Inequality and Income Segregation in Brazilian cities: A Nationwide Analysis

Urban segregation has brought significant challenges to cities worldwide and has important implications for health. This study aimed to assess income segregation in the 152 largest Brazilian cities included in the SALURBAL Project and identify specific socioeconomic characteristics related to residential segregation by income. Using the Brazilian demographic census database of the year 2010, we calculated the income dissimilarity index (IDI) at census tract level for each SALURBAL city; subsequently comparing it with Gini and other local socioeconomic variables. We evaluated our results' robustness using a bootstrap correction to the IDI to examine the consequences of using different cut-offs of income that were relevant in the context of strong urban and regional inequalities. We identified a 2 minimum wages cut-off as the most appropriate and found little evidence of upward bias in the calculation of the IDI regardless of the cut-off used. Among the 10 most segregated cities, 9 are in the Northeast region, the region with the highest income inequality and poverty in Brazil. Our results indicate that the Gini index and poverty are the main variables associated with residential segregation, measured by the IDI. Social and environmental characteristics were also associated with IDI, reinforcing the notion that access to education, water, sanitation, and better residential conditions are fundamental to improving social equity.

The Reflection of Income Segregation and Accessibility Cleavages in Sydney’s House Prices

This paper explores the relationships between accessibility, income segregation, and house prices in the Greater Sydney Area. Sydney is found to have reasonably even employment accessibility, reflecting the increasingly polycentric nature of the modern city; however, it also shows considerable income segregation and variance in property prices between different parts of the city. Entropy is used to examine the diversity and mixing of different income groups. Finally, hedonic price models using ordinary least square and geographically-weighted regression techniques to show the differing effects of employment accessibility on house prices in different parts of the city. The results show that accessibility has small to negative effects on prices in the most valuable areas, suggesting that other effects such as recreational access and employment type/quality may be important to investigate further in this context.

Mobility patterns are associated with experienced income segregation in large US cities

Traditional understanding of urban income segregation is largely based on static coarse-grained residential patterns. However, these do not capture the income segregation experience implied by the rich social interactions that happen in places that may relate to individual choices, opportunities, and mobility behavior. Using a large-scale high-resolution mobility data set of 4.5 million mobile phone users and 1.1 million places in 11 large American cities, we show that income segregation experienced in places and by individuals can differ greatly even within close spatial proximity. To further understand these fine-grained income segregation patterns, we introduce a Schelling extension of a well-known mobility model, and show that experienced income segregation is associated with an individual’s tendency to explore new places (place exploration) as well as places with visitors from different income groups (social exploration). Interestingly, while the latter is more strongly associated with demographic characteristics, the former is more strongly associated with mobility behavioral variables. Our results suggest that mobility behavior plays an important role in experienced income segregation of individuals. To measure this form of income segregation, urban researchers should take into account mobility behavior and not only residential patterns.

Neighborhood Economic Change in an Era of Metropolitan Divergence

This study foregrounds the metropolitan area as a key driver of contemporary neighborhood economic change. The recent “Great Divergence” in metros’ economic, social, and political conditions suggests metros increasingly stratify neighborhood trajectories. Yet, many studies only consider neighborhood-level predictors of change or implicate metro-level factors more applicable to the twentieth century (e.g., manufacturing exposure) than the twenty first. To clarify the metro's contemporary role, this study synthesizes multiple literatures, deriving novel hypotheses that link metropolitan skill agglomeration and income segregation to neighborhood economic change, and then tests them using multilevel models and data drawn from multiple sources, including the census, Opportunity Insights, and National Transit Database. Analyses, based on all neighborhoods within 325 metros between 2000 and the mid-2010s, suggest over 10% of the variance in neighborhood median income change resides between, rather than within, metros. As predicted, metro skill agglomeration dynamics appear to boost neighborhoods’ median incomes, and metro income segregation depresses them. Results remain intact after accounting for state fixed effects and controls for five plausible alternative explanations of metro effects. Overall, the study provides a theoretical and empirical foundation for future neighborhood change research highlighting the metro in general, and two higher order spatial processes—income segregation and skill agglomeration—in particular.

Spatial income inequality in Toronto: a longitudinal study

This paper examines the trends and changes in both spatial and non-spatial income inequality in the Toronto CMA between 1985 and 2015 at various geographic scales, including both within and between neighbourhoods. Fixed effects panel regression models are used to uncover which local demographic and housing characteristics are most significant in explaining changes in inequality within neighbourhoods over time. Findings indicate that macro-scale income segregation among neighbourhoods has declined, while micro-scale intra-neighbourhood income segregation has increased since 1985. Further, compared to overall changes in income inequality in the region, neighbourhoods have become more homogenous in terms of their household income distribution. Thus, neighbourhood sorting by households based on income has increased since 1985. Consistent with extant literature, local housing characteristics have spillover effects on income segregation. Specifically, variables associated with greater housing affluence are negatively correlated with intra-neighbourhood inequality measures, and thus positively correlated with income homogenization. This confirms and adds to the literature that local land use regulations impact income spatial inequality. KEYWORDS Spatial Income Inequality; Segregation; Neighbourhoods; Toronto CMA; Fixed Effects Models; Quantitative Analysis; GIS; Housing Regulation

Spatial income inequality in Toronto: a longitudinal study

This paper examines the trends and changes in both spatial and non-spatial income inequality in the Toronto CMA between 1985 and 2015 at various geographic scales, including both within and between neighbourhoods. Fixed effects panel regression models are used to uncover which local demographic and housing characteristics are most significant in explaining changes in inequality within neighbourhoods over time. Findings indicate that macro-scale income segregation among neighbourhoods has declined, while micro-scale intra-neighbourhood income segregation has increased since 1985. Further, compared to overall changes in income inequality in the region, neighbourhoods have become more homogenous in terms of their household income distribution. Thus, neighbourhood sorting by households based on income has increased since 1985. Consistent with extant literature, local housing characteristics have spillover effects on income segregation. Specifically, variables associated with greater housing affluence are negatively correlated with intra-neighbourhood inequality measures, and thus positively correlated with income homogenization. This confirms and adds to the literature that local land use regulations impact income spatial inequality. KEYWORDS Spatial Income Inequality; Segregation; Neighbourhoods; Toronto CMA; Fixed Effects Models; Quantitative Analysis; GIS; Housing Regulation