Selected Characteristics of Eligible to Naturalize Adults by Probability of Naturalization, United States
Tableau maps and charts developed by Sabrina Kim, Data Analyst
This interactive map presents CSII’s most recent estimates of eligible-to-naturalize adults in the United States. In a first of-its-kind analysis, we disaggregate the eligible-to-naturalize adult population by probability of naturalizing in the next two-to-three years: low probability, medium probability, and high probability. The tool also provides a table of each population’s demographic information, including age, race, education attainment, poverty status, English speaking ability, top five places of origin, and top five languages spoken at home (other than or in addition to English).
For CSII's estimates on the size and region-of-origin composition of eligible-to-naturalize adults in the United States, see our map here: https://dornsife.usc.edu/csii/eligible-to-naturalize-map/
Tableau maps and charts developed by Sabrina Kim, Data Analyst
With growing numbers of eligible-to-naturalize legal permanent residents (LPRs) and more economic, political, and social pressures to integrate, naturalization is an increasingly important process for immigrants to access opportunities and resources that are privileged to U.S. citizens. These include the right to vote, access to certain government benefits programs and jobs, prioritized sponsorship of immediate family to the United States, and protection from deportation. We hope this tool will provide useful information to activists, agencies, and civic and business leaders seeking to encourage naturalization and civic engagement.
How to Use the Map:
Please note: this map is best viewed in Google Chrome.
The estimates presented in the map stem from a dataset we assembled using the 2016 5-year American Community Survey (ACS) microdata from IPUMS-USA, covering the years 2012 through 2016, and the 2014 Survey of Income and Program Participation (SIPP). We chose the 5-year ACS microdata because it contains a wide variety of individual and household characteristics and the sample size is large enough to make reasonably accurate estimates for sub-state geographies. One critical shortcoming of this dataset for our purposes, however, is that while it identifies non-citizen immigrants, it does identify which non-citizens are documented and which are not. In order to figure out who was eligible to naturalize, we first had to determine who was undocumented, then then assumed that the remaining non-citizen immigrants were documented Lawful Permanent Residents (LPRs). Our estimation of who was undocumented is based on a statistical model developed using the 2014 SIPP that was applied to the ACS microdata. For those interested in the details of our methodology, please refer to this document. For the current research, we applied the same methodology to the more recent aforementioned datasets.
With identifiers in place for who was an LPR among non-citizens in the ACS microdata, we applied some basic conditions to determine which of them were likely to be eligible-to-naturalize adults. We included all persons at least 18 years old who had been in the U.S. for at least five years prior to the survey (or three years if married to a U.S. citizen).
We then compared eligible-to-naturalize adults to immigrants who had recently naturalized (as adults) so we could examine which individual characteristics and other factors were most strongly associated with adult naturalization and estimate the probability of naturalization for each eligible-to-naturalize adult in the dataset. We focus on the recently naturalized – those naturalizing two to three years prior to the survey – to guard against reverse causality and so that the effects of different characteristics, and the probabilities of naturalization we estimate, are relevant to the contemporary social, economic, and political climate. We estimate probabilities of naturalization using a statistical model (a binomial logistic regression) that predicts the likelihood of naturalizing in the next two to three years based on a variety of demographic, economic, and country-of-origin characteristics that seem to be important to the naturalization decision, either theoretically or empirically.
We then placed eligible-to-naturalize adults into three categories by their estimated probabilities of naturalization (low, middle, and high), using the mean and standard deviation of the estimated probabilities to draw the lines between each group, and aggregated the data to the geographic levels shown in the maps. It should be noted that we only estimated probabilities of naturalization for eligible-to-naturalize adults living in households (not group quarters), since variables such as household income and tenure were used to estimate the probabilities. Thus, the data in map excludes eligible-to-naturalize adults living in group quarters, leaving the totals slightly lower than in our related interactive map of eligible-to-naturalize adults by size, concentration, and impact. For more detailed on the methodology, please refer to the research brief that informs these maps.
To avoid reporting highly unreliable estimates, we do not report any data for geographies with fewer than 50 non-citizen adult survey respondents in the ACS microdata (unweighted). We also do not report detailed demographic data on the characteristics of eligible-to-naturalize adults (just the basic breakdown by low, middle, and high probability of naturalization) if based on fewer than 30 unweighted survey respondents (overall or for any particular probability group); when the number is between 30 and 99, we include an asterisk and cautionary note around data reliability.
The USC Center for the Study of Immigrant Integration (CSII) would like to thank the Carnegie Corporation of New York, The California Endowment, the James Irvine Foundation, the California Wellness Foundation, and Bank of America for providing funding to enable us to carry out this research.
We also thank CSII staff and graduate student researchers who helped produce this research brief and accompanying interactive maps. Gladys Malibiran handled communications/promotions/social media and media relations related to the release (including getting everything on our website), Sabrina Kim developed the maps in Tableau Public, the related infographics, and designed the brief, Vanessa Carter edited and coordinated the writing process, Cynthia Moreno helped with writing and editing, Stina Rosenquist, Joanna Lee, and Sarah Letson (of the Immigrant Legal Resource Center) assisted with the case studies, and Rhonda Ortiz helped with overall project coordination and advice. We also thank Angelica Peña, Nasim Khansari, and Christine Chen from Asian Americans Advancing Justice Los Angeles, Pablo Blank from CASA, and Connie Cheng and Sandra Sandoval from Citizenshipworks for their contributions to the case studies.
Join USC's Center for the Study of Immigrant Integration (CSII) and partners at the Immigrant Legal Resource Center's (ILRC) New Americans Campaign to learn about CSII's latest research and interactive mapping tool on the eligible-to-naturalize populations in the U.S.