Residential Mobility Dynamics Research Articles

Does gentrification constrain housing markets for low-income households? Evidence from household residential mobility in the New York and San Francisco metropolitan areas

This research investigates whether gentrification restricts housing markets for low-income households by focussing on the New York and San Francisco metropolitan areas from 2013 to 2019. We investigate whether gentrification correlates with increased out-migration and decreased in-migration of low-income residents in affected neighbourhoods, and how it shapes where out-movers relocate. We leverage a unique longitudinal dataset to compare two extreme regional contexts characterised by significant affordability challenges and intense housing regulations. By doing so, this study aims to provide a more refined understanding of gentrification and residential mobility dynamics, avoiding broad generalisations or a narrow focus on single metropolitan contexts. The findings indicate that in both regions, low-income households are indeed more likely to leave gentrifying neighbourhoods compared to non-gentrifying ones and less likely to enter them compared to higher-income households. The study also finds mixed results regarding the subsequent residential situations of these low-income movers. Based on these findings, we provide implications for research and policies oriented towards improving housing and neighbourhood access for low-income households in rapidly changing urban areas.

Predicting households’ residential mobility trajectories with geographically localized interpretable model-agnostic explanation (GLIME)

Human mobility analytics using artificial intelligence (AI) has gained significant attention with advancements in computational power and the availability of high-resolution spatial data. However, the application of deep learning in social sciences and human geography remains limited, primarily due to concerns with model explainability. In this study, we employ an explainable GeoAI approach called geographically localized interpretable model-agnostic explanation (GLIME) to explore human mobility patterns over large spatial and temporal extents. Specifically, we develop a two-layered long short-term memory (LSTM) model capable of predicting individual-level residential mobility patterns across the United States from 2012 to 2019. We leverage GLIME to provide geographical perspectives and interpret deep neural networks at the state level. The results reveal that GLIME enables spatially explicit interpretations of local impacts attributed to different variables. Our findings underscore the significance of considering path dependency in residential mobility dynamics. While the prediction of complex human spatial decision-making processes still presents challenges, this research demonstrates the utility of deep neural networks and explainable GeoAI to support human dynamics understanding. It sets the stage for further finely tuned investigations in the future, promising deep insights into intricate mobility phenomena.

Moving away from opportunity? Social networks and access to social services

Strong social connections often deter residential mobility beyond reach of the social network. A missing link in the body of research on this subject is the significance of the role of social networks in pooling resources for costly services and neighbourhood-level access to social services. Few have explored whether assistance from local social service agencies may substitute for practical help from social networks, thereby enabling low-income assisted renters to locate housing in more desirable neighbourhoods. Relying on data from the Moving to Opportunity experiment, this article examines the impact of social networks and social services on the dynamics of residential mobility. I find that the existence of social networks in the place movers left behind tends to increase the likelihood of moving back, but this likelihood varies with current access to social service providers and distance moved. These findings suggest that policy efforts in spatial dispersion of poverty should pay close attention to the geography of social services.

¿Seleccionan las ciudades a su población? Tendencias de selectividad residencial en las cabeceras metropolitanas andaluzas

After the generalization of metropolitan processes and the recent specialization in the new services economy, inner-cities are undergoing a process of socio-demographic reconfiguration, according to which certain groups are attracted to them, while others are progressively displaced to the Metropolitan peripheries, extrapolating the spatial social division on a metropolitan scale. The objective of the present work is to delve into the role played by the dynamics of residential mobility in this process, in order to know if inner-cities select in some way the inhabitants. To do this we will use the data from the 2011 Census for Andalusia, of which we own a particular explotation wich include a delimitation of the metropolitan areas that allows defining different residential mobility flows with origin and destination in the cities. Our objective is to analyze, through two multinomial logistic regression models, the propensity of individuals, according to their characteristics, to perform each of the movements contemplated, in order to approach the factors of attraction and repulsion of inner-cities. Among the main findings of the work we show that, although incipient, already exist trends that allow us to talk about a certain inner-cities residential selectivity.

Generadores y transversalidad del discurso sobre inmigración en el ámbito metropolitano de Sevilla

Problems related to immigrant integration reveal the importance of developing a holistic analysis of the underlying dynamics of residential mobility, segregation and integration. In this sense, aspects such as discourse analysis can represent an important contribution to both the analysis of causes and consequences of residential segregation, as to a proper design of inclusive immigration public policy. Through a qualitative analysis, this study focuses on the development of a social discourse, along with its expansion and effects on immigration in Seville´s Metropolitan Area. The results show that, despite the important role of the media in the diffusion of this speech, other factors such as the vision of residents and former residents, or occasional travel, should be taken into account to understand how immigration imaginary and the role it plays in the integration and residential segregation, is built.

Modelling the Spatial Nature of Household Residential Mobility within Municipalities in Colombia

In this paper, we examine household residential mobility within Colombian municipalities and determine whether the factors that trigger residential movement vary across the country. Using Geographically Weighted Regression (GWR) and detailed data from the 2005 Census for all municipalities in Colombia, our analysis takes into account the spatial variation in the relationship between household residential mobility and the associated housing, socioeconomic and environmental factors derived from theory and previous empirical research. Our findings demonstrate that household residential mobility is strongly and positively associated with living conditions, age and income, and negatively associated with homeownership and household composition within municipalities. The comparison of global (Ordinary Least Squares regression) and local (GWR) parameter estimates reveals the presence of a non-stationary effect on household residential mobility for the predictor variables considered, and highlights the importance of local variation of the relationships. In addition to contributing to the debate on the dynamics of residential mobility in Colombia, the study results have implications for effective policy-making with regard to urban expansion and settlement of various groups.

Local Ethnic Composition and Natives’ and Immigrants’ Geographic Mobility in France, 1982–1999

This article provides empirical results on patterns of native and immigrant geographic mobility in France. Using longitudinal data, we measure mobility from one French municipality (commune) to another over time and estimate the effect of the initial municipality’s ethnic composition on the probability of moving out. These data allow us to use panel techniques to correct for biases related to selection based on geographic and individual unobservables. Our findings tend to discredit the hypothesis of a “white flight” pattern in residential mobility dynamics in France. Some evidence does show ethnic avoidance mechanisms in natives’ relocating. We also find a strong negative and highly robust effect of co-ethnics’ presence on immigrants’ geographic mobility.

A Disaggregate Model of Residential Mobility and Housing Choice

The independent but linked traditions of stock adjustment models of residential mobility and the hedonic theory of housing demand are brought together. The principal research findings of these traditions are reviewed an application of the random utility model to housing choice and mobility decisions is proposed and preliminary empirical results based on retrospective household surveys conducted in South Bend Indiana are reported. (authors)