Metropolitan Context and Racial/Ethnic Intermixing in Residential Space: U.S. Metropolitan Statistical Areas, 1990-20001

Abstract

This study is concerned with racial/ethnic intermixing as it varies among the 49 largest U.S. MSAs in 2000 and its change over the 1990-2000 decade. Race/ethnicity is defined in terms of the major census categories of African American, American Indian, Asian, Caucasian, and Hispanic. Intermixing is calibrated by the Theil Entropy Index, which treats the five groups simultaneously and produces measures of an MSA's diversity (Diversity Score) and its level of intermixing (Entropy). The latter (Entropy) also serves as a dependent variable in regression analyses, wherein independent variables include demographic, socio-economic, and builtenvironment characteristics. The study departs from earlier work at the urban system level in a number of ways. First, MSAs are treated as objects of study in their own right, not simply as observational units. Second, this leads to challenging the usual practice of employing a 1/0 dummy variable to indicate the region in which an MSA is located, a practice that interferes with the emergence of other, more place-specific factors. Third, earlier studies mainly examine metropolitan areas from the perspective of two-group comparisons, rather than the multi-group comparison approach taken here. Fourth, in a major conceptual departure from earlier work, we contextualize racial/ethnic mixing and its 1990-2000 change within broader forces of economic restructuring related to the Fordist/Post-Fordist transition and broad transformational processes that invoke such concepts as inertia, sunk cost, and path dependence effects. Especially noteworthy in our findings is that MSAs that lagged in racial/ethnic intermixing in 1990 experienced the greatest change in the 1990-2000 decade, a catch-up phenomenon that we attribute to a set of widely shared norms concerning intermixing-termed the community, or social, norm premise.[

Patterns of Socioeconomic Segregation in the Capital Cities of Fast-Track Reforming Postsocialist Countries

“…The complex relationship between economic inequality and patterns of intraurban socioeconomic segregation depends on the diverse forms of the housing market and the extent of welfare provision. The link between inequality and segregation is also codetermined by the various characteristics of the city, such as its size, historically developed economic profile (manufacturing base) and employment structure (Burgers and Musterd 2002;Brown and Sharma 2010;Reardon and Bischoff 2011), inherited residential built-up and tenurial makeup (Galster and Booza 2007), and topography (Meyer 2005). For example, a more substantial involvement of the public sector in welfare provision and housing distribution as well as a significantly more compact spatial structure render less clear-cut sociospatial divisions within the city and between the central city and the suburbs in the case of Western Europe (van Kempen and Murie 2009).…”

“…Unfortunately, the limited number of case cities precludes a more formal test of the relationship between intraurban segregation and economic inequality, which could be controlled for other causal factors (cf. Watson 2009;Brown and Sharma 2010). Based on the evidence discussed in the previous section, however, we hypothesize that there is a contingent relation among economic inequality, other contributory factors, and patterns of socioeconomic intraurban segregation in the postsocialist city.…”

Black–White and Hispanic–White Segregation in U.S. Counties

“…Various measures for different concepts of segregation have been evaluated by scholars studying segregation, and several have been widely used (Massey and Denton 1988 Lee et al 2008;Brown and Sharma 2010). Although many new approaches and methods are valuable, complexity of calculation or difficulty in interpretation has meant that most have been applied to only one place.…”

“…In its focus on places it is similar to Brown and Sharma's (2010) recent study of diversity in metropolitan areas, but in contrast to Brown and Sharma, we measured segregation in counties rather than in metropolitan areas. This required special methodological adjustments, but it enabled us to include both metropolitan and nonmetropolitan areas across the country.…”

The Contributions of Places to Metropolitan Ethnoracial Diversity and Segregation: Decomposing Change Across Space and Time

“…Recent advances are apparent on this front, with regression and decomposition analyses deployed separately or together to highlight the structural correlates of ethnoracial residential distributions (Brown and Sharma 2010; Farrell 2016; Iceland and Scopilliti 2008; Lichter et al 2015; Logan et al 2004). Our own decomposition strategy offers further insights about such correlates for census-defined places.…”