Papers Containing Keywords(s): 'provided census'
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Viewing papers 1 through 10 of 11
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Working PaperLODES 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.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 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 PaperThe Impact of Household Surveys on 2020 Census Self-Response
July 2022
Working Paper Number:
CES-22-24
Households who were sampled in 2019 for the American Community Survey (ACS) had lower self-response rates to the 2020 Census. The magnitude varied from -1.5 percentage point for household sampled in January 2019 to -15.1 percent point for households sampled in December 2019. Similar effects are found for the Current Population Survey (CPS) as well.View Full Paper PDF
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Working PaperAgglomeration Spillovers and Persistence: New Evidence from Large Plant Openings
June 2022
Working Paper Number:
CES-22-21
We use confidential Census microdata to compare outcomes for plants in counties that 'win' a new plant to plants in similar counties that did not to receive the new plant, providing empirical evidence on the economic theories used to justify local industrial policies. We find little evidence that the average highly incentivized large plant generates significant productivity spillovers. Our semiparametric estimates of the overall local agglomeration function indicate that residual TFP is linear for the range of 'agglomeration' densities most frequently observed, suggesting local economic shocks do not push local economies to a new higher equilibrium. Examining changes twenty years after the new plant entrant, we find some evidence of persistent, positive increases in winning county-manufacturing shares that are not driven by establishment births.View Full Paper PDF
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Working PaperMeasuring the Impact of COVID-19 on Businesses and People: Lessons from the Census Bureau's Experience
January 2021
Working Paper Number:
CES-21-02
We provide an overview of Census Bureau activities to enhance the consistency, timeliness, and relevance of our data products in response to the COVID-19 pandemic. We highlight new data products designed to provide timely and granular information on the pandemic's impact: the Small Business Pulse Survey, weekly Business Formation Statistics, the Household Pulse Survey, and Community Resilience Estimates. We describe pandemic-related content introduced to existing surveys such as the Annual Business Survey and the Current Population Survey. We discuss adaptations to ensure the continuity and consistency of existing data products such as principal economic indicators and the American Community Survey.View Full Paper PDF
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Working PaperDetermination of the 2020 U.S. Citizen Voting Age Population (CVAP) Using Administrative Records and Statistical Methodology Technical Report
October 2020
Working Paper Number:
CES-20-33
This report documents the efforts of the Census Bureau's Citizen Voting-Age Population (CVAP) Internal Expert Panel (IEP) and Technical Working Group (TWG) toward the use of multiple data sources to produce block-level statistics on the citizen voting-age population for use in enforcing the Voting Rights Act. It describes the administrative, survey, and census data sources used, and the four approaches developed for combining these data to produce CVAP estimates. It also discusses other aspects of the estimation process, including how records were linked across the multiple data sources, and the measures taken to protect the confidentiality of the data.View Full Paper PDF
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Working PaperAssessing Coverage and Quality of the 2007 Prototype Census Kidlink Database
September 2015
Working Paper Number:
carra-2015-07
The Census Bureau is conducting research to expand the use of administrative records data in censuses and surveys to decrease respondent burden and reduce costs while improving data quality. Much of this research (e.g., Rastogi and O''Hara (2012), Luque and Bhaskar (2014)) hinges on the ability to integrate multiple data sources by linking individuals across files. One of the Census Bureau's record linkage methodologies for data integration is the Person Identification Validation System or PVS. PVS assigns anonymous and unique IDs (Protected Identification Keys or PIKs) that serve as linkage keys across files. Prior research showed that integrating 'known associates' information into PVS's reference files could potentially enhance PVS's PIK assignment rates. The term 'known associates' refers to people that are likely to be associated with each other because of a known common link (such as family relationships or people sharing a common address), and thus, to be observed together in different files. One of the results from this prior research was the creation of the 2007 Census Kidlink file, a child-level file linking a child's Social Security Number (SSN) record to the SSN of those identified as the child's parents. In this paper, we examine to what extent the 2007 Census Kidlink methodology was able to link parents SSNs to children SSN records, and also evaluate the quality of those links. We find that in approximately 80 percent of cases, at least one parent was linked to the child's record. Younger children and noncitizens have a higher percentage of cases where neither parent could be linked to the child. Using 2007 tax data as a benchmark, our quality evaluation results indicate that in at least 90 percent of the cases, the parent-child link agreed with those found in the tax data. Based on our findings, we propose improvements to the 2007 Kidlink methodology to increase child-parent links, and discuss how the creation of the file could be operationalized moving forward.View Full Paper PDF
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Working PaperBIAS IN FOOD STAMPS PARTICIPATION ESTIMATES IN THE PRESENCE OF MISREPORTING ERROR
March 2013
Working Paper Number:
CES-13-13
This paper focuses on how survey misreporting of food stamp receipt can bias demographic estimation of program participation. Food stamps is a federally funded program which subsidizes the nutrition of low-income households. In order to improve the reach of this program, studies on how program participation varies by demographic groups have been conducted using census data. Census data are subject to a lot of misreporting error, both underreporting and over-reporting, which can bias the estimates. The impact of misreporting error on estimate bias is examined by calculating food stamp participation rates, misreporting rates, and bias for select household characteristics (covariates).View Full Paper PDF
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Working PaperUsing Internal Current Population Survey Data to Reevaluate Trends in Labor Earnings Gaps by Gender, Race, and Education Level
July 2008
Working Paper Number:
CES-08-18
Most empirical studies of trends in labor earnings gaps by gender, race or education level are based on data from the public use March Current Population Survey (CPS). Using the internal March CPS, we show that inconsistent topcoding in the public use data will understate these gaps and inaccurately capture their trends. We create a cell mean series beginning in 1975 that provides the mean of all values above the topcode for each income source in the public use March CPS and better approximate earnings gaps found in the internal March CPS than was previously possible using publically available data.View Full Paper PDF
