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Integrating Multiple U.S. Census Bureau Data Assets to Create Standardized Profiles of Program Participants
January 2026
Working Paper Number:
CES-26-01
The Foundations for Evidence-Based Policymaking Act of 2018 (Evidence Act) directed federal agencies to systematically use data when making policy decisions. In response, the U.S. Census Bureau established the Evidence Group within its Center for Economic Studies (CES). With an interdisciplinary team of economists, sociologists, and statisticians, the Evidence Group can support the broader federal government in their efforts to use existing data to improve program operations without increasing respondent burden. For federal agencies administering social safety net and business assistance programs in particular, the team provides a no-cost evidence-building service that links program records to Census Bureau data assets and creates a series of standardized tables describing participants, their economic outcomes prior to program entry, and the communities where they live. These tables provide partner agencies with the detailed information they need to better understand their participants and potentially make their programs more accountable and effective in reaching their target populations. In this working paper, we describe the standardized tables themselves as well as the data assets available at the Census Bureau to create these tables, the data files produced by the table production process, and the methodology used to merge and harmonize data on participants and subsequently calculate unbiased and accurate estimates. We conclude with a brief discussion of steps taken to ensure confidentiality and data security. This documentation is intended to facilitate proper use and understanding of the standardized tables by partner agencies as well as researchers who are interested in leveraging these tools to explore characteristics of their samples of interest.
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Redesigning the Longitudinal Business Database
May 2021
Working Paper Number:
CES-21-08
In this paper we describe the U.S. Census Bureau's redesign and production implementation of the Longitudinal Business Database (LBD) first introduced by Jarmin and Miranda (2002). The LBD is used to create the Business Dynamics Statistics (BDS), tabulations describing the entry, exit, expansion, and contraction of businesses. The new LBD and BDS also incorporate information formerly provided by the Statistics of U.S. Businesses program, which produced similar year-to-year measures of employment and establishment flows. We describe in detail how the LBD is created from curation of the input administrative data, longitudinal matching, retiming of economic census-year births and deaths, creation of vintage consistent industry codes and noise factors, and the creation and cleaning of each year of LBD data. This documentation is intended to facilitate the proper use and understanding of the data by both researchers with approved projects accessing the LBD microdata and those using the BDS tabulations.
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United States Earnings Dynamics: Inequality, Mobility, and Volatility
September 2020
Working Paper Number:
CES-20-29
Using data from the Census Bureau's Longitudinal Employer-Household Dynamics (LEHD) infrastructure files, we study changes over time and across sub-national populations in the distribution of real labor earnings. We consider four large MSAs (Detroit, Los Angeles, New York, and San Francisco) for the period 1998 to 2017, with particular attention paid to the subperiods before, during, and after the Great Recession. For the four large MSAs we analyze, there are clear national trends represented in each of the local areas, the most prominent of which is the increase in the share of earnings accruing to workers at the top of the earnings distribution in 2017 compared with 1998. However, the magnitude of these trends varies across MSAs, with New York and San Francisco showing relatively large increases and Los Angeles somewhere in the middle relative to Detroit whose total real earnings distribution is relatively stable over the period. Our results contribute to the emerging literature on differences between national and regional economic outcomes, exemplifying what will be possible with a new data exploration tool'the Earnings and Mobility Statistics (EAMS) web application'currently under development at the U.S. Census Bureau.
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Addressing Data Gaps:
Four New Lines of Inquiry in the 2017 Economic Census
September 2019
Working Paper Number:
CES-19-28
We describe four new lines of inquiry added to the 2017 Economic Census regarding (i) retail health clinics, (ii) management practices in health care services, (iii) self-service in retail and service industries, and (iv) water use in manufacturing and mining industries. These were proposed by economists from the U.S. Census Bureau's Center for Economic Studies in order to fill data gaps in current Census Bureau products concerning the U.S. economy. The new content addresses such issues as the rise in importance of health care and its complexity, the adoption of automation technologies, and the importance of measuring water, a critical input to many manufacturing and mining industries.
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The Parental Gender Earnings Gap in the United States
January 2017
Working Paper Number:
CES-17-68
This paper examines the parental gender earnings gap, the within-couple differences in earnings over time, before and after the birth of a child. The presence and timing of children are important components of the gender wage gap, but there is selection in both decisions. We estimate the earnings gap between male and female spouses over time, which allows us to control for this timing choice as well as other shared external earnings shifters, such as the local labor market. We use Social Security Administration Detail Earnings Records (SSA-DER) data linked to the Survey of Income and Program Participation (SIPP) to examine a panel of earnings from 1978 to 2011 for the individuals in the SIPP sample. Our main results show that the spousal earnings gap doubles between two years before the birth of the first child and the year after that child is born. After the child's first year of life the gap continues to grow for the next five years, but at a much slower rate, then tapers off and even begins to fall once the child reaches school-age.
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LEHD Data Documentation LEHD-OVERVIEW-S2008-rev1
December 2011
Working Paper Number:
CES-11-43
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Using 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.
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Consistent Cell Means for Topcoded Incomes in the Public Use March CPS (1976-2007)
March 2008
Working Paper Number:
CES-08-06
Using the internal March CPS, we create and in this paper distribute to the larger research community a cell mean series that provides the mean of all income values above the topcode for any income source of any individual in the public use March CPS that has been topcoded since 1976. We also describe our construction of this series. When we use this series together with the public use March CPS, we closely match the yearly mean income levels and income inequalities of the U.S. population found using the internal March CPS data.
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Trends in the Relative Household Income of Working-Age Men with Work Limitations: Correcting the Record Using Internal Current Population Survey Data
March 2008
Working Paper Number:
CES-08-05
Previous research measuring the economic well-being of working-age men with work limitations relative to such men without work limitations in the public use March Current Population Survey (CPS) systematically understates the mean household income of both groups; overstates the relative household income of those with work limitations; and understates the decline in their relative household income over time. Using the internal March CPS, we demonstrate this by creating a cell mean series beginning in 1975 that provides the mean reported income of all topcoded persons for each source of income in the public use March CPS data. Using our cell mean series with the public use March CPS, we closely match the yearly mean income of working-age men with and without work limitations over the period 1987-2004 in the internal data and show that this match is superior to ones using alternative methods of correcting for topcoding currently used in the disability literature. We then provide levels and trends in the relative income of working-age men with work limitations from 1980-2006, the earliest year in the March CPS that such comparisons can be made.
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Using Worker Flows in the Analysis of the Firm
August 2003
Working Paper Number:
tp-2003-09
This paper uses a novel approach to measure firm entry and exit, mergers and
acquisition. It uses information about the flows of clusters of workers across business
units to identify longitudinal linkage relationships in longitudinal business data. These
longitudinal relationships may be the result of either administrative or economic changes
and we explore both types of newly identified longitudinal relationships. In particular,
we develop a set of criteria based on worker flows to identify changes in firm
relationships ? such as mergers and acquisitions, administrative identifier changes and
outsourcing. We demonstrate how this new data infrastructure and this cluster flow
methodology can be used to better differentiate true firm entry/exit and simple changes in
administrative identifiers. We explore the role of outsourcing in a variety of ways but in
particular the outsourcing of workers to the temporary help industry. While the primary
focus is on developing the data infrastructure and the methodology to identify and
interpret these clustered flows of workers, we conclude the paper with an analysis of the
impact of these changes on the earnings of workers.
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