We contrast the spatial mismatch hypothesis with what we term the racial mismatch hypothesis - that the problem is not a lack of jobs, per se, where blacks live, but a lack of jobs into which blacks are hired, whether because of discrimination or labor market networks in which race matters. We first report new evidence on the spatial mismatch hypothesis, using data from Census Long-Form respondents. We construct direct measures of the presence of jobs in detailed geographic areas, and find that these job density measures are related to employment of black male residents in ways that would be predicted by the spatial mismatch hypothesis - in particular that spatial mismatch is primarily an issue for low-skilled black male workers. We then look at racial mismatch, by estimating the effects of job density measures that are disaggregated by race. We find that it is primarily black job density that influences black male employment, whereas white job density has little if any influence on their employment. This evidence implies that space alone plays a relatively minor role in low black male employment rates.
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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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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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Place of Work and Place of Residence: Informal Hiring Networks and Labor Market Outcomes
October 2005
Working Paper Number:
CES-05-23
We use a novel dataset and research design to empirically detect the effect of social interactions among neighbors on labor market outcomes. Specifically, using Census data that characterize residential and employment locations down to the city block, we examine whether individuals residing in the same block are more likely to work together than those in nearby blocks. We find evidence of significant social interactions operating at the block level: residing on the same versus nearby blocks increases the probability of working together by over 33 percent. The results also indicate that this referral effect is stronger when individuals are similar in sociodemographic characteristics (e.g., both have children of similar ages) and when at least one individual is well attached to the labor market. These findings are robust across various specifications intended to address concerns related to sorting and reverse causation. Further, having determined the characteristics of a pair of individuals that lead to an especially strong referral effect, we provide evidence that the increased availability of neighborhood referrals has a significant impact on a wide range of labor market outcomes including employment and wages.
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Re-assessing the Spatial Mismatch Hypothesis
April 2025
Working Paper Number:
CES-25-23
We use detailed location information from the Longitudinal Employer-Household Dynamics (LEHD) database to develop new evidence on the effects of spatial mismatch on the relative earnings of Black workers in large US cities. We classify workplaces by the size of the pay premiums they offer in a two-way fixed effects model, providing a simple metric for defining 'good' jobs. We show that: (a) Black workers earn nearly the same average wage premiums as whites; (b) in most cities Black workers live closer to jobs, and closer to good jobs, than do whites; (c) Black workers typically commute shorter distances than whites; and (d) people who commute further earn higher average pay premiums, but the elasticity with respect to distance traveled is slightly lower for Black workers. We conclude that geographic proximity to good jobs is unlikely to be a major source of the racial earnings gaps in major U.S. cities today.
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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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RESIDENTIAL MOBILITY ACROSS LOCAL AREAS IN THE UNITED STATES AND THE GEOGRAPHIC DISTRIBUTION OF THE HEALTHY POPULATION
February 2014
Working Paper Number:
CES-14-14
Determining whether population dynamics provide competing explanations to place effects for observed geographic patterns of population health is critical for understanding health inequality. We focus on the working-age population where health disparities are greatest and analyze detailed data on residential mobility collected for the first time in the 2000 US census. Residential mobility over a 5-year period is frequent and selective, with some variation by race and gender. Even so, we find little evidence that mobility biases cross-sectional snapshots of local population health. Areas undergoing large or rapid population growth or decline may be exceptions. Overall, place of residence is an important health indicator; yet, the frequency of residential mobility raises questions of interpretation from etiological or policy perspectives, complicating simple understandings that residential exposures alone explain the association between place and health. Psychosocial stressors related to contingencies of social identity associated with being black, urban, or poor in the U.S. may also have adverse health impacts that track with structural location even with movement across residential areas.
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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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Wage Premia in Employment Clusters: Agglomeration or Worker Heterogeneity?
February 2010
Working Paper Number:
CES-10-04
This paper tests whether the correlation between wages and the spatial concentration of employment can be explained by unobserved worker productivity differences. Residential location is used as a proxy for a worker's unobserved productivity, and average workplace commute time is used to test whether location based productivity differences are compensated away by longer commutes. Analyses using confidential data from the 2000 Decennial Census Long Form find that the agglomeration estimates are robust to comparisons within residential location and that the estimates do not persist after controlling for commutes suggesting that the productivity differences across locations are due to agglomeration, rather than productivity differences across individuals.
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The Opportunity Atlas: Mapping the Childhood Roots of Social Mobility
September 2018
Working Paper Number:
CES-18-42R
We construct a publicly available atlas of children's outcomes in adulthood by Census tract using anonymized longitudinal data covering nearly the entire U.S. population. For each tract, we estimate children's earnings distributions, incarceration rates, and other outcomes in adulthood by parental income, race, and gender. These estimates allow us to trace the roots of outcomes such as poverty and incarceration back to the neighborhoods in which children grew up. We find that children's outcomes vary sharply across nearby tracts: for children of parents at the 25th percentile of the income distribution, the standard deviation of mean household income at age 35 is $4,200 across tracts within counties. We illustrate how these tract-level data can provide insight into how neighborhoods shape the development of human capital and support local economic policy using two applications. First, we show that the estimates permit precise targeting of policies to improve economic opportunity by uncovering specific neighborhoods where certain subgroups of children grow up to have poor outcomes. Neighborhoods matter at a very granular level: conditional on characteristics such as poverty rates in a child's own Census tract, characteristics of tracts that are one mile away have little predictive power for a child's outcomes. Our historical estimates are informative predictors of outcomes even for children growing up today because neighborhood conditions are relatively stable over time. Second, we show that the observational estimates are highly predictive of neighborhoods' causal effects, based on a comparison to data from the Moving to Opportunity experiment and a quasi-experimental research design analyzing movers' outcomes. We then identify high-opportunity neighborhoods that are affordable to low-income families, providing an input into the design of affordable housing policies. Our measures of children's long-term outcomes are only weakly correlated with traditional proxies for local economic success such as rates of job growth, showing that the conditions that create greater upward mobility are not necessarily the same as those that lead to productive labor markets.
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