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Consequences of Eviction for Parenting and Non-parenting College Students
June 2025
Working Paper Number:
CES-25-35
Amidst rising and increasingly unaffordable rents, 7.6 million people are threatened with eviction each year across the United States'and eviction rates are twice as high for renters with children. One important and neglected population who may experience unique levels of housing insecurity is college students, especially given that one in five college students are parents. In this study, we link 11.9 million student records to eviction filings from housing courts, demographic characteristics reported in decennial census and survey data, incomes reported on tax returns by students and their parents, and dates of birth and death from the Social Security Administration. Parenting students are more likely than non-parenting students to identify as female (62.81% vs. 55.94%) and Black (19.66% vs. 14.30%), be over 30 years old (42.73% vs. 20.25%), and have parents with lower household incomes ($100,000 vs. $140,000). Parenting students threatened with eviction (i.e., had an eviction filed against them) are much more likely than non-threatened parenting students to identify as female (81.18% vs. 62.81%) and Black (56.84% vs. 19.66%). In models adjusted for individual and institutional characteristics, we find that being threatened with an eviction was significantly associated with reduced likelihood of degree completion, reduced post-enrollment income, reduced likelihood of being married post-enrollment, and increased post-enrollment mortality. Among parenting students, 38.38% (95% confidence interval (CI): 32.50-44.26%) of non-threatened students completed a bachelor's degree compared to just 15.36% (CI: 11.61-19.11%) of students threatened with eviction. Our findings highlight the long-term economic and health impacts of housing insecurity during college, especially for parenting students. Housing stability for parenting students may have substantial multigenerational benefits for economic mobility and population health.
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Potential Bias When Using Administrative Data to Measure the Family Income of School-Aged Children
January 2025
Working Paper Number:
CES-25-03
Researchers and practitioners increasingly rely on administrative data sources to measure family income. However, administrative data sources are often incomplete in their coverage of the population, giving rise to potential bias in family income measures, particularly if coverage deficiencies are not well understood. We focus on the school-aged child population, due to its particular import to research and policy, and because of the unique challenges of linking children to family income information. We find that two of the most significant administrative sources of family income information that permit linking of children and parents'IRS Form 1040 and SNAP participation records'usefully complement each other, potentially reducing coverage bias when used together. In a case study considering how best to measure economic disadvantage rates in the public school student population, we demonstrate the sensitivity of family income statistics to assumptions about individuals who do not appear in administrative data sources.
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Earnings Through the Stages: Using Tax Data to Test for Sources of Error in CPS ASEC Earnings and Inequality Measures
September 2024
Working Paper Number:
CES-24-52
In this paper, I explore the impact of generalized coverage error, item non-response bias, and measurement error on measures of earnings and earnings inequality in the CPS ASEC. I match addresses selected for the CPS ASEC to administrative data from 1040 tax returns. I then compare earnings statistics in the tax data for wage and salary earnings in samples corresponding to seven stages of the CPS ASEC survey production process. I also compare the statistics using the actual survey responses. The statistics I examine include mean earnings, the Gini coefficient, percentile earnings shares, and shares of the survey weight for a range of percentiles. I examine how the accuracy of the statistics calculated using the survey data is affected by including imputed responses for both those who did not respond to the full CPS ASEC and those who did not respond to the earnings question. I find that generalized coverage error and item nonresponse bias are dominated by measurement error, and that an important aspect of measurement error is households reporting no wage and salary earnings in the CPS ASEC when there are such earnings in the tax data. I find that the CPS ASEC sample misses earnings at the high end of the distribution from the initial selection stage and that the final survey weights exacerbate this.
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Revisions to the LEHD Establishment Imputation Procedure and Applications to Administrative Job Frame
September 2024
Working Paper Number:
CES-24-51
The Census Bureau is developing a 'job frame' to provide detailed job-level employment data across the U.S. through linked administrative records such as unemployment insurance and IRS W-2 filings. This working paper summarizes the research conducted by the job frame development team on modifying and extending the LEHD Unit-to-Worker (U2W) imputation procedure for the job frame prototype. It provides a conceptual overview of the U2W imputation method, highlighting key challenges and tradeoffs in its current application. The paper then presents four imputation methodologies and evaluates their performance in areas such as establishment assignment accuracy, establishment size matching, and job separation rates. The results show that all methodologies perform similarly in assigning workers to the correct establishment. Non-spell-based methodologies excel in matching establishment sizes, while spell-based methodologies perform better in accurately tracking separation rates.
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The Demographics of the Recipients of the First Economic Impact Payment
May 2023
Working Paper Number:
CES-23-24
Starting in April 2020, the federal government began to distribute Economic Impact Payments (EIPs) in response to the health and economic crisis caused by COVID-19. More than 160 million payments were disbursed. We produce statistics concerning the receipt of EIPs by individuals and households across key demographic subgroups. We find that payments went out particularly quickly to households with children and lower-income households, and the rate of receipt was quite high for individuals over age 60, likely due to a coordinated effort to issue payments automatically to Social Security recipients. We disaggregate statistics by race/ethnicity to document whether racial disparities arose in EIP disbursement. Receipt rates were high overall, with limited differences across racial/ethnic subgroups. We provide a set of detailed counts in tables for use by the public.
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Self-Employment Income Reporting on Surveys
April 2023
Working Paper Number:
CES-23-19
We examine the relation between administrative income data and survey reports for self-employed and wage-earning respondents from 2000 - 2015. The self-employed report 40 percent more wages and self-employment income in the survey than in tax administrative records; this estimate nets out differences between these two sources that are also shared by wage-earners. We provide evidence that differential reporting incentives are an important explanation of the larger self-employed gap by exploiting a well-known artifact ' self-employed respondents exhibit substantial bunching at the
first EITC kink in their administrative records. We do not observe the same behavior in their survey responses even after accounting for survey measurement concerns.
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Universal Preschool Lottery Admissions and Its Effects on Long-Run Earnings and Outcomes
March 2023
Working Paper Number:
CES-23-09
We use an admissions lottery to estimate the effect of a universal (non-means tested) preschool program on students' long-run earnings, income, marital status, fertility and geographic mobility. We observe long-run outcomes by linking both admitted and non-admitted individuals to confidential administrative data including tax records. Funding for this preschool program comes from an Indigenous organization, which grants Indigenous students admissions preference and free tuition. We find treated children have between 5 to 6 percent higher earnings as young adults. The results are strongest for individuals from the lower half of the household income distribution in childhood. Likely mechanisms include high-quality teachers and curriculum.
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Full Report of the Comparisons of Administrative Record Rosters to Census Self-Responses and NRFU Household Member Responses
March 2023
Working Paper Number:
CES-23-08
One of the U.S. Census Bureau's innovations in the 2020 U.S. Census was the use of administrative records (AR) to create household rosters for enumerating some addresses when a self response was not available but high-quality ARs were. The goal was to reduce the cost of fieldwork during the Nonresponse Followup operation (NRFU). The original plan had NRFU beginning in mid-May and continuing through late July 2020. However, the COVID-19 pandemic forced the delay of NRFU and caused the Internal Revenue Service to postpone the income tax filing deadline, resulting in an interruption in the delivery of ARs to the U.S. Census Bureau. The delays were not anticipated when U.S. Census Bureau staff conducted the research on AR enumeration with the 2010 Census data in preparation for the 2020 Census or during the fine tuning of plans for using ARs during the 2018 End-to-End Census Test. These circumstances raised questions about whether the quality of the AR household rosters was high enough for use in enumeration. To aid in investigating the concern about the quality of the AR rosters, our analyses compared AR rosters to self-response rosters and NRFU household member responses at addresses where both ARs and a self-response were available.
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Introducing the Medical Expenditure Panel Survey-Insurance Component with Administrative Records (MEPS-ICAR): Description, Data Construction Methodology, and Quality Assessment
August 2022
Working Paper Number:
CES-22-29
This report introduces a new dataset, the Medical Expenditure Panel Survey-Insurance Component with Administrative Records (MEPS-ICAR), consisting of MEPS-IC survey data on establishments and their health insurance benefits packages linked to Decennial Census data and administrative tax records on MEPS-IC establishments' workforces. These data include new measures of the characteristics of MEPS-IC establishments' parent firms, employee turnover, the full distribution of MEPS-IC workers' personal and family incomes, the geographic locations where those workers live, and improved workforce demographic detail. Next, this report details the methods used for producing the MEPS-ICAR. Broadly, the linking process begins by matching establishments' parent firms to their workforces using identifiers appearing in tax records. The linking process concludes by matching establishments to their own workforces by identifying the subset of their parent firm's workforce that best matches the expected size, total payroll, and residential geographic distribution of the establishment's workforce. Finally, this report presents statistics characterizing the match rate and the MEPS-ICAR data itself. Key results include that match rates are consistently high (exceeding 90%) across nearly all data subgroups and that the matched data exhibit a reasonable distribution of employment, payroll, and worker commute distances relative to expectations and external benchmarks. Notably, employment measures derived from tax records, but not used in the match itself, correspond with high fidelity to the employment levels that establishments report in the MEPS-IC. Cumulatively, the construction of the MEPS-ICAR significantly expands the capabilities of the MEPS-IC and presents many opportunities for analysts.
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Gender Differences in Self-employment Duration: the Case of Opportunity and Necessity Entrepreneurs
September 2019
Working Paper Number:
CES-19-24
A strand of the self-employment literature suggests that those 'pushed' into self-employment out of necessity may perform differently from those 'pulled' into self-employment to pursue a business opportunity. While findings on self-employment outcomes by self-employed type are not unanimous, there is mounting evidence that performance outcomes differ between these two self-employed types. Another strand of the literature has found important gender differences in self-employment entry rates, motivations for entry, and outcomes. Using a unique set of data that links the American Community Survey to administrative data from Form 1040 and W-2 records, we bring together these two strands of the literature. We explore whether there are gender differences in self-employment duration of self-employed types. In particular, we examine the likelihood of self-employment exit towards unemployment versus the wage sector for five consecutive entry cohorts, including two cohorts who entered self-employment during the Great Recession. Severely limited labor-market opportunities may have driven many in the recession cohorts to enter self-employment, while those entering self-employment during the boom may have been pursuing opportunities under favorable market conditions. To more explicitly test the concept of 'necessity' versus 'opportunity' self-employment, we also examine the wage labor attachment (or weeks worked in the wage sector) in the year prior to becoming self-employed. We find that, within the cohorts we examine, there are gender differences in the rate at which men and women depart self-employment for either wage work or non-participation, but that the patterns are dependent on pre self-employment wage-sector attachment and cohort effects.
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