1The likelihood of migrating illegally from Mexico to the United States rises when there are other family members already residing in the country, many of whom might be legal (Massey et al.2002).
2For instance, Cortés (2008) shows that the low-skilled immigration wave of the 1980-2000 resulted in an important reduction in the price of an agglomerate of non-traded goods and services by a city average of 9-11 percent.
3Another state-level initiative we tried examining was omnibus immigration bills. Starting with Arizona’s SB1070 in 2010, six states have enacted omnibus immigration legislation, including Alabama (HB56), Georgia (HB87), Indiana (SB590), South Carolina (S20) and Utah (Utah’s package – H116, H466, H469 and H497) in 2011. Their laws address a variety of topics, from immigration enforcement by local and state police to verification for employment and public benefits. In some instances, they have gone even further, such as requiring schools to verify students’ immigration status. Unfortunately, due to the recent nature of these laws, we are unable to properly examine their impact with our data.
4See Table 5 in the Appendix for a listing of the states with E-Verify mandates, as well as the mandates’ enactment dates and scope.
6The three types refer to:
■ Task force model that permits local and state officers to question and arrest suspected noncitizens during routine law enforcement operations.
■ Jail enforcement model, which enables local officers to question detained individuals about their immigration status.
■ Hybrid models, which allow jurisdictions to participate in both types of programs. The various types of programs can be implemented using a "targeted" or a "universal" model. When implementing the program as a targeted model, local and state officers focus on identifying serious criminal offenders, whereas the universal model implementation focuses on processing as many undocumented immigrants as possible.
7United States v. Maricopa County, case number 2:12-cv-00981-LOA, filed May 10, 2012, available at: http://www.justice.gov/iso/opa/resources/46420125101544060757.pdf; DHS, FY 2013 Budget in Brief, 16.
8ICE distinguishes between criminals in Priority 1, 2 and 3 based on the charge for which they were arrested and their criminal history. Priority 1 being individuals convicted of an aggravated felony or multiple felonies, Priority 2 those with one felony or three misdemeanors, and Priority 3 those with at least one misdemeanor.
9We are implicitly assuming that the vast majority of migrants impacted by these policies do not relocate to other counties or states. They either stay in their original location or, if apprehended, they are deported to Mexico. In both instances, their incomes fall to YL. There is emerging empirical evidence suggesting that, indeed, that is most commonly the case (Amuedo-Dorantes and Lozano 2013Watson 2013) in light of the large number of deportations in the past years –averaging approximately 400,000/year. Nevertheless, we also experiment with a theoretical extension that allows for the possibility that migrants relocate to another U.S. locality not adopting tougher immigration measures and, as such, are not adversely impacted by the policy. Comparative statics are displayed in Appendix C. Our main predictions remain unchanged.
10Please refer to the appendix for the derivation of these conditions.
11Each household (and its members) is only interviewed once. Respondents are not followed over time.
12For more detailed information on the survey design, please visit: http://mmp.opr.princeton.edu/databases/dataoverview-en.aspx.
13For the purpose of the analysis, we label as treated those U.S. localities adopting one of the policy measures being examined at some point in time, whereas control localities are those that do not.
14Because of the limited number of women in the MMP, dropping them from our sample does not significantly alter our main findings. These results are available from the authors.
15Earnings and remittance data are deflated using the consumer price index from the Bureau of Labor Statistics website (http://www.bls.gov/cpi/).
17We also experiment with dropping those observations corresponding to migrants whose last year in the United States coincides with the enactment year of the policy. Results (available from the authors) prove robust to that alternative definition of the policy variables.
18Our LM statistics is 1768.4, which is above 1 percent critical value of 29.92 by a large margin.
19The least squares estimators are unbiased and consistent even when the assumptions of linearity, homoscedasticity and normality of the error term are violated.
20While legal migrants’ propensity to remit does not appear to significantly change with the enactment of E-Verify mandates, the coefficients gauging the impact of E-Verify mandates on legal and undocumented immigrants are jointly significant. As such, the overall impact of E-Verify mandates on the likelihood of sending money home by Mexican migrants is given by: (0.022-0.181*share of undocumented) = 0.022-0.181*0.64 = -0.094.
21The overall impact of 287(g) agreements and Secure Communities on the likelihood of sending money home by migrants is given by: (-0.26 + 0.251*share of undocumented) = -0.26 + 0.251*0.64 = -0.099.
22The police-based initiatives, such as 287(g) agreements and Secure Communities, increase the dollar amount remitted by Mexican migrants by 50 percent [(0.724-0.347*0.64)*100] or an increase of $166.
23Before the adoption of these policies, 64.5 percent of migrants remitted an average of $331/month. Hence, on average, the dollar amount remitted per migrant was: (0.645*$331) = $214/month. Following the adoption of the aforementioned policies, the share of remitters drops to 47 percent, whereas the average dollar amount remitted home by those sending money to their families increases by $166/month to approximately $498/month. Hence, on average, the dollar amount remitted per migrant increases to $234/month = (0.47*$498).