Race, ethnicity, economics, and federalism : state sentiment regarding noncitizens from 2009 to 2014
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This dissertation examines the causes and means of state legislative action on immigration in the United States along a range of policy issues from 2009 to 2014. The work begins by placing the phenomenon of immigration restriction and accommodation in its historical context, alongside other instances of localized opposition to demographic change. Next, I examine the state-level demographic changes which occurred during the last Census period, from 2001 to 2010. I find that Latino population growth occurred heaviest in rural states with large African American populations. I then turn to analyze state restrictions placed on noncitizens residing in the American states. I find that the growth rates of the foreign-born, Asian, and Latino populations all associate with restriction. Also, states with weaker economies and conservative populations tended to adopt restrictive immigration policies. Following this, I examine state accommodations and find that the respective sizes of the foreign-born, Asian, and Latino populations are associated with accommodation, suggesting that these groups demonstrate cohesiveness and look out for noncitizens that are affected by state policies. After considering both restrictions and accommodations separately, I create a sentiment score which measures each state's overall policy posture on the issue of immigration. This score differentiates states such that a state with many accommodations and fewer restrictions is ranked higher than a state with few accommodations and many restrictions, and vice versa. Models are developed to explain these scores. I find that the states altered their behavior in 2012, and from that year on they enact more accommodations than restrictions. I conclude by examining the role of immigration in the 2016 presidential election. I find that as states are less accommodating and more restrictive, Trump's probability of winning the state went up, controlling for other factors.