Panel Paper:
Pathways to Citizenships: Understanding the Characteristics Driving Naturalization in the United States 2012-2016
*Names in bold indicate Presenter
This paper utilizes a logistical regression model to determine the drivers and deterrents of recent naturalization. Using publicly available datasets—the 2016 5-year American Community Survey and the 2014 Survey of Income and Program Participation—the model in this paper generates individual-level estimates of who is eligible to naturalize and the factors contributing to naturalization. To address bias in previous work on naturalization, this paper additionally implements logical and probability edits to identify and exclude from the sample undocumented immigrants who are systematically unable to naturalize. Our results indicate that the main drivers of an eligible adult’s propensity to naturalize are related to (1) individual characteristics, such as English language ability, educational attainment, income, and whether they are married to a U.S. citizen; (2) country-of-origin characteristics, such as whether dual citizenship is allowed and whether they come from a refugee-sending country; and (3) characteristics of where eligible adults live in the U.S., such as whether they reside in a Democratic-leaning state and the concentration of immigrants in their sub-county area.
Of notable significance and omitted from previous research, we find that one of the strongest predictor negatively impacting one’s propensity to naturalize is an individual’s mixed-family status. Our model indicates that the presence of an undocumented family member reduces the odds of naturalizing by nearly 50 percent. Though this point needs further investigation, we suspect this is largely due to the growing fear of interacting with immigrant officials and procedural formalities including questions on the N-400 form asking the legal status of family members.