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Abstract
Approximately 65,000 immigrant students who lack legal documentation to reside in the United States graduate from American high schools each year. Among these students, only about 5-10% persist to higher education, a rate that is far below the attainment of their native-born peers. This discrepancy is due in part to federal and state policies that restrict undocumented students access to postsecondary institutions. In response to the lack of federal immigration reform, some states have endeavored to influence the policy arena by adopting varying forms of in-state residency tuition (ISRT) policies that have the impact of expanding or restricting access to public postsecondary education among undocumented students. Guided by the policy frameworks of advocacy coalitions, policy diffusion, and social construction, an event history analysis analyzes the adoption of ISRT policies of both a restrictive and permissive form between 2000 and 2015 across all 50 states. The combined EHA approach includes both internal state characteristics and the effects of diffusion to model the rate of policy adoption among states across the years of analysis. Additional variables measuring citizen and government ideology capture the extent to which undocumented students are socially constructed as worthy or unworthy of public postsecondary benefits. Results of this study suggest that the internal state dynamics are exceedingly influential in ISRT policy adoption, particularly with regard to population demographics, gubernatorial power, postsecondary governance, and political partisanship of citizens. However, the strength and direction of these relationships is indeterminate, given the competing economic and moral interests of legislators to protect the privileges of native-born students while also promoting attainment for undocumented students. Future research will expand upon these findings to uncover the relationship between policy adoption and the elusive measures of social construction and policy diffusion with the aim of providing policymakers and researchers with models for predicting future policy action.