This article investigates the complex interactions between local and national economic contexts and volunteering behavior. We examine three dimensions of local economic context'economic disadvantage (e.g., the percentage of families living in poverty), income inequality, and economic growth (e.g., the change in median household income) and the impact of a national/global economic jolt'the Great Recession. Analysis of data from the Current Population Survey's (CPS) Volunteering Supplement (2002-2015) reveals. Individuals who live in places characterized by economic disadvantage and economic inequality are less likely to volunteer than individuals in more advantaged, equitable communities. The recession had a dampening effect on volunteering overall, but it had the largest dampening effect on individual volunteering in communities with above average rates of income equality and higher rates of economic growth. While individuals living in rural communities were more likely to volunteer than their urban counterparts before the recession, rural/urban differences disappear after the recession.
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The Rural/Urban Volunteering Divide
June 2025
Working Paper Number:
CES-25-42
Are rural residents more likely to volunteer than those living in urban places? Although early sociological theory posited that rural residents were more likely to experience social bonds connecting them to their community, increasing their odds of volunteer engagement, empirical support is limited. Drawing upon the full population of rural and urban respondents to the United States Census Bureau's Current Population Survey (CPS) Volunteering Supplement (2002-2015), we found that rural respondents are more likely to report volunteering compared to urban respondents, although these differences are decreasing over time. Moreover, we found that propensities for rural and urban volunteerism vary based on differences in both individual and place-based characteristics; further, the size of these effects differ across rural and urban places. These findings have important implications for theory and empirical analysis.
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Civic Community in Small-Town America: How Civic Welfare is Influenced by Local Capitalism and Civic Engagement
December 2001
Working Paper Number:
CES-01-19
The aims of this paper are twofold: first, to gain a fuller understanding of factors that foster community cohesion and contribute to the residents' social and economic well-being; and, second, to move beyond previous research that used larger spatial units such as states, counties, or aggregates of counties and to focus instead on American small towns (population 2,500-20,000). The data on small towns are drawn from public-use files and from confidential microdata from various economic censuses. From these sources we construct measures of locally oriented firms, self-employment, business establishments that serve as gathering places, and associations. The local capitalism and civic engagement variables generally perform as hypothesized; in some cases they are related quite strongly to civic welfare outcomes such as income levels, poverty rates, and nonmigration rates. We discuss the advantages and disadvantages of working with place-level data and suggest some strategies for subsequent work on small towns and other incorporated places.
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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.
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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.
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Disconnected Geography: A Spatial Analysis of Disconnected Youth in the United States
January 2016
Working Paper Number:
CES-16-37
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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In-migration and Dilution of Community Social Capital
June 2018
Working Paper Number:
CES-18-32
Consistent with predictions from the literature, we find that higher levels of in-migration dilute multiple dimensions of a community's level of social capital. The analysis employs a 2SLS
methodology to account for potential endogeneity of migration.
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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.
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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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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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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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