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The Effect of Immigration on Labor Market Transitions of Native-Born Unemployed in the United States

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Abstract

Unemployed workers are the group most likely to be affected by the presence of immigrants in their local labor markets since they are actively competing for job opportunities. Yet, little is known about the effect of immigration on labor market opportunities of the unemployed. Using a sample of unemployed native-born citizens from the monthly Current Population Survey from 2001 to 2015 and state level immigration statistics, we employ a multinomial model in the framework of a discrete hazard model with competing risks to examine the effects of immigration on the transition out of unemployment. The results suggest that immigration does not affect attrition not the probabilities of native-born workers finding a job. Instead, we find that immigration is associated with smaller probabilities of remaining unemployed.

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Notes

  1. Migration may influence unemployment spells since access to unemployment benefits (natives are more likely to have unemployment benefits and therefore, longer unemployment spells. I would expect a more significant effect on low skilled foreign-born non-citizens) or the degree of substitution/complementarity between natives and immigrants.

  2. We assume that if an individual was not followed in the CPS from one month to the next, it was because they have moved to a different location. Thus, while attrition may raise a concern, we run robustness tests that confirm that this is not an issue.

  3. For race, we use the aggregate classification of white, black, hispanic, or other. For country of birth we use a dual classification of U.S. born or born abroad.

  4. Later in the paper we use information for individuals interviewed for three or more consecutive months to assess the robustness of the results to spurious employment status changes, as in Rothstein (2011).

  5. These types of models have been proposed explicitly and implicitly in the literature when analyzing unemployment transitions in work by Farber and Valletta (2015), Allison (2014), and Baussola and Mussida (2014), among others.

  6. Nevertheless, as robustness checks, we also estimate models to test the sensitivity to including attrition as a competing event by excluding observations that fall in this category, adjusting sample weights after observations are excluded, and considering attrition as remaining unemployed.

  7. As argued in Addison and Portugal (2003), decisions over the model specification are often done based on criteria of flexibility and tractability. For the purpose of our research, it is important to maintain a simple framework to address the potential problem of endogeneity on our main variable of interest, for which a model of independent competing risks was chosen. Nevertheless, based on the results from Addison and Portugal (2003), parametric corrections to unobserved heterogeneity does not yield substantial changes to the results that ignores unobserved heterogeneity.

  8. We choose to use regions instead of countries, because even at the national level the identification of immigrants for certain countries is not accurately captured in the data. The broad regions used in the data are: other North American countries, Mexico, other Central American countries, the Caribbean, South America, Europe, East Asia, South Asia, India/Southwest Asia, Middle East/Minor Asia, Africa, and Oceania.

  9. When using the semi-annual pooled data, the change is defined as the difference in the immigration ratio of the current immigration ratio and the immigration ratio two semesters ago.

  10. We use “less than one month” as the base category, identifying unemployment spells of one month, two months, between three to five months, six to eleven months, twelve to twenty-three months, and twenty-four months or more.

  11. Results for the first-stage regression can be found in appendix Table 11.

  12. This estimation is obtained by calculating the change in the average relative risk ratios caused by an increase in the change of immigration-to-population of 1 percentage point. The new relative risk ratios are then used to estimate the new out of unemployment transition probabilities. These estimates of marginal effects are practically identical to the marginal effect obtained from estimating a multinomial probit model. These results are presented in appendix Table 13.

  13. Estimations ignoring the possible endogeneity problem of immigration suggest that native workers living in areas with larger net-flows of immigrants are more likely to transition into employment. This can be explained because immigrants may be more likely to be attracted to areas with higher economic activity, which would also be related to higher transitions towards employment. Appendix Table 13 provides the relative risk ratios for models ignoring the possible endogeneity problems. Also, this, however, does not imply that immigration has no effects on the availability of jobs or job displacement of native-born citizens in the local market who are currently employed or not in the labor force.

  14. This could be explained by the changes in immigration mean education which decreased in the less than high school group but increased slightly in the high school and some college group.

  15. For this specification, the instrumental variables are also constructed using the skill-specific concentration of immigrants across states.

  16. For alternative explanations on the labor market effects of immigration see Chassamboulli and Peri (2015) and Orozco-Aleman and Gonzalez-Lozano (2018)

  17. Additional models were also estimated by restricting the sample to observations that remain in the sample for 3 consecutive periods, with similar results. These models are available upon request.

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Acknowledgments

We would like to thank Catalina Amuedo-Dorantes, Klaus Zimmermann, and the participants at the Bolivian Development Conference and the Latin American Meetings of the Econometric Society in for helpful comments and suggestions.

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Authors and Affiliations

  1. Levy Economics Institute of Bard College, Annandale-on-Hudson, NY, 12504-5000, USA

    Fernando Rios-Avila

  2. Universidad Privada Boliviana, La Paz, Bolivia

    Gustavo Canavire-Bacarreza

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  1. Fernando Rios-Avila
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Both Authors (FRA and GJCB) contributed equally.

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Correspondence to Fernando Rios-Avila or Gustavo Canavire-Bacarreza.

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Appendix

Appendix

Table 10 Transition Rates by Selected Characteristics
Full size table
Table 11 Discrete Duration Model: Coefficient Estimates and First Stage Results
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Table 12 Discrete Duration Model: Marginal Effects Multinomial Probit
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Table 13 Discrete Hazard Model: Heterogeneity by Sex, Age, and Education without instruments for ∆IMM
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Rios-Avila, F., Canavire-Bacarreza, G. The Effect of Immigration on Labor Market Transitions of Native-Born Unemployed in the United States. J Labor Res 41, 295–331 (2020). https://doi.org/10.1007/s12122-020-09304-5

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