To what extent do immigrants and the native-born work in separate workplaces? Do worker and employer characteristics explain the degree of workplace concentration? We explore these questions using a matched employer-employee database that extensively covers employers in selected MSAs. We find that immigrants are much more likely to have immigrant coworkers than are natives, and are particularly likely to work with their compatriots. We find much higher levels of concentration for small businesses than for large ones, that concentration varies substantially across industries, and that concentration is particularly high among immigrants with limited English skills. We also find evidence that neighborhood job networks are strongly positively associated with concentration. The effects of networks and language remain strong when type is defined by country of origin rather than simply immigrant status. The importance of these factors varies by immigrant country of origin'for example, not speaking English well has a particularly strong association with concentration for immigrants from Asian countries. Controlling for differences across MSAs, we find that observable employer and employee characteristics account for about half of the difference between immigrants and natives in the likelihood of having immigrant coworkers, with differences in industry, residential segregation and English speaking skills being the most important factors.
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Workplace Segregation in the United States: Race, Ethnicity, and Skill
January 2007
Working Paper Number:
CES-07-02
We study workplace segregation in the United States using a unique matched employer employee data set that we have created. We present measures of workplace segregation by education and language, and by race and ethnicity, and . since skill is often correlated with race and ethnicity we assess the role of education- and language-related skill differentials in generating workplace segregation by race and ethnicity. We define segregation based on the extent to which workers are more or less likely to be in workplaces with members of the same group, and we measure segregation as the observed percentage relative to maximum segregation. Our results indicate that there is considerable segregation by education and language in the workplace. Among whites, for example, observed segregation by education is 17% (of the maximum), and for Hispanics, observed segregation by language ability is 29%. Racial (blackwhite) segregation in the workplace is of a similar magnitude to education segregation (14%), and ethnic (Hispanic-white) segregation is somewhat higher (20%). Only a tiny portion (3%) of racial segregation in the workplace is driven by education differences between blacks and whites, but a substantial fraction of ethnic segregation in the workplace (32%) can be attributed to differences in language proficiency. Finally, additional evidence suggests that segregation by language likely reflects complementarity among workers speaking the same language.
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Neighbors and Co-Workers: The Importance of Residential Labor Market Networks
January 2009
Working Paper Number:
CES-09-01
We specify and implement a test for the importance of network effects in determining the establishments at which people work, using recently-constructed matched employer-employee data at the establishment level. We explicitly measure the importance of network effects for groups broken out by race, ethnicity, and various measures of skill, for networks generated by residential proximity. The evidence indicates that labor market networks play an important role in hiring, more so for minorities and the less-skilled, especially among Hispanics, and that labor market networks appear to be race-based.
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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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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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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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HUMAN CAPITAL TRAPS? ENCLAVE EFFECTS USING LINKED EMPLOYER-HOUSEHOLD DATA
June 2013
Working Paper Number:
CES-13-29
This study uses linked employer-household data to measure the impact of immigrant social networks, as identified via neighborhood and workplace affiliation, on immigrant earnings. Though ethnic enclaves can provide economic opportunities through job creation and job matching, they can also stifle the assimilation process by limiting interactions between enclave members and non-members. I find that higher residential and workplace ethnic clustering among immigrants is consistently correlated with lower earnings. For immigrants with a high school education or less, these correlations are primarily due to negative self-selection. On the other hand, self-selection fails to explain the lower earnings associated with higher ethnic clustering for immigrants with post-secondary schooling. The evidence suggests that co-ethnic clustering has no discernible effect on the earnings of immigrants with lower education, but may be leading to human capital traps for immigrants who have more than a high school education.
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Earnings Growth, Job Flows and Churn
April 2020
Working Paper Number:
CES-20-15
How much do workers making job-to-job transitions benefit from moving away from a shrinking and towards a growing firm? We show that earnings growth in the transition increases with net employment growth at the destination firm and, to a lesser extent, decreases if the origin firm is shrinking. So, we sum the effect of leaving a shrinking and entering a growing firm and remove the excess turnover-related hires because gross hiring has a much smaller association with earnings growth than net employment growth. We find that job-to-job transitions with the cross-firm job flow have 23% more earnings growth than average.
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Changes in Workplace Segregation in the United States Between 1990 and 2000: Evidence from Matched Employer-Employee Data
June 2007
Working Paper Number:
CES-07-15
We present evidence on changes in workplace segregation by education, race, ethnicity, and sex, from 1990 to 2000. The evidence indicates that racial and ethnic segregation at the workplace level remained quite pervasive in 2000. At the same time, there was fairly substantial segregation by skill, as measured by education. Putting together the 1990 and 2000 data, we find no evidence of declines in workplace segregation by race and ethnicity; indeed, black-white segregation increased. Over this decade, segregation by education also increased. In contrast, workplace segregation by sex fell over the decade, and would have fallen by more had the services industry - a heavily female industry in which sex segregation is relatively high - not experienced rapid employment growth.
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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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Separate but Not Equal: The Uneven Cost of Residential Segregation for Network-Based Hiring
October 2024
Working Paper Number:
CES-24-56
This paper studies how residential segregation by race and by education affects job search via neighbor networks. Using confidential microdata from the US Census Bureau, I measure segregation for each characteristic at both the individual level and the neighborhood level. My findings are manifold. At the individual level, future coworkership with new neighbors on the same block is less likely among segregated individuals than among integrated workers, irrespective of races and levels of schooling. The impacts are most adverse for the most socioeconomically disadvantaged demographics: Blacks and those without a high school education. At the block level, however, higher segregation along either dimension raises the likelihood of any future coworkership on the block for all racial or educational groups. My identification strategy, capitalizing on data granularity, allows a causal interpretation of these results. Together, they point to the coexistence of homophily and in-group competition for job opportunities in linking residential segregation to neighbor-based informal hiring. My subtle findings have important implications for policy-making.
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