Elsevier

Social Science Research

Volume 36, Issue 3, September 2007, Pages 1257-1275
Social Science Research

Black students’ graduation from elite colleges: Institutional characteristics and between-institution differences

https://doi.org/10.1016/j.ssresearch.2006.06.006Get rights and content

Abstract

Among the nation’s elite colleges and universities, black graduation rates vary dramatically from institution to institution. Many sociologists have suggested that this is due not to differences in the student bodies but to institutional factors; however, this “institutional hypothesis” has not been recently examined empirically. We test the institutional hypothesis for a set of elite institutions using College and Beyond, a restricted dataset containing data for the entire 1989 cohort of 27 elite institutions, matched to institution-level data, employing HLM techniques. We ask three questions: Do institutional factors affect black students’ probability of graduation? Do they account for between-institution differences in black graduation? And are institutions where blacks have a high probability of graduation the same as or different from those where whites do? Testing for the effect of eight major institutional factors, we find, surprisingly, that only selectivity has a statistically significant effect. Contrary to common belief, selectivity improves black probabilities of graduation, and helps blacks more than it helps whites. It also accounts for roughly 38% of the between-institution variance in black graduation. Finally, we find that after controls, black and white probabilities of graduation across institutions are highly correlated (.909), such that institutions in which blacks are likely to graduate are those in which whites are likely to graduate, too. Findings suggest that researchers should examine other institutional factors in greater depth, as well as the role of pre-college preparation more seriously.

Introduction

The politics of Affirmative Action have made the performance of black students in elite colleges and universities an issue of social and political concern. Indeed, the (2003) Supreme Court case involving the University of Michigan prompted the Bush administration to file a brief with the Court opposing the use of race in admissions at both the undergraduate and graduate levels (Nagourney, 2003). That an Affirmative Action case involving a top university attracted controversy is no accident: the presence of blacks in these gatekeeper institutions is much more contentious than their presence in the typical college. Indeed, as Kane (Dickens and Kane, 1999, Kane, 1998) has shown, it is only in the nation’s elite colleges that Affirmative Action increases black students’ chance of admission. At the vast majority of colleges, blacks would be admitted at the current rates even under completely race-blind policies. Since black students in these institutions have lower graduation rates than whites (Bowen and Bok, 1998), it is of pressing social interest to conduct rigorous research on which factors affect their performance and which do not.

One fact rarely appreciated about elite colleges is the high variance in their black students’ graduation rates. According to the 1997 Journal of Blacks in Higher Education, the 1996 black graduation rate was only 66% at the University of Michigan but 95% at Harvard University. Some of the variance is due to the characteristics of the students who apply, are accepted, and choose to attend different elite institutions. However, sociologists have also suggested that much of it is due to institutional factors. Previous tests of this “institutional hypothesis,” however, have been inadequate because of inappropriate data or modeling techniques.

In what follows we present more rigorous tests of this hypothesis for a set of elite institutions using College and Beyond (C&B). The dataset was the source of Bowen and Bok’s (1998) influential book, The Shape of the River, which covered a wide breath of material but did not examine the institutional hypothesis in depth. Our analysis focuses on why black graduation rates vary across an elite set of institutions. We seek to answer three questions: Do institutional factors affect black students’ probability of graduation? Do they account for between-institution differences in black graduation? And are institutions where blacks have a high probability of graduation the same as those where whites do? We begin by reviewing previous research.

Section snippets

Previous research

A vast, but contradictory literature, stimulated by the Coleman Report (Coleman et al., 1966), has examined the importance of institutional factors for explaining academic success at the primary and secondary schooling levels. Card and Krueger (1996) provide new evidence and review the existing literature, arguing that institutional factors are important. But Hanushek (1996) also reviews the literature and reaches the opposite conclusion.

The literature specifically on higher-education

Data

We use C&B and supplementary datasets. Our sub-sample of C&B is a restricted dataset, collected by the Mellon Foundation, which contains transcript data on most or all students of the 1989 first-year cohort in 27 elite colleges and universities.

Analysis

We examine which institutional factors predict black probability of graduation, how much of the variance across institutions they account for, and whether institutions where blacks have a high probability of graduation are the same as or different from those where whites do.

Which factors matter? Models I to VIII in Table 3 test for the effect of our eight measures. The findings are unexpected. Neither the difference between the average black and average white SAT scores nor the percentage of

Discussion and conclusion

We have three sets of findings. Our first findings were perhaps the most surprising—as almost none of the most common institutional factors expected to affect probabilities of graduation had a statistically significant effect. This occurred for three reasons.

First, we should be clear we did not test for all potentially relevant factors. Future tests and additional data collection are needed to determine whether other factors matter; we consider our study only a first step. For example, one

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