Since the Great Recession, US policy and advocacy groups have sought to better understand its effect on a group of especially vulnerable young adults who are not enrolled in school or training programs and not participating in the labor market, so called 'disconnected youth.' This article distinguishes between disconnected youth and unemployed youth and examines the spatial clustering of these two groups across counties in the US. The focus is to ascertain whether there are differences in underlying contextual factors among groups of counties that are mutually exclusive and spatially disparate (non-adjacent), comprising two types of spatial clusters ' high rates of disconnected youth and high rates of unemployed youth. Using restricted, household-level census data inside the Census Research Data Center (RDC) under special permission by the US Census Bureau, we were able to define these two groups using detailed household questionnaires that are not available to researchers outside the RDC. The geospatial patterns in the two types of clusters suggest that places with high concentrations of disconnected youth are distinctly different in terms of underlying characteristics from places with high concentrations of unemployed youth. These differences include, among other things, arrests for synthetic drug production, enclaves of poor in rural areas, persistent poverty in areas, educational attainment in the populace, children in poverty, persons without health insurance, the
social capital index, and elders who receive disability benefits. This article provides some preliminary evidence regarding the social forces underlying the two types of observed geospatial clusters and discusses how they differ.
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Income Packaging and Economic Disconnection: Do Sources of Support Differ from Other Low-Income Women?
December 2013
Working Paper Number:
CES-13-61
Income packaging, or piecing together cash and non-cash resources from a variety of sources, is a common financial survival strategy among low-income women. This strategy is particularly important for economically disconnected women, who lack both employment income and public cash assistance receipt. Using data from the confidential Census Bureau versions of the Survey of Income and Program Participation, this study compares the use of public and private supports between disconnected and connected low-income women, controlling for differences in state welfare rules and county unemployment rates. Findings from bivariate comparisons and multilevel logistic regressions indicate that disconnected women utilize public non-cash supports at similar rates to connected women, but rely more heavily on private sources. Conclusions focus on the policy implications for outreach and program development.
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Using Small-Area Estimation (SAE) to Estimate Prevalence of Child Health Outcomes at the Census Regional-, State-, and County-Levels
November 2022
Working Paper Number:
CES-22-48
In this study, we implement small-area estimation to assess the prevalence of child health outcomes at the county, state, and regional levels, using national survey data.
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Neighborhood Effects on High-School Drop-Out Rates and Teenage Childbearing: Tests for Non-Linearities, Race-Specific Effects, Interactions with Family Characteristics, and Endogenous Causation using Geocoded California Census Microdata
May 2008
Working Paper Number:
CES-08-12
This paper examines the relationship between neighborhood characteristics and the likelihood that a youth will drop out of high school or have a child during the teenage years. Using a dataset that is uniquely wellsuited to the study of neighborhood effects, the impact of the neighborhood poverty rate and the percentage of professionals in the local labor force on youth outcomes in California is examined. The first section of the paper tests for non-linearities in the relationship between indicators of neighborhood distress and youth outcomes. Some evidence is found for a break-point at low levels of poverty. Suggestive but inconclusive evidence is also found for a second breakpoint, at very high levels of poverty, for African-American youth only. The second part of the paper examines interactions between family background characteristics and neighborhood effects, and finds that White youth are most sensitive to neighborhood effects, while the effect of parental education depends on the neighborhood measure in question. Among White youth, those from single-parent households are more vulnerable to neighborhood conditions. The third section of the paper finds that for White youth and Hispanic youth, the relevant neighborhood variables appear to be the own-race poverty rates and the percentage of professionals of youths' own race. The final section of the paper estimates a tract-fixed effects model, using the results from the third section to define multiple relevant poverty rates within each tract. The fixed-effects specification suggests that for White and Hispanic youth in California, neighborhood effects remain significant, even with the inclusion of controls for any unobserved family and neighborhood characteristics that are constant within tracts.
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Poverty Estimates for Places in the United States
September 2005
Working Paper Number:
CES-05-12
This paper first describes some historical poverty trends, overall and for demographic groups and broad locations within the U.S. from an ongoing household survey, and then presents some specific information on poverty for localities by size, from the most recent decennial census (2000). Rural poverty exceeded urban poverty in 1969 and 1979, but urban poverty in 1999 was higher than rural poverty. Non-metropolitan area poverty exceeded metropolitan area poverty in each of the four censuses, but within each of those areas, rural poverty is now less than urban poverty. Within metropolitan areas, poverty is highest for those in central cities. For urbanized areas (50,000 or more population), the poverty rate is lower as the area gets larger, with the exception of the very largest-sized areas. This higher poverty for the largest places is accounted for entirely by the higher poverty rate for the central city or cities in those urban agglomerations, as the poverty rates for the parts of the urbanized areas not in the central place continue to fall as the area itself gets larger. Some of the critical relationships affecting the poverty rate of places appear to be the location of certain types of people - female householders, non-citizens, people of color, and college graduates.
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Examining Multi-Level Correlates of Suicide by Merging NVDRS and ACS Data
January 2017
Working Paper Number:
CES-17-25
This paper describes a novel database and an associated suicide event prediction model that surmount longstanding barriers in suicide risk factor research. The database comingles person-level records from the National Violent Death Reporting System (NVDRS) and the American Community Survey (ACS) to establish a case-control study sample that includes all identified suicide cases, while faithfully reflecting general population sociodemographics, in sixteen USA states during the years 2005 2011. It supports a statistical model of individual suicide risk that accommodates person-level factors and the moderation of these factors by their community rates. Named the United States Multi-Level Suicide Data Set (US-MSDS), the database was developed outside the RDC laboratory using publicly available ACS microdata, and reconstructed inside the laboratory using restricted access ACS microdata. Analyses of the latter version yielded findings that largely amplified but also extended those obtained from analyses of the former. This experience shows that the analytic precision achievable using restricted access ACS data can play an important role in conducting social research, although it also indicates that publicly available ACS data have considerable value in conducting preliminary analyses and preparing to use an RDC laboratory. The database development strategy may interest scientists investigating sociodemographic risk factors for other types of low-frequency mortality.
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Federal-Local Partnerships on Immigration Law Enforcement: Are the Policies Effective in Reducing Violent Victimization?
April 2023
Working Paper Number:
CES-23-18
Our understanding of how immigration enforcement impacts crime has been informed by data from the police crime statistics. This study complements existing research by using longitudinal multilevel data from the National Crime Victimization Survey (NCVS) for 2005-2014 to simultaneously assess the impact of the three predominant immigration policies that have been implemented in local communities. The results indicate that the activation of Secure Communities and 287(g) task force agreements significantly increased violent victimization risk among Latinos, whereas they showed no evident impact on victimization risk among non-Latino Whites and Blacks. The activation of 287(g) jail enforcement agreements and anti-detainer policies had no significant impact on violent victimization risk during the period.Contrary to their stated purpose of enhancing public safety, our results show that the Secure Communities program and 287(g) task force agreements did not reduce crime, but instead eroded security in American communities by increasing the likelihood that Latinos experienced violent victimization. These results support the Federal government's ending of 287(g) task force agreements and its more recent move to end the Secure Communities program. Additionally, the results of our study add to the evidence challenging claims that anti-detainer policies pose a threat to violence risk.
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Food Security Status Across the Rural-Urban Continuum Before and During the COVID-19 Pandemic
January 2025
Working Paper Number:
CES-25-01
Background: Food security, defined as consistent access to sufficient food to support an active life, is a crucial social determinant of health. A key dimension affecting food security is position along the rural-urban continuum, as there are important socio-economic and environmental differences between communities related to urbanicity or rurality that impact food access. The COVID-19 pandemic created social and economic shocks that altered financial and food security, which may have had differential effects by rurality and urbanicity. However, there has been limited research on how food security differs across the shades of the rural-urban community spectrum, as most often researchers have characterized communities as either urban or rural.
Methods: In this study, which linked restricted use Current Population Survey Food Security Supplement data to census-tract level United States Department of Agriculture Rural-Urban Commuting Area codes, we estimated the prevalence of household food security across temporal (2015-2019 versus 2020-2021) and socio-spatial (urban, large rural city/town, small rural town, or isolated rural town/area) dimensions in order to characterize variations before and during the COVID-19 pandemic by urbanicity/rurality. We report prevalences as point estimates with 95% confidence intervals.
Results: The prevalence of food security was 87.7% (87.5-88.0%) in 2015-2019 and 88.8% (88.4-89.3%) in 2020-2021 for urban areas, 85.5% (84.7-86.2%) in 2015-2019 and 87.1% (85.7-88.3%) in 2020-2021 for large rural towns/cities, 82.8% (81.5-84.1%) in 2015-2019 and 87.3% (85.7-89.2%) in 2020-2021 for small rural towns, and 87.6% (86.3-88.8%) in 2015-2019 and 90.9% (88.7-92.7%) in 2020-2021 for isolated rural towns/areas.
Conclusion: These findings show that rural communities experiences of food security vary and aggregating households in these environments may mask areas of concern and concentrated need.
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Mortality in a Multi-State Cohort of Former State Prisoners, 2010-2015
February 2022
Working Paper Number:
CES-22-06
Previous studies report that individuals who have been imprisoned have higher mortality rates than their demographic counterparts in the general population, particularly non-Hispanic white former prisoners. Most of these studies have been based on a single state's prison system, and the extent to which their findings can be generalized has not been established. In this study we explore the role that race/Hispanic origin, other demographic characteristics, and custodial/ criminal history factors have on post-release mortality, including on the timing of deaths. We also assess whether conditional release to community supervision or reimprisonment may explain the higher post-release mortality found among non-Hispanic whites. In the second part of the analysis, we estimate standardized mortality ratios (SMRs) by sex, age group, and race/Hispanic origin using as reference the U.S. general population. The data come from state prison releases from the Bureau of Justice Statistics' (BJS) National Corrections Reporting Program (NCRP). The NCRP records were linked to the Census Numident to identify deaths occurring within five years from prison release. We also linked NCRP records to previous decennial censuses and survey responses to obtain self-reported race and Hispanic origin if available. We found that non-Hispanic white former prisoners were more likely to die within five years after prison release and more likely to die in the initial weeks after release compared to racial minorities and Hispanics. Reimprisonment, age at release, and a history of multiple prison terms had a similar influence on the odds of dying across all race/Hispanic origin groups. Other factors, such as the type of release and the duration of the last term in prison, were associated with higher risks of mortality for some groups but not for others.
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Connected and Uncooperative: The Effects of Homogenous and Exclusive Social Networks on Survey Response Rates and Nonresponse Bias
January 2024
Working Paper Number:
CES-24-01
Social capital, the strength of people's friendship networks and community ties, has been hypothesized as an important determinant of survey participation. Investigating this hypothesis has been difficult given data constraints. In this paper, we provide insights by investigating how response rates and nonresponse bias in the American Community Survey are correlated with county-level social network data from Facebook. We find that areas of the United States where people have more exclusive and homogenous social networks have higher nonresponse bias and lower response rates. These results provide further evidence that the effects of social capital may not be simply a matter of whether people are socially isolated or not, but also what types of social connections people have and the sociodemographic heterogeneity of their social networks.
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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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