This article examines the characteristics of residents moving into new rail transit neighborhoods using longitudinal, individual‐level data from the Housing Mortgage Disclosure Act. To disentangle the role of transit from other neighborhood amenities that may give rise to shifts in the socioeconomic or demographic profile of homebuyers, an exploratory text analysis is first performed on property advertisements in transit‐adjacent neighborhoods. This informs the creation of variables for our models that estimate the probability of an applicant applying for a loan by race and income, and highlights where light rail is most prominently advertised as an amenity. We do not find that the announcement of a new light rail line significantly alters the income profile of loan applicants. Rather, proximity to the center city is a more important determinant in attracting higher income applicants. We do find that the announcement of the transit line is significant in explaining changes in the racial profile of applicants. Postannouncement, White applicants are significantly more likely to apply for loans in transit‐adjacent neighborhoods, while Blacks are significantly less likely to. As for other amenities, the walkability of a neighborhood is significant in predicting where White applicants are more likely to apply for home purchase loans.
more »
« less
New rail transit stations and the out-migration of low-income residents
This article tests the hypothesis that low-income residents disproportionately move out of neighbourhoods in close proximity to new rail transit stations. This transit-induced gentrification scenario posits that the development of rail transit will place an upward pressure on land and housing values and that higher-income residents will outbid low-income residents for this new amenity. The most transit-dependent population may therefore be displaced from the most accessible locations, forming a paradox in the investment in new transit systems. We test this hypothesis using the Panel Study on Income Dynamics (PSID) dataset to trace the out-migration of residents across the United States from census tracts within five years of the opening of a new station, between 1970 and 2014. We find that low-income individuals are more likely to move, regardless of their neighbourhood. However, we do not find significant evidence that low-income individuals are more likely to move out of transit neighbourhoods, after controlling for both individual and other neighbourhood characteristics. The odds of moving out of a transit neighbourhood for low-income residents is statistically insignificant. In other words, they do not have a heightened probability of leaving new transit neighbourhoods compared with other residents. Our results are robust across decades, when examining renters alone, for different time spans and for varying definitions of transit neighbourhoods. We further find that those living in transit neighbourhoods are not more likely to live in a crowded dwelling. Our results therefore suggest that, on average, across the nation, low-income residents do not disproportionately exit new transit neighbourhoods.
more »
« less
- Award ID(s):
- 1759714
- PAR ID:
- 10547549
- Publisher / Repository:
- SAGE Publications
- Date Published:
- Journal Name:
- Urban Studies
- Volume:
- 57
- Issue:
- 1
- ISSN:
- 0042-0980
- Format(s):
- Medium: X Size: p. 134-151
- Size(s):
- p. 134-151
- Sponsoring Org:
- National Science Foundation
More Like this
-
-
In this paper we move away from a static view of neighbourhood inequality and investigate the dynamics of neighbourhood economic status, which ties together spatial income inequality at different moments in time. Using census data from three decades (1980–2010) in 294 metropolitan statistical areas, we use a statistical decomposition method to unpack the aggregate spatiotemporal income dynamic into its contributing components: stability, growth and polarisation, providing a new look at the economic fortunes of diverse neighbourhoods. We examine the relative strength of each component in driving the overall pattern, in addition to whether, how, and why these forces wax and wane across space and over time. Our results show that over the long run, growth is a dominant form of change across all metros, but there is a very clear decline in its prominence over time. Further, we find a growing positive relationship between the components of dispersion and growth, in a reversal of prior trends. Looking across metro areas, we find temporal heterogeneity has been driven by different socioeconomic factors over time (such as sectoral growth in certain decades), and that these relationships vary enormously with geography and time. Together these findings suggest a high level of temporal heterogeneity in neighbourhood income dynamics, a phenomenon which remains largely unexplored in the current literature. There is no universal law governing the changing economic status of neighbourhoods in the US over the last 40 years, and our work demonstrates the importance of considering shifting dynamics over multiple spatial and temporal scales.more » « less
-
Abstract A long-standing expectation is that large, dense and cosmopolitan areas support socioeconomic mixing and exposure among diverse individuals1–6. Assessing this hypothesis has been difficult because previous measures of socioeconomic mixing have relied on static residential housing data rather than real-life exposures among people at work, in places of leisure and in home neighbourhoods7,8. Here we develop a measure of exposure segregation that captures the socioeconomic diversity of these everyday encounters. Using mobile phone mobility data to represent 1.6 billion real-world exposures among 9.6 million people in the United States, we measure exposure segregation across 382 metropolitan statistical areas (MSAs) and 2,829 counties. We find that exposure segregation is 67% higher in the ten largest MSAs than in small MSAs with fewer than 100,000 residents. This means that, contrary to expectations, residents of large cosmopolitan areas have less exposure to a socioeconomically diverse range of individuals. Second, we find that the increased socioeconomic segregation in large cities arises because they offer a greater choice of differentiated spaces targeted to specific socioeconomic groups. Third, we find that this segregation-increasing effect is countered when a city’s hubs (such as shopping centres) are positioned to bridge diverse neighbourhoods and therefore attract people of all socioeconomic statuses. Our findings challenge a long-standing conjecture in human geography and highlight how urban design can both prevent and facilitate encounters among diverse individuals.more » « less
-
Abstract We explore the impact of rising incomes at the top of the distribution on spatial sorting patterns within large U.S. cities. We develop and quantify a spatial model of a city with heterogeneous agents and non-homothetic preferences for neighbourhoods with endogenous amenity quality. As the rich get richer, demand increases for the high-quality amenities available in downtown neighbourhoods. Rising demand drives up house prices and spurs the development of higher quality neighbourhoods downtown. This gentrification of downtowns makes poor incumbents worse off, as they are either displaced to the suburbs or pay higher rents for amenities that they do not value as much. We quantify the corresponding impact on well-being inequality. Through the lens of the quantified model, the change in the income distribution between 1990 and 2014 led to neighbourhood change and spatial resorting within urban areas that increased the welfare of richer households relative to that of poorer households, above and beyond rising nominal income inequality.more » « less
-
Inadequate water access is central to the experience of urban inequality across low- and middle-income countries and leads to adverse health and social outcomes. Previous literature on water inequality in Mumbai, India’s second-largest city, offers diverse explanations for water disparities between and within slums. This study provides new insights on water disparities in Mumbai’s slums by evaluating the influence of legal status on water access. We analysed data from 593 households in Mandala, a slum with legally recognized (notified) and unrecognized (non-notified) neighbourhoods. Households in a non-notified neighbourhood suffered relative disadvantages in water infrastructure, accessibility, reliability and spending. Non-notified households also used significantly fewer litres per capita per day of water, even after controlling for religion and socioeconomic status. Findings suggest that legal exclusion may be a central driver of water inequality. Extending legal recognition to excluded slum settlements, neighbourhoods and households could be a powerful intervention for reducing urban water inequality.more » « less
An official website of the United States government
