Papers Containing Tag(s): 'Internal Revenue Service'
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John Voorheis - 22
Maggie R. Jones - 16
John Haltiwanger - 16
Martha Stinson - 15
Javier Miranda - 13
Viewing papers 51 through 60 of 334
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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
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Working PaperIncome, Wealth, and Environmental Inequality in the United States
October 2024
Working Paper Number:
CES-24-57
This paper explores the relationships between air pollution, income, wealth, and race by combining administrative data from U.S. tax returns between 1979'2016, various measures of air pollution, and sociodemographic information from linked survey and administrative data. In the first year of our data, the relationship between income and ambient pollution levels nationally is approximately zero for both non-Hispanic White and Black individuals. However, at every single percentile of the national income distribution, Black individuals are exposed to, on average, higher levels of pollution than White individuals. By 2016, the relationship between income and air pollution had steepened, primarily for Black individuals, driven by changes in where rich and poor Black individuals live. We utilize quasi-random shocks to income to examine the causal effect of changes in income and wealth on pollution exposure over a five year horizon, finding that these income'pollution elasticities map closely to the values implied by our descriptive patterns. We calculate that Black-White differences in income can explain ~10 percent of the observed gap in air pollution levels in 2016.View Full Paper PDF
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Working PaperSeparate but Not Equal: The Uneven Cost of Residential Segregation for Network-Based Hiring
October 2024
Working Paper Number:
CES-24-56
This paper studies how residential segregation by race and by education affects job search via neighbor networks. Using confidential microdata from the US Census Bureau, I measure segregation for each characteristic at both the individual level and the neighborhood level. My findings are manifold. At the individual level, future coworkership with new neighbors on the same block is less likely among segregated individuals than among integrated workers, irrespective of races and levels of schooling. The impacts are most adverse for the most socioeconomically disadvantaged demographics: Blacks and those without a high school education. At the block level, however, higher segregation along either dimension raises the likelihood of any future coworkership on the block for all racial or educational groups. My identification strategy, capitalizing on data granularity, allows a causal interpretation of these results. Together, they point to the coexistence of homophily and in-group competition for job opportunities in linking residential segregation to neighbor-based informal hiring. My subtle findings have important implications for policy-making.View Full Paper PDF
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Working PaperComparison of Child Reporting in the American Community Survey and Federal Income Tax Returns Based on California Birth Records
September 2024
Working Paper Number:
CES-24-55
This paper takes advantage of administrative records from California, a state with a large child population and a significant historical undercount of children in Census Bureau data, dependent information in the Internal Revenue Service (IRS) Form 1040 records, and the American Community Survey to characterize undercounted children and compare child reporting. While IRS Form 1040 records offer potential utility for adjusting child undercounting in Census Bureau surveys, this analysis finds overlapping reporting issues among various demographic and economic groups. Specifically, older children, those of Non-Hispanic Black mothers and Hispanic mothers, children or parents with lower English proficiency, children whose mothers did not complete high school, and families with lower income-to-poverty ratio were less frequently reported in IRS 1040 records than other groups. Therefore, using IRS 1040 dependent records may have limitations for accurately representing populations with characteristics associated with the undercount of children in surveys.View Full Paper PDF
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Working PaperTransitional Costs and the Decline of Coal: Worker-Level Evidence
September 2024
Working Paper Number:
CES-24-53
We examine the labor market impacts of the U.S. coal industry's decline using comprehensive administrative data on workers from 2005-2021. Coal workers most exposed to the industry's contraction experienced substantial earnings losses, equivalent to 1.6 years of predecline wages. These losses stem from both reduced employment duration (0.37 fewer years employed) and lower annual earnings (17 percent decline) between 2012-2019, relative to similar workers less exposed to coal's decline. Earnings reductions primarly occur when workers remain in local labor markets but are not employed in mining. While coal workers do not exhibit lower geographic mobility, relocation does not significantly mitigate their earnings losses.View Full Paper PDF
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Working PaperEarnings 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.View Full Paper PDF
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Working PaperRevisions 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.View Full Paper PDF
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Working PaperInternal Migration in the U.S. During the COVID-19 Pandemic
September 2024
Working Paper Number:
CES-24-50
Survey and administrative internal migration data disagree on whether the COVID-19 pandemic increased or decreased mobility in the U.S. Moreover, though scholars have theorized and documented migration in response to environmental hazards and economic shocks, the novel conditions posed by a global pandemic make it difficult to hypothesize whether and how American migration might change as a result. We link individual-level data from the United States Postal Service's National Change of Address (NCOA) registry to American Community Survey (ACS) and Current Population Survey (CPS-ASEC) responses and other administrative records to document changes in the level, geography, and composition of migrant flows between 2019 and 2021. We find a 2% increase in address changes between 2019 and 2020, representing an additional 603,000 moves, driven primarily by young adults, earners at the extremes of the income distribution, and individuals (as opposed to families) moving over longer distances. Though the number of address changes returned to pre-pandemic levels in 2021, the pandemic-era geographic and compositional shifts in favor of longer distance moves away from the Pacific and Mid-Atlantic regions toward the South and in favor of younger, individual movers persisted. We also show that at least part of the disconnect between survey, media, and administrative/third-party migration data sources stems from the apparent misreporting of address changes on Census Bureau surveys. Among ACS and CPS-ASEC householders linked to NCOA data and filing a permanent change of address in their 1-year survey response reference period, only around 68% of ACS and 49% of CPS-ASEC householders also reported living in a different residence one year ago in their survey response.View Full Paper PDF
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Working PaperDriving the Gig Economy
August 2024
Working Paper Number:
CES-24-42
Using rich administrative tax data, we explore the effects of the introduction of online ridesharing platforms on entry, employment and earnings in the Taxi and Limousine Services industry. Ridesharing dramatically increased the pace of entry of workers into the industry. New entrants were more likely to be young, female, White and U.S. born, and to combine earnings from ridesharing with wage and salary earnings. Displaced workers have found ridesharing to be a substantially more attractive fallback option than driving a taxi. Ridesharing also affected the incumbent taxi driver workforce. The exit rates of low-earning taxi drivers increased following the introduction of ridesharing in their city; exit rates of high-earning taxi drivers were little affected. In cities without regulations limiting the size of the taxi fleet, both groups of drivers experienced earnings losses following the introduction of ridesharing. These losses were ameliorated or absent in more heavily regulated markets.View Full Paper PDF
