Papers Containing Tag(s): 'Social Security'
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Viewing papers 1 through 10 of 132
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Working PaperPrivate Equity and Workers: Modeling and Measuring Monopsony, Implicit Contracts, and Efficient Reallocation
June 2025
Working Paper Number:
CES-25-37
We measure the real effects of private equity buyouts on worker outcomes by building a new database that links transactions to matched employer-employee data in the United States. To guide our empirical analysis, we derive testable implications from three theories in which private equity managers alter worker outcomes: (1) exertion of monopsony power in concentrated markets, (2) breach of implicit contracts with targeted groups of workers, including managers and top earners, and (3) efficient reallocation of workers across plants. We do not find any evidence that private equity-backed firms vary wages and employment based on local labor market power proxies. Wage losses are also very similar for managers and top earners. Instead, we find strong evidence that private equity managers downsize less productive plants relative to productive plants while simultaneously reallocating high-wage workers to more productive plants. We conclude that post-buyout employment and wage dynamics are consistent with professional investors providing incentives to increase productivity and monitor the companies in which they invest.View Full Paper PDF
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Working PaperGeographic 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.View Full Paper PDF
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Working PaperWork Organization and Cumulative Advantage
March 2025
Working Paper Number:
CES-25-18
Over decades of wage stagnation, researchers have argued that reorganizing work can boost pay for disadvantaged workers. But upgrading jobs could inadvertently shift hiring away from those workers, exacerbating their disadvantage. We theorize how work organization affects cumulative advantage in the labor market, or the extent to which high-paying positions are increasingly allocated to already-advantaged workers. Specifically, raising technical skill demands exacerbates cumulative advantage by shifting hiring towards higher-skilled applicants. In contrast, when employers increase autonomy or skills learned on-the-job, they raise wages to buy worker consent or commitment, rather than pre-existing skill. To test this idea, we match administrative earnings to task descriptions from job posts. We compare earnings for workers hired into the same occupation and firm, but under different task allocations. When employers raise complexity and autonomy, new hires' starting earnings increase and grow faster. However, while the earnings boost from complex, technical tasks shifts employment toward workers with higher prior earnings, worker selection changes less for tasks learned on-the-job and very little for high autonomy tasks. These results demonstrate how reorganizing work can interrupt cumulative advantage.View Full Paper PDF
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Working PaperThe Design of Sampling Strata for the National Household Food Acquisition and Purchase Survey
February 2025
Working Paper Number:
CES-25-13
The National Household Food Acquisition and Purchase Survey (FoodAPS), sponsored by the United States Department of Agriculture's (USDA) Economic Research Service (ERS) and Food and Nutrition Service (FNS), examines the food purchasing behavior of various subgroups of the U.S. population. These subgroups include participants in the Supplemental Nutrition Assistance Program (SNAP) and the Special Supplemental Nutrition Program for Women, Infants, and Children (WIC), as well as households who are eligible for but don't participate in these programs. Participants in these social protection programs constitute small proportions of the U.S. population; obtaining an adequate number of such participants in a survey would be challenging absent stratified sampling to target SNAP and WIC participating households. This document describes how the U.S. Census Bureau (which is planning to conduct future versions of the FoodAPS survey on behalf of USDA) created sampling strata to flag the FoodAPS targeted subpopulations using machine learning applications in linked survey and administrative data. We describe the data, modeling techniques, and how well the sampling flags target low-income households and households receiving WIC and SNAP benefits. We additionally situate these efforts in the nascent literature on the use of big data and machine learning for the improvement of survey efficiency.View Full Paper PDF
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Working PaperCTC 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.View Full Paper PDF
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Working PaperEITC 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.View Full Paper PDF
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Working PaperTip of the Iceberg: Tip Reporting at U.S. Restaurants, 2005-2018
November 2024
Working Paper Number:
CES-24-68
Tipping is a significant form of compensation for many restaurant jobs, but it is poorly measured and therefore not well understood. We combine several large administrative and survey datasets and document patterns in tip reporting that are consistent with systematic under-reporting of tip income. Our analysis indicates that although the vast majority of tipped workers do report earning some tips, the dollar value of tips is under-reported and is sensitive to reporting incentives. In total, we estimate that about eight billion in tips paid at full-service, single-location, restaurants were not captured in tax data annually over the period 2005-2018. Due to changes in payment methods and reporting incentives, tip reporting has increased over time. Our findings have implications for downstream measures dependent on accurate measures of compensation including poverty measurement among tipped restaurant workers.View Full Paper PDF
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Working PaperThe Census Historical Environmental Impacts Frame
October 2024
Working Paper Number:
CES-24-66
The Census Bureau's Environmental Impacts Frame (EIF) is a microdata infrastructure that combines individual-level information on residence, demographics, and economic characteristics with environmental amenities and hazards from 1999 through the present day. To better understand the long-run consequences and intergenerational effects of exposure to a changing environment, we expand the EIF by extending it backward to 1940. The Historical Environmental Impacts Frame (HEIF) combines the Census Bureau's historical administrative data, publicly available 1940 address information from the 1940 Decennial Census, and historical environmental data. This paper discusses the creation of the HEIF as well as the unique challenges that arise with using the Census Bureau's historical administrative data.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
