CUNY Office of Policy Research

Working Paper

At-Risk At College:

Achievement Gaps at CUNY

Colin C. Chellman <colin.chellman@mail.cuny.edu>

David Crook <david.crook@mail.cuny.edu>

Aleksandra Holod <ah2574@columbia.edu>

The City University of New York, Office of Policy Research

Amy Ellen Schwartz <amy.schwartz@nyu.edu>

Leanna Stiefel <leanna.stiefel@nyu.edu>

New York University, Institute for Education and Social Policy,

Steinhardt and Wagner Schools

CUNY OFFICE OF POLICY RESEARCH

555 W. 57th St., Suite 1240

New York, NY 10019

March 2011

© 2011 by CUNY Office of Policy Research. All rights reserved. Short sections of text, not to exceed two paragraphs, may be quoted without explicit permission provided that full credit, including © notice, is given to the source.

1

At-Risk At College:

Differing Paths to Success for Disadvantaged Students in Higher Education

Colin C. Chellman <colin.chellman@mail.cuny.edu>

David Crook <david.crook@mail.cuny.edu>

Aleksandra Holod <ah2574@columbia.edu>

The City University of New York, Office of Policy Research

Amy Ellen Schwartz <amy.schwartz@nyu.edu>

Leanna Stiefel <leanna.stiefel@nyu.edu>

New York University, Institute for Education and Social Policy, Steinhardt and Wagner Schools

Abstract

Increasing access to postsecondary education for students who have traditionally been excluded from

participation is a goal that is gaining greater attention from foundations and policymakers in recent years.

Access without completion, however, is problematic and college completion rates are stubbornly low.

Indeed, while between 1992 and 2006, the national college-going rate increased from 54% to 62%, college

completion rates remained relatively flat. Furthermore, disadvantaged students completed college at a much

lower rate than their more advantaged peers. Our study aims to examine the educational pathways of

students who are successful in higher education despite their disadvantaged backgrounds.

Success in this paper is measured as graduation from a four–year City University of New York (CUNY)

college within six years. We define individual (dis)advantage as individual-level demographic factors

shown to increase (decrease) a student’s odds of graduating from college and pre-college and college (dis)advantage as factors at these stages that support (impede) college success. Conducting multivariate

regression analysis with fixed effects to account for unobserved college characteristics, we examine

whether early indicators of student success vary depending on students’ (dis)advantage profiles.

Our data are uniquely suited to answering questions about students’ higher education trajectories; CUNY

maintains a rich database that allows us to track 11 cohorts of students -- from the application process to

graduation -- and to identify several successful outcomes, one of which, six-year graduation, we focus on in

this paper. We improve on previous research by including students who entered college in the spring

semester in our analyses. Ultimately, our results may inform the development of an early warning system at

CUNY, and other systems that serve large numbers of disadvantaged students, to help target interventions

to students who are at highest risk of failure and drop out.

2

Introduction

Increasing access to postsecondary education for students who have traditionally been

underrepresented is a goal that is gaining greater attention from foundations and policymakers in

recent years. Access alone, however, will not be sufficient to close gaps in post-secondary

degree attainment if disadvantaged students complete college at lower rates than their more

advantaged peers. Trends in college completion rates over the last 15 years suggest concern

about college completion is warranted. While the national college-going rate increased from

54% to 62% between 1992 and 2006, college completion rates remained relatively flat.

Unfortunately, there is little research to guide education policymakers and leaders in colleges,

high schools, or governmental and non-governmental organizations who aim to increase student

success rates. This study explores the early behavioral markers associated with academic

success or failure to aid in the development of interventions that reduce drop out.

Using data on students attending urban four-year colleges at the City University of New

York (CUNY), the city’s public university system, we examine the educational pathways of

students who are successful in higher education despite of their disadvantaged backgrounds.

What distinguishes those who succeed from those who do not? How early can we effectively

identify students who are at high risk of failure? We first focus our analyses on two background

characteristics known to be related to the rates of degree attainment among college students --

race and gender -- to investigate whether risk factors differ along these dimensions of

demographic background. We then add factors that capture high school performance and

ultimately college enrollment, program participation, and performance. We improve on previous

research by including students who entered college in the spring semester in our analyses and by

using 11 cohorts of students.

3

What Factors Might Influence Success?

High School and College Factors

Students’ academic preparation in high school, including enrollment in a college-

preparatory curriculum and grade point average, clearly shape a student’s prospects for success

at college (Adelman, 2006; Bowen, Chingos, & McPherson 2009; Murtaugh, Burns, & Schuster,

1999). Adelman (2006) suggests that enrolling in a college preparatory curriculum is the most

important step on the path to a baccalaureate. Bowen, et al. (2009) suggest GPA matters because

it is a marker of the motivation and skills needed to succeed in college, such as good study habits

and time management.

Several aspects of first-year college performance and enrollment are also related to

degree completion. GPA and number of credits accumulated in the first year are important early

college predictors of persistence and ultimate baccalaureate completion (Adelman, 2006;

Herzog, 2005). Students who enroll immediately after graduating from high school, enroll full

time, and attend summer school are also more likely to earn a bachelor’s degree (Adelman, 2006;

McCormick & Carroll, 1999; O’Toole, Stratton, & Wetzel, 2006). Finally, receiving certain

types of financial aid is positively associated with student persistence (e.g. St. John, 1991; Chen

& DesJardins, 2008). Receipt of a Pell grant or merit aid – two forms of financial assistance that

do not need to be repaid – significantly increases the likelihood that low-income students will

complete their bachelor’s degree in one recent study (Chen & DesJardins, 2008). Because high

school preparation and college factors are likely to influence college completion, we include

these in our models.

Race and Ethnicity

4

The link between race and baccalaureate attainment is well established (Bowen & Bok,

1998; Camburn, 1990; Cook & Cordova, 2007; Peltier, Laden, & Matranga, 1999). Black,

Hispanic, and Native American students graduate from high school, enroll in college, and

complete college at lower rates than white and Asian students (Bowen & Bok, 1998; Cook &

Cordova, 2007). These race-related differences in degree attainment can be explained in part by

accounting for other structural background characteristics, such as SES, academic preparation in

high school, and other variables (Adelman, 2006; Velez, 1985).

Previous studies also suggest that persistence and retention processes are different for

various racial and ethnic groups. For example, early college GPA is more predictive of

persistence for minority students that for whites (Zea, Reisen, Beil, & Caplan, 1997; Nora &

Cabrera, 1996). One study of college students in Indiana found that parental education was more

predictive of persistence for white students than for blacks and Hispanics, and that receipt of

adequate financial aid is particularly important for black students (St. John, Carter, Chung, &

Musoba, 2006 as cited in Carter, 2006). St. John, Hu, Simmons, Carter, and Weber (2004)

suggest that pursuing a college education may have different meaning for minorities and whites.

Whites are more likely to have the economic resources to treat a college degree as having

symbolic value, while black students may view the choice to go to college and their field of

study as a stepping stone to a better paying career (St. John, Hu, Simmons, Carter, & Weber,

2004). Following this literature, we examine differences between racial/ethnic groups in our

models.

Gender

Student gender is also tied to rates of college success. Over the last thirty years, women

have surpassed men in college degree attainment (Goldin, Katz, & Kuziemko, 2006; Sum et al.,

5

2003). In 2000, women were awarded 133 bachelor’s degrees for every 100 degrees awarded to

men (Sum et al., 2003). Patterns of undergraduate enrollment and degree attainment by gender

have remained steady since approximately 2000, with men representing 43 percent of college

enrollees and 43 percent of baccalaureate graduates (American Council on Education, 2010).

A number of hypotheses have been proposed to explain why women earn bachelor’s

degree at higher rates than men. First, women may be better academically prepared for college.

They have fewer behavioral problems during the K-12 years, spend more time on homework,

earn higher grades, and graduate from high school at higher rates (Goldin, Katz, & Kuziemko,

2006). As a result, it simply may be easier for women to keep up with the academic work

necessary to earn a bachelor’s degree. Second, women’s labor market returns to a college

education are higher than men’s (Dougherty, 2005). Finally, demographic shifts in marriage and

family structure, i.e. greater rates of divorce and single parenthood, have increased women’s

responsibility for supporting themselves and their families. These changes may have increased

women’s motivation to pursue higher education (Goldin, Katz, & Kuziemko, 2006). Following

this literature, we examine gender differences in our empirical work. We also examine gender

differences within racial/ethnic groups, because the size of the gender gap tends to vary across

groups (Sum et al., 2003).

Spring Enrollment

Previous research acknowledges that patterns of student enrollment are associated with

student success. For example, students who enroll immediately after high school, attend full-

time, and maintain continuous enrollment are more likely to complete a baccalaureate degree

(Adelman, 2006; Bozick and DeLuca, 2005; McCormick & Carroll, 1999; O’Toole, Stratton, &

Wetzel, 2006). Even after acknowledging the importance of enrollment patterns, however, few

6

studies of student attrition or persistence attend to the differences between fall and spring

entrants (e.g. Attewell & Lavin, 2007; Bowen, Chingos, & McPherson, 2009). Retention studies

that focus exclusively on fall entrants exclude important demographic groups. For example,

Hispanic and black students are less likely than white students to start their studies in the fall

term. Lower SES students are also less likely to enroll in the fall, as compared to students from a

higher SES background (Adelman, 2006). A preliminary analysis of CUNY data suggests that

students who begin their post-secondary education in the spring semester tend to be less

academically prepared than fall entrants. Including spring entrants in our sample is an important

step to remedying this oversight in previous research. We also investigate the impact spring

entrance has on the likelihood of student success.

Data Source and Sample

To address our research questions, we use a student-level dataset drawn from

administrative files maintained by CUNY’s Office of Institutional Research and Assessment

(OIRA). Our data are uniquely suited to answering questions about students’ higher education

trajectories. CUNY’s database allows us to track student progress -- from the application

process to graduation -- and to identify proximal and distal college outcomes such as credit

accumulation, grade point average (GPA), and graduation. We track 11 Baccalaureate cohorts

across six years – or 150% of on-time graduation – in order to capture the majority of CUNY

graduates, who do not graduate “on-time” (i.e., four years).

Our sample consists of first-time freshmen students who entered CUNY Baccalaureate

programs in the fall or spring of academic years 1999-2004. We follow these students through

the CUNY system for six years, even if they transfer within the system. If students leave the

CUNY system, however, we do not have data on them and they are recorded as not being

7

retained and not graduating.1 As mentioned previously, we include both fall and spring entrants

in our analytic sample. The sample excludes the students who attended high school overseas or

who entered CUNY with GEDs, because they are missing data on key variables.

Table 1 displays descriptive statistics for the fall 1999 and fall 2004 cohorts of

Baccalaureate students entering CUNY; the fall 2004 cohort is the last cohort for which we can

calculate 6-year graduation rates. The proportion of black and Hispanic students per cohort

decreased slightly, while the proportion of Asian students per cohort increased slightly.

Approximately half of the fall 2004 cohort received Pell grant aid, down four percentage points

from the fall of 1999. Women composed 58% of the Fall 2004 cohort, as compared to 62% in

fall 1999. The graduation rate increased 5 percentage points from 43% to 48% over the

observation period.

We also calculated descriptive statistics (not shown) for the 57,211 students in the entire

sample. The analytic sample has an overall six-year graduation rate of 45%. This rate varies

substantially across subgroups of students, however, with white and Asian students graduating at

rates of 53-54% while the black student graduation rate is 35% and that of Hispanic students is

36%. Female graduation rates are higher than males (49% versus 39%) as is true nationwide,

with some variation in the gender gap within race groups. Among white students, women

graduate at a 59% rate, considerably higher than the 45% graduation rate for men. Among black

students, the disparity is somewhat lower: women graduate at a 38% rate while the graduation

rate for black men is 28%, and Hispanic women graduate at a 41% rate which is considerably

1 To be more precise, we analyze systemwide graduation rates rather than institutional rates. That is to say, students

in each cohort are counted as retained or graduated as long as they remain enrolled in, or graduate from, the

university system, not just their original institution. Therefore, a student who is enrolled in year two at a school within the system other than the one in which s/he originally enrolled is counted as having been retained.

Additionally, four- and six-year graduation rates are cumulative and include students who graduated within the

university system before the end of that particular reporting period. Although for this project we cannot track

students who leave the CUNY system, other internal analyses by OIRA suggest that few obtain a BA degree within

six years from other non-CUNY institutions.

8

higher than the 28% rate among Hispanic men. The lower overall rates for black and Hispanic

men make them a particularly important subgroup upon which to focus early indicators and

intervention efforts.

Methods

We estimate a series of probit models with cohort year and college fixed effects to

identify factors that increase (decrease) the likelihood of graduating within six years. We then

split the sample by race and gender and explore whether – and how much – the predictors of

success differ across subgroups.

Our first model – labeled “Background” – includes only background (non-academic)

characteristics of students:

(1) G i = β0 + β1R i + β2S i + β3I i + β4SPi + α + γ + εi

where G is a dichotomous variable that takes a value of 1 if student i graduated within six years;

R represents indicators for the five non-overlapping racial/ethnic groups; S is the gender of the

student taking the value of 1 for female; I represents variables related to student income,

including their dependency status (for aid purposes), and receipt of Pell grant; α represents

cohort year fixed effects; γ represents college fixed effects; and ε is an error term with the usual

properties.

The second model – labeled “Pre-CUNY”-- adds high school performance variables and

first term financial aid:

(2) G i = β0 + β1R i + β2S i + β3I i + β4SP + β5C i + β6RGTi + β7D i + β8F i + α + γ + εi

9

where G, R, S, I, SP, α, γ, and ε are defined as above; C represents the College Admissions

Average (CAA), more commonly known as high school grade point average, and College

Preparatory Initiative (CPI) units2, both expressed as z scores; RGT represents the highest score

on the New York State high school math test (Regent’s math) attained by a student and the

student’s high school English test score (Regent’s English), both expressed as z scores. The

Regent’s exams are a series of high school exit exams required for graduation in the state of New

York; D represents “no delay after high school” (less than 15 months); and F represents total

financial aid award in a student’s first term, expressed as a z score.

The third and final model – labeled “Post-CUNY”– supplements the previous two by

adding non-academic characteristics and program participation indicators for students when they

enter CUNY as well as including CUNY intermediate academic outcomes of students. This third

model is specified as:

(3) G i = β0 + β1R i + β2S i + β3I i + β4SPi + β5C i + β6RGTi + β7D i β8F i + β9SEEKi + β10SMR i

+ β11FTi + β12GPA i + β13CREDi + α + γ + εi

where G, R, S, I, SP, C, RGT, D, F, α, γ, and ε are defined as above; SEEK takes a value of 1 if

a student participated in the SEEK program; SMR takes a value of 1 is the student took courses

in the summer following the first year at CUNY; FT represents full-time attendance in the first

semester; CUNY GPA represents a student’s cumulative GPA after the first year (z score); and

CRED is a student’s credits accumulated after the first year (again, expressed as a z score).

2 High school units (or CPI units), total and by subject, are calculated as the number of units taken in courses

designated as college-preparatory by CUNY’s University Application Processing Center (UAPC), which is charged with standardizing high school course credits and grade point averages within and across school districts. Generally,

a full year course is worth 1 unit; units are pro-rated for courses offered for less than a full-year (e.g., a one-semester

course is worth 0.5 units). A student’s overall CAA is calculated as the weighted average of grades received in all

high school courses designated as college preparatory by UAPC: English, Math, Social Sciences, Science, Foreign

Language, and Fine Arts.

10

As mentioned previously, all models include college fixed effects to distinguish the

different CUNY’s baccalaureate granting colleges. Finally, we include cohort fixed effects by

year.

Results

All Students

As shown in Table 2, where marginal values of probit estimates, evaluated at means are

displayed -- holding other variables constant -- black and Hispanic students are less likely to

graduate than other racial and ethnic groups, although the magnitude of this effect is muted as

controls for high school performance and early college factors are introduced. As expected,

female students are always more likely to graduate, with the magnitude of the effect becoming

more muted with additional variables. In the pre-CUNY model, which includes high school

performance variables, we find that CPI units and CAA are significant predictors of graduation.

CAA appears to be more strongly associated with graduation success than the number of college-

preparatory course units earned in high school because the z-score coefficient is twice as large.

This makes sense, because students need a minimum number of CPI units to graduate from high

school. In our final model, summer school attendance, first semester GPA, and first semester

credits earned all emerge as strong predictors of graduation, while spring entrance is associated

with substantially lower likelihood of graduation (the latter in all models).

Racial/Ethnic Subgroups

Table 3 displays results for students by racial/ethnic group. Examining the coefficients

for demographic characteristics we see that the importance of gender varies across racial/ethnic

groups. Women of all ethnic groups are more likely to graduate, but the gender effect is

substantially larger for Hispanic students and white students. White students who are financially

11

dependent on their parents graduate at higher rates than white students who are financially

independent, but dependency status does not significantly predict graduation for other

racial/ethnic groups. Pell receipt significantly increases the likelihood of graduation for all

racial/ethnic groups, especially Asians. Spring entry is negatively associated with graduation for

all racial/ethnic groups.

Two high school performance variables are significant and positive for all racial/ethnic

groups: the number of college preparatory units (CPI) taken by a student in high school and high

school GPA for college preparatory courses (CAA). Somewhat unexpectedly, higher scores on

the Regents’ exams – New York’s high school exit exams – are associated with a very small

decrease in the probability of graduating among some groups.

College enrollment patterns and early college performance are also significantly

associated with graduation within 6 years of entry. Enrolling within a year of completing high

school and taking summer courses are associated with higher graduation rates for all racial/ethnic

groups. The latter has the highest magnitude for white and Hispanic students. Full-time

enrollment has a positive effect on graduation for whites and Asians but does not achieve

significance for blacks and Hispanics. A one standard deviation increase in first semester GPA

or credits earned is associated with a large increase in the likelihood of graduation for all groups.

Black Men, Black Women, Hispanic Men and Hispanic Women

Table 4 displays results for particularly at-risk groups of students, black and Hispanic

men, with black and Hispanic women included for comparison. Comparing gender subgroup

results for black and Hispanic students suggests that the positive association between Pell receipt

and graduation shown for these students in Table 3 was driven by women. Regardless of the

ethnic/gender category to which they belong, students who took more college preparatory units

12

and earned higher GPAs in high school are more likely to graduate. Attending summer school

has a uniformly positive association with graduation as do first semester GPA and credits

accumulated. The two enrollments variables that do differ in importance across groups are “no

delay after high school” and spring entrance. Entering college with a year of graduating from

high school has a stronger association with graduation for female students than male students,

within racial/ethnic group. Spring entrance has a negative effect for all groups, except black

women.

Conclusions and Discussion

The goal of this study is to identify risk factors that are most strongly associated with

student attrition. We also investigate whether risk factors for college drop out vary with student

race/ethnicity or gender. We find that many of the variables we examined were significantly

associated with college success across all groups of students. For example, we find that

academic performance during high school and early college are predictive of student success for

all students. High school and college GPA and the number of credits students earn in their first

semester are among the most influential variables we examined. Student enrollment choices,

such as the decision to enroll attend summer school, are also important for all groups.

Several of the predictors in our models have effects only for specific subgroups of

students. Receipt of Pell grant aid was not significantly associated with graduation for black or

Hispanic men. Enrolling in college within a year after high school was positively associated with

graduation for all groups, except black men. Spring entrance was negatively associated with

graduation for all groups other than black women. Higher Regents English test scores were

associated with a slightly reduced likelihood of earning a baccalaureate degree among black

women and Hispanic women.

13

Our research will assist CUNY administrators with the development of an early warning

system that tracks student progress and appropriately targets interventions to students at-risk of

drop out. Results suggest that baccalaureate students entering CUNY may initially be flagged as

“at-risk” based on demographic background. Descriptive statistics indicate that fewer than half

of black and Hispanic students graduate (33% and 36%, respectively), while more than half of

white and Asian students graduate (53% and 54%, respectively). Examining these at-risk groups

by gender, we see that only 28% of black men and 28% of Hispanic men who entered CUNY

four-year colleges had completed a baccalaureate degree six years later. Thus, an early warning

system aimed at reducing achievement gaps between racial and ethnic groups must focus on

black and Hispanic students, especially men.

Aspects of high school academic performance may also be used to initially identify

students at risk of drop out, because the number of college preparatory units and high school

grade point averages were both strongly associated with graduation. Our initial set of step-wise

models demonstrates that enrollment and academic performance at CUNY mediates

approximately one third of the high school GPA “effect”. Therefore, a comprehensive early

warning system would take these college factors into account as students progress through their

studies. First-year college GPA and number of credits accumulated are two variables that are

consistently associated with the probability of drop out for all racial and ethnic groups, and for

men and women. The models for black and Hispanic men also point to some “protective

factors” that may matter for these groups. Attending summer school was associated with a

slightly higher probability of graduating for both black and Hispanic men. Entering college after

high school without a delay was also positively associated with graduation for Hispanic men.

14

To be clear, the models we develop and estimate likely reflect many endogenous

relationships and we make no claim that the estimated coefficients are capturing causal

relationships. For example, those who attend summer school and complete more rather than

fewer credits their first year at CUNY are perhaps more likely to graduate in the first place.

Nonetheless the factors we identify can be used in at least three ways to improve the graduation

rates of at-risk students.

First, the statistically significant factors can be used to flag students at risk for special

attention. Second, and related, the flags used can be differentiated by subgroup. For example,

black and Hispanic students with below average high school grade averages need attention when

they enter CUNY. Third, the statistically significant factors may point to programs and

interventions that have the potential help students. These interventions, of course, would need to

be evaluated. As an example, black and Hispanic students who attend summer school after the

first year are more likely to succeed and, thus, incentives to help them do this could be helpful.

The number of credits accumulated during the first year at CUNY is important for all groups

and, thus, academic counselors may want to encourage students to take more credits and provide

them with support services so that they complete their courses rather than withdrawing mid-term.

There might, however, be a tradeoff between taking additional credits and first year GPA, which

would need to be monitored, since a higher GPA is also predictive of success.

The models we have developed point to the need to differentiate the systems by

subgroups, especially in urban post-secondary education systems with large numbers of at-risk

students. We also need to experiment with and rigorously evaluate alternative retention

programs that account for the varying importance of predictor variables across racial/ethnic and

15

gender groups. In future analyses, we expect to further explore both the student and institutional

characteristics that are associated with student success using duration models.

16

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Table 1: Descriptive Statistics for All Students

Baccalaureate Cohorts Entering CUNY in Fall 1999 and Fall 2004

Fall 1999 (N= 7,845) Fall 2004 (N= 10,349)

Variable Mean SD Mean SD % Change

6-year Grad Rate 0.426 0.495 0.481 0.500 0.055

White Student 0.328 0.469 0.323 0.468 -0.005

Black Student 0.221 0.415 0.194 0.395 -0.027

Hispanic Student 0.274 0.446 0.263 0.440 -0.011 Asian or Pacific Is. Student 0.176 0.381 0.218 0.413 0.042

Native American Student 0.001 0.037 0.002 0.043 0.001

Female 0.618 0.486 0.577 0.494 -0.041 Pell recipient 0.548 0.498 0.505 0.500 -0.043

Total Financial Aid, Sem 1 2718.584 1115.986 3008.718 1551.181 290.134

Total CPI units 18.371 3.664 18.844 3.503 0.473

Total CAA 81.636 5.779 82.257 6.568 0.621 Highest Regents Math 80.688 15.329 79.929 13.258 -0.759

Regents English 72.423 10.130 80.718 10.035 8.295

No delay after high school 0.909 0.287 0.933 0.250 0.024 SEEK 0.219 0.413 0.178 0.383 -0.041

Attended Summer after First Year 0.385 0.487 0.317 0.465 -0.068

Attended Full Time 0.942 0.234 0.979 0.145 0.037 GPA, Sem 1 2.474 0.989 2.663 0.943 0.189

Credits earned, Sem 1 9.538 4.511 11.237 4.136 1.699

19

Table 2: Six-Year Graduation

Baccalaureate Cohorts Entering CUNY in Fall and Spring, Fall 1999 - Fall 2004

(1) (2) (3)

VARIABLES Background Pre-CUNY Acad. Year 1

Black Student -0.141*** -0.099*** -0.064***

(0.006) (0.006) (0.007)

Hispanic Student -0.153*** -0.130*** -0.079***

(0.006) (0.006) (0.006) Asian or Pacific Is. Student -0.008 -0.021** -0.001

(0.006) (0.006) (0.007)

Native American Student -0.058 -0.046 -0.032 (0.054) (0.058) (0.061)

Female 0.130*** 0.093*** 0.075***

(0.004) (0.005) (0.005)

Dependent (for aid purposes) 0.172*** 0.076* 0.074* (0.032) (0.033) (0.035)

Pell recipient 0.022*** 0.039*** 0.029***

(0.005) (0.005) (0.005) Spring Entrant -0.141*** -0.127*** -0.083***

(0.006) (0.009) (0.010)

Total Financial Aid Awarded (Sem 1 (z)) 0.011 0.004 (0.006) (0.006)

Total CPI units (z) 0.054*** 0.031***

(0.003) (0.003)

Total CAA (z) 0.127*** 0.072*** (0.003) (0.003)

Highest Regents Math (z) -0.002 -0.012***

(0.003) (0.003) Regents English (z) 0.002 -0.012***

(0.003) (0.003)

No delay after high school 0.118*** 0.115***

(0.008) (0.009) SEEK 0.003

(0.007)

Attended Summer after First Year 0.143*** (0.005)

Attended Full Time 0.057***

(0.015) GPA, Sem 1 (z) 0.143***

(0.004)

Credits earned, Sem 1 (z) 0.119***

(0.004)

Observations 57211 57211 57211

Pseudo R2 0.060 0.110 0.216 *** p<0.001, ** p<0.01, * p<0.05. Probit regression, reporting marginal effects. Robust standard errors in

parentheses.

Models include -- but results are not shown for -- controls for cohort year, college attended, and indicators for

missing data.

Omitted categories: white, male, independent (for aid purposes), Fall entrants.

20

Table 3: Six-Year Graduation, by Race/Ethnicity

Baccalaureate Cohorts Entering CUNY in Fall and Spring, Fall 1999 - Fall 2004 (1) (2) (3) (4) VARIABLES White Black Hispanic Asian

Female 0.082*** 0.052*** 0.084*** 0.057***

(0.008) (0.010) (0.009) (0.011)

Dependent (for aid purposes) 0.143* 0.116 -0.039 0.070

(0.066) (0.062) (0.048) (0.106)

Pell recipient 0.020* 0.025* 0.025* 0.048***

(0.009) (0.011) (0.010) (0.012)

Spring Entrant -0.091*** -0.048** -0.091*** -0.100***

(0.019) (0.016) (0.016) (0.025)

Total Financial Aid Awarded (Sem 1 (z)) -0.008 0.010 0.007 -0.028

(0.013) (0.010) (0.011) (0.019)

Total CPI units (z) 0.033*** 0.026*** 0.032*** 0.028***

(0.006) (0.007) (0.006) (0.008)

Total CAA (z) 0.073*** 0.076*** 0.063*** 0.071***

(0.006) (0.006) (0.006) (0.007)

Highest Regents Math (z) -0.016** -0.010 -0.012* -0.009

(0.006) (0.006) (0.005) (0.008)

Regents English (z) -0.011* -0.016** -0.006 -0.015*

(0.006) (0.006) (0.005) (0.006)

No delay after high school 0.122*** 0.104*** 0.102*** 0.118***

(0.017) (0.014) (0.015) (0.025)

SEEK -0.004 0.000 0.011 0.002

(0.019) (0.014) (0.012) (0.016)

Attended Summer after First Year 0.163*** 0.120*** 0.133*** 0.118***

(0.009) (0.010) (0.009) (0.011)

Attended Full Time 0.071** 0.005 0.054 0.081*

(0.025) (0.025) (0.029) (0.038)

GPA, Sem 1 (z) 0.134*** 0.137*** 0.138*** 0.144***

(0.006) (0.007) (0.006) (0.008)

Credits earned, Sem 1 (z) 0.128*** 0.116*** 0.116*** 0.096***

(0.007) (0.008) (0.007) (0.008)

Observations 19224 12141 14639 11126

Pseudo R2 0.209 0.205 0.196 0.186 *** p<0.001, ** p<0.01, * p<0.05. Probit regression, reporting marginal effects. Robust standard errors in

parentheses.

Models include -- but results are not shown for -- controls for cohort year, college attended, and indicators for

missing data.

Omitted categories: male, independent (for aid purposes), Fall entrants.

21

Table 4: Six-Year Graduation, by Race/Ethnicity and Gender

Baccalaureate Cohorts Entering CUNY in Fall and Spring, Fall 1999 - Fall 2004

(1) (2) (3) (4)

VARIABLES

Black

Men

Black

Women

Hispanic

Men

Hispanic

Women

Dependent (for aid purposes) 0.057 0.139 -0.100 0.010

(0.104) (0.075) (0.055) (0.068)

Pell recipient 0.008 0.034* 0.019 0.029*

(0.016) (0.014) (0.015) (0.014)

Spring Entrant -0.063** -0.040 -0.069** -0.103***

(0.021) (0.021) (0.022) (0.022)

Total Financial Aid Awarded (Sem 1 (z)) -0.007 0.019 0.026 -0.008

(0.016) (0.014) (0.015) (0.014)

Total CPI units (z) 0.030** 0.023** 0.026** 0.035***

(0.010) (0.009) (0.009) (0.008)

Total CAA (z) 0.065*** 0.082*** 0.053*** 0.068***

(0.009) (0.009) (0.008) (0.008)

Highest Regents Math (z) -0.007 -0.011 -0.008 -0.014*

(0.009) (0.007) (0.008) (0.007)

Regents English (z) -0.009 -0.020** 0.006 -0.014*

(0.009) (0.007) (0.008) (0.007)

No delay after high school 0.036 0.141*** 0.080*** 0.114***

(0.021) (0.018) (0.020) (0.021)

SEEK 0.032 -0.015 0.026 0.002

(0.023) (0.017) (0.018) (0.015)

Attended Summer after First Year 0.119*** 0.119*** 0.101*** 0.150***

(0.016) (0.013) (0.015) (0.012)

Attended Full Time -0.026 0.020 0.023 0.069

(0.039) (0.033) (0.042) (0.038)

GPA (Sem 1 (z)) 0.119*** 0.143*** 0.125*** 0.143***

(0.010) (0.009) (0.009) (0.009)

Credits earned (Sem 1 (z)) 0.096*** 0.125*** 0.095*** 0.125***

(0.011) (0.010) (0.010) (0.010)

Observations 4077 8064 5299 9223

Pseudo R2 0.217 0.195 0.193 0.182

*** p<0.001, ** p<0.01, * p<0.05. Probit regression, reporting marginal effects. Robust standard errors in parentheses.

Models include -- but results are not shown for -- controls for cohort year, college attended, and indicators for missing

data.

Omitted categories: independent (for aid purposes), Fall entrants.