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U.S. Border Enforcement and Mexican Immigrant Location Choice

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Demography

An Erratum to this article was published on 25 September 2015

Abstract

We provide the first evidence on the causal effect of border enforcement on the full spatial distribution of Mexican immigrants to the United States. We address the endogeneity of border enforcement with an instrumental variables strategy based on administrative delays in budgetary allocations for border security. We find that 1,000 additional Border Patrol officers assigned to prevent unauthorized migrants from entering a U.S. state decreases that state’s share of Mexican immigrants by 21.9 %. Our estimates imply that if border enforcement had not changed from 1994 to 2011, the shares of Mexican immigrants locating in California and Texas would each be 8 percentage points greater, with all other states’ shares lower or unchanged.

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Notes

  1. These patterns have been amply documented in other work (Card and Lewis 2007; Hall 2013; Hall and Stringfield 2014; Singer 2004, 2009; Zuniga and Hernandez-Leon 2005).

  2. We are grateful to the anonymous referees for helping to clarify our thinking about these issues.

  3. The model includes the choice to remain in the source country as the outside option. However, this choice will be unobserved when using U.S. data, so we focus attention on the case where a migrant is choosing among locations in the destination country.

  4. The leading panel data sets with crossing locations of Mexican migrants—the Mexican Migration Project (MMP) and Survey on Migration at the Northern Border (EMIF-N)—do not meet these criteria. The MMP is not nationally representative, and the EMIF-N surveys migrants on the Mexican side of the border, making it difficult to connect crossing locations to the current spatial distribution of migrants. We use the EMIF-N for data on historical crossing locations, however.

  5. Consequently, summing the index by sector across all destinations (i.e., \( {\displaystyle \sum_k{\upomega}_{ks}{e}_{st}} \)) equals total enforcement in that sector.

  6. Our results are robust to using weights based on time-varying crossing location, where this time variation remains predetermined with respect to enforcement. Results are available in Online Resource 1.

  7. We base this section on discussions with former U.S. Department of Homeland Security officials.

  8. We prefer state to other levels of geographic aggregation, such as the metropolitan statistical area (MSA), because state-years will contain fewer cells with zero immigrants than will alternative geographic units. Passel and Cohn (2010) cautioned against using the CPS and ACS for MSA-level analysis when focusing on unauthorized immigrants. States also leave more scope to control for changing economic conditions because of greater data availability. A few states nonetheless have zero immigrants in a few years of the CPS. We drop these observations and check for robustness to this choice.

  9. See Online Resource 1 for additional details on the consistency and comparability of these data sources.

  10. Given the availability of data on an immigrant’s crossing location and U.S. destination in the EMIF-N, one might reasonably ask why we do not use the EMIF-N to construct our outcome measures in addition to the enforcement weights. We prefer using the CPS (and Census/ACS) for the outcome data because the much larger sample sizes (more than 1.5 million annually in the CPS compared with approximately 15,000 in the EMIF-N) will lead to more accurate measures of population shares. A similar argument applies to the Mexican Migration Project (MMP), which covers only selected Mexican communities, in addition to its relatively smaller sample. See also footnote 4.

  11. National Conference of State Legislatures state laws on immigration are available online (http://www.ncsl.org/research/immigration/state-laws-related-to-immigration-and-immigrants.aspx). Also see Online Resource 1, Section B.

  12. Arizona is chosen as an illustrative example, rather than a representative one. Interior states will not show as strong a correlation between their enforcement index and that of a particular border sector.

  13. For ease of exposition, the enforcement index based on Border Patrol agents is specified in thousands.

  14. First-stage F statistics reported in Table 3 do not correspond exactly to those in column 1 of Table 2 because estimation samples vary as a result of state-years with a zero population share, for which the log population share is undefined. Cells with a zero share also explain the uneven sample sizes across columns. We check the sensitivity of results to exclusion of these observations in Table S4 in Online Resource 1.

  15. To give a better sense of the magnitudes of our estimates, the average change in the enforcement index is 0.017, representing an annual increase of 17 Border Patrol agents assigned to a state. Multiplying this figure by our IV estimate of –0.219 results in a predicted annual decline of 0.37 % in an average state’s Mexican immigrant share. In the average state with a 2 % Mexican immigrant share, this will result in a decline to 1.99 % in one year, or a decline to 1.88 % when compounded over the 17 years of our sample. Our IV estimate implies an elasticity of –0.04 (standard error 0.016) when evaluated at the mean level of enforcement (−0.219 × 0.21 = −0.04); standard error found by the delta method.

  16. In Online Resource 1, we investigate the response of unauthorized immigrants. U.S. government surveys do not ask about immigrants’ legal status. Instead, we use state-level estimates of unauthorized immigrants from Warren and Warren (2013), multiplied by the proportion of immigrants who are Mexican (according to the state-year cell of the CPS panel) to obtain an estimate of a state’s share of unauthorized Mexican immigrants. Our estimates imply that 34 % of Mexican immigrants are unauthorized, which is low compared with Hanson’s (2006:870) estimate of 56 %. Given this discrepancy, the results of this supplemental analysis should be taken with a grain of salt. Nonetheless, we find that the response of unauthorized Mexican immigrants to border enforcement is greater in magnitude than for all Mexican immigrants, as expected.

  17. Another possibility, suggested by an anonymous referee, is that border enforcement induces Mexican immigrants to self-identify as natives in surveys, leading to a spurious increase in the native share. Using native white non-Hispanic share as the dependent variable, we obtain an IV coefficient of –0.06 (with standard error of 0.19), consistent with this explanation. Other explanations are also plausible. For instance, native Hispanics may relocate as a result of inflows of immigrants because employers may see the newly arrived Mexican immigrants as close substitutes.

  18. Online Resource 1 presents results using aggregated data from U.S. Census Department divisions, plus a Mexican border division. Point estimates are substantially smaller in magnitude than their state-level counterparts, suggesting that substitution of migrant destinations within regions in response to enforcement is important. However, 95 % confidence intervals from the state- and division-level analyses generally overlap.

  19. Online Resource 1 presents additional counterfactual results using a range of enforcement coefficient estimates, including using the apprehensions instrument (Table 5, column 3) and halving the preferred point estimate from Table 3, column 1. Although the magnitudes of counterfactual immigrant shares change, the main results remain: California and Texas would have gained migrant share, with all other states losing or experiencing no change.

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Authors and Affiliations

  1. Public Policy Institute of California, 500 Washington Street, San Francisco, CA, 94111, USA

    Sarah Bohn

  2. Oregon State University and IZA, Ballard Ext Hall 311, Corvallis, OR, 97331, USA

    Todd Pugatch

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  1. Sarah Bohn
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Correspondence to Sarah Bohn.

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Bohn, S., Pugatch, T. U.S. Border Enforcement and Mexican Immigrant Location Choice. Demography 52, 1543–1570 (2015). https://doi.org/10.1007/s13524-015-0416-z

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