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Foreign-born Peers and Academic Performance

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Demography

Abstract

The academic performance of foreign-born youth in the United States is well studied, yet little is known about whether and how foreign-born students influence their classmates. In this article, I develop a set of expectations regarding the potential consequences of immigrant integration across schools, with a distinction between the effects of sharing schools with immigrants who are designated as English language learners (ELL) and those who are not. I then use administrative data on multiple cohorts of Florida public high school students to estimate the effect of immigrant shares on immigrant and native-born students’ academic performance. The identification strategy pays careful attention to the selection problem by estimating the effect of foreign-born peers from deviations in the share foreign-born across cohorts of students attending the same school in different years. The assumption underlying this approach is that students choose schools based on the composition of the entire school, not on the composition of each entering cohort. The results of the analysis, which hold under several robustness checks, indicate that foreign-born peers (both those who are ELL and those who are non-ELL) have no effect on their high school classmates’ academic performance.

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Notes

  1. I use the terms “immigrant,” “foreign-born,” and “first-generation immigrant” interchangeably to refer to children who were born abroad. The terms “children of immigrants” and “immigrant-origin” are used interchangeably to refer to both first-generation and second-generation immigrant youth (born in the United States with one or both parents born abroad).

  2. The administrative data do not distinguish between Hispanic ethnicity and race. Instead, students are given the option to identify as Hispanic; black, not of Hispanic origin; white, not of Hispanic origin; Asian; or other.

  3. The FLDOE requires all students in homes where a language other than English is primarily spoken to take English language assessments and the scores on these exams are used to determine entry into and exit from ELL status. Unlike most other states with large ELL populations, the FLDOE also relies on parent or teacher referrals and a formal committee review to classify ELL students, which suggests that at least relative to several other states, students in Florida are less likely to be misclassified as either ELL or non-ELL (Ragan and Lesaux 2006).

  4. Data on earlier progressive cohorts was used for these aggregations, such that the counts include all students in the grade and year, not just those in the cohort.

  5. Consistent with the characteristics of high school dropouts nationally, the students who are not enrolled in the 10th grade are more likely to be male, black, eligible for free or reduced-price lunch, and disabled than students who remain enrolled. The students who exit by the 10th grade are also slightly less likely to be immigrant non-ELL than students who remain and more likely to be native-born, with equal shares of immigrant ELL in both groups.

  6. The three most frequently used national probability samples of high school students do not provide the large numbers of students and multiple cohorts afforded in these data. The National Educational Longitudinal Study (NELS) and its later counterpart, the Education Longitudinal Study (ELS), are both single-cohort designs with small numbers of students in each high school. Add Health provides multiple cohorts, but insufficient numbers of immigrant ELL and non-ELL within each school across cohorts to identify estimates with precision using this design.

  7. This technique has also been used to study the effects of the racial composition of peers (see Hanushek et al. 2009; Hoxby 2000).

  8. Results from alternative specifications using 9th grade peers and the average of the students’ 9th and 10th grade peers are qualitatively similar to those presented in this article and available upon request.

  9. For the students who attended more than one school in the fall of the 10th grade, I chose the school that they attended the majority of the time. If the time was equal, I randomly chose one of the schools.

  10. All sensitivity analyses were estimated for the models presented in Table 6 and in Table 8 in the appendix, and the results were robust to these alternative models.

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Acknowledgments

I thank the Florida Department of Education for maintaining such comprehensive records and for making them available to me for analysis. I am also grateful to the insightful comments provided by Brandon Bartels, Stephanie Riegg Cellini, David Deming, Bruce Fuller, Guanglei Hong, Micere Keels, Paco Martorell, Steven Raudenbush, Amy Ellen Schwartz, Leanna Stiefel, Jacob Vigdor, and seminar participants at the Association for Education Finance and Policy, George Washington University, Public Policy Institute of California, University of California at Berkeley, University of Chicago, and University of Maastricht. Special thanks to Rajeev Darolia and Megan Hatch for exceptional research assistance. Errors or omissions belong to me.

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Correspondence to Dylan Conger.

Appendix

Appendix

Table 7 Top 10 origin countries of immigrants by race
Table 8 Differential effects of immigrant peers by nativity/language status of the student

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Conger, D. Foreign-born Peers and Academic Performance. Demography 52, 569–592 (2015). https://doi.org/10.1007/s13524-015-0369-2

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