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Do as the Neighbors Do: Examining the Effect of Residential Neighborhoods on Labor Market Outcomes

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Abstract

This paper examines the effect of where immigrants live on their labor market outcomes. We provide robust evidence that both the number and the labor market activity of immigrants’ neighbors affect their employment. In particular, we demonstrate that immigrants are much more likely to be employed in the same firm as their geographic neighbors than are other immigrants.

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Notes

  1. The statistics are based on authors’ own calculations based on data from the 2,000 Decennial Census; there are several recent studies that also document the residential segregation of immigrants (Cutler et al. 2008; Iceland and Scopilliti 2008).

  2. For instance, the 2,500 most immigrant-dense block groups account for almost half of the foreign-born population and only some 13 % of the native-born.

  3. Papers have estimated neighborhood effects for a variety of socioeconomic variables, including crime, drug use, sexual behavior and educational attainment. Most papers tend to find a strong correlation between individual and mean neighborhood outcomes (Jencks and Mayer 1990).

  4. Data are typically not available at a high enough level of geographic precision to permit more granular analysis.

  5. The probabilistic links are derived from a statistical model that conditions on distance between candidate units and place of residence as well as longitudinal restrictions based on the demographics of the firm (Abowd et al. 2009; Freedman et al. 2008).

  6. While an illegal immigrant with a TIN will generally be included in our data we are not able to provide estimates of what fraction of illegal immigrants are included in our sample, because we have no independent information available on legal status nor do we have available reliable estimates of the number of immigrant workers who are illegal that are comparable to the estimates of immigrant workers in the LEHD database.

  7. The MSAs included in the sample are Austin, Chicago, Dallas, Daytona Beach, Houston, Los Angeles, Miami, Orange County, Philadelphia, Pittsburg, Riverside, and Ventura.

  8. A comparison of our sample to the broader population is provided in the following section.

  9. The expected match rate to the Decennial is about 1 in 6. However, the match rate for certain subpopulations, including recent immigrants, are known to be lower, as a result of higher rates of mobility and lower participation rates (Mulrow et al. 2011).

  10. The definition of recent immigrant in the Decennial Census is that the respondent arrived in the United States in the previous five years

  11. Our approach is very different from the block by block specification employed by Bayer et al., which is based on the assumption that interactions with neighbors are very local in nature. This is unlikely to be the case for immigrant clusters, which are bound by language, religion and shared interest.

  12. Measuring the size of the neighborhood in logs, rather than levels, is consistent with the notion that the returns to the number of contacts are diminishing. However, qualitatively the results are similar if we instead specify measure the size of the neighborhood in levels.

  13. A fourth issue, which we do not pursue further here but deserves to be noted when interpreting results, is that the expected earnings are likely correlated with the labor supply decision. Thus, the estimates from the earnings equation need to be interpreted as conditional rather than unconditional earnings effects.

  14. Our comparison with IPUMS data suggests that the LEHD data capture many more young workers and workers with less than a high school education: this is consistent with the different coverage of the two data sources.

  15. It is worth noting that these estimates are likely to be quite conservative and result in an understatement of neighborhood effects, because of the many controls included correcting for potential sources of omitted variable biases that may serve as proxy for neighborhood effects in their own right. For instance, the area and the country-of-birth specific fixed effects are likely to pick up some of the true neighborhood effects if the reach of neighborhoods goes beyond country of birth or neighborhoods defined by Census tracts.

  16. Again, we compute the expected increase in the employment rate and earnings resulting from a change in living in an immigrant neighborhood: for regions with employment rates in the 90th percentile, living in an immigrant neighborhood is associated with a 4.79 % increase in the employment rate and increases in earnings, conditional on employment, of 0.73 %. The detrimental effects of living in an immigrant neighborhood for regions with employment rates in the 10th percentile are of the same order of magnitude.

  17. Coworkers include everyone in the same firm and the sample is as before, recent immigrants with a minimum sample size of 1,000.

  18. We define status as 1 if the actual exposure to individuals of the same country of birth in the tract exceeds the expected exposure (based on MSA composition) by 200 percent.

  19. It is worth noting that our results are relatively short term in nature; more research is necessary to determine longer term outcomes.

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Authors and Affiliations

  1. Office of the Comptroller of the Currency, Washington, DC, USA

    Fredrik Andersson

  2. CMPO, University of Bristol, Bristol, UK

    Simon Burgess

  3. American Institutes for Research, Washington, DC, USA

    Julia Lane

Authors
  1. Fredrik Andersson
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  2. Simon Burgess
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  3. Julia Lane
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Corresponding author

Correspondence to Fredrik Andersson.

Additional information

We greatly appreciate thoughtful comments from Iwan Barankay, Helen Simpson, seminar participants at the University of Bristol and the Society of Labor Economists. This work was partially supported by the National Science Foundation Grant SES-9978093 and SES-0427889, the National Institute on Aging Grant R01-AG18854, and the Alfred P. Sloan Foundation. All data used in this paper are confidential. The U.S. Census Bureau supports external researchers’ use of some of these data through the Research Data Center network (www.census.gov/ces).

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Andersson, F., Burgess, S. & Lane, J. Do as the Neighbors Do: Examining the Effect of Residential Neighborhoods on Labor Market Outcomes. J Labor Res 35, 373–392 (2014). https://doi.org/10.1007/s12122-014-9188-2

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  • DOI: https://doi.org/10.1007/s12122-014-9188-2

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