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High School Economic Composition and College Persistence

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Abstract

Using a longitudinal sample of Texas high school seniors of 2002 who enrolled in college within the calendar year of high school graduation, we examine variation in college persistence according to the economic composition of their high schools, which serves as a proxy for unmeasured high school attributes that are conductive to postsecondary success. Students who graduated from affluent high schools have the highest persistence rates and those who attended poor high schools have the lowest rates. Multivariate analyses indicate that the advantages in persistence and on-time graduation from 4-year colleges enjoyed by graduates of affluent high schools cannot be fully explained by high school college orientation and academic rigor, family background, pre-college academic preparedness or the institutional characteristics. High school college orientation, family background and pre-college academic preparation largely explain why graduates from affluent high schools who first enroll in 2-year colleges have higher transfer rates to 4-year institutions; however, these factors and college characteristics do not explain the lower transfer rates for students from poor high schools. The conclusion discusses the implications of the empirical findings in light of several recent studies that call attention to the policy importance of high schools as a lever to improve persistence and completion rates via better institutional matches.

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Notes

  1. Economists also have attempted to show that high school quality matters not only for interim outcomes, such as receipt of a diploma, college enrollment, and degree completion, but also labor market outcomes (Betts 1995; Strayer 2002). Betts (1995) finds an association between high school attended and earnings, but notes that conventional measures of school quality, such as teacher salaries and average class size are not associated with variation in student performance.

  2. The sampling scheme for the baseline is described in detail in the “Methodology Report,” http://theop.princeton.edu/surveys/baseline/baseline_methods_pu.pdf. For wave 2 surveys, the sampling scheme is described in ‘Senior Wave 2 Survey Methodology Report,’ http://theop.princeton.edu/surveys/senior_w2/senior_w2_methods_pu.pdf. Finally, the wave 3 sampling scheme is described in ‘Senior Wave 3 Survey Methodology Report,’ http://theop.princeton.edu/surveys/senior_w3/senior_w3_methods_pu.pdf. Tables comparing respondent attributes across waves are in the methods reports.

  3. About 66 % of the wave 3 sample enrolled in college within the same calendar year of high school graduation, 14 % delayed college enrollment until the following year or later, and the remaining 20 % had never enrolled anywhere at the wave 3 interview. We exclude 14 percent of the cohort that enrolled with delay to preserve a uniform window for observing completion and persistence and because students who delay enrollment differ in systematic ways from those who do not. In particular, students who delay are more likely to enter via 2-year institutions compared with on-time enrollees. These sensitivity analyses are available from authors on request.

  4. Students could have dropped out and re-enrolled, and also could have attended other institutions during the summers. Transfer students could have attended multiple institutions over the observation window, but nearly 70 % of transfer students attended only two institutions.

  5. These data are obtained from the Texas Education Agency and appended to individual records.

  6. We convert ACT scores if available or predict missing SAT scores using students’ decile class rank, high school curriculum, most recent math and English grades, whether they have taken English and math AP courses, whether languages other than English are spoken at home, race/ethnicity, parental education, high school types, and several high school attributes including % enrolled in grades 11–12 taking AP courses, % AP exams passed, % students passed algebra test, % with college plans, and high school dropout rate.

  7. Using Barron’s selectivity index, we group 4-year institutions into four categories, non/less competitive (e.g., UT-El Paso), competitive (e.g., Texas Tech), very competitive (e.g., UT-Dallas and Texas A&M), highly and most competitive (e.g., Rice University and UT-Austin). For each category, we obtain SAT 25th and 75th percentile mean scores.

  8. About 13 % of 4-year enrollees missing SAT 25th percentile scores for their 1st enrolled institution, and 12 % missing SAT 75th percentile scores. However, only 6 % of students are missing the information among those attending institutions with competitive admissions.

  9. We do not disaggregate 2-year college enrollees by class rank because very few top decile graduates enroll in community colleges, and vocational institutions in particular. Results are available on request.

  10. These transfer rates are based on 4 years after initial enrollment, unlike Adelman’s (2006), which are based on outcomes 8 years after initial enrollment.

  11. These tabulations are available from the authors on request.

  12. Table 7 in Appendix, which presents robustness checks using different working samples, reports the baseline model estimates of high school economic composition.

  13. We estimated a model that interacted class rank and high school economic composition. The interaction terms indicated no difference in persistence odds among top decile graduates who attended affluent, average and poor high schools. Therefore, we report only results from the additive specification.

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Acknowledgments

This research was supported by grants from the Ford, Mellon and Hewlett Foundations and NSF (GRANT # SES-0350990). We gratefully acknowledge institutional support from Princeton University’s Office of Population Research (NICHD Grant # R24 H0047879).

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  1. The College Board, 661 Penn Street, Suite B, Newtown, PA, 18940, USA

    Sunny X. Niu

  2. Office of Population Research Princeton University, 184 Wallace Hall, Princeton, NJ, 08544, USA

    Marta Tienda

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  1. Sunny X. Niu
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Correspondence to Marta Tienda.

Appendix

Appendix

See Tables 5, 6 and 7.

Table 5 Summary statistics for 4-year enrollees by high school economic composition
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Table 6 Summary statistics for 2-year enrollees by high school economic composition
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Table 7 Relative risk ratios for college persistence outcomes using different working samples (clustered SE in parentheses)
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Niu, S.X., Tienda, M. High School Economic Composition and College Persistence. Res High Educ 54, 30–62 (2013). https://doi.org/10.1007/s11162-012-9265-4

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