Hispanic Border State Emigration Response to Stricter Immigration Control

Hispanic Border State Emigration Response to Stricter Immigration Control | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Hispanic Border State Emigration Response to Stricter Immigration Control Cesar Escalante, Tianyuan Luo This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5759327/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract This study draws upon assertions that Arizona’s stringent state immigration law has created a hostile social environment for Hispanics due to the law’s unintended racial profiling consequences that have serious spillover effects affecting even documented immigrants and American-born citizens of Hispanic ethnicity. Recent evidence indicates the law’s serious repercussions on the mental and physical health conditions especially among the state’s Hispanic adolescents. This study determines whether in the face of such adverse social environment, affected Hispanic families have considered relocation and migration to its contiguous neighboring states. The border state emigration argument is explored as a logical alternative due proximity and relatively more lenient immigration environment considerations. We employed differences-in-difference and synthetic control method analytical techniques to discern Hispanics’ migration trends leaving Arizona to move into bordering, contiguous states. This study’s findings indicate the lack of significant migratory response of Hispanics in Arizona, thereby suggesting that noncitizen Hispanics instead choose to remain in the state as those with legal residence status assert their immigration residential rights. Given such compelling evidence, policy attention should then be geared towards more significant damage control efforts, perhaps by redirecting resources to launch effective, efficient mechanisms to alleviate Hispanics’ mental and physical health issues. Figures Figure 1 Figure 2 Figure 3 Figure 4 Introduction Since 2010, immigration control in the United States has become increasingly tighter as several states began enacting their own laws to supplement the existing federal immigration law. Arizona pioneered these state-level efforts in 2010 when the Support Our Law Enforcement and Safe Neighborhoods Act (SB 1070) was passed. Since then, SB 1070 set the precedent and became the most controversial immigration bill in the U.S. as its immigration control provisions are arguably the strictest among its counterparts in the country. Specifically, the law’s “show me your documents” provision is the most contentious as law enforcement authorities are empowered to demand immigration documents from anyone reasonably suspected of unlawful presence. As non-compliance could be penalized with detention, its aggressive implementation has effectively led to many deportations, which realizes the law’s primary instrumental goal of decreasing the number of undocumented immigrants in the state. Beyond the law’s instrumental effect, some serious symbolic effects also emerge. These consequences emanate not from the law’s true intent, but from the conditioning of social constructs and public opinion through information dissemination and articulation (Schneider, Ingram, and DeLeon, 2014). According to previous studies, SB 1070 imposed a broad and adverse impact that seem to be targeted towards the Hispanic population in Arizona owing to their closer connection to illegal immigrants compared to other minorities (Lopez, Gonzales-Barrera, and Krogstad, 2014; Sanchez, Pedraza, and Vargas, 2015). SB 1070 would stigmatize the Hispanic population, which enhances its symbolic effect, hence even exceeding the law’s instrumental effect. Stigma usually is portrayed as an aggregated concept associated with multiple confluences of related concepts such as labeling, setting apart, discriminating, and stereotyping (Link and Hatzenbuehler 2016). The close relationship among Hispanics thereby implies that the effect of SB 1070 would not be confined to undocumented immigrants but would also influence Hispanic legal immigrants and citizens (Barreto and Segura 2010; Vargas, Sanchez, and Juarez, 2017; Santos, Menjivar, and Godfrey, 2013; Berkman, Kuwachi, and Glymour 2014). While SB 1070 and other immigration laws have very clear intentions of apprehending and deporting undocumented immigrants, they have nonetheless produced hostile social environments that caused some serious “unintended” spillover effects that reach even documented immigrants and American-born citizens (Philbin et al., 2018; Almeida et al., 2016). Recent evidence indicates that the law has seriously impaired the mental and physical health conditions of Hispanic adolescents in Arizona, recognizing these young people’s greater emotional vulnerability as they negotiate such delicate phase in their cognitive and personal development. The law has encouraged the labeling of an “undocumented immigrant” social label on Hispanics and inevitably conveyed through a confluence of labeling, ostracism, stereotyping, and discrimination (Link and Hatsenbuehler 2016). This study analyzes migration data for the years 2009 to 2011 covering a reference pre-SB 1070 enactment period (2009) and the first two years of the law’s implementation. The study period coincides with the legislative reality that the state law was not completely implemented due to pressures and demands from higher courts for relaxation of some its provisions (Dinan, 2011; Trevizo and Brosseau, 2014). Notwithstanding the law’s less aggressive implementation, its original assertions and eventual enactment in April 2010 have caused serious social and health repercussions. Our study follows the perspective of Torche and Sirois (2019) who uncover declines in infants’ birth weight attributed to SB 1070’s enactment, instead of its “controlled” implementation. Our empirical framework considers a possible migratory response of Hispanics, especially to Arizona’s contiguous, neighboring states, under the constrained social living conditions prevailing at the time that the law was created. Our expectation is that Hispanic residents could consider relocation and migration to another state that could offer more conducive living arrangements. In this analysis, we initially use synthetic control method (SCM) techniques to examine changes in Hispanic population shares and, by controlling for other covariates and guaranteeing parallel pre-trends, discern if any movements can be attributed to the implementation of SB 1070. Moreover, we develop a differences-in-difference (DID) to analyze migration trends among Hispanics from Arizona into bordering, contiguous states. Background SB 1070 Implementation As soon as SB 1070 was signed into law, there were some swift, immediate reactions that challenged the constitutionality of certain provisions of the state law. These complaints were taken up at lower courts (district and federal appeals courts) until the issue was elevated to the country’s highest court (Dinan, 2011 ). The Supreme Court (SC) struck down three controversial provisions that empower police to arrest individuals without a warrant based merely on police suspicion of individual’s illegal alien status as well as charge immigrants with state crime for either not carrying immigration documents or accepting employment without authorization (ACLU, 2024). The Court, however, retained SB 1070’s “Show Me Your Papers” provision as “it is not preempted by federal law (ACLU, 2024).” Beyond the SC ruling, SB 1070 became only partially operational as Arizona authorities were observed to have adopted a less aggressive implementation stance. According to Treviso and Brosseau (2014), a scrutiny of thousands of police records from 12 law enforcement agencies in Southern Arizona reveals that, in the early post-SC decision years, the police have adopted a more controlled, quite limited enforcement of SB 1070 as they were more faithful to prevailing local ordinances instead of SB 1070’s mandates. The SB 1070 Social Environment Nonetheless, the open, wide dissemination of SB 1070’s original immigration control principles, especially its persisting “Show Me Your Papers” provision, kept the public well-informed and stimulated discussions and opinion formation that eventually modified the social environment in Arizona. Among various racial and ethnic groups, the Hispanics seem to be more associated with illegal immigration, given their closer association to undocumented immigrants. Lopez, Gonzales-Barrera, and Krogstad (2014) find that 23% of US-born children with both Latino parents and 31% of US-born children with at least one Latino parent report personally knowing individuals who have been deported. In another survey conducted by the Center for Health Policy of the University of New Mexico, 61% of the respondents have some personal connections with an undocumented immigrant, with 48% of this sub-sample revealing close family or friendly relations with the latter (Sanchez, Pedraza, and Vargas, 2015 ). Flores ( 2017 ) provides concrete evidence on the growing hostility against Arizona residents of Hispanic ethnicity through his exposition of twitter data that surged in social media circles soon after SB 1070’s enactment. The trends indicate the proliferation of negative comments directed towards Hispanics, especially those of Mexican origins, that further incited a strong protracted anti-immigration atmosphere in the state. The effects of the ensuing social environment are validated by a host of empirical studies documenting the Hispanic’s seemingly withdrawn, elusive, cautious, and increasingly passive social behavior. These assertions are supported by evidence on reductions in the Hispanic population’s use of medical facilities and patronage of public assistance and health programs, especially among Hispanic adolescent mothers (Salas, Ayon, and Gurrola, 2013; Toomey et al. 2014 ), their use of social welfare and food security improvement programs (Winham and Armstrong 2015) and likelihood of reporting crimes (Hardy et al. 2012 ), which further threaten security and emotional stability within the community. Some studies dwell on the law’s health repercussions on the state’s young Hispanics, given their fragility and vulnerability as they navigate through the delicate, challenging period of adolescence. Moreover, Hispanic adolescents are inevitably constantly exposed to social interactions when they attend school. Luo and Escalante ( 2021 ) examine the impact of SB 1070 on the mental health, health-risk behaviors, and academic performances of the state’s Hispanic adolescents enrolled in school during the years 2001–2017. Their findings indicate that SB 1070 can be credited for significant increases in the Hispanic youth’s emotional state (probability of feeling sad) and considerable reductions in their physical activity engagements. Their results further establish that male and obese Hispanic students have greater tendencies to externalize the law’s social pressure and thus, would more likely engage in risky health behaviors. A follow-up study explores the law’s physical health repercussion (Escalante, Luo and Taylor, 2022 ). This study validates the law’s obesogenic consequences of mutually reinforcing mental and physical health behaviors among young Hispanics in Arizona. Immigration Control Mechanisms in Neighboring States The federal government launched at least two immigration control mechanisms that state and local governments may choose to adopt. The 1996 Illegal Immigration Reform and Immigrant Responsibility Act includes Section 287(g), which sets up possible collaborations for joint immigration control enforcement between federal immigration authorities and law enforcement officers of interested local governments. Under this agreement, prior to their joint efforts, the latter would receive training from the U.S. Immigration and Customs Enforcement (ICE). Consenting local governments specify in their 287(g) agreements their choice of the specific mode of immigration control enforcement selected among the following: (a) Jail Enforcement (JE) model that allows local enforcement authorities to conduct interrogation of apprehended immigrants regarding their immigration status; (b) Warrant Service Officer (WSO) model that allows local police to execute arrest warrants; and (c) Task Force (TF) model that allows police officers to question and arrest individuals suspected as undocumented. The TF model is now being phased out as the program uses mostly the JE and WSO models. As of 2024, there are 137 local governments with active 287(g) agreements, with 41 jurisdictions that terminated their agreements and have not renewed (ILRC, 2024). Table 1 presents a tabulation of the 287(g) contracts signed in Arizona and its neighboring (bordering) states. The summary shows that in this regional vicinity, there are only 7 existing agreements in place (5 in Arizona and 2 in Colorado) while the other contiguous states either have expired contracts or did not enlist in the program. E-Verify is the other federal program that regulates hiring decisions of local employers and ensures that they employ only residents who are legally authorized to work. The work permits are verified through a free online system that contains a comprehensive database of employment data obtained from the employee’s I-9 form (Employment Verification Form) and cross-checked with records from the Department of Homeland Security and Social Security Administration. The E-Verify adoption summary in Table 1 shows that states can implement this employment verification tool at varying degrees. In our sample region, all Arizona public and private businesses are currently mandated to comply with E-Verify, while Colorado and Utah impose a partial mandate that affects only government-related transactions. Notably, California, Nevada, and New Mexico do not have any E-Verify mandates. Empirical Evidence on Migration Responses Several studies clarify the prevalence of migratory responses among affected ethnic groups when laws modify social dynamics and economic opportunities in their communities. Bohn, Lofstrom, and Raphael ( 2014 ) find evidence of a declining population of foreign-born residents, specifically noncitizen Hispanics, attributed to the implementation of the state’s 2007 Legal Arizona Workers Act (LAWA). Migration studies on the effect of the E-Verify mandate, which supplemented the state’s LAWA, confirm significant reductions in the state’s population of non-naturalized citizens (Ellis et al., 2014 ) especially among less-educated and Hispanic immigrants (Amuedo-Dorantes and Lozano 2015 ). Good ( 2013 ) provides evidence in U.S. states that adopted state omnibus immigration laws (including E-Verify) of declining population of undocumented immigrants. The 287(g) program’s effect on migration decisions is also well supported. Kostandini, Mykerezi, and Escalante (2012) confirm reductions in foreign-born residents in counties that signed 287(g) contracts that, in turn, have adverse effects on wages, production decisions, and business profitability. Watson ( 2013 ) clarifies a stronger tendency for foreign-born immigrants, especially among those with college education, to relocate to other states, especially in counties that adopt the former task force model of the 287(g) program. Notably, native born immigrants do not exhibit the same migratory response. O-Neil (2013), however, could not validate a clear, systematic linkage between the 287(g) adoption and foreign-born immigrants’ population share. Earlier investigations on the SB 1070 effect primarily analyze the non-citizen Hispanics’ share of Arizona’s population. Amuedo-Dorantes and Lozano ( 2015 ) find null to minimal impact on the share of non-citizen Hispanics in Arizona, including women, after the enactment of SB 1070. Using population data for 2009 to 2012, Sánchez ( 2017 ) finds a moderate, short-lived reduction impact (about 10%) of SB 1070 on the proportion of noncitizen Hispanics in Arizona, which eventually vanished several months later. Hoekstra and Orozco-Aleman ( 2017 ) analyze activities at the Southern border and find that the flow of undocumented migrants from Mexico to Arizona fell by 30 to 70% after the passing of SB 1070, but there is no significant evidence of emigration back to their home country among those that successfully migrated and were already living in the state. Data Sources This study utilizes a couple of data sources to analyze the Hispanics’ migratory response to the previously verified mental and physical health repercussions of Arizona’s state immigration law. These datasets allow for the development of analytical models to examine the possibility of an emigration response by affected Hispanics in the state. The first phase of our emigration analysis involves the validation of published evidence on the changing demographic profiles in the state in the wake of SB 1070. In this analysis, we use monthly data from the Current Population Survey (CPS). Following previous studies (Amuedo-Dorantes and Lozano 2015 ), we construct three dependent (outcome) variables: the shares of noncitizen Hispanics, noncitizen Hispanics with higher education levels (high school graduates and with college education), and likely undocumented Hispanics. Following Amuedo-Dorantes and Bansak ( 2014 ), we define likely undocumented Hispanics as noncitizens, with complete high school education, and younger than 45 years old. The latter phase of our analytical model examines the emigration of Hispanics from Arizona into bordering, contiguous states following the SB 1070 enactment. Our primary contention recalls SB 1070’s instrumental effect of evicting undocumented immigrants from the state. If such effect indeed results in SB 1070 effectively driving Hispanics out of Arizona, its bordering states could be popular destinations for relocation based on two arguments: their proximity translating to more convenient, easier relocation logistical arrangements and their relatively more lenient immigration control stance compared to Arizona (Table 1 ). We use data obtained from the 2006–2012 American Community Survey (ACS) that has a total of 303,881 observations. The ACS polls on the interviewee’s migration status one year prior and provides a count of Hispanics who moved into a state from Arizona and other inter-state relocations. As a result, we could identify Hispanic migrants from Arizona or other states before and during the SB 1070 regime. Table 1 . 287g Agreements and E-Verify Subscription in Arizona and its Contiguous (Bordering) States Sources: ILRC, 2024; Equifax, 2023; NCSL, 2015; Capps et al., 2011 Arizona and its Border States Current Immigration Controls 1 2010-2011 Immigration Controls 1 Jurisdictions with 287g Agreements (2024) 2 E-Verify Subscription (2023) Jurisdictions with 287g Agreements as of August 2010 2 E-Verify Subscription (As of 2011) Active Expired Arizona 4 JE 1 WSO/TF 1 JE 2 TF All Government and Private 2 JE 1 TF 6 JE-TF All Government and Private California None 3 JE No State E-Verify (Forbids local E-Verify) 4 JE No State E-Verify Colorado 2 JE 1 JE State and Local Government (Contractors only) 1 JE 1 TF State and Local Government (Contractors only) Nevada None 3 JE No State E-Verify 1 JE No State E-Verify New Mexico None No State E-Verify 1 JE No State E-Verify Utah None` State and Local Government (Agencies and Contractors) 2 JE All Government and Private (Allows private employers to employ undocumented aliens with UT Guest Worker Permit, contingent on federal waiver) Note: 1 Green-shaded cells indicate the absence of any active immigration control mandate under the program. 2 287(g) contracts stipulate the following specific immigration control mechanisms agreed upon by the contracting local government and ICE: Jail Enforcement (JE), Task Force (TF), Warrant Service Officer (WSO) Analytical Models Synthetic Control Method (SCM) The first phase of our analytical model employs the SCM framework, which is an appropriate analytical tool for investigating the impact of an “event” or a single-unit treatment (Abadie, Diamond, and Hainmueller, 2010 ). Through a data-driven algorithm, a counterfactual unit (herein referred to as the control group) is constructed ensuring that this unit shares similar pre-treatment trends in the outcome variables with the unit affected by the “event” (the treated unit). SCM ensures parallel trends between the treated and control units during the period prior to the occurrence of the event (pre-treatment) period. This is accomplished by choosing a weighted combination of control states that will collectively form the “synthetic control unit” that shares similar pre-treatment characteristics and conditions as those present in the real treated unit. Our analysis uses the state level as the unit of observation. The treated unit is coded as j = 0 and candidate states for the synthetic control group are coded as j=(1,2,…,J). In this empirical framework, the enactment of SB 1070 law is the “event” of interest. The real Arizona state is our base treated state. The “Synthetic Arizona” control group is collectively built around other states that yielded positive weights in the data-driven process of SCM. Weights are obtained through the minimization of the value of the distance, derived as follows $$\:\left|\right|\:{X}_{0}-\:{X}_{1}W\left|\right|=\sqrt{{\left({X}_{0}-\:{X}_{1}W\right)}^{{\prime\:}}V\left({X}_{0}-\:{X}_{1}W\right)}\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\left(1\right)\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:$$ where \(\:{X}_{0}\) is a \(\:k\times\:1\) vector capturing the characteristics of Arizona in the pre-treatment period and \(\:{X}_{1}\) is a \(\:k\times\:j\) vector applies to the control units. Both \(\:{X}_{0}\) and \(\:{X}_{1}\) include the outcomes of interest as well as independent variables that may affect outcomes in each state. The weights that are assigned to states in the donor (mother) pool of state observations are positive and sum up to one. A vector of optimal weights to each state \(\:{W}^{\text{*}}=({w}_{1},\:\:{w}_{2},\dots\:,{w}_{J})\) is generated and the states with non-zero weights are singled out to construct the collective synthetic Arizona group that best approximates the real Arizona case. Each covariate used to control for each of the outcomes is assigned a weight. The importance of each covariate in the X vector in predicting any change in each of the outcome variables is indicated by generating a k×k vector V. The covariates chosen for predicting a specific outcome are aggregated at the state level. In this analysis, the synthetic Arizona unit is constructed using a set of covariates that include the undocumented immigrants’ and Hispanic shares in the state’s population, unemployment rate, 287(g) participation, E-Verify status, real GDP per capita, and lagged outcome variables from the pre-treatment period. In addition, real dollar values of per capital state expenditures for education, health, and overall government spending are also included in these estimations. Thus, for each outcome variable, there will be a different composition of the synthetic Arizona unit as in every estimation for each outcome variable, the synthetic control unit will include only those states with non-zero weights. The unique composition of synthetic Arizona states in each outcome ensures that given the varied emphases of the outcome variables (overall immigration profile, educational attainment of non-immigrants, and concentration of undocumented population), every constructed synthetic control unit closely resembles the treated state’s conditions. The only differentiating factor between such constructed synthetic Arizona clusters and the real Arizona case is the latter’s experience of this model’s event of interest, that is the enactment of SB1070 legislation, which is non-existent in the “synthetic Arizona” states. Differences–in-Difference (DID) Estimation In our DID model, the adoption of SB 1070 in Arizona is treated as a quasi-natural experiment. Our DID model is an extension of the SCM migration analysis and is designed to capture Hispanic migration to adjacent states. For this analysis, we construct a DID regression with the following specification $$\:{Migrant-AZHisp}_{ist}=\alpha\:+\beta\:{SB1070\_adjacent}_{ist}+\gamma\:{X}_{ist}^{{\prime\:}}+{\theta\:}_{s}+{\mu\:}_{t}+{\epsilon\:}_{ist}$$ 2 where \(\:{Migrant-AZHisp}_{ist}\) equals one if an individual is identified as a Hispanic migrant from Arizona, zero if a Hispanic migrant is from other states. \(\:\:{SB1070\_adjacent}_{ist}\) equals one if a migrant is in one of Arizona’s bordering states (California, Nevada, Colorado, New Mexico, and Utah) after SB 1070. \(\:{X}_{ist}^{{\prime\:}}\) includes a series of demographic and state level covariates. \(\:{\theta\:}_{s}\) and \(\:{\mu\:}_{t}\) are state and year fixed effects. \(\:{\epsilon\:}_{ist}\) is the error term. \(\:\beta\:\) measures if bordering states would experience a higher likelihood of seeing more Hispanic migrants from Arizona after SB 1070. The demographic covariates include gender, age, marital status, education, employment status, family size, and other immigration-related policies such as E-verify mandates, and the 287(g) contracts. Since the data set does not provide county identifiers, the 287(g) variable is controlled at the state level. Business cycle covariates include the state-level unemployment rate, real GDP per capita, real government expenditure per capita, and the employment rate specific to the construction sector. The construction industry is included in the analysis as this sector usually attracts foreign workers and usually holds hiring advantages given its more favorable compensation structure (Luo and Escalante, 2017). Hispanics Migration Response Results Descriptive results Figure 1 shows the comparative trends of the shares of noncitizen Hispanics, more highly educated noncitizen Hispanics, and likely undocumented Hispanics in Arizona and California, which account for the two highest concentrations of undocumented immigrants in the region in 2010 and 2011 (CMS, 2022). California is the logical choice for the comparative analysis since around SB 1070’s enactment, it accounts for about 77 percent and almost 25 percent of all undocumented immigrants in the region and the entire country, respectively (CMS, 2022). As can be seen from the plots, we do not find substantial disparities of the share trends between the two states, thus suggesting that SB 1070 has limited impact on altering trends in Hispanic population shares in Arizona. To further corroborate our preliminary findings, we use SCM analytical techniques to examine if these shares decrease due to SB 1070. In the SCM analysis, we will control for other covariates and validate the parallel pre-trend condition. Synthetic control method results Figure 2 features the SCM estimates for the impact of SB 1070 on the share of noncitizen Hispanics. The covariates included are state level unemployment rate, state level unemployment rate in construction, real GDP per capita, real government expenditure per capita, the share of population in agriculture, the share of population in construction, mean Hispanics education level, mean Hispanics age, and lagged share of noncitizen Hispanics. The states that are assigned positive weights for constructing a synthetic Arizona for the share of noncitizen Hispanics are: California (0.305), Iowa (0.306), and Nevada (0.389). The plot on the right side shows the permutation test results indicating the significance level. Figure 2 shows that the parallel pre-trend condition is satisfied as both the real and synthetic Arizona lines consistently converge during pre-SB 1070 (2010) period. Subsequently, the share of noncitizen Hispanics did not significantly change after 2010. As can be gleaned from the plots, there is no clear deviation between Arizona’s (blue) and synthetic Arizona’s (red) trend lines. Moreover, the permutation test graph on the right presents the same conclusion as Arizona’s line lies well among other placebo lines. The analysis is then extended to consider a subpopulation of advantaged, more educated noncitizen Hispanics (those who are either high school graduates or have college education). The states with positive weights that comprise the synthetic Arizona group are Alabama (0.037), Florida (0.239), Georgia (0.187), California (0.11), Nevada (0.154), New Mexico (0.024), Texas (0.191). and Utah (0.06). The findings of the SCM graph on the left and the permutation graph on the right (Fig. 3 ) indicate that there is no significant gap between Arizona and synthetic Arizona, thus suggesting the absence of an impact of SB 1070 on the population share of advantaged noncitizen Hispanics in Arizona. In the second extension of the analysis, we analyze the law’s migratory effect on disadvantaged Hispanics with lower education and younger age (and theoretically tagged as likely undocumented residents). The states assigned positive weights for constructing the synthetic Arizona are California (0.394), Indiana (0.491), and Nevada (0.116). The results presented in Fig. 4 validate the same conclusion deduced from Figs. 2 and 3 , confirming the same lack of significant evidence of any notable decrease in the share of likely undocumented Hispanics after SB 1070. The permutation test graph also shows no significant difference between Arizona’s line and other placebo lines. The preliminary (descriptive plots) evidence, together with the SCM findings, suggest that SB 1070 did not cause a notably large-scale emigration from Arizona among the Hispanic population. Although Allen and McNeely ( 2017 ) and Bohn, Lofstrom, and Raphael ( 2014 ) contend that low-skilled noncitizen Latinos are more likely to migrate from states with omnibus laws, our findings suggest otherwise in relation to the SB 1070 enactment. Our findings instead support the contention of Sadowski-Smith and Li ( 2016 ), who assert that there possibly would not be wide distinctions in migration decisions made by both low and highly skilled immigrants. Adjacent states migration results The DID estimation results for the Hispanic’s migration decisions are presented in Table 2 . The DID analysis focuses on the emigration of Hispanics from Arizona to its neighboring (contiguous) states, given proximity and immigration environment considerations. Table 2 Estimates of SB 1070 impact on Arizona migrants in bordering states. Migrants from Arizona Variables Noncitizen Hispanics Advantaged (Educated) Noncitizen Hispanics Disadvantaged (Likely Undocumented) Noncitizen Hispanics SB 1070 coefficient (standard error) 0.0007 (0.0010) 0.0011 (0.0008) 0.0011 (0.0008) Demographic covariates Yes Yes No Business cycle covariates Yes No No N 303,364 303,881 303,881 Notes: The estimates are obtained by the linear probability model. Demographic covariates included are gender, age, marital status, education, employment status, family size, and other immigration policy variables. Business cycle covariates included are state unemployment rate, state unemployment rate in construction, real GDP per capita, real government expenditure per capita. Regression coefficients are weighted, and robust standard errors are clustered at the state level. * p < 0.1, **p < 0.05, and ***p < 0.01. Based on the summary in Table 2 , the coefficients for the SB 1070 variable are consistently insignificant in all three versions of the model. These results corroborate the trends validated in our earlier analyses. Both DID and SCM models provide compelling evidence on decisions of Arizona’s noncitizen Hispanics to forego migration to a neighboring state as an escape mechanism as SB 1070 has modified their in-state social environment. Ideally, the states that border around Arizona offer a logical residential and employment choice for Arizona’s Hispanics. Around the time of SB 1070’s enactment, four of the five neighboring states have at most only two counties that signed 287(g) contracts (Table 1 ). These contracts usually are concentrated in the jurisdiction of their capital cities, thus leaving the rest of the state unregulated (Capps et al, 2011 ). In contrast, Arizona had 9 active 287(g) contracts in force at that time. The E-Verify mechanism, which poses a significant economic restraint for likely undocumented Hispanics (model 3), had not been enforced widely in the region during the time of the SB 1070 enactment. As of 2011, three states (California, Nevada, and New Mexico) did not employ E-Verify at all in their hiring activities (Table 1 ). Colorado and Utah had partial E-Verify models that affected only state and local government employment decisions. The latter even allowed the employment of undocumented residents who were holders of their state guest worker permit. Thus, the work environments in these bordering states were more conducive to undocumented immigrants’ pursuit of employment opportunities compared to Arizona’s E-Verify mandate that applied to all government and private businesses. Moreover, two neighboring states (New Mexico and Utah) offered an additional benefit for undocumented immigrants as they (along with Washington) were the only states in the country at that time to allow such immigrants to obtain driver’s licenses (Luo and Escalante, 2024). Nevada and Colorado would eventually join this pack in 2014, with California chiming in two years later. Overall, the neighboring states’ immigration stances were relatively more accommodating in both social and economic terms than the Arizona residence option. However, this study’s findings emphasize the Hispanics’ decisions to instead remain in Arizona despite the state’s enforcement of multiple immigration control mechanisms. Summary and Conclusions This study provides empirical evidence on possible migratory responses of legal and documented Hispanic residents in Arizona may adopt as a possible mechanism for coping with the social repercussions, even if they are arguably unintended, of the state’s immigration law (SB 1070). Earlier studies have clearly shown that such negative “racial profiling “consequences of the state law have led to serious adverse effects on Hispanic mental and physical health conditions. When faced with such adversities, we surmise that Hispanic residents may consider migration to other states with relatively more lenient immigration regulations. A cursory analysis of Arizona’s neighboring states reveals potentials for social and economic assimilation of Hispanic residents. Notwithstanding the bordering states’ leniency towards certain immigration issues, our results indicate a general lack of significant migratory response of Hispanics in Arizona. This could imply that the state’s Hispanic residents still choose to assert their rights as legal residents of the state, a status acquired over many years of satisfying procedural and documentary requirements prescribed by the country’s naturalization process. As this study establishes the Hispanics’ firm claim on legally acquired residence in the state, the inevitable and unintended mental and physical health consequences of racial profiling and social ostracism persist. These unfortunate repercussions of the law should not be ignored, especially by local and federal authorities who have the jurisdiction and capability to introduce effective reforms. The mental and physical health of vulnerable populations, especially Hispanic youths, must be given broader attention by the whole society as well as policymakers. After the unsuccessful attempts of the Department of Justice to tone down several provisions of Arizona’s state immigration policies, current policies must now be geared towards more significant damage control efforts. Local and federal policymakers should consider redirecting resources to launching more effective, efficient mechanisms to help Hispanics with their mental and physical health issues. Moreover, legislators should formulate social engagement and modification policies aimed at neutralizing the negative elements of the alienating, harmful social environment created under the SB 1070 regime. Declarations Author Contribution C.E. wrote most of the main manuscript text. T.L. took care of the analytical models (DID and SCM). C.E. and T.L. both prepared tables and analyzed the results. Both authors reviewed the manuscript and prepared it for submission. Data Availability Data analyzed and reported in the manuscript can be accessed athttps://drive.google.com/file/d/1K3Aq9stw6Jzb_pLel24TCxKfvL_hT8Qm/view References Abadie, A., Diamond, A., & Hainmueller, J. 2010. Synthetic control methods for comparative case studies: Estimating the effect of California’s tobacco control program. Journal of the American Statistical Association, 105(490): 493-505. Allen, C.D. and McNeely, C.A., 2017. Do restrictive omnibus immigration laws reduce enrollment in public health insurance by Latino citizen children? A comparative interrupted time series study. Social Science & Medicine, 191:19-29. Almeida, J., K. B. Biello, F. Pedraza, S. Wintner, & E. Viruell-Fuentes. 2016. The Association between Anti-immigrant Policies and Perceived Discrimination among Latinos in the US: A Multilevel Analysis. SSM-Population Health 2, 897–903. https://doi.org/10.1016/ j.ssmph.2016.11.003. American Civil Liberties Union (ACLU). 2024. SB 1070 at the Supreme Court: What’s at Stake. American Civil Liberties Union, New York, NY. Available online at https://www.aclu.org/sb-1070-supreme-court-whats-stake. Accessed on August 28, 2024. Amuedo-Dorantes, C., & C. Bansak. 2014. Employment Verification Mandates and the Labor Market Outcomes of Likely Unauthorized and Native Workers. Contemporary Economic Policy, 32 (3): 671–80. https://doi.org/10.1111/coep.12043 Amuedo-Dorantes, C. and Lozano, F., 2015. On the effectiveness of SB1070 in Arizona. Economic inquiry, 53(1): 335-351. American Psychiatric Association. (2017). Mental Health Disparities: Diverse Populations. https://www.psychiatry.org/psychiatrists/cultural-competency/mental-health-disparities. Accessed on August 1, 2018. Antman, F., Duncan, B., & Trejo, S. J. 2016. Ethnic attrition and the observed health of later-generation Mexican Americans. American Economic Review, 106(5): 467-71. Antman, F. M., Duncan, B., & Trejo, S. J. 2020. Ethnic attrition, assimilation, and the measured health outcomes of Mexican Americans. Journal of Population Economics, 1-24. Berkman, L.F., Kawachi, I. and Glymour, M.M. eds., 2014. Social epidemiology. Oxford University Press. Barreto, M.A. and Segura, G.M., 2010. Do NES Models of Voting Apply to Blacks and Latinos? Results of the 2008 NES Oversample. In Western Political Science Association Annual Conference, San Francisco, CA. Bohn, S., M. Lofstrom, and S. Raphael. 2014. Did the 2007 Legal Arizona Workers Act Reduce the State’s Unauthorized Immigrant Population? Review of Economics and Statistics, 96 (2), 258–69. https://doi.org/10.1162/REST_a_00429. Capps, R., M.R. Rosenblum, C. Rodriguez, and M. Chishti. 2011. Delegation and Divergence: A Study of 287(g) State and Local Immigration Enforcement. Migration Policy Institute, Washington, DC. Center for Migration Studies (CMS). 2022. Undocumented Immigrants in the United States, by State and Year, 2010 to 2019. Center for Migration Studies, New York, NY. Dinan S. 2011. A year later, Ariz. Immigration fights rage. Washington Times. Available online at https://www.washingtontimes.com/news/2011/apr/21/one-year-later-the-battle-still-rages-in-arizona/. Accessed on August 28, 2024. Eaton, D. K., Kann, L., Kinchen, S., Shanklin, S., Ross, J., Hawkins, J., & Lim, C. 2008. Youth risk behavior surveillance--United States, 2007. Morbidity and mortality weekly report. Surveillance summaries (Washington, DC: 2002), 57(4), 1-131. Ellis, M., Wright, R., Townley, M., and Copeland, K. 2014. The migration response to the Legal Arizona Workers Act, Political Geography, 42: 46-56, https://doi.org/10.1016/j.polgeo.2014.06.001. Equifax. 2023. Guardian E-Verify Compliance and Requirements. Equifax, Inc., Atlanta, GA. Available online at https://assets.equifax.com/ews/lawlogix/assets/e-verify-compliance-requirements.pdf. Accessed on August 28, 2024. Escalante, C.L., Luo, T. & Taylor, C.E. 2022. The Obesity Effect of Arizona’s State Immigration Law Among Hispanic Adolescents. J Immigrant Minority Health 24, 853–861. https://doi.org/10.1007/s10903-022-01333-9. Flores, R. D. 2017. "Do anti-immigrant laws shape public sentiment? A study of Arizona’s SB 1070 using Twitter data." American Journal of Sociology 123.2: 333-384. Good M. 2013. Do immigrant outflows lead to native inflows? An empirical analysis of the migratory responses to US state immigration legislation. Appl Econ. 45:4275–97. Hardy, L.J., Getrich, C.M., Quezada, J.C., Guay, A., Michalowski, R.J. and Henley, E., 2012. A call for further research on the impact of state-level immigration policies on public health. American journal of public health, 102(7), pp.1250-1253. Hoekstra, M. and S. Orozco-Aleman. 2017. "Illegal Immigration, State Law, and Deterrence." American Economic Journal: Economic Policy, 9 (2): 228-52. Immigrant Legal Resource Center (ILRC). 2024. National Map of 287(g) Agreements. Immigrant Legal Resource Center, San Francisco, CA. Available online at https://www.ilrc.org/resources/national-map-287g-agreements. Accessed on August 28, 2024. Kostandini, G., E. Mykerezi, and C.L. Escalante. 2014. “The Impact of Immigration Enforcement on the Farming Sector.” American Journal of Agricultural Economics, 96,1: 172-192. Link, B. and Hatzenbuehler, M.L., 2016. Stigma as an unrecognized determinant of population health: research and policy implications. Journal of health politics, policy and law, 41(4), pp.653-673. Lopez, M.H., Gonzalez-Barrera, A. and Krogstad, J.M., 2014. Latino support for democrats falls, but democratic advantage remains. Pew Research Center, October, 29. Luo, T. and Escalante, C.L. (2021), Stringent immigration enforcement and the mental health and health‐risk behaviors of Hispanic adolescent students in Arizona. Health Economics, 30: 86-103. https://doi.org/10.1002/hec.4178. National Conference of State Legislatures (NCSL). 2015. State E-Verify Action. National Conference of State Legislatures, Denver, CO. Available online at https://www.ncsl.org/immigration/state-e-verify-action. Accessed on September 2, 2024. O'Neil, K, S. 2013. Immigration Enforcement by Local Police Under 287(g) and Growth of Unauthorized Immigrant and Other Populations. University of Cape Town Working Paper. Available at SSRN: https://ssrn.com/abstract=2210765 or http://dx.doi.org/10.2139/ssrn.2210765. Philbin, M. M., M. Flake, M. L. Hatzenbuehler, & J. S. Hirsch. 2018. State-Level Immigration and Immigrant-Focused Policies as Drivers of Latino Health Disparities in the United States. Social Science & Medicine, 199, 29–38. https://doi.org/10.1016/j.socscimed.2017.04.007 Sadowski-Smith C., Li W. 2016. Return migration and the profiling of non-citizens: Highly skilled BRIC migrants in the Mexico–US borderlands and Arizona’s SB 1070. Population, Space, and Place, 22, 487–500. Salas, L.M., Ayón, C. and Gurrola, M., 2013. Estamos traumados: The effect of anti‐immigrant sentiment and policies on the mental health of Mexican immigrant families. Journal of Community Psychology, 41(8), pp.1005-1020. Sánchez, G.E. 2017. "The short-term response of the Hispanic noncitizen population to anti-illegal immigration legislation: The case of Arizona SB 1070", Journal of Economics, Finance and Administrative Science, Vol. 22 No. 42, pp. 25-36. https://doi.org/10.1108/JEFAS-02-2017-0034. Sanchez, G.R., F. Pedraza, and E.D. Vargas. 2015. National Latino Health and Immigration Survey. Center for Health Policy, Robert Wood Johnson Foundation, University of New Mexico, Albuquerque, NM. Santos, C., Menjívar, C. and Godfrey, E., 2013. Effects of SB 1070 on children. In Latino politics and Arizona’s immigration law SB 1070 (pp. 79-92). Springer, New York, NY. Schneider, A. L., Ingram, H., and DeLeon, P. (2014). Democratic policy design: Social construction of target populations. Theories of the policy process, 3, 105-149. Toomey, R.B., Umaña-Taylor, A.J., Williams, D.R., Harvey-Mendoza, E., Jahromi, L.B. and Updegraff, K.A., 2014. Impact of Arizona’s SB 1070 immigration law on utilization of health care and public assistance among Mexican-origin adolescent mothers and their mother figures. American journal of public health, 104(S1), pp. S28-S34. Torche, F. and C. Sirois. 2019. Restrictive Immigration Law and Birth Outcomes of Immigrant Women, American Journal of Epidemiology, 188 (1): 24–33, https://doi.org/10.1093/aje/kwy218. Trevizo P and C. Brosseau. 2014. Lax record-keeping blurs SB1070 impact. Arizona Daily Star. Available online at https://tucson.com/news/local/border/lax-record-keeping-blurs-sb-1070-impact/article_755d577f-be7b-593a-ac11-5d43d17de100.html, Accessed on August 28, 2024. Vargas, E.D., Sanchez, G.R. and Juárez, M., 2017. Fear by association: perceptions of anti-immigrant policy and health outcomes. Journal of health politics, policy and law, 42(3), pp.459-483. Watson, T. 2013. Enforcement and Immigrant Location Choice. Working Paper # 19626, National Bureau of Economic Research, Cambridge, MA. Winham, D.M. and Armstrong Florian, T.L., 2015. Nativity, not acculturation, predicts SNAP usage among low-income Hispanics with food insecurity. Journal of Hunger & Environmental Nutrition, 10(2), pp.202-213. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-5759327","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":398275819,"identity":"59e7dceb-68d1-461b-bb0b-413e29c0f016","order_by":0,"name":"Cesar Escalante","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAx0lEQVRIiWNgGAWjYNCCAgYGfgiLmVgtBgwMkg0kazE4QKwW/vb2hx9+GNjlGd9Iv/iBocI6sYGQFokzZ4wlewySi81u5BRLMJxJJ6zFQCKHjYHHgDlx242cBAnGtsNEaJF//ozxj0F94uYZOck/GP8Ro0WCwYyZx+Bw4gaJ9GMSjA1EaJE4k2MsLWNwPHHGmTdsFgnH0o0JauFvP/7w45uK6sT+9vTHNz7UWMsS1IIEeAwYEkhQDgLsD0jUMApGwSgYBSMFAAA+Uj3YkJpInAAAAABJRU5ErkJggg==","orcid":"","institution":"University of Georgia","correspondingAuthor":true,"prefix":"","firstName":"Cesar","middleName":"","lastName":"Escalante","suffix":""},{"id":398275821,"identity":"535d2f20-6c59-46d6-9e66-7c8cb4742c88","order_by":1,"name":"Tianyuan Luo","email":"","orcid":"","institution":"Xi'an Jiaotong University","correspondingAuthor":false,"prefix":"","firstName":"Tianyuan","middleName":"","lastName":"Luo","suffix":""}],"badges":[],"createdAt":"2025-01-03 15:38:20","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-5759327/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-5759327/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":73237924,"identity":"c0897f2a-8148-4d50-88b7-fe1f36dd2ab8","added_by":"auto","created_at":"2025-01-08 05:29:02","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":34965,"visible":true,"origin":"","legend":"\u003cp\u003eTrends of share of noncitizen and likely undocumented Hispanics in Arizona and California.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-5759327/v1/51ee9938c18001701b05444b.png"},{"id":73240725,"identity":"56d976f1-cbee-448f-8074-3313647b2c6b","added_by":"auto","created_at":"2025-01-08 06:01:02","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":18991,"visible":true,"origin":"","legend":"\u003cp\u003eThe impact of SB 1070 on the share of noncitizen Hispanics.\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-5759327/v1/23f71f90586bc8f3ec75cdd0.png"},{"id":73238361,"identity":"56cc0cda-d878-4461-80e8-6ffd248c8846","added_by":"auto","created_at":"2025-01-08 05:37:02","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":17562,"visible":true,"origin":"","legend":"\u003cp\u003eThe impact of SB 1070 on the share of noncitizen Hispanics with a higher education level.\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-5759327/v1/52517e609323f02d7d8861c5.png"},{"id":73237929,"identity":"26df5b38-2f0a-4aee-aeeb-807f7cb5a8d8","added_by":"auto","created_at":"2025-01-08 05:29:02","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":19024,"visible":true,"origin":"","legend":"\u003cp\u003eThe impact of SB 1070 on the share of likely undocumented Hispanics.\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-5759327/v1/d0a19a5cb2a15d4d6c34d61a.png"},{"id":73372741,"identity":"4fa413ce-a300-4c13-bf2c-2f824efa57ff","added_by":"auto","created_at":"2025-01-09 10:29:47","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":678599,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5759327/v1/a7abecab-c8c7-452b-b95e-9e5f6855e7ed.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Hispanic Border State Emigration Response to Stricter Immigration Control","fulltext":[{"header":"Introduction","content":"\u003cp\u003eSince 2010, immigration control in the United States has become increasingly tighter as several states began enacting their own laws to supplement the existing federal immigration law. \u0026nbsp;Arizona pioneered these state-level efforts in 2010 when the Support Our Law Enforcement and Safe Neighborhoods Act (SB 1070) was passed. \u0026nbsp;Since then, SB 1070 set the precedent and became the most controversial immigration bill in the U.S. as its immigration control provisions are arguably the strictest among its counterparts in the country. \u0026nbsp;Specifically, the law\u0026rsquo;s \u0026ldquo;show me your documents\u0026rdquo; provision is the most contentious as law enforcement authorities are empowered to demand immigration documents from anyone reasonably suspected of unlawful presence. \u0026nbsp;As non-compliance could be penalized with detention, its aggressive implementation has effectively led to many deportations, which realizes the law\u0026rsquo;s primary instrumental goal of decreasing the number of undocumented immigrants in the state. \u0026nbsp;\u003c/p\u003e\n\u003cp\u003eBeyond the law\u0026rsquo;s instrumental effect, some serious symbolic effects also emerge. \u0026nbsp;These consequences emanate not from the law\u0026rsquo;s true intent, but from the conditioning of social constructs and public opinion through information dissemination and articulation (Schneider, Ingram, and DeLeon, 2014). According to previous studies, SB 1070 imposed a broad and adverse impact that seem to be targeted towards the Hispanic population in Arizona owing to their closer connection to illegal immigrants compared to other minorities (Lopez, Gonzales-Barrera, and Krogstad, 2014; Sanchez, Pedraza, and Vargas, 2015). \u0026nbsp; \u0026nbsp;SB 1070 would stigmatize the Hispanic population, which enhances its symbolic effect, hence even exceeding the law\u0026rsquo;s instrumental effect. Stigma usually is portrayed as an aggregated concept associated with multiple confluences of related concepts such as labeling, setting apart, discriminating, and stereotyping (Link and Hatzenbuehler 2016). The close relationship among Hispanics thereby implies that the effect of SB 1070 would not be confined to undocumented immigrants but would also influence Hispanic legal immigrants and citizens (Barreto and Segura 2010; Vargas, Sanchez, and Juarez, 2017; Santos, Menjivar, and Godfrey, 2013; Berkman, Kuwachi, and Glymour 2014).\u003c/p\u003e\n\u003cp\u003eWhile SB 1070 and other immigration laws have very clear intentions of apprehending and deporting undocumented immigrants, they have nonetheless produced hostile social environments that caused some serious \u0026ldquo;unintended\u0026rdquo; spillover effects that reach even documented immigrants and American-born citizens (Philbin et al., 2018; Almeida et al., 2016). \u0026nbsp;Recent evidence indicates that the law has seriously impaired the mental and physical health conditions of Hispanic adolescents in Arizona, recognizing these young people\u0026rsquo;s greater emotional vulnerability as they negotiate such delicate phase in their cognitive and personal development. The law has encouraged the labeling of an \u0026ldquo;undocumented immigrant\u0026rdquo; social label on Hispanics and inevitably conveyed through a confluence of labeling, ostracism, stereotyping, and discrimination (Link and Hatsenbuehler 2016).\u003c/p\u003e\n\u003cp\u003eThis study analyzes migration data for the years 2009 to 2011 covering a reference pre-SB 1070 enactment period (2009) and the first two years of the law\u0026rsquo;s implementation. \u0026nbsp;The study period coincides with the legislative reality that the state law was not completely implemented due to pressures and demands from higher courts for relaxation of some its provisions (Dinan, 2011; Trevizo and Brosseau, 2014). \u0026nbsp;Notwithstanding the law\u0026rsquo;s less aggressive implementation, its original assertions and eventual enactment in April 2010 have caused serious social and health repercussions. \u0026nbsp;Our study follows the perspective of Torche and Sirois (2019) who uncover declines in infants\u0026rsquo; birth weight attributed to SB 1070\u0026rsquo;s enactment, instead of its \u0026ldquo;controlled\u0026rdquo; implementation.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eOur empirical framework considers a possible migratory response of Hispanics, especially to Arizona\u0026rsquo;s contiguous, neighboring states, under the constrained social living conditions prevailing at the time that the law was created. \u0026nbsp; Our expectation is that Hispanic residents could consider relocation and migration to another state that could offer more conducive living arrangements. \u0026nbsp;In this analysis, we initially use synthetic control method (SCM) techniques to examine changes in Hispanic population shares and, by controlling for other covariates and guaranteeing parallel pre-trends, discern if any movements can be attributed to the implementation of SB 1070. Moreover, we develop a differences-in-difference (DID) to analyze migration trends among Hispanics from Arizona into bordering, contiguous states.\u003c/p\u003e"},{"header":"Background","content":"\u003cdiv id=\"Sec2\" class=\"Section2\"\u003e \u003ch2\u003eSB 1070 Implementation\u003c/h2\u003e \u003cp\u003eAs soon as SB 1070 was signed into law, there were some swift, immediate reactions that challenged the constitutionality of certain provisions of the state law. These complaints were taken up at lower courts (district and federal appeals courts) until the issue was elevated to the country’s highest court (Dinan, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2011\u003c/span\u003e). The Supreme Court (SC) struck down three controversial provisions that empower police to arrest individuals without a warrant based merely on police suspicion of individual’s illegal alien status as well as charge immigrants with state crime for either not carrying immigration documents or accepting employment without authorization (ACLU, 2024). The Court, however, retained SB 1070’s “Show Me Your Papers” provision as “it is not preempted by federal law (ACLU, 2024).”\u003c/p\u003e \u003cp\u003eBeyond the SC ruling, SB 1070 became only partially operational as Arizona authorities were observed to have adopted a less aggressive implementation stance. According to Treviso and Brosseau (2014), a scrutiny of thousands of police records from 12 law enforcement agencies in Southern Arizona reveals that, in the early post-SC decision years, the police have adopted a more controlled, quite limited enforcement of SB 1070 as they were more faithful to prevailing local ordinances instead of SB 1070’s mandates.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eThe SB 1070 Social Environment\u003c/h2\u003e \u003cp\u003eNonetheless, the open, wide dissemination of SB 1070’s original immigration control principles, especially its persisting “Show Me Your Papers” provision, kept the public well-informed and stimulated discussions and opinion formation that eventually modified the social environment in Arizona. Among various racial and ethnic groups, the Hispanics seem to be more associated with illegal immigration, given their closer association to undocumented immigrants. Lopez, Gonzales-Barrera, and Krogstad (2014) find that 23% of US-born children with both Latino parents and 31% of US-born children with at least one Latino parent report personally knowing individuals who have been deported. In another survey conducted by the Center for Health Policy of the University of New Mexico, 61% of the respondents have some personal connections with an undocumented immigrant, with 48% of this sub-sample revealing close family or friendly relations with the latter (Sanchez, Pedraza, and Vargas, \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2015\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eFlores (\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2017\u003c/span\u003e) provides concrete evidence on the growing hostility against Arizona residents of Hispanic ethnicity through his exposition of twitter data that surged in social media circles soon after SB 1070’s enactment. The trends indicate the proliferation of negative comments directed towards Hispanics, especially those of Mexican origins, that further incited a strong protracted anti-immigration atmosphere in the state.\u003c/p\u003e \u003cp\u003eThe effects of the ensuing social environment are validated by a host of empirical studies documenting the Hispanic’s seemingly withdrawn, elusive, cautious, and increasingly passive social behavior. These assertions are supported by evidence on reductions in the Hispanic population’s use of medical facilities and patronage of public assistance and health programs, especially among Hispanic adolescent mothers (Salas, Ayon, and Gurrola, 2013; Toomey et al. \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2014\u003c/span\u003e), their use of social welfare and food security improvement programs (Winham and Armstrong 2015) and likelihood of reporting crimes (Hardy et al. \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2012\u003c/span\u003e), which further threaten security and emotional stability within the community.\u003c/p\u003e \u003cp\u003eSome studies dwell on the law’s health repercussions on the state’s young Hispanics, given their fragility and vulnerability as they navigate through the delicate, challenging period of adolescence. Moreover, Hispanic adolescents are inevitably constantly exposed to social interactions when they attend school. Luo and Escalante (\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) examine the impact of SB 1070 on the mental health, health-risk behaviors, and academic performances of the state’s Hispanic adolescents enrolled in school during the years 2001–2017. Their findings indicate that SB 1070 can be credited for significant increases in the Hispanic youth’s emotional state (probability of feeling sad) and considerable reductions in their physical activity engagements. Their results further establish that male and obese Hispanic students have greater tendencies to externalize the law’s social pressure and thus, would more likely engage in risky health behaviors. A follow-up study explores the law’s physical health repercussion (Escalante, Luo and Taylor, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). This study validates the law’s obesogenic consequences of mutually reinforcing mental and physical health behaviors among young Hispanics in Arizona.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eImmigration Control Mechanisms in Neighboring States\u003c/h3\u003e\n\u003cp\u003eThe federal government launched at least two immigration control mechanisms that state and local governments may choose to adopt. The 1996 Illegal Immigration Reform and Immigrant Responsibility Act includes Section 287(g), which sets up possible collaborations for joint immigration control enforcement between federal immigration authorities and law enforcement officers of interested local governments. Under this agreement, prior to their joint efforts, the latter would receive training from the U.S. Immigration and Customs Enforcement (ICE).\u003c/p\u003e \u003cp\u003eConsenting local governments specify in their 287(g) agreements their choice of the specific mode of immigration control enforcement selected among the following: (a) Jail Enforcement (JE) model that allows local enforcement authorities to conduct interrogation of apprehended immigrants regarding their immigration status; (b) Warrant Service Officer (WSO) model that allows local police to execute arrest warrants; and (c) Task Force (TF) model that allows police officers to question and arrest individuals suspected as undocumented. The TF model is now being phased out as the program uses mostly the JE and WSO models.\u003c/p\u003e \u003cp\u003eAs of 2024, there are 137 local governments with active 287(g) agreements, with 41 jurisdictions that terminated their agreements and have not renewed (ILRC, 2024). Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e presents a tabulation of the 287(g) contracts signed in Arizona and its neighboring (bordering) states. The summary shows that in this regional vicinity, there are only 7 existing agreements in place (5 in Arizona and 2 in Colorado) while the other contiguous states either have expired contracts or did not enlist in the program.\u003c/p\u003e \u003cp\u003eE-Verify is the other federal program that regulates hiring decisions of local employers and ensures that they employ only residents who are legally authorized to work. The work permits are verified through a free online system that contains a comprehensive database of employment data obtained from the employee’s I-9 form (Employment Verification Form) and cross-checked with records from the Department of Homeland Security and Social Security Administration. The E-Verify adoption summary in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e shows that states can implement this employment verification tool at varying degrees. In our sample region, all Arizona public and private businesses are currently mandated to comply with E-Verify, while Colorado and Utah impose a partial mandate that affects only government-related transactions. Notably, California, Nevada, and New Mexico do not have any E-Verify mandates.\u003c/p\u003e\n\u003ch3\u003eEmpirical Evidence on Migration Responses\u003c/h3\u003e\n\u003cp\u003eSeveral studies clarify the prevalence of migratory responses among affected ethnic groups when laws modify social dynamics and economic opportunities in their communities. Bohn, Lofstrom, and Raphael (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2014\u003c/span\u003e) find evidence of a declining population of foreign-born residents, specifically noncitizen Hispanics, attributed to the implementation of the state’s 2007 Legal Arizona Workers Act (LAWA). Migration studies on the effect of the E-Verify mandate, which supplemented the state’s LAWA, confirm significant reductions in the state’s population of non-naturalized citizens (Ellis et al., \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2014\u003c/span\u003e) especially among less-educated and Hispanic immigrants (Amuedo-Dorantes and Lozano \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). Good (\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2013\u003c/span\u003e) provides evidence in U.S. states that adopted state omnibus immigration laws (including E-Verify) of declining population of undocumented immigrants.\u003c/p\u003e \u003cp\u003eThe 287(g) program’s effect on migration decisions is also well supported. Kostandini, Mykerezi, and Escalante (2012) confirm reductions in foreign-born residents in counties that signed 287(g) contracts that, in turn, have adverse effects on wages, production decisions, and business profitability. Watson (\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2013\u003c/span\u003e) clarifies a stronger tendency for foreign-born immigrants, especially among those with college education, to relocate to other states, especially in counties that adopt the former task force model of the 287(g) program. Notably, native born immigrants do not exhibit the same migratory response. O-Neil (2013), however, could not validate a clear, systematic linkage between the 287(g) adoption and foreign-born immigrants’ population share.\u003c/p\u003e \u003cp\u003eEarlier investigations on the SB 1070 effect primarily analyze the non-citizen Hispanics’ share of Arizona’s population. Amuedo-Dorantes and Lozano (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2015\u003c/span\u003e) find null to minimal impact on the share of non-citizen Hispanics in Arizona, including women, after the enactment of SB 1070. Using population data for 2009 to 2012, Sánchez (\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2017\u003c/span\u003e) finds a moderate, short-lived reduction impact (about 10%) of SB 1070 on the proportion of noncitizen Hispanics in Arizona, which eventually vanished several months later. Hoekstra and Orozco-Aleman (\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2017\u003c/span\u003e) analyze activities at the Southern border and find that the flow of undocumented migrants from Mexico to Arizona fell by 30 to 70% after the passing of SB 1070, but there is no significant evidence of emigration back to their home country among those that successfully migrated and were already living in the state.\u003c/p\u003e\n\u003ch3\u003eData Sources\u003c/h3\u003e\n\u003cp\u003eThis study utilizes a couple of data sources to analyze the Hispanics’ migratory response to the previously verified mental and physical health repercussions of Arizona’s state immigration law. These datasets allow for the development of analytical models to examine the possibility of an emigration response by affected Hispanics in the state.\u003c/p\u003e \u003cp\u003eThe first phase of our emigration analysis involves the validation of published evidence on the changing demographic profiles in the state in the wake of SB 1070. In this analysis, we use monthly data from the Current Population Survey (CPS). Following previous studies (Amuedo-Dorantes and Lozano \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2015\u003c/span\u003e), we construct three dependent (outcome) variables: the shares of noncitizen Hispanics, noncitizen Hispanics with higher education levels (high school graduates and with college education), and likely undocumented Hispanics. Following Amuedo-Dorantes and Bansak (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2014\u003c/span\u003e), we define likely undocumented Hispanics as noncitizens, with complete high school education, and younger than 45 years old.\u003c/p\u003e \u003cp\u003eThe latter phase of our analytical model examines the emigration of Hispanics from Arizona into bordering, contiguous states following the SB 1070 enactment. Our primary contention recalls SB 1070’s instrumental effect of evicting undocumented immigrants from the state. If such effect indeed results in SB 1070 effectively driving Hispanics out of Arizona, its bordering states could be popular destinations for relocation based on two arguments: their proximity translating to more convenient, easier relocation logistical arrangements and their relatively more lenient immigration control stance compared to Arizona (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). We use data obtained from the 2006–2012 American Community Survey (ACS) that has a total of 303,881 observations. The ACS polls on the interviewee’s migration status one year prior and provides a count of Hispanics who moved into a state from Arizona and other inter-state relocations. As a result, we could identify Hispanic migrants from Arizona or other states before and during the SB 1070 regime.\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eTable 1\u003c/strong\u003e. \u0026nbsp;287g Agreements and E-Verify Subscription in Arizona and its Contiguous (Bordering) States\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eSources: \u0026nbsp;ILRC, 2024; Equifax, 2023; NCSL, 2015; Capps et al., 2011\u003c/em\u003e\u003c/p\u003e\n\u003cdiv align=\"center\" style=\"margin: 0in 0in 8pt; font-size: 11pt; font-family: Calibri, sans-serif;\"\u003e\n \u003ctable style=\"width: 652.25pt; border-collapse: collapse; border: none;\"\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd rowspan=\"3\" style=\"width: 85.25pt; border: 1pt solid windowtext; padding: 0in 5.4pt; vertical-align: top;\"\u003e\n \u003cp style=\"margin: 0in; font-size: 11pt; font-family: Calibri, sans-serif; text-align: center; line-height: normal;\"\u003e\u003cspan style=\"font-size: 16px; font-family: \u0026quot;Times New Roman\u0026quot;, serif;\"\u003e\u0026nbsp;\u003c/span\u003e\u003c/p\u003e\n \u003cp style=\"margin: 0in; font-size: 11pt; font-family: Calibri, sans-serif; text-align: center; line-height: normal;\"\u003e\u003cspan style=\"font-size: 16px; font-family: \u0026quot;Times New Roman\u0026quot;, serif;\"\u003e\u0026nbsp;\u003c/span\u003e\u003c/p\u003e\n \u003cp style=\"margin: 0in; font-size: 11pt; font-family: Calibri, sans-serif; text-align: center; line-height: normal;\"\u003e\u003cspan style=\"font-size: 16px; font-family: \u0026quot;Times New Roman\u0026quot;, serif;\"\u003eArizona and its Border States\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\u003ctd colspan=\"3\" style=\"width: 297pt; border-top: 1pt solid windowtext; border-right: 1pt solid windowtext; border-bottom: 1pt solid windowtext; border-image: initial; border-left: none; padding: 0in 5.4pt; vertical-align: top;\"\u003e\n \u003cp style=\"margin: 0in; font-size: 11pt; font-family: Calibri, sans-serif; text-align: center; line-height: normal;\"\u003e\u003cspan style=\"font-size: 16px; font-family: \u0026quot;Times New Roman\u0026quot;, serif;\"\u003eCurrent Immigration Controls\u003csup\u003e1\u003c/sup\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\u003ctd colspan=\"2\" style=\"width: 3.75in; border-top: 1pt solid windowtext; border-right: 1pt solid windowtext; border-bottom: 1pt solid windowtext; border-image: initial; border-left: none; padding: 0in 5.4pt; vertical-align: top;\"\u003e\n \u003cp style=\"margin: 0in; font-size: 11pt; font-family: Calibri, sans-serif; text-align: center; line-height: normal;\"\u003e\u003cspan style=\"font-size: 16px; font-family: \u0026quot;Times New Roman\u0026quot;, serif;\"\u003e2010-2011 Immigration Controls\u003csup\u003e1\u003c/sup\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colspan=\"2\" style=\"width: 148.5pt; border-top: none; border-left: none; border-bottom: 1pt solid windowtext; border-right: 1pt solid windowtext; padding: 0in 5.4pt; vertical-align: top;\"\u003e\n \u003cp style=\"margin: 0in; font-size: 11pt; font-family: Calibri, sans-serif; text-align: center; line-height: normal;\"\u003e\u003cspan style=\"font-size: 16px; font-family: \u0026quot;Times New Roman\u0026quot;, serif;\"\u003eJurisdictions with 287g Agreements (2024)\u003csup\u003e2\u003c/sup\u003e\u003c/span\u003e\u003c/p\u003e\n \u003cp style=\"margin: 0in; font-size: 11pt; font-family: Calibri, sans-serif; text-align: center; line-height: normal;\"\u003e\u003cspan style=\"font-size: 16px; font-family: \u0026quot;Times New Roman\u0026quot;, serif;\"\u003e\u0026nbsp;\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\u003ctd rowspan=\"2\" style=\"width: 148.5pt; border-top: none; border-left: none; border-bottom: 1pt solid windowtext; border-right: 1pt solid windowtext; padding: 0in 5.4pt; vertical-align: top;\"\u003e\n \u003cp style=\"margin: 0in; font-size: 11pt; font-family: Calibri, sans-serif; text-align: center; line-height: normal;\"\u003e\u003cspan style=\"font-size: 16px; font-family: \u0026quot;Times New Roman\u0026quot;, serif;\"\u003eE-Verify Subscription (2023)\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\u003ctd rowspan=\"2\" style=\"width: 1.5in; border-top: none; border-left: none; border-bottom: 1pt solid windowtext; border-right: 1pt solid windowtext; padding: 0in 5.4pt; vertical-align: top;\"\u003e\n \u003cp style=\"margin: 0in; font-size: 11pt; font-family: Calibri, sans-serif; text-align: center; line-height: normal;\"\u003e\u003cspan style=\"font-size: 16px; font-family: \u0026quot;Times New Roman\u0026quot;, serif;\"\u003eJurisdictions with 287g Agreements as of August 2010\u003csup\u003e2\u003c/sup\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\u003ctd rowspan=\"2\" style=\"width: 2.25in; border-top: none; border-left: none; border-bottom: 1pt solid windowtext; border-right: 1pt solid windowtext; padding: 0in 5.4pt; vertical-align: top;\"\u003e\n \u003cp style=\"margin: 0in; font-size: 11pt; font-family: Calibri, sans-serif; text-align: center; line-height: normal;\"\u003e\u003cspan style=\"font-size: 16px; font-family: \u0026quot;Times New Roman\u0026quot;, serif;\"\u003eE-Verify Subscription\u0026nbsp;\u003c/span\u003e\u003c/p\u003e\n \u003cp style=\"margin: 0in; font-size: 11pt; font-family: Calibri, sans-serif; text-align: center; line-height: normal;\"\u003e\u003cspan style=\"font-size: 16px; font-family: \u0026quot;Times New Roman\u0026quot;, serif;\"\u003e(As of 2011)\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd style=\"width: 76.5pt; border-top: none; border-left: none; border-bottom: 1pt solid windowtext; border-right: 1pt solid windowtext; padding: 0in 5.4pt; vertical-align: top;\"\u003e\n \u003cp style=\"margin: 0in; font-size: 11pt; font-family: Calibri, sans-serif; text-align: center; line-height: normal;\"\u003e\u003cspan style=\"font-size: 16px; font-family: \u0026quot;Times New Roman\u0026quot;, serif;\"\u003eActive\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\u003ctd style=\"width: 1in; border-top: none; border-left: none; border-bottom: 1pt solid windowtext; border-right: 1pt solid windowtext; padding: 0in 5.4pt; vertical-align: top;\"\u003e\n \u003cp style=\"margin: 0in; font-size: 11pt; font-family: Calibri, sans-serif; text-align: center; line-height: normal;\"\u003e\u003cspan style=\"font-size: 16px; font-family: \u0026quot;Times New Roman\u0026quot;, serif;\"\u003eExpired\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd style=\"width: 85.25pt; border-right: 1pt solid windowtext; border-bottom: 1pt solid windowtext; border-left: 1pt solid windowtext; border-image: initial; border-top: none; padding: 0in 5.4pt; vertical-align: top;\"\u003e\n \u003cp style=\"margin: 0in; font-size: 11pt; font-family: Calibri, sans-serif; text-align: justify; line-height: normal;\"\u003e\u003cspan style=\"font-size: 16px; font-family: \u0026quot;Times New Roman\u0026quot;, serif;\"\u003eArizona\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\u003ctd style=\"width: 76.5pt; border-top: none; border-left: none; border-bottom: 1pt solid windowtext; border-right: 1pt solid windowtext; padding: 0in 5.4pt; vertical-align: top;\"\u003e\n \u003cp style=\"margin: 0in; font-size: 11pt; font-family: Calibri, sans-serif; text-align: center; line-height: normal;\"\u003e\u003cspan style=\"font-size: 16px; font-family: \u0026quot;Times New Roman\u0026quot;, serif;\"\u003e4 JE\u003c/span\u003e\u003c/p\u003e\n \u003cp style=\"margin: 0in; font-size: 11pt; font-family: Calibri, sans-serif; text-align: center; line-height: normal;\"\u003e\u003cspan style=\"font-size: 16px; font-family: \u0026quot;Times New Roman\u0026quot;, serif;\"\u003e1 WSO/TF\u003c/span\u003e\u003c/p\u003e\n \u003cp style=\"margin: 0in; font-size: 11pt; font-family: Calibri, sans-serif; text-align: center; line-height: normal;\"\u003e\u003cspan style=\"font-size: 16px; font-family: \u0026quot;Times New Roman\u0026quot;, serif;\"\u003e\u0026nbsp;\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\u003ctd style=\"width: 1in; border-top: none; border-left: none; border-bottom: 1pt solid windowtext; border-right: 1pt solid windowtext; padding: 0in 5.4pt; vertical-align: top;\"\u003e\n \u003cp style=\"margin: 0in; font-size: 11pt; font-family: Calibri, sans-serif; text-align: center; line-height: normal;\"\u003e\u003cspan style=\"font-size: 16px; font-family: \u0026quot;Times New Roman\u0026quot;, serif;\"\u003e1 JE\u003c/span\u003e\u003c/p\u003e\n \u003cp style=\"margin: 0in; font-size: 11pt; font-family: Calibri, sans-serif; text-align: center; line-height: normal;\"\u003e\u003cspan style=\"font-size: 16px; font-family: \u0026quot;Times New Roman\u0026quot;, serif;\"\u003e2 TF\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\u003ctd style=\"width: 148.5pt; border-top: none; border-left: none; border-bottom: 1pt solid windowtext; border-right: 1pt solid windowtext; padding: 0in 5.4pt; vertical-align: top;\"\u003e\n \u003cp style=\"margin: 0in; font-size: 11pt; font-family: Calibri, sans-serif; text-align: justify; line-height: normal;\"\u003e\u003cspan style=\"font-size: 16px; font-family: \u0026quot;Times New Roman\u0026quot;, serif;\"\u003eAll Government and Private\u0026nbsp;\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\u003ctd style=\"width: 1.5in; border-top: none; border-left: none; border-bottom: 1pt solid windowtext; border-right: 1pt solid windowtext; padding: 0in 5.4pt; vertical-align: top;\"\u003e\n \u003cp style=\"margin: 0in; font-size: 11pt; font-family: Calibri, sans-serif; text-align: center; line-height: normal;\"\u003e\u003cspan style=\"font-size: 16px; font-family: \u0026quot;Times New Roman\u0026quot;, serif;\"\u003e2 JE\u003c/span\u003e\u003c/p\u003e\n \u003cp style=\"margin: 0in; font-size: 11pt; font-family: Calibri, sans-serif; text-align: center; line-height: normal;\"\u003e\u003cspan style=\"font-size: 16px; font-family: \u0026quot;Times New Roman\u0026quot;, serif;\"\u003e1 TF\u003c/span\u003e\u003c/p\u003e\n \u003cp style=\"margin: 0in; font-size: 11pt; font-family: Calibri, sans-serif; text-align: center; line-height: normal;\"\u003e\u003cspan style=\"font-size: 16px; font-family: \u0026quot;Times New Roman\u0026quot;, serif;\"\u003e6 JE-TF\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\u003ctd style=\"width: 2.25in; border-top: none; border-left: none; border-bottom: 1pt solid windowtext; border-right: 1pt solid windowtext; padding: 0in 5.4pt; vertical-align: top;\"\u003e\n \u003cp style=\"margin: 0in; font-size: 11pt; font-family: Calibri, sans-serif; text-align: justify; line-height: normal;\"\u003e\u003cspan style=\"font-size: 16px; font-family: \u0026quot;Times New Roman\u0026quot;, serif;\"\u003eAll Government and Private\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd style=\"width: 85.25pt; border-right: 1pt solid windowtext; border-bottom: 1pt solid windowtext; border-left: 1pt solid windowtext; border-image: initial; border-top: none; padding: 0in 5.4pt; vertical-align: top;\"\u003e\n \u003cp style=\"margin: 0in; font-size: 11pt; font-family: Calibri, sans-serif; text-align: justify; line-height: normal;\"\u003e\u003cspan style=\"font-size: 16px; font-family: \u0026quot;Times New Roman\u0026quot;, serif;\"\u003eCalifornia\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\u003ctd style=\"width: 76.5pt; border-top: none; border-left: none; border-bottom: 1pt solid windowtext; border-right: 1pt solid windowtext; background: rgb(168, 208, 141); padding: 0in 5.4pt; vertical-align: top;\"\u003e\n \u003cp style=\"margin: 0in; font-size: 11pt; font-family: Calibri, sans-serif; text-align: center; line-height: normal;\"\u003e\u003cspan style=\"font-size: 16px; font-family: \u0026quot;Times New Roman\u0026quot;, serif; color: black;\"\u003eNone\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\u003ctd style=\"width: 1in; border-top: none; border-left: none; border-bottom: 1pt solid windowtext; border-right: 1pt solid windowtext; padding: 0in 5.4pt; vertical-align: top;\"\u003e\n \u003cp style=\"margin: 0in; font-size: 11pt; font-family: Calibri, sans-serif; text-align: center; line-height: normal;\"\u003e\u003cspan style=\"font-size: 16px; font-family: \u0026quot;Times New Roman\u0026quot;, serif;\"\u003e3 JE\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\u003ctd style=\"width: 148.5pt; border-top: none; border-left: none; border-bottom: 1pt solid windowtext; border-right: 1pt solid windowtext; background: rgb(168, 208, 141); padding: 0in 5.4pt; vertical-align: top;\"\u003e\n \u003cp style=\"margin: 0in; font-size: 11pt; font-family: Calibri, sans-serif; text-align: justify; line-height: normal;\"\u003e\u003cspan style=\"font-size: 16px; font-family: \u0026quot;Times New Roman\u0026quot;, serif; color: black;\"\u003eNo State E-Verify\u0026nbsp;\u003c/span\u003e\u003c/p\u003e\n \u003cp style=\"margin: 0in; font-size: 11pt; font-family: Calibri, sans-serif; text-align: justify; line-height: normal;\"\u003e\u003cspan style=\"font-size: 16px; font-family: \u0026quot;Times New Roman\u0026quot;, serif; color: black;\"\u003e(Forbids local E-Verify)\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\u003ctd style=\"width: 1.5in; border-top: none; border-left: none; border-bottom: 1pt solid windowtext; border-right: 1pt solid windowtext; padding: 0in 5.4pt; vertical-align: top;\"\u003e\n \u003cp style=\"margin: 0in; font-size: 11pt; font-family: Calibri, sans-serif; text-align: center; line-height: normal;\"\u003e\u003cspan style=\"font-size: 16px; font-family: \u0026quot;Times New Roman\u0026quot;, serif;\"\u003e4 JE\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\u003ctd style=\"width: 2.25in; border-top: none; border-left: none; border-bottom: 1pt solid windowtext; border-right: 1pt solid windowtext; background: rgb(168, 208, 141); padding: 0in 5.4pt; vertical-align: top;\"\u003e\n \u003cp style=\"margin: 0in; font-size: 11pt; font-family: Calibri, sans-serif; text-align: justify; line-height: normal;\"\u003e\u003cspan style=\"font-size: 16px; font-family: \u0026quot;Times New Roman\u0026quot;, serif; color: black;\"\u003eNo State E-Verify\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd style=\"width: 85.25pt; border-right: 1pt solid windowtext; border-bottom: 1pt solid windowtext; border-left: 1pt solid windowtext; border-image: initial; border-top: none; padding: 0in 5.4pt; vertical-align: top;\"\u003e\n \u003cp style=\"margin: 0in; font-size: 11pt; font-family: Calibri, sans-serif; text-align: justify; line-height: normal;\"\u003e\u003cspan style=\"font-size: 16px; font-family: \u0026quot;Times New Roman\u0026quot;, serif;\"\u003eColorado\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\u003ctd style=\"width: 76.5pt; border-top: none; border-left: none; border-bottom: 1pt solid windowtext; border-right: 1pt solid windowtext; padding: 0in 5.4pt; vertical-align: top;\"\u003e\n \u003cp style=\"margin: 0in; font-size: 11pt; font-family: Calibri, sans-serif; text-align: center; line-height: normal;\"\u003e\u003cspan style=\"font-size: 16px; font-family: \u0026quot;Times New Roman\u0026quot;, serif;\"\u003e2 JE\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\u003ctd style=\"width: 1in; border-top: none; border-left: none; border-bottom: 1pt solid windowtext; border-right: 1pt solid windowtext; padding: 0in 5.4pt; vertical-align: top;\"\u003e\n \u003cp style=\"margin: 0in; font-size: 11pt; font-family: Calibri, sans-serif; text-align: center; line-height: normal;\"\u003e\u003cspan style=\"font-size: 16px; font-family: \u0026quot;Times New Roman\u0026quot;, serif;\"\u003e1 JE\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\u003ctd style=\"width: 148.5pt; border-top: none; border-left: none; border-bottom: 1pt solid windowtext; border-right: 1pt solid windowtext; padding: 0in 5.4pt; vertical-align: top;\"\u003e\n \u003cp style=\"margin: 0in; font-size: 11pt; font-family: Calibri, sans-serif; text-align: justify; line-height: normal;\"\u003e\u003cspan style=\"font-size: 16px; font-family: \u0026quot;Times New Roman\u0026quot;, serif;\"\u003eState and Local Government (Contractors only)\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\u003ctd style=\"width: 1.5in; border-top: none; border-left: none; border-bottom: 1pt solid windowtext; border-right: 1pt solid windowtext; padding: 0in 5.4pt; vertical-align: top;\"\u003e\n \u003cp style=\"margin: 0in; font-size: 11pt; font-family: Calibri, sans-serif; text-align: center; line-height: normal;\"\u003e\u003cspan style=\"font-size: 16px; font-family: \u0026quot;Times New Roman\u0026quot;, serif;\"\u003e1 JE\u003c/span\u003e\u003c/p\u003e\n \u003cp style=\"margin: 0in; font-size: 11pt; font-family: Calibri, sans-serif; text-align: center; line-height: normal;\"\u003e\u003cspan style=\"font-size: 16px; font-family: \u0026quot;Times New Roman\u0026quot;, serif;\"\u003e1 TF\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\u003ctd style=\"width: 2.25in; border-top: none; border-left: none; border-bottom: 1pt solid windowtext; border-right: 1pt solid windowtext; padding: 0in 5.4pt; vertical-align: top;\"\u003e\n \u003cp style=\"margin: 0in; font-size: 11pt; font-family: Calibri, sans-serif; text-align: justify; line-height: normal;\"\u003e\u003cspan style=\"font-size: 16px; font-family: \u0026quot;Times New Roman\u0026quot;, serif;\"\u003eState and Local Government (Contractors only)\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd style=\"width: 85.25pt; border-right: 1pt solid windowtext; border-bottom: 1pt solid windowtext; border-left: 1pt solid windowtext; border-image: initial; border-top: none; padding: 0in 5.4pt; vertical-align: top;\"\u003e\n \u003cp style=\"margin: 0in; font-size: 11pt; font-family: Calibri, sans-serif; text-align: justify; line-height: normal;\"\u003e\u003cspan style=\"font-size: 16px; font-family: \u0026quot;Times New Roman\u0026quot;, serif;\"\u003eNevada\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\u003ctd style=\"width: 76.5pt; border-top: none; border-left: none; border-bottom: 1pt solid windowtext; border-right: 1pt solid windowtext; background: rgb(168, 208, 141); padding: 0in 5.4pt; vertical-align: top;\"\u003e\n \u003cp style=\"margin: 0in; font-size: 11pt; font-family: Calibri, sans-serif; text-align: center; line-height: normal;\"\u003e\u003cspan style=\"font-size: 16px; font-family: \u0026quot;Times New Roman\u0026quot;, serif; color: black;\"\u003eNone\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\u003ctd style=\"width: 1in; border-top: none; border-left: none; border-bottom: 1pt solid windowtext; border-right: 1pt solid windowtext; padding: 0in 5.4pt; vertical-align: top;\"\u003e\n \u003cp style=\"margin: 0in; font-size: 11pt; font-family: Calibri, sans-serif; text-align: center; line-height: normal;\"\u003e\u003cspan style=\"font-size: 16px; font-family: \u0026quot;Times New Roman\u0026quot;, serif;\"\u003e3 JE\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\u003ctd style=\"width: 148.5pt; border-top: none; border-left: none; border-bottom: 1pt solid windowtext; border-right: 1pt solid windowtext; background: rgb(168, 208, 141); padding: 0in 5.4pt; vertical-align: top;\"\u003e\n \u003cp style=\"margin: 0in; font-size: 11pt; font-family: Calibri, sans-serif; text-align: justify; line-height: normal;\"\u003e\u003cspan style=\"font-size: 16px; font-family: \u0026quot;Times New Roman\u0026quot;, serif; color: black;\"\u003eNo State E-Verify\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\u003ctd style=\"width: 1.5in; border-top: none; border-left: none; border-bottom: 1pt solid windowtext; border-right: 1pt solid windowtext; padding: 0in 5.4pt; vertical-align: top;\"\u003e\n \u003cp style=\"margin: 0in; font-size: 11pt; font-family: Calibri, sans-serif; text-align: center; line-height: normal;\"\u003e\u003cspan style=\"font-size: 16px; font-family: \u0026quot;Times New Roman\u0026quot;, serif;\"\u003e1 JE\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\u003ctd style=\"width: 2.25in; border-top: none; border-left: none; border-bottom: 1pt solid windowtext; border-right: 1pt solid windowtext; background: rgb(168, 208, 141); padding: 0in 5.4pt; vertical-align: top;\"\u003e\n \u003cp style=\"margin: 0in; font-size: 11pt; font-family: Calibri, sans-serif; text-align: justify; line-height: normal;\"\u003e\u003cspan style=\"font-size: 16px; font-family: \u0026quot;Times New Roman\u0026quot;, serif; color: black;\"\u003eNo State E-Verify\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd style=\"width: 85.25pt; border-right: 1pt solid windowtext; border-bottom: 1pt solid windowtext; border-left: 1pt solid windowtext; border-image: initial; border-top: none; padding: 0in 5.4pt; vertical-align: top;\"\u003e\n \u003cp style=\"margin: 0in; font-size: 11pt; font-family: Calibri, sans-serif; text-align: justify; line-height: normal;\"\u003e\u003cspan style=\"font-size: 16px; font-family: \u0026quot;Times New Roman\u0026quot;, serif;\"\u003eNew Mexico\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\u003ctd colspan=\"2\" style=\"width: 148.5pt; border-top: none; border-left: none; border-bottom: 1pt solid windowtext; border-right: 1pt solid windowtext; background: rgb(168, 208, 141); padding: 0in 5.4pt; vertical-align: top;\"\u003e\n \u003cp style=\"margin: 0in; font-size: 11pt; font-family: Calibri, sans-serif; text-align: center; line-height: normal;\"\u003e\u003cspan style=\"font-size: 16px; font-family: \u0026quot;Times New Roman\u0026quot;, serif; color: black;\"\u003eNone\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\u003ctd style=\"width: 148.5pt; border-top: none; border-left: none; border-bottom: 1pt solid windowtext; border-right: 1pt solid windowtext; background: rgb(168, 208, 141); padding: 0in 5.4pt; vertical-align: top;\"\u003e\n \u003cp style=\"margin: 0in; font-size: 11pt; font-family: Calibri, sans-serif; text-align: justify; line-height: normal;\"\u003e\u003cspan style=\"font-size: 16px; font-family: \u0026quot;Times New Roman\u0026quot;, serif; color: black;\"\u003eNo State E-Verify\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\u003ctd style=\"width: 1.5in; border-top: none; border-left: none; border-bottom: 1pt solid windowtext; border-right: 1pt solid windowtext; padding: 0in 5.4pt; vertical-align: top;\"\u003e\n \u003cp style=\"margin: 0in; font-size: 11pt; font-family: Calibri, sans-serif; text-align: center; line-height: normal;\"\u003e\u003cspan style=\"font-size: 16px; font-family: \u0026quot;Times New Roman\u0026quot;, serif;\"\u003e1 JE\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\u003ctd style=\"width: 2.25in; border-top: none; border-left: none; border-bottom: 1pt solid windowtext; border-right: 1pt solid windowtext; background: rgb(168, 208, 141); padding: 0in 5.4pt; vertical-align: top;\"\u003e\n \u003cp style=\"margin: 0in; font-size: 11pt; font-family: Calibri, sans-serif; text-align: justify; line-height: normal;\"\u003e\u003cspan style=\"font-size: 16px; font-family: \u0026quot;Times New Roman\u0026quot;, serif; color: black;\"\u003eNo State E-Verify\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd style=\"width: 85.25pt; border-right: 1pt solid windowtext; border-bottom: 1pt solid windowtext; border-left: 1pt solid windowtext; border-image: initial; border-top: none; padding: 0in 5.4pt; vertical-align: top;\"\u003e\n \u003cp style=\"margin: 0in; font-size: 11pt; font-family: Calibri, sans-serif; text-align: justify; line-height: normal;\"\u003e\u003cspan style=\"font-size: 16px; font-family: \u0026quot;Times New Roman\u0026quot;, serif;\"\u003eUtah\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\u003ctd colspan=\"2\" style=\"width: 148.5pt; border-top: none; border-left: none; border-bottom: 1pt solid windowtext; border-right: 1pt solid windowtext; background: rgb(168, 208, 141); padding: 0in 5.4pt; vertical-align: top;\"\u003e\n \u003cp style=\"margin: 0in; font-size: 11pt; font-family: Calibri, sans-serif; text-align: center; line-height: normal;\"\u003e\u003cspan style=\"font-size: 16px; font-family: \u0026quot;Times New Roman\u0026quot;, serif; color: black;\"\u003eNone`\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\u003ctd style=\"width: 148.5pt; border-top: none; border-left: none; border-bottom: 1pt solid windowtext; border-right: 1pt solid windowtext; padding: 0in 5.4pt; vertical-align: top;\"\u003e\n \u003cp style=\"margin: 0in; font-size: 11pt; font-family: Calibri, sans-serif; text-align: justify; line-height: normal;\"\u003e\u003cspan style=\"font-size: 16px; font-family: \u0026quot;Times New Roman\u0026quot;, serif;\"\u003eState and Local Government (Agencies and Contractors)\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\u003ctd style=\"width: 1.5in; border-top: none; border-left: none; border-bottom: 1pt solid windowtext; border-right: 1pt solid windowtext; padding: 0in 5.4pt; vertical-align: top;\"\u003e\n \u003cp style=\"margin: 0in; font-size: 11pt; font-family: Calibri, sans-serif; text-align: center; line-height: normal;\"\u003e\u003cspan style=\"font-size: 16px; font-family: \u0026quot;Times New Roman\u0026quot;, serif;\"\u003e2 JE\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\u003ctd style=\"width: 2.25in; border-top: none; border-left: none; border-bottom: 1pt solid windowtext; border-right: 1pt solid windowtext; padding: 0in 5.4pt; vertical-align: top;\"\u003e\n \u003cp style=\"margin: 0in; font-size: 11pt; font-family: Calibri, sans-serif; text-align: justify; line-height: normal;\"\u003e\u003cspan style=\"font-size: 16px; font-family: \u0026quot;Times New Roman\u0026quot;, serif;\"\u003eAll Government and Private\u003c/span\u003e\u003c/p\u003e\n \u003cp style=\"margin: 0in; font-size: 11pt; font-family: Calibri, sans-serif; text-align: justify; line-height: normal;\"\u003e\u003cspan style=\"font-size: 16px; font-family: \u0026quot;Times New Roman\u0026quot;, serif;\"\u003e(Allows private employers to employ undocumented aliens with UT Guest Worker Permit, contingent on federal waiver)\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003eNote: \u0026nbsp;\u003csup\u003e1\u003c/sup\u003e Green-shaded cells indicate the absence of any active immigration control mandate under the program.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003csup\u003e2\u003c/sup\u003e\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e287(g) contracts stipulate the following specific immigration control mechanisms agreed upon by the contracting local government and ICE: \u0026nbsp;Jail Enforcement (JE), Task Force (TF), Warrant Service Officer (WSO)\u003c/p\u003e"},{"header":"Analytical Models","content":"\u003ch2\u003eSynthetic Control Method (SCM)\u003c/h2\u003e\u003cp\u003eThe first phase of our analytical model employs the SCM framework, which is an appropriate analytical tool for investigating the impact of an “event” or a single-unit treatment (Abadie, Diamond, and Hainmueller, \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2010\u003c/span\u003e). Through a data-driven algorithm, a counterfactual unit (herein referred to as the control group) is constructed ensuring that this unit shares similar pre-treatment trends in the outcome variables with the unit affected by the “event” (the treated unit). SCM ensures parallel trends between the treated and control units during the period prior to the occurrence of the event (pre-treatment) period. This is accomplished by choosing a weighted combination of control states that will collectively form the “synthetic control unit” that shares similar pre-treatment characteristics and conditions as those present in the real treated unit.\u003c/p\u003e\u003cp\u003eOur analysis uses the state level as the unit of observation. The treated unit is coded as j = 0 and candidate states for the synthetic control group are coded as j=(1,2,…,J).\u003c/p\u003e\u003cp\u003eIn this empirical framework, the enactment of SB 1070 law is the “event” of interest. The real Arizona state is our base treated state. The “Synthetic Arizona” control group is collectively built around other states that yielded positive weights in the data-driven process of SCM. Weights are obtained through the minimization of the value of the distance, derived as follows\u003c/p\u003e\u003cdiv id=\"Equa\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equa\" name=\"EquationSource\"\u003e\n$$\\:\\left|\\right|\\:{X}_{0}-\\:{X}_{1}W\\left|\\right|=\\sqrt{{\\left({X}_{0}-\\:{X}_{1}W\\right)}^{{\\prime\\:}}V\\left({X}_{0}-\\:{X}_{1}W\\right)}\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\left(1\\right)\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:$$\u003c/div\u003e\u003c/div\u003e\u003cp\u003ewhere \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{X}_{0}\\)\u003c/span\u003e\u003c/span\u003e is a \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:k\\times\\:1\\)\u003c/span\u003e\u003c/span\u003e vector capturing the characteristics of Arizona in the pre-treatment period and \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{X}_{1}\\)\u003c/span\u003e\u003c/span\u003e is a \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:k\\times\\:j\\)\u003c/span\u003e\u003c/span\u003e vector applies to the control units. Both \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{X}_{0}\\)\u003c/span\u003e\u003c/span\u003e and \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{X}_{1}\\)\u003c/span\u003e\u003c/span\u003e include the outcomes of interest as well as independent variables that may affect outcomes in each state. The weights that are assigned to states in the donor (mother) pool of state observations are positive and sum up to one. A vector of optimal weights to each state \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{W}^{\\text{*}}=({w}_{1},\\:\\:{w}_{2},\\dots\\:,{w}_{J})\\)\u003c/span\u003e\u003c/span\u003e is generated and the states with non-zero weights are singled out to construct the collective synthetic Arizona group that best approximates the real Arizona case.\u003c/p\u003e\u003cp\u003eEach covariate used to control for each of the outcomes is assigned a weight. The importance of each covariate in the X vector in predicting any change in each of the outcome variables is indicated by generating a k×k vector V. The covariates chosen for predicting a specific outcome are aggregated at the state level.\u003c/p\u003e\u003cp\u003eIn this analysis, the synthetic Arizona unit is constructed using a set of covariates that include the undocumented immigrants’ and Hispanic shares in the state’s population, unemployment rate, 287(g) participation, E-Verify status, real GDP per capita, and lagged outcome variables from the pre-treatment period. In addition, real dollar values of per capital state expenditures for education, health, and overall government spending are also included in these estimations.\u003c/p\u003e\u003cp\u003eThus, for each outcome variable, there will be a different composition of the synthetic Arizona unit as in every estimation for each outcome variable, the synthetic control unit will include only those states with non-zero weights. The unique composition of synthetic Arizona states in each outcome ensures that given the varied emphases of the outcome variables (overall immigration profile, educational attainment of non-immigrants, and concentration of undocumented population), every constructed synthetic control unit closely resembles the treated state’s conditions. The only differentiating factor between such constructed synthetic Arizona clusters and the real Arizona case is the latter’s experience of this model’s event of interest, that is the enactment of SB1070 legislation, which is non-existent in the “synthetic Arizona” states.\u003c/p\u003e\u003ch3\u003eDifferences–in-Difference (DID) Estimation\u003c/h3\u003e\u003cp\u003eIn our DID model, the adoption of SB 1070 in Arizona is treated as a quasi-natural experiment. Our DID model is an extension of the SCM migration analysis and is designed to capture Hispanic migration to adjacent states. For this analysis, we construct a DID regression with the following specification\u003c/p\u003e\u003cdiv id=\"Equ1\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equ1\" name=\"EquationSource\"\u003e\n$$\\:{Migrant-AZHisp}_{ist}=\\alpha\\:+\\beta\\:{SB1070\\_adjacent}_{ist}+\\gamma\\:{X}_{ist}^{{\\prime\\:}}+{\\theta\\:}_{s}+{\\mu\\:}_{t}+{\\epsilon\\:}_{ist}$$\u003c/div\u003e\u003cdiv class=\"EquationNumber\"\u003e2\u003c/div\u003e\u003c/div\u003e\u003cp\u003ewhere \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{Migrant-AZHisp}_{ist}\\)\u003c/span\u003e\u003c/span\u003e equals one if an individual is identified as a Hispanic migrant from Arizona, zero if a Hispanic migrant is from other states.\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\:{SB1070\\_adjacent}_{ist}\\)\u003c/span\u003e\u003c/span\u003e equals one if a migrant is in one of Arizona’s bordering states (California, Nevada, Colorado, New Mexico, and Utah) after SB 1070. \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{X}_{ist}^{{\\prime\\:}}\\)\u003c/span\u003e\u003c/span\u003e includes a series of demographic and state level covariates. \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{\\theta\\:}_{s}\\)\u003c/span\u003e\u003c/span\u003e and \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{\\mu\\:}_{t}\\)\u003c/span\u003e\u003c/span\u003e are state and year fixed effects. \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{\\epsilon\\:}_{ist}\\)\u003c/span\u003e\u003c/span\u003e is the error term. \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\beta\\:\\)\u003c/span\u003e\u003c/span\u003e measures if bordering states would experience a higher likelihood of seeing more Hispanic migrants from Arizona after SB 1070.\u003c/p\u003e\u003cp\u003eThe demographic covariates include gender, age, marital status, education, employment status, family size, and other immigration-related policies such as E-verify mandates, and the 287(g) contracts. Since the data set does not provide county identifiers, the 287(g) variable is controlled at the state level.\u003c/p\u003e\u003cp\u003eBusiness cycle covariates include the state-level unemployment rate, real GDP per capita, real government expenditure per capita, and the employment rate specific to the construction sector. The construction industry is included in the analysis as this sector usually attracts foreign workers and usually holds hiring advantages given its more favorable compensation structure (Luo and Escalante, 2017).\u003c/p\u003e"},{"header":"Hispanics Migration Response Results","content":"\u003ch2\u003eDescriptive results\u003c/h2\u003e\u003cp\u003eFigure \u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e shows the comparative trends of the shares of noncitizen Hispanics, more highly educated noncitizen Hispanics, and likely undocumented Hispanics in Arizona and California, which account for the two highest concentrations of undocumented immigrants in the region in 2010 and 2011 (CMS, 2022). California is the logical choice for the comparative analysis since around SB 1070’s enactment, it accounts for about 77 percent and almost 25 percent of all undocumented immigrants in the region and the entire country, respectively (CMS, 2022).\u003c/p\u003e\u003cp\u003eAs can be seen from the plots, we do not find substantial disparities of the share trends between the two states, thus suggesting that SB 1070 has limited impact on altering trends in Hispanic population shares in Arizona. To further corroborate our preliminary findings, we use SCM analytical techniques to examine if these shares decrease due to SB 1070. In the SCM analysis, we will control for other covariates and validate the parallel pre-trend condition.\u003c/p\u003e\u003ch2\u003eSynthetic control method results\u003c/h2\u003e\u003cp\u003eFigure \u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e features the SCM estimates for the impact of SB 1070 on the share of noncitizen Hispanics. The covariates included are state level unemployment rate, state level unemployment rate in construction, real GDP per capita, real government expenditure per capita, the share of population in agriculture, the share of population in construction, mean Hispanics education level, mean Hispanics age, and lagged share of noncitizen Hispanics. The states that are assigned positive weights for constructing a synthetic Arizona for the share of noncitizen Hispanics are: California (0.305), Iowa (0.306), and Nevada (0.389). The plot on the right side shows the permutation test results indicating the significance level.\u003c/p\u003e\u003cp\u003eFigure \u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e shows that the parallel pre-trend condition is satisfied as both the real and synthetic Arizona lines consistently converge during pre-SB 1070 (2010) period. Subsequently, the share of noncitizen Hispanics did not significantly change after 2010. As can be gleaned from the plots, there is no clear deviation between Arizona’s (blue) and synthetic Arizona’s (red) trend lines. Moreover, the permutation test graph on the right presents the same conclusion as Arizona’s line lies well among other placebo lines.\u003c/p\u003e\u003cp\u003eThe analysis is then extended to consider a subpopulation of advantaged, more educated noncitizen Hispanics (those who are either high school graduates or have college education). The states with positive weights that comprise the synthetic Arizona group are Alabama (0.037), Florida (0.239), Georgia (0.187), California (0.11), Nevada (0.154), New Mexico (0.024), Texas (0.191). and Utah (0.06).\u003c/p\u003e\u003cp\u003eThe findings of the SCM graph on the left and the permutation graph on the right (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e) indicate that there is no significant gap between Arizona and synthetic Arizona, thus suggesting the absence of an impact of SB 1070 on the population share of advantaged noncitizen Hispanics in Arizona.\u003c/p\u003e\u003cp\u003eIn the second extension of the analysis, we analyze the law’s migratory effect on disadvantaged Hispanics with lower education and younger age (and theoretically tagged as likely undocumented residents). The states assigned positive weights for constructing the synthetic Arizona are California (0.394), Indiana (0.491), and Nevada (0.116). The results presented in Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e validate the same conclusion deduced from Figs.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e and \u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e, confirming the same lack of significant evidence of any notable decrease in the share of likely undocumented Hispanics after SB 1070. The permutation test graph also shows no significant difference between Arizona’s line and other placebo lines.\u003c/p\u003e\u003cp\u003eThe preliminary (descriptive plots) evidence, together with the SCM findings, suggest that SB 1070 did not cause a notably large-scale emigration from Arizona among the Hispanic population. Although Allen and McNeely (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2017\u003c/span\u003e) and Bohn, Lofstrom, and Raphael (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2014\u003c/span\u003e) contend that low-skilled noncitizen Latinos are more likely to migrate from states with omnibus laws, our findings suggest otherwise in relation to the SB 1070 enactment. Our findings instead support the contention of Sadowski-Smith and Li (\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2016\u003c/span\u003e), who assert that there possibly would not be wide distinctions in migration decisions made by both low and highly skilled immigrants.\u003c/p\u003e\u003ch2\u003eAdjacent states migration results\u003c/h2\u003e\u003cp\u003eThe DID estimation results for the Hispanic’s migration decisions are presented in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e. The DID analysis focuses on the emigration of Hispanics from Arizona to its neighboring (contiguous) states, given proximity and immigration environment considerations.\u003c/p\u003e\u003cdiv class=\"gridtable\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eEstimates of SB 1070 impact on Arizona migrants in bordering states.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e\u003ccolgroup cols=\"4\"\u003e\u003c/colgroup\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003eMigrants from Arizona\u003c/p\u003e \u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNoncitizen Hispanics\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAdvantaged (Educated) Noncitizen Hispanics\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eDisadvantaged (Likely Undocumented) Noncitizen Hispanics\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSB 1070\u003c/p\u003e \u003cp\u003ecoefficient (standard error)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.0007\u003c/p\u003e \u003cp\u003e(0.0010)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.0011\u003c/p\u003e \u003cp\u003e(0.0008)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.0011\u003c/p\u003e \u003cp\u003e(0.0008)\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDemographic covariates\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBusiness cycle covariates\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eN\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e303,364\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e303,881\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e303,881\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"4\"\u003e\u003cem\u003eNotes: The estimates are obtained by the linear probability model. Demographic covariates included are gender, age, marital status, education, employment status, family size, and other immigration policy variables. Business cycle covariates included are state unemployment rate, state unemployment rate in construction, real GDP per capita, real government expenditure per capita. Regression coefficients are weighted, and robust standard errors are clustered at the state level. * p \u0026lt; 0.1, **p \u0026lt; 0.05, and ***p \u0026lt; 0.01.\u003c/em\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003cp\u003eBased on the summary in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, the coefficients for the SB 1070 variable are consistently insignificant in all three versions of the model. These results corroborate the trends validated in our earlier analyses. Both DID and SCM models provide compelling evidence on decisions of Arizona’s noncitizen Hispanics to forego migration to a neighboring state as an escape mechanism as SB 1070 has modified their in-state social environment.\u003c/p\u003e\u003cp\u003eIdeally, the states that border around Arizona offer a logical residential and employment choice for Arizona’s Hispanics. Around the time of SB 1070’s enactment, four of the five neighboring states have at most only two counties that signed 287(g) contracts (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). These contracts usually are concentrated in the jurisdiction of their capital cities, thus leaving the rest of the state unregulated (Capps et al, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2011\u003c/span\u003e). In contrast, Arizona had 9 active 287(g) contracts in force at that time.\u003c/p\u003e\u003cp\u003eThe E-Verify mechanism, which poses a significant economic restraint for likely undocumented Hispanics (model 3), had not been enforced widely in the region during the time of the SB 1070 enactment. As of 2011, three states (California, Nevada, and New Mexico) did not employ E-Verify at all in their hiring activities (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Colorado and Utah had partial E-Verify models that affected only state and local government employment decisions. The latter even allowed the employment of undocumented residents who were holders of their state guest worker permit. Thus, the work environments in these bordering states were more conducive to undocumented immigrants’ pursuit of employment opportunities compared to Arizona’s E-Verify mandate that applied to all government and private businesses.\u003c/p\u003e\u003cp\u003eMoreover, two neighboring states (New Mexico and Utah) offered an additional benefit for undocumented immigrants as they (along with Washington) were the only states in the country at that time to allow such immigrants to obtain driver’s licenses (Luo and Escalante, 2024). Nevada and Colorado would eventually join this pack in 2014, with California chiming in two years later.\u003c/p\u003e\u003cp\u003eOverall, the neighboring states’ immigration stances were relatively more accommodating in both social and economic terms than the Arizona residence option. However, this study’s findings emphasize the Hispanics’ decisions to instead remain in Arizona despite the state’s enforcement of multiple immigration control mechanisms.\u003c/p\u003e"},{"header":"Summary and Conclusions","content":"\u003cp\u003eThis study provides empirical evidence on possible migratory responses of legal and documented Hispanic residents in Arizona may adopt as a possible mechanism for coping with the social repercussions, even if they are arguably unintended, of the state’s immigration law (SB 1070). Earlier studies have clearly shown that such negative “racial profiling “consequences of the state law have led to serious adverse effects on Hispanic mental and physical health conditions. When faced with such adversities, we surmise that Hispanic residents may consider migration to other states with relatively more lenient immigration regulations. A cursory analysis of Arizona’s neighboring states reveals potentials for social and economic assimilation of Hispanic residents.\u003c/p\u003e\u003cp\u003eNotwithstanding the bordering states’ leniency towards certain immigration issues, our results indicate a general lack of significant migratory response of Hispanics in Arizona. This could imply that the state’s Hispanic residents still choose to assert their rights as legal residents of the state, a status acquired over many years of satisfying procedural and documentary requirements prescribed by the country’s naturalization process.\u003c/p\u003e\u003cp\u003eAs this study establishes the Hispanics’ firm claim on legally acquired residence in the state, the inevitable and unintended mental and physical health consequences of racial profiling and social ostracism persist. These unfortunate repercussions of the law should not be ignored, especially by local and federal authorities who have the jurisdiction and capability to introduce effective reforms. The mental and physical health of vulnerable populations, especially Hispanic youths, must be given broader attention by the whole society as well as policymakers. After the unsuccessful attempts of the Department of Justice to tone down several provisions of Arizona’s state immigration policies, current policies must now be geared towards more significant damage control efforts. Local and federal policymakers should consider redirecting resources to launching more effective, efficient mechanisms to help Hispanics with their mental and physical health issues. Moreover, legislators should formulate social engagement and modification policies aimed at neutralizing the negative elements of the alienating, harmful social environment created under the SB 1070 regime.\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eC.E. wrote most of the main manuscript text. T.L. took care of the analytical models (DID and SCM). C.E. and T.L. both prepared tables and analyzed the results. Both authors reviewed the manuscript and prepared it for submission.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eData analyzed and reported in the manuscript can be accessed athttps://drive.google.com/file/d/1K3Aq9stw6Jzb_pLel24TCxKfvL_hT8Qm/view\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAbadie, A., Diamond, A., \u0026amp; Hainmueller, J. 2010. 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Nativity, not acculturation, predicts SNAP usage among low-income Hispanics with food insecurity. Journal of Hunger \u0026amp; Environmental Nutrition, 10(2), pp.202-213.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-5759327/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5759327/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"This study draws upon assertions that Arizona’s stringent state immigration law has created a hostile social environment for Hispanics due to the law’s unintended racial profiling consequences that have serious spillover effects affecting even documented immigrants and American-born citizens of Hispanic ethnicity. Recent evidence indicates the law’s serious repercussions on the mental and physical health conditions especially among the state’s Hispanic adolescents. This study determines whether in the face of such adverse social environment, affected Hispanic families have considered relocation and migration to its contiguous neighboring states. The border state emigration argument is explored as a logical alternative due proximity and relatively more lenient immigration environment considerations. We employed differences-in-difference and synthetic control method analytical techniques to discern Hispanics’ migration trends leaving Arizona to move into bordering, contiguous states. This study’s findings indicate the lack of significant migratory response of Hispanics in Arizona, thereby suggesting that noncitizen Hispanics instead choose to remain in the state as those with legal residence status assert their immigration residential rights. Given such compelling evidence, policy attention should then be geared towards more significant damage control efforts, perhaps by redirecting resources to launch effective, efficient mechanisms to alleviate Hispanics’ mental and physical health issues. ","manuscriptTitle":"Hispanic Border State Emigration Response to Stricter Immigration Control","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-01-08 05:28:57","doi":"10.21203/rs.3.rs-5759327/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"1d204647-9597-4207-9906-3d1e0e399fea","owner":[],"postedDate":"January 8th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-02-11T05:23:14+00:00","versionOfRecord":[],"versionCreatedAt":"2025-01-08 05:28:57","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-5759327","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-5759327","identity":"rs-5759327","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}