Family Matters: Modeling Naturalization Propensities in the United States

Abstract

Despite the benefits of gaining citizenship, many eligible immigrants in the United States are not naturalizing. In this article, we examine factors that lead to naturalization in the United States, finding that immigrants’ pathways to citizenship are simultaneously shaped by individual characteristics, place-based attributes, and family dynamics. Of notable significance, and largely omitted from previous empirical work on naturalization, we find that having a naturalized spouse prior to one’s own naturalization is associated with a higher probability of naturalization, whereas being married to an undocumented immigrant reduces the probability of naturalization. Similarly, having a naturalized adult in the family other than a spouse improves the odds of naturalization, but having an undocumented family member other than a spouse reduces the odds. These findings suggest that while eligible immigrants with naturalized family members are more likely to improve their access to naturalization through pooled resources and increased information sharing, eligible immigrants with undocumented family members are more likely to avoid the naturalization process entirely, likely due to chilling effects from immigrant enforcement and policies that target close ties with liminal legality. These findings suggest that immigrants’ access to citizenship could be improved by (1) reaching immigrants who are the first in their families to naturalize and (2) improving the context of reception for undocumented immigrants and mixed-status families. More broadly, while individual factors play a role in naturalization, complex contextual factors, including place and family, shape immigrants’ pathways to citizenship and provide opportunities for new policies to promote immigrant integration.

Introduction

The US Office of Immigration Statistics (OIS) estimates that of the 13.6 million lawful permanent residents (LPR) residing in the United States in 2019, 9.1 million were eligible to naturalize, of whom nearly 80 percent had been eligible for at least five years (Baker 2019). Given the individual and collective benefits that come with citizenship (Pastor and Scoggins 2012; Aptekar 2015), understanding what drives or delays naturalization can lead to more effective policies and tools that foster greater immigrant integration. In the analysis presented here, we find and argue that the decision and ability to successfully naturalize in the United States are not solely dependent on individual characteristics but rather are also simultaneously influenced by complex contextual factors, such as place and family dynamics. Achieving a deeper understanding of these place-based attributes and family structures can lead to policies that can improve access to resources and encourage eligible immigrants to seek citizenship.

Studies of naturalization often focus on the significance of individual and, to some degree, place-based determinants that shape pathways to citizenship (e.g., Yang 1994; Johnson et al. 1999; Jones-Correa 2001; Aptekar 2015; Woroby and Groves 2016; Abascal 2017). This article builds on previous research on naturalization and adds a novel analysis of family effects on successfully gaining citizenship. Specifically, we attempt to isolate and empirically measure the impact that both naturalized and undocumented family members have on immigrants’ propensities to naturalize in the United States. We suggest that individuals in mixed-status families experience conflicting privileges and threats stemming from their relatives’ differential treatment as either a lawful resident or an undocumented immigrant under the US immigration system (Fix and Zimmermann 2001; Aranda, Menjívar, and Donato 2014; Vargas and Pirog 2016; Gomberg-Muñoz 2017). While eligible immigrants with naturalized family members may be more likely to access citizenship because of pooled resources and increased information sharing, eligible immigrants with undocumented family members may face concerns that the application process could heighten attention and risk the well-being of close ties with liminal legality.

Below, we explore the determinants of naturalization in the United States, examining how propensities to naturalize are simultaneously influenced by individual, place-based, and family attributes. After reviewing the existing literature on naturalization and specifying our hypotheses, we discuss the methodology we use to estimate who in the 2016 American Community Survey (ACS) five-year microdata is eligible to naturalize. We also discuss a novel method of estimating who is likely to be an undocumented immigrant, a step necessary to more accurately determine who is eligible, as well as the impacts of mixed family status on naturalization. We, then, consider the likely effects of specific determinants on naturalization, including human capital, place variables, and the significant role of family effects, the latter of which has been largely omitted in previous empirical research on naturalization (e.g.,Yang 1994; Jones-Correa 2001; Abascal 2017). We conclude with a brief discussion on the policy implications of this research, particularly the reasons why a broader comprehensive immigration reform that includes the legalization of undocumented immigrants could have positive spillover effects on naturalization in the United States.

Benefits of Naturalization in the United States

In the United States, naturalization comes with privileges and benefits that can further facilitate immigrants’ social, economic, and political well-being, including the right to formally participate in the US political system (Aptekar 2015). In particular, voting is often cited by naturalized citizens in the United States as a primary reason they chose to naturalize, since voting allows them to more directly affect policy change and have more agency in choosing who represents them (Aptekar 2015; National Academies of Sciences, Engineering and Medicine 2015).

Naturalization also has positive impacts on immigrants’ wages and earnings (Bratsberg, Ragan, and Nasir 2002; Pastor and Scoggins 2012; Sumption and Flamm 2012; Enchautegui and Giannarelli 2015). Citizenship reduces barriers that discriminate against noncitizens, including restrictions on certain employment opportunities in the majority of US federal government jobs and private-sector work requiring a high security clearance (Enchautegui and Giannarelli 2015; Ayers 2018). In employment where citizenship is not a requirement, naturalization can still play a factor in promoting more gainful employment, as noncitizens are more likely to face wage and hiring discrimination (Brettell 2011; Morrison 2018). Lewis, Liu, and Edwards (2014), for example, found that in state and local governments where citizenship is not always a requirement but a preference when hiring, an immigrant’s odds of gainful employment substantially improve with citizenship.

Citizenship also improves access to public assistance programs (Aptekar 2015; Bojorquez and Fry-Bowers 2019). Though eligible-to-naturalize immigrants in the United States often qualify for welfare benefits that require at least five years of residence (e.g., Medicaid and Temporary Aid for Needy Families), the combination of public charge rules and attempts to legislate citizenship requirements contributes to chilling effects that deter qualified immigrants who lack citizenship from seeking public assistance (Fortuny and Chaudry 2011; Watson 2014; Pedraza and Zhu 2015; Bojorquez and Fry-Bowers 2019). Vargas and Pirog (2016) find such chilling effects to be especially striking for mixed-status families — that is, families with both documented and undocumented members — living in places with higher deportation rates. They conclude that mixed-status families, particularly those that are more likely to be targeted by immigration enforcement and at risk of deportation because of their race/ethnicity, are significantly less likely to access Women, Infants, and Children (WIC), the third largest federally funded food program in the United States that supports pregnant women or women with children under the age of five.

With protection from deportation and greater ease in travelling internationally, citizenship also provides immigrants with more security (Aptekar 2015; National Academies of Sciences, Engineering and Medicine 2015; Asad 2020). It is worth noting that even though naturalized citizens are broadly protected from deportation, their status adjustment does not always alleviate deportation fears. Asad (2020), for example, finds that although deportation fears among Latinx noncitizens are significantly higher, naturalized Latinx immigrants experienced significant growth in their deportation fears after the 2016 US presidential election, nearing parity with their noncitizen counterparts, despite their adjusted status. Increasing deportation fears among Latinx immigrants with US citizenship may be due to the higher propensity of Latinx immigrants to have noncitizen family members or close ties whose likelihood of being targeted and deported is perceived to be high by both Latinx US citizen and noncitizen immigrants (Asad 2020; Amuedo-Dorantes and Lopez 2021).

Naturalization additionally provides greater access to family reunification through prioritized and expanded family sponsorship in the United States (Aptekar 2015). Citizens not only have, on average, a shorter waiting period to have their petitions to bring family to the United States reviewed and approved but also can sponsor a wider range of relatives to live and potentially gain permanent residency in the United States, including siblings, parents, and married or single children (Carr and Tienda 2013; Aptekar 2015). By contrast, LPRs can only petition to sponsor spouses and unmarried children, whereas undocumented immigrants are not able to sponsor anyone (Aptekar 2015). However, mixed-status families face different challenges with family reunification, due to how existing immigration laws criminalize undocumented immigrants (Enchautegui and Menjívar 2015; Abrego et al. 2017; López 2017). In particular, the Illegal Immigration Reform and Immigrant Responsibility Act of 1996 (IIRIRA) created disproportionate barriers for low-income mixed-status families by (1) requiring a minimum income threshold for US citizens wanting to sponsor a spouse for lawful permanent residency and (2) instating temporary bars from reentry to the United States of up to 10 years if an individual is found to have lived without legal authorization in the United States (López 2017). Family reunification, thus, may not be so great an incentive to naturalize for eligible immigrants in mixed-status families who may face barriers even as citizens.

Factors Impacting Naturalization

If citizenship confers civic and socio-economic advantages, why do so many immigrants in the United States fail to naturalize when they are eligible? Earlier work on naturalization has focused solely on individual characteristics and socioeconomic status to determine what drives successful naturalization in the United States (Bernard 1936), with later empirical work incorporating how place and context of reception significantly influence successful naturalization (e.g., Yang 1994; Jones-Correa 2001; Aptekar 2015; Abascal 2017). This empirical literature, however, is limited in its analysis of how family structures simultaneously shape pathways to citizenship in the United States. Recent ethnographic work on naturalization (e.g., Gomberg-Muñoz 2017; López 2017) helps bridge this gap in understanding how family dynamics related to immigration and citizenship status influence eligible-to-naturalize immigrants’ decision to seek citizenship in the United States. In this section, we discuss what the literature on naturalization and citizenship — both large-n analyses and ethnographic studies — suggests about the individual and structural factors that simultaneously shape immigrants’ decisions and abilities to naturalize in the United States.

Individual Characteristics

Immigrants with greater human capital have greater odds of naturalizing, as they are better equipped to meet US naturalization requirements (Yang 1994; Johnson et al. 1999; Bloemraad 2006; Aptekar 2015). Higher educational attainment, for example, often provides immigrants with the experience, skillset, and knowledge to prepare for the required US civics, history, and English exams, which are similarly formatted to assessments administered in the US education system (Kunnan 2009; Aptekar 2015). Relatedly, as the naturalization process is primarily in English, immigrants with higher English proficiency have greater odds of passing the naturalization tests and are able to more effectively navigate procedural barriers, including the application and study materials provided by the United States Citizenship and Immigration Services (USCIS) (Bloemraad 2006; Aptekar 2015; Flores 2018).

Income affects naturalization in multiple ways, with the most direct impact being the ability to afford the application fees, although the application’s cost is mitigated by fee waivers and fee reductions for low-income applicants, which were generous during Barack Obama’s presidency and then constrained during Donald Trump’s presidency (Yasenov et al. 2019). In an executive order signed in February 2021, US President Joe Biden committed to “make the naturalization process more accessible to all eligible individuals, including through a potential reduction of the naturalization fee and restoration of the fee waiver process” (Executive Order No. 14012 2021). Beyond application fees, immigrants can face other financial costs in naturalizing, including retaining lawyers and services to assist in what can be a complex naturalization process (Aptekar 2015). Income may be needed to access services and classes that can improve an applicant’s odds of passing the required citizenship test (Aptekar 2015). Wealth matters as well: owning a home signals the capacity to more easily absorb the costs of naturalization and is also an indicator of immigrants’ ties and intentions to stay in the United States (McConnell and Marcelli 2007).

Naturalization patterns differ by demography. Latinx immigrants, particularly immigrants from Mexico, consistently exhibit the lowest naturalization rates in the United States (Aptekar 2015; Gonzalez-Barrera 2017; Waldinger 2021). Latinx immigrants primarily report language and financial barriers as individual reasons for not naturalizing (Gonzalez-Barrera 2017), and these reasons are often linked to a higher share of Latinx immigrants arriving in the United States with limited educational opportunities and resources and at an older age, when language acquisition becomes more challenging (Bleakley and Chin 2010). Additionally, immigration policies and racialized enforcement impact how Latinx immigrants navigate the naturalization process (Waldinger 2021). Since 1965, the undocumented immigrant population in the United States has been predominantly Latinx, leading to enforcement that disproportionately targets Latinx communities (Massey, Pren, and Durand 2009; Massey and Pren 2012). Such targeted enforcement of Latinx communities may influence how Latinx immigrants access public resources and processes where immigration officials are involved (Aranda, Menjívar, and Donato 2014; López 2017; Asad 2020; Amuedo-Dorantes and Lopez 2021; Waldinger 2021).

Similarly, naturalization disparities exist across gender identities. Immigrant women comprise a larger share of the US LPR population and naturalize at higher rates than immigrant men (Dziadula 2018; Amuedo-Dorantes and Lopez 2021). Research has shown that differences in naturalization rates are often associated with the gender gap in educational attainment, English proficiency, and social networks that can provide additional naturalization information and resources (National Academies of Sciences, Engineering and Medicine 2015). More recent work by Amuedo-Dorantes and Lopez (2021) finds that immigrant women, particularly those in non-mixed-status households and families, have higher propensities to naturalize as a response to increasing immigrant enforcement. Such responses are gendered and shaped by migration patterns and policies, including the disproportionate policing and targeted enforcement of immigrant men (Golash-Boza and Hondagneu-Sotelo 2013).

LPR status is a requirement to naturalize in the United States, but an immigrant’s status before gaining permanent residency status can also impact their choice to pursue citizenship (Cheong 2021). Cheong (2021) finds that immigrants who once entered the United States without authorization are more likely to naturalize when becoming eligible than their immigrant counterparts with no history of illegality. The author utilizes the theory of “defensive naturalization” to explain this increased propensity among once-undocumented LPRs who find citizenship “a crucial commodity with which to achieve legal security and formal equality in a host country that had previously excluded them from the mainstream” (2021, 25). Massey and Pren (2012) find similar trends of defensive naturalization when anti-immigrant measures are proposed or implemented; however, their analysis is situated within the context and wake of large-scale legalization programs (e.g., the 1986 Immigration Reform and Control Act) that led to entire families securing LPR status in the United States. While past status history can play a role, estimating who was undocumented prior to adjusting to lawful status is not measurable in the dataset we use.

Place-Based Attributes

The places immigrants live and come from can also impact their decisions to naturalize (Yang 1994; Hampshire 2010; Dziadula 2018). Low wages, scarce employment prospects, and inadequate safety nets can dissuade immigrants from returning to their origin country and, thus, lead them to make a permanent commitment to the United States (Rosenblum and Brick 2011; Portes and Rumbaut 2014). Similarly, concerns about political violence and persecution in home countries have led to significant international migration and deterred immigrants’ permanent return (Menjívar 2000; Abrego 2014; Portes and Rumbaut 2014). Asylum-seekers and refugees, for example, often flee their origin country with little intention to return, due to the uncertainty of their survival in their homeland compared to the idea of permanent security and safety in the United States (Bloemraad 2018). Although this desire to stay in the United States can lead to higher rates of naturalization among immigrants fleeing conflict or persecution, many refugees and asylum seekers in the United States come with limited human capital and resources and, thus, face other challenges in gaining citizenship (Mossaad et al. 2018).

Allowing dual citizenship can also influence an immigrant’s choice to naturalize. According to the City University of New York’s Citizenship Now group, the majority of the world’s countries nominally allow their citizens to retain their origin-country citizenship if they choose to naturalize in the United States, totaling approximately 65 percent of origin countries represented in our data (The City University of New York 2018). Immigrants may be hesitant to forfeit their origin-country citizenship for a multitude of reasons, such as symbolic attachments to their motherland and intentions for return migration in some form (Mazzolari 2009; Leblang 2017). Research finds that once this cost of foregoing citizenship is removed through dual citizenship, immigrants are more likely to seek naturalization (Jones-Correa 2001; Mazzolari 2009). However, the effect of dual citizenship on an immigrant’s choice to naturalize may vary by origin country, as dual citizenship rules and benefits can differ, with some nations revoking voting rights for citizens with multiple citizenships (Sejersen 2008).

The context of reception for immigrants in the United States also influences both the choice and ability to naturalize (Van Hook, Brown, and Bean 2006). States and localities that have pro-immigrant policies and attitudes are more likely to have the resources and political will to foster immigrant integration and naturalization outcomes (Bloemraad 2006; Van Hook, Brown, and Bean 2006; Woroby and Groves 2016; deGraauw and Bloemraad 2017). However, places with pro-immigrant policies and attitudes are also more likely to attract noncitizen immigrants who often arrive with low educational attainment and limited English proficiency and, thus, without the human capital needed to facilitate naturalization, suggesting why a multivariate approach to statistically estimate propensity to successfully naturalize is key in disentangling factors that shape pathways to citizenship (Johnson et al. 1999).

Some scholars argue that a less welcoming environment can actually encourage naturalization. For example, Latinx immigrants in California experienced a significant increase in their naturalization rate after the passage of Proposition 187, a ballot measure that sought to bar undocumented immigrants from accessing public education, health care, and other social services provided by the state (Cort 2012). Similarly, rising immigrant enforcement can increase naturalization rates among LPRs seeking to gain citizenship as a measure to secure their stay in the country (Amuedo-Dorantes and Lopez 2021). Woroby and Groves (2016) argue that anti-immigrant policies that target undocumented immigrants can increase naturalization rates among authorized immigrants who turn to citizenship as a way to distinguish themselves from the undocumented.

Another place-based factor that may shape pathways to citizenship in the United States arises from a residence in an ethnic enclave. Here, the impact on naturalization can be cut two ways. Abascal’s (2017) work on a geographically representative sample of Latinx immigrants in 15 states and the District of Columbia — localities representing 87.5 percent of the Latinx population in the United States at the time of the study — finds that the concentration of naturalized co-ethnics is positively associated with greater sharing of naturalization information because such communities have a stronger sense of a shared hyphenated American identity. Immigrant-serving organizations and religious congregations may also be more common when and where immigrant populations are concentrated, and such institutions can provide services, resources, and connections that facilitate immigrant integration (Bloemraad 2006; Manglos-Weber 2020). By contrast, Woroby and Groves (2016) argue that some immigrant clusters can be disadvantageous, particularly if those immigrants who tend to cluster lack the knowledge and intentions to naturalize.

Family Effects

Family members serve as important nodes in an immigrant’s social network and can impact other eligible-to-naturalize family members’ decisions to naturalize. In line with Menjívar’s (2000) analysis of social networks as a conduit of information and source of assistance among immigrants, going through the process of applying for citizenship can be easier if a family member or someone with close ties can share relevant resources and information based on their own experiences (Liang 1994). Having an already-naturalized family member, thus, should have a positive impact on the naturalization choices of other family members.

However, what if part of the family structure includes close ties with persons who have liminal legality or undocumented status? One might speculate that those who are eligible to naturalize and who live in mixed-status families with undocumented members might view naturalization as a way to provide additional resources and some protection for the whole family. Yet ethnographic studies, including Gomberg-Muñoz (2017) and López (2017), find that LPRs and US citizens in mixed-status families may actually avoid accessing public benefits and processes like naturalization and family reunification for fear of risking the safety of their undocumented family member.

Of particular importance to understanding how the presence of an undocumented immigrant in the family unit may shape pathways to citizenship is that the N-400 form, the official application for citizenship in the United States, requires the disclosure of the immigration status of one’s spouse and children, regardless of whether they are co-residents (Marquez and Rodgers 2017; U.S. Citizenship and Immigration Services 2019b). As noted previously, some eligible immigrants may have concerns about exposing their spouses’ and children’s documentation status to immigration officials (Aranda, Menjívar, and Donato 2014; López 2017). For eligible immigrants in mixed-status families who do pursue naturalization under the US citizenship regime, there are additional legal, financial, and emotional costs that further strain the family as they go through a scrutinized legalization process that has no guaranteed outcome (Gomberg-Muñoz 2017). While other family members who are not a spouse or children (e.g., siblings and parents) are not part of the official naturalization process, their uncertain legal status can similarly create a chilling effect that further dissuades eligible immigrants from pursuing citizenship (Gomberg-Muñoz 2017). For these reasons, having undocumented family members might be a deterrent to naturalization for eligible immigrants in mixed-status families, holding all other factors constant. As we note in the conclusion, this chilling effect may suggest that encouraging naturalization and promoting comprehensive immigration reform that includes legalization for the undocumented are complementary processes.

Hypotheses

The previous discussion of the literature on naturalization suggests several hypotheses that we explore in our multivariate regression analyses. We test our hypotheses on top of a baseline model which accepts, based on previous studies of naturalization and immigrant integration in the United States (e.g.,Yang 1994; Johnson et al. 1999), that immigrants with greater human capital and financial resources have greater propensities to naturalize. After all, to gain US citizenship, immigrants are expected to go through a relatively costly and time- and labor-intensive process that, by design, is more accessible to wealthier immigrants with higher educational attainment and English proficiency (Yang 1994; Johnson et al. 1999; National Academies of Sciences, Engineering and Medicine 2015; Abascal 2017).

However, place — both the sending country and the receiving context — can also simultaneously influence eligible immigrants’ decisions to naturalize. As noted above, immigrants may seek permanent residency and citizenship in the United States if they believe that there are greater economic and social opportunities than in their origin country or if their return could leave them and their families in unsafe situations due to political persecution and violence (Menjívar 2000; Bloemraad 2006; Abrego 2014; Portes and Rumbaut 2014). Alternatively, immigrants may face additional costs to becoming a citizen in the United States if they must forfeit their origin-country citizenship, which could create barriers to visiting family, threaten important relationships, weaken symbolic ties, and limit formal political engagement in one’s origin country (Leblang 2017; Mazzolari 2009). As discussed previously, one structural factor that can mitigate these costs is whether dual citizenship is allowed (Jones-Correa 2001; Mazzolari 2009).

H1: All else equal, immigrants with poorer social, economic, and political conditions in their origin country have greater propensities to naturalize; this effect is mitigated when dual citizenship is possible.

Receiving place matters as well. While eligible immigrants residing in localities (e.g., states) with anti-immigrant policies and enforcement might see naturalization as a defense mechanism to secure their rights to stay in the United States and to preserve their access to public benefits, there may be barriers to naturalization if local conditions are hostile (Cort 2012; Amuedo-Dorantes and Lopez 2021; Cheong 2021). In general, we conjecture that immigrants living in states with pro-immigrant policies and attitudes may feel more welcomed and have better access to resources and services nurturing their integration, human capital, and networks (Bloemraad 2006; deGraauw and Bloemraad 2017). The concentration of co-ethnic immigrants could either indicate the presence of resources for immigrant integration or signal informational insularity and have a negative effect on naturalization.

H2: All else equal, immigrants living in more immigrant-friendly states have greater propensities to naturalize; the impact of the presence of co-ethnic immigrants in a more geographically confined locality (e.g., neighborhood) could be either positive or negative.

Naturalization can be a cumbersome and complex process that is difficult to navigate without the necessary human capital, financial resources, and information (Liang 1994; Menjívar 2000; Bloemraad 2006; Abascal 2017). We expect that immigrants with close ties to a naturalized family member who can share resources and information will have greater odds of naturalizing. On the other hand, we expect immigrants who have an undocumented family member to be less likely to naturalize, due to fears that any contact with immigration and federal officials, including during the naturalization process, could put the safety and security of their undocumented family members at risk.

H3: All else equal, immigrants with a naturalized family member will have a greater propensity to naturalize, while immigrants with an undocumented family member will have a lower propensity to naturalize.

Data, Methodology, and Model Specifications

For this analysis, we use the 2016 ACS five-year microdata level estimates from IPUMS¹ (Integrated Public Use Microdata Series) (Ruggles et al. 2020). The ACS microdata provide a comprehensive selection of individual and household characteristics, including information on immigrants’ naturalization status, years in the United States, sociodemographic characteristics, and reported measures of human capital (e.g., educational attainment and English proficiency). We are also able to aggregate these variables to determine place-based estimates. Importantly, this micro dataset allows us to link individuals within the same family and household unit to determine the significant family effects discussed in the previous sections.

The limitation of this dataset, however, is that while each survey respondent can be identified as either citizen or noncitizen, the ACS does not explicitly specify documentation status. Estimating such status is necessary to both accurately estimate who is an LPR and truly eligible to naturalize and consider whether an individual is in a mixed-status family. To address this shortcoming, we apply a series of logical edits and probability imputations, building on work estimating the undocumented immigrant population in the United States (e.g., Capps et al. 2013; Warren 2014; Van Hook et al. 2015; Pastor and Scoggins 2016). Previous empirical studies of naturalization (Yang 1994; Johnson et al. 1999; Jones-Correa 2001; Aptekar 2015) often do not account for the likely undocumented immigrants in their dataset who, despite meeting residency and age requirements, are not eligible to naturalize as they lack the required LPR status. After creating our sample of naturalized and eligible-to-naturalize immigrants, we utilize a series of logit models to determine the impact of specific individual characteristics, place-based attributes, and family ties on the eligible immigrants’ odds of naturalization in the United States.

Estimating Who Is Eligible to Naturalize and Who Recently Naturalized

Immigrants in the United States become eligible to naturalize when they satisfy the following conditions: (1) be at least 18 years of age at the time of filing the application for naturalization (Form N-400); (2) have resided in the United States as an LPR for at least five years (or three if married to a US citizen); (3) be physically present in the United States for at least 30 months; (4) be deemed a person of good moral character by USCIS officers; (5) have the ability to write, speak, and read in English; (6) have a basic understanding of US civics and history; (7) demonstrate attachment to the Constitution and its principles; and (8) be able to take the Oath of Allegiance (U.S. Citizenship and Immigration Services 2019a).

How do we model eligibility to naturalize with ACS data? The first step, noted above, is to identify likely undocumented immigrants and remove them from the sample to focus on likely LPRs (Pastor, Le, and Scoggins 2021). We, then, narrow the pool further by restricting our attention to LPRs who — at the time they completed the ACS survey between 2012 and 2016 — were at least 18 years old and had been in the United States for at least five years or three years if they were married to a US citizen. Although there are other requirements to be eligible to naturalize, these conditions can be clearly identified in our dataset. We utilize ACS microdata information on reported English speaking proficiency only when estimating the likelihood of naturalization and not to determine eligibility to naturalize because English speaking ability is not a measure used to determine eligibility in the official estimates of the eligible-to-naturalize population published by the OIS (Lee and Baker 2017).

Once we have applied our screens to estimate who is eligible to naturalize in the ACS, we compare our estimates to the official numbers available from the OIS (Baker 2019). OIS estimates are used for reference, as their numbers are based on government administrative data (essentially, those who had LPR status and met the residency tenure thresholds). Given that aggregated OIS estimates include children under 18, we include LPR children if either parent was eligible so that a more consistent comparison can be made; children are not included in the regression analysis because their citizenship is derivative and because adults, not their children, make the choice to naturalize. The results of the comparison are shown in Table 1. While our estimates are slightly larger for the eligible-to-naturalize population in 2016 than OIS’s estimates (8.97 million versus 8.88 million), the distribution of the population by entry period, birth country, and state of residence is relatively similar.

Table 1.

Comparing OIS and Le & Pastor Estimates of the Eligible to Naturalize.

		OIS Estimates (2019)		OIS Estimates (2016)		OIS Estimates (2014)		Le & Pastor (2012–2016)
		Number	Percent	Number	Percent	Number	Percent	Number	Percent
Period of entry
	Before 1990	2,680,000	29%	3,010,000	34%	2,400,000	27%	2,900,000	32%
	1990–1999	1,940,000	21%	2,190,000	25%	2,270,000	26%	2,440,000	27%
	2000–2009	2,650,000	29%	3,030,000	34%	3,920,000	44%	3,240,000	36%
	2010–2014	1,730,000	19%	650,000	7%	290,000	3%	390,000	4%
	2015 + …	120,000	1%	0	0%	0	0%	0	0%
	Total	9,130,000	100%	8,880,000	100%	8,880,000	100%	8,970,000	100%

Country of birth
	Mexico	2,490,000	27%	2,540,000	29%	2,710,000	31%	3,060,000	34%
	China	490,000	5%	430,000	5%	330,000	4%	330,000	4%
	Philippines	370,000	4%	350,000	4%	340,000	4%	280,000	3%
	Cuba	350,000	4%	300,000	3%	300,000	3%	330,000	4%
	Dominican Republic	340,000	4%	320,000	4%	300,000	3%	250,000	3%
	India	310,000	3%	270,000	3%	250,000	3%	390,000	4%
	Canada	250,000	3%	260,000	3%	260,000	3%	260,000	3%
	El Salvador	220,000	2%	230,000	3%	250,000	3%	310,000	3%
	United Kingdom	220,000	2%	230,000	3%	230,000	3%	280,000	3%
	Vietnam	220,000	2%	210,000	2%	200,000	2%	130,000	1%
	South Korea	200,000	2%	190,000	2%	190,000	2%	180,000	2%
	Haiti	160,000	2%	160,000	2%	150,000	2%	120,000	1%
	Jamaica	160,000	2%	160,000	2%	160,000	2%	130,000	1%
	Colombia	140,000	2%	140,000	2%	140,000	2%	130,000	1%
	Guatemala	120,000	1%	120,000	1%	120,000	1%	200,000	2%
	Rest of Countries	3,090,000	34%	2,970,000	33%	2,950,000	33%	2,590,000	29%
	Total	9,130,000	100%	8,880,000	100%	8,880,000	100%	8,970,000	100%

State of residence
	California	2,340,000	26%	2,360,000	27%	2,470,000	28%	2,270,000	25%
	New York	1,130,000	12%	1,080,000	12%	1,040,000	12%	1,050,000	12%
	Texas	990,000	11%	950,000	11%	960,000	11%	900,000	10%
	Florida	880,000	10%	830,000	9%	830,000	9%	810,000	9%
	New Jersey	380,000	4%	380,000	4%	370,000	4%	340,000	4%
	Illinois	380,000	4%	370,000	4%	380,000	4%	360,000	4%
	Massachusetts	210,000	2%	210,000	2%	200,000	2%	200,000	2%
	Washington	190,000	2%	180,000	2%	180,000	2%	180,000	2%
	Arizona	190,000	2%	180,000	2%	190,000	2%	210,000	2%
	Virginia	180,000	2%	170,000	2%	160,000	2%	160,000	2%
	Rest of states	2,260,000	25%	2,170,000	24%	2,100,000	24%	2,490,000	28%
	Total	9,130,000	100%	8,880,000	100%	8,880,000	100%	8,970,000	100%

Note: numbers are rounded to the nearest 10,000.

In the analysis below, we compare only those who recently naturalized to those who were eligible but had not yet taken that step. A comparison of those who were eligible to all those who had naturalized could be misleading, since research has shown shifts in income, education, and English language abilities among immigrants after naturalizing (Pastor and Scoggins 2012). For example, a finding of higher income among all naturalized observations would not necessarily be strong evidence that income is a significant driver for naturalization, as such economic gains could have occurred after gaining citizenship. To account for possible maturation bias and effects of naturalization that may change an immigrant’s social and human capital, we only include those individuals who naturalized within three years of the ACS survey, with the control group being those who were eligible over that period but did not naturalize.

Modeling Propensity to Naturalize

We utilize a series of binomial logit models to determine an eligible LPR’s probability to naturalize and to show how including our novel measure of family effects impacts naturalization compared to baseline models that include variables from previous empirical studies. In Model 1, we specifically estimate an equation where Y is the binary outcome of naturalization, H_i represents the set of human capital measures, and λ_t represents year-fixed effects:

Y i = \frac{1}{1 + e^{- (α + β H i + λ t + ε)}}

Our base Model 1 estimates the effects of individual characteristics on naturalization, including demographic variables and human capital measures. Our demographic predictors include gender, race/ethnicity, age at entry (linear and quadratic forms), years having been eligible for naturalization (logged), and number of children. Research on naturalization has found that certain demographic characteristics are associated with higher probability of naturalization, such as being a woman, whereas other characteristics like age at entry and years since becoming eligible to naturalize have non-linear effects (Yang 1994; Johnson et al. 1999). We control for age at entry, as research indicates that immigrants who arrive and attend school in the United States at a younger age are able to assimilate and learn English much easier than their older counterparts (National Academies of Sciences, Engineering and Medicine 2015; Waldinger 2021). To estimate the impact of human capital, we include educational attainment, employment status, occupational prestige, reported English proficiency, homeownership status, and household income (Yang 1994; Johnson et al. 1999; Aptekar 2015). The year-fixed effects are based on the underlying year of the 5-year sample, and their inclusion is an attempt to control for the ways in which naturalization can be affected in any given year by either political circumstances or the shifting backlog of applications that often occurs, for example, in an election year.

Model 2 builds from Model 1 by introducing specific place variables (P_i), in addition to measures of human capital and year-fixed effects:

Y i = \frac{1}{1 + e^{- (α + β H i + β P i + λ t + ε)}}

Here, we explore the origin-country dimensions outlined in H1, including the distance between an immigrant’s origin country and their current state of residence, whether dual citizenship is allowed between an immigrant’s origin country and the United States, whether their origin country is a Temporary Protected Status-designated (TPS) country or a refugee-sending country, and the origin country’s gross domestic product (GDP) per capita. We include all countries with a TPS designation during or prior to 2016, such as El Salvador and Honduras (US Citizenship and Immigration Services 2021). We identify refugee-sending countries, such as Vietnam and Cambodia, from data provided by the OIS at the Department of Homeland Security (Department of Homeland Security 2020).

Yang (1994) found that the probability of naturalizing increased, the further the origin country was from the host country, likely due to challenges of returning home associated with geographical distance. Immigrants who are allowed dual citizenship are expected to have greater odds of naturalizing, as costs associated with forfeiting origin-country citizenship are absent (Mazzolari 2009). Refugee and TPS status are included to measure political, physical, and social turmoil in an immigrant’s origin country, which may be indicative of their inability or unwillingness to permanently return (Portes and Rumbaut 2014; Mossaad et al. 2018). GDP per capita normalized using purchasing power parity (PPP) is an indicator of the economic opportunities available in the origin country. These variables measure general conditions that might deter immigrants from permanently returning and, thus, incentivize their stay in the United States as citizens.

Model 2 also includes the place-based attributes of the locales where immigrants resided at the time of ACS data collection and factors associated with H2. Place-based variables include the unemployment rate in the Metropolitan Statistical Area (MSA) and the political leaning of the state in which the observed individual resided. We include the MSA unemployment rate for immigrant adults, as some adults may naturalize it as a way to increase employment opportunities and earnings (Johnson et al. 1999; Pastor and Scoggins 2012; Aptekar 2015). The results of the US Presidential Election in 2012 are used as a proxy to measure the state’s general political leaning; such election results have been consistently used in political research to measure constituency ideology and attitudes, due to the measure’s relative simplicity, availability of data, and representation of actual — rather than simulated or imputed — constituency behavior and opinion (Leogrande and Jeydel 1997). The limitation of using US presidential election results to measure constituency ideology and attitudes is that it does not fully measure the nuances of politics, such as political conservatives who support immigration and have created important political opportunities for immigrants in the United States (Davidson 2015). However, it is also true that, in general, liberal-leaning states express more positive attitudes toward immigration and are more supportive of policies that promote citizenship (Krogstad 2015). A final place-based variable is the concentration of co-ethnic immigrants in a Public Use Microdata Area (PUMA), which indirectly measures ethnic enclaves and captures the mixed effects that might be expected from living in such a locale (Yang 1994; Menjívar 2000; Abascal 2017).

In Model 3, we add measures of family composition and status (Fi) to estimate the family effects discussed in H3. We include the spouse’s citizenship and immigration status, as well as variables that control for other naturalized or undocumented members in the family:

Y i = \frac{1}{1 + e^{- (α + β H i + β P i + β F i + λ t + ε)}}

Our dataset provides the years in which immigrants arrived in the United States, naturalized, and married their spouses. This information and the ability to link observations within the same family unit allow us to more accurately code spouses’ and adult family members’ citizenship and immigration status prior to their own naturalization. Immigrants with close ties with someone who has naturalized would have access to valuable information, whereas immigrants in mixed-status families may experience chilling effects that hinder their choice to naturalize (Aranda, Menjívar, and Donato 2014; Asad 2020).

In Model 4, we drop our specific place variables in favor of having origin-country (γ_c) and state residence fixed effects (δ_s):

Y i = \frac{1}{1 + e^{- (α + β H i + β F i + δ s + γ c + λ t + ε)}}

Such a test is designed to ensure that family effects are robust across specifications; like any baseline model predicting naturalization (e.g., Yang 1994; Johnson et al. 1999; Aptekar 2015), ours retains the human capital variables. In each model, we estimate the average impact a variable has on an immigrant’s propensity to naturalize through an odds ratio value by calculating the exponential relationship of the log-odds.

Results

Similar to previous studies (e.g., Yang 1994; Johnson et al. 1999; Jones-Correa 2001; Aptekar 2015; Waldinger 2021), we find that multiple individual and place-based factors drive naturalization in the United States. Our results also suggest that family dynamics are statistically associated with eligible immigrants’ odds of successfully naturalizing. More specifically, having naturalized family members and spouses significantly and positively improved eligible immigrants’ odds of naturalization, whereas the presence of undocumented family members and spouses had a large negative effect on eligible immigrants’ odds of naturalization — a novel finding that has not been fully explored in previous empirical studies. Estimates and significance of each predictor are presented in Table 2.

Table 2.

Estimated Effects on the Odds of Naturalization.

	(1)	(2)	(3)	(4)
	Model 1	Model 2	Model 3	Model 4

Man/male	0.867***	0.851***	0.886***	0.887***
	(0.007)	(0.007)	(0.008)	(0.008)
Family size	1.022***	1.007**	1.028***	1.040***
	(0.002)	(0.002)	(0.003)	(0.003)
Age at entry	0.975***	0.977***	0.979***	0.977***
	(0.001)	(0.001)	(0.001)	(0.001)
Age at entry (squared)	1.000***	1.000***	1.000***	1.000***
	(0.000)	(0.000)	(0.000)	(0.000)
Years eligible (log)	0.803***	0.843***	0.783***	0.816***
	(0.004)	(0.004)	(0.004)	(0.004)
Race (compared to non-Hispanic white)
Black	2.003***	1.268***	1.128***	1.245***
	(0.032)	(0.026)	(0.024)	(0.052)
Latinx	0.802***	0.825***	0.869***	1.012
	(0.010)	(0.014)	(0.015)	(0.048)
Asian/Pacific Islander	1.145***	0.799***	0.799***	1.088*
	(0.014)	(0.012)	(0.012)	(0.041)
Other or mixed race	1.359***	1.013	0.971	1.054
	(0.041)	(0.031)	(0.031)	(0.039)
Education (compared to less than high school degree)
HS degree or equivalent	1.101***	1.119***	1.098***	1.023
	(0.014)	(0.015)	(0.015)	(0.014)
Some college or AA	1.530***	1.561***	1.510***	1.380***
	(0.021)	(0.022)	(0.021)	(0.020)
Bachelor’s degree	1.540***	1.600***	1.608***	1.444***
	(0.024)	(0.025)	(0.026)	(0.024)
Higher than Bachelor	1.162***	1.235***	1.346***	1.188***
	(0.021)	(0.023)	(0.025)	(0.023)
English language proficiency (compared to “not at all”)
Not well	1.660***	1.620***	1.598***	1.593***
	(0.034)	(0.033)	(0.033)	(0.033)
Well	2.375***	2.360***	2.367***	2.386***
	(0.048)	(0.049)	(0.050)	(0.051)
Very well	2.401***	2.401***	2.446***	2.535***
	(0.050)	(0.051)	(0.053)	(0.055)
English only	1.375***	1.751***	1.822***	2.049***
	(0.031)	(0.041)	(0.043)	(0.052)
Employment (compared to employed)
Unemployed	0.931***	0.914***	0.856***	0.843***
	(0.019)	(0.018)	(0.018)	(0.018)
Not in labor force	0.775***	0.814***	0.790***	0.783***
	(0.009)	(0.009)	(0.009)	(0.009)
Household income (log)	1.000	0.998	0.987***	0.999
	(0.003)	(0.003)	(0.003)	(0.004)
Duncan socioeconomic index	1.002***	1.003***	1.004***	1.003***
	(0.000)	(0.000)	(0.000)	(0.000)
Homeowner	1.230***	1.310***	1.191***	1.217***
	(0.011)	(0.012)	(0.011)	(0.012)
Distance from country of origin (per 1,000 km)		1.011***	1.008***
		(0.002)	(0.002)
From TPS status country		0.716***	0.733***
		(0.014)	(0.014)
From traditional refugee-sending country		1.708***	1.488***
		(0.023)	(0.021)
GDP per capita PPP of country of origin (log)		0.723***	0.739***
		(0.004)	(0.005)
Dual citizenship allowed		1.196***	1.129***
		(0.013)	(0.012)
Reside in left-leaning state		1.272***	1.185***
		(0.014)	(0.013)
Percent of co-ethnic nationals in PUMA		0.994***	0.995***
		(0.001)	(0.001)
Unemployment rate in MSA		1.013***	1.008**
		(0.003)	(0.003)
Marriage status (compared to not married)
US-born spouse			0.812***	0.855***
			(0.012)	(0.012)
Naturalized spouse			1.811***	1.699***
			(0.023)	(0.022)
LPR spouse			0.513***	0.519***
			(0.008)	(0.008)
Undocumented spouse			0.138***	0.142***
			(0.004)	(0.004)
Naturalized family member (not spouse)			1.424***	1.306***
			(0.021)	(0.020)
Undocumented family member (not spouse)			0.631***	0.635***
			(0.010)	(0.010)
Year FE	Yes	Yes	Yes	Yes
Country-of-origin and state FE				Yes
Pseudo R-squared	0.0599	0.0801	0.1251	0.1410
Observations (unweighted)	415,182	415,182	415,182	415,182

Note: standard errors in parentheses. Coefficients are in odds ratio.

*p < .05, **p < .01, ***p < .001.

Individual Characteristics

Model 1 offers the baseline estimate for individual characteristics. Recalling that a coefficient greater than one implies higher odds of naturalization and that a coefficient below one indicates lower odds of naturalization, we can see that immigrant men, those who entered the United States at an older age, and those who had been eligible for naturalization longer were less likely to naturalize. Black immigrants showed higher odds of naturalizing, and Latinx immigrants showed lower odds of naturalizing; Asian/Pacific Islander immigrants showed higher odds in the baseline model, but this effect flips in subsequent models where we control for a specific place and family effects. These results suggest racial hierarchies in accessing citizenship in which immigrants of a certain race/ethnicity and religion can experience prolonged delays and disproportionate scrutiny, due to being stereotyped and discriminated against by USCIS (Ahluwalia 2014).

As expected, we find immigrants with more resources and greater human capital to be more likely to naturalize. Compared to those with less than a high school degree, immigrants with higher educational attainment, particularly some college or a college degree, had greater odds of naturalizing. We also find that English proficiency significantly impacted naturalization outcomes, with the least likely to naturalize being those who did not speak English at all. Compared to those who did not speak English at all, those who reported any proficiency with English had much greater odds of naturalizing, with those who spoke English at least “well” having the highest likelihood.

Relative to employed immigrants, immigrants who were unemployed had lower odds of naturalizing, and those not in the labor force had even lower odds. The Duncan Socioeconomic Index, a constructed measure of occupational prestige based on income level and educational attainment (Duncan 1961), was associated with slightly higher odds of naturalizing among employed immigrants. Household income was not statistically significant in the baseline model, perhaps because income was associated with many co-variates; it was statistically significant with a negative effect in Model 3 when we offer our full model controlling for family effects (Yasenov et al. 2019). As expected, owning a home prior to naturalization was also associated with greater odds of naturalizing.

Place-Based Attributes

In Model 2, we include place-based attributes that were omitted from Model 1 and test for H1 and H2. In testing H1, we confirm Yang’s (1994) earlier findings that greater geographical distance from one’s origin country is associated with greater odds of naturalizing. Similar to Mazzolari (2009), we find that immigrants from countries that allowed dual citizenship had greater odds of naturalizing. To analyze the impact of economic conditions on an eligible immigrant’s odds of naturalization, we use GDP per capita adjusted by PPP and find that immigrants from wealthier countries with greater economic opportunities had lower odds of naturalizing.

Using TPS and refugee-sending designations as proxies for the social, economic, and political conditions in immigrants’ origin countries, we find mixed results. Immigrants from a country that is traditionally refugee-sending had greater odds of naturalizing, whereas immigrants from TPS-designated countries had lower odds. This significant increase in odds for immigrants from refugee-sending countries may be related to several factors, including an increased network of co-ethnic nationals and family members who had already gone through the naturalization process and additional federal resources specifically designated for refugees (Mossaad et al. 2018). In contrast, immigrants from TPS-designated countries may have unobserved characteristics that are associated with lower rates of naturalization, such as a limited network of naturalized immigrants due to the liminal legality associated with TPS (Menjívar 2000; Abrego 2014). We recommend that this issue receive further analysis with particular attention to the context of reception immigrants from TPS-designated countries experience, compared to those from traditionally refugee-sending countries.

As for H2, we find that immigrants residing in left-leaning states had greater odds of naturalizing. We also find the concentration of co-ethnic nationals in a PUMA — a place-based measure of network effects — slightly reduced an immigrant’s odds of naturalizing. In particular, a 10-percentage point increase in the percent of co-ethnic nationals reduced the odds of naturalizing by 0.5 to 0.6 percent. Though this effect is relatively small, it contradicts earlier findings on the importance of information exchange and networks among immigrants with shared identities and experiences (Abascal 2017). It is, however, consistent with arguments that clusters of immigrants with similar ethnic backgrounds may be less connected to outside resources and less likely to naturalize (Woroby and Groves 2016). This point may need further analysis, in particular, expanding the definition of co-ethnic nationals to other ethnic groups who share similar cultural backgrounds (e.g., language). Finally, our results show that unemployment in the MSA was positively associated with an eligible immigrant’s odds of naturalization, perhaps because stressed economic circumstances create incentives to be able to more easily access the social safety net and other economic opportunities (e.g., public sector jobs).

Family Effects

Of notable significance in our analysis and novel to the empirical literature on naturalization (e.g., Yang 1994; Jones-Correa 2001; Aptekar 2015; Abascal 2017; Waldinger 2021), we find that family dynamics significantly influenced naturalization. In testing H3, we find that being married improved the odds of naturalization, but this effect was driven entirely by immigrants who were married to someone who had already naturalized. In contrast, having an undocumented spouse dramatically reduced the probability of naturalizing, even compared to an unmarried individual. What might seem to be an unexpected finding at first is that being married to a US-born citizen actually lowered the odds of naturalization, compared to being unmarried, but upon reflection, having a US-born spouse may confer a sense of security without imparting any information around naturalization that comes from being married to a naturalized spouse (Menjívar 2000; Abrego 2014; Gomberg-Muñoz 2017).

Spousal information is explicitly elicited in the N-400; what about the impact of other relatives? As it turns out, having a naturalized adult in the family other than a spouse improved the odds of naturalization, but having an undocumented family member other than a spouse reduced the odds. These findings support both our hypotheses on the importance of having close ties to someone with experience navigating the naturalization process and the significant and negative spillover effects on naturalization when an undocumented spouse or family member is present.

Model 4 explores a methodological issue. Our models explicitly specify what we think the place-based effects will be: for example, we assume that less distance from one’s origin country will reduce the likelihood of naturalization while living in a left-leaning state will increase the likelihood. This approach allows us to mix geographies, including state-level effects, as well as those associated with an MSA (unemployment rate among immigrants) and with a more compact neighborhood (the percent of co-ethnic nationals in a PUMA). Another approach would come at the expense of specific hypotheses and varying geographic scales but is also common in the literature (e.g., Johnson et al. 1999; Cheong 2021; Waldinger 2021) — namely, including fixed effects to control for underlying differences across state residence and origin country, including differences in rights associated with dual citizenship (e.g., some nations revoke voting rights for citizens with multiple citizenships) (Sejersen 2008). There are few shifts in the baseline model when taking this approach. For example, the Latinx effect becomes insignificant, and the Asian effect becomes positive, likely reflecting the heterogeneity within racial groups and associated with specific home countries. Crucial to this article, the family effects central to this analysis remain relatively similar to our results from Model 3 in terms of directionality, size, and significance. As expected, Model 4 has higher explanatory power, as it controls for unobserved heterogeneity across origin country and state residence.

Discussion and Conclusion

Consistent with previous studies on naturalization (e.g., Yang 1994; Johnson et al. 1999; Aptekar 2015), our results show that immigrants with more human capital, including stronger English proficiency and higher educational attainment, had greater odds of gaining citizenship. These skills help eligible immigrants seeking citizenship in the United States navigate the cumbersome naturalization process, such as the application, the English-proctored interviews, and the US civics and history exam (Aptekar 2015). We also find that place-based attributes simultaneously influenced immigrants’ decisions and ability to naturalize. For example, immigrants coming from countries with precarious conditions may be disincentivized to return permanently and, instead, turn to US citizenship as a way to secure their stay in the country and access to public benefits (Rosenblum and Brick 2011; Portes and Rumbaut 2014). Receiving locales are also important, as we find that immigrants’ odds of naturalizing increased in places that were more immigrant-friendly in terms of politics, but the odds reduced when the percent of co-ethnic nationals in a geographic neighborhood increased.

Contributing to the literature on naturalization and immigrant integration (e.g., Liang 1994; Yang 1994; Bloemraad 2006; Aptekar 2015; National Academies of Sciences, Engineering and Medicine 2015), our research finds novel empirical evidence suggesting the significant effects of family structure on naturalization. These findings are made possible by our ability to estimate which noncitizens in our sample were likely to be undocumented, a feature that also allows us to focus on those who were truly eligible to naturalize. Our results show that having a naturalized spouse or family member positively impacted an immigrant’s propensity to gain citizenship. In contrast, having an undocumented spouse or family member present was associated with significantly lower odds of naturalizing.

We find and argue that the decision and ability to successfully naturalize in the United States are simultaneously shaped by individual characteristics and complex contextual factors, including place-based attributes and family structure. To effectively address the barriers to naturalization previously discussed, policies may need to concurrently address multiple mechanisms that are delaying eligible immigrants’ abilities (e.g., human capital) and decisions (e.g., fear for undocumented immigrant family members) to naturalize. For example, just as standardizing and expanding the fee waiver and fee reduction program helped improve naturalization outcomes for low-income immigrants in the United States (Yasenov et al. 2019), allowing for more generous language exemptions could reduce barriers to citizenship for immigrants with limited English proficiency. Additionally, having a more welcoming political environment and strengthening community organizations that can help immigrants prepare for their citizenship interview and exam would also help mitigate certain barriers to naturalization (Aptekar 2015).

In line with our novel empirical findings on family effects, immigrant-serving organizations and advocates can improve naturalization rates by strategically prioritizing and reaching immigrant families without a naturalized member. If at least one family member gains citizenship through naturalization, there is likely to be positive spillover effects for other eligible immigrant family members through pooled resources and information sharing. In the same regard, promoting naturalization among immigrant women, whom we find to have greater odds of naturalization, can create a ripple effect in paving pathways to citizenship for the rest of the family.

However, it is also imperative to understand that enhancing the human capital and place-based factors may not be enough if immigrants worry that the naturalization process may endanger, rather than protect, their families. Service providers and policymakers should consider how to assist families with undocumented members in a way that ensures them their security and safety, including advocating for the N-400 form to be revised so that applicants are not required or pressured to disclose family members’ immigration status in a way that threatens their safety. Legislation providing lawful status or pathways to citizenship for currently undocumented immigrants could also mitigate negative spillover effects that hinder pathways to citizenship for eligible-to-naturalize immigrants with undocumented family members.

Encouraging naturalization has long been a point of unity among those on all sides of the broader immigration debate (Collins 2021). Gaining citizenship provides individual benefits and aligns with long-held notions that a nation of immigrants can and should fully and completely integrate newcomers — e pluribis, unum (Pastor and Scoggins 2012; Aptekar 2015; Enchautegui and Giannarelli 2015; National Academies of Sciences, Engineering and Medicine 2015). During the Trump administration, this general agreement fell victim to polarized immigration politics, and the backlog of citizenship applications grew (Jayapal and Pastor 2018). Clearing the backlog of naturalization applications and creating an encouraging atmosphere for naturalization require a comprehensive understanding of the determinants that drive or hinder immigrants’ access to citizenship. This article provides some guidance, but perhaps its most profound implication is that the regularization of those who are undocumented and the naturalization and integration of those who are eligible are not disconnected issues in the United States or other countries with a sizeable and rising share of undocumented immigrants and mixed-status families (Del Real 2022). Encouraging naturalization will require a policy push on multiple fronts if we are to forge a more equitable and effective approach to immigrant integration.

Footnotes

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article. This work was supported by the Carnegie Corporation of New York, Bank of America, California Wellness Foundation, California Endowment, James Irvine Foundation.

ORCID iD

Manuel Pastor

Notes

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