This paper explores how useful information about social and civic engagement (social capital)
might be to the U.S. Census Bureau in their efforts to improve predictions of mail return rates for the Decennial Census (DC) at the census tract level. Through construction of Hard-to-count (HRC) scores and multivariate analysis, we find that if information about social capital were available, predictions of response rates would be marginally improved.
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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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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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Wage Determination in Social Occupations: the Role of Individual Social Capital
January 2016
Working Paper Number:
CES-16-46
We make use of predicted social and civic activities (social capital) to account for selection into "social" occupations. Individual selection accounts for more than the total difference in wages observed between social and non-social occupations. The role that individual social capital plays in selecting into these occupations and the importance of selection in explaining wage differences across occupations is similar for both men and women. We make use of restricted 2000 Decennial Census and 2000 Social Capital Community Benchmark Survey. Individual social capital is instrumented by distance weighted surrounding census tract characteristics.
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Predicting the Effect of Adding a Citizenship Question to the 2020 Census
June 2019
Working Paper Number:
CES-19-18
The addition of a citizenship question to the 2020 census could affect the self-response rate, a key driver of the cost and quality of a census. We find that citizenship question response patterns in the American Community Survey (ACS) suggest that it is a sensitive question when asked about administrative record noncitizens but not when asked about administrative record citizens. ACS respondents who were administrative record noncitizens in 2017 frequently choose to skip the question or answer that the person is a citizen. We predict the effect on self-response to the entire survey by comparing mail response rates in the 2010 ACS, which included a citizenship question, with those of the 2010 census, which did not have a citizenship question, among households in both surveys. We compare the actual ACS-census difference in response rates for households that may contain noncitizens (more sensitive to the question) with the difference for households containing only U.S. citizens. We estimate that the addition of a citizenship question will have an 8.0 percentage point larger effect on self-response rates in households that may have noncitizens relative to those with only U.S. citizens. Assuming that the citizenship question does not affect unit self-response in all-citizen households and applying the 8.0 percentage point drop to the 28.1 % of housing units potentially having at least one noncitizen would predict an overall 2.2 percentage point drop in self-response in the 2020 census, increasing costs and reducing the quality of the population count.
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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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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 Impact of Household Surveys on 2020 Census Self-Response
July 2022
Working Paper Number:
CES-22-24
Households who were sampled in 2019 for the American Community Survey (ACS) had lower self-response rates to the 2020 Census. The magnitude varied from -1.5 percentage point for household sampled in January 2019 to -15.1 percent point for households sampled in December 2019. Similar effects are found for the Current Population Survey (CPS) as well.
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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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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 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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