The 2008 Legal Arizona Workers Act (LAWA) requires all public and private employers to authenticatethe legal status of their workers using the federal employment verification system known as E-Verify.With LAWA, Arizona became the first state to have a universal mandate for employment verification.While LAWA targets unauthorized workers, most of whom are Latino immigrants, other groups couldexperience LAWA's effects, such as those who share households with undocumented workers. In addi-tion, employers may seek to minimize their risk of LAWA penalties by not hiring those who appear tothem as more likely to be unauthorized, such as naturalized Latino immigrants and US-born Latinos.Existing research has found a reduction in foreign-born Latino employment and population in responseto LAWA. This paper asks a different question: have groups that are most likely to be affected by the lawmigrated to other states? We find a significant and sustained increase in the internal outmigration ratefrom Arizona of foreign-born, noncitizen Latinos e the group most likely to include the unauthorized e
after the passage of LAWA. There was no significant LAWA internal migration response by foreign-bornLatino citizens. US-born Latinos showed some signs of a LAWA-induced internal migration response afterthe law went into effect, but it is not sustained. The results indicate that local and state immigrationpolicy can alter the settlement geography of the foreign born. This leads us to speculate about howimmigrant settlement may adjust in the coming years to the intersecting geographies of post-recessioneconomic opportunity and tiered immigration policies.
Any summary of US immigration trends since 1990 wouldinclude these three observations: the doubling of the foreign-bornpopulation from 19.8 million in 1990 to 40 million in 2010; therapid growth in immigrant settlement in “newdestinations”, whichare places that had previously been relatively untouched by thepost 1960s upturn in immigration (e.g., Singer, 2004; Singer,Hardwick, & Brettell 2008); and the emergence of local and statepolicy responses to both of these developments, particularly inreaction to the increase in unauthorized immigrant populations innew destinations (e.g., Varsanyi, 2010;Walker& Leitner, 2011). Thisarticle studies these new nonfederal immigration statutes, not fromthe perspective of why they emerged in certain places but rathertheir effects: in particular, do they spur the foreign born to moveand thereby alter the geography of immigrant settlement?
Specifically, we investigate if immigrants disproportionatelyexited Arizona during the buildup to and after the implementation
of the 2008 Legal Arizona Workers Act (LAWA). LAWAwas the firstall-employer implementation of E-Verify e the federally hosteddatabase system for checking each worker's legal right to work.Arizona pioneered such a universal verification scheme. A fewother states had limited E-Verify requirements for governmentcontracts or were starting to phase in E-Verify requirements, butnone had Arizona's comprehensive verification mandate in 2008 or2009. Thus LAWAwas singular in the timing of this enlarged scopeof enforcement and, as such, presents a unique opportunity tomeasure if such state-wide exclusionary laws generated an inter-state migration response.
Migration is not the only possible reaction to LAWA or to any ofthe other local and state exclusionary policies targeting unautho-rized immigrants. Such policies further drive undocumented pop-ulations toward the fringes of society in search of unregulated orself-employment, or by limiting or changing their daily travelpatterns to minimize the risk of apprehension (Coleman, 2012a).Exiting the state, however, is the only alternative to becomingadditionally marginalized in situ.
Unauthorized workers may not be the only group to leave Ari-zona because of LAWA. Other immigrants and the US-born who
M. Ellis et al. / Political Geography 42 (2014) 46e56 47
experience or fear the possibility of discrimination based on theirappearance or ethnicity may also opt to migrate because of this lawor because they share their lives in households or as partners withundocumented workers. With these possibilities in mind, weinvestigate the interstate migration response to LAWA's imple-mentation across various US- and foreign-born groups.
The analysis proceeds with a review of the recent rise in localand state immigration policy-making and the effects of these lawson immigrant lives. We set these statutes in historical context,outlining how the scale of their application marks a break from thepast but arguing that their motivation aligns with the forces thatpromoted nativist movements and legislative action in the nine-teenth and twentieth centuries. This frames a discussion of E-Verifyand its adoption by states, the passage and implementation ofLAWA, and the findings of other studies on its effects and those of E-Verify more generally. Arizona's law went far beyond the employ-ment enforcement regimes in other states, which leads us to hy-pothesize a greater migration response by affected groups inArizona compared with other states at the time LAWA came intoeffect. Then we turn to the analytics, reviewing data and mea-surement issues, modeling strategies, and results. Here we speak tothe complications posed by the Great Recession in measuring aLAWAmigration push and our techniques for distilling the effect ofthe latter from the former (cf. Bohn, Lofstrom, & Raphael, 2014;Lofstrom, Bohn, & Raphael, 2011). We end with a discussion of theimplications of our findings, speculating on how exclusionarypolicies, such as universal E-Verify within a state, may combinewith the new geography of employment opportunity post-GreatRecession to change the geographies of immigrant settlement andweaken the pull of new destinations.
Immigrant exclusion policies: spatial scale and historicalcontext
LAWA is by no means the first subnational exclusionary policyaimed at removing unauthorized immigrants from a place. In thedecade or so prior to LAWA, various cities and counties across thecountry devised policies designed to make life difficult for thispopulation and thereby discourage their presence (Leitner &Preston, 2011; Walker & Leitner, 2011). By 2008, most states hadramped up identification requirements for driving licenses, makingit harder, if not impossible, for the unauthorized to obtain a drivingpermit. In addition, a number of local police departments developed287(g) agreements with the federal government, which empoweredlocal police to perform immigration enforcement tasks (Coleman,2009). LAWA, though, represented an expansion in the scope ofthese subnational exclusionary measures by mandating employeeverification statewide. Since its enactment,whichwas bolstered by a2011 US Supreme Court ruling that allowed LAWA and by extensionsimilar E-Verify laws elsewhere to stand, other states have followedsuit by passing LAWA-like all-employer E-Verify requirements.
Arizona itself attempted to expand its enforcement regime byenacting SB1070 in 2010, which criminalized the unauthorized forbeing present in the state. In June 2012, the US Supreme Courtstruck down much of SB1070 on the grounds that some of itsmeasures undermine federal authority to regulate immigration.This ruling, Arizona v. the United States, helped undo similar“attrition through enforcement” legislation that had subsequentlybeen enacted in Alabama, Georgia, Indiana, South Carolina, andUtah. Alabama's SB58, for example, would have required K-12public schools to collect information about the immigration statusof their students and, in addition, criminalized noncitizens whofailed to carry their alien registration documents. SB58 also maderenting housing to an unauthorized immigrant a criminal offense(Chishti & Hipsman, 2013).
This eruption of state-scale legislation is not the first time stateshave tried to influence immigration. Prior to the assertion of federalauthority over immigration in the late nineteenth century, statesregulated and taxed immigration for the purposes of screening outpaupers, convicts, and others deemed undesirable, and to coversocial costs when those procedures failed (Klebaner, 1958; Zolberg,2006). California's Proposition 187, a 1994 referendum designed toexclude undocumented immigrants from a wide variety of publicservices, was, in many respects, the first modern-day variant ofthese nineteenth-century policies. But California's “Save Our State”initiative, which is how Proposition 187 was packaged to the public,emerged during a period of much greater federal authority overimmigration matters than in the earlier era. The law was neverenforced because of an immediate court injunction and was voidedin 1999 after the US District Court had previously ruled most of itunconstitutional on the grounds that it infringed on the authorityof the federal government to regulate immigration. Californiaagreed to mediate rather than appeal this decision.
Immigrant rights groups have also challenged the LAWA. Thislaw, however, was never going to face the same level of legal dif-ficulties as Proposition 187 e or Arizona's SB1070, for that matter ebecause LAWA is an application of an existing federal workplacedetection scheme with added state sanctions for employers whohire unauthorized workers. Sanctions for employing unauthorizedimmigrant workers have been part of US law since the 1986Immigration Reform and Control Act. LAWA expanded the appli-cation of this existing statute rather than proposing qualitativelydifferent enforcement regimes that challenged or exceededfederal law.
While the geography of contemporary immigration policiesmight be new, the underlying forces are the same as those thathave motivated immigration restriction in the past. John Higham's(1955) classic study of US nativism examined the ebb and flow ofanti-immigration sentiment from the mid nineteenth centurythrough to the passage of the restrictive quota acts of the 1920s. Inthis period, targeted groups included Catholics, Jews, and othersdeemed unassimilable, as well as suspected radicals. The tides ofnativism, however, waxed during economic downturns. Americannativism in any era is always bound up with racism and xeno-phobia but the receptivity of the larger population to anti-immigration campaigns often hinges on the state of the econ-omy. Immigrants can be more easily scapegoated during economichard times when good jobs, or any jobs, are much harder to comeby for residents.
The mapping of recent economic cycles onto the rise ofcontemporary anti-immigration movements is beyond the scope ofthis paper. While we await a Higham-like dissection of theseevents, the high rate of immigration, both documented and unau-thorized, combined with recession surely amplified the clamor forrestriction in the last decade. The surge in the enactment of stateimmigration legislation coincides with the acceleration of job lossbeginning in 2007, but the timing is not precise. A handful ofcounties and municipalities passed anti-immigrant measuresbefore the crash, and the regime of enforcement at the federal levelthat militarized the border and accelerated deportations has itsroots in events that predate the current crisis (Nevins, 2010).
The five states that followed Arizona's lead and passed LAWA-style universal employment verification laws were new immi-grant destinations; no major immigrant gateway state had such alaw.1 At the county and municipal scales, 88.5% of immigration-oriented policies in southern jurisdictions were exclusionarycompared to 69% nationally (Walker & Leitner, 2011). New desti-nations, or places with rapid growth in immigrant populations,appear more likely to adopt these policies than established immi-grant destinations. These categorizations alone, however, are
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unable to account fully for variations in policy response amongneighboring localities experiencing broadly similar immigrationevents (Walker & Leitner, 2011). The adoption of local anti-immigrant policies appears to also depend on whether the areahas experienced an influx of immigrants at a time in which thenational political climate is particularly hostile to immigration andif it has a Republican majority (Hopkins, 2010; Ramakrishnan &Wong, 2010).
Our focus in this paper is not to investigate further the causes ofthe geography of these local policies but to contribute to thegrowing literature on the implementation and effects of these lawson the lives of immigrant populations (e.g., Coleman, 2007, 2009,2012b; Coleman & Kocher, 2011; Varsanyi, 2008; Varsanyi, Lewis,Provine, & Decker, 2012). Unsurprisingly, these programs serve tocreate insecurity in the daily lives of immigrants. The denial ofdriving licenses to unauthorized immigrants elevates their chancesof contact with local police who work with federal immigrationauthorities through programs such as 287(g) (Coleman, 2012a). Inplaces with such programs, immigrants worry more about detec-tion and deportation than in other, morewelcoming, places (Garcia,Griesbach, Andrade, Gonzalez, & Barbosa, 2011).
If everyday life becomes more difficult amid a general climate offear, some people maymove to places where local and/or state lawsare less hostile. Unauthorized immigrants and thosewho employ orprovide services to them speak of such departures when theselaws or programs come into effect, but these anecdotal accountsdo not match up with survey-based results. Garcia et al. (2011), forexample, report that there were several such accounts of migrantdeparture from Oklahoma after the 2007 passage of a lawthat limited immigrant access to state services and ramped up statelaw enforcement requirements to detect the unauthorized. Surveydata, however, suggest that immigrants in Oklahoma did notchange location or make migration decisions because of the law,despite their clearly articulated fear of the law's effects. Otherresearch aligns with this result, finding that anti-immigrant laws atcounty or state level do not spur the spatial redistribution of un-authorized populations away from these areas (Amuedo-Dorrantes,Puttitanum, & Martinez-Donate, 2013; García, 2013; Leerkes,Bachmeier, & Leach, 2013; Parrado, 2012).
The absence of any migration or population redistributionresponse, at least at the scales and locations analyzed in thesestudies, is hard to square with the punitive and climate-of-feargenerating effects of these laws, as Menjívar (2013) and Orrenius(2013) state in their responses to Amuedo-Dorrantes, Puttitanum,and Martinez-Donate (2013). We hypothesize these laws generatean outmigration response in tandem with unauthorized workerspreserving in place. Hunkering down may be manageable if onecan still obtain or hold a job, even if that work is increasinglymarginalized. Previous research finds that anti-immigrant hostileenvironments drive unauthorized workers further underground insitu, such as shifting from formal wage employment to self-employment to avoid detection at the workplace (Lofstrom et al.,2011).
At the national scale, unauthorized immigrants continued tocome to the US, or stayed in the country, after enforcementexpanded in the late 1990s and before the Great Recession started.They did this even though enhanced enforcement furthermarginalized their position in the US labor market by underminingtheir rights as workers and making them avoid some types of workto minimize detection (Gentsch & Massey, 2011; Orrenius &Zavodny 2009). Despite these accruing labor market disadvan-tages, many local labor markets absorbed unskilled immigrantworkers in most years during this period. The allure of employmentremained sufficient to overcome any reluctance to move to the USdespite new and tougher immigration enforcement regimes. So
perhaps it is no surprise there is scant evidence for an effect of thesepolicies at state and local levels on immigrant redistributionwithinthe country. LAWA, however, took the policing of labor markets inArizona for unauthorized workers to another level compared to anyother state at the time. We want to know if LAWA and its universalemployment verification requirements generated immigrantredistribution via outmigration from Arizona. Beforewe discuss theanalytical strategies for answering this question we briefly reviewE-Verify, LAWA, and what is known about their impacts.
E-Verify and the Legal Arizona Workers Act
The 1986 Immigration Reform and Control Act (IRCA) marks thebeginning of the current phase of immigration enforcementthrough the workplace.2 The employment authorization section ofthis law required employers to check the documents of employeesto determine their eligibility to work. It was part of a larger deal togrant amnesty to a significant fraction of the unauthorized popu-lation as well as to penalize employers who hired unauthorizedworkers. Verification of these documents against centralized da-tabases was not part of the original scheme but pressure to tightenworkplace enforcement led Congress in 1996, as part of the pro-visions of the Illegal Immigration Reform and Immigrant Re-sponsibility Act (IIRIRA), to instruct the then Immigration andNaturalization Service (INS) to pilot an electronic record-checkingprogram, which became “E-Verify” in 2007. E-Verify is now apartnership between the INS's successor in the Department ofHomeland Security and the Social Security Administration. Em-ployers are invited to enroll in the system and then submit, via theinternet, employee information for checking against agency data-bases. The program has grown from its initial pilot years. Employerenrollment in the electronic scheme expanded from 24,463 in 2007to 353,822 in March 2012, but participation is not mandatory (USCitizen and Immigration Services, 2013). If they prefer, most em-ployers, with some notable exceptions such as companies and or-ganizations that contract with the federal government, can opt touse paper document checking as allowed by IRCA.
The Legal Arizona Workers Act, passed in March 2007 andimplemented at the beginning of 2008, made E-Verify mandatoryfor all employers in Arizona. Business license suspension is thepenalty for non-compliance. At that time, a small number of stateshad limited E-Verify requirements in place for public employersand contractors but no other state had a mandatory enrollmentrequirement for all employers. Mississippi passed a LAWA-like lawin July 2008 but it had the mandatory requirement phase in overthree years instead of becoming fully active immediately. As of2012, five states in addition to Arizona had LAWA-style laws but,unlike LAWA, none of these were operational for all employees in2008 and 2009 (Feere, 2012).3 Soon after passage, business andimmigration rights groups challenged LAWA by claiming it pre-empted federal immigration law. Lower courts affirmed the legalityof LAWA in 2008 and 2009 and the US Supreme Court did the samein the 2011 Whiting decision (Chishti & Bergeron, 2011).
LAWA's impact on E-Verify enrollment in Arizona was dramatic.Only 300 employers in Arizona were enrolled in E-Verify in March,2007, the month the law was passed. By mid-2008, six monthsafter it took effect, that number was 15,000 (38% of all employersenrolled nationwide), growing to 36,000 by January 2011(Rosenblum, 2011; Westat, 2009). In early 2011, 26% of Arizona'semployers were enrolled in E-Verify, almost twice the percentagein the next highest enrollment state, Missouri (Rosenblum &Hoyt, 2011).4
Did this LAWA surge in E-Verify enrollment have any effects onthe employment of immigrants, particularly the unauthorized?LAWA is the product of a broad, hostile cultural and political
M. Ellis et al. / Political Geography 42 (2014) 46e56 49
environment for immigrants in Arizona and so its measurable ef-fects are, in a general theoretical sense, inseparable from the anti-immigrant context in which it emerged. Nevertheless, LAWA verylikely contributed to the reduction of the population of non-citizenLatinos in the state by 92,000 (17% of the pre LAWA population ofthis subgroup) by the end of 2009 (Bohn et al., 2014; Lofstrom et al.,2011). The employment of that same group fell by 56,000 and asubstantial number had shifted into informal self-employment,presumably to avoid E-Verify (see also Bachmeier, Leach, Bean, &Van Hook, 2012). In addition, Leerkes, Leach, and Bachmeier(2012) place Arizona in a league of its own relative to other statesin the severity of its restrictive policies around the time of LAWAspassage. They show a negative association between the severity ofthese restrictions and change in the unauthorized population be-tween 2008 and 2009 at the state scale. Leerkes, Leach, and Bach-meier, however, concede that their analysis is simply bivariate andcannot account for other factors, such as differences in state eco-nomic health.
Critically, all prior research measures the impact of restrictivepolicies on state-level employment or population change amongthe unauthorized; the outmigration response per se has not beenstudied (Leerkes et al., 2013). This is an important distinction. Theidentification of employment declines could reflect reactions in situ(e.g., leaving the workforce, informalization of work). Populationchange among the unauthorized has multiple dimensions,including births and deaths, internal in- and outmigration, newimmigration, voluntary international return migration, anddeportation. The timing of an increase in outmigration begins toisolate the effect of LAWA on voluntary relocation within thecountry.
Accordingly, this analysis develops a strategy that assesses ifLAWA prompted the unauthorized, or the population most likely tobe unauthorized, to leave Arizona for other states in the US. Webuild a multivariate model that accounts for local and nationaleconomic cycles and changes in employment patterns, as well asindividual-level characteristics. We advance the work of Leerkeset al. (2012, 2013) by comparing Arizona, not with clusters ofother states, but directly with California, Nevada, and Florida. Thesefour states had similar employment concentrations in construction,a sector that provides work for many unauthorized immigrants,and were hit hardest by the construction employment declines inthe Great Recession. In doing so, we evaluate whether exclusionarylaws such as LAWA, controlling for other factors, have the potentialto redistribute immigrants within the US.
Data and analytical strategy
The most comprehensive data on migration before, during, andafter the period of LAWA's enactment are the microdata files of theAmerican Community Survey (ACS). They record state of residenceone year prior to the survey, which means we can observe theinterstate flows of migrants by the socio-demographic character-istics of ACS respondents, such as age, nativity, ethnicity, and citi-zenship. As LAWA and other exclusionary policies likely inducedsome unauthorized immigrants to leave the country, we wouldideally also like to use comparable information on emigration fromthe US. Such data, however, do not exist. We do know that a sig-nificant decline in net Mexican immigration occurred between2005 and 10 (Passel, Cohn, & Gonzalez-Barrera 2012). Estimates ofa specific return migration to Mexico, for example, suggest 1.4million moved back in the 2005e10 period, twice that of the1995e2000 period. Perhaps as much as 35 percent of the total re-turn migration in the late 2000s resulted from involuntary depor-tation (Passel et al., 2012). In any event, we should expect to see aninternal migration response to state-scale exclusionary policies,
especially considering that conditions in the home country of themajority of unauthorized migrants e Mexico e are not especiallyfavorable and when the cost of returning to the US across themilitarized border is high. Further, it is vital to know whether suchlocal laws might alter the geography of immigrant settlement forthose who remain in the US.
ACS data do not identify who is in the US without authoriza-tion. They do, however, separate the foreign born into two cate-gories: those who are naturalized citizens and those who are not.The latter includes both authorized and unauthorized immigrants.According to census data, 37% of the foreign born are naturalizedand the Pew Hispanic Center estimates that the unauthorizedcomprise just under half of the non-citizen foreign-born popula-tion (Passel & Cohn, 2011). Mexicans are by far the largest group ofunauthorized immigrants being 56% of the total. Mexicans andCentral Americans together comprise 73% of the unauthorizedimmigrant population but supply only 36.9% of the total foreign-born population (Grieco et al., 2012; Hoefer, Rytner, & Baker,2012; Passel et al., 2012). Thus the non-citizen foreign-bornLatino population has a higher percentage of unauthorized im-migrants than other non-citizen foreign-born subgroups. Hence,we treat non-citizen foreign-born Latinos as the closest approxi-mation to the unauthorized population and expect that membersof this group will be more likely than any other to experienceLAWA's effects and opt to leave the state as a consequence. Thisapproximation means that our estimate of the migration responseis probably on the low side because some members of this grouphave the right to work.
While non-citizen foreign-born Latinos should be the groupmost likely to leave Arizona post-LAWA, naturalized and US-bornLatinos may also migrate if they experience or fear discriminationby employers (and others) because of the law. As unauthorizedimmigrants frequently form households with citizens and docu-mented immigrants, such mixed-status households may choose tomove as a unit for the sake of a family member and to keep thehousehold intact. In either of these circumstances, rates of depar-ture from Arizona for these two groups would increase post LAWA,although we would expect them to be of a smaller magnitude thanthose for non-citizen foreign-born Latinos.
The Great Recession further complicates the identification of aLAWA migration effect. As we argued earlier, there is reason tobelieve that the timing of the implementation of restrictive actionsdepends on the economic cycle. Any analysis of the effect of suchlegislation must therefore distinguish the impact of changing legalregimes from what may be produced by shifts in prevailing eco-nomic conditions. LAWA became law just after the recession offi-cially started in late 2007. Employment losses were concentrated inconstruction e the sector in which unauthorized immigrantworkers frequently find employment. Nationally, 4.9% of the USworkforce was unauthorized in 2005 whereas 14% of all construc-tion workers were so categorized (Passel, 2006). For some con-struction occupations, such as insulators, roofers, drywallers, andgeneral construction laborers, the unauthorized worker share oftotal employment at that timewas 25 percent or greater. Regardlessof an expansion of E-Verify, the rapid loss of these jobs within ahousing-boom state, such as Arizona, is very likely to have spurredsome outmigration of affected workers.
Arizona's housing-market crash was significant but itsemployment losses were not exceptional. For example, Fig. 1 chartsthe annual percentage change in total jobs in Arizona and twocomparison states in the region, California and Nevada. Arizona'spattern resembles its neighbors, rising growth rates through to themid-part of the decade leading to slower growth by 2007 and thena substantial employment decline in 2009 that moderated in 2010.This similarity suggests that any distinctiveness in Arizona's
Fig. 1. Annual percentage change in employment.Source: Bureau of Labor Statistics, Local Area Unemployment Statistics.
M. Ellis et al. / Political Geography 42 (2014) 46e5650
outmigration profile, if it exists, cannot be attributed to a uniquerecessionary effect there.
Trends in construction employment losses reinforce thisconclusion (Table 1). The focal points of the collapse of constructionemployment were in four states: Arizona, California, Nevada, andFlorida. The location quotients in this table, which are the ratio ofannual percentage construction job loss in a state to annual per-centage construction job loss nationally, make it clear that from thepeak of the boom in 2006 through to 2008, the first full year of therecession, construction jobs hemorrhaged from these four states ata much faster rate than in other states with significant Latinopopulations. Florida and Nevada's job losses in construction werealmost five times the national rate of decline; Arizona's loss wascloser to four times. Between 2008-2009, construction job lossdeepened considerably across the country and the geographicalunevenness of this decline, captured by the diminished range of
Table 1Percentage change in construction employment (states >200,000 foreign-bornLatinos in 2008).
New Jersey �5.18% 1.29 Washington �29.06% 1.55North
Carolina�1.07% 0.27 Colorado �26.95% 1.44
Georgia �0.05% 0.01 Illinois �25.42% 1.36Colorado 2.98% �0.74 New Jersey �25.15% 1.35Washington 7.65% �1.90 Virginia �23.66% 1.27New York 9.97% �2.48 Texas �10.42% 0.56Texas 14.30% �3.55 New York �8.34% 0.45
US ¡4.02% US ¡29.06%
a LQ % Change ¼ state % change/US % change; LQ % Change > 1 means state islosing construction jobs at a faster rate than the US as a whole; LQ % Change < 1means state is losing construction jobs at a slower rate than the US average, or isgaining construction jobs.Source: County Business Patterns.
the location quotients on the right side of the table, became lesspronounced. The recession had spread from the four states at itsepicenter in 2008 but they remained the hardest hit states.
This similarity of Arizona to California, Florida, and Nevada inrecessionary job-loss profile is important and makes it possible todifferentiate an enforcement push from a recessionary effect. Anincrease in outmigration by LAWA-targeted populations in Arizonabut not by those same populations in these three related stateswithout a similar law would suggest that LAWA, not the recession,is responsible, at least in part, for this elevated rate of departure toother states.
Descriptive outmigration trends
Using weighted ACS data to approximate population trends,Fig. 2 charts outmigration rates from 2006 to 2009 for four groupse US-born whites, US-born Latinos, foreign-born Latinos withcitizenship, and foreign-born Latinos without citizenship e forArizona and the three comparison states: California, Nevada, andFlorida. We restricted the samples for these rate calculations tothose of workforce age, 18e65, to focus on the migratory responseof people who would most likely be subject to an E-Verify check.Before we focus on the outmigration of the group of intereste non-citizen foreign-born Latinosewe draw attention to patterns sharedby all four states.
US-born whites are the most migratory group and foreign-bornLatino citizens the least migratory. Note also that rates for US-bornwhites decline in each state as the recession deepens, a trend thatmatches the dampening effect of recessions on migration observedin previous economic downturns (e.g., Clark, 1982; Greenwood,Hunt, & McDowell, 1986; Long, 1988). In addition, we observesome differences among states across all groups. California hadrelatively low outmigration rates; Arizona and especially Nevadahad higher outmigration rates. After 2006, Arizona was the onlystate in which foreign-born Latino non-citizen outmigration wasmarkedly higher in every year. The pattern in other states varied. InCalifornia foreign-born Latino non-citizen outmigration declinedpost 2006; In Nevada it fell then spiked in 2009; in Florida it rose in2007 then fell back to 2006 levels by 2009. Nevada's 2009 spikewasthe largest absolute increase in outmigration rate for this group inany of the four states.
Fig. 2. Outmigration rates for Arizona, California, Nevada, and Florida, 2006e9.Source: American Community Survey.
Fig. 3. Annual percentage change in the outmigration rate of non-citizen foreign-bornLatinos in Arizona, California, Nevada, Florida.
M. Ellis et al. / Political Geography 42 (2014) 46e56 51
Arizona's increases in 2007 and 2009 were larger in relativeterms, however, when measured as a percentage change from therate observed in 2006 (see Fig. 3). The 2008 percentage increasewas smaller but exceeded the same percentage increase in theother three states. This relative-change perspective plus theconsistently higher rate of outmigration post 2006 lends credenceto the idea that something happened to outmigration from Arizonawhen LAWA passed that did not happen in the other three states.Note also that the group most affected by the law in Arizona ex-hibits the strongest and most consistent increase in outmigration.The increases in US-born Latino outmigration in 2008 and foreign-born Latino citizen outmigration in 2007 and 2008 in Arizona wererelatively small compared to those of non-citizen foreign-bornLatinos. This contrasts with Nevada where the relative magnitudeof the post 2006 increase in outmigration was greater for foreign-born Latino citizens than for non-citizens e a pattern inconsistentwith the idea that enforcement targeting the unauthorized isdriving foreign-born Latino outmigration from that state.
Difference in differences models of outmigration
The descriptive data suggest a distinctive migration response toLAWA in Arizona by the subgroup most likely to be unauthorized.The increase in outmigration from Arizona by non-citizen foreign-born Latinos after LAWA's passage is not large in absolute terms andthe migratory propensity for this group remained well below that
for US-born whites two years after LAWA came into effect. Inrelative terms, however, this group's migration rate increase post2006 is certainly larger in Arizona than in any of the comparisonstates. To determine if this increase is statistically significant we
M. Ellis et al. / Political Geography 42 (2014) 46e5652
estimated a series of difference in differences models that measuredifferential change in the outmigration rate for the key groups ofinterest. These models test whether the difference between themigration propensity of the key group of interest (non-citizenforeign-born Latinos in Arizona) and a baseline group is constantover time after controlling for other relevant variables that mayaffect migration rates.
Following Lofstrom et al. (2011), we identify if therewas a LAWAoutmigration push in two ways. The first is a within-state com-parison over a pre- and post-LAWA time period of the migrationpropensity of relevant groups. The baseline group in this formula-tion is the population least likely to be affected by LAWA eUS-bornwhites. The estimated coefficients in these models measure dif-ferences in outmigration rates and, crucially, changes in those dif-ferences between them and three other groups e non-citizenforeign-born Latinos, naturalized foreign-born Latinos, and US-born Latinos. The model is restricted to those who live within asingle state producing a situation in which state economic condi-tions are implicitly controlled for. Thus any differential change ingroup outmigration rates must derive from non-economic factorsaffecting specific groups, which in Arizona's case we expect to beLAWA disproportionately increasing the non-citizen foreign-bornLatino outmigration rate relative to US-born whites. The followinggeneral formulation represents this within-state version of ourdifference in differences model:
pikt ¼ f ðbXit þ ggk þ tbt þ dgkbtÞ (1)
This model estimates the probability that person i in group k inyear t (pikt) migrates from a specific state as a function of a vector ofpersonal characteristics (Xit), group-fixed effects (gk), year-fixedeffects (bt), and the interaction of group membership and year(gkbt). The group-fixed effects measure the difference in migrationrates between group k and the baseline group after controlling forindividual characteristics. If migration rates change year-to-yearbut this group difference from the baseline is constant then theyear-fixed effects coefficients, t, will be greater or less than zero,depending on the time trend, and d will be zero. If the differencechanges over time (i.e., there is a difference in differences) thendwill not equal zero.We hypothesize these difference in differencescoefficients will be positive for the group most affected by LAWA,non-citizen foreign-born Latinos (i.e., we expect their outmigrationto increase relative to US-born whites, the baseline group).
This modeling strategy depends on the selection of an appro-priate time-span to capture migration before and after the imple-mentation of LAWA. As in the earlier analysis, we use four years ofannual outmigration data from 2006 to 2009 to estimate thismodel. Our pre-LAWA year is 2006 and the d coefficients measurethe change in group differences in outmigration rates during theyear of LAWA's passage, 2007, and in the first two years of itsimplementation, 2008 and 2009. We estimate the model for Ari-zona and to check the robustness of our results we also estimate itfor the three comparison states e California, Florida, and Nevada.
The second strategy is a within-group analysis of outmigrationacross a set of comparison states. Here the focus is on estimatingthe difference in differences between outmigration rates for aparticular subgroup (such as non-citizen foreign-born Latinos) inthe specific state of interest, Arizona, and a set of other states thatmirror Arizona in key ways. These difference in differences modelstake the following general form:
pijt ¼ f ðbXit þ gAZ þ tbt þ dAZbtÞ (2)
This model estimates the probability (pijt) of individual imigrating from state j in year t as a function of a vector of individualcharacteristics (Xit), an Arizona dummy (AZ), a vector of year fixed
effects (bt), and a vector of interactions between the Arizona statedummy and year dummies tomeasure any difference in differencesbetween outmigration from that state and the comparison statesover the years in which the model is estimated. As before, we useoutmigration in 2006 as our base and compare it to outmigration in2007, 2008, and 2009.
The choice of comparison states is key to this estimation strat-egy. We want to compare the change in outmigration from Arizonato the change in outmigration that occurs from a pooled set ofstates that, like Arizona, have a large foreign-born Latino popula-tion and a similar recessionary profile. As we have alreadydemonstrated, California, Nevada, and Florida resemble Arizona onthese dimensions, most notably in terms of the intensity of theirconstruction employment crash, and so these three states compriseour comparison set. They serve as our counterfactual, if you will, forwhat would have happened in Arizona absent LAWA. Thus thedataset for this model is restricted to these three states plus Ari-zona; the Arizona dummy and its interaction by year measuredifferences pre- and post-LAWA between Arizona and the pooledset of California, Nevada, and Florida. We estimate this across-statemodel for each of the four groups e US-born whites, US-bornLatinos, naturalized foreign-born Latinos, and non-citizen foreign-born Latinos. If there is a LAWA effect we expect to see significantpositive effects of d for the latter group, perhaps some positive ef-fects for the other Latino groups if there is some discriminationspillover, but no effect for US-born whites.
We estimate both types of models using the same age restrictionas the rates charted in Figs. 2 and 3 (i.e., 18e65). The individualcharacteristics in both within and across state models includegender, four categories of age, four categories of education, and fourcategories of family type. Human capital theory predicts that ageand education condition migration (e.g., Schultz, 1961; Sjaastad,1962); family migration studies show that couples with childrenare less likely to move than single-person households (e.g., Mincer,1978). Some migration events are associated with gender so weinclude this variable. Including all these characteristics as re-gressors controls for differences in age, education, gender, andfamily structure across groups or states. These socio-demographiccharacteristics, however, are the basis for weighting in the ACS.Estimating models with independent variables related to theweighting structure of the sample can cause difficulties in inter-pretation of the estimated coefficients (Winship & Radbill, 1994).Accordingly, our estimation uses unweighted data.
We calibrated both types of difference in differences modelsusing ordinary least squares, correcting standard errors for heter-oscedasticity. Linear probability models yield estimates of d directlyinterpretable as the change in the probability of outmigration forthe group in question. In a logit formulation, the estimated d co-efficients measure change in the log-odds of outmigration. Theconversion of an interaction term in the log-odds metric to amarginal effect in the probability metric comparable to the co-efficients in the linear probability model requires a nonlineartransformation. In this transformation, the marginal effect of theinteraction term is dependent on the value of the other regressorsin the model, which is not the case for linear probability modelestimates (Ai & Norton, 2003). Hence, logit estimates are compli-cated to interpret in terms of the marginal probability effects ofrelevance to the primary measurement goals of this paper. An ob-jection to linear probability models is that they run the risk ofpredicting probabilities outside the 0e1 range. This, however, is nota concern for us. Our interest lies in estimates of the marginal effectof d on the probability of migration rather than on the accuracy ofthe predicted probabilities. Besides, our linear probability modelsnever predict outside the 0e1 bound because all of our regressorsare categorical variables.
M. Ellis et al. / Political Geography 42 (2014) 46e56 53
Model results
To recap, we expect the effect of LAWA on the outmigration ofnon-citizen foreign-born Latinos from Arizona to be greatest in2008, when the law went into effect. Their relative propensity toleave the state, however, could have increased in 2007 in antici-pation of its effects, after the law was passed in March of that yearbut before it came into effect. Employers might have begun tochange employment decisions in 2007 in anticipation of the law;workers may have seen the writing on the wall. More likely,perhaps LAWA's effect may have strengthened over time because ofthe limited take-up of E-Verify by Arizona's employees in 2008. Inthis case, we could expect the outmigration push to be greater in2009 than in 2008. Push effects may also have occurred for natu-ralized foreign-born Latinos and US-born Latinos; to be consistentwith the idea of a LAWA push, the model coefficients for thesegroups should be smaller than for non-citizen foreign-born Latinos.If these patterns of effects only exist in Arizona thenwe have strongevidence that LAWA promoted the domestic outmigration andredistribution of unauthorized immigrants.
Table 2 contains the results of the within-state models for Ari-zona and the three comparison states. The coefficients on the socio-demographic variables are in line with expectations in all fourstates. The probability of migration decreasedwith age, was highestfor the college educated, and was lower for those who are part-nered, especially if they had children. Gender had no effect.Consistent with the trends charted in Fig. 1, the coefficients for thethree Latino groups are negative, meaning that their migrationpropensity was lower than for US-born whites, the baseline
Table 2Within state models.
Column1 Arizona California Nevada Florida
Constant 0.0509*** 0.0306*** 0.0561*** 0.0473***Female �0.000798 0.00000810 0.000511 �0.00042630e39 �0.0142*** �0.00612*** �0.0130*** �0.0130***40e49 �0.0310*** �0.0151*** �0.0296*** �0.0248***50e65 �0.0380*** �0.0184*** �0.0377*** �0.0319***High School 0.00267 0.00000390 0.00414 �0.00255**Some College 0.000233 �0.000600 0.00452 �0.00393***College 0.00937*** 0.00363*** 0.0136*** 0.00211*Partnered e with kids �0.0146*** �0.00760*** �0.0168*** �0.0120***Partnered e no kids �0.00738*** �0.00434*** �0.00963*** �0.00718***Non partnered e
with kids�0.0122*** �0.00597*** �0.0109** �0.00337**
excluded category. Overall, the year-fixed effects are negative,which accords with the downward trend in outmigration rates forUS-born whites (and depicted in Fig. 2).
The nine interaction coefficients are estimates of the differencein differences in outmigration probability (i.e., d) for the threeLatino groups. For non-citizen foreign-born Latinos, these co-efficients are positive and significant in Arizona all three years.They also increase over time; relative to US-born whites, the out-migration of non-citizen foreign-born Latinos from Arizonaincreased by 0.85 percentage points in 2007, 1.03 percentage pointsin 2008, and 1.84 percentage points in 2009. US-born Latinos inArizona experienced a significant jump in outmigration in 2007and 2008 but the effect was smaller than for non-citizen foreign-born Latinos and it was not sustained into 2009. Positive and sig-nificant coefficients for non-citizen foreign-born Latinos also showup in Nevada in 2009 and in Florida in 2008 and 2009. The Nevadacase is inconsistent with an enforcement push that targeted theunauthorized; specifically, the non-citizen foreign-born Latino co-efficient is only significant in 2009 and in previous years it wasnaturalized foreign-born Latinos whose outmigration rate jumps,not non-citizen foreign-born Latinos. The Florida pattern is moreambiguous although the significant rise in non-citizen foreign-bornLatino outmigration there was about half the magnitude recordedin Arizona.5
The across-state models make a stronger case for a LAWA effect(Table 3). Recall that these models compare change in outmigrationrates in Arizona for a specific subgroup to change in outmigrationrates for the same subgroup in a pooled set of counterfactual statesthat had similar recessionary profiles and significant foreign-bornLatino populations. Each column in the table is a version of themodel in equation (2) estimated using a sample restricted to one ofthese subgroups. Coefficients on the socio-demographic regressorsvary across groups in these models but the pattern for each issimilar: decreasing mobility with age and if children are present;increasing mobility with education.
The three interactions coefficients are key. They are the differ-ence in differences, measuring change in the difference in
M. Ellis et al. / Political Geography 42 (2014) 46e5654
outmigration rates between Arizona and the pooled comparisonstates. The outmigration rates for non-citizen foreign-born Latinosfrom Arizona significantly increased relative to the same group inthe comparison states in 2008 and 2009. The coefficient for 2007 isjust shy of p < 0.05 significance (a t-score of 1.94). The 2008 coef-ficient suggests an increase of 0.8 percentage points relative to thecomparison set; this grows to 1.25 percentage points in 2009, inline with the idea that the LAWA push grew as more employersenrolled in E-Verify. In relation to the group's baseline outmigrationrate (the constant þ the Arizona fixed effect), these increasesindicate that the non-citizen foreign-born Latino outmigration ratefrom Arizona more than doubled between 2006 and 2009. US-bornLatinos are the only other group to show a significant difference indifferences. In 2008, all else being equal, their outmigrationincreased by 0.9 percentage points. This was a larger increase thanfor non-citizen foreign-born Latinos in the same year but it was notsustained into the next year. Both across and within state modelsidentify an effect for this group in 2008, suggesting perhaps alimited LAWA push for this group. The absence of any significantinteraction coefficients for US-born whites underscores thedistinctiveness of the findings for non-citizen foreign-born Latinos.Something boosted the outmigration of non-citizen foreign-bornLatinos from Arizona starting in 2008 relative to similar states butdid not do the same for US-born whites.6
Summary and discussion
The evidence suggests that those whose employment is most atrisk from an E-Verify expansion e non-citizen foreign-born Latinose left Arizona for other states at relatively higher rates after LAWAmandated universal employment verification beginning in 2008.The departure rate for this group increased further in the secondyear after LAWA's passage as enrollment in E-Verify swelled. Thereis weaker evidence of an effect on other Latino groups who mightexperience, fear, or resent LAWA's requirements. US-born Latinosdo leave Arizona at higher rates in 2008 but naturalized foreign-born Latinos do not.
The results alignwith prior research that showed LAWA reducedthe employment of unauthorized immigrants in Arizona. We findthat some immigrants subject to LAWA's employment conse-quences left the state for other regions of the US. This migrationresponse demonstrates that enforcement has the capacity to shifttargeted immigrant populations to other parts of the country net ofrecessionary impacts. This, of course, is likely not the only migra-tion response to LAWA. Given that Arizona and Mexico share aborder and that over half of all undocumented workers in the USare Mexican, some of the targeted population will have left forMexico. We also expect that fewer unauthorized immigrants, andpossibly authorized immigrants as well, will have moved into thestate, both from other parts of the US and directly from abroad. Asmigration is always a selective process, with some people beingmore able to move than others, these migration responses likelycomplement in situ reactions to the law: i.e., LAWA also helpeddrive unauthorized populations further into the margins andshadows of Arizona's society. The fact that the phase in of E-Verifyas well as its enforcement in Arizona took time and variedgeographically within the state likely serves to enhance suchselectivity.
Since LAWA's passage several other states, mostly in thesoutheast, have enacted similar mandatory E-Verify laws. Arizonaattempted to extend its enforcement push beyond the workplacewith SB1070 in 2010, which gave local police powers to check forimmigration status. Although the US Supreme Court vacated muchof SB1070 in 2012, it endorsed the ability of states to mandateemployee verification and employer penalties along the lines of
LAWA. The LAWA migration-push effect we find for Arizona couldnow have spread to a set of states with similar verification andenforcement policies. LAWA's migration push could be even greaternow than in the two years after it came into effect because of thegrowth in employer enrollment and the Supreme Court decisionaffirming its constitutionality. An interesting question is whetherSB1070, even when in legal limbo between its passage and its 2012partial affirmation, added energy to the migration impulse likelytriggered by LAWA. We suspect that the earlier outmigration thatfollowed LAWA's implementation will have muted SB1070's effecton migration. Those who would have left because of SB1070 mighthave already left the state because of LAWA.
The fact that an SB1070-outmigration effect might be hard todistinguish from the prior effects of LAWA highlights a broaderexplanatory challenge associated with attributing outcomes tospecific policy changes. Considerable cultural and political hostilitytoward immigrants in Arizona existed prior to the passage of theselaws and provided the context for their enactment. From thisperspective LAWA is an outcome of this hostile environment andthus migration effects (or population or employment effects forthat matter) that appear directly attributable to it are indirectly afunction of the cultural and political context that produced the law.Nevertheless, as a discrete policy change with targeted labor mar-ket aims, LAWA fundamentally altered the hiring environment forunauthorized immigrants in Arizona. As far we can tell, this changegenerated a significant increase in the internal outmigration of theunauthorized from the state.
Other important questions concern where these outmigrantsfrom Arizona choose to go. Some must have left the country, butcertainly not all. For those who remained in the US, are immigrantsmaking destination choices to avoid places with hostile environ-ments? The geography of job opportunity and the channeling effectof networks that guide immigrants to particular places surely play arole in immigrant destination choice. The geography of state andlocality immigrant policies may also affect the pattern of thesemigrations. Immigrants, especially the unauthorized, may bemoving from places with exclusionary policies to places wherepolicies are inclusionary or less exclusionary. A question of partic-ular interest is whether the rising tide of state-level enforcementpractices in new destination states in the south has increasedoutmigration from these states and reduced their attraction forparticular subgroups of immigrants. This redistribution may beselective not only in terms of legal status but also by age, education,and family status. Those who are young, single, and more educatedare more migratory in general; they may also be more likely tomove from environments of exclusion to places where they feelmore welcome. Such redistributive selectivity will enhance thelabor supply at low social cost in the places they choose to move to.Where they come fromwill have older immigrant populations withfamilies that will consume more state and local resources.
As we write, the idea of immigration reform has gained sometraction in the period after President Obama's reelection. Immi-gration reform may have a greater chance of passage throughCongress in the next few years than at any time in the pastdecade. It seems likely that any deal would require enhancedborder security and internal enforcement in exchange for someform of amnesty for the unauthorized. Nationwide, mandatory E-Verify enrollment along the lines of LAWA is a possibility in thishorse-trading. Such an extension is likely to run into oppositionfrom states opposed to the compulsory implementation of E-Verify. Resistance to a nationwide rollout of universal employ-ment checks is broad, spanning the political spectrum fromimmigrant rights advocates to ultra-conservative Republicanswho object to “forcing businesses to become policemen” (RandPaul, quoted by Associated Press, March 18, 2013). A more
M. Ellis et al. / Political Geography 42 (2014) 46e56 55
probable outcome is greater resources and incentives for work-place enforcement and greater federal penalties for failure tocomply. In this scenario, the landscape of workplace enforcementwill still be uneven post immigration reform and this differen-tiation may continue to shift patterns of settlement away fromplaces with more harsh policies. If a more extreme option comesabout and a LAWA-style law becomes national, the incentives forrelocation within the country should diminish. Even in thisinstance, some places are very likely to have more welcomingenvironments than others. Thus, regardless of any federal law, wewill continue to need more investigations of the effect of localand state policies on where immigrants, whether authorized ornot, settle.
Acknowledgment
The Geography and Spatial Sciences Program at the NationalSciences Foundation funded this research through award 0961232.The Eunice Kennedy Shriver National Institute of Child Healthand Human Development provided additional support throughawards 5R24HD042828 and 5T32HD007543. Thanks go to threeanonymous reviewers who provided useful feedback on an earlierversion of this paper.
Endnotes
1 The six states with the largest immigrant populations e California, Texas, NewYork, Florida, Illinois, and New Jersey e are the major gateways. These states arewhere the majority of the immigrant population lives and were the almost exclu-sive destinations of post WWII immigrants until the emergence of new destinationsin the 1990s.2 It also contains a provision requiring the US Attorney General to expeditiouslydeport non-citizens convicted of removable offenses. This is the taproot of thecurrent system of expedited removal. Noncitizens convicted of aggravated felonies,for example, can now be removed from the US without process (Inda, 2013).3 These states were Mississippi, South Carolina, Alabama, Georgia, and NorthCarolina.4 While there is no doubting the effects of LAWA on employer participation in E-Verify, even during a period when the law was potentially subject to judicial repeal,there is some question about whether the state, or its county prosecutors, havevigorously pursued enforcement of businesses. The state listed only two companiescharged under the law by mid-2012 (Feere, 2012).5 These findings are robust to functional form. Average marginal effects calculatedfrom a logit model with the same specification as the linear probability model aresimilar in sign, magnitude, and significance to the estimates of d reported in Table 2.6 As in the within state models, functional form does not change the findings.Average marginal effects for the difference in differences estimated from logitmodels are of the same sign, order of magnitude and have the same pattern ofsignificance as in the linear probability models. We also tested the across statemodels with a larger set of comparison states that includes the original three statesplus Colorado, Georgia, and North Carolina e all states with more than 200,000foreign-born Latinos. Like California and Nevada, Colorado is a border state toArizona and so is an additional southwestern state counterfactual in regionaleconomic and ethnic history terms. Georgia and North Carolina are so-called “newdestination” states that by 2009 ranked 5th and 6th in construction job loss (i.e. justafter Arizona and the three original comparison states). Georgia and North Carolinaenacted laws with universal verification requirements similar to LAWA but not until2011. Thus, in addition, to the fact that their construction job loss profile is similarto the main housing crash states, they also represent an emerging exclusionaryenvironment similar to Arizona pre LAWA, but one without a LAWA-style lawduring the 2007e9 period of the analysis. Estimates from these expanded com-parison set models are very similar to those from the smaller comparison set (i.e.they are consistent with a LAWA push from Arizona of the subset of people mostlikely to include the unauthorized).
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