Papers Containing Tag(s): 'Current Population Survey'
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Viewing papers 1 through 10 of 293
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Working PaperCTC and ACTC Participation Results and IRS-Census Match Methodology, Tax Year 2021
August 2026
Working Paper Number:
CES-26-49
The Child Tax Credit (CTC) and Additional Child Tax Credit (ACTC) 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 2021. In this tax year the credit was temporarily expanded under the American Rescue Plan Act. The estimates derive from linking the 2022 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 2021, eligible taxpayers participated in the CTC and ACTC program at a rate of 91 percent while dollar participation was 85 percent.View Full Paper PDF
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Working PaperDesperate Capital Breeds Productivity Loss: Evidence From Public Pension Investments in Private Equity
July 2026
Working Paper Number:
CES-26-47
I study investments of U.S. public pensions in private equity (PE), and trace them to ultimate micro assets'target firms which PE funds invest in, using micro-data on private investments combined with confidential U.S. Census data. I show that more severely underfunded public pensions receive lower average PE returns, and match with smaller GPs on average, than less underfunded pensions. Consistent with matching and returns, firms financed by most underfunded public pensions and smallest PE funds face labor productivity decreases. I introduce a novel instrument'public unionization'in support of underfunding positions driving selection into funds. Lastly, I evaluate alternate mechanisms.View Full Paper PDF
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Working PaperAccess to the Special Supplemental Nutrition Program for Women, Infants, and Children (WIC) at the State and Substate Levels: Meaning and Measurement
July 2026
Working Paper Number:
CES-26-44
This study estimates eligibility and access rates for the U.S. Department of Agriculture's (USDA) Special Supplemental Nutrition Program for Women, Infants, and Children (WIC) administrative data linked with American Community Survey (ACS) data. This study is one result of a long-term research collaboration among USDA's Economic Research Service; the U.S. Department of Commerce, Bureau of the Census; USDA's Food and Nutrition Service (FNS); and participating state WIC agencies.'By analyzing WIC participation at the state and substate levels, the report provides insights into program reach and demographic differences. The findings confirm that the Census Bureau estimates meet high statistical reliability standards, providing valuable data for program officials and managers, and other stakeholders, to enhance program outreach and effectiveness. A key focus of the report is the comparison between Census Bureau and USDA, FNS estimates, which differ in methodology and measurement scope.View Full Paper PDF
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Working PaperThe Impact of Expanding Public Health Insurance on Safety Net Program Participation: Evidence From the ACA Medicaid Expansion
May 2026
Working Paper Number:
CES-26-32
We examine spillover effects from the ACA Medicaid expansion to public programs providing cash and food assistance. We consider program participation in contiguous county pairs crossing state borders, where one state took up the Medicaid expansion and the other did not, allowing us to better control for local economic trends that could affect program participation. We find that the Medicaid expansion increased participation in food assistance and one of the cash programs, with impacts mainly due to participation conditional on eligibility, rather than from labor supply responses. Our results demonstrate the potential for spillovers across safety net programs.View Full Paper PDF
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Working PaperThe Microstructure of AI Diffusion: Evidence From Firms, Business Functions, and Worker Tasks
April 2026
Working Paper Number:
CES-26-25
Using novel, nationally representative data from the 2026 AI supplement to the U.S. Census Bureau's Business Trends and Outlook Survey (BTOS), we characterize AI diffusion across three interconnected layers: overall firm use, deployment across business functions, and worker-task use. This multi-layered approach provides a nuanced picture of business AI adoption. During the supplement reference period (Nov 2025-Jan 2026), 18% of firms used AI in a business function, rising to 32% on an employment-weighted basis; adoption is expected to reach 22% within six months. AI use is substantially higher in large firms and knowledge-intensive sectors, with use rates reaching 50%-60% (60%-70%, employment-weighted) for very large firms in the Information, Professional Services, and Finance sectors. Among adopting firms, the scope of use remains limited: 57% of users integrate AI in three or fewer business functions, most commonly Sales and Marketing (52%), Strategy and Business Development (45%), and IT (41%). In 23% (41%, employment-weighted) of firms, workers use AI in work-related tasks. Writing, document analysis, and information search are the leading Generative AI use in tasks, though 65% of firms limit use to three or fewer tasks. The evidence points to both top-down and bottom-up diffusion channels: worker task use sometimes occurs without formal firm-level adoption, and firm-level adoption sometimes occurs without worker task use. Most users (66%) rely on AI solely to augment tasks, while AI-related employment decreases are rare, occurring in only 2% of firms. Regression analysis shows a robust positive correlation between firm commercial performance and the breadth of AI integration, including functional deployment, task-level use, and operational investment. A distinct divergence emerges, however, with respect to labor outcomes. Functional breadth and operational investment are positively associated with employment decreases, whereas worker-task integration shows no significant link to headcount reduction once functional integration and operational investment are taken into account.View Full Paper PDF
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Working PaperUnemployment Insurance Extensions, Labor Market Concentration, and Match Quality
April 2026
Working Paper Number:
CES-26-24
I investigate whether the effects of UI extensions are different for workers exposed to higher levels of local labor market concentration, a potential source of employer market power. I exploit measurement error in state unemployment rates that led to quasi-random assignment of UI durations in the U.S. during the Great Recession. Using matched employer-employee data from the Longitudinal Employer-Household Dynamics program, I find that UI extensions lengthen nonemployment durations by one week and cause economically meaningful but not statistically significant increases in earnings. The UI-earnings effect is significantly lower at higher levels of concentration, while there is no difference in the UI-duration effect. The lower UI-earnings effect is driven by the extremes of the distribution of concentration. My results suggest that match improvements from UI are attenuated at higher levels of concentration.View Full Paper PDF
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Working PaperThe Mortality Risk of Raising Grandchildren in the United States
February 2026
Working Paper Number:
CES-26-13
In the United States, grandparents who live with and provide primary care to their grandchildren have emerged as a particularly vulnerable group since the 1990s. Using confidential data from the U.S. Census Bureau and Social Security Administration, this study linked individuals aged 50 years or older from the 2000 census long-form sample to their death records from 2000'2019 (weighted n = 64,027,000) and examined the longitudinal association between coresident grandparenting status and mortality for non-Hispanic Whites, non-Hispanic Blacks, Hispanics, and Asians. We found consistently higher rates of mortality for White coresident grandparents and lower rates for Asian coresident grandparents, regardless of the duration of primary caregiving, compared to their peers without coresident grandchildren. We also found increased risks of mortality among Hispanic long-term primary caregivers but reduced risks among Black short-term primary caregivers, compared to their peers without coresident grandchildren.View Full Paper PDF
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Working PaperCareers of Minimum Wage Workers
January 2026
Working Paper Number:
CES-26-07
We characterize the careers of minimum wage workers by merging SIPP panels covering 1992-2016 into the LEHD. A long-run analysis shows strong earnings growth for these workers in subsequent decades, becoming indistinguishable from peers earning modestly more initially. Most of this growth is due to the steep earnings trajectories of young workers. Older workers earning minimum wages show a modest dip in earnings at that moment compared to earlier and later periods. Increases in state minimum wages do not significantly alter the future careers of workers who are on the minimum wage when the increases occur.View Full Paper PDF
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Working PaperNon-Random Assignment of Individual Identifiers and Selection into Linked Data: Implications for Research
January 2026
Working Paper Number:
CES-26-06
The U.S. Census Bureau's Person Identification Validation System facilitates anonymous linkages between survey and administrative records by assigning Protected Identification Keys (PIKs) to person records. While PIK assignment is generally accurate, some person records are not successfully assigned a PIK, which can lead to sample selection bias in analyses of linked data. Using the American Community Survey (ACS) and the Current Population Survey Annual Social and Economic Supplement (CPS ASEC) between 2005 and 2022, we corroborate and extend existing findings on the drivers of PIK assignment, showing that the rate of PIK assignment varies widely across socio-demographic subgroups. Using earnings as a test case, we then show that limiting a survey sample of wage earners to person records with PIKs or successful linkages to W-2 wage records tends to overestimate self-reported wage earnings, on average, indicative of linkage-induced selection bias. In a validation exercise, we demonstrate that reweighting methods, such as inverse probability weighting or entropy balancing, can mitigate this bias.View Full Paper PDF
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Working PaperIntegrating Multiple U.S. Census Bureau Data Assets to Create Standardized Profiles of Program Participants
January 2026
Working Paper Number:
CES-26-01
The Foundations for Evidence-Based Policymaking Act of 2018 (Evidence Act) directed federal agencies to systematically use data when making policy decisions. In response, the U.S. Census Bureau established the Evidence Group within its Center for Economic Studies (CES). With an interdisciplinary team of economists, sociologists, and statisticians, the Evidence Group can support the broader federal government in their efforts to use existing data to improve program operations without increasing respondent burden. For federal agencies administering social safety net and business assistance programs in particular, the team provides a no-cost evidence-building service that links program records to Census Bureau data assets and creates a series of standardized tables describing participants, their economic outcomes prior to program entry, and the communities where they live. These tables provide partner agencies with the detailed information they need to better understand their participants and potentially make their programs more accountable and effective in reaching their target populations. In this working paper, we describe the standardized tables themselves as well as the data assets available at the Census Bureau to create these tables, the data files produced by the table production process, and the methodology used to merge and harmonize data on participants and subsequently calculate unbiased and accurate estimates. We conclude with a brief discussion of steps taken to ensure confidentiality and data security. This documentation is intended to facilitate proper use and understanding of the standardized tables by partner agencies as well as researchers who are interested in leveraging these tools to explore characteristics of their samples of interest.View Full Paper PDF
