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Demography
Published in: Demography 3/2013

01-06-2013

How Do Tougher Immigration Measures Affect Unauthorized Immigrants?

Authors: Catalina Amuedo-Dorantes, Thitima Puttitanun, Ana P. Martinez-Donate

Published in: Demography | Issue 3/2013

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Abstract

The recent impetus of tougher immigration-related measures passed at the state level raises concerns about the impact of such measures on the migration experience, trajectory, and future plans of unauthorized immigrants. In a recent and unique survey of Mexican unauthorized immigrants interviewed upon their voluntary return or deportation to Mexico, almost a third reported experiencing difficulties in obtaining social or government services, finding legal assistance, or obtaining health care services. Additionally, half of these unauthorized immigrants reported fearing deportation. When we assess how the enactment of punitive measures against unauthorized immigrants, such as E-Verify mandates, has affected their migration experience, we find no evidence of a statistically significant association between these measures and the difficulties reported by unauthorized immigrants in accessing a variety of services. However, the enactment of these mandates infuses deportation fear, reduces interstate mobility among voluntary returnees during their last migration spell, and helps curb deportees’ intent to return to the United States in the near future.
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Appendix
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Footnotes
1
The E-Verify system was originally established by the Illegal Immigration Reform and Immigrant Responsibility Act of 1996 as a voluntary pilot program. Logistically, E-Verify is an internet-based, free program run by the United States government that compares information from an employee's employment eligibility verify form (I-9) to data from U.S. government records. If the information matches, that employee is considered eligible to work in the United States. If there is a mismatch, E-Verify alerts the employer, and the employee is allowed to work while the problem is resolved.
 
2
Georgia, Alabama, and Utah are some of the states that have followed Arizona, passing laws that expand the power of local police to check the immigration status of residents. Like bills have been passed by at least one chamber of state legislatures in Indiana, Oklahoma, and South Carolina. In total, up to 30 states are contemplating similar measures.
 
3
See Menjivar and Abrego (2012) for more information on the dramatic increase in deportations taking place nationally.
 
4
For instance, Donato et al. (1992) and Orrenius (2001) relied on data from the Mexican Migration Project (MMP) to examine changes in the likelihood of a variety of events—such as taking a first illegal trip, repeat migration, being apprehended, using a border smuggler or coyote, and changes in smuggling costs or border-crossing sites—before and after the 1986 Immigration Reform and Control Act (IRCA). Angelucci (2005) also relied on MMP data to assess the impact of border enforcement on net flows (i.e., coming into and exiting the United States) of illegal Mexican immigrants. Ritcher et al. (2007), however, used data from the Encuesta Nacional a Hogares Rurales de Mexico (ENHRUM) to examine the impact of three policies: IRCA, NAFTA, and increased border enforcement expenditures on migration. And Amuedo-Dorantes and Bansak (2011) relied on data from the Encuesta sobre Migración en la Frontera Norte de México (EMIF) to explore how changes in border enforcement helped deter undocumented migrants from repetitively attempting to cross the Mexico-U.S. border.
 
5
In 2002, more than 40 % of immigrants are without health insurance (Bell 2004). Kaiser Commission on Medicaid and the Uninsured (2003) found that low-income immigrants are more than twice as likely to be uninsured as low-income citizens. Moreover, immigrants’ health coverage varies by state. Uninsured immigrants ranged from 46 % in California and New York to 56 % in Texas during a 2001–2002 population survey by this agency.
 
6
A comprehensive overview of state and local immigration policy–making in the United States can be found in Varsanyi (2010).
 
7
Rosenblum (2011) discussed the strengths and weaknesses of the E-Verify system and how E-Verify is highly vulnerable to identity fraud and employer noncompliance, as documented by Westat Corporation (2009) and numerous audits by the Social Security Administration Office of the Inspector General.
 
8
See the Appendix for more detailed information on the survey methodology.
 
9
See Secretaría de Gobernación, Consejo Nacional de Población, Instituto Nacional de Migración, Secretaría de Relaciones Exteriores, Secretaría del Trabajo y Previsión Social, El Colegio de la Frontera Norte (2007).
 
10
Unlike migrants in groups (1) and (4), who are return migrants, or migrants in group (3), who have resided in the border region and have often crossed to the United States before, the vast majority of individuals in group (2) did not have previous U.S. migratory experience and, as such, they were not questioned about their experiences in obtaining needed services while in the United States.
 
11
This hypothesis is supported by the fact that other surveys—such as the Mexican Migration Project (MMP; www.​pop.​upenn.​edu/​mexmig/​databases/​databases.​htm)—in their attempt to obtain a representative sample of Mexican migrants, interviewed a relatively small number of Mexican migrant households residing in the United States, while the vast majority of households with U.S. migration experience were interviewed in Mexico.
 
12
Indeed, even surveys that interview migrants both in Mexico and in the United States, as is the case with the Mexican Migration Project (MMP), lack data on the questions’ object of study, including those regarding encountered difficulties, deportation fears, interstate mobility, or the intent to go back to the United States in the foreseeable future.
 
13
Because of the small number of women in our sample, we also conducted the analysis using only men. Results, available from the authors upon request, were robust to the use of that alternative sample.
 
14
The low unemployment rate follows from the fact that the samples used in this article are undocumented returnees, many of them deported while crossing or voluntarily returning home after not finding work.
 
15
”Poor housing” includes a mobile home, homeless shelter, halfway house or boarding home, car or truck, and on the streets.
 
16
These refer to difficulties in finding legal assistance when encountering difficulties in renting, when experiencing discrimination, or when being abused, for example.
 
17
The various categories of encountered difficulties originate from different scales of acculturative stress used in the literature (e.g., Finch et al. 2001, 2003; Finch and Vega 2003).
 
18
We do not have information on all moves across state lines. We know, however, the migrant’s destination state when he or she last entered the United States, as well as the state in which he or she spent most of the migration spell. We use that information to identify mobility across state lines during the last migration spell.
 
19
E-Verify was mandated in Arizona in July 2007 (see http://​www.​ncsl.​org/​issues-research/​immig/​2011-state-laws-addressing-e-verify.​aspx). We use the enactment dates of E-Verify mandates, regardless of their scope.
 
20
The vast majority of our sample, modeled after the EMIF, was headed to California (75.26 %) and Arizona (6.81 %) during their last visit.
 
21
Examples of the latter include any ICE agreements with state law enforcement agencies under Section 287(g) of the Immigration and Nationality Act (INA).
 
22
We also estimate Eq. (2) separately for voluntary returnees and deportees. Our main finding regarding the impact of E-Verify mandates on the intent to return to the United States proves robust. However, the model fails to document the very important role that deportation during the last migration spell plays in explaining the intention to cross again in the near future or the extent to which the enactment of an E-Verify mandate offsets such an impact.
 
23
The F statistics from the Chow tests determining whether deportees and voluntary returnees differ in their experienced difficulties in receiving government assistance or finding legal services, or in their fear of deportation are 3.23, 4.33, and 4.96, respectively. These differences are statistically significant at 10 %, 5 %, and 5 % levels, respectively.
 
24
The F statistics from the Chow tests determining whether the impact of E-Verify on the experienced difficulties in receiving government assistance, finding legal services, and finding health care services differs between deportees and voluntary returnees are 1.39, 0.64, and 0.46, respectively. None of these differences are statistically significant at standard significance levels. The F statistic from the Chow test determining whether the impact of E-Verify mandates on the experienced fear of deportation differs for these two groups of immigrants is 26.68, which is significant at the 1 % level.
 
25
The F statistic from the Chow test determining whether deportees and voluntary returnees differ in their decision to move across states is 8.06, which is significant at the 1 % level.
 
26
The F statistic from the Chow test determining whether deportees and voluntary returnees differ with respect to the effect of E-Verify on the decision to move across states is 10.73, which is significant at the 1 % level.
 
27
The coefficient estimates for Deported and E-Verify State × Deported are jointly significant at the 1 % level.
 
28
Deportations may not increase the desire to return to the United States in the near future if, as noted by Hagan et al. (2008), they disrupt the stream of remittances and separate families.
 
29
Our results are similar to Parrado (2012), who studied the effect of the 287(g) program on the geographic dispersion of Mexican immigrants. Parrado (2012) found no direct impact of the program on the number of undocumented Mexican migrants in the locality.
 
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Metadata
Title
How Do Tougher Immigration Measures Affect Unauthorized Immigrants?
Authors
Catalina Amuedo-Dorantes
Thitima Puttitanun
Ana P. Martinez-Donate
Publication date
01-06-2013
Publisher
Springer US
Published in
Demography / Issue 3/2013
Print ISSN: 0070-3370
Electronic ISSN: 1533-7790
DOI
https://doi.org/10.1007/s13524-013-0200-x

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