White partners would purchase into neighborhoods with similar concentrations of Whites and socioeconomic status as White couples after controlling for economic resources.

We illustrate the spatial assimilation theory in Figure 1.¹ In this figure, the intercept of the majority group (b1), White couples, is higher than the intercept for the minority groups (b2), couples with Black representation. However, the slope representing the spatial assimilation of couples with Black representation (b2) is steeper than that of White couples (b1) where, at higher levels of economic resources, couples with Black representation purchase into similar neighborhoods as White couples.

Figure 1.

Hypothesized patterns of the spatial assimilation and place stratification (weak and strong) theories.

Historically, Blacks have encountered difficulty in converting economic resources into predominantly White and higher-income neighborhoods (Logan and Alba 1993; Pattillo 2005). This has prompted the place stratification theory, which argues that discrimination exerts sufficient force to hinder Blacks from spatially assimilating into higher-quality neighborhoods (Charles 2003). These discriminatory forces manifest in numerous ways such as racial steering by real estate agents (Turner et al. 2013) and predatory mortgage lending (Rugh, Albright, and Massey 2015). Some scholars assert that these, and other (Rothwell and Massey 2010), discriminatory forces coalesce to create persistent obstructions for Blacks in their attempt to reside in Whiter and higher-income neighborhoods, even among the economically advantaged.

Unlike the spatial assimilation theory, the place stratification theory predicts racial group differences in the effect of economic resources on the attainment of predominantly White and higher-income neighborhoods. As shown in Figure 1, the place stratification theory has two variants: the weak and the strong versions. First, the “weak version” of the place stratification theory argues that the influence of economic resources will be less pronounced for the majority group (b1), White couples, than for the minority groups (b3), couples with Black representation. However, even the highest-earning couples with Black representation are predicted to not purchase into neighborhoods that similarly resourced White couples are predicted to attain. Second, the “strong version” states that couples with Black representation are unable to convert their economic resources into higher-status neighborhoods, leading to economic resources having a more pronounced effect on the neighborhood attainment of White couples (b1) than for couples with Black representation (b4) (Logan and Alba 1993).

Although there has yet to be any research on the how the place stratification theory relates to Black-White individuals with Black or White partners, a small number of scholars have assessed how the place stratification theory relates to the neighborhood attainment of Black-White couples (Gabriel 2018b; Wright et al. 2013). In his analysis of the level of neighborhood poverty that Black-White couples migrate into, Gabriel (2018b) finds support for the weak version of the place stratification theory; hence, even the most affluent Black-White couples are more likely to migrate to higher-poverty neighborhoods than White couples with similar resources. Bennett (2011) finds Black-White individuals are more likely to reside in Whiter neighborhoods than Blacks. Based on this, and other prior findings that Blacks have encountered barriers to entering and remaining in predominantly White and higher-income neighborhoods (Crowder and South 2005), we might expect that Black-White individuals with Black partners are likely to purchase a home in more diverse and lower-income neighborhoods than White couples. Conversely, Black-White individuals with White partners, along with Black-White couples, might be endowed with a greater ability to purchase into predominantly White and higher-income neighborhoods because of the ascribed social advantages associated with the greater White representation within their couples.

Besides discrimination functioning as an obstacle to neighborhood attainment, racial differences in preferences for neighborhoods with specific racial compositions have been postulated as a salient force in racial residential stratification (Charles 2000). Past research studying the neighborhood racial composition preferences of Black-White couples has observed that these couples tend to report a desire for neighborhoods with meaningful levels of racial and ethnic diversity (Dalmage 2000). In her interviews with Black-White couples, Heather M. Dalmage (2000) finds a push factor that many of these couples purposely select neighborhoods with higher diversity to avoid the threat of discrimination toward themselves and their families. Alternately, Rachel F. Moran (2001) notes a pull factor toward diverse neighborhoods for Black-White couples that want to raise their children in areas that reflect their families’ diversity. If both of these push and pull factors are not only observed among Black-White couples, but among Black-White individuals with Black or White partners, we might expect that each of these types of couples will reside in more diverse neighborhoods than Whites, and that Black-White individuals with Black partners will purchase into neighborhoods that are more diverse than their counterparts with White partners.

In addition to the three traditional theories of neighborhood attainment discussed above, scholars have recently asserted that the processes of neighborhood attainment are likely influenced by disparate levels of neighborhood knowledge between racial groups (Krysan and Crowder 2017). Maria Krysan and Kyle Crowder (2017:52) argue with their theory, the social structural sorting perspective, that neighborhood decisions are influenced by “residential histories and daily activities (work, school, shopping, and so on) that provide individuals with direct exposure to specific neighborhoods and allow for the development of familiarity” with neighborhoods throughout their metropolitan areas. Because of the history of residential segregation between Blacks and Whites (Logan and Stults 2011), many operate in same-race social and spatial spheres (Krivo et al. 2013). For Black-White individuals, however, their exposure to a broader selection of neighborhoods throughout their metropolitan areas likely occurs because of having kith and kin located in separate racially segregated places. This may not only provide them a greater knowledge of these racially segregated places, but also facilitate greater comfort in neighborhoods of varying racial and socioeconomic status above and beyond their monoracial counterparts. Evidence for the ability of Black-White individuals to be comfortable in both Black and White social worlds has been observed in their friendship networks. Lincoln Quillian and Rozlyn Redd (2009) find that adolescent Black-White individuals are particularly likely to serve as a link between their monoracial heritage groups. Therefore, in the realm of neighborhood attainment, Black-White individuals with either Black or White partners could be particularly flexible in the neighborhoods they enter, potentially allowing the preferences of their monoracial partners to be accentuated in the selection of their neighborhoods.

Based on the aforementioned theoretical arguments, and as seen in Figure 2, we hypothesize that the greater the level of Black representation within a couple, the lower the percentage White and average income will be in the neighborhoods they purchase a home, even when economic resources are allowed to vary across the different types of couples.² Exploring these theoretical arguments, and the general hypothesis that stems from them, will provide the opportunity to assess how these racially diverse individuals and couples fit within contemporary patterns of racial stratification.

Figure 2.

Hypothesized patterns of the neighborhood attainment of Black-White individuals with Black or White partners, Black-White couples, and monoracial Black and White couples by economic resources.

Data and Method

The primary data source for our analysis are characteristics of homebuyers who obtained mortgage loans from 2005 to 2015. The data on mortgage loans are made available by the Federal Financial Institutions Examination Council (FFIEC) under the 1975 HMDA. We concatenated records on conventional purchase money loan originations for owner-occupied single-family unit properties from the 2005–2015 annual HMDA Loan Application Register data sets (FFIEC 2006, 2010, 2011, 2015). By law, HMDA data include information on the race and income of the borrower (and co-borrower), and the census tract of the mortgaged property.

We follow the precedent set by other researchers who have used HMDA data to study neighborhood attainment outcomes (Fischer 2013; Fischer and Lowe 2015) and exclude borrowers who are using loans to refinance an existing mortgage to better proxy for the decision to select a neighborhood. We also follow previous scholarship assessing neighborhood attainment by using census tracts to characterize neighborhoods (Pais et al. 2012). We address possible issues related with adjustments in census tract boundaries across censuses by using the Neighborhood Change Database (NCDB; GeoLytics 2013). The NCDB harmonizes 2000 and 2010 census tract data to 2010 census tract boundaries. We use linear interpolation to estimate values for all census tract and metropolitan characteristics in non-census years.

Since 2004, the HMDA data have included up to five different race fields and a separate question on Hispanic ethnicity that are each self-reported by borrowers and co-borrowers.³ We select borrowers and co-borrowers who form opposite-sex mixed-race or monoracial dyads with a total sample of 9,034,759 home purchases. Included are a series of couple combinations consisting of multiracial Black-White individuals with Black partners (N = 2,132), Black-White individuals with White partners (N = 5,300), Black-White couples that contain monoracial Black and monoracial Whites (N = 84,339), Black-Black couples (N = 373,877), and White-White couples (N = 8,569,111). The relatively robust sample sizes of multiracial individuals and mixed-race couples in the HMDA data provide us a unique opportunity to analyze neighborhood attainment outcomes at the census tract level above and beyond what other frequently used individual-level datasets can accomplish (e.g., Panel Study of Income Dynamics or the National Longitudinal Study of Adolescent Health).

We explore two commonly used outcomes in our analysis of the neighborhood couples purchase into neighborhood percentage non-Hispanic White and neighborhood average income. These outcome variables are derived from the U.S. Census supplied by the NCDB. Neighborhood percentage White is calculated as the total number of non-Hispanic Whites within a tract divided by the total population within the tract multiplied by 100. Neighborhood average income is operationalized as the aggregate household income (in $1,000s) in the tract divided by the total number of households in the tract.⁴

Additionally, we consider the effects of a number of theoretically derived household- and contextual-level independent variables that may account for couple combination differences in neighborhood attainment. A key household-level characteristic available in the HMDA data is family income, measured in thousands of dollars, which is the combined income of the borrower and co-borrower. Furthermore, we include a measure for the front-end debt-to-income ratio for couples that is the family income divided by the amount of the home loan. This income-to-loan amount measure is an imperfect operationalization of the back-end debt-to-income ratio which would ideally include all couples’ existing debt, but it is a useful proxy. We consider the type of loan obtained as well: conventional versus Federal Housing Administration (FHA), Veterans Administration (VA), or Farm Service Area (FSA).

We also consider metropolitan contextual characteristics that have been known to be related with neighborhood attainment (Frey and Farley 1996; Iceland and Nelson 2010). First, we control for the level of Black-White segregation as measured by the dissimilarity index. One of the major reasons to include Black-White segregation as a control is that metropolitan areas with lower levels of segregation will make it possibly easier for couples with Black representation to purchase into neighborhoods with higher shares of Whites and higher socioeconomic status. This pattern could be spurred by the fact that metropolitan areas with lower levels of segregation might be associated with an increased level of neighborhood knowledge across couples with Black representation because individuals within these couples will be more likely to be exposed to a broader swath of neighborhoods. As predicted by the social structural sorting perspective (Krysan and Crowder 2017), couples’ daily rounds, including where they work, shop, play, and worship, could be in more areas across metropolitan space than those who live in metropolitan areas highly segregated across racial lines. In turn, this increased knowledge of neighborhoods could have a meaningful impact on the neighborhoods that couples will even know to consider purchasing in. Second, metropolitan areas with larger population sizes evince larger levels of segregation; because the effects of population size are known to be nonlinear, we include a control for the log of the total population size. Third, the construction of new housing is associated with higher levels of neighborhood racial diversity because areas of new construction do not have established patterns of residential segregation. Fourth, the functional specialization of metropolitan areas has been demonstrated to be associated with patterns of neighborhood attainment (Fischer and Lowe 2015). Metropolitan areas with older populations and higher levels of manufacturing will have different housing markets compared with those areas with large universities, government workers, and a military presence. Because of this, we include these functional specialization characteristics: the percentage employed in government positions, the percentage of individuals in the military, the percentage in the labor force employed in manufacturing, the percentage enrolled in college, and the percentage of the population aged more than 65 years.

We also take into account the region of the United States given that the level of residential segregation tends to vary by region of the country—the South and West tend to be less segregated than the Northeast and Midwest. We include an indicator for the year of observation to control for trends in neighborhood racial and socioeconomic change.

Analytically, we highlight the descriptive statistics of our two neighborhood outcomes of percentage non-Hispanic White and average income across each of the couples in our analysis. Next, we assess couple combination differences across our neighborhood outcomes controlling for family income, loan characteristics, debt-to-income ratio, contextual characteristics, and year of observation through the use of ordinary least squares regression. We then investigate couple combination differences in the effect of family income on purchasing into Whiter and higher-income neighborhoods. To illustrate the moderating effect of family income on the neighborhood attainment between couples, we display marginal predicted values of couple combination differences by family income for each of our neighborhood outcomes while holding control variables at their mean values.

Finally, previous research has established that numerous individual- and household-level characteristics are associated with neighborhood attainment such as age, education, number of children, and marital status (Goyette, Iceland, and Weininger 2014). However, data from HMDA do not have these types of individual- and household-level characteristics available. Furthermore, the HMDA data that we use only represents homeowners, yet their patterns of neighborhood attainment may potentially have more lasting consequences on broader patterns of racial residential stratification because homeowners are likely to remain in their neighborhoods longer than renters (Crowder, Pais, and South 2012). Despite these limitations, scholars have produced impactful research on neighborhood attainment using HMDA data (see Fischer and Lowe 2015; Fischer and Rugh 2018).

Results

Figure 3 illustrates the couple combination differences in mean neighborhood percentage White and mean neighborhood average income. As it relates to the first outcome of neighborhood percentage White in Panel A, it is apparent that White-White couples have the highest concentration of Whites in their neighborhoods (79.41) with Black-Black couples possessing the lowest concentration of Whites in the neighborhoods they purchase into (50.98). Expanding on prior scholarship (Pais et al. 2012), there is added variation for those couples with both Black and White representation. For example, Black-White individuals with White partners (71.79) have the highest percentage of Whites in their neighborhoods out of all couples with Black representation followed by Black-White couples (67.38) and Black-White individuals with Black partners (58.64). Indeed, Black-White individuals with Black partners have approximately 13 percent fewer Whites in the neighborhoods they purchase into compared with Black-White couples with White partners. The overall pattern of couple combination differences in neighborhood percentage White is similar in our second outcome of neighborhood average income with one small difference—Black-White individuals with White partners actually purchase into neighborhoods with a slightly higher neighborhood average income (82,027) as compared with White-White couples (80,942). These two prior types of couples are followed by Black-White couples (76,909), Black-White individuals with Black partners (71,517) and, finally, Black-Black couples purchase into neighborhoods with the lowest average incomes (65,434).

Figure 3.

Mean neighborhood percentage White and neighborhood average income for Black-White individuals with Black or White partners, Black-White couples, and monoracial Black and White couples: Home Mortgage Disclosure Act, 2005–2015.

Table 1 highlights the couple combination differences in a number of characteristics, with our focus being on the key measure of family income. Family income follows known racial differences (Fischer and Rugh 2018), where Whites tend to have greater economic resources (116,770) than Blacks (97,400). Black-White couples with White partners are most similar in family income (104,490) to White-White couples as compared with any couple with Black representation, followed by Black-White couples (103,880), and Black-White couples with Black partners (99,670).

Table 1.

Descriptive Statistics for the Analyses of Black-White Individuals with Black or White Partners, Black-White Couples, and Monoracial Black and White Couples: Home Mortgage Disclosure Act, 2005–2015.

	Black-Black		Black-White individuals/Black partner		Black-White		Black-White individuals/White partner		White-White
Variables	M	SD	M	SD	M	SD	M	SD	M	SD
Neighborhood outcomes
Neighborhood percentage White	50.98	27.67	58.64	26.23	67.38	22.80	71.79	21.01	79.41	17.13
Neighborhood average income	65,434.25	49,536.68	71,517.93	41,040.54	76,909.48	63,662.40	82,027.70	46,293.41	80,942.34	69,410.48
Economic resources
Family income ($1,000)	97.40	93.75	99.67	63.46	103.88	100.92	104.49	80.77	116.77	132.32
Front-end debt-to-income
Debt-to-income ratio	0.47	0.46	0.49	1.05	0.48	0.38	0.48	0.32	0.53	0.48
Loan characteristics	%		%		%		%		%
Conventional	52.45		46.81		52.74		58.47		75.07
FHA	31.54		31.29		28.44		24.74		16.96
VA	15.53		21.25		17.84		15.85		7.11
FSA	0.48		0.66		0.99		0.94		0.87
Metropolitan characteristics
Black-White segregation (dissimilarity)	0.57	0.12	0.55	0.12	0.53	0.13	0.52	0.14	0.52	0.15
Total population (log)	14.47	1.39	14.29	1.42	14.16	1.43	14.07	1.49	13.88	1.57
Percentage housing built in past 10 years	15.71	6.37	15.27	6.32	14.80	6.39	14.18	6.29	14.21	6.44
Percentage in government	2.63	1.54	2.54	1.40	2.52	1.41	2.45	1.34	2.26	1.16
Percentage in military quarters	0.59	1.17	0.60	1.23	0.55	1.21	0.50	1.17	0.34	0.96
Percentage in manufacturing	4.57	1.91	4.75	2.09	4.78	2.12	4.85	2.11	5.24	2.34
Percentage in college	3.11	3.77	2.80	3.66	2.53	3.51	2.51	3.70	2.37	3.59
Percentage 65+	2.00	9.53	1.67	8.44	1.61	8.35	1.55	8.56	1.54	8.29
Region	%		%		%		%		%
Northeast	11.78		12.57		13.56		16.26		16.20
Midwest	13.27		17.03		20.95		21.94		25.71
South	65.71		56.80		42.64		34.89		35.63
West	9.25		13.60		22.85		26.91		22.46
Year	%		%		%		%		%
2005	17.77		13.93		13.34		9.04		14.13
2006	17.42		12.52		12.14		10.26		12.14
2007	12.72		11.87		9.86		8.77		10.31
2008	9.04		10.27		8.27		6.91		8.32
2009	6.17		6.85		7.05		5.83		7.22
2010	5.69		6.33		6.11		6.21		6.70
2011	4.68		4.78		5.70		6.09		6.16
2012	5.24		5.77		6.59		7.94		7.21
2013	5.63		6.05		8.35		10.17		8.55
2014	7.06		8.68		10.20		12.36		9.09
2015	8.59		12.95		12.40		16.42		10.17
No. of observations by race and gender			Black-White female/Black male		Black female/White male		Black-White female/White male
			1,227		25,618		2,287
			Black-White male/Black female		Black male/White female		Black-White male/ White female
			905		58,721		3,013
No. of observations	373,877		2,132		84,339		5,300		8,569,111

Note. FHA = Federal Housing Administration; VA = Veterans Administration; FSA = Farm Service Area.

Neighborhood Percentage White for Couples

Figure 3 and Table 1 display the couple combination differences in neighborhood percentage White and neighborhood average income. These descriptive findings prompt us to assess the effect of household- and contextual-characteristics and temporal trends on the association between couple combination differences in neighborhood attainment outcomes while also investigating the moderating role of family income on couple combination differences in these outcomes. Table 2 shows the neighborhood percentage White of Black-White individuals with Black or White partners, Black-White couples, and monoracial Black and monoracial White couples using OLS regression.⁵ In Model 1, with White-White couples functioning as the reference category, Black-Black couples emerge with the lowest exposure to Whites in the neighborhoods they purchase into out of all couples (b = −28.475, p < .001).⁶ Conversely, Black-White couples with White partners purchase into neighborhoods with the highest shares of Whites out of all couples with Black representation (b = −6.742, p < .001), trailed by Black-White couples (b = −12.122, p < .001), and Black-White couples with Black partners (b = −21.375, p < .001). These results reveal a relatively large difference in percentage White in the neighborhoods Black-White individuals with White partners and Black-White individuals with Black partners purchase into.⁷ In fact, Black-White couples with Black partners have, on average, 14.63 percent fewer Whites in their neighborhoods than their counterparts with White partners.

Table 2.

OLS Regression of Neighborhood Percentage White for Black-White Individuals with Black or White Partners, Black-White Couples, and Monoracial Black and White Couples: Home Mortgage Disclosure Act, 2005–2015.

	Model 1		Model 2		Model 3		Model 4
Variables	b	SE	b	SE	b	SE	b	SE
Couple combinations
Black-Black	–28.475***	0.030	–23.914***	0.027	–23.803***	0.027	–26.147***	0.038
Black-White individuals/Black Partner	–21.375***	0.384	–17.628***	0.341	–17.544***	0.340	–23.349***	0.633
Black-White couples	–12.122***	0.061	–9.355***	0.055	–9.297***	0.054	–10.228***	0.078
Black-White individuals/White Partner	–6.742***	0.244	–4.817***	0.216	–4.739***	0.216	–5.640***	0.352
Economic resources
Family income ($1000)					0.008***	0.000	0.008***	0.000
Interactions
Black-Black × family income							0.024***	0.000
Black-White individuals/Black partner × family income							0.058***	0.005
Black-White × family income							0.009***	0.001
Black-White individuals/White Partner × family income							0.009**	0.003
Front-end debt-to-income
Debt-to-income ratio			–0.805***	0.011	–1.627***	0.012	–1.644***	0.012
Loan characteristics
FHA			–3.916***	0.014	–3.590***	0.014	–3.574***	0.014
VA			–2.826***	0.021	–2.636***	0.021	–2.647***	0.021
FSA			2.395***	0.057	2.769***	0.057	2.766***	0.057
Metropolitan characteristics
Black-White segregation (dissimilarity)			2.529***	0.074	2.589***	0.073	2.627***	0.073
Total population (log)			–2.403***	0.007	–2.491***	0.007	–2.493***	0.007
Percentage housing built in past 10 years			0.000	0.001	0.008***	0.001	0.008***	0.001
Percentage in government			–0.057***	0.005	–0.062***	0.005	–0.071***	0.005
Percentage in military quarters			–1.262***	0.006	–1.290***	0.006	–1.290***	0.006
Percentage in manufacturing			0.479***	0.003	0.491***	0.003	0.490***	0.003
Percentage in college			–0.432***	0.002	–0.458***	0.002	–0.458***	0.002
Percentage 65+			0.035***	0.001	0.037***	0.001	0.037***	0.001
Region
Northeast			14.789***	0.023	15.059***	0.023	15.061***	0.023
Midwest			11.937***	0.021	12.233***	0.021	12.230***	0.021
South			1.963***	0.017	2.143***	0.017	2.152***	0.017
Year			–0.035***	0.002	–0.048***	0.002	–0.050***	0.002
Constant	79.451***	0.006	175.477***	3.420	203.142***	3.416	205.516***	3.415

Note. No. of observations = 9,034,759. OLS = ordinary least squares; FHA = Federal Housing Administration; VA = Veterans Administration; FSA = Farm Service Area.

p < .05. **p < .01. ***p < .001.

Model 2 includes debt-to-income ratio, loan and metropolitan characteristics, region, and year of observation.⁸ Most important for our purposes in this model is that there is modest attenuation in the coefficient size for each couple with Black representation relative to White-White couples with the inclusion of these control variables, meaning that there remain substantial differences between the concentration of Whites in the neighborhoods that couples with Black representation purchase into as compared with White-White couples. Also, higher debt-to-income ratios are significantly related to lower shares of Whites in the neighborhoods of couples. Unsurprisingly, couples who obtain an FSA home loan evince significantly higher concentrations of Whites in their neighborhoods relative to couples who obtain a conventional mortgage. Moreover, Black-White segregation (dissimilarity) is positively and significantly associated with the concentration of Whites that couples are exposed to in the neighborhoods they purchase a home. Both the percentage in manufacturing and the percentage aged 65 or older also emerge with positive and significant associations with the outcome. Several metropolitan characteristics reveal a negative and significant association with the concentration of Whites in the neighborhoods of couples, these characteristics being the total population, the percentage employed in government positions, in military quarters, and in college. Moreover, couples in the Northeast have a significantly higher share of Whites in their neighborhoods relative to couples who purchase homes in the West net of controls and that over time couples have a negative and significant relationship with purchasing into Whiter neighborhoods.

Model 3 tests the spatial assimilation theory by including family income. With the addition of family income (b = 0.008, p < .001) the couple combination differences remain highly similar to the results displayed in Model 2, challenging the spatial assimilation perspective that economic resources will eliminate the disparity in neighborhood percentage White between couples with Black representation and White-White couples.

In Model 4, we test the weak and strong versions of the place stratification theory. We include an interaction between couple combinations and family income to investigate to what degree the neighborhood concentration of Whites varies between different types of couples by their family income while controlling for household- and contextual-characteristics and year of observation. For White-White couples, the effect of higher family income is positive and significant, meaning that higher-income White-White couples purchase into neighborhoods with higher percentages of Whites (b = 0.008, p < .001). Following the weak version of the place stratification theory, the effect of family income for couples with Black representation is stronger than that of White-White couples. For instance, Black-White individuals with Black partners emerge with the greatest returns to their economic resources on the percentage of Whites in the neighborhoods they purchase into relative to all other couples with Black representation in comparison with White-White couples (b = 0.008 + 0.058 = 0.066, p < .001). This is followed by Black-Black couples (b = 0.008 + 0.024 = 0.032, p < .001), and both Black-White couples (b = 0.008 + 0.009 = 0.017, p < .001) and Black-White individuals with White partners (b = 0.008 + 0.009 = 0.017, p < .01) emerge with the same coefficient magnitude.

To provide a clear picture of the findings presented in Model 4 of Table 2, we include Figure 4, which illustrates the predicted values of neighborhood percentage White for the couple combinations in our analysis by family income while holding the remaining covariates at their mean values. First, it is evident that couples with greater Black representation are more likely to purchase into higher-diversity neighborhoods than couples with less Black representation. Second, the effect of family income on the percentage of Whites in the neighborhoods couples with Black representation purchase into is relatively modest but stronger than that of White-White couples. This finding is largely consistent with the weak version of the place stratification theory. That is, although couples with Black representation experience a stronger effect of family income on the dependent variable than do White-White couples, even those neighborhoods occupied by the highest income couples with Black representation have substantially lower percentages of Whites relative to the neighborhoods that similarly resourced White-White couples purchase into.

Figure 4.

Predicted neighborhood percentage White for Black-White individuals with Black or White partners, Black-White couples, and monoracial Black and White couples by family income: Home Mortgage Disclosure Act, 2005–2015.

Neighborhood Average Income for Couples

In Table 3, we show the results from an OLS regression on another common outcome in studies of neighborhood attainment—average neighborhood income. In particular, we assess couple combination differences in neighborhood average income while controlling for our same set of covariates, while also investigating how the effect of family income varies across couples. Model 1 in Table 3 highlights that most couples with Black representation purchase into neighborhoods that possess lower average neighborhood incomes than White-White couples. Relative to other couples with Black representation, Black-Black couples are revealed to have the greatest disparity in average neighborhood income in the neighborhoods they purchase into compared with White-White couples (b = −15464, p < .001). Similar to the outcome for neighborhood percentage White, Black-White individuals with White partners are most comparable to White-White couples in the average income their neighborhoods possess (b = 2811, p < .01). Next, Black-White couples (b = −4216, p < .001) and Black-White individuals with Black partners (b = −9599, p < .001) emerge with significant negative differences from White-White couples in their average neighborhood income.

Table 3.

OLS Regression of Neighborhood Average Income for Black-White Individuals with Black or White Partners, Black-White Couples, and Monoracial Black and White Couples: Home Mortgage Disclosure Act, 2005–2015.

	Model 1		Model 2		Model 3		Model 4
Variables	b	SE	b	SE	b	SE	b	SE
Couple combinations
Black-Black	–15,464.93***	114.96	–12,088.23***	105.18	–10,939.67***	103.76	–9,680.61***	147.74
Black-White individuals/Black partner	–9,599.06***	1,490.43	–9,008.71***	1,336.66	–8,140.32***	1,318.27	–13,979.51***	2,454.61
Black-White	–4,216.43***	238.10	–5,618.16***	213.91	–5,019.82***	210.97	–4,823.81***	302.31
Black-White individuals/White partner	2,811.94**	945.47	–4,274.07***	847.91	–3,468.52***	836.24	–7,915.28***	1,367.13
Economic resources
Family income ($1000)					86.51***	0.17	86.77***	0.17
Interactions
Black-Black × family income							–12.86***	1.07
Black-White individuals/Black partner × family income							58.64**	20.77
Black-White × family income							–1.86	2.08
Black-White individuals/White partner × family income							42.58***	10.35
Front-end debt-to-income
Debt-to-income ratio			–2,362.15***	43.51	–10,896.58***	46.13	–10,887.28***	46.14
Loan characteristics
FHA			–14,036.76***	55.41	–10,655.67***	55.05	–10,662.38***	55.06
VA			–11,923.39***	81.03	–9,957.10***	80.01	–9,949.98***	80.02
FSA			–21,754.09***	225.18	–17,868.00***	222.21	–17,863.96***	222.21
Metropolitan characteristics
Black-White segregation (dissimilarity)			4,914.74***	288.93	5,542.03***	284.96	5,522.91***	284.96
Total population (log)			6,514.02***	26.60	5,600.59***	26.30	5,601.80***	26.30
Percentage housing built in past 10 years			–149.16***	5.01	–65.04***	4.94	–65.12***	4.94
Percentage in government			2,742.67***	20.90	2,690.89***	20.61	2,695.70***	20.61
Percentage in military quarters			476.56***	23.64	187.41***	23.32	187.43***	23.32
Percentage in manufacturing			181.57***	12.25	305.54***	12.08	306.25***	12.08
Percentage in college			1,483.18***	9.75	1,213.32***	9.63	1,213.34***	9.63
Percentage 65+			–110.90***	2.82	–88.72***	2.78	–88.71***	2.78
Region
Northeast			–4,668.29***	90.65	–1,861.89***	89.57	–1,862.15***	89.57
Midwest			–4,963.40***	82.31	–1,890.11***	81.41	–1,887.15***	81.41
South			–5,082.34***	68.04	–3,214.99***	67.21	–3,218.98***	67.21
Year			7,498.10***	6.66	7,356.70***	6.58	7,357.17***	6.58
Constant	81,000.26***	23.51	–1.51***	13,417.57	–1.48***	13,245.14	–1.48***	13,245.50

Note. No. of observations = 9,034,759. OLS = ordinary least squares; FHA = Federal Housing Administration; VA = Veterans Administration; FSA = Farm Service Area.

p < .05. **p < .01. ***p < .001.

Model 2 includes debt-to-income ratio, loan and metropolitan characteristics, region, and year of observation. After controlling for these factors, the coefficient for Black-White individuals with White partners changes to the expected negative direction (b = −4274, p < .001). Consequently, the pattern of neighborhood average income for couples with Black representation from White-White couples aligns with our hypothesis—that couples with greater Black representation purchase homes in lower income neighborhoods. Additionally, couples with higher debt-to-income ratios are significantly more apt to reside in lower income neighborhoods and couples who obtain either an FHA, VA, or FSA home loan are significantly more likely to purchase in lower income areas than those with a conventional loan; this is expected given the lower required down payments and lower household asset levels associated with government-backed loans. Also, multiple metropolitan characteristics are positively and significantly associated with couples purchasing into higher-income neighborhoods. Black-White segregation, the total population, the percentage in government positions and in military quarters, the percentage of individuals employed in manufacturing, and the percentage in college are all positively and significantly associated with the outcome. Conversely, both the percentage of new housing and the percentage of individuals aged 65 and older in the metropolitan area are negatively and significantly associated with neighborhood average income for couples. Moreover, neighborhood average incomes are significantly at their lowest for couples in the South relative to those in the West and couples are significantly more likely to purchase into higher-income neighborhoods in more recent years.

To investigate the spatial assimilation theory, Model 3 of Table 3 adds family income to the controls included in Model 2. With the inclusion of family income (b = 86.51, p < .001), and contradicting the spatial assimilation theory, there is only a slight decline from Model 2 in differences in neighborhood average income between couples with Black representation and White-White couples. In Model 4, we investigate the weak and strong versions of the place stratification theory by including an interaction between family income and couple combinations to explore variations in the effect of family income across couples in purchasing into higher-income neighborhoods. The effect of family income on purchasing into higher-income neighborhoods is positive and significant for White-White couples (b = 86.77, p < .001). Family income is less impactful on the neighborhood attainment of Black-Black couples (b = −12.86, p < .001) in relation to White-White couples, which is in-line with the strong version of the place stratification theory. The effect of family income for Black-White couples (b = 86.77 – 1.86 = 84.91) is not significant. In contrast, and following the weak version of the place stratification theory, the effect of family income for Black-White individuals with Black partners (b = 86.77 + 58.64 = 145.41, p < .01) and those with White partners (b = 86.77 + 42.58 = 129.35, p < .001) are the strongest out of all couples compared with White-White couples.

In Figure 5, we display the predicted values from Model 4 of Table 3 of neighborhood average income for couple combinations by family income, while holding the remaining covariates at their mean values. Similar to Figure 3, as couples increase in Black representation, the lower neighborhood average income is in the areas they tend to purchase into. Additionally, the height of the respective intercepts associated with couples with Black representation roughly aligns with the traditional racial hierarchy that advantages Whites and disadvantages Blacks in the housing market; however, couple combination differences in neighborhood average income are more similar than the results for the previous outcome of neighborhood percentage White. Moreover, Black-Black couples align with the strong version of the place stratification theory, meaning that the effect of family income is weaker for these couples than for White-White couples. The same pattern is observed for Black-White couples. In contrast, the influence of family income on the neighborhood average income for Black-White individuals with Black partners and those with White partners largely follow the weak version of the place stratification theory; therefore, the effect of family income for these couples is stronger than that of White-White couples. Despite the effect of family income for Black-White individuals with Black partners and those with White partners being stronger than that of White-White couples, even the highest-earning of these couples with Black representation are not able to purchase homes in neighborhoods of similar average income as comparably resourced White-White couples.

Figure 5.

Predicted neighborhood average income for Black-White individuals with Black or White partners, Black-White couples, and monoracial Black and White couples by family income: Home Mortgage Disclosure Act, 2005–2015.

Supplemental Analyses

Gender.⁹

Previous research has demonstrated that the neighborhood attainment patterns of mixed-race couples can differ by the race/gender combination of couples (Gabriel 2018a; Wright et al. 2013). Given this pattern, we have investigated whether the neighborhood attainment patterns for the diverse couples in our analysis vary by gender. The results of this analysis demonstrate that the differences within couple combinations (e.g., Black-White females with Black male partners and Black-White males with Black female partners) are quite modest. This finding aligns with what Gabriel (2018a) observes in his analysis of gender and neighborhood attainment patterns of Black-White couples. In his analysis he finds that there are minimal differences between the race/gender pairings of couples who migrate to new neighborhood destinations.

Residential segregation

Our theoretical framing posits that Black-White individuals might be especially knowledgeable of, and comfortable with, neighborhoods of varying racial and socioeconomic status because of their potentially greater exposure to varied spaces within segregated metropolitan areas. To further investigate this possibility, we estimated an interaction between the couple combinations and a dichotomous measure of metropolitan Black-White residential segregation (high = 1, dissimilarity ≥ .60) on both neighborhood attainment outcomes of percentage White and average income with Black-Black couples functioning as the reference category. Comparing the neighborhood attainment outcomes of these couples in highly segregated areas is beneficial because Black-White individuals with Black partners are racially similar to Black-Black couples but have the distinguishing difference of possessing White representation within their couple. Consequently, Black-White individuals with Black partners might have expanded knowledge of, and greater comfort with, various neighborhoods in segregated metropolitan areas relative to Black-Black couples whose knowledge of, and comfort with, potential neighborhoods would likely be most limited because of high levels of segregation influencing the social spheres and spatial exposures of both members of the couple. If there is a difference between Black-White individuals with Black partners and Black-Black couples purchasing homes in highly segregated areas that would provide further suggestive evidence for our thesis that Black-White individuals may have an expanded knowledge of, and greater comfort with, various neighborhoods in segregated metropolitan areas.

Our results indicate that Black-White individuals with Black partners in metropolitan areas with high levels of Black-White segregation purchase into neighborhoods with greater concentrations of Whites and neighborhoods that are higher income than Black-Black couples who purchase homes in highly segregated metropolitan areas (48 percent White vs. 56 percent White, respectively; $66,164 vs. $71,148, respectively). However, the difference between neighborhood average income between Black-White individuals with Black partners and Black-Black couples in highly segregated metropolitan areas is not statistically significant.

The joint distribution of neighborhood percentage White and neighborhood average income

There is a distinct possibility that some couples with Black representation might prefer to purchase homes in neighborhoods that are more diverse and higher income. To investigate this possibility, we estimated a four neighborhood-type multinomial model consisting of these neighborhoods: low percentage White/low income, low percentage White/high income, high percentage White/low income, and high percentage White/high income (reference category). The cutoff between low and high neighborhood contexts is operationalized at the mean of neighborhood percentage White and neighborhood average income, where neighborhoods below 78 percent White and below $80,320 are defined as low. The results show that as compared with White-White couples, couples with Black representation are more likely to purchase a home in a low percentage White/high income neighborhood than a high percentage White/high income neighborhood. Also, the effect of family income across this neighborhood-type comparison is weaker for couples with Black representation than for White-White couples and statistically significant in most cases. Furthermore, the magnitude of the coefficients across this neighborhood-type comparison for couples with Black representation follows our overarching hypothesis presented in Figure 2, where the greater the level of Black representation within a couple, the higher the likelihood that they will purchase a home in a neighborhood that has lower percentages of Whites and higher average income.

Conclusion

Scholars have observed a recent rise in the number of mixed-race couples and multiracial individuals (Lee and Bean 2010; Livingston and Brown 2017; Parker et al. 2015), calling for greater attention to be given to these populations that are diversifying the landscape of American institutions (Alba and Beck 2018). In this study, we have undertaken this challenge by using data from the HMDA and the U.S. Census to investigate the neighborhood percentage White and neighborhood average income of couples defined by increasing Black representation beginning with Black-White individuals with White partners, followed by Black-White couples, Black-White individuals with Black partners, and Black couples, with White couples serving as the comparison group.

Our results highlight that a number of distinct neighborhood attainment patterns are associated with the various couple combinations in our study. We observe that couples with greater Black representation have lower shares of Whites in the neighborhoods they purchase into, along with lower levels of neighborhood average income, while controlling for household and contextual characteristics, year of observation, and family income. We also investigated how the level of neighborhood percentage White and neighborhood average income varies by family income for each of the couples in our analysis. Compared with White couples, family income has a relatively modest effect on the abilities of racially diverse couples to purchase into neighborhoods with higher shares of Whites; conversely, the effect of family income for racially diverse couples tends to be more varied along the outcome of neighborhood average income.

In particular, the results of our regression analysis indicate that most couples with Black representation appear to follow the weak version of the place stratification theory as it relates to both neighborhood percentage White and neighborhood average income. This pattern highlights that there is a cross-section of couples with Black representation that purchase into relatively diverse, comparatively higher-income neighborhoods, which is confirmed by our supplemental multinomial models—possibly indicating that these couples who can translate their economic resources into higher-income neighborhoods might not necessarily view Whiter neighborhoods as “better.” Moreover, these couples might prefer more diverse neighborhoods for numerous reasons such as avoiding discrimination to valuing the cultural variation that racial diversity provides. Furthermore, Black couples and Black-White couples seem to follow the weak version of the place stratification theory in relation to neighborhood percentage White, but the strong version in reference to average neighborhood income. The combination of these results for Black couples and Black-White couples indicates that they often purchase into more diverse and lower-income neighborhoods.

The place stratification theory would suggest that the decrease in neighborhood percentage White and neighborhood average income that is associated with the greater Black representation within a couple would largely be due to housing market discrimination. Yet, it is quite possible that the difference between couples with greater Black representation and White couples is related to a nuanced combination of individual, household, and social forces, with discrimination being one of the components. Although the data currently available make it impossible to clearly adjudicate how these couples’ economic standing, exposure to discrimination, and residential preferences all combine to create the patterns observed here, the recently developed social structural sorting perspective could be helpful in partially explaining the neighborhood attainment patterns found in our analysis (Krysan and Crowder 2017).

The patterns of neighborhood attainment shown in our analysis appear to point to the notion that the combined neighborhood knowledge of members of couples plays an important role in shaping their residential search and acquisition patterns. And, the combined neighborhood knowledge of members of couples is likely strongly influenced by enduring legacies of racial residential segregation that sharply separate the social and spatial spheres of Blacks and Whites (Massey and Denton 1993; Krivo et al. 2013). For instance, one of the major effects of the enduring pattern of racial residential segregation for Black-White individuals is that they are likely to have kin and kith networks more evenly distributed across metropolitan areas than monoracial Black and White individuals. This more even residential distribution of kith and kin for Black-White individuals feasibly provides them with greater exposure to a larger swath of neighborhoods over the life course than their monoracial counterparts, seemingly endowing them with a greater knowledge of neighborhood options and an enhanced flexibility in the types of neighborhoods they will consider purchasing into.

In addition, the results of our analysis also have implications for our understanding of how the one-drop rule has changed since its inception. Historically, any individual who had one drop of Black blood would be considered Black and, consequently, relegated to the inferior social, economic, and political status of Black individuals. Today it seems that in the housing market the one-drop rule functions by degrees where racially diverse couples with lesser Black representation are closer to the neighborhood attainment patterns of White couples than Black couples. Meanwhile, racially diverse couples with greater Black representation are more similar to Black couples than White couples in terms of the neighborhoods where they purchase homes. Thus, the one-drop rule has partially diluted since its period of greatest concentration, fostering racially diverse couples access to a greater set of neighborhood options when purchasing a home.

A number of salient questions remain about the neighborhood attainment of Black-White individuals with Black or White partners and Black-White couples. Part of the difficulty in learning more about these specific types of couples has been the little amount of data that allows for the investigation of these groups. And, although the HMDA data that we use is novel, scholars have noted a number of complexities in investigating these diverse populations with available data. Carolyn A. Liebler and colleagues (2017) have demonstrated that structural circumstances may influence whether individuals report or fail to report certain aspects of their racial identity. Additionally, previous research has indicated that racial self-identification can differ by social position and exposures to various contexts (Saperstein and Penner 2012). Therefore, our results could be affected by selection-based endogeneity bias in the racial self-identification of individuals, where individuals observed in a particular couple combination are related to their past and present neighborhood attainment. Because of this possibility, we suggest that future research use individual-level longitudinal data that tracks individuals’ race and neighborhood contexts to help address selection-based endogeneity associated with racial self-identification that might influence the neighborhood attainment of couples across the Black/White spectrum.

Furthermore, future research should extend our analysis of couples to other racial and ethnic groups such as the Latinx/White and Asian/White spectrums. Moreover, fruitful research could also consider how the specific income contributions of each member of the couple combinations by race and gender are related to their neighborhood attainment. Additionally, scholars might explicitly assess the role of time in conditioning the neighborhood attainment of couples along the Black/White spectrum. For example, past research has indicated racial differences in neighborhood attainment during the foreclosure crisis (Hall et al. 2017); hence, investigating the types of neighborhoods these diverse couples purchase into before, during, and after the Great Recession could provide meaningful insight on patterns of contemporary stratification. What is apparent, though, is that there are multiple directions that can be constructively studied as it relates to this diverse population, a population that will have an impact on broader patterns of racial residential stratification and assist in blurring boundaries that have enduringly separated Black and White Americans.

Footnotes

Acknowledgements

The authors wish to thank the editor and the anonymous reviewers for their incredibly helpful comments on earlier versions of this article.

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

Notes

Author Biographies

Ryan Gabriel is assistant professor of sociology at Brigham Young University. His research focuses on urban sociology with a specific emphasis on racial residential segregation and neighborhood attainment. He is also broadly interested in the legacies of racial violence.

Jacob Rugh is associate professor of sociology at Brigham Young University. His research is centered on urban policy, housing markets, land use regulation, and the foreclosure crisis.

Hannah Spencer is an MA student in the Department of Sociology at Brigham Young University. She examines the how multiracial individuals fare in systems of racial residential stratification.

Aïsha Lehmann is an undergraduate student at Brigham Young University whose primary focus is on U.S. slavery’s relationship with modern postsecondary institutions of higher learning.

References

Alba

Richard

Beck

Brenden

. 2018. “The Rise of Mixed Parentage: A Sociological and Demographic Phenomenon to be Reckoned With.” ANNALS of the American Academy of Political & Social Science 677:26–38.

Bennett

Pamela

. 2011. “The Social Position of Multiracial Groups in the United States: Evidence from Residential Segregation.” Ethnic & Racial Studies 34(4):707–29.

Bratter

Jenifer L.

2018. “Multiracial Identification and Racial Gaps: A Work in Progress.” ANNALS of the American Academy of Political and Social Science 677(1):69–80.

Brunsma

David L.

2005. “Interracial Families and the Racial Identification of Mixed-race Children: Evidence from the Early Childhood Longitudinal Study.” Social Forces 84(2):1131–57.

Charles

Camille Z.

2000. “Neighborhood Racial-composition Preferences: Evidence from a Multiethnic Metropolis.” Social Problems 47:379–407.

Charles

Camille Z.

2003. “The Dynamics of Racial Residential Segregation.” Annual Review of Sociology 29:167–207.

Clark

William A. V.

Andersson

Eva K.

Malmberg

. 2018. “What Can We Learn about Changing Ethnic Diversity from the Distributions of Mixed-race Individuals?” Urban Geography 39(2):263–81.

Crowder

Kyle

Pais

Jeremy

South

Scott J.

2012. “Neighborhood Diversity, Metropolitan Constraints, and Household Migration.” American Sociological Review 77(3):325–53.

Crowder

Kyle

South

Scott J.

2005. “Race, Class, and Changing Patterns of Migration between Poor and Nonpoor Neighborhoods.” American Journal of Sociology 110(6):1715–63.

10.

Dalmage

Heather M.

2000. Tripping on the Color Line: Black-White Multiracial Families in a Racially Divided World. New Brunswick, NJ: Rutgers University Press.

11.

Emirbayer

Mustafa

Desmond

Matthew

. 2015. The Racial Order. Chicago, IL: The University of Chicago Press.

12.

Evans

Gary W.

Kantrowitz

Elyse

. 2002. “Socioeconomic Status and Health: The Potential Role of Environmental Risk Exposure.” Annual Review of Public Health 23:303–31.

13.

Federal Financial Institutions Examination Council. 2006. Home Mortgage Disclosure Act (HMDA): Loan Application Register (LAR) Raw Data, 2004-2005. (http://www.ffiec.gov/hmda/hmdaflat.htm).

14.

Federal Financial Institutions Examination Council. 2010. Home Mortgage Disclosure Act (HMDA): Loan Application Register (LAR) Raw Data, 2006. ICPSR24611-v1. Ann Arbor, MI: Inter-university Consortium for Political and Social Research [Distributor].

15.

Federal Financial Institutions Examination Council. 2011. Home Mortgage Disclosure Act (HMDA): Loan Application Register (LAR) Raw Data, 2007. ICPSR24612-v1. Ann Arbor, MI: Inter-university Consortium for Political and Social Research [Distributor].

16.

Federal Financial Institutions Examination Council. 2015. Home Mortgage Disclosure Act (HMDA): Loan Application Register (LAR) Raw Data, 2008-2014. (http://www.ffiec.gov/hmda/hmdaflat.htm).

17.

Finnegan

Terence

. 2013. A Deed So Accursed: Lynching in Mississippi and South Carolina, 1881-1940. Charlottesville, VA: University of Virginia Press.

18.

Fischer

Mary J.

2013. “Black and White Homebuyer, Homeowner, and Household Segregation in the United States, 1990–2010.” Social Science Research 42(6):1726–36.

19.

Fischer

Mary J.

Lowe

Travis S.

2015. “Homebuyer Neighborhood Attainment in Black and White: Housing Outcomes During the Housing Boom and Bust.” Social Forces 93:1481–512.

20.

Fischer

Mary J.

Rugh

Jacob S.

2018. “Military Veterans and Neighborhood Racial Integration: VA Mortgage Lending across Three Eras.” Population Research and Policy Review 37(4):569–89.

21.

Frey

William H.

Farley

Reynolds

. 1996. “Latino, Asian, and Black Segregation in U.S. Metropolitan Areas: Are Multiethnic Metros Different?” Demography 33(1):35–50.

22.

Frey

William H.

Myers

Dowell

. 2002. Neighborhood Segregation in Single-race and Multi-race America: A Census 2000 Study of Cities and Metropolitan Areas. Washington, DC: Fannie Mae Foundation.

23.

Gabriel

Ryan

. 2016. “A Middle Ground? Residential Mobility and Attainment of Mixed-race Couples.” Demography 53(1):165–88.

24.

Gabriel

Ryan

. 2018a. “Gender and the Residential Mobility and Neighborhood Attainment of Black-White Couples.” Demography 55(2):459–84.

25.

Gabriel

Ryan

. 2018b. “Mixed-race Couples, Residential Mobility, and Neighborhood Poverty.” Social Science Research 73:146–62.

26.

Garrow

David

. 1986. The Civil Rights Movement in America. Edited by Eagles

Charles

. Jackson, MS: University of Mississippi Press.

27.

GeoLytics. 2013. Neighborhood Change Database. East Brunswick, NJ: GeoLytics, Inc. Retrieved February 11, 2021, https://geolytics.com/products/normalized-data/neighborhood-change-database#:~:text=Neighborhood%20Change%20Database%20(NCDB)%20gives,funded%20by%20The%20Rockefeller%20Foundation.

28.

Goyette

Kimberly

Iceland

John

Weininger

Elliot

. 2014. “Moving for the Kids: Examining the Influence of Children on White Residential Segregation.” City and Community 13(2):158–78.

29.

Hall

Matthew

Crowder

Kyle

Spring

Amy

Gabriel

Ryan

. 2017. “Foreclosure Migration and Neighborhood Outcomes: Moving Toward Segregation and Disadvantage.” Social Science Research 70:107–14.

30.

Holloway

Steven R.

Ellis

Mark

Wright

Richard

Hudson

Margaret

. 2005. “Partnering ‘Out’ and Fitting in: Residential Segregation and the Neighbourhood Contexts of Mixed-race Households.” Population, Space and Place 11:299–324.

31.

Iceland

John

Nelson

Kyle A.

2010. “The Residential Segregation of Mixed-nativity Married Couples.” Demography 47(4):869–93.

32.

Krivo

Lauren J.

Washington

Heather M.

Peterson

Ruth D.

Kwan

Mei Po

. 2013. “Social Isolation of Disadvantage and Advantage: The Reproduction of Inequality in Urban Space.” Social Forces 92(1):407–11.

33.

Krysan

Maria

Crowder

Kyle

. 2017. Cycle of Segregation: Social Processes of Residential Segregation. New York: Russell Sage Foundation.

34.

Lee

Jennifer

Bean

Frank D.

2010. The Diversity Paradox: Immigration and the Color Line in 21st Century America. New York: Russell Sage Foundation.

35.

Liebler

Carolyn A.

Porter

Sonya

Fernandez

Leticia

Noon

James

Ennis

Sharon R.

2017. “America’s Churning Races: Race and Ethnic Response Changes Between Census 2000 and the 2010 Census.” Demography 54(1):259–84.

36.

Livingston

Gretchen

Brown

Anna

. 2017. Intermarriage in the U.S. 50 Years after Loving v. Virginia. Washington, DC: Pew Research Center.

37.

Logan

John R.

Alba

Richard D.

1993. “Locational Returns to Human Capital: Minority Access to Suburban Community Resources.” Demography 30:243–68.

38.

Logan

John R.

Stults

Brian J.

2011. The Persistence of Segregation in the Metropolis: New Findings from the 2010 Census. US2010 Project Report. Providence, RI: Brown University.

39.

Massey

Douglas S.

2015. “The Legacy of the 1968 Fair Housing Act.” Sociological Forum 30(Suppl. 1): 571–88.

40.

Massey

Douglas S.

Gross

Andrew B.

Shibuya

Kumiko

. 1994. “Migration, Segregation, and the Geographic Concentration of Poverty.” American Sociological Review 59(3):425–45.

41.

Massey

Douglas S.

Denton

Nancy A.

1993. American Apartheid: Segregation and the Making of the Underclass. Cambridge, MA: Harvard University Press.

42.

Moran

Rachel F.

2001. Interracial Intimacy: The Regulation of Race and Romance. Chicago, IL: The University of Chicago Press.

43.

Mouw

Ted

. 2000. “Job Relocation and the Racial Gap in Unemployment in Detroit and Chicago, 1980 to 1990.” American Sociological Review 65(5):730–53.

44.

Pais

Jeremy

South

Scott J.

Crowder

Kyle

. 2012. “Metropolitan Heterogeneity and Minority Neighborhood Attainment: Spatial Assimilation or Place Stratification?” Social Problems 59(2):258–81.

45.

Parker

Kim

Morin

Rich

Horowitz

Juliana Menasce

Rohal

Mark Hugo

. 2015. “Multiracial in America: Proud, Diverse and Growing in Numbers.” Pew Research Center 11:1–50.

46.

Patterson

James T.

2001. Brown v. Board of Education: A Civil Rights Milestone and Its Troubled Legacy. New York: Oxford University Press.

47.

Pattillo

Mary

. 2005. “Black Middle-class Neighborhoods.” Annual Review of Sociology 31(1):305–29.

48.

Perlmann

Joel

Waters

Mary C.

2002. The New Race Question: How the Census Counts Multiracial Individuals. New York: Russell Sage Foundation.

49.

Peterson

Ruth D.

Krivo

Lauren J.

2009. “Segregated Spatial Locations, Race-ethnic Composition, and Neighborhood Violent Crime.” The ANNALS of the American Academy of Political and Social Science 623(1):93–107.

50.

Qian

Zhenchao

. 2004. “Options: Racial/Ethnic Identification of Children of Intermarried Couples.” Social Science Quarterly 85(3):746–66.

51.

Quillian

Lincoln

Redd

Rozlyn

. 2009. “The Friendship Networks of Multiracial Adolescents.” Social Science Research 38(2):279–95.

52.

Rothstein

Richard

. 2017. The Color of Law: A Forgotten History of How Our Government Segregated America. New York: Liveright Publishing.

53.

Rothwell

Jonathan T.

Massey

Douglas S.

2010. “Density Zoning and Class Segregation in U.S. Metropolitan Areas.” Social Science Quarterly 91(5):1123–43.

54.

Ruggles

Steven

Flood

Sarah

Goeken

Ronald

Grover

Josiah

Meyer

Erin

Pacas

Jose

Sobek

Matthew

. 2020. IPUMS USA: Version 10.0. Dataset. Minneapolis, MN: IPUMS.

55.

Rugh

Jacob S.

2020. “Why Black and Latino Home Ownership Matter to the Color Line and Multiracial Democracy.” Race and Social Problems 12:57–76.

56.

Rugh

Jacob S.

Albright

Len

Massey

Douglas S.

2015. “Race, Space, and Cumulative Disadvantage: A Case Study of the Subprime Mortgage Collapse.” Social Problems 62(2):186–218.

57.

Saperstein

Aliya

Penner

Andrew M.

2012. “Racial Fluidity and Inequality in the United States.” American Journal of Sociology 118(3):676–727.

58.

Turner

Margery Austin

Santos

Rob

Levy

Diane K.

Wissoker

Doug

Aranda

Claudia

Pitingolo

Rob

. 2013. Housing Discrimination against Racial and Ethnic Minorities 2012. Washington, DC: U.S. Department of Housing and Urban Development.

59.

Wright

Richard

Ellis

Mark

Holloway

Steven

. 2011. “Where Black-White Couples Live.” Urban Geography 32:1–22.

60.

Wright

Richard

Holloway

Steven

Ellis

Mark

. 2013. “Gender and the Neighborhood Location of Mixed-race Couples.” Demography 50(2):393–420.

The Neighborhood Attainment of Mixed-Race Couples across the Black/White Spectrum

Abstract

Keywords

Introduction

Background and Theory

Data and Method

Results

Neighborhood Percentage White for Couples

Neighborhood Average Income for Couples

Supplemental Analyses

Gender. 9

Residential segregation

The joint distribution of neighborhood percentage White and neighborhood average income

Conclusion

Footnotes

Acknowledgements

Declaration of Conflicting Interests

Funding

Notes

Author Biographies

References

Gender.⁹