This study examines how neighborhood status and individual status jointly shape geographic mobility in the United States. Drawing on restricted-use American Community Survey data, we conceptualize neighborhood status as the relative standing of a census tract's median family income compared to demographically similar reference neighborhoods, and individual status as a household's relative income rank within its tract. Building on comparison theory and status inconsistency perspectives, we test whether mismatches between neighborhood and individual status influence short-distance (within-county) and long-distance (between-county) mobility. Multinomial logistic models reveal that disadvantaged neighborhood status increases within-county mobility, particularly when paired with high individual status, supporting spatial assimilation arguments. Conversely, low individual status in high-status neighborhoods heightens mobility, consistent with relative deprivation theory rather than status signaling. Results suggest that status inconsistency plays a central role in residential decision-making and that neighborhood status primarily affects short-distance mobility. The findings advance research on stratification and internal migration by integrating relative contextual and positional mechanisms.
-
Neighborhood Racial Status and White Out-Mobility
March 2026
Working Paper Number:
CES-26-19
Drawing on American Community Survey data, this study examines how whites' relative socioeconomic standing vis-'-vis nonwhite neighbors affects the association between minority presence and white out-mobility. Moving beyond the racial preferences versus racial proxy debate, we integrate group competition and contact theories with status theory to conceptualize 'racial status' as whites' first-order income rank relative to the subgroup status of Black, Hispanic, and Asian residents at the census tract level. Multilevel linear probability models show that whites lacking advantaged status are generally more likely to move. However, the positive association between Black or Asian concentration and white departure is weaker among status-disadvantaged whites, while the negative association with Hispanic concentration is stronger. These patterns lend greater support to contact theory than to group competition theory. By foregrounding relative status, the study demonstrates that racial and socioeconomic mechanisms are intertwined in shaping white residential mobility.
View Full
Paper PDF
-
Whose Neighborhood Now? Gentrification and Community Life in Low-Income Urban Neighborhoods
June 2024
Working Paper Number:
CES-24-29
Gentrification is a process of urban change that has wide-ranging social and political impacts, but previous studies provide divergent findings. Does gentrification leave residents feeling alienated, or does it bolster neighborhood social satisfaction? Politically, does urban change mobilize residents, or leave them disengaged? I assess a national, cross-sectional sample of about 17,500 respondents in lower-income urban neighborhoods, and use a structural equation modeling approach to model six latent variables pertaining to local social environment and political participation. Amongst the full sample, gentrification has a positive association with all six factors. However, this relationship depends upon respondents' level of income, length of residency, and racial identity. White residents and those with shorter length of residency report higher levels of social cohesion as gentrification increases, but there is no such association amongst racial minority groups and longer-term residents. This finding aligns with a perspective on gentrification as a racialized process, and demonstrates that gentrification-related amenities primarily serve the interests of white residents and newcomers. All groups, however, are more likely to participate in neighborhood politics as gentrification increases, drawing attention to the agency of local residents as they attempt to influence processes of urban change.
View Full
Paper PDF
-
Neighborhood Income and Material Hardship in the United States
January 2022
Working Paper Number:
CES-22-01
U.S. households face a number of economic challenges that affect their well-being. In this analysis we focus on the extent to which neighborhood economic conditions contribute to hardship. Specifically, using data from the 2008 and 2014 Survey of Income and Program Participation panel surveys and logistic regression, we analyze the extent to which neighborhoods income levels affect the likelihood of experiencing seven types of hardships, including trouble paying bills, medical need, food insecurity, housing hardship, ownership of basic consumer durables, neighborhood problems, and fear of crime. We find strong bivariate relationships between neighborhood income and all hardships, but for most hardships these are explained by other household characteristics, such as household income and education. However, neighborhood income retains a strong association with two hardships in particular even when controlling for a variety of other household characteristics: neighborhood conditions (such as the presence of trash and litter) and fear of crime. Our study highlights the importance of examining multiple measures when assessing well-being, and our findings are consistent with the notion that collective socialization and community-level structural features affect the likelihood that households experience deleterious neighborhood conditions and a fear of crime.
View Full
Paper PDF
-
Who Gentrifies Low Income Neighborhoods?
January 2008
Working Paper Number:
CES-08-02
This paper uses confidential Census data, specifically the 1990 and 2000 Census Long- Form data, to study the demographic processes underlying the gentrification of low income urban neighborhoods during the 1990's. In contrast to previous studies, the analysis is conducted at the more refined census-tract level with a narrower definition of gentrification and more narrowly defined comparison neighborhoods. The analysis is also richly disaggregated by demographic characteristic, uncovering differential patterns by race, education, age and family structure that would not have emerged in the more aggregate analysis in previous studies. The results provide little evidence of displacement of low-income non-white households in gentrifying neighborhoods. The bulk of the income gains in gentrifying neighborhoods are attributed to white college graduates and black high school graduates. It is the disproportionate in-migration of the former and the disproportionate retention and income gains of the latter that appear to be the main engines of gentrification.
View Full
Paper PDF
-
Individual Social Capital and Migration
March 2018
Working Paper Number:
CES-18-14
This paper determines how individual, relative to community social capital affects individual migration decisions. We make use of non-public data from the Social Capital Community Benchmark Survey to predict multi-dimensional social capital for observations in the Current Population Survey. We find evidence that individuals are much less likely to have moved to a community with average social capital levels lower than their own and that higher levels of community social capital act as positive pull-factor amenities. The importance of that amenity differs across urban/rural locations. We also confirm that higher individual social capital is a negative predictor of migration.
View Full
Paper PDF
-
Leaving Home: Modeling the Effect of Civic and Economic Structure on Individual Migration Patterns
June 2002
Working Paper Number:
CES-02-16
This research analyzes the effect of community structure upon individuals' probabilities of moving between 1985 and 1990. Using the full Census sample long form microdata for 1990, we re-allocate adult persons in 1990 to their 1985 county of residence. Then, using origin county macro-structural variables (derived from the Economic Census microdata) and individual characteristics (from Decennial Census microdata), we develop a two level hierarchical linear model. In level 1, we construct a logistic equation modeling individual probabilities of moving. In level 2, we model the contextual effects of origin community structure on these models. These contextual effects fall into two categories: 1) economic conditions that comprise the usual aggregate 'push' factors and 2) civic community factors that act to retain people in their community. Results specify the relationship between community context and individual migration patterns, and demonstrate effects of local economic structure and local civic structure on these individual probabilities. Most notably, we find that civic attributes of communities are associated with a propensity to stay in place, net of community economic factors and individual characteristics.
View Full
Paper PDF
-
Internal Migration in the U.S. During the COVID-19 Pandemic
September 2024
Working Paper Number:
CES-24-50
Survey and administrative internal migration data disagree on whether the COVID-19 pandemic increased or decreased mobility in the U.S. Moreover, though scholars have theorized and documented migration in response to environmental hazards and economic shocks, the novel conditions posed by a global pandemic make it difficult to hypothesize whether and how American migration might change as a result. We link individual-level data from the United States Postal Service's National Change of Address (NCOA) registry to American Community Survey (ACS) and Current Population Survey (CPS-ASEC) responses and other administrative records to document changes in the level, geography, and composition of migrant flows between 2019 and 2021. We find a 2% increase in address changes between 2019 and 2020, representing an additional 603,000 moves, driven primarily by young adults, earners at the extremes of the income distribution, and individuals (as opposed to families) moving over longer distances. Though the number of address changes returned to pre-pandemic levels in 2021, the pandemic-era geographic and compositional shifts in favor of longer distance moves away from the Pacific and Mid-Atlantic regions toward the South and in favor of younger, individual movers persisted. We also show that at least part of the disconnect between survey, media, and administrative/third-party migration data sources stems from the apparent misreporting of address changes on Census Bureau surveys. Among ACS and CPS-ASEC householders linked to NCOA data and filing a permanent change of address in their 1-year survey response reference period, only around 68% of ACS and 49% of CPS-ASEC householders also reported living in a different residence one year ago in their survey response.
View Full
Paper PDF
-
The Effect of Low-Income Housing on Neighborhood Mobility:
Evidence from Linked Micro-Data
May 2016
Working Paper Number:
carra-2016-02
While subsidized low-income housing construction provides affordable living conditions for poor households, many observers worry that building low-income housing in poor communities induces individuals to move to poor neighborhoods. We examine this issue using detailed, nationally representative microdata constructed from linked decennial censuses. Our analysis exploits exogenous variation in low-income housing supply induced by program eligibility rules for Low-Income Housing Tax Credits to estimate the effect of subsidized housing on neighborhood mobility patterns. The results indicate little evidence to suggest a causal effect of additional low-income housing construction on the characteristics of neighborhoods to which households move. This result is true for households across the income distribution, and supports the hypothesis that subsidized housing provides affordable living conditions without encouraging households to move to less-affluent neighborhoods than they would have otherwise.
View Full
Paper PDF
-
Who are the people in my neighborhood? The 'contextual fallacy' of measuring individual context with census geographies
February 2018
Working Paper Number:
CES-18-11
Scholars deploy census-based measures of neighborhood context throughout the social sciences and epidemiology. Decades of research confirm that variation in how individuals are aggregated into geographic units to create variables that control for social, economic or political contexts can dramatically alter analyses. While most researchers are aware of the problem, they have lacked the tools to determine its magnitude in the literature and in their own projects. By using confidential access to the complete 2010 U.S. Decennial Census, we are able to construct'for all persons in the US'individual-specific contexts, which we group according to the Census-assigned block, block group, and tract. We compare these individual-specific measures to the published statistics at each scale, and we then determine the magnitude of variation in context for an individual with respect to the published measures using a simple statistic, the standard deviation of individual context (SDIC). For three key measures (percent Black, percent Hispanic, and Entropy'a measure of ethno-racial diversity), we find that block-level Census statistics frequently do not capture the actual context of individuals within them. More problematic, we uncover systematic spatial patterns in the contextual variables at all three scales. Finally, we show that within-unit variation is greater in some parts of the country than in others. We publish county-level estimates of the SDIC statistics that enable scholars to assess whether mis-specification in context variables is likely to alter analytic findings when measured at any of the three common Census units.
View Full
Paper PDF
-
The Opportunities and Challenges of Linked IRS Administrative and Census Survey Records in the Study of Migration
July 2018
Working Paper Number:
carra-2018-06
This paper details efforts to link administrative records from the Internal Revenue Service (IRS) to American Community Survey (ACS) and 2010 Census microdata for the study of migration in the United States. Specifically, we (1) document our linkage strategy and methodology for inferring migration in IRS records; (2) model selection into and survival across IRS records to determine suitability for research applications; and (3) gauge the efficacy of the IRS records by demonstrating how they can be used to validate and potentially improve migration responses in ACS microdata. Our results show little evidence of selection or survival bias in the IRS records, suggesting broad generalizability to the nation as a whole. Moreover, we find that the combined IRS 1040, 1099, and W2 records may provide important information on populations that are hard to reach with traditional Census surveys. Finally, while preliminary, the results of our comparison of IRS and ACS migration responses shows that IRS records may be useful in improving ACS migration measurement for respondents whose migration response is proxy, allocated, or imputed. Taking these results together, we discuss the potential applications of our longitudinal IRS dataset to innovations in migration research in the United States.
View Full
Paper PDF