Documenting Their Decisions: How Undocumented Students Enroll and Persist in College

Abstract

The absence of federal support leaves undocumented students reliant on state policies to financially support their postsecondary education. We descriptively examine the postsecondary trajectories of tens of thousands of undocumented students newly eligible for California’s state-aid program, using detailed application data to compare them to similar peers. In this context, undocumented students who apply and are eligible for the program use grant aid to attend college at rates similar to their peers. Undocumented students remain more likely to enroll in a community college rather than attend a broad-access 4-year college and have higher exit rates from 2-year colleges. However, undocumented students are equally likely to attend the more selective University of California system and across 4-year public colleges have persistence rates similar to their peers, showing that those who do attend 4-year colleges perform well.

Keywords

descriptive analysis educational policy higher education immigration/immigrants postsecondary education regression analyses

Introduction

Undocumented students have a legal right to a K–12 education but have not been afforded equal access to pursue a postsecondary degree (Plyler v. Doe, 1982). Roughly 100,000 undocumented immigrants graduate from high school each year, yet only 5%–10% enroll in college (Richards & Bohorquez, 2016; Zong & Batalova, 2019). Although many factors can inhibit college attendance, one barrier is clear: an inability to access financial aid (Abrego, 2006; Contreras, 2009; Gonzales, 2010). For example, providing undocumented students In-State Resident Tuition (ISRT) increases enrollment, persistence, and degree completion (Conger & Turner, 2017; Darolia & Potochnick, 2015; Flores, 2010; Kaushal, 2008).

This project quantitatively studies the postsecondary enrollment patterns of California’s undocumented students who became eligible for its state-aid program. In 2013–2014, California became one of the first states to offer state aid to undocumented students via the Cal Grant, a generous program that fully subsidizes 4-year college tuition and provides cash subsidies for community college attendance. Undocumented students apply by completing the California Dream Act Application (CDAA), which is substantively similar to the Free Application for Federal Student Aid (FAFSA), and we use rich individual-level data on all aid applicants to track students’ postsecondary pathways.

This article presents our observations of undocumented students in a period when the social environment was becoming relatively more supportive, as observed by increased access to financial aid, reductions in some legal barriers (e.g., increased ability to work through Deferred Action for Childhood Arrivals [DACA]), and more sympathetic presidential rhetoric. Our question is “In the context of a relatively more welcoming environment, how different are the postsecondary pathways of undocumented students relative to their peers?” It is important that we consider financial and other barriers to enrollment these students still face (e.g., prohibited from receiving the federal Pell Grant and a social climate that varies geographically in its support for undocumented students). We see our results—which control for many key background characteristics—as an accounting of the remaining differences between undocumented students and other residents in a setting where significant financial barriers (although clearly not all) have been removed. We believe that these results provide important insights into where additional policy initiatives may need to occur to support undocumented students.¹

We investigate two questions:

How do the college-going preferences, attendance, persistence, and completion patterns of state aid–eligible undocumented high school students differ from their peers?

Do we observe evidence of “mismatch,” wherein state aid–eligible undocumented students who attend more selective institutions have worse academic outcomes than their peers?

We find that undocumented students who are eligible for the Cal Grant are more likely to enroll than are their peers. Even though all Cal Grant students have their tuition fully covered, undocumented students are more likely to enroll in community colleges rather than 4-year colleges, and those who attend community college are also more likely to drop out. Increased community college enrollment comes at the expense of enrolling in a less “selective” 4-year California State University (CSU), as undocumented students enroll in the more “selective” University of California (UC) system at similar rates. Differences in enrollment patterns are likely driven by application choices rather than differences in acceptance rates, as undocumented students are more likely to list fewer colleges on their aid applications and predominately focus on community colleges. Yet we find little evidence of “mismatch” in 4-year colleges, as undocumented students who enroll in the CSU or UC system persist at similar or better rates than their peers and—although this next point is subject to a number of caveats—are equally likely to earn a degree.

These new data improve on previous work in a number of ways. Ours is the first quantitative study that uses state-level data on undocumented students who apply for state aid, unlike previous studies that observe earlier resident tuition policies, smaller samples from a few colleges, or use nationally representative data that can only proxy for undocumented status (Bozick et al., 2016; Darolia & Potochnick, 2015). We track undocumented students beginning in high school, whereas previous studies often observe students who have already enrolled in college (Conger & Chellman, 2013; Ngo & Astudillo, 2019). Understanding differences in how undocumented students make the high school–to-college transition is important for understanding potential “mismatch” within this community, which is known to affect degree attainment (Belasco & Trivette, 2015; Black et al., 2015).

More work is needed to understand the enrollment decisions of undocumented students, as those who attend 4-year colleges in our study persist similarly to their peers, in contrast to the challenges observed in the 2-year environment. Although prior studies have shown lower levels of 4-year enrollment for undocumented students, we show significant variation in the types of 4-year colleges attended, which has not been previously observed and has implications for postsecondary and labor market success (Bleemer, 2021). These findings suggest that the educational context plays a huge role in undocumented students’ success. In the high school context, more efforts can be made to encourage undocumented students to consider a wider set of potential colleges, as some who attend community college may benefit from choosing a 4-year college instead. Yet these results reinforce the importance of the college context as well, as the persistence of undocumented students is strongly determined by the sector of attendance. These results raise questions about how best to ensure that the broader social conditions are in place to maximize the postsecondary success of undocumented students.

Literature Review

Among the barriers to college enrollment and success of undocumented students, cost is consistently rated as a key concern (Abrego, 2006; Contreras, 2009; Gonzales, 2010, 2015; Pérez, 2010). At the core of Perna’s (2006) model of college choice is the human capital theory that students will be motivated to invest in their own education if the perceived benefit outweighs the cost (Becker, 2009; Contreras, 2009; Hossler et al., 1989, 1999). Financial aid can promote educational attainment by relieving short-term credit constraints, alleviating behavioral barriers, or reducing other costs that often prevent students from earning a degree (Nguyen et al., 2019). In addition, aid may alter the type of college a student selects, with prior research showing that enrolling in more “selective” colleges that are nominally more expensive and have more resources per pupil increases graduation rates (Deming & Walters, 2017; Zimmerman, 2014).

Undocumented students have fewer financial-aid options than their peers, and these short-term costs could negatively affect long-term educational attainment (Abrego, 2006, 2008; Conger & Turner, 2017; Contreras, 2009; Gonzales, 2010). States have been at the forefront of alleviating these financial challenges, given mostly unsuccessful legislation for federal immigration reform, with about 20 states currently offering ISRT and at least 11 states offering state financial aid to undocumented students (Morse & Mendoza, 2015). ISRT and other financial-aid policies have positive effects on enrollment, primarily by increasing community college participation rates (Amuedo-Dorantes & Sparber, 2014; Kaushal, 2008; Ngo & Astudillo, 2019). Yet even with this support, undocumented students often have to work more hours and reduce their course loads, and they cite dissatisfaction with their potential postgraduation employment options as a key reason for leaving (Terriquez, 2015). Although DACA is one federal initiative that could theoretically open doors to higher education by securing the possibility of future employment, preliminary evidence suggests that it may have decreased higher-education participation, as individuals were more likely to pursue newly available legal employment (Amuedo-Dorantes & Antman, 2017; Hsin & Ortega, 2018).

However, financial aid might not be sufficient to equalize postsecondary outcomes between undocumented students and their peers if nonfinancial barriers to postsecondary education are higher for undocumented students. Perna’s (2006) model of college access and choice notes layers that must be considered in students’ postsecondary decisions: individual habitus; school and community context; the higher-education context; and the broader, social, economic, and policy contexts. The first layer, individual habitus, reflects the influence of students’ background characteristics on their postsecondary decisions. One key finding is that undocumented students who attend college are, on average, more academically prepared than are their peers (Hsin & Reed, 2020). This result is due in part to differences in the college-selection process, as undocumented students may “undermatch” (i.e., their academic credentials would allow them to attend a college that is more selective than the one in which they enroll), as they rely on social and family networks with less access to information, time, and money that can propel students into more selective colleges (Abrego, 2006, 2011). Postsecondary decisions are also influenced by the choices of older siblings and peer networks, which can reinforce enrollment in more geographically proximate colleges (Altmejd et al., 2021; Pérez & McDonough, 2008).

Perna (2006) also identifies the community, high school, and postsecondary contexts as key vehicles to support undocumented students’ needs. School personnel can influence postsecondary choices via personal connections, mentorship, or technical knowledge of the postsecondary processes needed to successfully apply and enroll (Gonzales, 2010; Nienhusser, 2013; Pérez, 2010; Pérez & McDonough, 2008; Suárez-Orozco et al., 2015; Sulkowski, 2017). School counselors can provide counseling tailored to undocumented students and their parents, which can create a supportive setting by helping students identify colleges that have embraced undocumented students and instilling advocacy skills to boost parents’ confidence in taking a proactive role in their child’s postsecondary education (Chen et al., 2010; Groce & Johnson, 2021; Morrison & Bryan, 2014; Perez, 2010; Roth, 2017). At the same time, the higher-education context can influence undocumented students’ college choices and persistence through the institutions’ climate, which can affect students’ perceptions of institutional prejudice or social belonging within the institution (Cabrera et al., 1999; Locks et al., 2008). College campuses are not always perceived as welcoming places for undocumented students, and undocumented students frequently also encounter faculty, administration, and staff who are misinformed about state and national policies that might affect their immigration status (Bjorklund, 2018; Gonzales, 2008; Muñoz, 2016; Muñoz & Maldonado, 2012; Terriquez, 2015). Even though many undocumented students are more likely to consider 2-year colleges, which have flexible admission and enrollment policies that better fit undocumented students’ need to work and support their family, they still find difficulties within this system, as there are differences in the levels of conformity, ease, and understanding with respect to serving the undocumented population (Benitez & DeAro, 2004; Nienhusser & Espino, 2017; Terriquez, 2015).

The social, economic, and policy contexts in which undocumented students experience college choice and enrollment also play roles in their college decisions (Perna, 2006). Putting undocumented students on more equal footing by offering state aid that fully covers 4-year college tuition provides an important context for examining undocumented student enrollment. Although our data do not allow us to explicitly test the causal role of policy climates, undocumented students at the time of this study were considering college in a period when the social environment was becoming relatively more supportive, including a slightly more welcoming state environment (e.g., new policies made undocumented individuals eligible to access driver’s licenses or practice law, for example), along with reductions in some federal legal barriers (e.g., DACA) and more sympathetic presidential rhetoric.

California Policy Background and the Dream Act

California has roughly one quarter of the nation’s undocumented high school graduates at about 27,000 undocumented seniors annually (Zong & Batalova, 2019). At any one point, the UC, CSU, and community college systems enroll approximately 4,000, 9,500, and 50,000–70,000 students, respectively (Zaidee, 2019). California began providing ISRT to undocumented students in 2002 but, following the passage of DACA in 2012, passed its own Dream Act to allow undocumented students to apply for the Cal Grant in 2013–2014. (Undocumented Cal Grant applicants are likely DACA-eligible, given the similar age and residency requirements.) The Dream Act also allows undocumented students to use the California College Promise Grant (formerly “BOGS fee waiver”), which waives community college tuition for low-income students. Simultaneously, California passed other initiatives, such as access to driver’s licenses, that lower barriers that undocumented students face in the transition to work and college.

The Cal Grant is a need- and merit-based program administered by the California Student Aid Commission (CSAC). Low- and middle-income students must have a high school grade point average (GPA) of at least 2.0 or 3.0, respectively. Income status varies by year, family size, and dependency status. For example, a dependent student in a family of four in 2013–2014 was considered to be low- and middle-income if their application reported adjusted gross income below $43,700 or $83,100, respectively. In practice, essentially all undocumented applicants fall into the low-income designation.

The Cal Grant offers two financial benefits. One is full tuition and fees at in-state public 4-year colleges (CSU or UC). Annual tuition rose during the Great Recession to $5,472 and $11,160, respectively, in 2013–2014, but it did not rise over the time period studied in this article. Students can receive an annual tuition subsidy of $9,084 to attend private, nonprofit colleges. The Cal Grant does not cover community college tuition, as these monies are available via the California College Promise Grant that became available to undocumented students at the same time; we cannot observe Promise Grant receipt. The second benefit is an alternative cash “subsistence award” of approximately $1,500 per year, which students are encouraged to use for books or other expenses. This award is enough to roughly cover full-time community college enrollment.

Cal Grant applicants must complete the FAFSA and a one-page GPA verification form (see Online Appendix Figure A1) by March 2. Undocumented students complete the CDAA rather than the FAFSA, although it asks similar questions (see Online Appendix Figure A2).

Data

Cal Grant Applicants

Our data include all FAFSA and CDAA applicants for 2013–2014 through 2015–2016 (i.e., 2013–2015 cohorts) who were Cal Grant–eligible (i.e., met GPA and income requirements). We consider any student who completes the state CDAA application to be undocumented, whereas students who submit the FAFSA are considered to be legal residents; although it is possible that this proxy for undocumented status may contain some error, it is likely to be quite low, particularly as we focus on students who have been income- and GPA-verified as Cal Grant–eligible. Cal Grant applications annually identify more than 6,000 undocumented and 125,000 legal residents. We identify high school characteristics by matching the school listed on the GPA verification form to records from the Common Core of Data (CCD).

To measure postsecondary preferences and intentions, we rely on two sources of data provided by students on their financial-aid form. The first is a list of up to 10 colleges to which students are sending their financial information, which we aggregate into four sectors: in-state community college (CC, or “2-year college” enrollment), CSU, UC, and private, nonprofit colleges (e.g., a student might list three CCs, two CSUs, and no other colleges).² The second measure is the type of degree they intend to earn (“What college degree or certificate will you be working on when you begin the school year?”). Although this question offers a number of options, we aggregate values into bachelor’s, associate, or other, with the first two values constituting most of the responses.

We measure postsecondary attendance based on CSAC’s financial payment data made on behalf of students to these institutions. We classify enrollment into the same four sectors (CC, CSU, UC, and private nonprofit). A student is considered to have enrolled if they receive any state-aid payment made to that postsecondary sector during the academic year.³ These data are highly accurate, as they are tracked through Social Security Numbers (SSNs) or a unique CDAA ID, but there are limitations: (a) students may enroll in college but have no payment if they attend out of state, a for-profit college, or less than half-time, or if they enroll but drop out quickly before the payment transfers; (b) students may enroll in college but place the award on hold (usually to support later transfer from a 2-year to a 4-year college); and (c) the award expires after 4 years and cannot identify whether a student earned a degree.

In additional analysis, we match applicants to the National Student Clearinghouse (NSC), which identifies enrollment and degree completion from most colleges. Ultimately, we have concerns regarding the accuracy of the NSC match, although the results are broadly similar to data from Cal Grant payments; we discuss these results briefly in the text (refer to Online Appendix B for further details).

Table 1 provides descriptive statistics for the full sample, disaggregated by FAFSA and CDAA (undocumented) students. Average income for CDAA students ($21,400) is lower than that of FAFSA students ($36,200). Only 10% of undocumented students identify having a parent with a college degree, compared to 36% of their peers, although the GPA and gender composition are similar for both groups. Undocumented applicants are more likely to live in cities (52% vs. 42%) and attend schools with a higher proportion of free- and reduced-lunch students (66% vs. 56%) and Hispanic students (69% vs. 54%). Online Appendix Table 1 provides the same descriptive characteristics but disaggregated by cohort years, to examine trends over time.

Table 1

Summary Statistics, FAFSA and CDAA Applicants

	FAFSA students		CDAA / Undocumented students
	Mean	Standard deviation	Mean	Standard deviation
Demographics
High school GPA	3.11	(0.54)	3.00	(0.53)
Family income (in 10,000s)	3.62	(3.45)	2.14	(1.65)
Family size	4.09	(1.55)	4.75	(1.77)
Female	0.60	(0.49)	0.60	(0.49)
Age	18.59	(0.78)	18.79	(0.87)
Parent education (college degree)	0.36	(0.48)	0.10	(0.30)
Dependent	0.96	(0.19)	0.98	(0.14)
High school characteristics
School size	1992.20	(896.92)	1835.41	(916.52)
Located in city	0.42	(0.49)	0.52	(0.50)
Located in town	0.05	(0.22)	0.05	(0.22)
Located in suburb	0.42	(0.49)	0.36	(0.48)
Located in rural	0.05	(0.22)	0.04	(0.20)
Free- or reduced-lunch students	0.56	(0.25)	0.66	(0.22)
% of school population that is Black	0.07	(0.09)	0.06	(0.08)
% of school population that is Asian	0.13	(0.16)	0.08	(0.11)
% of school population that is Hispanic	0.54	(0.27)	0.69	(0.24)
% of school population that is White	0.23	(0.22)	0.13	(0.17)
N	379,501		19,078

Notes. The sample includes students who submitted either the Free Application for Federal Student Aid (FAFSA) or the California Dream Act Application (CDAA; i.e., undocumented) who were Cal Grant–eligible (i.e., met GPA and income requirements) and entering college in 2013–2014 through 2015–2016. High school identifiers and grade point average (GPA) come from Cal Grant GPA verification forms and are matched to National Center of Education Statistics’ Common Core of Data (CCD).

Methodology

We compare differences in postsecondary patterns between CDAA and FAFSA students using multivariate regression analysis based on rich application data. Our model is:

Y_{i s t} = β_{0} + β_{1} U n d o c u m e n t e d_{i s t} + X_{i t} + π_{s} + θ_{t} + ε_{i s t}

(1)

$Y_{i s t}$ are the outcomes of interest (e.g., sector of initial enrollment) for student i in high school s in year t. Our focus is a dummy variable for undocumented students that identifies differences in postsecondary outcomes after controlling for individual-level covariates ( $X_{i t}$ ; GPA, income, age, family size, and dummies for gender, college-educated parents, dependency status) and including high school ( $π_{s}$ s) and cohort fixed effects ( $θ_{t}$ ). The inclusion of school fixed effects eliminates many potential confounders, such as the stable elements of the composition of the neighborhood, teacher quality, peers and their college-going preferences, school-level supports, and geographic distance to college.⁴

We also examine heterogeneous effects by running regressions similar to equation (1) but for subsets of students (e.g., high vs. low GPA, urban vs. rural, or early vs. later cohorts). We also examine how the pool of undocumented applicants changes as the program rolls out by estimating the following equation over the first 3 years, using the first cohort as the baseline value:

\begin{array}{l} X_{i s t} = β_{0} + β_{1} U n d o c u m e n t e d * {(y e a r = 2014)}_{i s t} \\ + β_{2} U n d o c u m e n t e d * {(y e a r = 2015)}_{i s t} + θ_{t} \\ + U n d o c u m e n t e d_{i s t} + ε_{i s t} \end{array}

(2)

Equation (2) tests for differences in applicant characteristics across cohorts, without additional controls.

Results

Postsecondary Intentions

Undocumented students who apply for aid have a more constrained postsecondary focus than do their peers, as they consider fewer institutions, are more likely to focus on community colleges over 4-year colleges, and report stronger interest in pursuing an associate degree than do FAFSA-submitting students (see Table 2). Raw differences show that undocumented students list 3.9 colleges on average, relative to 4.2 colleges for FAFSA students, but after we adjust for background differences, this gap expands slightly, such that undocumented students list 0.5 fewer colleges than do similar peers. These differences are driven by the fact that undocumented students are 11 percentage points (pp) more likely to list only one college on their financial-aid form; they are 8pp less likely to list four to 10 colleges, even though 41% of their peers do so (Online Appendix Table 2).

Table 2

Differences Between FAFSA and CDAA (Undocumented) Students in College Listings and Degree Aspirations on Financial-Aid Applications

	Baseline rate for FAFSA students	Unadjusted model	High school fixed-effect model
College listings
Average number of colleges	4.19	−0.253** (0.021)	−0.494** (0.020)
Only 2-year colleges	23.2%	0.147** (0.002)	0.095** (0.003)
Only 4-year colleges	51.3%	−0.119** (0.003)	−0.054** (0.003)
Both 2- and 4-year colleges	19.2%	0.025** (0.002)	−0.017** (0.003)
Degree aspirations
Bachelor’s degree	64.4%	−0.011+ (0.006)	−0.010 (0.006)
Associate degree	20.2%	0.067** (0.005)	0.082** (0.005)
Undecided	12.6%	−0.047** (0.004)	−0.063** (0.005)
Controls			X
High school fixed effects			X
N		398,579	398,452

Notes. Results show differences in college listings and degree aspirations on the Cal Grant application between Free Application for Federal Student Aid (FAFSA) and California Dream Act Application (CDAA; undocumented) students in the 2013–2015 cohorts. Student-level controls include grade point average (GPA), income, age, family size, sex, having college-educated parents, dependency status, and application year. Data on degree aspiration are only available for the 2013 cohort (n = 126,738); the three outcomes shown represent 97% of observed student responses.

p < .10. ^*p < .05. ^**p < 0.01.

Regression models show that the types of colleges listed are also substantially different, as undocumented students are 10pp more likely to list only 2-year colleges, 5pp less likely to list only 4-year colleges, and 2pp less likely to list a mix of 2- and 4-year colleges. Distance plays a role but does not appear to be the primary determinant. Undocumented students are actually more likely to send their information to the closest community colleges and other community colleges that are farther away; they are slightly less likely to list the closest CSU or UC (2–3pp) or farther CSU or UC colleges (3–4pp; Online Appendix Table 2).

Although undocumented students are equally likely to aspire to a bachelor’s degree, they are 8pp more likely to report that they will be pursuing an associate degree, and they are less likely to be undecided about the degree program they intend to pursue. Although we cannot be certain why this is the case, it may be that undecided students prefer to keep their options open and so are more likely to attend a 4-year college; alternately, it may be that undocumented students intending to enroll in college are more certain about their choices or less comfortable stating uncertainty on key government forms.

College Enrollment

Shifting to actual enrollment, as proxied by state-aid payments, undocumented students are 10pp more likely to attend 2-year colleges (baseline for FAFSA students is 17%; see Table 3). This difference comes mostly from a 5pp lower likelihood of enrolling in the CSU system (baseline of 21%), along with a 2pp lower likelihood of nonprofit college enrollment (baseline of 5%). Yet undocumented students are almost equally likely to enroll in the UC system, even though these colleges have higher admission standards and financial costs and are (potentially) farther from home.⁵

Table 3

Differences Between FAFSA and CDAA (Undocumented) Students’ Enrollment and Persistence Patterns

	First year	Second year	Third year	Fourth year
California Community College (CCC)	0.097**(0.003)	0.054**(0.002)	0.019**(0.002)	0.002+(0.001)
Baseline rate for FAFSA students	17.4%	11.0%	6.9%	2.8%
California State University (CSU)	−0.047**(0.003)	−0.033**(0.003)	−0.025**(0.003)	−0.025**(0.003)
Baseline rate for FAFSA students	21.2%	17.0%	15.8%	15.9%
University of California (UC)	−0.002(0.002)	−0.001(0.002)	−0.001(0.002)	−0.004+(0.002)
Baseline rate for FAFSA students	12.5%	11.1%	11.1%	11.0%
Non-profit private colleges	−0.020**(0.002)	−0.018**(0.001)	−0.016**(0.001)	−0.016**(0.001)
Baseline rate for FAFSA students	4.6%	3.9%	3.7%	3.5%
Used Cal Grant	0.023**(0.004)	0.000(0.003)	−0.025**(0.003)	−0.044**(0.003)
Baseline rate for FAFSA students	56.3%	43.3.%	37.7%	33.4%

Notes. N = 398,452. Results show differences in the enrollment and persistent patterns of undocumented students in the 2013–2015 cohorts when comparing California Dream Act Application (CDAA) to Free Application for Federal Student Aid (FAFSA) students and controlling for background characteristics and high school fixed effects. Student-level controls include grade point average (GPA), income, age, family size, and dummies for sex, having college-educated parents, dependency status, and application year. For-profit colleges are not shown because very few profit institutions are eligible for receipt of the Cal Grant.

p < .10. ^*p < .05. ^**p < 0.01.

Summing their postsecondary choices, undocumented students are 2pp more likely to use the Cal Grant (last row of Table 3). Thus, the overall enrollment decisions of undocumented students are not much different than those of their peers in the context of generous state support, in sharp contrast to enrollment gaps typically observed in prior studies (Darolia & Potochnick, 2015). State payment data cannot observe out-of-state enrollment, but NSC data on FAFSA students show that only 2% enroll out of state (FAFSA-submitting Cal Grant applicants are generally lower-income and less likely to choose this option). Removing students who list an out-of-state school leaves results unchanged (Online Appendix Table 3).

College Persistence

Postsecondary research has been concerned with academic “mismatch”—generally, when students with weak academic credentials attend an academically rigorous college outside their capabilities—although most studies find that attending a more selective institution increases graduation rates (e.g., Bleemer, 2020). We do not find that potential “mismatch” appears to drive persistence rates in college. First, and in line with prior research, we find that undocumented students who attend community colleges are actually more academically prepared than are their peers (Hsin & Reed, 2020). Online Appendix Figure 1 presents box plots showing median, 25th, and 75th percentile high school GPAs for students attending each of the four postsecondary sectors. Median GPA of community college students is 2.81 and 2.71 for undocumented students and their peers, respectively; in contrast, undocumented students in 4-year colleges have marginally lower GPAs than their peers, although these differences are even smaller in magnitude (e.g., median GPA at UC is 3.64 for undocumented students and 3.69 for their peers).

Even though the differences in GPA would favor relatively higher undocumented student success in 2-year colleges and lower success in 4-year colleges, we find that the opposite pattern holds (see Table 3). Undocumented students in 4-year colleges have persistence rates in the 4-year sector that are similar or even stronger than those of their peers; this result may be surprising in light of the additional financial and social challenges that undocumented students may face in these environments. Undocumented students are similarly likely to attend UC the first year and to be enrolled in year 4, thus showing equal persistence rates to their peers. Although undocumented students are almost 5pp less likely to attend CSU, they are only 3pp less likely to be enrolled in CSU after 4 years, so they actually are less likely to drop out over time. Figure 1 illustrates these persistence patterns by plotting the raw attendance values for CSU enrollment (there are minimal differences between raw values and covariate-adjusted results for these estimates; Online Appendix Figure 2 shows similar results for UC enrollment).

Figure 1.

Unadjusted differences in Cal Grant usage in the California State University System for FAFSA and CDAA (undocumented) students.

Although community college exit rates are high for all students, they are worse for undocumented students. In the year after applying for the award, just over 17% and 30% of FAFSA and CDAA students use a Cal Grant at a community college, respectively, but after 4 years, their enrollment rates are equal, at roughly 3%–4% (see Figure 2). Table 3 confirms these high exit rates, with undocumented students 10pp more likely to attend a community college in year 1 but equally likely to be enrolled in year 4. These gaps are not explained by differential movement patterns, as undocumented students exhibit relatively similar patterns of delayed enrollment and transfer, which have little explanatory power due to low baseline rates (refer to Online Appendix Table 4).

Figure 2.

Unadjusted differences in Cal Grant usage in the California Community College System for FAFSA and CDAA (undocumented) students.

Although 85% of California’s public high school students who attend college do so in the public sector (Kurlaender et al., 2018), observing just Cal Grant receipt cannot capture all enrollment or any degree attainment. In supplementary analysis, we estimate enrollment and degree completion effects by using NSC data but encounter a problem, as undocumented students are less likely to match even when controlling for accurate enrollment observed through Cal Grant receipt. Online Appendix B provides an in-depth discussion of these details. Nonetheless, NSC data show a generally similar pattern of attendance results as reported above. Undocumented students appear less likely to earn a bachelor’s degree and equally as likely to earn an associate degree as their peers, but these differences are simply reflections of initial enrollment and persistence differences. For example, fewer undocumented students enroll at CSU, so fewer earn a bachelor’s degree from that sector, whereas equal numbers enroll at UC and so are equally likely to earn a degree from that sector.

Heterogeneity by Student Characteristics

To better understand program rollout, we first examine differences in student characteristics and outcomes across the first three cohorts of the program before turning to other types of potentially heterogeneous effects. Online Appendix Table 5 shows that across many characteristics, such as sex, family size, or high school urbanicity, undocumented applicants do not significantly differ between earlier and later cohorts (these results rely on equation [2], described above). We do see some meaningful differences over time, particularly between the first and the later two cohorts, as undocumented applicants have lower GPAs and incomes and are less likely to have college-educated parents. This result provides some evidence of “positive selection” into the Cal Grant program in the first year, as in the later cohorts, the program begins to draw in students who are typically less advantaged in the college selection and enrollment process. These new applicants also list more community colleges and CSUs, although there is no change in listing UC. Given limitations in our data, we cannot differentiate whether these new applicants arise due to the Cal Grant becoming more known or trusted; whether state aid increases motivation to graduate, as with DACA (e.g., Kuka et al., 2020); or some other factor.

Table 4 provides heterogenous differences in enrollment outcomes by student characteristics, first focusing on differences by initial cohort. We find that later cohorts are even more likely to attend community college, although in all cases, the fourth-year enrollment is equal to their peers. In all three cohorts, we find evidence that CSU or UC enrollees have stronger or similar persistence to that of their peers, although the table provides some evidence that later cohorts are slightly more successful in the UC system. Altogether, these cross-cohort results suggest that later cohorts are not swayed to enroll in 4-year colleges, even as knowledge of the Cal Grant program becomes more widely spread.

Table 4

Differences Between FAFSA and CDAA (Undocumented) Students’ Enrollment and Persistence Patterns, Heterogeneous Effects

	First year			Fourth year
	Community college	California State University	University of California	Community college	California State University	University of California	Sample size
Cohorts (2013–2015)
2013	0.073**(0.005)	−0.034**(0.006)	−0.008+(0.004)	−0.004(0.003)	−0.024**(0.005)	−0.019**(0.004)	126,540
2014	0.106**(0.005)	−0.053**(0.005)	−0.004(0.004)	0.007**(0.002)	−0.022**(0.005)	−0.006+(0.004)	134,737
2015	0.108**(0.005)	−0.050**(0.005)	0.005(0.004)	0.002(0.002)	−0.028**(0.005)	0.011**(0.004)	136,792
Gender
Females	0.114**(0.004)	−0.053**(0.004)	−0.002(0.003)	0.005**(0.002)	−0.028**(0.004)	−0.004(0.003)	237,540
Males	0.073**(0.004)	−0.037**(0.005)	−0.002(0.004)	−0.001(0.002)	−0.020**(0.004)	−0.004(0.003)	160,689
High school urbanicity
City/Suburb	0.094**(0.003)	−0.044**(0.003)	−0.003(0.002)	0.002+(0.001)	−0.025**(0.003)	−0.006*(0.002)	335,543
Town/Rural	0.122**(0.010)	−0.082**(0.010)	0.004(0.007)	0.002(0.005)	−0.038**(0.009)	0.002(0.006)	41,549
Socioeconomic status
High FRPL	0.096**(0.003)	−0.054**(0.004)	−0.006*(0.003)	0.002(0.002)	−0.029**(0.003)	−0.007**(0.002)	250,105
Low FRPL	0.101**(0.005)	−0.017**(0.006)	0.017**(0.005)	0.001(0.002)	−0.008(0.005)	0.009*(0.005)	148,347
High school GPA
≤ 2.5	0.061**(0.008)	−0.017**(0.004)	−0.000(0.000)	−0.006(0.003)	−0.003(0.003)	−0.001(0.001)	68,176
2.5 ≤ 3.0	0.120**(0.006)	−0.072**(0.006)	0.001(0.002)	0.005+(0.003)	−0.035**(0.005)	0.001(0.002)	93,581
3.0 ≤ 3.5	0.114**(0.004)	−0.071**(0.006)	0.011*(0.004)	0.005*(0.002)	−0.044**(0.006)	0.009*(0.004)	131,954
3.5 <	0.075**(0.004)	−0.006(0.006)	−0.013+(0.008)	0.002(0.002)	−0.004(0.006)	−0.018*(0.007)	104,064

Notes. Results show differences in the enrollment and persistent pattern of California Dream Act Application (CDAA; undocumented) students in different postsecondary education sectors relative to their peers, controlling for background characteristics and high school fixed effects by various heterogenous characteristics in the 2013–2015 cohorts. High Free Reduced-Price Lunch (FRPL) represents students attending schools with more than 50% of the population eligible for this program, and low FRPL refers to those students in schools with less than or 50% eligible. Student-level controls include grade point average (GPA), income, age, family size, and dummies for sex, having college-educated parents, dependency status, and application year. For-profit colleges are not shown because very few profit institutions are eligible to receiving institutions of the Cal Grant.

p < .10. ^*p < .05. ^**p < 0.01.

Table 4 then examines whether postsecondary trajectories vary by background characteristics, such as GPA, sex, high school urbanicity, or high school rates of free and reduced-price lunch. We find the largest shifts into community colleges and away from CSU in the middle of the GPA distribution (a GPA between 2.5 and 3.5). We find relatively small differences across other background characteristics, with all results pointing to a persistent difference in postsecondary enrollment patterns that favors community colleges over the CSU system, along with correspondingly high exit rates from community colleges.

Representativeness of Cal Grant Applicants

As we lack precise information on the size of the undocumented population, we are unable to answer key questions, such as what percentage of eligible students applies for the program. One concern could be that our comparisons are drawing from different parts of the population distributions of CDAA and FAFSA students—for example, if the majority of FAFSA-submitting students apply for aid, but only higher-performing undocumented students take this step.

We examine this issue by using public data on Cal Grant application patterns, with Online Appendix Figure 3 showing annual eligible Cal Grant applications from 2013 through 2019.⁶ CDAA applications grow over time, rising 22%, from roughly 6,200 in 2013 to 7,600 in 2019, but this increase is mirrored among FAFSA-submitting students, for which applications rise 27% over the same period. Growth comes almost entirely from students interested in community college, for CDAA and FAFSA students; these public data, culled over a longer time frame than our microdata, mirror the increasing community college focus seen in our regression results in Online Appendix Table 5. This pushes against the hypothesis of significant information frictions when the program started that might depress applications, especially as we observe no change in CSU or UC applications in the first few years. Migration patterns show that the undocumented population has declined over the last decade—nationally and in California—so population changes are unlikely to be driving increases in applications.⁷ This information suggests that the program is reaching most students who are independently interested in 4-year colleges, although efforts to increase interest in 4-year colleges could potentially change future application rates.

Although this article relies on comparisons based only on students who apply for the program, we think these results are likely to be fairly representative. From above, we see relatively little change in applications over the first 7 years of the program, a substantial period of time for information to spread to the wider community. Given an annual estimate of 27,000 high school graduates in California (Zong & Batalova, 2019), approximately one-quarter of undocumented graduates are offered a Cal Grant, compared to one-third of the full California population.⁸ Clearly, these are very rough estimates of the true size of California’s undocumented population; the true application rate could easily span 20%–40%.

At a minimum, these numbers suggest that application rates are not wildly divergent between groups, although there are reasons for thinking that undocumented applicants’ rates should be higher than those of their peers. First, given the almost 7,000 undocumented applicants per year, we cannot plausibly be drawing only from the very top of the undocumented student distribution; unfortunately, we are unlikely to improve this comparison, given the inherent imprecision in estimating undocumented graduates. But one concern is that lower-income families should be more heavily represented in the Cal Grant data, and so we might expect significantly higher numbers for undocumented students, were all eligible students to apply. Nonetheless, our results do not appear to be driven by a very select subset of the population and may understate students’ preferences for community college enrollment over the 4-year sector.

Discussion

We study the educational trajectories of California’s undocumented state-aid applicants as they leave high school, in the period from the mid- to late 2010s, when they are financially supported by state aid and ISRT. We find little difference in overall take-up rate of the grant program between undocumented students and residents who apply and are deemed eligible for the award. Although it is a descriptive finding, prior research finds large gaps in enrollment rates between undocumented students and those of their peers, and substantial offers of state aid appear to minimize these gaps. One reason may be the “free college” structure of the Cal Grant program, as this messaging has been successful in many contexts (Dynarski et al., 2021; Rosinger et al., 2021). This new program was folded into the already well-known Cal Grant, in a state with a relatively more supportive environment for undocumented students. States adopting similar programs may be less successful if their program is entirely new or if students have justified hesitancy regarding sharing confidential data with state agencies. Programs with eligibility requirements often require administrative hurdles that can dissuade families from applying, but in our data, we find that undocumented graduates have similar GPAs to those of their peers, and almost all come from families whose income is substantially below the eligibility thresholds, suggesting that most applicants easily meet requirements. We do find some evidence that the program has expanded over time to draw in more students with lower-average GPAs and from lower-income neighborhoods, although whether this shift is due to administrative burdens or better diffusion of information is not known. Taking this change into account, states might try offering aid with minimal application burdens to increase take-up, at least in the first years of the program, to help families develop trust in the process.

Undocumented students enroll in 2-year colleges over the broad-access 4-year CSU system, although they are equally likely to attend the more selective UC system. Differences in the colleges listed on the FAFSA suggest that enrollment gaps may arise from application patterns rather than acceptance rates. For example, undocumented students are less likely to list UC on their FAFSA application but equally likely to attend, suggesting that differences arise from student choices rather than from college decisions. Although lower CSU enrollment may arise if undocumented students lack access to the types of coursework or admissions tests needed for 4-year access (e.g., Umansky, 2016), equal rates of UC enrollment complicate this theory, and thus it requires more attention.

If driven by student choices, what aspects of CSU are less appealing to undocumented students: distance from home, the social climate, more flexible work opportunities offered by community college degree programs, or counseling the students receive from their high school or from other undocumented students who may have attended CSU? Clearly, some of these questions would be better resolved through qualitative research. Prior qualitative research has already highlighted some key issues that affect college choice and persistence, such as unremedied financial responsibilities beyond just tuition as well as the role of high school counseling (Murillo, 2021; Raza et al., 2019). Another possibility is that undocumented students may be uncertain about the return on investment for a 4-year college degree, particularly for students at the margin of community college and CSU attendance. For example, the types of degree programs offered by community colleges may offer more appealing employment opportunities when compared to a degree from a broad-access college that lacks the prestige of UC. One clear finding is that 4-year enrollment rates do not substantially increase over time. This result pushes against a theory common to administrative programs: that eligible students might be initially unaware of program benefits but become more knowledgeable or trusting over time. Starting in a 4-year college rather than in a community college leads to better long-term outcomes, all things equal, and supports the idea of encouraging undocumented students to enroll in CSU (Goodman et al., 2017; Long & Kurlaender, 2009). Yet without knowing why undocumented students are hesitant to attend, efforts to advocate for CSU enrollment might backfire.

Nonetheless, our results push against a “mismatch” story, as undocumented students’ persistence rates are much stronger in the 4-year system. Overall, this article gives further confirmation of the importance of the high school, college, and policy contexts in promoting students’ success. State policy choices appear to minimize often large gaps in college enrollment for undocumented students, but college completion rates are strongly driven by the college environment where they choose to study. Ultimately, high schools are a key place to help resolve these differences, as efforts to reach undocumented students must begin earlier in the application process to help them choose the postsecondary environment that will maximize their chances of success. Alternately, colleges or states can engage in more targeted policies that simplify and provide clarity to admissions processes, which have been shown to increase enrollment (Dynarski et al., 2021; Odle & Delaney, 2022). It is a smaller point, but these results also highlight the importance of better microdata, as we provide a more complicated narrative of differences in CSU and UC college enrollment rather than one that simply examines the choice between 2- and 4-year colleges.

As the Cal Grant essentially provides free college tuition across sectors, an additional question is what other social and psychological barriers affect undocumented students’ college success, particularly in community colleges (Suárez-Orozco et al., 2011). We observe very large exit rates for undocumented students in the first year of college, as is true of their peers, which is obviously a key moment for intervention. Any hands-off process that assumes that new college students need time to figure out their “fit” is clearly going to be unsuccessful. Colleges have engaged in many types of interventions to help incoming students succeed, such as summer bridge programs, but their effectiveness is debatable, and it is not clear how well the structures also help undocumented students. Clearly, much more work here is needed.

Our most promising result is that undocumented students attending 4-year colleges perform well, but we need to continue exploring additional channels that are holding these students back from reaching their potential. This topic is even more relevant now, as hard-fought gains in rights may be eroded by changes in federal policies or public sentiment that often refuses to acknowledge the positive impacts of immigrants on society.

Supplemental Material

sj-pdf-1-edr-10.3102_0013189X221107941 – Supplemental material for Documenting Their Decisions: How Undocumented Students Enroll and Persist in College

Supplemental material, sj-pdf-1-edr-10.3102_0013189X221107941 for Documenting Their Decisions: How Undocumented Students Enroll and Persist in College by Oded Gurantz and Ann Obadan in Educational Researcher

Footnotes

ORCID iDs

Oded Gurantz

Ann Obadan

Notes

Authors

ODED GURANTZ, PhD, is an assistant professor at the Truman School of Government and Public Affairs, University of Missouri, 615 Locust Street, Columbia, MO 65211; gurantzo@missouri.edu . His research is in the areas of economic of education, education policy, and higher education and focuses on gaps in college enrollment and completion between students from historically underserved groups and their more privileged peers.

ANN OBADAN is a doctoral candidate at the Truman School of Government and Public Affairs, University of Missouri, 615 Locust Street, Columbia, MO 65211; aooc7k@mail.missouri.edu . Her research is in the areas of education policy, immigration policy, and social policy and focuses on evaluating policies and programs affecting immigrants and underserved populations.

References

Abrego

(2006). “I can’t go to college because I don’t have papers”: Incorporation patterns of Latino undocumented youth. Latino Studies, 4(3), 212–231.

Abrego

(2008). Legitimacy, social identity, and the mobilization of law: The effects of Assembly Bill 540 on undocumented students in California. Law and Social Inquiry, 33(3), 709. http://proxy.mul.missouri.edu/login?url=http://search.ebscohost.com/login.aspx?direct=true&db=edsjsr&AN=edsjsr.20108779&site=eds-live&scope=site

Abrego

(2011). Legal consciousness of undocumented Latinos: Fear and stigma as barriers to claims-making for first-and 1.5-generation immigrants. Law & Society Review, 45(2), 337–370.

Altmejd

Barrios-Fernández

Drlje

Goodman

Hurwitz

Kovac

Mulhern

Neilson

Smith

(2021). O brother, where start thou? sibling spillovers on college and major choice in four countries*. The Quarterly Journal of Economics, 136(3), 1831–1886. https://doi.org/10.1093/qje/qjab006

Amuedo-Dorantes

Antman

(2017). Schooling and labor market effects of temporary authorization: Evidence from DACA. J Popul Econ, 30(1), 339–373. https://doi.org/10.1007/s00148-016-0606-z

Amuedo-Dorantes

Sparber

(2014). In-state tuition for undocumented immigrants and its impact on college enrollment, tuition costs, student financial aid, and indebtedness. Regional Science and Urban Economics, 49, 11–24. https://doi.org/10.1016/j.regsciurbeco.2014.07.010

Becker

(2009). Human capital: A theoretical and empirical analysis, with special reference to education: University of Chicago Press.

Belasco

A. S.

Trivette

M. J.

(2015). Aiming low: Estimating the scope and predictors of postsecondary undermatch. Journal of Higher Education, 86(2), 233–263. https://doi.org/10.1080/00221546.2015.11777363

Benitez

DeAro

(2004). Realizing student success at Hispanic-serving institutions. New Directions for Community Colleges, 127, 35–48.

10.

Bjorklund

(2018). Undocumented students in higher education: A review of the literature, 2001 to 2016. Review of Educational Research, 88(5), 631–670. https://doi.org/10.3102/0034654318783018

11.

Bleemer

(2022). Affirmative action, mismatch, and economic mobility after California’s Proposition 209. The Quarterly Journal of Economics, 137(1), 115–160.

12.

Bleemer

(2021). Top percent policies and the return to postsecondary selectivity. Research & Occasional Paper Series: CSHE. 1.2021. Center for Studies in Higher Education.

13.

Black

S. E.

Cortes

K. E.

Lincove

J. A.

(2015). Academic undermatching of high-achieving minority students: Evidence from race-neutral and holistic admissions policies. American Economic Review, 105(5), 604–610. https://doi.org/10.1257/aer.p20151114

14.

Bleemer

(2020). Affirmative action, mismatch, and economic mobility after California’s proposition 209.

15.

Bleemer

(2021). Top percent policies and the return to postsecondary selectivity.

16.

Bozick

Miller

Kaneshiro

(2016). Non-citizen Mexican youth in US higher education: A closer look at the relationship between state tuition policies and college enrollment. International Migration Review, 50(4), 864–889. https://doi.org/10.1111/imre.12167

17.

Cabrera

A. F.

Nora

Terenzini

P. T.

Pascarella

Hagedorn

L. S.

(1999). Campus racial climate and the adjustment of students to college: A comparison between white students and African-American students. The Journal of Higher Education, 70(2), 134–160. https://doi.org/10.2307/2649125

18.

Capps

Gelatt

Soto

A. G. R.

Hook

J. V.

(2020). Unauthorized immigrants in the United States—Stable number, changing origins. Migration Policy Institute. https://www.migrationpolicy.org/sites/default/files/publications/mpi-unauthorized-immigrants-stablenumbers-changingorigins_final.pdf

19.

Chen

E. C.

Budianto

Wong

(2010). Professional school counselors as social justice advocates for undocumented immigrant students in group work. Journal for Specialists in Group Work, 35(3), 255–261.

20.

Conger

Chellman

C. C.

(2013). Undocumented college students in the United States: In-state tuition not enough to ensure four-year degree completion. Education, Finance, and Policy, 8(3), 364–377.

21.

Conger

Turner

L. J.

(2017). The effect of price shocks on undocumented students’ college attainment and completion. Journal of Public Economics, 148, 92–114. https://doi.org/10.1016/j.jpubeco.2017.02.006

22.

Contreras

(2009). Sin papeles y rompiendo barreras: Latino students and the challenges of persisting in college. Harvard Educational Review, 79(4), 610–632.

23.

Darolia

Potochnick

(2015). Educational “when,” “where,” and “how” implications of in-state resident tuition policies for Latino undocumented immigrants. Review of Higher Education, 38(4), 507–535. https://doi.org/10.1353/rhe.2015.0028

24.

Deming

D. J.

Walters

C. R.

(2017). The impact of price caps and spending cuts on US postsecondary attainment (No. w23736). National Bureau of Economic Research.

25.

Dynarski

S. M.

Libassi

Michelmore

Owen

(2021). Closing the gap: The effect of a targeted, tuition-free promise on college choices of high-achieving, low-income students. American Economic Review, 111(6), 1721–1756.

26.

Flores

S. M.

(2010). The first state Dream Act: In-state resident tuition and immigration in Texas. Educational Evaluation and Policy Analysis, 32(4), 435–455. https://doi.org/10.3102/0162373710380741

27.

Gonzales

R. G.

(2008). Left out but not shut down: Political activism and the undocumented student movement. Northwestern Journal of Law & Social Policy, 3, 219.

28.

Gonzales

R. G.

(2010). More than just access: Undocumented students navigating the postsecondary terrain. https://vtechworks.lib.vt.edu/handle/10919/86901

29.

Gonzales

R. G.

(2015). Lives in limbo: Undocumented and coming of age in America. University of California Press.

30.

Goodman

J. S.

Hurwitz

Smith

(2017). Access to four-year public colleges and degree completion. Journal of Labor Economics, 35(3), 829–867.

31.

Groce

L. L.

Johnson

L. V.

(2021). School counselors igniting the hope of undocumented students in college access. Journal for Specialists in Group Work, 46(1), 128–142.

32.

Hossler

Braxton

Coopersmith

(1989). Understanding student college choice. Higher Education: Handbook of Theory and Research, 5, 231–288.

33.

Hossler

Schmit

Vesper

(1999). Going to college: How social, economic, and educational factors influence the decisions students make. JHU Press.

34.

Hsin

Reed

H. E.

(2020). The academic performance of undocumented students in higher education in the United States. International Migration Review, 54(1), 289–315. https://doi.org/10.1177/0197918318825478

35.

Hsin

Ortega

(2018). The effects of deferred action for childhood arrivals on the educational outcomes of undocumented students. Demography, 55(4), 1487–1506. https://doi.org/10.1007/s13524-018-0691-6

36.

Kaushal

(2008). In-state tuition for the undocumented: Education effects on Mexican young adults. Journal of Policy Analysis and Management, 27(4), 771–792. https://doi.org/10.1002/pam.20366

37.

Kuka

Shenhav

N. A.

Shih

(2020). Do human capital decisions respond to the returns to education? Evidence from DACA. American Economic Journal: Economic Policy, 12(1), 293–324. https://doi.org/10.1257/pol.20180352

38.

Kurlaender

Reed

Cohen

Naven

Martorell

Carrell

(2018, December). Where California high school students attend college [Report]. Policy Analysis for California Education. https://edpolicyinca.org/publications/where-california-high-school-students-attend-college

39.

Locks

A. M.

Hurtado

Bowman

N. A.

Oseguera

(2008). Extending notions of campus climate and diversity to students’ transition to college. The Review of Higher Education, 31(3), 257–285. https://doi.org/10.1353/rhe.2008.0011

40.

Long

B. T.

Kurlaender

(2009). Do community colleges provide a viable pathway to a baccalaureate degree? Educational Evaluation and Policy Analysis, 31(1), 30–53.

41.

Morrison

Bryan

(2014). Addressing the challenges and needs of English-speaking Caribbean immigrant students: Guidelines for school counselors. International Journal for the Advancement of Counselling, 36(4), 440–449.

42.

Morse

Mendoza

G. S.

(2015). Tuition benefits for immigrants. https://www.ncsl.org/research/immigration/tuition-benefits-for-immigrants.aspx

43.

Muñoz

S. M.

(2016). Undocumented and unafraid: Understanding the disclosure management process for undocumented college students and graduates. Journal of College Student Development, 57(6), 715–729.

44.

Muñoz

S. M.

Maldonado

M. M.

(2012). Counterstories of college persistence by undocumented Mexicana students: Navigating race, class, gender, and legal status. International Journal of Qualitative Studies in Education, 25(3), 293–315.

45.

Nienhusser

H. K.

Espino

M. M.

(2017). Incorporating undocumented/DACAmented status competency into higher education institutional agents’ practice. Journal of Student Affairs Research and Practice, 54(1), 1–14.

46.

Ngo

Astudillo

(2019). California DREAM: The impact of financial aid for undocumented community college students. Educational Researcher, 48(1), 5–18. https://doi.org/10.3102/0013189x18800047

47.

Nguyen

T. D.

Kramer

J. W.

Evans

B. J.

(2019). The effects of grant aid on student persistence and degree attainment: A systematic review and meta-analysis of the causal evidence. Review of Educational Research, 89(6), 831–874. https://doi.org/10.3102/0034654319877156

48.

Nienhusser

H. K.

(2013). Role of high schools in undocumented students’ college choice. Education Policy Analysis Archives, 21(85), n85.

49.

Odle

T. K.

Delaney

J. A.

(2022). You are admitted! Early evidence on enrollment from Idaho’s direct admissions system. Research in Higher Education. https://doi.org/10.1007/s11162-022-09675-x

50.

Pérez

P. A.

(2010). College choice process of Latino undocumented students: Implications for recruitment and retention. https://vtechworks.lib.vt.edu/handle/10919/86963

51.

Pérez

P. A.

McDonough

P. M.

(2008). Understanding Latina and Latino college choice: A social capital and chain migration analysis. Journal of Hispanic Higher Education, 7(3), 249–265.

52.

Perez

(2010). Higher education access for undocumented students: Recommendations for counseling professionals. Journal of College Admission, 206, 32–35.

53.

Perna

L. W.

(2006). Studying college access and choice: A proposed conceptual model. In Smart

J. C.

(Ed.), Higher education: Handbook of theory and research (pp. 99–157). Springer.

54.

Richards

Bohorquez

(2016). Institutional policies and programs with and for undocumented students. https://unitedwedream.org/wp-content/uploads/2015/04/NICOD2016_TOOLKIT-copy.pdf

55.

Rosinger

Meyer

Wang

(2021). Leveraging insights from behavioral science and administrative burden in free college program design: A typology. Journal of Behavioral Public Administration, 4(2).

56.

Roth

B. J.

(2017). When college is illegal: Undocumented Latino/a youth and mobilizing social support for educational attainment in South Carolina. Journal of the Society for Social Work and Research, 8(4), 539–561.

57.

Suárez-Orozco

Katsiaficas

Birchall

Alcantar

C. M.

Hernandez

Garcia

. . .Teranishi

(2015). Undocumented undergraduates on college campuses: Understanding their challenges and assets and what it takes to make an undocufriendly campus. Harvard Educational Review, 85(3), 427–463.

58.

Suárez-Orozco

Yoshikawa

Teranishi

Suárez-Orozco

(2011). Growing up in the shadows: The developmental implications of unauthorized status. Harvard Educational Review, 81(3), 438–473. https://doi.org/10.17763/haer.81.3.g23x203763783m75

59.

Sulkowski

M. L.

(2017). Unauthorized immigrant students in the United States: The current state of affairs and the role of public education. Children and Youth Services Review, 77, 62–68. https://doi.org/10.1016/j.childyouth.2017.04.006

60.

Terriquez

(2015). Dreams delayed: Barriers to degree completion among undocumented community college students. Journal of Ethnic and Migration Studies, 41(8), 1302–1323.

61.

Umansky

I. M.

(2016). Leveled and exclusionary tracking: English learners’ access to academic content in middle school. American Educational Research Journal, 53(6), 1792–1833. https://doi.org/10.3102/0002831216675404

62.

Warren

(2021). In 2019, the US undocumented population continued a decade-long decline and the foreign-born population neared zero growth. Journal on Migration and Human Security, 9(1), 31–43. https://doi.org/10.1177/2331502421993746

63.

Zaidee

(2019). University of California will support undocumented students even if DACA ends. https://edsource.org/2019/university-of-california-will-support-undocumented-students-even-if-daca-ends/619844

64.

Zimmerman

S. D.

(2014). The returns to college admission for academically marginal students. Journal of Labor Economics, 32(4), 711–754.

65.

Zong

Batalova

(2019). How many unauthorized immigrants graduate from U.S. high schools annually. Migration Policy Institute.

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