CREAT: Census Research Exploration and Analysis Tool

Papers Containing Tag(s): 'Comparison of Putative Reidentification Rates'

The following papers contain search terms that you selected. From the papers listed below, you can navigate to the PDF, the profile page for that working paper, or see all the working papers written by an author. You can also explore tags, keywords, and authors that occur frequently within these papers.
Click here to search again

Frequently Occurring Concepts within this Search

Composite Person Record - 14

American Community Survey - 13

Longitudinal Employer Household Dynamics - 13

Protected Identification Key - 12

Center for Economic Studies - 11

Internal Revenue Service - 11

Master Address File - 11

Bureau of Labor Statistics - 9

North American Industry Classification System - 9

Quarterly Workforce Indicators - 9

Quarterly Census of Employment and Wages - 9

Social Security Number - 8

Individual Characteristics File - 8

Local Employment Dynamics - 8

Office of Personnel Management - 8

Current Population Survey - 8

Cornell University - 7

2010 Census - 7

Decennial Census - 7

Employment History File - 7

Employer Characteristics File - 7

National Science Foundation - 7

Alfred P Sloan Foundation - 7

Disclosure Review Board - 6

Metropolitan Statistical Area - 6

Unemployment Insurance - 6

Census Bureau Disclosure Review Board - 5

Business Register - 5

Core Based Statistical Area - 5

Social Security Administration - 5

American Economic Association - 5

Standard Industrial Classification - 5

Service Annual Survey - 5

Employer Identification Numbers - 5

Research Data Center - 5

Successor Predecessor File - 5

CDF - 4

MAF-ARF - 4

Cumulative Density Function - 4

Housing and Urban Development - 4

Department of Housing and Urban Development - 4

Federal Statistical Research Data Center - 4

Longitudinal Business Database - 4

Federal Tax Information - 4

Business Master File - 4

American Housing Survey - 4

Business Employment Dynamics - 4

Business Register Bridge - 4

MAFID - 3

LEHD Program - 3

Social Security - 3

Person Validation System - 3

Census Numident - 3

Office of Management and Budget - 3

University of Chicago - 3

Indian Health Service - 3

Standard Statistical Establishment List - 3

American Economic Review - 3

Probability Density Function - 3

North American Industry Classi - 3

HHS - 3

Postal Service - 3

Survey of Income and Program Participation - 3

Viewing papers 1 through 10 of 16


  • Working Paper

    A Simulated Reconstruction and Reidentification Attack on the 2010 U.S. Census

    August 2025

    Working Paper Number:

    CES-25-57

    For the last half-century, it has been a common and accepted practice for statistical agencies, including the United States Census Bureau, to adopt different strategies to protect the confidentiality of aggregate tabular data products from those used to protect the individual records contained in publicly released microdata products. This strategy was premised on the assumption that the aggregation used to generate tabular data products made the resulting statistics inherently less disclosive than the microdata from which they were tabulated. Consistent with this common assumption, the 2010 Census of Population and Housing in the U.S. used different disclosure limitation rules for its tabular and microdata publications. This paper demonstrates that, in the context of disclosure limitation for the 2010 Census, the assumption that tabular data are inherently less disclosive than their underlying microdata is fundamentally flawed. The 2010 Census published more than 150 billion aggregate statistics in 180 table sets. Most of these tables were published at the most detailed geographic level'individual census blocks, which can have populations as small as one person. Using only 34 of the published table sets, we reconstructed microdata records including five variables (census block, sex, age, race, and ethnicity) from the confidential 2010 Census person records. Using only published data, an attacker using our methods can verify that all records in 70% of all census blocks (97 million people) are perfectly reconstructed. We further confirm, through reidentification studies, that an attacker can, within census blocks with perfect reconstruction accuracy, correctly infer the actual census response on race and ethnicity for 3.4 million vulnerable population uniques (persons with race and ethnicity different from the modal person on the census block) with 95% accuracy. Having shown the vulnerabilities inherent to the disclosure limitation methods used for the 2010 Census, we proceed to demonstrate that the more robust disclosure limitation framework used for the 2020 Census publications defends against attacks that are based on reconstruction. Finally, we show that available alternatives to the 2020 Census Disclosure Avoidance System would either fail to protect confidentiality, or would overly degrade the statistics' utility for the primary statutory use case: redrawing the boundaries of all of the nation's legislative and voting districts in compliance with the 1965 Voting Rights Act.
    View Full Paper PDF
  • Working Paper

    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.
    View Full Paper PDF
  • Working Paper

    Driving 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
  • Working Paper

    Mobility, Opportunity, and Volatility Statistics (MOVS): Infrastructure Files and Public Use Data

    April 2024

    Working Paper Number:

    CES-24-23

    Federal statistical agencies and policymakers have identified a need for integrated systems of household and personal income statistics. This interest marks a recognition that aggregated measures of income, such as GDP or average income growth, tell an incomplete story that may conceal large gaps in well-being between different types of individuals and families. Until recently, longitudinal income data that are rich enough to calculate detailed income statistics and include demographic characteristics, such as race and ethnicity, have not been available. The Mobility, Opportunity, and Volatility Statistics project (MOVS) fills this gap in comprehensive income statistics. Using linked demographic and tax records on the population of U.S. working-age adults, the MOVS project defines households and calculates household income, applying an equivalence scale to create a personal income concept, and then traces the progress of individuals' incomes over time. We then output a set of intermediate statistics by race-ethnicity group, sex, year, base-year state of residence, and base-year income decile. We select the intermediate statistics most useful in developing more complex intragenerational income mobility measures, such as transition matrices, income growth curves, and variance-based volatility statistics. We provide these intermediate statistics as part of a publicly released data tool with downloadable flat files and accompanying documentation. This paper describes the data build process and the output files, including a brief analysis highlighting the structure and content of our main statistics.
    View Full Paper PDF
  • Working Paper

    A Simulated Reconstruction and Reidentification Attack on the 2010 U.S. Census: Full Technical Report

    December 2023

    Working Paper Number:

    CES-23-63R

    For the last half-century, it has been a common and accepted practice for statistical agencies, including the United States Census Bureau, to adopt different strategies to protect the confidentiality of aggregate tabular data products from those used to protect the individual records contained in publicly released microdata products. This strategy was premised on the assumption that the aggregation used to generate tabular data products made the resulting statistics inherently less disclosive than the microdata from which they were tabulated. Consistent with this common assumption, the 2010 Census of Population and Housing in the U.S. used different disclosure limitation rules for its tabular and microdata publications. This paper demonstrates that, in the context of disclosure limitation for the 2010 Census, the assumption that tabular data are inherently less disclosive than their underlying microdata is fundamentally flawed. The 2010 Census published more than 150 billion aggregate statistics in 180 table sets. Most of these tables were published at the most detailed geographic level'individual census blocks, which can have populations as small as one person. Using only 34 of the published table sets, we reconstructed microdata records including five variables (census block, sex, age, race, and ethnicity) from the confidential 2010 Census person records. Using only published data, an attacker using our methods can verify that all records in 70% of all census blocks (97 million people) are perfectly reconstructed. We further confirm, through reidentification studies, that an attacker can, within census blocks with perfect reconstruction accuracy, correctly infer the actual census response on race and ethnicity for 3.4 million vulnerable population uniques (persons with race and ethnicity different from the modal person on the census block) with 95% accuracy. Having shown the vulnerabilities inherent to the disclosure limitation methods used for the 2010 Census, we proceed to demonstrate that the more robust disclosure limitation framework used for the 2020 Census publications defends against attacks that are based on reconstruction. Finally, we show that available alternatives to the 2020 Census Disclosure Avoidance System would either fail to protect confidentiality, or would overly degrade the statistics' utility for the primary statutory use case: redrawing the boundaries of all of the nation's legislative and voting districts in compliance with the 1965 Voting Rights Act. You are reading the full technical report. For the summary paper see https://doi.org/10.1162/99608f92.4a1ebf70.
    View Full Paper PDF
  • Working Paper

    LEHD Snapshot Documentation, Release S2021_R2022Q4

    November 2022

    Working Paper Number:

    CES-22-51

    The Longitudinal Employer-Household Dynamics (LEHD) data at the U.S. Census Bureau is a quarterly database of linked employer-employee data covering over 95% of employment in the United States. These data are used to produce a number of public-use tabulations and tools, including the Quarterly Workforce Indicators (QWI), LEHD Origin-Destination Employment Statistics (LODES), Job-to-Job Flows (J2J), and Post-Secondary Employment Outcomes (PSEO) data products. Researchers on approved projects may also access the underlying LEHD microdata directly, in the form of the LEHD Snapshot restricted-use data product. This document provides a detailed overview of the LEHD Snapshot as of release S2021_R2022Q4, including user guidance, variable codebooks, and an overview of the approvals needed to obtain access. Updates to the documentation for this and future snapshot releases will be made available in HTML format on the LEHD website.
    View Full Paper PDF
  • Working Paper

    The Children of HOPE VI Demolitions: National Evidence on Labor Market Outcomes

    November 2020

    Working Paper Number:

    CES-20-39

    We combine national administrative data on earnings and participation in subsidized housing to study how the demolition of 160 public housing projects'funded by the HOPE VI program'affected the adult labor market outcomes for 18,500 children. Our empirical strategy compares children exposed to the program to children drawn from thousands of non-demolished projects, adjusting for observable differences using a flexible estimator that combines features of matching and regression. We find that children who resided in HOPE VI projects earn 14% more at age 26 relative to children in comparable non-HOPE VI projects. These earnings gains are strongest for demolitions in large cities, particularly in neighborhoods with higher pre-demolition poverty rates and lower pre-demolition job accessibility. There is no evidence that the labor market gains are driven by improvements in household or neighborhood environments that promote human capital development in children. Rather, subsequent improvements in job accessibility represent a likely pathway for the results.
    View Full Paper PDF
  • Working Paper

    LEHD Infrastructure S2014 files in the FSRDC

    September 2018

    Authors: Lars Vilhuber

    Working Paper Number:

    CES-18-27R

    The Longitudinal Employer-Household Dynamics (LEHD) Program at the U.S. Census Bureau, with the support of several national research agencies, maintains a set of infrastructure files using administrative data provided by state agencies, enhanced with information from other administrative data sources, demographic and economic (business) surveys and censuses. The LEHD Infrastructure Files provide a detailed and comprehensive picture of workers, employers, and their interaction in the U.S. economy. This document describes the structure and content of the 2014 Snapshot of the LEHD Infrastructure files as they are made available in the Census Bureau's secure and restricted-access Research Data Center network. The document attempts to provide a comprehensive description of all researcher-accessible files, of their creation, and of any modifications made to the files to facilitate researcher access.
    View Full Paper PDF
  • Working Paper

    Developing a Residence Candidate File for Use With Employer-Employee Matched Data

    January 2017

    Working Paper Number:

    CES-17-40

    This paper describes the Longitudinal Employer-Household Dynamics (LEHD) program's ongoing efforts to use administrative records in a predictive model that describes residence locations for workers. This project was motivated by the discontinuation of a residence file produced elsewhere at the U.S. Census Bureau. The goal of the Residence Candidate File (RCF) process is to provide the LEHD Infrastructure Files with residence information that maintains currency with the changing state of administrative sources and represents uncertainty in location as a probability distribution. The discontinued file provided only a single residence per person/year, even when contributing administrative data may have contained multiple residences. This paper describes the motivation for the project, our methodology, the administrative data sources, the model estimation and validation results, and the file specifications. We find that the best prediction of the person-place model provides similar, but superior, accuracy compared with previous methods and performs well for workers in the LEHD jobs frame. We outline possibilities for further improvement in sources and modeling as well as recommendations on how to use the preference weights in downstream processing.
    View Full Paper PDF
  • Working Paper

    Two Perspectives on Commuting: A Comparison of Home to Work Flows Across Job-Linked Survey and Administrative Files

    January 2017

    Working Paper Number:

    CES-17-34

    Commuting flows and workplace employment data have a wide constituency of users including urban and regional planners, social science and transportation researchers, and businesses. The U.S. Census Bureau releases two, national data products that give the magnitude and characteristics of home to work flows. The American Community Survey (ACS) tabulates households' responses on employment, workplace, and commuting behavior. The Longitudinal Employer-Household Dynamics (LEHD) program tabulates administrative records on jobs in the LEHD Origin-Destination Employment Statistics (LODES). Design differences across the datasets lead to divergence in a comparable statistic: county-to-county aggregate commute flows. To understand differences in the public use data, this study compares ACS and LEHD source files, using identifying information and probabilistic matching to join person and job records. In our assessment, we compare commuting statistics for job frames linked on person, employment status, employer, and workplace and we identify person and job characteristics as well as design features of the data frames that explain aggregate differences. We find a lower rate of within-county commuting and farther commutes in LODES. We attribute these greater distances to differences in workplace reporting and to uncertainty of establishment assignments in LEHD for workers at multi-unit employers. Minor contributing factors include differences in residence location and ACS workplace edits. The results of this analysis and the data infrastructure developed will support further work to understand and enhance commuting statistics in both datasets.
    View Full Paper PDF