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.
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LEHD Infrastructure files in the Census RDC - Overview
June 2014
Working Paper Number:
CES-14-26
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 2011 Snapshot of the LEHD Infrastructure files as they are made available in the Census Bureaus 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 modifcations made to the files to facilitate researcher access.
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The LEHD Infrastructure Files and the Creation of the Quarterly Workforce Indicators
January 2006
Working Paper Number:
tp-2006-01
The Longitudinal Employer-Household Dynamics (LEHD) Program at the U.S. Census Bureau,
with the support of several national research agencies, has built 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. Beginning in 2003 and building on this infrastructure, the Census
Bureau has published the Quarterly Workforce Indicators (QWI), a new collection of data series
that offers unprecedented detail on the local dynamics of labor markets. Despite the fine detail,
confidentiality is maintained due to the application of state-of-the-art confidentiality protection
methods. This article describes how the input files are compiled and combined to create the infrastructure
files. We describe the multiple imputation methods used to impute in missing data and
the statistical matching techniques used to combine and edit data when a direct identifier match
requires improvement. Both of these innovations are crucial to the success of the final product. Finally,
we pay special attention to the details of the confidentiality protection system used to protect
the identity and micro data values of the underlying entities used to form the published estimates.
We provide a brief description of public-use and restricted-access data files with pointers to further
documentation for researchers interested in using these data.
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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.
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LEHD Infrastructure Files in the Census RDC: Overview of S2004 Snapshot
April 2011
Working Paper Number:
CES-11-13
The Longitudinal Employer-Household Dynamics (LEHD) Program at the U.S. Census Bureau, with the support of several national research agencies, has built 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 2004 Snapshot of the LEHD Infrastructure files as they are made available in the Census Bureau's Research Data Center network.
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LEHD Data Documentation LEHD-OVERVIEW-S2008-rev1
December 2011
Working Paper Number:
CES-11-43
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The Creation of the Employment Dynamics Estimates
July 2002
Working Paper Number:
tp-2002-13
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The Sensitivity of Economic Statistics to Coding Errors in Personal Identifiers
October 2002
Working Paper Number:
tp-2002-17
In this paper, we describe the sensitivity of small-cell flow statistics
to coding errors in the identity of the underlying entities. Specifically,
we present results based on a comparison of the U.S. Census Bureau's
Quarterly Workforce Indicators (QWI) before and after correcting for
such errors in SSN-based identifiers in the underlying individual wage
records. The correction used involves a novel application of existing
statistical matching techniques. It is found that even a very conservative
correction procedure has a sizable impact on the statistics. The
average bias ranges from 0.25 percent up to 15 percent for flow statistics,
and up to 5 percent for payroll aggregates.
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Confidentiality Protection in the Census Bureau Quarterly Workforce Indicators
February 2006
Working Paper Number:
tp-2006-02
The QuarterlyWorkforce Indicators are new estimates developed by the Census Bureau's Longitudinal
Employer-Household Dynamics Program as a part of its Local Employment Dynamics
partnership with 37 state Labor Market Information offices. These data provide detailed quarterly
statistics on employment, accessions, layoffs, hires, separations, full-quarter employment
(and related flows), job creations, job destructions, and earnings (for flow and stock categories of
workers). The data are released for NAICS industries (and 4-digit SICs) at the county, workforce
investment board, and metropolitan area levels of geography. The confidential microdata - unemployment
insurance wage records, ES-202 establishment employment, and Title 13 demographic
and economic information - are protected using a permanent multiplicative noise distortion factor.
This factor distorts all input sums, counts, differences and ratios. The released statistics are analytically
valid - measures are unbiased and time series properties are preserved. The confidentiality
protection is manifested in the release of some statistics that are flagged as "significantly distorted
to preserve confidentiality." These statistics differ from the undistorted statistics by a significant
proportion. Even for the significantly distorted statistics, the data remain analytically valid for
time series properties. The released data can be aggregated; however, published aggregates are
less distorted than custom postrelease aggregates. In addition to the multiplicative noise distortion,
confidentiality protection is provided by the estimation process for the QWIs, which multiply imputes
all missing data (including missing establishment, given UI account, in the UI wage record
data) and dynamically re-weights the establishment data to provide state-level comparability with
the BLS's Quarterly Census of Employment and Wages.
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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.
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Dynamically Consistent Noise Infusion and Partially Synthetic Data as Confidentiality Protection Measures for Related Time Series
July 2012
Working Paper Number:
CES-12-13
The Census Bureau's Quarterly Workforce Indicators (QWI) provide detailed quarterly statistics on employment measures such as worker and job flows, tabulated by worker characteristics in various combinations. The data are released for several levels of NAICS industries and geography, the lowest aggregation of the latter being counties. Disclosure avoidance methods are required to protect the information about individuals and businesses that contribute to the underlying data. The QWI disclosure avoidance mechanism we describe here relies heavily on the use of noise infusion through a permanent multiplicative noise distortion factor, used for magnitudes, counts, differences and ratios. There is minimal suppression and no complementary suppressions. To our knowledge, the release in 2003 of the QWI was the first large-scale use of noise infusion in any official statistical product. We show that the released statistics are analytically valid along several critical dimensions { measures are unbiased and time series properties are preserved. We provide an analysis of the degree to which confidentiality is protected. Furthermore, we show how the judicious use of synthetic data, injected into the tabulation process, can completely eliminate suppressions, maintain analytical validity, and increase the protection of the underlying confidential data.
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