Although an increasing number of studies consider married or cohabiting couples as current, former, or potential co-workers, there is surprisingly little evidence on the extent to which couples work at the same workplace. This study provides benchmark estimates on the frequency with which opposite-sex married and cohabiting couples in the United States share the same occupation, industry, work location, and employer using Census 2000 responses linked with administrative records data. This study contains the first representative estimate of the fraction of couples that share an employer, which is in the range of 11% to 13%. These shared employers can account for much of couples' shared industry, occupation, and location of employment. Longitudinal data on the employment and residency indicates that co-working couples much more likely to have chosen the same employer than to have met at work.
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Design Comparison of LODES and ACS Commuting Data Products
October 2014
Working Paper Number:
CES-14-38
The Census Bureau produces two complementary data products, the American Community Survey (ACS) commuting and workplace data and the Longitudinal Employer-Household Dynamics (LEHD) Origin-Destination Employment Statistics (LODES), which can be used to answer questions about spatial, economic, and demographic questions relating to workplaces and home-to-work flows. The products are complementary in the sense that they measure similar activities but each has important unique characteristics that provide information that the other measure cannot. As a result of questions from data users, the Census Bureau has created this document to highlight the major design differences between these two data products. This report guides users on the relative advantages of each data product for various analyses and helps explain differences that may arise when using the products.2,3
As an overview, these two data products are sourced from different inputs, cover different populations and time periods, are subject to different sets of edits and imputations, are released under different confidentiality protection mechanisms, and are tabulated at different geographic and characteristic levels. As a general rule, the two data products should not be expected to match exactly for arbitrary queries and may differ substantially for some queries.
Within this document, we compare the two data products by the design elements that were deemed most likely to contribute to differences in tabulated data. These elements are: Collection, Coverage, Geographic and Longitudinal Scope, Job Definition and Reference Period, Job and Worker Characteristics, Location Definitions (Workplace and Residence), Completeness of Geographic Information and Edits/Imputations, Geographic Tabulation Levels, Control Totals, Confidentiality Protection and Suppression, and Related
Public-Use Data Products.
An in-depth data analysis'in aggregate or with the microdata'between the two data products will be the subject of a future technical report. The Census Bureau has begun a pilot project to integrate ACS microdata with LEHD administrative data to develop an enhanced frame of employment status, place of work, and commuting. The Census Bureau will publish quality metrics for person match rates, residence and workplace match rates, and commute distance comparisons.
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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.
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Labor Market Networks and Recovery from Mass Layoffs Before, During, and After the Great Recession
June 2015
Working Paper Number:
CES-15-14
We test the effects of labor market networks defined by residential neighborhoods on re-employment following mass layoffs. We develop two measures of labor market network strength. One captures the flows of information to job seekers about the availability of job vacancies at employers of workers in the network, and the other captures referrals provided to employers by other network members. These network measures are linked to more rapid re-employment following mass layoffs, and to re-employment at neighbors' employers. We also find evidence that network connections ' especially those that provide information about job vacancies ' became less productive during the Great Recession.
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Spatial Influences on the Employment of U.S. Hispanics: Spatial Mismatch, Discrimination, or Immigrant Networks?
January 2009
Working Paper Number:
CES-09-03
Employment rates of Hispanic males in the United States are considerably lower than employment rates of whites. In the data used in this paper, the Hispanic male employment rate is 61 percent, compared with 83 percent for white men.1 The question of the employment disadvantage of Hispanic men likely has many parallels to the question of the employment disadvantage of black men, where factors including spatial mismatch, discrimination, and labor market networks have all received attention as contributing factors. However, the Hispanic disadvantage has been much less studied, and the goal of this paper is to bridge that gap. To that end, we present evidence that tries to assess which of the three factors listed above appears to contribute to the lower employment rate of Hispanic males. We focus in particular on immigrant Hispanics and Hispanics who do not speak English well.
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Do Labor Market Networks Have An Important Spatial Dimension?
September 2012
Working Paper Number:
CES-12-30
We test for evidence of spatial, residence-based labor market networks. Turnover is lower for workers more connected to their neighbors generally and more connected to neighbors of the same race or ethnic group. Both results are consistent with networks producing better job matches, while the latter could also reflect preferences for working with neighbors of the same race or ethnicity. For earnings, we find a robust positive effect of the overall residence-based network measure, whereas we usually find a negative effect of the same-group measure, suggesting that the overall network measure reflects productivity enhancing positive network effects, while the same-group measure captures a non-wage amenity.
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A COMPARISON OF PERSON-REPORTED INDUSTRY TO EMPLOYER-REPORTED INDUSTRY
IN SURVEY AND ADMINISTRATIVE DATA
September 2013
Working Paper Number:
CES-13-47
The Census Bureau collects industry information through surveys and administrative data and creates associated public-use statistics. In this paper, we compare person-reported industry in the American Community Survey (ACS) to employer-reported industry from the Quarterly Census of Employment and Wages (QCEW) that is part of the Census Bureau's Longitudinal Employer-Household Dynamics (LEHD) program. This research provides necessary information on the use of administrative data as a supplement to survey data industry information, and the findings will be useful for anyone using industry information from either source. Our project is part of a larger effort to compare information on jobs from household survey data to employer-reported information. This research is the first to compare ACS job data to firm-based administrative data. We find an overall industry sector match rate of 75 percent, and a 61 percent match rate at the 4-digit Census Industry Code (CIC) level. Industry match rates vary by sector and by whether industry sector is classified using ACS or LEHD industry information. The educational services and health care and social assistance sectors have among the highest match rates. The management of companies and enterprises sector has the lowest match rate, using either ACS-reported or LEHD-reported sector. For individuals with imputed industry data, the industry sector match rate is only 14 percent. Our findings suggest that the industry distribution and the sample in a particular industry sector will differ depending on whether ACS or LEHD data are used.
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Fathers, Children, and the Intergenerational
Transmission of Employers
March 2018
Working Paper Number:
CES-18-12
We document the tendency of fathers in the U.S. to share employers with their sons and daughters. We show that the rate of job sharing is much higher than can be explained by the fact that fathers and sons tend to live near each other. Younger children are much more likely to share their father's employer, as are children of high-earning fathers. We find that sons' earnings at shared jobs tend to be higher than at unshared jobs but see no statistically signi?cant di'erence for daughters. Much of the earnings differential is associated with jobs at shared employers being in higher-paying industries. When we control for employer characteristics, we see a much smaller son earnings premium for working together with his father. We also investigate the impact of sharing an employer on intergenerational mobility and demonstrate that for sons, sharing an employer at some point before age 30 is associated with a higher rank in the earnings distribution as an adult but that this association is independent of the father's rank in the earnings distribution.
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Comparing Measures of Earnings Instability Based on Survey and Adminstrative Reports
August 2010
Working Paper Number:
CES-10-15
In Celik, Juhn, McCue, and Thompson (2009), we found that estimated levels of earnings instability based on data from the Current Population Survey (CPS) and the Survey of Income and Program Participation (SIPP) were reasonably close to each other and to others' estimates from the Panel Study of Income Dynamics (PSID), but estimates from unemployment insurance (UI) earnings were much larger. Given that the UI data are from administrative records which are often posited to be more accurate than survey reports, this raises concerns that measures based on survey data understate true earnings instability. To address this, we use links between survey samples from the SIPP and UI earnings records in the LEHD database to identify sources of differences in work history and earnings information. Substantial work has been done comparing earnings levels from administrative records to those collected in the SIPP and CPS, but our understanding of earnings instability would benefit from further examination of differences across sources in the properties of changes in earnings. We first compare characteristics of the overall and matched samples to address issues of selection in the matching process. We then compare earnings levels and jobs in the SIPP and LEHD data to identify differences between them. Finally we begin to examine how such differences affect estimates of earnings instability. Our preliminary findings suggest that differences in earnings changes for those in the lower tail of the earnings distribution account for much of the difference in instability estimates.
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U.S. Worker Mobility Across Establishments within Firms: Scope, Prevalence, and Effects on Worker Earnings
May 2024
Working Paper Number:
CES-24-24
Multi-establishment firms account for around 60% of U.S. workers' primary employers, providing ample opportunity for workers to change their work location without changing their employer. Using U.S. matched employer-employee data, this paper analyzes workers' access to and use of such between-establishment job transitions, and estimates the effect on workers' earnings growth of greater access, as measured by proximity of employment at other within-firm establishments. While establishment transitions are not perfectly observed, we estimate that within-firm establishment transitions account for 7.8% percent of all job transitions and 18.2% of transitions originating from the largest firms. Using variation in worker's establishment locations within their firms' establishment network, we show that having a greater share of the firm's jobs in nearby establishments generates meaningful increases in workers' earnings: a worker at the 90th percentile of earnings gains from more proximate within-firm job opportunities can expect to enjoy 2% higher average earnings over the following five years than a worker at the 10th percentile with the same baseline earnings.
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Business Owners and the Self-Employed: 33 Million (and Counting!)
September 2025
Working Paper Number:
CES-25-60
Entrepreneurs are known to be key drivers of economic growth, and the rise of online platforms and the broader 'gig economy' has led self-employment to surge in recent decades. Yet the young and small businesses associated with this activity are often absent from economic data. In this paper, we explore a novel longitudinal dataset that covers the owners of tens of millions of the smallest businesses: those without employees. We produce three new sets of statistics on the rapidly growing set of nonemployer businesses. First, we measure transitions between self-employment and wage and salary jobs. Second, we describe nonemployer business entry and exit, as well as transitions between legal form (e.g., sole proprietorship to S corporation). Finally, we link owners to their nonemployer businesses and examine the dynamics of business ownership.
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