Race and Income in Higher Education

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Abstract: Within the American education system, a radical reshuffling of student demographics is underway. While broad demographic shifts in higher education are covered fairly often in academia and media, the literature seems to overlook important distinctions between different categorizations of institutions, such as online/traditional, private/public, and two-year/four-year universities.  It is the purpose of this study to address this hole in the literature by showing how these shifting demographics—specifically race and socioeconomic status—manifest across Ivy League institutions, with a special focus on Dartmouth College, as compared to non-Ivy League American Universities. Beyond identifying the demographic disparities across institutions, I also analyze some of literature which explores some of the underlying causes of these trends.

Introduction: Within the American education system, a radical reshuffling of student demographics is underway. As of 2014, the National Center for Education Statistics (NCES) reported that, for the first time, the total percentage of minority students – Latinos, African-Americans, Asian-Americans, Pacific Islanders and Native Americans combined – was larger than the percentage of whites in public grade-school classrooms (NCES 2014).  While lagging behind grade-school classrooms, these demographic shifts are reflected in higher education as well with the percentage of minority students growing from 29% in 2000 to 42% in 2014 (Hussar 2016, 4). Not only limited to race, the demographic landscape in higher education has made notable shifts in many categories including age, gender, and socioeconomic status.

Though these broad demographic shifts in higher education are covered fairly often in academia and media (Keller 2001) (Williams 2014), the literature seems to overlook important distinctions between different categorizations of institutions, such as online/traditional, private/public, and two-year/four-year universities.  It is the purpose of this study to fill this hole in the literature by showing how these shifting demographics—specifically race, age, socioeconomic status and geography—manifest across these different institutional categories with a special focus on Ivy League institutions. Beyond identifying the demographic disparities across institutions, I will also analyze some of the underlying causes of these trends.

Income: Before exploring the ways in which the demographics within higher education have changed over the past half-century, namely in terms of race, it is important to look into one defining demographic that has remained constant over this period–the socioeconomic backgrounds of students. As the chart below demonstrates, over the past 50 years, the income stratification among recipients of bachelor degree has remained largely the same since the 1970s.

[Figure 1]

This chart is based on the data collected from the Pell Grant Institute’s 2015 report “Indicators of Higher Education Equity in the United States” (Cahalan, 2015). The data source used in the report is from the October Education Supplement of the Current Population survey conducted by the U.S. Census Bureau. Data from 1970 to 1986 consider unmarried 18- to 24-year-olds, and data from 1987 to 2013 are based on dependent 18- to 24-year-old. The income quartiles have been converted to be read in terms of constant 2014 real dollars in order to adjust for inflation. In 2014, the family income quartiles identified by the Census Bureau were as follows: $0-$34,933, $34,933-$65,496, $65,496-$116,466, and $116,466+. The major limitation of this dataset is that it omits independent students, who constitute roughly 35% of undergraduates (Wei and Neville 2005). As a result, we can expect that the data for the top quartile for dependent students are especially likely to overestimate degree attainment relative to entire population of individuals from the top family quartile.

What is most notable about this chart is that in 2014, 54% of degree recipients were in the top quartile of family income and 10% were in the bottom quartile, marking a 2% decrease in students from the bottom quartile and a 2% increase in students from the top since 1970. Additionally, over the 44-year period, the percentage of bachelor degree recipients coming from the bottom two quartiles  fluctuated between a high of 28.5% in 1977 and a low of 19% in 1985.

Beyond graduation rates, the low-income student experience is very different from that of high-income students on various levels, including major concentration, the control of the institution, and the selectivity of the institution. For example, one of the most salient divisions between selective and nonselective schools can be found in the income backgrounds of the enrolled students. This divide is so striking that the New York Times reported that for every student from the entire bottom half of the nation’s income distribution at Penn, Princeton, Yale, Brown and more than a few other colleges, there appear to be roughly two students from just the top 5 percent (Leonhardt 2016). However, at Dartmouth College, the ratio of low-income to high-income students is even lower than that.

[Figure 2A,  Figure 2B]

These charts compare the family incomes of the US population and of Dartmouth students in 2013. The data is drawn from three sources: (1) Current Population Survey (CPS) Annual Social and Economic (ASEC) Supplement for the 2013 census year, (2) the Office of Financial Aid Data for 2013 (Asch 2014), and (3) data collected through Dartmouth Pulse.  This chart reveals that for every one student in the bottom 45% of the nation’s income distribution, there are nearly ten students in the top 6.5% percent. In other words, 59% of Dartmouth students come from families in the top 6.5% of households by income in America. This lack of economic diversity is by no means unique to Dartmouth or even the lowest compared to peer institutions. Among 179 universities with a five-year graduation rate of 75 percent or higher, Dartmouth ranks only 55th in terms of economic diversity, according to the Upshot’s College Access Index.  However, it is important to note that this index doesn’t use family income, but instead relies on the share of students who receive Pell Grants, the graduation rates of those students, and the net tuition price for low- and middle-income students to determine the accessibility of the institution.

Similar to the Upshot, we will not be looking at the family incomes of all Ivy League institutions and national Institutions as a measure of economic diversity because this information is largely unavailable, incomplete, and unreliable. Instead we will be looking at the proportion of students receiving federal Pell Grants, which are awarded to undergrads from low-income families or low-income independent undergrads to help pay for college. In 2013-2014, 2.3 million or 61% of the 3.8 million Grants were awarded to students with family incomes below 30,000$, and 87% were awarded to students. In addition to family income, Pell Grants are awarded based on family size and number of family members attending college. While this is by no means a perfect measure, several news organizations and scholars alike understand Pell figures as the best available proxy of socioeconomic diversity on campus (Kahlenberg et al 2014) (Muraskin 2004). This next chart gives us insight into how Pell Grants are distributed among the Ivy League as compared to all other universities in the US.

[Figure 3]

The data to make this chart (code) is drawn from the Department of Education’s College Score Card dataset which includes data from 1996 through 2016 for all undergraduate degree-granting institutions of higher education. The percent of undergraduates awarded Pell Grants is only available over the 2008-2014 period. This chart shows that students receiving Pell Grants are far less likely to attend an Ivy League institution than another University. In fact, in 2014, the average percentage of students who received Pell Grants among all national universities was 53% compared to just 14% at Dartmouth and other Ivy League institutions. It is also important to note that while the share of non Ivy League students who received Pell Grants increased from 43% in 2008 to 56% in 2011 in the wake of the Great Recession, we only see an increase of 2% among Ivy Leagues during the same period.

Confirming this trend, Bastedo, M. N., & Jaquette, O. (2011) were able to study the family income of students directly and found that as institutional selectivity increases, the percentage of lower income students decreases. Through an analysis of the US Department of Education statistics, Bastedo shows that in 2004, only 4% of students attending schools he classifies as “Most Competitive” were from the bottom socioeconomic quartile, while 69% of these students were from the top socioeconomic quartile. While the gap between the top and bottom percentiles has declined from 73% to 65% since 1972, this was largely due to the increase of students from the third quartile, who see a 10% increase. Meanwhile, over this 32-year span, the percent of students attending these schools from the bottom quartile only increased by a mere 1.2%.

According to the 2016 Pell Grant Institute report, we do not only see a disparity in Pell Grant recipient enrollment between the level of selectivity of an institution, but we can also see a disparity in the type of level of the institution. Specifically, in 2013, 56% of full-time undergraduates who received Pell or other Federal Grants attended 4-year private institutions rather than 2-year institutions, compared with 75% of students who did not receive any Federal Grants. (Callahan and Perna 2015). We can also see an enrollment difference within the type of control of institution attended by Federal Grant Recipients. According to the National Center for Education Statistics, Federal Grant recipients were more than 3 times as likely as non-Federal Grant recipients to attend private for-profit institutions in 2013 (U.S. Department of Education 2015).

Scholars, policymakers and higher ed institutions alike have all developed many theories trying to explain these various divides between low- and high- income students. Most scholars broadly agree that it is a confluence of factors inclusive different level of schooling, parental education and financial resources. When it comes to specifics, some scholars turn to the strong positive correlation between high SAT scores and high family income to explain why low income students flock to certain types of institutions. Scholars disagree over the causal factor of this relationship, with some arguing that it the SAT score disparity arises because wealthy students can afford prep courses (Buchmann et al 2010). However, other research suggests that test prep has fairly limited effect on scores (Zwick and Green 2007).

Moving beyond SAT scores, other scholars maintain that there is a significant pool of low-socioeconomic-status (SES) students who are attending colleges that are less selective than the ones they could have attended based on their academic preparation or SAT scores. This hypothesis is often referred to as the “under-matching” hypothesis. (Bowen, Chingos, & McPherson, 2009)  Supporting this hypothesis, one 2013 study found that many low income students do not apply to selective college even when their SAT scores are sufficiently high. Instead, these students are more likely to attend non-selective two or four year universities close to their  hometown. The dominant explanation for this trend offered by the authors is that low income students tend to be geographically isolated from other high achieving students and therefore lack the information or encouragement support that high-income students receive (Hoxby and Avery 2013).

In addition to enrollment disparity, the different levels of graduation completion further widens the gap between low- and high income students. According to a series of longitudinal study conducted by the National Center for Education Statistics (BPS: 1996, 2001, 2009), only 26% of first-time students enrolled in a postsecondary education institution obtained a bachelor’s degree within 6 years, compared to 59% of students from the top income quartile. This 33% gap between the two income quartiles have remained largely stable since the first longitudinal study began in 1990.


Unlike income which has been mostly static over the past few decades, the racial demographics of college students have undergone radical reshuffling paralleling that of the general US public.

[Figure 4]

The data used to make this chart is drawn from several sources including the U.S. Department of Education, National Center for Education Statistics, Higher Education General Information Survey (HEGIS), “Fall Enrollment in Colleges and Universities” surveys, 1976 and 1980; Integrated Postsecondary Education Data System (IPEDS), “Fall Enrollment Survey” (IPEDS-EF:90); and IPEDS Spring 2001 through Spring 2015, Fall Enrollment component.  As we can see, the share of White students enrolled in American Universities has declined from 82.6% in 1976 to 55.6% to 2014–a reflection of the decline of the White population in the US from 84.3% to 58.3% during the same time.

[Figure 5]

While in terms of college enrollment, students are more or less racially representative of the rest of the country, in terms of completion rates and receiving a Bachelor degree, the student population is not representative.

[Figure 6]

The data used to make this chart is also drawn from several sources including the U.S. Department of Education, National Center for Education Statistics, Higher Education General Information Survey (HEGIS), “Degrees and Other Formal Awards Conferred” surveys, 1976-77 and 1980-81; Integrated Postsecondary Education Data System (IPEDS), “Completions Survey” (IPEDS-C:90-99); and IPEDS Fall 2000 through Fall 2014, Completions component.

While White, non-Hispanics as a share of degree recipients continue to be overrepresented as compared to the US population, their degree share has decreased from 89% to 69% over the course of 34 years—reflecting the national decline from 80% to 62% in the same period. Meanwhile the percentage of Black degree and Hispanic recipients grew from 7% and 3% to 11% and 11% respectively. Comparing this to the overall shifts in the national population, this means that African Americans and Hispanics are now over 1.5 and 1.8 times as likely to be represented among bachelor’s degree recipients as in the population, respectively. Degree recipients of the remaining races including American Indian and Asian have grown roughly proportionately to the population of the US. We can see this disparity clearly in the following chart.

[Figure 7]

Not only can race be used as a predictor of the likelihood of university completion, but like income, it also can be used to predict the type of university that a student attends. Among Ivy League institutions and most selective colleges, Black and Hispanic students are dramatically underrepresented as compared to the undergraduate average, while Asian students tend to be overrepresented.

[Figure 8]

The data to make this chart (code) is also drawn from the Department of Education’s College Score Card dataset. As we can see the average share of Asians across all Universities has hovered consistently around 3.5% from 1996 to 2014. Meanwhile, at Dartmouth this number has grown from 8.68% to 14.6% over the same period. Inversely, the average share of Blacks and Hispanics across all Universities has increased from 14.9% and 9.34% to 18.9% and 16.2% respectively over this period, while the on Ivy League campuses these numbers have hovered around 7-9%.

While we might be tempted to attribute this racial disparity in the Ivy League to the aforementioned socioeconomic disparity, scholar have shown that the probability of enrolling in a highly selective college is five times greater for white students than black students, even after controlling for income (Hussar 2016). Building off of this finding, other studies have concluded that race and ethnicity have become one of the strongest predictors of SAT scores and in turn college admissions, as compared to family income and parental education levels (Geiser 2015).

Conclusion: While the causes underlying these trends in Higher Education are not yet fully understood, this analysis has shown that in order to begin to explain these trends, it is important to look beyond the aggregate levels of fall enrollment across a given demographic. First, it is important to also look at graduation rates as well, as in the case of race, some races are far more likely to graduate than others. Secondly, it is critical to look at the enrollment and graduation rates by selectivity of institution. By using the Ivy League as a proxy for selectivity, I have demonstrated that there are stark differences in both race and socioeconomic status between Ivy League students and students from other universities. For future research, I would suggest looking at the breakdown in enrollment across other level of institutions including private vs public, two-year vs four-year, and online versus traditional.

Works Cited:

Bastedo, Michael N., and Ozan Jaquette. “Running in place: Low-income students and the dynamics of higher education stratification.” Educational Evaluation and Policy Analysis 33.3 (2011): 318-339.


Buchmann, Claudia, Dennis J. Condron, and Vincent J. Roscigno. “Shadow education, American style: Test preparation, the SAT and college enrollment.”Social Forces 89.2 (2010): 435-461.


Cahalan, Margaret, and Laura Perna. “Indicators of Higher Education Equity in the United States: 45 Year Trend Report.” Pell Institute for the Study of Opportunity in Higher Education (2015).


Dreier, Peter, and Richard D. KAHLENBERG. “Making Top Colleges Less Aristocratic and More Meritocratic.” Web log post. The Upshot. New York times, 14 Sept. 2014. Web.


Geiser, Saul. “THE GROWING CORRELATION BETWEEN RACE AND SAT SCORES: NEW FINDINGS FROM CALIFORNIA.” Center for Studies in Higher Education 10.15 (2015): n. pag. Web.


Hoxby, Caroline, and Christopher Avery. “The missing” one-offs”: The hidden supply of high-achieving, low-income students.” Brookings Papers on Economic Activity 2013.1 (2013): 1-65.


Hussar, William J. “Projections of Education Statistics to 2023.” Projections of Education Statistics to 2023. National Center for Education Statistics, 4 Apr. 2016. Web. 11 Oct. 2016.


Keller, George. “The new demographics of higher education.” The Review of Higher Education 24.3 (2001): 219-235.


Leonhardt, David. “California’s Upward-Mobility Machine.” New York Times. N.p., Sept.-Oct. 2016.


Muraskin, Lana, and John Lee. “Raising the Graduation Rates of Low-Income College Students.” Pell Institute for the Study of Opportunity in Higher Education (2004).


Williams, Joseph P. “College of Tomorrow: The Changing Demographics of the Student Body.” US News. N.p., Sept.-Oct. 2014.


US Department of Education, ed. “The Condition of Education.” National Center for Education Statistics (2014).


U.S. Department of Education, National Center for Education Statistics, Integrated Postsecondary Education Data System (IPEDS), Digest of Education Statistics, 2015. Table 331.20


Wei, Christina Chang Chang, and Stephanie Nevill. “Independent Undergraduates: 1999-2000.” National Center for Education Statistics. N.p., Oct.-Nov. 2005. Web.


Zwick, Rebecca, and Jennifer Greif Green. “New perspectives on the correlation of SAT scores, high school grades, and socioeconomic factors.”Journal of Educational Measurement 44.1 (2007): 23-45.