Poverty Segregation Research Articles

Rapid Economic Growth But Rising Poverty Segregation: Will Vietnam Meet the Sdgs for Equitable Development?

Rapid Economic Growth But Rising Poverty Segregation: Will Vietnam Meet the Sdgs for Equitable Development?

The dynamics of socio-economic segregation: What role do private schools play?

Although residential sorting along socio-economic lines has increased in many cities across Europe, few studies have examined what drives changes in segregation over time. This study looks at the role of school choice expansion in shaping patterns of spatial inequality. We adopt a longitudinal perspective and investigate how the increasing availability of private primary schools is related to the dynamics of socio-economic segregation in German cities. Drawing on a uniquely compiled data set for the years 2005 to 2014 that includes 74 large and medium-sized cities with over 3500 districts, we estimate linear panel regression models with city fixed effects. The analyses show that an increase in the share of private primary schools is associated with a decrease in the segregation of poverty in West German cities but not in East German ones. The association in West Germany is particularly pronounced in local contexts characterised by growing rates of poor residents and growing proportions of young children. Results imply that school choice availability may promote residential integration and at the same time reinforce school segregation.

The spatial reordering of poverty and crime: A study of Glasgow and Birmingham (United Kingdom), 2001/2 to 2015/16

Across developed polities, there is growing evidence of the spatial reordering of poverty and of its detrimental impact on the life chances of poorer people. This paper extends this body of research, via a comparative case study of two cities in the United Kingdom, by unravelling the interplay of policies shaping the changing morphology of poverty. It progresses to examine the significance of the changing centralisation and segregation of poverty on neighbourhood inequalities in the exposure to crime, probing the relevance of urban criminological tool sets to account for the spatial patterning of crime. It achieves this through interweaving fifteen years of data on poverty and police recorded crime with accounts of the policies and interventions that have sought to reshape and address their manifestation. Though the cities exhibit distinct trajectories, we find evidence of both the decentralisation of poverty and of decreasing segregation in contrast to previous studies. Poverty and crime patterns are converging in the neighbourhoods closest to, but less so in the neighbourhoods furthest away from, city centres. We discuss the relevance of these findings for research seeking to understand the spatial reordering of poverty and neighbourhood inequality in the exposure to crime.

A Downside of Increasing Human Capital: The Role of Higher Education in Poverty Segregation in U.S. Cities

City administrations often work hard to attract or retain college-educated residents. Research has consistently demonstrated that increased education in a city is associated with beneficial outcomes, making cities’ efforts to recruit and retain college-educated individuals logical. However, we challenge the notion that rising rates of education is a universal positive by investigating a potential downside of such efforts: poverty segregation. In this article, we ask, how does an increase in higher education rates affect poverty segregation and are all cities at equal risk of this harmful consequence? Using fixed-effects analyses of U.S. cities from 1990 to 2010 to test this relationship, our results show that an increase of college-educated residents is associated with increased poverty segregation. Yet, not all cities are affected equally. Cities with predominantly Black residents and more civil rights organizations have lower or reversed associations between higher education and poverty concentration, especially when the college-educated population is increasingly Black. Recruiting college-educated individuals may help some, while further worsening existing structural inequalities.

Socio-economic segregation in European cities. A comparative study of Brussels, Copenhagen, Amsterdam, Oslo and Stockholm

ABSTRACT The purpose of this study is to compare socioeconomic segregation patterns and levels in Brussels, Copenhagen, Amsterdam, Oslo, and Stockholm with uniform measurements. Previous research has been hampered by conceptual and methodological shortcomings. We use harmonized datasets containing geocoded indicators based on a nearest-neighbors approach. Our analyses offer an unprecedented comparison of patterns and levels of socio-spatial inequalities in European capitals at multiple scales. Using maps, segregation indices and percentile plots, we find that for all cities, the segregation of the rich is much stronger than the segregation of the poor. Macro-scale poverty segregation is most prominent in Stockholm and Brussels, and quite low in Amsterdam, while macro-scale affluence segregation is most pronounced in Oslo. At micro-scales, Brussels and Stockholm stand out with very high local poverty concentrations, indicating high levels of polarization. We interpret differences in the light of spatial inequalities, welfare regimes, housing systems, migration and area-based interventions.

Examining the Relationship Between Racialized Poverty Segregation and Hazardous Industrial Facilities in the U.S. Over Time

Scholars interested in understanding the unequal exposure to environmental harms by race and class have often relied on urban sociological theory. Specifically, the argument that the outmigration of middle-class Whites and African Americans from America’s industrial areas, and the decline in manufacturing employment in these communities, concentrated minority poverty around industrial sites. These nested, community-level, processes have not yet been measured as such in the environmental inequality literature. This article addresses this limitation by using spatial measures of poverty segregation between and within racial groups. Multilevel models are presented that examine how the density of industrial facilities is related to the economic health of a host tract, the broader economic context of the county, and the level of poverty segregation (both within and between racial/ethnic groups). Results demonstrate a spatial separation of the economic benefits and environmental harms across the United States, a pattern that has remained consistent over time.

Racial and Socioeconomic Test-Score Gaps in New England Metropolitan Areas: State School Aid and Poverty Segregation

Test-score data show that both low-income and racial-minority children score lower, on average, on states’ elementary-school accountability tests compared with higher-income children or white children. While different levels of scholastic achievement depend on a host of influences, such test-score gaps point toward unequal educational opportunity as a potentially important contributor. This report explores the relationship between racial and socioeconomic test-score gaps in New England metropolitan areas and two factors associated with unequal opportunity in education: state equalizing school-aid formulas and geographic segregation of low-income students. The underlying methods do not allow a strict causal interpretation; however, both aspects are strongly related to test-score gaps, with poverty segregation between school districts especially important in New England. The report first explores the degree to which state school aid is progressive, that is, distributed disproportionately to districts with high fractions of students living in poverty; more progressive distributions are associated with smaller test-score gaps in high-poverty metropolitan areas. All U.S. states distribute some state revenue to support local school districts, but the extent to which such aid is focused on districts with greater concentrations of poverty varies considerably. The relationships estimated in the empirical analysis suggest that New England metro areas with high average district poverty in states with more progressive aid distributions, such as Springfield, Massachusetts, should see somewhat smaller racial and socioeconomic test-score gaps than metro areas with lower district poverty in states with less progressive school aid, such as Burlington, Vermont; that predicted difference in white-Black test-score gaps amounts to about one-quarter of the actual difference between Springfield’s gap and Burlington’s gap. The second factor explored is poverty segregation; test-score gaps are larger in metropolitan areas where, compared with white children or higher-income children, minority children or low-income children go to school with, or are in school districts with, more students from low-income families. Partly because school districts (and cities and towns) are relatively small geographically in New England, poverty segregation in the region’s metropolitan areas is most pronounced between districts, not between schools within school districts. The sizes of the estimated relationships suggest that metro areas with the highest between-district poverty segregation, such as Bridgeport-Stamford-Norwalk, Connecticut, should have markedly larger test-score gaps than metro areas with moderate poverty segregation between districts, such as Manchester-Nashua, New Hampshire; those predicted differences amount to 60 percent to 90 percent of the actual test-score gap differences between the Bridgeport and Manchester metro areas. States can alter either or both of these factors via policy changes. States set the terms—and thereby the progressivity—of school-aid policy. Many states include cost adjustments in their aid formulas to offset some of the additional costs of educating students from low-income families, and some recent proposals (such as for Connecticut) or policy changes (such as in Massachusetts) involve more closely targeting state equalizing aid to high-poverty districts. State policy levers regarding between-district poverty segregation are less direct and potentially more controversial. Nonetheless, statewide affordable housing policies, such as those in Massachusetts and Rhode Island, if applied more comprehensively, might reduce concentrations of poverty and provide more low-income families access to the higher-quality schools in low-poverty suburban districts.

On the Relationship between Poverty Segregation and Homelessness in the American City and Suburb

Although existing scholarship notes that homelessness thrives in concentrated poverty, models estimating the association between the intensity of residential poverty segregation and local homelessness rates across communities remain absent from the literature. To fill this gap, the author considers this relationship for 272 homelessness Continuums of Care covering urban and suburban spaces spanning 43 states and the District of Columbia. Models suggest that poverty segregation is positively associated with the expected homelessness rate of a Continuum of Care, a relationship that remains significant when controlling for a range of established drivers of the condition. The author discusses this finding within a framework qualifying residential poverty segregation as both a cause and a consequence of the local prevalence of economic disadvantage that predicts homelessness via its relationship with disadvantage and unique spatial effects.

The Roles of State Aid and Local Conditions in Elementary School Test-Score Gaps

Equal educational opportunity is a core American value. Yet many children of low-income or minority racial or ethnic status attend public schools that are lower quality compared with those that white children or high-income children attend. And data indicate that, on average, low-income or minority children score lower on states’ elementary-school accountability tests compared with higher-income children or white children. Such test-score gaps serve as evidence of unequal educational opportunity. This study uses information from metropolitan areas and from school districts to understand which factors are strongly related to the size of racial and socioeconomic test-score gaps. One key factor is the degree to which state aid to school districts is distributed progressively—that is, distributed disproportionately to districts with high fractions of students living in poverty—with progressive distributions associated with smaller test-score gaps in high-poverty metros or districts. Second, test-score gaps are larger in metropolitan areas and districts where poverty segregation is greater, that is, where, compared with white children or higher-income children, minority children or low-income children go to school with, or are in school districts with, more students from low-income families.

Longitudinal Study of Socioeconomic Segregation Between Schools in the UK

The aim of this study is to understand the behavior of school segregation by socioeconomic level in the UK. To do this, all data from the United Kingdom are analyzed in the PISA Assessment from 2000 to 2015 and the Gorard index, Dissimilarity index, and the Isolation index are estimated. The analysis has shown that socio-economic segregation between schools has declined somewhat in the UK from 2000 to 2015, although the clustering of the 25% poorest of students remained relatively static since 2006. England remains more highly segregated by poverty than Wales, Scotland and Northern Ireland. The segregation levels of the 10% poorest student has declined in state-maintained schools but shown a sharp increase in private schools. The level of isolation of disadvantaged students is less in state-maintained schools than private schools. The findings show that poverty segregation trends using PISA data match with segregation trends previously analysed using the national datasets using only state-maintained schools for England. This finding leads to research implications for a detailed analysis of national school segregation trends, including student data from private school.

Is discrimination a driving force behind the over-representation of children with an immigrant background in Swedish out-of-home care? A quantitative study from Stockholm City

ABSTRACT To research potential discrimination in concluding decisions of child-welfare investigations, i.e. to place children into out-of-home care or let them remain at home while providing services, this study applies logistic regression to a random sample of 132 (n = 132) investigations conducted by Stockholm City, Sweden, in 2014. First, the risk of entry into care associated with a set of practice-related factors was estimated. Second, the interactions between the significant factors and having first or second-generation immigrant background from outside of Europe was estimated using interaction terms. All interactions were insignificant: Lone parenting: OR = 0.301, 95% CI: 0.052–1.737; Number of reporters: OR:0.405, 95% CI: 0.082–1.964; Social problems in the child: OR = 0.788, 95 CI: 0.140–4.706; Neglect: OR = 2.210, 95% CI: 0.239–27.327; Number of social problems in the parent(s): OR = 2.209, 95% CI: 0.797–8.184; Previous placement: OR = 0.236, 95% CI: 0.017–2.950. Discrimination is therefore not indicated by the results. The large over-representation of immigrant children in Swedish out-of-home care is therefore more likely driven by disproportionate exposure to common risk factors for child welfare involvement (cf. Drake et al., 2011. Racial bias in child protection? A comparison of competing explanations using national data. Pediatrics, 127(3), 471–478. https://doi.org/10.1542/peds.2010-1710). Poor housing conditions, poverty and neighbourhood segregation are of relevance for Stockholm City.

RACIAL RESIDENTIAL SEGREGATION AND COGNITIVE DECLINE AMONG OLDER ADULTS

Racial residential segregation may be a fundamental cause of health disparities in the U.S., and few studies employ objective measures of segregation to estimate its impacts on cognitive decline. Using data from 21,446 REGARDS participants in urban areas, we employed race-stratified growth curve models to examine how city racial segregation was associated with trajectories of cognitive decline over time. Controlling for demographics and health conditions/behaviors, higher segregation for blacks was marginally associated with lower cognitive function at baseline (b=-0.159, p<.10) while higher segregation for whites was associated with better cognitive function (b=0.158, p<.01). For both blacks and whites, there were no significant associations between segregation and rate of cognitive decline but neighborhood poverty was adversely related to cognitive function (b=-0.171, p<.01 for blacks, b=-0.289, p<.001 for whites). Further research into mechanisms that contributes to heterogeneity in associations between racial segregation and cognitive function is needed to develop effective prevention interventions.

Government, poverty and corruption in Haiti. Critical reflections on two social programs, brain drain and destination countries

This article aims to make a critical analysis of the performance of the last Haitian governments as well as the factors that contribute to the rise of extreme poverty in the country. It shows that corruption has a role in the violation of human rights, extreme poverty and social segregation, socioeconomic inequality, institutional mistrust and the lack of productivity of work whose situation results in the massive displacement and the brain drain of Haitians, although remittances remain the main economic source of families but also influence the national economy. Similarly, the impact of the two main social programs for combating poverty is questioned. At the end of the work, the results of the research carried out in northeast and northwest, as well as the countries most wanted by this group of Haitians to migrate, are presented. As a qualitative research, the focus groups methodology was used to gather information, perception and evaluate the study instrument. As a result, a semi-structured survey was used using a questionnaire with open and half open questions, and a structured technique as a tool for evaluating and compiling research data. Also, the participant observation allowed us to understand the daily life and the attitude of the interviewees.

Abstract 041: Perceived and Objective Characteristics of the Neighborhood Environment Are Associated With Accelerometer Measured Sedentary Time and Physical Activity, the CARDIA Study

Introduction: Growing evidence suggests that features of the neighborhood environment are associated with moderate to vigorous intensity physical activity (MVPA). Less is known about whether the neighborhood environment is associated with sedentary time (SED) or light-intensity physical activity (LPA), two emerging, independent risk factors for adverse health outcomes. Objective: To investigate the cross-sectional and longitudinal associations of perceived and objective characteristics of the neighborhood environment with accelerometer-measured SED, LPA, and MVPA. Methods: Participants were 2,120 men and women from the Coronary Artery Risk Development in Young Adults (CARDIA) study who took part in the year 20 (2005-2006, aged 38-50 years) and year 30 exams (2015-2016, aged 48-60 years). Characteristics of the neighborhood environment assessed at year 20 included self-reported neighborhood cohesion, self-reported resources for physical activity, and objectively-measured neighborhood poverty and racial residential segregation using geocoded addresses linked to U.S. Census data. Physical activity was measured by accelerometer at year 20 in the full sample, and at year 30 in a sub-sample (n=892). Multivariable linear regression models examined cross-sectional associations of neighborhood measures at year 20 with SED, LPA, and MVPA assessed that year, and with 10-year changes in SED, LPA, and MVPA. Differences by race and sex group were also examined. Results: In cross-sectional analyses, each one standard deviation increase in the neighborhood cohesion score was associated with 4.1 less SED minutes/day (95% CI: -8.0, -0.2, p=0.04), and 4.5 more LPA minutes/day (95% CI: 0.9, 8.0, p=0.01). Each one standard deviation increase in the neighborhood resources score was associated with 1.2 more MVPA minutes/day (95% CI: 0.1, 2.3, p=0.04). A one standard deviation increase in neighborhood poverty was associated with 11.1 less SED minutes/day (95% CI: -21.2, -1.2, p=0.03) and 10.6 more LPA minutes/day (95% CI: 1.8, 19.4, p=0.02), among black men only. None of the neighborhood characteristics were associated with 10-year changes in activity in the full study sample; however, each one standard deviation increase in the neighborhood cohesion score was associated with a 10-year decrease of 25.4 SED minutes/day (95% CI: -46.7, -4.1, p=0.02) and a 10-year increase of 19.0 LPA minutes/day (95% CI: 1.9, 36.1, p=0.03), among black men only. Conclusions: Higher neighborhood cohesion and resources were beneficially associated with accelerometer-measured activity in cross-sectional analyses; however, neighborhood characteristics did not associate with 10-year changes in activity. Differences were observed by race and sex, with more robust findings observed in black men for neighborhood poverty and cohesion.

Determinants of Economic Segregation and Spatial Distribution of Poverty

Purpose - While many related prior studies have focused on the segregation by race and ethnicity, the academic interest in the separation of residence...

A multilevel structural equation modelling approach to study segregation of deprivation: an application to Bolivia

The study of segregation of deprivation can provide a tool to determine the economic, social and institutional factors associated with spatial unevenness in the distribution of wealth. Segregation is linked to social exclusion, diminished opportunities for human capital development and lower access to public services. In comparison to descriptive measures of poverty segregation, a multilevel structural equation modelling approach allows us to make statistical inferences about segregation, and to assess the extent to which segregation can be explained by contextual variables. Previous research using multilevel models to analyse segregation is extended to handle a continuous latent variable, measured by multiple binary indicators. The proposed approach is used to quantify the extent to which household deprivation is clustered within communities in Bolivia and to explore contextual factors associated with between-community differences in deprivation. Bolivia had one of the worst performances in poverty headcount ratio and chronic malnutrition in Latin America in the first decade of the twenty-first century, according to World Bank data. Bolivia is found to have a high level of segregation, since the main source of variation in deprivation arises from differences across communities, rather than within communities. Ethnicity, education, administrative region, distance to urban centres, and drought-induced migration significantly predict differences in the mean level of deprivation across Bolivian villages. This analysis helps to identify clusters of deprivation and highlights crucial sectors to be developed in order to reduce unevenness in the distribution of deprivation.

Dissecting income segregation: Impacts of concentrated affluence on segregation of poverty

ABSTRACTThis article investigates how income inequality shapes residential segregation by income. Using agent-based modeling, it develops a residential preferences model that is capable of generating results mimicking empirical income segregation patterns. Simulation analysis shows how varying income inequality produces differential residential mobility outcomes that alter income segregation profiles. The model is used to capture the distinct impacts of households’ moves into richer or poorer neighborhoods, and how these impacts are further differentiated with respect to the moving household’s income. The article demonstrates how aggregating such diverse outcomes of micro-level interactions at a meso-level can help us to better understand the changes in macro-level income segregation patterns. Analyzing residential mobility patterns carefully, the article suggests that i) segregation of affluence and of poverty can trigger each other via initiating cascades of residential mobility and housing prices, and ii) increasing income inequality can disrupt housing market and lead to shortages in affordable housing, which can yield high residential instability and eviction rates among the poorest stratum.

Not All Civic Action Is Equal: Two Forms of Civic Associations and Their Disparate Effects on Poverty and Poverty Segregation

This study specifies the relationship between civic associations and their effects on communities by analyzing how two forms of civic association—neighborhood development organizations and institution-based community organizing coalitions—impact poverty in neighborhoods and cities, and poverty segregation in cities. Some social scientists argue that civic associations are the key to well-functioning democracy, allowing people to collectively organize for the promotion of their common interests, but others argue that civic associations instead breed exclusion, leaving few communities in the position to reap their benefits. Results show that not all civic associations’ effects are equal. The form of civic association is vital in determining its effects. Place-based organizations help their neighborhoods, but not their cities, unless they are organizing in poor cities. Alternatively, identity-based organizations do not affect their neighborhood but do significantly decrease city-level poverty segregation. Longitudinal analyses of neighborhoods and cities from 1990 to 2010 provide evidence.

Comment – Income segregation in cities: A reflection on the gap between concept and measurement

[eng] In his study of twelve French metropolises, Jean-Michel Floch argues that the level of segregation, defined as the spatial separation of groups with different living standards within cities, is higher, in the city‑centres as well as the suburbs than in the outer-suburbs. It is also more marked in the higher living standards. This commentary argues that income segregation in French cities is low for international standards. Based on issues around the measurement . and comparability of income segregation indices, it elaborates on three issues. The first is that, contrary to popular belief, the segregation of poverty contributes little to overall city segregation, while the segregation of affluence as a large contributor remains under-debated. The second is that an empirical or normative benchmark for segregation is needed to frame the discussion around “ too much” segregation. The third is that the actual degree of physical disconnection between income groups, and between income groups and city amenities and services, is not truly measured by current income segregation measures, limiting the usefulness of such measures for policy designs.

The Role of Contextual Socioeconomic Circumstances and Neighborhood Poverty Segregation on Mortality in 4 European Cities.

Several studies have recognized the health disadvantage of residents in socioeconomically deprived neighborhoods, independent of the influence of individual socioeconomic conditions. The effect of neighborhood socioeconomic deprivation on general mortality has appeared heterogeneous among the cities analyzed: the underlying mechanisms have been less empirically explored, and explanations for this heterogeneous health effect remain unclear. The present study aimed to: (1) analyze the distribution of socioeconomically disadvantaged persons in neighborhoods of 4 European cities-Turin, Barcelona, Stockholm and Helsinki-trying to measure segregation of residents according to their socioeconomic conditions. Two measuring approaches were used, respectively, through dissimilarity index and clustering estimated from Bayesian models. (2) Analyze the distribution of mortality in the above mentioned cities, trying to disentangle the independent effects of both neighborhood socioeconomic deprivation and neighborhood segregation of residents according to their socioeconomic conditions, using multilevel models. A significantly higher risk of death was observed among residents in more deprived neighborhoods in all 4 cities considered, slightly heterogeneous across them. Poverty segregation appeared to be slightly associated with increasing mortality in Turin and, among females and only according to dissimilarity, in Barcelona. Few studies have explored the health effects of social clustering, and results could inform urban policy design with regard to social mix.