METHODOLOGICAL ISSUES IN THE ANALYSIS OF RESIDENTIAL PREFERENCES, RESIDENTIAL MOBILITY, AND NEIGHBORHOOD CHANGE

Linking sequences of exposure to residential (dis)advantage, individual socioeconomic status, and health

Life course theories suggest that the relationship between residential (dis)advantage and health is best understood by examining the ordering and duration of cumulative exposures across the life course. This study employs sequence and cluster analysis on two decades of residential histories linked to the Survey of the Health of Wisconsin to define typologies of exposure to residential (dis)advantage and use these typologies to predict self-rated fair/poor health. Exposure to residential (dis)advantage is mostly stable across the adult life course and greater disadvantage predicts fair/poor health. Longitudinal exposures to residential (dis)advantage shape health independently of and in tandem with individual-level resources.

Preferences in the Design and Delivery of Neurodevelopmental Follow-Up Care for Children: A Systematic Review of Discrete Choice Experiments

Neurodevelopmental disorders are a significant cause of morbidity. Early detection of neurodevelopmental delay is essential for timely diagnosis and intervention, and it is therefore important to understand the preferences of parents and clinicians for engaging with neurodevelopmental surveillance and follow-up care. Discrete choice experiment (DCE) may be an appropriate method for quantifying these preferences. This review systematically examined how DCEs have been designed and delivered in studies examining neurodevelopmental care of children and identified the preferred attributes that have been reported. PubMed, Embase, CINAHL, and Scopus databases were systematically searched. Studies were included if they used DCE to elicit preferences for a neurodevelopmental follow-up program for children. Two independent reviewers conducted the title and abstract and full-text screening. Risk of bias was assessed using a DCE-specific checklist. Findings were presented using a narrative synthesis. A total of 6618 records were identified and 16 papers were included. Orthogonal (n=5) and efficient (n=5) experimental designs were common. There was inconsistent reporting of design-related features. Analysis was primarily completed using mixed logit (n=6) or multinomial logit (n=3) models. Several key attributes for neurodevelopmental follow-up care were identified including social, behavioral and emotional support, therapy, waiting time, and out-of-pocket costs. DCE has been successfully used as a preference elicitation method for neurodevelopmental-related care. There is scope for improvement in the design and analysis of DCE in this field. Nonetheless, attributes identified in these studies are likely to be important considerations in the design and implementation of programs for neurodevelopmental care.

What Would It Take to Desegregate U.S. Metropolitan Areas? Pathways to Residential Desegregation by Race

Patterns of household mobility across neighborhoods reproduce patterns of racial segregation at the metropolitan level. Substantial literature across the social sciences has explored the scale and predictors of household mobility as well as changes in metropolitan residential segregation over time. This study unifies these two strands of inquiry by connecting the sorting of households across neighborhoods to aggregate changes in segregation levels. Using discrete choice models of intrametropolitan mobility and restricted decennial census and American Community Survey data for 1960-2014, I model the correlates of household mobility and identify the counterfactual scenarios under which lower segregation levels can be achieved. The results show that even though the mobility flows of the White, Black, Hispanic, and Asian populations across census tracts have become more similar over time, U.S. metropolitan areas are far from experiencing large drops in segregation.

The Trojan-horse mechanism: How networks reduce gender segregation

The segregation of labor markets along ethnic and gender lines is socially highly consequential, and the social science literature has long viewed homophily and network-based job recruitments as some of its most crucial drivers. Here, we focus on a previously unidentified mechanism, the Trojan-horse mechanism, which, in contradiction to the main tenet of previous research, suggests that network-based recruitment reduce rather than increase segregation levels. We identify the conditions under which networks are desegregating, and using unique data on all individuals and all workplaces located in the Stockholm region during the years 2000-2017, we find strong empirical evidence for the Trojan-horse mechanism and its role in the gender segregation of labor markets.

Choice Set Formation in Residential Mobility and Its Implications for Segregation Dynamics

We develop and estimate a statistical model of neighborhood choice that draws on insights from cognitive science and decision theory as well as qualitative studies of housing search. The model allows for a sequential decision process and the possibility that people consider a small and selective subset of all potential destinations. When combined with data from the Los Angeles Family and Neighborhood Survey, our model reveals that affordability constraints and households' tendency toward short-distance moves lead blacks and Hispanics to have racially stratified choice sets in which their own group is disproportionately represented. We use an agent-based model to assess how racially stratified choice sets contribute to segregation outcomes. Our results show that cognitive decision strategies can amplify patterns of segregation and inequality.

Skill-Based Contextual Sorting: How Parental Cognition and Residential Mobility Produce Unequal Environments for Children

Highly skilled parents deploy distinct strategies to cultivate their children’s development, but little is known about how parental cognitive skills interact with metropolitan opportunity structures and residential mobility to shape a major domain of inequality in children’s lives: the neighborhood. We integrate multiple literatures to develop hypotheses on parental skill-based sorting by neighborhood socioeconomic status and public school test scores, which we test using an original follow-up of the Los Angeles Family and Neighborhood Survey. These data include more than a decade’s worth of residential histories for households with children that are linked to census, geographic information system, and educational administrative data. We construct discrete-choice models of neighborhood selection that account for heterogeneity among household types, incorporate the unique spatial structure of Los Angeles County, and include a wide range of neighborhood factors. The results show that parents’ cognitive skills interact with neighborhood socioeconomic status to predict residential selection after accounting for, and confirming, the expected influences of race, income, education, housing market conditions, and spatial proximity. Among parents in the upper/upper-middle class, cognitive skills predict sorting on average public school test scores rather than neighborhood socioeconomic status. Overall, we reveal skill-based contextual sorting as an overlooked driver of urban stratification.

Neighborhood change from the bottom Up: What are the determinants of social distance between new and prior residents?

An important source of neighborhood change occurs when there is a turnover in the housing unit due to residential mobility and the new residents differ from the prior residents based on socio-demographic characteristics (what we term social distance). Nonetheless, research has typically not asked which characteristics explain transitions with higher social distance based on a number of demographic dimensions. We explore this question using American Housing Survey data from 1985 to 2007, and focus on instances in which the prior household moved out and is replaced by a new household. We focus on four key characteristics for explaining this social distance: the type of housing unit, the age of the housing unit, the length of residence of the exiting household, and the crime and social disorder in the neighborhood. We find that transitions in the oldest housing units and for the longest tenured residents result in the greatest amount of social distance between new and prior residents, implying that these transitions are particularly important for fostering neighborhood socio-demographic change. The results imply micro-mechanisms at the household level that might help explain net change at the neighborhood level.

ESTIMATING MULTINOMIAL LOGIT MODELS WITH SAMPLES OF ALTERNATIVES

This comment reconsiders advice offered by Bruch and Mare regarding sampling choice sets in conditional logistic regression models of residential mobility. Contradicting Bruch and Mare's advice, past econometric research shows that no statistical correction is needed when using simple random sampling of unchosen alternatives to pare down respondents' choice sets. Using data on stated residential preferences contained in the Los Angeles portion of the Multi-City Study of Urban Inequality, it is shown that following Bruch and Mare's advice-to implement a statistical correction for simple random choice set sampling-leads to biased coefficient estimates. This bias is all but eliminated if the sampling correction is omitted.

Neighborhood Diversity, Neighborhood Affluence: An Analysis of the Neighborhood Destination Choices of Mixed-Race Couples With Children

Past research has indicated that mixed-race couples with children appear to possess a heightened preference for neighborhoods that are racially and ethnically diverse and relatively affluent so as to reside in areas that are requisitely accepting of, and safe for, their children. However, neighborhoods with higher racial and ethnic diversity tend to be lower in socioeconomic status, implying that some residentially mobile mixed-race couples with children encounter trade-offs between neighborhood diversity and neighborhood affluence in their residential search processes. To investigate this, we apply discrete-choice models to longitudinal data from the Panel Study of Income Dynamics linked to neighborhood-level data from multiple population censuses to compare the neighborhood choices of mixed-race couples with children to those of monoracial couples with children, while assessing how these choices are simultaneously driven by neighborhood diversity and neighborhood affluence. We observe that mixed-race couples with children tend to be more likely to choose higher-diversity neighborhoods than white couples with children, even when neighborhood affluence is allowed to determine the residential choices for these couples. Some higher-income mixed-race couples with children seemingly translate their resources into neighborhoods that are both diverse and affluent.

Choice modelling with Gaussian processes in the social sciences: A case study of neighbourhood choice in Stockholm

We present a non-parametric extension of the conditional logit model, using Gaussian process priors. The conditional logit model is used in quantitative social science for inferring interaction effects between personal features and choice characteristics from observations of individual multinomial decisions, such as where to live, which car to buy or which school to choose. The classic, parametric model presupposes a latent utility function that is a linear combination of choice characteristics and their interactions with personal features. This imposes strong and unrealistic constraints on the form of individuals' preferences. Extensions using non-linear basis functions derived from the original features can ameliorate this problem but at the cost of high model complexity and increased reliance on the user in model specification. In this paper we develop a non-parametric conditional logit model based on Gaussian process logit models. We demonstrate its application on housing choice data from over 50,000 moving households from the Stockholm area over a two year period to reveal complex homophilic patterns in income, ethnicity and parental status.

Influence of Proximity to Kin on Residential Mobility and Destination Choice: Examining Local Movers in Metropolitan Areas

A growing body of research has examined how family dynamics shape residential mobility, highlighting the social-as opposed to economic-drivers of mobility. However, few studies have examined kin ties as both push and pull factors in mobility processes or revealed how the influence of kin ties on mobility varies across sociodemographic groups. Using data on local residential moves from the Panel Study of Income Dynamics (PSID) from 1980 to 2013, we find that location of noncoresident kin influences the likelihood of moving out of the current neighborhood and the selection of a new destination neighborhood. Analyses of out-mobility reveal that parents and young adult children living near each other as well as low-income adult children living near parents are especially deterred from moving. Discrete-choice models of neighborhood selection indicate that movers are particularly drawn to neighborhoods close to aging parents, white and higher-income households tend to move close to parents and children, and lower-income households tend to move close to extended family. Our results highlight the social and economic trade-offs that households face when making residential mobility decisions, which have important implications for broader patterns of inequality in residential attainment.

Decision-Making Processes in Social Contexts

Over the past half-century, scholars in the interdisciplinary field of Judgment and Decision Making have amassed a trove of findings, theories, and prescriptions regarding the processes ordinary people enact when making choices. But this body of knowledge has had little influence on sociology. Sociological research on choice emphasizes how features of the social environment shape individual behavior, not people's underlying decision processes. Our aim in this article is to provide an overview of selected ideas, models, and data sources from decision research that can fuel new lines of inquiry on how socially situated actors navigate both everyday and major life choices. We also highlight opportunities and challenges for cross-fertilization between sociology and decision research that can allow the methods, findings, and contexts of each field to expand their joint range of inquiry.

Are there neighborhood effects on young adult neighborhood attainment? Evidence from mixed-logit models

Studies of racial residential attainment show an intergenerational transmission of racial contexts from youth to adulthood, but it is unclear why this transmission is so robust. It is possible that experiences in racial contexts during youth have lasting effects on neighborhood selection in adulthood, but evidence for this claim has come from research using statistical methods that suffer from problems of ecological dependence and conflation of other neighborhood characteristics. In this study, we address these limitations using mixed-logit models, a form of discrete choice analyses, allowing us to control for differences across metropolitan areas and for multiple characteristics of neighborhoods that may affect the selection of destination neighborhoods. Data for the analyses come from the National Educational Longitudinal Study, the 1990 and 2000 Censuses, and other sources. We find that most of the intergenerational process results from young adults moving to neighborhoods short distances from their origin ones, but the models also suggest a contextual effect of youth experiences in racial compositions on neighborhood selection. The latter finding indicates that policies promoting integration among youth can have long-lasting effects on residential attainment.

Why Did People Move During the Great Recession?: The Role of Economics in Migration Decisions

Labor migration offers an important mechanism to reallocate workers when there are regional differences in employment conditions. Whereas conventional wisdom suggests migration rates should increase during recessions as workers move out of areas that are hit hardest, initial evidence suggested that overall migration rates declined during the Great Recession, despite large regional differences in unemployment and growth rates. In this paper, we use data from the American Community Survey to analyze internal migration trends before and during the economic downturn. First, we find only a modest decline in the odds of adults leaving distressed labor market areas during the recession, which may result in part from challenges related to the housing price crash. Second, we estimate conditional logit models of destination choice for individuals who migrate across labor market areas and find a substantial effect of economic factors such as labor demand, unemployment, and housing values. We also estimate latent class conditional logit models that test whether there is heterogeneity in preferences for destination characteristics among migrants. Over all, the latent class models suggest that roughly equal percentages of migrants were motivated by economic factors before and during the recession. We conclude that fears of dramatic declines in labor migration seem to be unsubstantiated.

How do individual-level sociodemographics and neighbourhood-level characteristics influence residential location behaviour in the context of the food and built environment? Findings from 25 years of follow-up in the CARDIA Study

BACKGROUND

Little is known about how diet-related and activity-related amenities relate to residential location behaviour. Understanding these relationships is essential for addressing residential self-selection bias.

METHODS

Using 25 years (6 examinations) of data from the Coronary Artery Risk Development in Young Adults (CARDIA) study (n=11 013 observations) and linked neighbourhood-level data from the 4 CARDIA baseline cities (Birmingham, Alabama; Chicago, Illinois; Minneapolis, Minnesota; Oakland, California, USA), we characterised participants' neighbourhoods as having low, average or high road connectivity and amenities using non-hierarchical cluster analysis. We then used repeated measures multinomial logistic regression with random effects to examine the associations between individual-level sociodemographics and neighbourhood-level characteristics with residential neighbourhood types over the 25-year period, and whether these associations differed by individual-level income.

RESULTS

Being female was positively associated with living in neighbourhoods with low (vs high) road connectivity and activity-related and diet-related amenities among high-income individuals only. At all income levels, a higher percentage of neighbourhood white population and neighbourhood population <18 years were associated with living in neighbourhoods with low (vs high) connectivity and amenities. Individual-level race; age; and educational attainment, neighbourhood socioeconomic status and housing prices did not influence residential location behaviour related to neighbourhood connectivity and amenities at any income level.

CONCLUSIONS

Neighbourhood-level factors appeared to play a comparatively greater role in shaping residential location behaviour than individual-level sociodemographics. Our study is an important step in understanding how residential locational behaviour relates to amenities and physical activity opportunities, and may help mitigate residential self-selection bias in built environment studies.

Illuminating the lifecourse of place in the longitudinal study of neighbourhoods and health

Place and health are inextricably entwined. Whilst insights have been gained into the associations between places, such as neighbourhoods, and health, the understanding of these relationships remains only partial. One of the reasons for this relates to time and change and the inter-relationships between the dynamic nature of both neighbourhoods and health. This paper argues that the lifecourse of place can be used as a conceptual framework to understand the evolution and ongoing development of neighbourhoods, and their impact on the geographies of health, past, present and future. Moreover, this paper discusses the capacity of a longitudinal form of enquiry - latent transition analysis - that is able to operationalise conceptual models of the lifecourse of place. To date, latent transition analysis has not been applied to the study of neighbourhoods and health. Drawing on research across a range of disciplines including developmental psychology, sociology, geography and epidemiology, this paper also considers praxis-based implications and recommendations for applications of latent transition analysis that aim to advance understanding of how neighbourhoods affect health in and over time.

Birds of a Feather: Social Bases of Neighborhood Formation in Newark, New Jersey, 1880

This study examines the bases of residential segregation in a late nineteenth century American city, recognizing the strong tendency toward homophily within neighborhoods. Our primary question is how ethnicity, social class, nativity, and family composition affect where people live. Segregation is usually studied one dimension at a time, but these social differences are interrelated, and thus a multivariate approach is needed to understand their effects. We find that ethnicity is the main basis of local residential sorting, while occupational standing and, to a lesser degree, family life cycle and nativity also are significant. A second concern is the geographic scale of neighborhoods: in this study, the geographic area within which the characteristics of potential neighbors matter in locational outcomes of individuals. Studies of segregation typically use a single spatial scale, often one determined by the availability of administrative data. We take advantage of a unique data set containing the address and geo-referenced location of every resident. We conclude that it is the most local scale that offers the best prediction of people's similarity to their neighbors. Adding information at larger scales minimally improves prediction of the person's location. The 1880 neighborhoods of Newark, New Jersey, were formed as individuals located themselves among similar neighbors on a single street segment.

AGENT-BASED MODELS IN EMPIRICAL SOCIAL RESEARCH

Agent-based modeling has become increasingly popular in recent years, but there is still no codified set of recommendations or practices for how to use these models within a program of empirical research. This article provides ideas and practical guidelines drawn from sociology, biology, computer science, epidemiology, and statistics. We first discuss the motivations for using agent-based models in both basic science and policy-oriented social research. Next, we provide an overview of methods and strategies for incorporating data on behavior and populations into agent-based models, and review techniques for validating and testing the sensitivity of agent-based models. We close with suggested directions for future research.

How population structure shapes neighborhood segregation

This study provides a framework for understanding how population composition conditions the relationship between individuals' choices about group affiliation and aggregate patterns of social separation or integration. The substantive focus is the role of income inequality in racial residential segregation. The author identifies three population parameters--between-group inequality, within-group inequality, and relative group size--that determine how income inequality between race groups affects racial segregation. She uses data from the Panel Study of Income Dynamics to estimate models of individual-level residential mobility and incorporates these estimates into agent-based models. She then simulates segregation dynamics under alternative assumptions about (1) the relative size of minority groups and (2) the degree of correlation between race and income among individuals. The author finds that income inequality can have offsetting effects at the high and low ends of the income distribution. She demonstrates the empirical relevance of the simulation results using fixed-effects, metro-level regressions applied to 1980-2000 U.S. census data.