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A Simulated Reconstruction and Reidentification Attack on the 2010 U.S. Census
August 2025
Authors:
Lars Vilhuber,
John M. Abowd,
Ethan Lewis,
Nathan Goldschlag,
Michael B. Hawes,
Robert Ashmead,
Daniel Kifer,
Philip Leclerc,
Rolando A. Rodríguez,
Tamara Adams,
David Darais,
Sourya Dey,
Simson L. Garfinkel,
Scott Moore,
Ramy N. Tadros
Working Paper Number:
CES-25-57
For the last half-century, it has been a common and accepted practice for statistical agencies, including the United States Census Bureau, to adopt different strategies to protect the confidentiality of aggregate tabular data products from those used to protect the individual records contained in publicly released microdata products. This strategy was premised on the assumption that the aggregation used to generate tabular data products made the resulting statistics inherently less disclosive than the microdata from which they were tabulated. Consistent with this common assumption, the 2010 Census of Population and Housing in the U.S. used different disclosure limitation rules for its tabular and microdata publications. This paper demonstrates that, in the context of disclosure limitation for the 2010 Census, the assumption that tabular data are inherently less disclosive than their underlying microdata is fundamentally flawed. The 2010 Census published more than 150 billion aggregate statistics in 180 table sets. Most of these tables were published at the most detailed geographic level'individual census blocks, which can have populations as small as one person. Using only 34 of the published table sets, we reconstructed microdata records including five variables (census block, sex, age, race, and ethnicity) from the confidential 2010 Census person records. Using only published data, an attacker using our methods can verify that all records in 70% of all census blocks (97 million people) are perfectly reconstructed. We further confirm, through reidentification studies, that an attacker can, within census blocks with perfect reconstruction accuracy, correctly infer the actual census response on race and ethnicity for 3.4 million vulnerable population uniques (persons with race and ethnicity different from the modal person on the census block) with 95% accuracy. Having shown the vulnerabilities inherent to the disclosure limitation methods used for the 2010 Census, we proceed to demonstrate that the more robust disclosure limitation framework used for the 2020 Census publications defends against attacks that are based on reconstruction. Finally, we show that available alternatives to the 2020 Census Disclosure Avoidance System would either fail to protect confidentiality, or would overly degrade the statistics' utility for the primary statutory use case: redrawing the boundaries of all of the nation's legislative and voting districts in compliance with the 1965 Voting Rights Act.
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Differences in Disability Insurance Allowance Rates
August 2025
Working Paper Number:
CES-25-54
Allowance rates for disability insurance applications vary by race and ethnicity, but it is unclear to what extent these differences are artifacts of other differing socio-economic and health characteristics, or selection issues in SSA's race and ethnicity data. This paper uses the 2015 American Community Survey linked to 2015-2019 SSA administrative data to investigate DI application allowance rates among non-Hispanic White, non-Hispanic Black, non-Hispanic Asian, non-Hispanic American Indian/Alaska Native, and Hispanic applicants aged 25-65. The analysis uses regression, propensity score matching, and inverse probability weighting to estimate differences in allowance rates among applicants who are similar on observable characteristics. Relative to raw comparisons, differences by race and ethnicity in multivariate analyses are substantially smaller in magnitude and are generally not statistically significant.
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Credit Access in the United States
July 2025
Working Paper Number:
CES-25-45
We construct new population-level linked administrative data to study households' access to credit in the United States. These data reveal large differences in credit access by race, class, and hometown. By age 25, Black individuals, those who grew up in low-income families, and those who grew up in certain areas (including the Southeast and Appalachia) have significantly lower credit scores than other groups. Consistent with lower scores generating credit constraints, these individuals have smaller balances, more credit inquiries, higher credit card utilization rates, and greater use of alternative higher-cost forms of credit. Tests for alternative definitions of algorithmic bias in credit scores yield results in opposite directions. From a calibration perspective, group-level differences in credit scores understate differences in delinquency: conditional on a given credit score, Black individuals and those from low-income families fall delinquent at relatively higher rates. From a balance perspective, these groups receive lower credit scores even when comparing those with the same future repayment behavior. Addressing both of these biases and expanding credit access to groups with lower credit scores requires addressing group-level differences in delinquency rates. These delinquencies emerge soon after individuals access credit in their early twenties, often due to missed payments on credit cards, student loans, and other bills. Comprehensive measures of individuals' income profiles, income volatility, and observed wealth explain only a small portion of these repayment gaps. In contrast, we find that the large variation in repayment across hometowns mostly reflects the causal effect of childhood exposure to these places. Places that promote upward income mobility also promote repayment and expand credit access even conditional on income, suggesting that common place-level factors may drive behaviors in both credit and labor markets. We discuss suggestive evidence for several mechanisms that drive our results, including the role of social and cultural capital. We conclude that gaps in credit access by race, class, and hometown have roots in childhood environments.
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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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Divorce, Family Arrangements, and Children's Adult Outcomes
May 2025
Working Paper Number:
CES-25-28
Nearly a third of American children experience parental divorce before adulthood. To understand its consequences, we use linked tax and Census records for over 5 million children to examine how divorce affects family arrangements and children's long-term outcomes. Following divorce, parents move apart, household income falls, parents work longer hours, families move more frequently, and households relocate to poorer neighborhoods with less economic opportunity. This bundle of changes in family circumstances suggests multiple channels through which divorce may affect children's development and outcomes. In the years following divorce, we observe sharp increases in teen births and child mortality. To examine long-run effects on children, we compare siblings with different lengths of exposure to the same divorce. We find that parental divorce reduces children's adult earnings and college residence while increasing incarceration, mortality, and teen births. Changes in household income, neighborhood quality, and parent proximity account for 25 to 60 percent of these divorce effects.
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The Composition of Firm Workforces from 2006'2022: Findings from the Business Dynamics Statistics of Human Capital Experimental Product
April 2025
Working Paper Number:
CES-25-20
We introduce the Business Dynamics Statistics of Human Capital (BDS-HC) tables, a new Census Bureau experimental product that provides public-use statistics on the workforce composition of firms and its relationship to business dynamics. We use administrative W-2 filings to combine population-level worker demographic data with longitudinal business data to estimate the demographic and educational composition of nearly all non-farm employer businesses in the United States between 2006 and 2022. We use this newly constructed data to document the evolution of employment, entry, and exit of employers based on their workforce compositions. We also provide new statistics on the interaction between firm and worker characteristics, including the composition of workers at startup firms. We find substantial changes between 2006 and 2022 in the distribution of employers along several dimensions, primarily driven by changing workforce compositions within continuing firms rather than the reallocation of employment between firms. We also highlight systematic differences in the business dynamics of firms by their workforce compositions, suggesting that different groups of workers face different economic environments due to their employers.
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Geographic Immobility in the United States: Assessing the Prevalence and Characteristics of Those Who Never Migrate Across State Lines Using Linked Federal Tax Microdata
March 2025
Working Paper Number:
CES-25-19
This paper explores the prevalence and characteristics of those who never migrate at the state scale in the U.S. Studying people who never migrate requires regular and frequent observation of their residential location for a lifetime, or at least for many years. A novel U.S. population-sized longitudinal dataset that links individual level Internal Revenue Service (IRS) and Social Security Administration (SSA) administrative records supplies this information annually, along with information on income and socio-demographic characteristics. We use these administrative microdata to follow a cohort aged between 15 and 50 in 2001 from 2001 to 2016, differentiating those who lived in the same state every year during this period (i.e., never made an interstate move) from those who lived in more than one state (i.e., made at least one interstate move). We find those who never made an interstate move comprised 75 percent of the total population of this age cohort. This percentage varies by year of age but never falls below 62 percent even for those who were teenagers or young adults in 2001. There are also variations in these percentages by sex, race, nativity, and income, with the latter having the largest effects. We also find substantial variation in these percentages across states. Our findings suggest a need for more research on geographically immobile populations in U.S.
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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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Places versus People: The Ins and Outs of Labor Market Adjustment to Globalization
December 2024
Working Paper Number:
CES-24-78
We analyze the distinct adjustment paths of U.S. labor markets (places) and U.S. workers (people) to increased Chinese import competition during the 2000s. Using comprehensive register data for 2000'2019, we document that employment levels more than fully rebound in trade-exposed places after 2010, while employment-to-population ratios remain depressed and manufacturing employment further atrophies. The adjustment of places to trade shocks is generational: affected areas recover primarily by adding workers to non-manufacturing who were below working age when the shock occurred. Entrants are disproportionately native-born Hispanics, foreign-born immigrants, women, and the college-educated, who find employment in relatively low-wage service sectors like medical services, education, retail, and hospitality. Using the panel structure of the employer-employee data, we decompose changes in the employment composition of places into trade-induced shifts in the gross flows of people across sectors, locations, and non-employment status. Contrary to standard models, trade shocks reduce geographic mobility, with both in- and out-migration remaining depressed through 2019. The employment recovery instead stems almost entirely from young adults and foreign-born immigrants taking their first U.S. jobs in affected areas, with minimal contributions from cross-sector transitions of former manufacturing workers. Although worker inflows into non-manufacturing more than fully offset manufacturing employment losses in trade-exposed locations after 2010, incumbent workers neither fully recover earnings losses nor predominately exit the labor market, but rather age in place as communities undergo rapid demographic and industrial transitions.
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CTC and ACTC Participation Results and IRS-Census Match Methodology, Tax Year 2020
December 2024
Working Paper Number:
CES-24-76
The Child Tax Credit (CTC) and Additional Child Tax Credit (ACTC) offer assistance to help ease the financial burden of families with children. This paper provides taxpayer and dollar participation estimates for the CTC and ACTC covering tax year 2020. The estimates derive from an approach that relies on linking the 2021 Current Population Survey Annual Social and Economic Supplement (CPS ASEC) to IRS administrative data. This approach, called the Exact Match, uses survey data to identify CTC/ACTC eligible taxpayers and IRS administrative data to indicate which eligible taxpayers claimed and received the credit. Overall in tax year 2020, eligible taxpayers participated in the CTC and ACTC program at a rate of 93 percent while dollar participation was 91 percent.
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