Papers Containing Tag(s): 'Census Household Composition Key'
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Viewing papers 1 through 10 of 15
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Working PaperFrom Marcy to Madison Square? The Effects of Growing Up in Public Housing on Early Adulthood Outcomes
November 2024
Working Paper Number:
CES-24-67
This paper studies the effects of growing up in public housing in New York City on children's long-run outcomes. Using linked administrative data, we exploit variation in the age children move into public housing to estimate the effects of spending an additional year of childhood in public housing on a range of economic and social outcomes in early adulthood. We find that childhood exposure to public housing improves labor market outcomes and reduces participation in federal safety net programs, particularly for children from the most disadvantaged families. Additionally, we find there is some heterogeneity in impacts across public housing developments. Developments located in neighborhoods with relatively fewer renters and higher household incomes are better for children overall. Our estimate of the marginal value of public funds suggests that for every $1 the government spends per child on public housing, children receive $1.40 in benefits, including $2.30 for children from the most disadvantaged families.View Full Paper PDF
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Working PaperNonresponse and Coverage Bias in the Household Pulse Survey: Evidence from Administrative Data
October 2024
Working Paper Number:
CES-24-60
The Household Pulse Survey (HPS) conducted by the U.S. Census Bureau is a unique survey that provided timely data on the effects of the COVID-19 Pandemic on American households and continues to provide data on other emergent social and economic issues. Because the survey has a response rate in the single digits and only has an online response mode, there are concerns about nonresponse and coverage bias. In this paper, we match administrative data from government agencies and third-party data to HPS respondents to examine how representative they are of the U.S. population. For comparison, we create a benchmark of American Community Survey (ACS) respondents and nonrespondents and include the ACS respondents as another point of reference. Overall, we find that the HPS is less representative of the U.S. population than the ACS. However, performance varies across administrative variables, and the existing weighting adjustments appear to greatly improve the representativeness of the HPS. Additionally, we look at household characteristics by their email domain to examine the effects on coverage from limiting email messages in 2023 to addresses from the contact frame with at least 90% deliverability rates, finding no clear change in the representativeness of the HPS afterwards.View Full Paper PDF
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Working PaperIncorporating Administrative Data in Survey Weights for the 2018-2022 Survey of Income and Program Participation
October 2024
Working Paper Number:
CES-24-58
Response rates to the Survey of Income and Program Participation (SIPP) have declined over time, raising the potential for nonresponse bias in survey estimates. A potential solution is to leverage administrative data from government agencies and third-party data providers when constructing survey weights. In this paper, we modify various parts of the SIPP weighting algorithm to incorporate such data. We create these new weights for the 2018 through 2022 SIPP panels and examine how the new weights affect survey estimates. Our results show that before weighting adjustments, SIPP respondents in these panels have higher socioeconomic status than the general population. Existing weighting procedures reduce many of these differences. Comparing SIPP estimates between the production weights and the administrative data-based weights yields changes that are not uniform across the joint income and program participation distribution. Unlike other Census Bureau household surveys, there is no large increase in nonresponse bias in SIPP due to the COVID-19 Pandemic. In summary, the magnitude and sign of nonresponse bias in SIPP is complicated, and the existing weighting procedures may change the sign of nonresponse bias for households with certain incomes and program benefit statuses.View Full Paper PDF
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Working PaperComparison of Child Reporting in the American Community Survey and Federal Income Tax Returns Based on California Birth Records
September 2024
Working Paper Number:
CES-24-55
This paper takes advantage of administrative records from California, a state with a large child population and a significant historical undercount of children in Census Bureau data, dependent information in the Internal Revenue Service (IRS) Form 1040 records, and the American Community Survey to characterize undercounted children and compare child reporting. While IRS Form 1040 records offer potential utility for adjusting child undercounting in Census Bureau surveys, this analysis finds overlapping reporting issues among various demographic and economic groups. Specifically, older children, those of Non-Hispanic Black mothers and Hispanic mothers, children or parents with lower English proficiency, children whose mothers did not complete high school, and families with lower income-to-poverty ratio were less frequently reported in IRS 1040 records than other groups. Therefore, using IRS 1040 dependent records may have limitations for accurately representing populations with characteristics associated with the undercount of children in surveys.View Full Paper PDF
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Working PaperCitizenship Question Effects on Household Survey Response
June 2024
Working Paper Number:
CES-24-31
Several small-sample studies have predicted that a citizenship question in the 2020 Census would cause a large drop in self-response rates. In contrast, minimal effects were found in Poehler et al.'s (2020) analysis of the 2019 Census Test randomized controlled trial (RCT). We reconcile these findings by analyzing associations between characteristics about the addresses in the 2019 Census Test and their response behavior by linking to independently constructed administrative data. We find significant heterogeneity in sensitivity to the citizenship question among households containing Hispanics, naturalized citizens, and noncitizens. Response drops the most for households containing noncitizens ineligible for a Social Security number (SSN). It falls more for households with Latin American-born immigrants than those with immigrants from other countries. Response drops less for households with U.S.-born Hispanics than households with noncitizens from Latin America. Reductions in responsiveness occur not only through lower unit self-response rates, but also by increased household roster omissions and internet break-offs. The inclusion of a citizenship question increases the undercount of households with noncitizens. Households with noncitizens also have much higher citizenship question item nonresponse rates than those only containing citizens. The use of tract-level characteristics and significant heterogeneity among Hispanics, the foreign-born, and noncitizens help explain why the effects found by Poehler et al. were so small. Linking administrative microdata with the RCT data expands what we can learn from the RCT.View Full Paper PDF
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Working PaperMobility, Opportunity, and Volatility Statistics (MOVS): Infrastructure Files and Public Use Data
April 2024
Working Paper Number:
CES-24-23
Federal statistical agencies and policymakers have identified a need for integrated systems of household and personal income statistics. This interest marks a recognition that aggregated measures of income, such as GDP or average income growth, tell an incomplete story that may conceal large gaps in well-being between different types of individuals and families. Until recently, longitudinal income data that are rich enough to calculate detailed income statistics and include demographic characteristics, such as race and ethnicity, have not been available. The Mobility, Opportunity, and Volatility Statistics project (MOVS) fills this gap in comprehensive income statistics. Using linked demographic and tax records on the population of U.S. working-age adults, the MOVS project defines households and calculates household income, applying an equivalence scale to create a personal income concept, and then traces the progress of individuals' incomes over time. We then output a set of intermediate statistics by race-ethnicity group, sex, year, base-year state of residence, and base-year income decile. We select the intermediate statistics most useful in developing more complex intragenerational income mobility measures, such as transition matrices, income growth curves, and variance-based volatility statistics. We provide these intermediate statistics as part of a publicly released data tool with downloadable flat files and accompanying documentation. This paper describes the data build process and the output files, including a brief analysis highlighting the structure and content of our main statistics.View Full Paper PDF
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Working PaperWhere Are Your Parents? Exploring Potential Bias in Administrative Records on Children
March 2024
Working Paper Number:
CES-24-18
This paper examines potential bias in the Census Household Composition Key's (CHCK) probabilistic parent-child linkages. By linking CHCK data to the American Community Survey (ACS), we reveal disparities in parent-child linkages among specific demographic groups and find that characteristics of children that can and cannot be linked to the CHCK vary considerably from the larger population. In particular, we find that children from low-income, less educated households and of Hispanic origin are less likely to be linked to a mother or a father in the CHCK. We also highlight some data considerations when using the CHCK.View Full Paper PDF
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Working PaperThe Long-Term Effects of Income for At-Risk Infants: Evidence from Supplemental Security Income
March 2024
Working Paper Number:
CES-24-10
This paper examines whether a generous cash intervention early in life can "undo" some of the long-term disadvantage associated with poor health at birth. We use new linkages between several large-scale administrative datasets to examine the short-, medium-, and long-term effects of providing low-income families with low birthweight infants support through the Supplemental Security Income (SSI) program. This program uses a birthweight cutoff at 1200 grams to determine eligibility. We find that families of infants born just below this cutoff experience a large increase in cash benefits totaling about 27%of family income in the first three years of the infant's life. These cash benefits persist at lower amounts through age 10. Eligible infants also experience a small but statistically significant increase in Medicaid enrollment during childhood. We examine whether this support affects health care use and mortality in infancy, educational performance in high school, post-secondary school attendance and college degree attainment, and earnings, public assistance use, and mortality in young adulthood for all infants born in California to low-income families whose birthweight puts them near the cutoff. We also examine whether these payments had spillover effects onto the older siblings of these infants who may have also benefited from the increase in family resources. Despite the comprehensive nature of this early life intervention, we detect no improvements in any of the study outcomes, nor do we find improvements among the older siblings of these infants. These null effects persist across several subgroups and alternative model specifications, and, for some outcomes, our estimates are precise enough to rule out published estimates of the effect of early life cash transfers in other settings.View Full Paper PDF
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Working PaperProducing U.S. Population Statistics Using Multiple Administrative Sources
November 2023
Working Paper Number:
CES-23-58
We identify several challenges encountered when constructing U.S. administrative record-based (AR-based) population estimates for 2020. Though the AR estimates are higher than the 2020 Census at the national level, they are over 15 percent lower in 5 percent of counties, suggesting that locational accuracy can be improved. Other challenges include how to achieve comprehensive coverage, maintain consistent coverage across time, filter out nonresidents and people not alive on the reference date, uncover missing links across person and address records, and predict demographic characteristics when multiple ones are reported or when they are missing. We discuss several ways of addressing these issues, e.g., building in redundancy with more sources, linking children to their parents' addresses, and conducting additional record linkage for people without Social Security Numbers and for addresses not initially linked to the Census Bureau's Master Address File. We discuss modeling to predict lower levels of geography for people lacking those geocodes, the probability that a person is a U.S. resident on the reference date, the probability that an address is the person's residence on the reference date, and the probability a person is in each demographic characteristic category. Regression results illustrate how many of these challenges and solutions affect the AR county population estimates.View Full Paper PDF
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Working PaperCoverage of Children in the American Community Survey Based on California Birth Records
September 2023
Working Paper Number:
CES-23-46
The U.S. Census Bureau's American Community Survey (ACS) collects information on individuals and households. The ACS provides survey-based estimates of children drawn from a sample of the U.S. population. However, survey responses may not match administrative records, such as birth records. Birth records should provide a complete account of all births, along with child-parent relationships and demographic characteristics. California is a state that has both a large population of children and a high undercount for young children. This paper uses California as a case study to examine differences between reported versus unreported children in the ACS based on state birth records. Child reporting rates were lower for more recent data years, younger children, for Black and Hispanic mothers, and for more complex households. Child reporting rates were higher for more educated mothers and for households above the poverty line. Using mother's race and Hispanic ethnicity from the birth records combined with poverty indices from the ACS, this analysis also finds that child reporting does not uniformly vary with poverty status across all race and ethnicity groups. This research builds support for the utility of state birth records in analyzing the undercount of children.View Full Paper PDF
