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Tip of the Iceberg: How Much Do Tips Bunch at Reporting Thresholds?
June 2026
Working Paper Number:
CES-26-40
We study the importance of bunching in the context of tip-income reporting by workers at full-service, single-unit restaurants in the United States. Using tax reports at both the individual and the employer levels, we show that reported tip income varies with minimum-wage laws that provide an incentive for tipped workers to report some, but not necessarily all, of their tips. As a result, reported tips bunch at the minimum required threshold. We quantify missing tips due to bunching at nearly $63 million per year in 2018 dollars, on average over the period 2005-2018. Bunching is stronger for jobs at small employers and in the earlier part of the time series and declined monotonically from 2010 to 2018. Using restaurant-level revenue data, we also estimate the total value of unreported tips assuming an average tip rate of 12%. We find that tips are missing throughout the distribution. All told, missing tips exceed $4 billion per year, implying that bunching explains only 1.5% of all missing tips.
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Employees in the US Nonprofit Sector
May 2026
Working Paper Number:
CES-26-33
The nonprofit sector employs roughly 10% of the American workforce, making it the third largest workforce behind the retail and manufacturing sectors. Despite this, relatively little is known about its employees. This paper is the first to use comprehensive administrative tax data, covering the near-universe of workers in the US, to quantify and explain the causes of the nonprofit pay differential. Unconditionally, we find the nonprofit earnings penalty to be 12% relative to for-profit workers. Estimating an 'AKM' worker-firm job ladder model, we show that most of the penalty is causal and not driven by selection. We also document considerable heterogeneity across industries, both in terms of earnings premia/penalties and worker selection, and show that nonprofit and for-profit earnings have been converging over time.
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Non-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.
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Gifted Identification Across the Distribution of Family Income
December 2025
Authors:
Quentin Brummet,
Andrew Penner,
Emily Penner,
Leah R. Clark,
Michelle Spiegel,
Paul Hanselman,
Nicholas J. Ainsworth,
Aaron J. Ainsworth,
Christopher Cleveland,
Jacob Hibel,
Andrew Saultz
Working Paper Number:
CES-25-73
Currently, 6.1 percent of K-12 students in the United States receive gifted education. Using education and IRS data that provide information on students and their family income, we show pronounced differences in who schools identify as gifted across the distribution of family income. Under 4 percent of students in the lowest income percentile are identified as gifted, compared with 20 percent of those in the top income percentile. Income-based differences persist after accounting for student test scores and exist across students of different sexes and racial/ethnic groups, underscoring the importance of family resources for gifted identification in schools.
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Measurement Matters: Financial Reporting and Productivity
December 2025
Working Paper Number:
CES-25-72
We examine how differences in financial reporting practices shape firm productivity. Leveraging new audit questions in the U.S. Census Bureau's 2021 Management and Organizational Practices Survey (MOPS), and complementary tax return data from the Internal Revenue Service (IRS) and detailed financial records from Sageworks, we find that (i) variation in reporting quality explains 10-20 percent of intra-industry total factor productivity dispersion, and (ii) evidence of complementarity between the effects of financial audits and management practices driving firm productivity. We then examine the underlying mechanisms. First, audits function as a managerial technology, improving the precision of internal information and raising efficiency, with stronger effects in competitive, low-margin industries and among younger firms. Second, exploiting cross-state variation in tax incentives, we show that audits constrain underreporting and mitigate the downward bias in measured productivity. Together, these results highlight the underrated importance of financial reporting quality driving firm productivity.
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LODES Design and Methodology Report: Methodology Version 7
August 2025
Working Paper Number:
CES-25-52
The purpose of this report is to document the important features of Version 7 of the LEHD Origin-Destination Employment Statistics (LODES) processing system. This includes data sources, data processing methodology, confidentiality protection methodology, some quality measures, and a high-level description of the published data. The intended audience for this document includes LODES data users, Local Employment Dynamics (LED) Partnership members, U.S. Census Bureau management, program quality auditors, and current and future research and development staff members.
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Measuring the Business Dynamics of Firms that Received Pandemic Relief Funding: Findings from a New Experimental BDS Data Product
January 2025
Working Paper Number:
CES-25-05
This paper describes a new experimental data product from the U.S. Census Bureau's Center for Economic Studies: the Business Dynamics Statistics (BDS) of firms that received Small Business Administration (SBA) pandemic funding. This new product, BDS-SBA COVID, expands the set of currently published BDS tables by linking loan-level program participation data from SBA to internal business microdata at the U.S. Census Bureau. The linked programs include the Paycheck Protection Program (PPP), COVID Economic Injury Disaster Loans (COVID-EIDL), the Restaurant Revitalization Fund (RRF), and Shuttered Venue Operators Grants (SVOG). Using these linked data, we tabulate annual firm and establishment counts, measures of job creation and destruction, and establishment entry and exit for recipients and non-recipients of program funds in 2020-2021. We further stratify the tables by timing of loan receipt and loan size, and business characteristics including geography, industry sector, firm size, and firm age. We find that for the youngest firms that received PPP, the timing of receipt mattered. Receiving an early loan correlated with a lower job destruction rate compared to non-recipients and businesses that received a later loan. For the smallest firms, simply participating in PPP was associated with lower employment loss. The timing of PPP receipt was also related to establishment exit rates. For businesses of nearly all ages, those that received an early loan exited at a lower rate in 2022 than later loan recipients.
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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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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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EITC Participation Results and IRS-Census Match Methodology, Tax Year 2021
December 2024
Working Paper Number:
CES-24-75
The Earned Income Tax Credit (EITC), enacted in 1975, offers a refundable tax credit to low income working families. This paper provides taxpayer and dollar participation estimates for the EITC covering tax year 2021. The estimates derive from an approach that relies on 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 EITC 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 EITC program at a rate of 78 percent while dollar participation was 81 percent.
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