Breaking Down the Wall: The Effect of Immigration Enforcement and Nonprofit Services on Undocumented Student Academic Performance

1 Educational Performance and Immigration Enforcement

Scholars have studied the undocumented community’s resilience, educational journeys, and persistence in higher education through in-depth interviews (Abrego & Gonazales 2010; Enriquez 2011; Gallo 2014; Gonzales 2009, 2010; Gonzales 2015; Perez et al. 2009), but quantitative work is limited. Except for Hill and Hawes (2011), we primarily rely on the literature examining the larger Latino student population. From second-generation discrimination to under-resourced schools, scholars examine several explanations for the educational attainment gap of Latino students (Arias 1986; Crosnoe and Turley 2011; Gibson and Carrasco 2009; Meier and Stewart 1991). Research finds that migrant students tend to perform less well academically than non-migrant students (Amuedo-Dorantes and Lopez 2015; Bean et al. 2011; Menchaca 1996). Latino migrant students have lower graduation rates, higher dropout rates (twice as high) and are more likely to be held back a grade level (Menchaca 2003). This is partially due to migrant students missing parts of the school year due to seasonal travel but also because many schools do not have teachers with cultural knowledge and teaching techniques that are necessary for this student demographic (Menchaca 2003).

Outside the classroom, home life is a crucial component of student success. Research has consistently found a student’s home life to be a strong and significant determinant of academic performance across a wide range of contexts (Griffith 1996; Parcel and Dufur 2001). The effects of home life on school performance extend beyond the immediate home. For immigrant students, especially undocumented students, violence within a student’s community can also hurt their academic performance (Bowen and Bowen 1999; Sharkey et al. 2014). The American Psychological Association (APA) notes that immigration enforcement undoubtedly has a destabilizing effect on the communities and homes of immigrants (APA 2018), and that detention and deportation policies impact the psychological well-being of children of immigrants (Zayas and Cook Heffron 2016). Thus, educational psychologists posit that immigration enforcement policies must influence student performance (Sulkowski 2017).

For students and parents who live in fear of deportation, increased immigration efforts heighten fear and anxiety in their community, schools, and homes. Filindra, Blanding, and Coll (2011) find that inclusionary and multicultural policies have a strong positive effect on graduation rates of immigrant children. Alternatively, Dee and Murphy (2018) find that local ICE immigration enforcement partnerships (e.g., 287(g) programs^[1]), have led to the displacement of more than 300,000 Latino students. Based on scholarly research and local reports, in both the Postville, Iowa and the recent Morton, Mississippi raid, the effects of detention caused many students to remain absent from school in the following days (Crowder & Elmer 2018, Crowder and MacKenzie 2018; Fowler 2019; Juby 2011, pp. 148–52). The Postville, Iowa raid affected all 220 Latino students who were from immigrant families resulting in about “150 Latino students … missing … school” the day after the raid (Zehr 2008). As immigration enforcement increases, communities living in the shadows are forced to further retreat from doing things such as taking their children to school for fear they might be detained, being afraid to visit the local hospital, to reducing the use of Medicaid (Dozier 1993; Vargas and Pirog 2016). Furthermore, Garcia (2001) also contends that the absence of social resources can have a deleterious effect on school performance and may be one of the indicators to account for educational inequalities among Latinos and non- Latinos, a result of living in the shadows. Undocumented youth, already, live with fear of deportation (Dozier 1993); with increased immigration enforcement, it is more likely undocumented students will perform lower on standardized tests. Due to the ubiquity of mixed family status among immigrant families (i.e. household members hold differing immigration statuses), we expect the negative effects of enforcement to extend to Latino students broadly; however, these effects will be particularly pronounced for undocumented students. Thus, we expect differences in performance between documented and undocumented students (H1a) as well as undocumented students in communities with differing levels of enforcement (H1b).

2 ISOs as an Intervention for Immigration Enforcement

A neutral bureaucracy is unable to help redress the factors that lead to lower educational attainment, especially for a segment of the student population that has limited political rights. External support systems can serve as a mechanism to help buffer the negative effects of immigration policy enforcement on the academic performance of undocumented students. Organizations and their bureaucratic norms and rules can sustain and entrench discrimination and inequities (Breslin, Pandey, and Riccucci 2017; Dill and Zambrana 2009). External services provided by social service organizations may be able to counter this by working against the current harmful norms and rules. Immigration proceedings are a civil administrative matter. Unlike in criminal proceedings, individuals facing deportation are not required to be provided representation. Thus, to fight against a deportation order or appeal any rejection during an adjustment of status, immigrants must find their own legal representation. Scholars note that undocumented students with protective networks, social capital, and cultural-capital-rich environments have higher academic attainment (Enriquez 2011; Perez et al. 2009; Yosso 2005). Discussing how academic resilience is formed, Perez et al. (2009) identify that environmental protective factors are external resources such as “parental support, adult mentoring, or community organizations that promote positive youth development” (154).

Along with academic resilience, students who can access a patchwork of social capital, despite being fearful of making close personal relationships due to the vulnerability of their status (Dozier 1993), can achieve higher educational success. Patchworking social capital (Enriquez 2011) can be made easier by going to community organizations where undocumented students do not have to live in fear of their status placing them in jeopardy or excluding them from participating in programs or scholarships for educational success. In this manner, local community organizations can help provide undocumented students with a variety of programs that are not just educationally related but that can provide resources for undocumented communities to remain in the country. Indeed, recently published research finds that the presence of immigrant-serving organizations (ISOs) predicts lower local deportation rates of immigrants (Chand et al. 2021). Providing basic resources and programs can help offset factors that decrease or increase the obstacles to educational attainment. In the context of immigration enforcement and deportation, we posit that ISOs offering legal assistance (and in most cases access to other social services as well) to immigrants provide undocumented students with a social justice safety net. First, these ISOs contribute to what Yosso (2005) identifies as navigational capital. By helping provide the family with access to legal recourse from adjustment of status to deportation defense, ISOs help challenge the “illegality” and “meritocracy” narrative applied to immigrants and additionally provide families of undocumented students with assistance navigating the administrative burden (Herd and Moynihan 2019) that is the American immigration system.

While no outcome can truly be guaranteed, the presence of ISOs offers an added layer of protection for undocumented students and their families. This process-oriented intervention focuses on ensuring social justice for immigrants facing deportation or an adjustment of status. Thus, undocumented students who attend schools in communities with higher levels of immigrant-serving nonprofit organizations will perform better on academic tests.

With ISOs providing legal assistance to challenge the enforcement of immigration policy, undocumented students receive social justice advocates who seek to challenge the bureaucratic immigration rules. When this is present, undocumented students find themselves in an environment with a stronger safety net leading to improved educational performance. As such, undocumented students who attend schools with a larger network of ISOs within the county will be less susceptible to the negative impacts of immigration enforcement.

3 Data and Methods

This study utilizes 2014 data from five primary sources: 1) district-level accountability data from the Texas Education Agency (TEA), 2) a unique student-level dataset identifying the number of undocumented students, 3) student-level TEA state test performance data, 4) county-level S-Comm immigration enforcement data, and (5) county-level data on the presence of immigrant-serving nonprofit organizations.

Texas school districts do not directly collect data on the presence of undocumented students; thus, the only measures available are rough proxies. To identify undocumented students, we adopt a method developed by Hill and Hawes (2011) that estimates the undocumented student population in Texas public schools. Similar to other states since 1982, students in Texas public schools are not required to report their immigration or legal status during registration. However, Texas has implemented a tracking system for students called the Person Identification Database (PID) that assigns a unique identifier for each student based on several forms of documentation including social security numbers. When students register, they must provide a social security number; however, if they do not provide one, they are assigned an alternative number in its place. Thus, students are either assigned a PID number or an Alternative PID number. These identifying data are available by race and ethnicity, which provides us a list of Latino students within each district who did not provide a social security number during school registration.

We obtained data from the Texas Education Agency for student-level performance data on all students in Texas public schools, including those who were assigned alternative PID numbers broken down by race and ethnicity.^[2] We limit our analysis to Latino students. As Hawes and Hill note, while not all students with alternative PIDs are undocumented, most undocumented students enrolled in public schools (provided they do not provide a falsified social security card) should be included in these data.^[3] At the very least, this measure should be highly correlated with true undocumented student enrollments. Since there is no objective measure that captures the undocumented population in the United States, the Hill and Hawes (2011) approach provides a measure that is best fit to capture the undocumented student population using the registration requirements within the Texas Public Education System. In addition to race and ethnicity, our analysis also includes identifiers on whether the student was categorized as 1) economically disadvantaged (qualified for free/reduced lunch), and 2) had Limited English Proficiency (LEP) status. These data, then, include student-level performance of documented and “undocumented” Latino students as well as a district identifier, which allows us to merge these student-level data with district characteristics.

Figure 1 presents the district aggregates of an adjusted measure^[4] of Latino undocumented students as a percentage of total enrollments. We see here that, as a percentage of total student enrollments, the figures tend to be highest in more heavily populated areas, along the border, and in the panhandle – an area with high agriculture and livestock production.

Figure 1:

Adjusted measure of percent latino undocumented students.

We examine the student-level performance on the State of Texas Assessments of Academic Readiness (STARR) exam for over 2 million Latino students, including nearly 225,000 with alternative PID numbers (which we refer to as undocumented students) for the 2014 school year. The student-level data were merged with school district data and county-level demographic and immigration enforcement data. Below is a discussion of the variables used in our analysis.

4 Findings

Table 2 presents a preliminary analysis. Here, we include a dichotomous variable to test the baseline difference in performance between undocumented and documented Latino students as well as to test whether enforcement has an effect on overall performance without considering the legal status of the student. Table 2 suggests there is no statistical difference in test performance between documented and undocumented students. Furthermore, immigration enforcement has mixed results where total removals are not significant but there is a negative effect for the presence of a 287(g) MOA. The effect is modest where students in districts with a 287(g) agreement, on average, score about 0.03 standard deviations lower on their exams. Several other relationships are worth noting. Among the county-level variables, students attending schools in a border county had significantly higher scores than those who were not on the border (nearly twice the effect size of 287(g) programs). Those who lived in counties that with higher Republican vote share performed slightly worse on these exams than those who did not (a 10 percent increase in vote share is associated with about a 0.001 standard deviation decrease in test scores). Among the district-level variables, students in larger districts, districts with more bilingual/ESL programs, districts with higher Latino TAKS pass rates, and districts with more teachers with advanced degrees and higher turnover rate all performed better, all else equal. Students in districts with more Latino students and higher instructional expenditures performed worse. All of the student-level variables (economically disadvantaged, LEP, and high school students) were statistically significant negative predictors of student performance.

Table 3 tests Hypothesis 1 by examining whether the effects of immigration enforcement have a differential effect between documented students and undocumented students (H1a). We do this by running the model separately for documented and undocumented students. H1a predicts that the effects of immigration should be more negative for undocumented students than other Latino students. The results are mixed. On the one hand, we see that total removals have a negative and statistically significant effect on performance for undocumented students but not for other Latino students. The effect is nontrivial where a one standard deviation increase in removals is associated with a 0.039 standard deviation decline in test scores.^[13] Moving across the full range of removals (from lowest to highest) would be associated with a about 1/3rd of a standard deviation decrease. Converted to raw scaled test scores, this would be nearly a 180-point decrease in test scores.^[14] Interestingly, while negative, the relationship for 287(g) programs is not statistically significant for undocumented students (but is at the alpha = 0.10 level for documented students).

We find support for Hypothesis 2 in that the presence of EOIR/BIA-registered organizations is positively associated with student performance but only for undocumented students. A one-standard-deviation increase in the presence of these nonprofits is associated with a 0.028 standard deviation increase in performance or a 223-point increase in raw scaled scores, on average across the full range of the variable (0–14). As discussed above, while these organizations do not directly interact with students for daily educational purposes, their existence in the community may provide a comforting presence to undocumented immigrants and their families.

The mixed effects of enforcement in Table 3 suggest there may be a compounding effect where removals and the presence of 287(g) programs reinforce one another, as suggested above. That is, 287(g) programs deputize local law enforcement to act on behalf of federal immigration agencies in certain capacities. This may magnify the “presence” and effects of federal immigration enforcement efforts hence heightening fears and disruptions in immigrant communities. We can test this by interacting total removals with 287(g) programs, as presented in Table 4. Here we see that for both documented and undocumented students, there is a multiplicative effect as noted by the statistically significant interaction term. For example, the effect of a one-standard-deviation increase in total removals is associated with a −0.039 standard deviation decrease in test scores for undocumented students (identical to the effect in Table 3) who live in communities without a 287(g) program. However, in counties that do employ a 287(g) program, the negative effect is substantially larger. A one-unit increase in removals (i.e. one standard deviation) is associated with a −0.172 standard deviation decrease in test scores for undocumented students.^[15] This translates to a roughly 92-point decrease in raw scaled test scores for a one-unit increase in removals or a 785-point reduction for the full range in the removal variable.

Interestingly, this effect is also present for documented students, although not as strong. That is, while the effect of removals is not statistically significant for documented students in communities without 287(g) programs, the effect is negative and statistically significant when such programs are present. However, the effect for undocumented students is about 2.4 times larger than for undocumented students (standardized β = −0.072 vs. −0.172). Figure 2 presents these effects differently by modeling the marginal effect of 287(g)s on performance across the range of enforcement levels (i.e. removals) for both documented and undocumented students. Here we see that, in both cases, the negative effect of 287(g)s on performance is conditional on overall enforcement levels. At low levels of removals (below the mean), 287(g) programs have little effect or even a positive effect. However, as enforcement levels increase above average levels, the presence of these programs has an increasingly large and negative effect. This effect is more than twice as large for undocumented students (right graph) than for other Latino students (left graph).

Figure 2:

Conditional effects of enforcement by documented status.

Also of interest is that the presence of ISOs is associated with a positive and statistically significant relationship with student scores for both documented and undocumented students. However, this effect is much stronger (2.43 times) for undocumented students than for documented students (standardized β = −0.07 vs. −0.029).

This leads us to our final question, Hypothesis 3, which asks whether these negative effects of immigration enforcement are moderated by ISOs. That is, are the negative impacts of enforcement lessened in communities with a stronger presence of ISOs? To test this, we re-run the analysis for undocumented students and split the sample between those who live in areas with differing levels of ISO presence. Most counties in Texas do not have any ISOs, including about 27 percent of our sample. Indeed, in our data, 50 percent of students live in a county with 3 or fewer ISOs. Thus, we use this (the median) as our cutoff. Table 5 presents the results of two models that examine the effects of enforcement for “low” and “high” levels of ISOs. Here we see that the interactive effects of enforcement (removals × 287(g)) exist but only in cases where there are few ISOs (Model 1). Removals still have a negative effect in high ISO communities (Model 2) and it is nontrivial (standardized β = −0.183) when 287(g)s are not present. However, the compounding effect of 287(g)s is no longer significant. However, in low ISO communities, the interactive effects are large and statistically significant. The marginal effect of removals in the presence of 287(g) agreements in low ISO communities is −1.397 (standardized β = −1.80). This suggests that a one standard deviation increase in removals is associated with a 1.80 decrease in test scores or a 970-point decrease in average raw scaled test scores. Figure 3 presents the marginal effect of 287(g) programs on test performance conditional on removals for low ISO communities. Here we see that 287(g) programs have an increasingly large and negative effect on performance as the number of removals increases. This conditional effect is only present in communities with low ISO presence.

Figure 3:

Conditional effects of enforcement by ISO presence.

5 Discussion and Conclusion

The United States is home to roughly 11 million undocumented Americans, of these about 55 % are parents to a child, both citizen and undocumented (Gelatt and Zong 2018). The effects of deportation are both short and long-term. As immigration policy and its enforcement continue to ramp up, immigrant communities have felt the effects of deportation. It is not hard to assume what social and economic effects occur to families, but little is known about the educational attainment of the children left behind and more so those who must live in the shadows, the undocumented youth. This paper provides an initial and unique examination of the effects of immigration enforcement on immigrant communities and the academic performance of Latino students, including undocumented students. Specifically, we examine how higher levels of removals affect the academic performance of undocumented students. We argue that more aggressive enforcement creates insecurity for immigrant communities and this insecurity produces fear and anxiety that hinders academic performance. A second and significant contribution to the field is the exploratory analysis of how this effect varies by the legal status of students as well as how ISOs can act to buffer these negative effects on the academic performance of undocumented students.

We argue that the presence of community organizations provides undocumented students a safety net of resources to help alleviate this anxiety and, thus, improve performance. Furthermore, the centering of marginalized voices is also found within the social justice component of immigration nonprofits. We focus, specifically, on ISOs that provide legal services. These ISOs provide cultural competency for the immigrant community. They allow immigrants to challenge the U.S. immigration system. This allows the undocumented community assistance not only as a final line of defense in deportation proceedings but also provides navigational assistance through adjustments of status. The world of bureaucrats and nonprofit organizations seem to operate parallel to each other, but as policy problems become more complex and inequitable, their interaction can help design a safety net for the most marginalized. We argue the interaction of these interventions serve as a buffer to the negative effects of immigration enforcement.

Using multi-level data from Texas, our research finds mixed support. For our enforcement hypothesis, we find that higher levels of removals are associated with lower test scores for undocumented students living in those districts. These negative effects are magnified in counties that have an agreement between local law enforcement and federal immigration agencies (e.g., 287(g) agreements) for all Latino students, but especially undocumented students who experience more than twice the negative impact. However, we find that these effects are primarily connected to the absence of ISOs in the community. Those in communities with high ISO presence are safeguarded from these compounding effects.

This analysis has several caveats. First, the measure of “undocumented” students has limitations since it may include those who are not actually undocumented students but simply did not provide proper documentation when registering. That said, it is currently the best large-N measure available and should, in theory, be highly correlated with the true undocumented figures. Second, the ISOs in our models focus primarily, although not exclusively, on legal aid for immigrants. This is relevant in how it relates to immigration enforcement and removal proceedings, which can affect student performance. However, future researchers may choose to focus more on immigration nonprofits that specialize in other services. Finally, the time frame of the analysis is limited due to data availability. Future research should expand the time frame to include some of the more recent events in immigration policy and enforcement. Additionally, this research attempted to examine how interconnected sectors are working to help redress inequities in the system. This research even as an exploratory analysis helps provide insights into how to strengthen the safety net for marginalized community groups, especially for those with limited political rights.