Using individual data from the restricted version of the American Community Survey, we examined the displacement locations of pre-Katrina adult residents of New Orleans in the year after the hurricane. Over half (53%) of adults had returned to'or remained in'the New Orleans metropolitan area, with just under one-third of the total returning to the dwelling in which they resided prior to Katrina. Among the remainder, Texas was the leading location with almost 40% of those living away from the metropolitan area (18% of the total), followed by other locations in Louisiana (12%), the South region of the US other than Louisiana and Texas (12%), and elsewhere in the U.S. (5%). Black adults were considerably more likely than nonblack adults to be living elsewhere in Louisiana, in Texas, and elsewhere in the South. The observed race disparity was not accounted for by any of the demographic or socioeconomic covariates in the multinomial logistic regression models. Consistent with hypothesized effects, we found that young adults (25'39 years of age) were more likely to move further away from New Orleans and that adults born outside Louisiana were substantially more likely to have relocated away from the state.
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RESIDENTIAL MOBILITY ACROSS LOCAL AREAS IN THE UNITED STATES AND THE GEOGRAPHIC DISTRIBUTION OF THE HEALTHY POPULATION
February 2014
Working Paper Number:
CES-14-14
Determining whether population dynamics provide competing explanations to place effects for observed geographic patterns of population health is critical for understanding health inequality. We focus on the working-age population where health disparities are greatest and analyze detailed data on residential mobility collected for the first time in the 2000 US census. Residential mobility over a 5-year period is frequent and selective, with some variation by race and gender. Even so, we find little evidence that mobility biases cross-sectional snapshots of local population health. Areas undergoing large or rapid population growth or decline may be exceptions. Overall, place of residence is an important health indicator; yet, the frequency of residential mobility raises questions of interpretation from etiological or policy perspectives, complicating simple understandings that residential exposures alone explain the association between place and health. Psychosocial stressors related to contingencies of social identity associated with being black, urban, or poor in the U.S. may also have adverse health impacts that track with structural location even with movement across residential areas.
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Black Pioneers, Intermetropolitan Movers, and Housing Desegregation
March 2016
Working Paper Number:
CES-16-23
In this project, we examine the mobility choices of black households between 1960 and 2000. We use household-level Decennial Census data geocoded down to the census tract level. Our results indicate that, for black households, one's status as an intermetropolitan migrant ' especially from an urban area outside the South ' is a powerful predictor of pioneering into a white neighborhood. Moreover, and perhaps even more importantly, the ratio of these intermetropolitan black arrivals to the incumbent metropolitan black population is a powerful predictor of whether a metropolitan area experiences substantial declines in housing segregation.
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Associations Between Public Housing and Individual Earnings in New Orleans
October 2015
Working Paper Number:
CES-15-32
This study uses a sample of the civilian labor force aged 16-64 constructed from the Decennial Census and American Community Survey, along with data from the HUD dataset Picture of Subsidized Households, to compare the likelihood for job earnings in relation to public housing developments in the New Orleans MSA before and after Hurricane Katrina. Results from a series of hierarchical linear models (HLM) indicate significant relationships are altered between time periods, including those from public and mixed-income developments, suggesting a fluid relationship between neighborhoods and economic outcomes during physical, demographic and economic restructuring.
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Estimating the U.S. Citizen Voting-Age Population (CVAP) Using Blended Survey Data, Administrative Record Data, and Modeling: Technical Report
April 2023
Authors:
J. David Brown,
Danielle H. Sandler,
Lawrence Warren,
Moises Yi,
Misty L. Heggeness,
Joseph L. Schafer,
Matthew Spence,
Marta Murray-Close,
Carl Lieberman,
Genevieve Denoeux,
Lauren Medina
Working Paper Number:
CES-23-21
This report develops a method using administrative records (AR) to fill in responses for nonresponding American Community Survey (ACS) housing units rather than adjusting survey weights to account for selection of a subset of nonresponding housing units for follow-up interviews and for nonresponse bias. The method also inserts AR and modeling in place of edits and imputations for ACS survey citizenship item nonresponses. We produce Citizen Voting-Age Population (CVAP) tabulations using this enhanced CVAP method and compare them to published estimates. The enhanced CVAP method produces a 0.74 percentage point lower citizen share, and it is 3.05 percentage points lower for voting-age Hispanics. The latter result can be partly explained by omissions of voting-age Hispanic noncitizens with unknown legal status from ACS household responses. Weight adjustments may be less effective at addressing nonresponse bias under those conditions.
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Using Restricted-Access ACS Data to Examine Economic and Noneconomic Factors of Interstate Migration By Race and Ethnicity
March 2023
Working Paper Number:
CES-23-12
We explore how determinants of internal migration differ between Black non-Hispanics, White non-Hispanics, and Hispanics using micro-level, restricted-use American Community Survey (ACS) data matched to data on attributes of sub-geographies down to the county level. This paper extends the discussion of internal migration in the U.S. by not only observing relationships between economic and noneconomic factors and household-level propensities to migrate, but also how these relationships differ across race and ethnicity within smaller geographies than have been explored in previous literature. We show that when controlling for household and location characteristics, minorities have a lower propensity to migrate than White households and document nuances in the responsiveness of internal migration to individual and locational attributes by racial and ethnic population subgroups.
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The Case of the Missing Ethnicity: Indians without Tribes in the 21st Century
June 2011
Working Paper Number:
CES-11-17
Among American Indians and Alaska Natives, most aspects of ethnicity are tightly associated with the person's tribal origins. Language, history, foods, land, and traditions differ among the hundreds of tribes indigenous to the United States. Why did almost one million of them fail to respond to the tribal affiliation part of the Census 2000 race question? We investigate four hypotheses about why one-third of multiracial American Indians and one-sixth of single-race American Indians did not report a tribe: (1) survey item non-response which undermines all fillin- the-blank questions, (2) a non-salient tribal identity, (3) a genealogy-based affiliation, and (4) mestizo identity which does not require a tribe. We use multivariate logistic regression models and high-density restricted-use Census 2000 data. We find support for the first two hypotheses and note that the predictors and results differ substantially for single race versus multiple race American Indians.
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Examining Racial Identity Responses Among People with Middle Eastern and North African Ancestry in the American Community Survey
March 2024
Working Paper Number:
CES-24-14
People with Middle Eastern and North African (MENA) backgrounds living in the United States are defined and classified as White by current Federal standards for race and ethnicity, yet many MENA people do not identify as White in surveys, such as those conducted by the U.S. Census Bureau. Instead, they often select 'Some Other Race', if it is provided, and write in MENA responses such as Arab, Iranian, or Middle Eastern. In processing survey data for public release, the Census Bureau classifies these responses as White in accordance with Federal guidance set by the U.S. Office of Management and Budget. Research that uses these edited public data relies on limited information on MENA people's racial identification. To address this limitation, we obtained unedited race responses in the nationally representative American Community Survey from 2005-2019 to better understand how people of MENA ancestry report their race. We also use these data to compare the demographic, cultural, socioeconomic, and contextual characteristics of MENA individuals who identify as White versus those who do not identify as White. We find that one in four MENA people do not select White alone as their racial identity, despite official guidance that defines 'White' as people having origins in any of the original peoples of Europe, the Middle East, or North Africa. A variety of individual and contextual factors are associated with this choice, and some of these factors operate differently for U.S.-born and foreign-born MENA people living in the United States.
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Dynamics of Race: Joining, Leaving, and Staying in the American Indian/Alaska Native Race Category between 2000 and 2010
August 2014
Working Paper Number:
carra-2014-10
Each census for decades has seen the American Indian and Alaska Native population increase substantially more than expected. Changes in racial reporting seem to play an important role in the observed net increases, though research has been hampered by data limitations. We address previously unanswerable questions about race response change among American Indian and Alaska Natives (hereafter 'American Indians') using uniquely-suited (but not nationally representative) linked data from the 2000 and 2010 decennial censuses (N = 3.1 million) and the 2006-2010 American Community Survey (N = 188,131). To what extent do people change responses to include or exclude American Indian? How are people who change responses similar to or different from those who do not? How are people who join a group similar to or different from those who leave it? We find considerable race response change by people in our data, especially by multiple-race and/or Hispanic American Indians. This turnover is hidden in cross-sectional comparisons because people joining the group are similar in number and characteristics to those who leave the group. People in our data who changed their race response to add or drop American Indian differ from those who kept the same race response in 2000 and 2010 and from those who moved between a single-race and multiple-race American Indian response. Those who consistently reported American Indian (including those who added or dropped another race response) were relatively likely to report a tribe, live in an American Indian area, report American Indian ancestry, and live in the West. There are significant differences between those who joined and those who left a specific American Indian response group, but poor model fit indicates general similarity between joiners and leavers. Response changes should be considered when conceptualizing and operationalizing 'the American Indian and Alaska Native population.'
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Receipt of Public and Private Food Assistance Across the Rural-Urban Continuum Before and During the COVID-19 Pandemic: Analysis of Current Population Survey Data
August 2025
Working Paper Number:
CES-25-51
Background: The nutrition safety net in the United States is critical to supporting food security among households in need. Food assistance in the United States includes both government-funded food programs and private community-based providers who distribute food to in need households. The COVID-19 pandemic impacted experiences of food security and use of private and public food assistance resources. However, this may have differed for households residing in urban versus rural areas. We explored receipt of Supplemental Nutrition Assistance Program (SNAP) benefits or food from community-based emergency food providers across a detailed measure of the rural-urban continuum before and during the COVID-19 pandemic.
Methods: We linked restricted use Current Population Survey Food Security Supplement data to census-tract level United States Department of Agriculture Rural-Urban Commuting Area codes to estimate prevalence of self-reported SNAP participation and receipt of emergency food support across temporal (2015-2019 versus 2020-2021) and socio-spatial (urban, large rural city/town, small rural town, or isolated rural town/area) dimensions. We report prevalences as point estimates with 95% confidence intervals, all weighted for national representation.
Results:
The weighted prevalence of self-reported SNAP participation was 8.9% (8.7-9.2%) in 2015-2019 and 9.1% (8.5-9.5%) in 2020-2021 in urban areas, 11.4% (10.8-12.2%) in 2015-2019 and 11.6% (10.5-12.9%) in 2020-2021 in large rural towns/cities, 13.4% (12.3-14.6%) in 2015-2019 and 12.3% (10.5-14.5%) in 2020-2021 in small rural towns, and 9.7% (8.6-10.9%) in 2015-2019 and 10.9% (8.8-13.4% )in 2020-2021 isolated rural towns. The weighted prevalence of self-reported receipt of emergency food was 4.9% (4.8-5.1%) in 2015-2019 and 6.2% (5.8-6.5%) in 2020-2021 in urban areas, 6.8% (6.2-7.4%) in 2015-2019 and 7.6% (6.6-8.6%) in 2020-2021 in large rural towns/cities, 8.1% (7.3-9.1%) in 2015-2019 and 7.1% (5.7-8.8%) in 2020-2021 in small rural towns, and 6.8% (5.9-7.7%) in 2015-2019 and 8.5% (6.7-10.6%) in 2020-2021 isolated rural towns.
Conclusion: Households in rural communities use public and private food assistance at higher rates than urban areas, but there is variation across communities depending on the level of rurality.
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The Census Historical Environmental Impacts Frame
October 2024
Working Paper Number:
CES-24-66
The Census Bureau's Environmental Impacts Frame (EIF) is a microdata infrastructure that combines individual-level information on residence, demographics, and economic characteristics with environmental amenities and hazards from 1999 through the present day. To better understand the long-run consequences and intergenerational effects of exposure to a changing environment, we expand the EIF by extending it backward to 1940. The Historical Environmental Impacts Frame (HEIF) combines the Census Bureau's historical administrative data, publicly available 1940 address information from the 1940 Decennial Census, and historical environmental data. This paper discusses the creation of the HEIF as well as the unique challenges that arise with using the Census Bureau's historical administrative data.
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