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Over the past two decades immigration enforcement has grown exponentially in the United States. Using data from the 2005 through 2011 American Community Survey, we exploit the geographical and temporal variation in a novel index of the intensity of immigration enforcement to show how the average yearly increase in interior immigration enforcement over that period raised the likelihood of living in poverty of households with U.S. born children by 4%. The effect is robust to a number of identification tests accounting for the potential endogeneity of enforcement policies and residential location of immigrants, and is primarily driven by police-based immigration enforcement measures adopted at the local level, such as 287(g) agreements.

Over the last years several states have enacted policies granting undocumented immigrants access to driver's licenses. We exploit the state and temporal variation in the issuing of state driver's licenses to undocumented immigrants to estimate their impact on labor market outcomes. Using 2005 through 2017 data from the American Community Survey, we show that likely undocumented men increase their weekly hours of work in response to the availability of driver's licenses. Perhaps due to their already high labor force participation, the impact is somewhat moderate. We also find no similar impacts among similarly skilled foreign-born Hispanic men who have naturalized. The policy slightly raises commuting time, suggesting changes in work patterns, as well as likely undocumented immigrants’ propensity to have an occupation that requires driving. At a time when anti-immigrant sentiments are at an all-time high, understanding how these policies impact targeted groups and similarly skilled citizens is crucial for maintaining an informed immigration policy debate.

Tougher immigration enforcement has been responsible for 1.8 million deportations between 2009 and 2013 alone, most of them involving fathers and heads of household. We exploit the geographic and temporal variation in intensified enforcement to gauge its impact on children’s propensity to live without their parents in households headed by relatives or friends, or in households singly headed by their mothers with absentee spouses. Given the emotional, cognitive and long run socioeconomic costs of being raised without parents or in a single-headed household, gaining a better understanding of the collateral damage of heightened enforcement on the families to which these children belong is well warranted.

A computer system based on Monte-Carlo simulation and fuzzy logic has been designed, developed and tested to: (i) identify covariates that influence remittances received in a specific country and (ii) explain their behavior throughout the time span involved. The resulting remittance model was designed theoretically, identifying the variables which determined remittances and their dependence relationships, and then developed into a computer cluster. This model aims to be global and is useful for assessing the long term evolution of remittances in scenarios where a rich country is the host (United States of America) while a poor country is the where the migrant is from (El Salvador). By changing the socio-economic characteristics of the countries involved, experts can analyze new socio-economic frameworks to obtain useful conclusions for decision-making processes involving development and sustainability.