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DEWEV
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Massachusetts Institute of Technology
Department of Economics
Working Paper Series
The Causes and Consequences of Attending
Historically Black Colleges and Universities
Roland G. Fryer, Jr.
Michael Greenstone
Working Paper 07-1
April 9, 2007
Room
E52-251
50 Memorial Drive
Cambridge, MA 021 42
This
paper can be downloaded without charge from the
Network Paper Collection at
Social Science Research
http://ssrn.com/Gbstroct=979336
I
The Causes and Consequences of Attending
Historically Black Colleges
and Universities*
Roland G. Fryer, Jr.
Harvard University and NBER
Michael Greenstone
MIT and NBER
April 2007
We
David Card, David
Bryan Graham, Chang-Tai Hsieh, Lawrence Katz, Henry Louis
Hoxby, Glenn Loury, Enrico Moretti, Andrei Shleifer, Lawrence
Summers, colleagues at the Mellon Foundation, and participants in numerous seminars. Fryer is especially thankful
to the Michor family in Kritzendorf, Austria for their support and generous hospitality while working on the paper.
This paper makes use of the College and Beyond (C&B) database. The C&B database is a restricted-use database.
Researchers who are interested in using the database may apply to the Andrew W. Mellon foundation for access.
Sam Schulhofer-Wohl, Sheldon Bond, Jorg Spenkuch, Elizabeth Greenwood, and Paul Torelli provided exceptional
research assistance. All errors are our own. Correspondence can be addressed to Fryer at the Department of
Economics, Harvard University, 1805 Cambridge Street, Cambridge MA, 02138, (e-mail: rfryer@fas.harvard.edu);
or Greenstone at Department of Economics, Massachusetts Institute of Technology, 50 Memorial Drive, E52-359,
Cambridge MA, 02142 (e-mail: mgreenst@mit.edu)
Gates,
are grateful to
Jr.,
Edward
Cutler,
Glaeser, Lani Gunier, Caroline
Digitized by the Internet Archive
in
2011 with funding from
Boston Library Consortium IVIember Libraries
http://www.archive.org/details/causesconsequencOOfrye
The Causes and Consequences
of Attending Historically Black Colleges and Universities
ABSTRACT
(HBCUs) were practically the only
Using nationally representative data
Until the 1960s, Historically Black Colleges and Universities
institutions
files
of higher learning open to Blacks
in the
irom 1970s and 1990s college attendees, we find
US.
that in the
1970s
HBCU matriculation was
associated with higher wages and an increased probability of graduation, relative to attending a
Traditionally
White
Institution
(TWI).
By
the 1990s, however, there
is
a
wage
penalty, resulting
wages of HBCU graduates between the two decades. We also
analyze the College and Beyond's 1976 and 1989 samples of matriculates which allows us to
focus on two of the most elite HBCUs. Between the 1970s and 1990s, HBCU students report
statistically significant declines in the proportion that would choose the same college again,
preparation for getting along with other racial groups, and development of leadership skills,
relative to black students in TWIs. On the positive side, HBCU attendees became relatively more
likely to be engaged in social, political, and philanthropic activities. The data provide modest
support for the possibility that HBCUs' relative decline in wages is partially due to
improvements in TWIs' effectiveness at educating blacks. The data contradict a number of other
in a
20%
decline in the relative
pre-coUege credentials
and expenditures per student at HBCUs.
intuitive explanations, including relative decline in
students attending
HBCUs
Roland G. Fryer, Jr.
Haiward University
Department of Economics
1805 Cambridge Street
Cambridge,
02138
scores) of
MIT
'
Department of Economics
50 Memorial Drive, E52-359
Cambridge,
02142
MA
MA
^^
andNBER
email: rfryer@fas.harvard.edu
SAT
Michael Greenstone
.
'
(e.g.,
"
•
:
,
,
andNBER
'
email:
mgreenst@mit.edu
Introduction
(HBCUs) have
Historically Black Colleges and Universities
and storied
a proud
role in the
education and progress of Blacks in America. For nearly a century, Historically Black Colleges and
Universities
(HBCUs) were
20%
Today, roughly
of
practically the only institutions of higher learning
22%
of cuirent bachelor's degrees granted
(Wilberforce), Ralph Ellison (Tuskegee), Martin Luther King,
Simmons
HBCU
Among
alumni.
HBCUs, 50%
state,
and
Blacks, 40%) of
80%
of lawyers, and
HBCUs'
all
to a lesser degree, local
While numbers are smaller
of famous
at
non-
for private
HBCUs,
HBCUs
public support
still
In the years 1999-2001, annual total public support of
total revenues.
et al.
2004).
HBCUs
are at a crossroads today. In U.S.
U.S. 717 (1992)), the Supreme Court instructed state legislatures to find "educational
justification" for the existence of
mission.
list
governments. Between 1977 and 2001, 61%) to 73%o of public
averaged roughly $2.65 billion (2005$) (Provasnik
Fordice
(Morehouse), Thurgood Marshall
State) headline a long
HBCU graduates.'
Despite their past successes and historical importance,
V.
and these
W.E.B. Dubois
congressmen, 12.5%) of CEOs, 50%) of professors
of judges are
fiinds.
accounts for nearly a third of
("505
HBCUs
to Blacks.
successes are in no small part due to their substantial financial support from federal,
revenues came from public
HBCUs
Jr.
and Oprah Winfrey (Tennessee
(Dillard),
Blacks in the US.
to
college going Blacks chooses to attend one of the 103
all
institutions are responsible for
(Lincoln), Ruth
open
In response,
some
HBCUs
HBCUs
or integrate them; the latter
would completely
alter their
experienced declines in enrollment, others have pursued dramatic
increases in the fraction of non-Black students, and a
number of HBCUs have seen important
declines in
their financial positions.^
The Supreme Court's
call for
an "educational justification"
is
surely related to the absence of
convincing evidence on the causes and consequences of attending an
proponents claim that they provide an
discrimination and racism.
by engendering
It is
also argued that
a strong sense of
environment that
idyllic learning
communal
HBCUs
HBCU
is
for Blacks.
help to build important social capital for Blacks
responsibility and civic consciousness
networking opportunities for high achieving Blacks (Drewry and Doennarm 2001).
are correct, then
HBCUs
HBCU
from the pressures of
free
offer unique opportunities for educafional and social
and providing
If these
arguments
development of Black
students and the argument for remaining segregated seems justified.
The
data sources are Congressional Black Caucus (congressmen), Black Enterprise (CEOs),
US
Department of
in
enrollment and
Education, Office of Civil Rights (professors), and Ehrenberg (1996) (Lawyers and Judges).
The
ruling had an adverse effect
Mississippi Valley State a
20.1%
on many HBCUs. Alcorn
decrease. Other
HBCUs,
increases in integration. Elizabeth City State increased from
State experienced a
9.9% decrease
especially in North Carolina, have
1
1%
white
from
in
1980 to 23.
7%
11. 9 to 22.2, North Carolina Central from 4.1 to 13.4, and Winston Salem from
such as Florida, the ruling has been largely ignored; Florida
remains 90% black.
A&M
1
shown
substantial
in 1998, Fayetteville State
1.3 to 18.0. In other states,
On
(TWIs)
in
the other hand,
it
HBCUs
possible that
is
preparing Blacks for post-college
life.
are inferior to Traditionally
White
Institutions
If students are taking less challenging courses fi-om less
distinguished faculty, have access to poor resources, or are not investing in the social skills necessary to
of people, then graduates will perform poorly
interact with diverse sets
inferior non-labor
market outcomes. In
in the labor
market and have
HBCUs
scenario, the case for supporting
this
with public
resources appears weak.
This paper empirically assesses the causes and consequences of
future decisions
HBCU
attendance so that the
by governments, students, and parents are based on evidence, rather than theories and
We
historical anecdotes.
analyze
thi^ee large
data sets with adequate pre and post college infonnation for
Blacks that identify the students' choice of college and whether
it
an
is
HBCU. The
data sets are: the
National Longitudinal Sui^vey of the High School Class of 1972 (NLS-72), Baccalaureate and
(B&B), and
the College
and Beyond database (C&B). The
nationally representative sample of
dataset contains four
look into the most
HBCU
students at
two
first
two points
HBCUs, Howard, Morehouse, Spelman, and
elite
HBCUs
in
Beyond
datasets provide a snapshot of a
in time:
1972 and 1992. The third
Xavier, allowing us to take a focused
1976 and 1989. Although there are important limitations with each of
these data sets, together they provide a rich portrait of the causes and labor market and non-labor market
consequences of HBCU attendance. Importantly, these data
and 1990s so
it
is
possible to assess
how
sets
sample college matriculates
in the
1970s
these causes and consequences changed during these
two
decades of dramatic social change.
The
between
analysis uses
HBCU
and
TWI
four separate statistical approaches to adjust for pre-college differences
attendees.
We
begin by using the rich
and high school academic achievement (including
the
same pre-college
SAT
set
scores) to
fit
of covariates on family backgroimd
least squares
models.
then use
covariates to implement a propensity-score matching estimator to assess the
robustness of the results to functional form assumptions about the observables.
These approaches are
supplemented by methods that are designed to account for selection bias due
observations
We
(Heckman 1979) and
bias
to
missing outcome
which emerges when colleges admit students based
characteristics unobsei"ved in our data that are positively correlated with future
partly
on
outcomes (Dale and
Ki-ueger 2002).
The
results are robust across these four
methods. However, lacking a randomized experiment or
may
credible quasi-experiment, thorny issues of selection
remain.
Consequently,
we
urge caution
in
interpreting the results as causal.
Together the nationally representative
HBCU
attendance. In the 1970s,
HBCU
NLS
and
matriculation
probability of graduation, relative to attending a
B&B
reveal an important change in the returns to
was associated with higher wages and an increased
TWI. By
the 1990s, however, there
is
a substantial
wage
Overall, there
penalty.
is
20%
a
Interestingly, relative pre-college
wages of
decline in the relative
HBCU
graduates in just two decades.
measures of student quality (SAT scores,
HBCU
improved among
e.g.)
attendees during this period, so higher achieving students were increasingly choosing these schools at the
same time
that the returns for attending these schools
The underlying source of the decline
in
were
falling behind.
HBCU perfoiTnance is unlikely
reasons, given the high court's stance. Nevertheless, understanding
researchers and educational practitioners.
support,
the possibility
that
HBCUs'
effectiveness at educating blacks.
the decline in
increased
outcomes among
more
The
at
C&B
HBCUs
than at
The data
fail to
decline
relative
is
it
attendees
TWIs between
—
for policy
interest to
and
contradict,
to
in at least
one specification
due to improvements in TWIs'
partially
In contrast, the data contradict a
HBCU
be important
would be of considerable
number of
intuitive explanations for
for example, educational expenditures per student
the 1970s
and 1990s.
provides a rare opportunity to assess the most
elite
evidence of a wage decline between the 1976 and 1989 cohorts but
suggestive because these estimates are imprecise. There
is
colleges.
Here
too, there is
should only be considered
it
HBCU
stronger evidence that the later
matriculates were less satisfied with their choice of college and self-reported developing fewer leadership
and
social skills that are valuable in post-college
later cohort
was
significantly
The paper proceeds
more Hkely
to
Section
as follows.
relative to
life,
TWI
students.
On
the other hand, the
be involved in political, social, and philanthropic
role in the education of blacks in America.
II
activities.
provides a brief history of HBCUS and their important
Section
reviews some theoretical explanations for
III
blacks might benefit (or be haniied) by attending a historically black college or university.
presents the data and
of
HBCU
summary
statistics.
Sections
Section IV
V and VI report results on the causes and consequences
Section VII summarizes the differences between the results from the
attendance.
1
970s and
1990s and assesses alternative explanations for these differences. Lastly, Section VIII concludes.
:
appendix describes the details of our sample constmction.
II.
A
why
A
data
.•
Brief History of Historically Black Colleges and Universities
A. Ante-Bellum Period
The 1860 Census counted 4.4 million Black people
in the
United States, most of
the Southern states and were held as slaves. Prior to the end of the Civil
write
was prohibited by law
(or social custom) in
colleges founded before the Civil War:
University)
was founded
Wilberforce College
in
in
Pennsylvania
Ohio, 1856.
students. Fonrial education for
many
the Institute
in
1837;
areas of the South.
for Colored
whom
War, teaching slaves
Still,
there were three Black
Youth (now known
Lincoln College in
lived in
to read or
Pennsylvania,
as
Cheney
1854,
and
All of these universities served secondary and post-secondai'y
most blacks would not become available
until after the Civil
War, when
the
Freedmen's Bureau, black communities and
their churches,
and private philanthropists organized
schools for Blacks (Donohue, Heckman, and Todd 2002).
B. Post-Civil
War and the Second Morrill Land Grant
During the period immediately following the Civil War, there was a dramatic increase
number of educational
in the
geared toward blacks, funded primarily through groups like the
institutions
American Missionary Association, the Freedmen's Bureaus, and southern
state
governments, especially
during the Reconstruction period. Between 1865 and 1890, over two hundred private black institutions
were founded
in
Very few of these early
the south.
American Missionary Association,
the
awarded bachelor's degrees. The
institutions
Freedmen's Bureaus, and other groups
that
were active
education of freed blacks played a large role in establishing some standard of education
literacy
—
that
would be important when degree granting
institutions for
in the early
—most notably
Blacks opened en masse
in the
1890s.
Most public
next decade, 16
HBCUs
HBCUs
trace their history to the
opened
their doors.
second Moixill Act, passed
The Morrill Act allowed
of land grant universities, with southern and border states creating
Florida
well-known
agricultural, mechanical,
and technical
August 1890.
In the
for the creation of a two-tier system
HBCUs
HBCUs
funds to develop white land grant colleges. These
federal"
training;
in
principally to gain access to
were largely limited
institutions
to vocational
such as North Carolina
A&T
and
A&M were founded during this period.
By
1895, public
education, as
HBCUs
was offered
During the Jim Crow era
at
had awarded 1,100 college diplomas
many
in the
to black students. Yet, liberal arts
public white institutions, remained unavailable to black students.
south that followed Reconstmction, educational opportunities for white
students expanded and blacks were almost completely excluded from white institutions.
1896 decision, Plessy
In the
v.
Ferguson (163 U.S. 537 (1896)), the two-tier system of higher
education, based on the incentive structure in the Second Morrill Act,
result,
HBCUs
schools.
The
demand chain
students into
began
to
become
World War
finnly
set.
As a
rapid expansion of black high schools in southern urban areas set in motion a supplyin
which
HBCUs
availability
to qualify
II
HBCUs,
of teaching positions, supported by
state treasuries,
drew more black
themselves for teaching positions (Roebuck and Murty 1993). There
became an interdependence between
C.
became more
institutions that primarily trained teachers to teach in segregated public
the public school system
and HBCUs.
and the Higher Education Act of 1965
as well as other institutions of higher learning, faced a funding crisis in the 1940s due to
the budget cuts in educational fimding associated with
WWII.
In 1944, the United
Negro College Fund
was
established, raising $765,000 for
been raised by the individual colleges
The landmark decision
developed
to
1965, which
implement
Brown
in
to
much
campaign; three times as
in its first fixnding
as
had
previous three years.
Board of Education (349 U.S. 294 (1955)) and
v.
improved the plight of many HBCUs.
was devoted
HBCUs. As
refen-ing to
it
HBCUs
in the
Title III
the legislation
of the Higher Education Act of
"Strengthening Developing Institutions" was interpreted as primarily
a result
many HBCUs
benefited greatly from the federal funds provided under
Title III, funds that could
be used for faculty and student exchanges, faculty improvement programs,
cumculum improvements,
student services, visiting scholars programs, and administrative improvements.
HBCUs
Despite the material gains to the
arising under the
Higher Education Act, the
NAACP
continued a legal strategy of attacking the two-tier educational system, asking the U.S. Department of
Health, Education, and Welfare to enforce the Civil Rights Act of
1
964 and prohibit southern
operating a segregated higher education system. In the 1973 case of Adams
92
(
D.D.C.), modified and aff d, 480 F.2d
1
159 (D.C. Cir. 1973)), the
v.
NAACP
from
states
Richardson (356
won, requiring
F.
Supp.
that states
develop desegregation strategies that would allow for a better racial mix of students, faculty, and staff
public colleges, and increase the access and retention of minorities at
ruling
was primarily aimed
at
non-HBCUs, however, and
mandate should not be accomplished
at the
improvement of black colleges'
was
that this
the only
way
HBCUs
and
facilities as
HBCUs
for
that they
levels of higher education.
all
made
expense of or detriment
The Adams decision increased funding
not meet their mandates by closing
the court
it
black colleges
to traditionally
because the decision stated that states could
must instead include "yardsticks"
HBCUs
The
clear that fulfilling the ruling's
well as their academic programs.
possible to ensure that
in
The
to
measure the
court's reasoning
would become desirable
was
institutions for white
students.
D. The Unintended Consequences of U.S.
On
litigant
Fordice
-
June 26, 1992, the Supreme Court decided U.S.
v.
.
•.
The
number and
plaintiff,
quality of the
that this resulted
represented by the
NAACP,
court ruled that
it
would be wasteful
to
,
HBCUs
r
staff,
and physical plant
:,y
.
.%'/
^
^
facihties, arguing
of higher education."
maintain the two-tier system that had been erected during an
had eight
institutions, five
white and three black, and
of them (two white and two black) were within 25 miles of one another. The decision was a
victoiy for civil rights lawyers, ordering Mississippi and 18 other southern states to do
its
:.
and traditionally white
racially segregated dual systems
era of de jure segregation, noting that Mississippi
that four
-^
brought the suit because of the disparity in the
academic programs, instmctional
from the "historically operated
,;•::;.'':;
Fordice, a decision brought by a black
with the chief aim of removing structural differences between
institutions.
The
v.
HBCUs
and traditionally white
institutions.
more
to integrate
However, the mling had an adverse
effect
on
HBCUs
to find "educational justification for the continued existence"
consequences of
seem
mling
this
for the future of
possible: 1) a decision that
HBCUs
HBCUs
is
because the court ordered
state legislatures
of the two parallel education systems. The
unclear at this point, but
at least three
outcomes
are indispensable for the education of Blacks and an increase in
public funding; 2) increased recruitment and matriculation of white students, which has the potential to
undermine the unique mission and culture of these
institutions;
and
3) a decision that they
no longer are
necessary (or as necessary) and a commensurate reduction in public financial support.
The remainder of
HBCUs, which
the paper assesses empirically the causes
Conceptual Framework
III.
There are
institutions
and consequences of attending
will help determine their "educational justification."
at
least
three theories for
of higher education.
First,
why
blacks would benefit from racial segregation of
Tatum (1997) argues
that racial
grouping
process in response to racism. This argument goes that segregation by race
that allows individuals to gather support
is
is
a developmental
a positive coping strategy
through shared experiences and mutual understanding. Second,
Wilson's (1987) pioneering study of the South Side of Chicago argues that the migration of talented
blacks
from black neighborhoods had adverse
phenomenon may
exist for
on the individuals
effects
segregation across schools - low
ability blacks
may
left
behind.
A
similar
benefit from segregation
through more intensive interactions with their high ability peers. Third, segregated social connections
within schools
may
Torelli (2006)
shows
in
also reduce adverse peer interactions resulting
that racial differences in the social price for
from
interracial contact. Fryer
with
academic achievement are exacerbated
environments with more inteixacial contact.
There are also several theories for
harm
blacks.
A
social interactions (Case
may
racial segregation across colleges
and universities
may
and Katz 1991, Cutler and Glaeser 1997), and network externalities (Borjas
1995, Lazear 1999), especially for youths.
skill
why
well developed literature emphasizes the importance of peer groups (Coleman 1966),
Many
argue that these effects are important in the fonnation of
and values and the development of human and social
capital.
Moreover, segi-egation across schools
lead to the development of an "oppositional culture" and the enforcement of other negative
behavioral nonns (Ogbu 1989). Additionally, segregation across schools can prevent positive spillovers
between
racially defined peer groups (Lazear 1999).
A
final
disadvantage
of the separation
of racial groups
across
universities
concerns the
importance of interracial contact in mediating stereotypes and promoting understanding and tolerance.
Interracial interaction generally leads to positive sentiment
(Hpmans
"bonding" and "bridging" capital (Granovetter 1973, Putnam 2000)
1950), and fosters the creation of
impossible to identify the separate impact of each of these chamiels on segregated Blacks'
It is
well being with the available data
net impact of
HBCU
sets.
The
attendance.
Instead, this paper's goal
is
produce reliable estimates of the
to
resulting "reduced forni" estimates will likely reflect a
number of
the channels specified in this section.
IV. Data Sources and
We
Summary
Statistics
analyze three large datasets: The National Longitudinal Study of the High School Class of
1972 (NLS-72), Baccalaureate and Beyond Longitudinal Study (B&B), and the College and Beyond
(C&B)
database.
These data
sets
have been chosen because of the enormous amount of information each
contains on pre-college academic performance, family background, college entry decisions, perfoiTnance
while in college, and
later life
outcomes.^ Throughout the analysis, the rich set of pre-college and family
background variables are used
HBCU
and
non-HBCU
and present summary
We
matriculates in equations for the other variables.
statistics
Before proceeding
Fall of
They
discuss each of these sources
from them.
to this material.
Appendix Table
1
provides some
4-year historically black colleges and universities in the United States.
institutions.
between
as conditioning variables to adjust for obsei^vable differences
summary
statistics
on the 89
Foity-nine of them are private
are predominantly located in the South. Together their undergraduate enrollment in the
2005 was 238,911 and there were an additional 37,151 graduate students
The fourteen
enrolled.
historically black 2-year colleges are not included in this table.
A. The National Longitudinal Survey
of the High School Class of 1972
The National Longitudinal Survey of
High School Class of 1972 (NLS-72)
the
representative sample of 23,451 high school seniors in 1972.
the Spring of 1972, and in a supplemental^ sample
and follow-up surveys
in 1973, 1974, 1976, 1979,
the sample, with an average of
A
wide range of data
1
parent's
education
characteristics of each student
also
detailed records
Two
other data
sets
Longitudinal Study 2000
the questions
posed here.
The data include
a nationally
in
a base year survey,
and 1986. Roughly 1,300 high schools are included in
gathered on the students
is
in 1973.
is
were selected
8 students per school in the study.
There
website (http://nces.ed.gov/surveys/nls72).
environment,
drawn
Participants in the sample
(i.e.
and
is
described in detail
in the study, as
detailed information on
occupation,
socio-economic
status,
at the
and
the
high school grades, college admission scores, and so on).
from post-secondary
transcripts,
collected in
NLS-72
each student's family
pre-college
There are
1984, and high school records.
by the National Center for Education Statistics, the National Educational
the Beginning Postsecondary Study (BPS), are equipped to answer some of
Unfortunately, however, these data sets do not track individuals long enough after college
collected
(NELS) and
completion to be useful for understanding
later life
outcomes.
Important for our purposes, a six digit identification number was assigned to educational institutions by
Committee on Education (FICE)
the Federal Interagency
distinguish postsecondary
historically,
to,
schools that qualified as institutions of higher learning from those that did not. These codes are cracial in
HBCUs
defining
B.
and ensuring
that this definition is consistent across data sets.
Baccalaureate and Beyond
The Baccalaureate and Beyond Longitudinal Study (B&B)
a nationally representative sample
is
of 11,192 degree completers from 648 American colleges and universities in the 1992-1993 academic
year.
To
identify a
Aid Study
random sample of degree completers,
as a basis.
B&B
uses the National Postsecondary Student
The National Postsecondary Student Aid Study
is
a large nationally representative
sample of colleges and universities, students, and parents.
A
B&B
the
considerable amount of data
website
characteristics
is
gathered on the students in the study, as described in detail
http://nces.ed.gov/sui"veys/b&b.
of each student, information about
It
contains
their parents
information
detailed
1
997
data
sui-vey,
and
which takes place
after
more extensively, but we found
about.
just
employment and entry
For example,
6%
25%
to
in the
1997 sample. And,
is
Whenever
this difference
to restrict the
was
this attrition
largely
attrited
had hoped
sample
in
the results
if
from
to
in
and the other data
we
cared most
to
TWIs.
sets
HBCUs
graduation rates between
this
use the 2003
from the 2003 sample, compared
from black students
B&B
we employ. The NLS
B&B
samples degree
and non-HBCUs
survey differ with our other data,
we
differ
be clear about
will
A convenient way to handle this is
can be accounted for by differences in samples.
our other data sets to be of degree completers, which
we do
throughout.
The College and Beyond Database
The College and Beyond Database contains student
time students
the
We
begin with samples of students that enrolled their freshman year. The
substantially.
C.
These follow-up surveys
focus on the responses to the
be of generally poor quality on the dimensions
one important difference between the
completers, which can introduce bias
whether
are in the workplace.
of the original black respondents
There
C&B
it
We
into graduate school.
most students
on pre-coUege
and home environment, and financial aid
infonnation. Follow-up sui"veys were administered in 1994, 1997, and 2003.
include information on
at
fall
who
level administrative data
on on 93,660
full-
entered (but did not necessarily graduate from) thirty-four colleges and universities in
of 1951, 1976, and 1989. These institutional records were linked to an extensive survey conducted
by the Andrew W. Mellon Foundation between 1995 and 1997 and
Entrance Examination Board and the Higher Education Research
database: Xavier, Morehouse, Spellman, and
Howard -
the
most
to files
Institute.
elite
provided by the College
There are four
HBCUs. The 1976
HBCUs
in the
cohort contains
data on
four black colleges; the
all
consists of black students
1
989 cohort only includes Morehouse and
The
Xavier.''
from 34 colleges and universities including the four
elite
final data set
HBCUs;
the sample
consists of 2,125 students in 1976 and 1,785 in 1989.
C&B
The
data are remarkably rich, containing infoiTnation
Scholastic Aptitude Test
transcripts,
drawn from
students' applications
(SAT) and American College Test (ACT)
and
as well
scores,
as
infonnation on family demographic and socioeconomic status. This information was attained by linking
the institutional files of the thii1y-four colleges and universities with data provided
Entrance Examination Board and the Higher Education Research
includes the responses to a questionnaire administered to
information on post-college labor market,
all
life satisfaction,
Institute. Importantly, the
Bowen and Bok
D.
Summaiy
and other outcomes. The response
is
who
(1998).
statistics for the variables in
our core specification are displayed in Table
Table
1
consists of five sets of columns.
first
college
An
year college a student attends.
then attends an
with
B&B
HBCU
whose
Across
individual
NLS-72,
HBCUs
C&B
SAT
are
and
C&B
column provides summary
first
college
is
statistics for students
defined as the
first
4-
attends a junior college, technical school, or the like and
a bachelor's degree, allowing
column
3.
HBCU. The
second column
one to make direct comparisons
Columns 4 and
5 provide
means of the
ACT
TWIs
tend to have substantially higher academic
scores of Blacks in
have slightly higher
GPAs
TWIs
are roughly
than their peers
1
who
standard deviation
attend
TWIs
(2.86
A
likely to attend private high schools. Similar trends are apparent in the
in
academic credentials between
portion of the difference between the
HBCU
students and
NLS-72 and
B&B
non-HBCU
students
can be explained by the
by restricting the 1976 cohort to Morehouse and Xavier to ensure
which emerge cannot be explained by different samples in the two cohorts.
1 976 data used to construct the summary statistics in Table 1 contains all 4 HBCUs available.
All forthcoming results have been run
The
TWI.
database for the 1976 and 1989 cohorts, respectively.^
HBCUs
more
though the differences
are less pronounced.
^
who
our datasets, blacks attending
all
or
to 2.83), suggesting that these students attend less academically challenging high schools.
Students in
differences
first
descriptive statistics are displayed in
higher. Yet, Blacks attending
B&B,
The
HBCU versus TWI, where
sample to those who completed
credentials. In the
compared
was an
will be counted as having his first college as an
variables for students in the
for black
1
HBCU
on race or which college they attended are dropped from the sample.
are missing data
NLS-72 whose
restricts the
rate to the
Statistics
Summary
in the
survey
described in greater
students in the three datasets described above, according to whether or not they attend a
Students
C&B
three cohorts in 1996 that provides detailed
1996 questionnaire was approximately 80%. The College and Beyond Survey
detail in
by the College
that
any
sample
different
restrictions.
In the 1976 and 1989 cohorts of
standard deviations
to
SAT
less, respectively.
deviation behind Black students in
C&B,
and
non-HBCUs.
GPAs
the
ACT
of Black students
scores of
HBCU
In these data, students
in
HBCUs
students are
who
attend
are .73 and .5
more than
HBCUs
1
standard
are less likely
have attended a private high school.
The "Pre-College Personal and Family Background"
environments that students were reared
in.
variables provide measures for the
These variables include family income (measured
whether or not a student attended high school
dollars), parental education, or
students were asked,
"What
the approximate
is
were dependents of
that
income before taxes of your parents
sources." For
all
to convert all
It is
income measures
to
1982-84
is
derived from the
HERI
raw
data, blacks
with
life.
HBCU
In the
who
attend
They
their bachelor's degree,
HBCUs
tend to
make
more
likely to
major
less
1991 for students
that
The CPI-U was
who
attend
HBCUs
to adjust for these differences.
attended graduate school, or obtained a
money
employed
are also less likely to be
students are
in
student sui"vey.
graduate degree, and variables designed to measure college experiences and job and
exception; NLS-72.^
NLS-72,
on many of the outcome variables. These include wages, major choice,
whether or not a student received
the
In
dollars.
apparent that there are important observable differences between blacks
third panel reports
sets.
(or guardian)? Include
used family income
and TWIs. The subsequent analysis uses a variety of statistical approaches
The
1972
and the student's own taxed and untaxed income for students
their parents
were not dependents.^ For C&B, family income
used
B&B, we
home
in a rural area or the
southern portion of the US. The definition of income differs slightly between data
taxable and non-taxable income from
in
than blacks
full-time
who
and more
life satisfaction.
attend
In
TWIs, with one
likely to
be dissatisfied
physical sciences.
in
two nationally representative samples, black students
at
HBCUs
are
more
likely to receive
a bachelor's degree and attend graduate school (though they are less likely to graduate). Black students in
the elite
HBCUs
are
more
likely to
major
in biological sciences (this is driven in large part
by Xavier who
has a storied reputation for pre-medical studies), business, less likely to receive a bachelor's degree or
attend graduate school, and, in the 1989 cohort, less likely to report that their college experience helped
For students
who were
their parents'
dependents
in 1991, total
family taxed and untaxed income was obtained, in
order of priority, from the student's financial aid application, a telephone interview of parents, a telephone interview
of the student, the student's Pell grant
dependent, the information was obtained,
interview, the student's Pell grant
'
In the
NLS-72,
file,
file,
in
or the student loan
that
were not
their parents'
or the student loan
file.
wage is $12.82 ($14.46) for HBCU attendees (graduates) and $10.55 ($11. 38)
The mean of the natural logarithm of hourly wages is about 5% (12%) higher for
wages across HBCUs and TWIs is due to a single HBCU
The influence of this obsei'vadon on the Table 1 entries is also
standard deviation of wages among HBCU attendees and graduates. See the Data Appendix for
difference in the rank of
respondent with an average hourly wage of $494.
details
For students
the average hourly
for TWI attendees (graduates).
TWI attendees (graduates). The
evident
file.
order of priority, from the financial aid application, the student's phone
in the larger
on the sample selection ndes.
10
,
develop an
ability to get
The
sample.
It
final
along with individuals of other races.
panel in Table
also provides
of observations with
some
at least
HBCU
provides the total number of
1
and
TWl
observations in each
on the incomplete observations. As a solution
details
one missing variable,
we
to the large
number
turn all of the explanatory variables into a series of
indicator variables based on ranges of the values of these variables and include separate indicators for
The bottom panel
missing responses to each variable.
also reports on the
number of observations with
missing wage information. The subsequent analysis implements a standard selection correction approach
to account for these cases
V.
(Heckman
1979).
The Causes and Consequences of Attending
A. The Causes
HBCUs in
the
NLS
and
B&B
Data
Files
of Attending HBCUs
Table 2 presents a series of estimates of the detenninants of HBCU attendance. The specifications
estimated are of the form:
HBCU, = a + pX.''""^ + yX.''^^-^''"^^^ + e,
(1)
where
X
°'
X/™
HBCU
"
is
a dichotomous variable that equals one if the student attends an
denotes
an
aiTay
of variables
which
proxy
for
a
HBCU
and zero
if not,
home environment, and
student's
^°
''^''denotes
pre-college
of each
characteristics
student.
In
instances,
all
weighted Probit
regressions are used and the coefficients reported are marginal effects evaluated at the sample mean.
weights are the sample weights
in the relevant data file.
of that coefficient relative to the omitted category when
The home environment
variables
we
that
The
all
interpretation of any coefficient
is
The
the effect
other variables are held at their sample mean.
include are family income, mother and father's
education, and whether or not a student lives in the South. Family income, measured in 1972 dollars,
divided into 4 categories: <$3,000, S3000
- $6000, $6000-$9000, and $9000+ based on
described in the previous section. Parental education (mother and father, independently)
a survey question
partitioned into
is
three categorical variables: less than a Bachelor's degree, a Bachelor's degree, and greater.
not a student lives in the South
is
a
Pre-college characteristics include
attended a private high school.
dummy
SAT
and
Whether or
variable that takes on the variable of one if the answer
ACT
Combined SAT
scores, high school
is
GPA, and whether
is
yes.
or not a student
scores are divided into less than 600, between 600-800,
ACT
scores are divided up similarly, less than 11, between 11 and 15, and greater
than 15. High school
GPA
is
and greater than
We
and greater than 800.
3.5.
In 1972, students
measured on a four point scale and
also include an indicator for
who
attend high school in the South.
attend
HBCUs
is
divided into less than 2.5, 2.5 to 3.5,
whether the respondent
have lower
Moving from an SAT
SAT
and
ACT
is
female.
scores and are
more
likely to
score below 600 to a score above 800 reduces the
.
probability of attending an
HBCU
by 32%. Similarly, moving from an
score of more than 15 reduces the likelihood of attending an
South are
43% more
likely to attend
HBCUs,
education are not statistically related to
holding
HBCU
all
HBCU
ACT
score of less than 11 to a
by 21%. Students who
live in the
Family income and parental
else constant.
attendance once our other covariates are taken into
account.
In the 1990s, things change. Standardized test scores are
HBCU
attendance. Parents with
else equal, a student
more education
more
are
whose mother has more than
HBCU.
This
legacies
(Drewiy and Doermann 2001). Residing
no longer such
powerful predictor of
a bachelor's degree is
28%) more likely
to attend
an
not surprising, as these institutions have a long histoi-y of loyal alumni and familial
is
South continues to be an important deteraiinant of
in the
college choice, though the magnitude of the coefficient
seventies. Private high school
is
negatively con'elated with
is
roughly a fourth of the magnitude
HBCU
The most obvious explanation of
selects for high ability students
Comparing colmnns
these differences
and among
2 and 3 in table 2
is
this set, differences
we can make
direct
in the
attendance.
There are marked differences between the determinants of
1990s.
a
have children who attend HBCUs. All
likely to
HBCU
attendance in the 1970s and
that conditioning
on degree completion
between the two periods
will disappear.
comparisons between the 70s and the 90s; each
sample consists only of degi^ee completers.
Intuition
suggests that as resistance to black attendance
at
TWIs
faded and the need for
segregated schooling declines, those with the highest opportunity cost of such schooling will opt out and
choose more tiaditional universities. In other words,
HBCUs.
Yet, the data
predictive of
HBCU
likely to attend
HBCU
show
it
might be reasonable to expect a "brain drain" from
the opposite to be true.
Lower academic
credentials are not as highly
attendance in the 1990s as the 1970s. Students with higher educated parents are more
HBCUs
in the
1990s and higher academic credentials are not as strong a predictor of non-
attendance. This provides evidence of a selection of talented Black students into
HBCUs
in recent
years.
B.
Econometric Approach
In the
attendance,
and
TWI
Estimating the Consequences of Attending
HBCUs
absence of a randomized experiment or a credible instrumental variable for
we implement
four statistical approaches to adjust for pre-college differences between
HBCU
HBCU
attendees. This subsection details these strategies.
The
(2)
to
first
and simplest model
outcome, =
p^+ pX
.""'"""
In all instances, the estimation
sample weights provided
is
we
estimate
is
a linear specification of the fonn:
5HBCU + f,
+ oXr"""'"' +
done using weighted
in the data.
Equation (2)
is
12
least squares,
with weights coiTcsponding to the
a simple and easily inteipretable
way
to obtain
estimates of the effect of
covariates
HBCU
and
Xj"""""^
attendance on outcomes, but
^.'"^-"'^s^_
may
This
on a linear model
relies
it
to control for the
be unappealing since their true functional form
is
unknown.
As
a solution,
we match
propensity scores (p-scores) of
HBCU
HBCU
TWI
and
attendance (Rosenbaum and Rubin 1983).^ The estimated p-scores
compress the multi-dimensional vector of covariates
score approach are twofold.
manner than
First,
possible with
is
is
it
HBCU
we model
and
is
among
attendees
a real asset here.
assumption
that just as with linear regression, the identifying
attendance)
provides an opportunity to focus the
it
those with similar distributions
of the covariates with indicator variables the former advantage
all
not so compelling in this setting, but the latter
HBCU
Finally,
is
important to emphasize
assignment
that
is
it is
associated only with observable pre-period variables.
is
the propensity
observables in a more flexible
to control for
Second,
TWI
The advantages of
an index.
into
method
a feasible
regression.
linear
comparisons of outcomes between the
of the obsei'vables. Since
students with similar predicted probabilities or
to the treatment (i.e.,
This
is
often called the
ignorable treatment assignment assumption or selection on observables.
We
implement the p-score matching strategy
obtained by
fitting probit regressions for
'^^'^
and
HBCU
attendance (identical to equation
as explanatoiy variables. In other words,
Xj'^'^'^"
We
selection rule with the obsei"ved covariates.
For both
suitable.
in three steps. First, the estimated p-scores are
tests,
we
and
/or estimate a richer probit
accepted for both
the
means of
If the null hypothesis
HBCU
outcome between
this in
one
two ways. The
TWI
HBCU
first
is
and
TWI
alternative
'
is
to
In
is
we
two
sets
of students
divide the qunitiles
interactions.'
Once
is
the null
is
calculated by comparing the difference in
HBCU
HBCU
student for which there
student's p-score.
that individual
(or possibly a few) crucial Govariate(s).
TWI
We
is at
In cases
take the simple average of outcome across
done with replacement so
match on a single
we
students with similar or "matched" values of the p-score.
multiple students have p-scores within 0.10,
An
we
the next step.
student with an estimated p-score within 0.10 of the
Rubin (1977)
In the first test,
rejected for either test,
calculates a treatment effect for each
students. Further, this matching
TWI
the covariates are equal for the
of equality
Second, the "treatment effecf for a given outcome
the
and
model by including higher order terms and
we proceed to
tests,
average student's
students within quintiles.
divide the sample into quintiles based on their p-scores.
we examine whether
test,
within each quintile.
to replicate the
try
then conduct two tests to ensure that the p-scores are
assess whether the estimated p-scores are equal across the
the second
we
above), using X!""^"""
1
all
do
least
where
of these
students can be used as
See Angrist and Lavy (1998) or
for applications.
See Dehejia and
Wahba
(2002) and
Rosenbaum (1984)
for
method.
13
more
details
on
how
to
implement the propensity score
controls for multiple
fomi
HBCU
student but in calculating the average
weighted average, where the weight
We use
score.
The second matching approach uses
students.
HBCU
a control for each
is
a Gaussian kernel with a
Third, a single treatment effect
which there was
students for
focuses the comparisons
and
TWI
where there
TWI
of the
inversely proportional to the distance to the
HBCU
students to
use a kernel
student's p-
bandwidth of 0. 1 0.
is
estimated by averaging the treatment effects across
all
HBCU
one suitable match. This approach has the desirable property
is
overlap in the distribution of propensity scores
among
the
that
it
HBCU
students so these students are "similar.""
We
First,
at least
all
among them we
we
also
implement two other econometric approaches
estimate probits for whether the
missing and non-missing wage values.
wage
We
variable
to
account for potential selection issues.
missing on the sample of obsei'vations with
is
then include the inverse Mill's ratio from these probits in
equation (2) to account for the possibility that wages are not missing
procedure
identified
is
at
random (Heckman 1979). This
from a functional form assumption, since we are unaware of a valid exclusion
restriction in this setting.
Second, the available data sets
may
some
not include measures of
attributes (e.g., strength
of
essay, motivation, and teacher recommendations) that persuade admissions committees to select certain
applicants for admission that are also rewarded in the labor market.
across
HBCU
and
TWI
students.
The
least squares
Further, these attributes
may
differ
and propensity score approaches rely on "selection on
observables" assumptions and will produce biased estimates in this case.
To
confront this source of misspecification,
Dale and Krueger (2002)
that
NLS
data
are admitted.
We
approach can only be implemented with the
sets
of colleges
to
we implement
which individuals
file,
accepted,
we
as
find the midpoint of the 25th-75th percentile
report only
We
use current
ACT scores, we
For each student,
B&B
student.
We
SAT
This
does not contain information on the
SAT
Among
the colleges
range reported in
scores since scores from 1972 are unavailable.
use an equivalence scale to convert to
we
method pioneered by
operationalize the Dale and Krueger approach by
detennining the identity of the colleges that accepted each student.
Report (2006).
a variant of the
matches students based on the colleges where they were accepted.
record the highest midpoint
SAT
SAT
where they were
US
Nev.'s
&
World
For colleges that
scores.
score of any college that accepted the
divide the students into four groups by quartiles of the school with the highest midpoint
among
the schools
groups
in
equation
where they were admitted.
(2).
We
SAT
then include separate indicators for each of these
This approach mitigates the impact of any confounding due to characteristics
See Dehejia and Wahba (2002) and Heckman, Ichimura, and Todd (1998) on propensity score algorithms.
" If there are heterogeneous treatment effects, this strategy produces an estimate of the average effect of the
'"
"treatment on the treated".
14
obsei-vable to admissions officers that are not measiu'ed in the data set.
assumption
is that after
non-HBCU
within a quartile
Specifically, the identifying
adjustment for the available covariates, the decision to attend a
HBCU
versus a
"ignorable" or orthogonal to unobserved determinants of outcomes.
is
See
Dale and Krueger (2002) for a more detailed discussion of this approach.
we
Finally,
were unconvinced
we
note that
distance to a student's nearest
considered a number of candidate instrumental variables, such as
HBCU,
was
very difficult to constmct an instmment with a powerful
may
C. Estimates
still
first stage.
the
and
B&B
data,
Figures
data
files,
respecdvely.
who completed
TWI
is
it
To
HBCUs
evident that the
mean
B&B
are
more
at
an
HBCU
or
TWI.
In Figure
p-scores exceeding roughly 0.9.
students with p-scores greater than about 0.8.
Thus,
it
3 presents results
graduation from a
HBCU
in
5).
HBCU
In Panel A, the treatment
Panel B.
For the
B&B
indicator.
is
For the NLS, wages are measured
relevant sample.
and roughly 10 years
based on
in
number of
is
distributions of p-
HBCU
In the
NLS
aren't
any
meaningful
on the natural
we
errors are
entries in Panels
HBCU,
A
same
that attended the
matriculation at a
entries in Panel C,
report the R-squared statistic, as well as the
The
The estimated standard
while
it
is
report standard en-ors that
allow for unspecified heteroskedasticity in the variance-covariance matrix.
we
with the
in this range.
and B, the standard eiTors allow for clustering among observations from students
column
is
However, there
of the effect of attending a
reported in parentheses below the point estimate for the
in
which
1,
will be difficult to obtain
logarithm of wages from the four approaches in the six columns.
high school (except
TWIs
propensity score differs across the populations, but there
similar throughout a broader range of the p-score.
Wage Outcomes. Table
and
obtain these figures, weighted probits were estimated on the
comparisons for the relatively small subset of HBCU students with p-scores
eiTors,
is
and 2 present separate kernel density plots of the
1
their bachelor's degree at
substandal overlap in the distributions, except
scores in the
it
Consequently, thorny issues of
of the Consequences ofAttending HBCUs
of students
NLS
we
cases
remain.
Distribution of Estimated P-Scores.
set
all
With approximately 300 observations,
estimated propensity scores for black students that received degrees from
NLS
but in
were not powerful enough
valid or the instruments
for the relatively small samples in the available data files.
selection
HBCUs,
residing in the South, or the closing of
that the exclusion restriction
Underneath the standard
students in
HBCUs
and TWIs
in the
1986 - fourteen years
after high school graduation
B&B, wages
are in 1997, five years after
after obtaining a bachelor's degree. In the
completion of the bachelor's degree.
Column
1
reports the
mean
difference in labor market
without adjustment for any controls.
In the
NLS,
15
HBCU
wages
for individuals
students earn roughly
who
5%
attend
less
HBCUs,
when
the
treatment
is
the
these estimates
statistically different
1
on observable dimensions
1.5% when
from zero
HBCU graduates earn
1990s indicates that
that
college attended and
first
is
HBCU
16.6%
is
it
receipt of a bachelor's degree.
less than
students have
TWI
Column
downward
HBCU
is
1970s
in the
is
11.1% when
HBCU
status
is
NLS
dramatically.'"
based on the
defined as receiving a bachelor's degree. The foiTner estimate
has an associated
t-statistic less
-13.8%) and the null of zero
matching.'^
1.'^
would be
The next two columns
of these results
than
to the linear
B&B,
In the
first
is
TWI
their
biased.
The adjustment
2 reports the results from estimating equation (2).
controls changes the results in the
demonstrated
1
academic credentials than
lesser
Neither of
estimate from the
graduates. Recall, Table
counterparts (especially in the NLS), so these raw gaps are likely
home environment
B&B
The
conventional levels.
at
The wage
for the
academic and
benefit of attending a
6.0% when
college attended and
marginally significant, while the
however, the wage effect for attending
it
latter
HBCUs
is
rejected with conventional criterion.'''
report on the implementation of the p-score
method
to test the sensitivity
model. Column 3 uses kernel matching, while column 4 relies on radius
Standard errors for both matching estimates were bootstrapped (200
with
iterations),
propensity scores recomputed for each bootstrap sample. Further, the p-score matching estimates are not
weighted with the sample weights.
The p-score estimates
are remarkably similar to those
from the
linear regression in
column
2.
This finding shouldn't be teixibly sui"prising because equation (2) models the covariates flexibly,
nevertheless
it
is
Column
full set
of covariates.
from the labor
change
reassuring that functional fomi issues don't appear important in this setting.
5 presents estimates that are selection corrected for
in the
force.
It
seems plausible
This possibility
is
that
HBCU
attendance
is
missing wages and adjusted for the
coiTelated with selective withdrawal
not supported by the data as this approach produces unimportant
estimated impact of HBCUs on wages.'
'^
A
'^
Results are similar
'^
In the
similar result
was found
in Constantine (1995).
one implements a "fraction method," using individual transcripts
a student's college experience that was spent at an HBCU.
if
B&B (B&B 2003) there is no wage gap between HBCU students and non-HBCU
HBCU sample does not have valid wages in the later survey (some are in the
while others were dropped completely). HBCU graduates have a 9.6% higher
most recent wave of
students. Unfortunately,
53%
the
of the
survey and unemployed
unemployment rate, and median regression techniques provide
concentrate on the earlier wave with more complete data.
''
Observations with estimated p-scores that are not
observations in the
of
to calculate the fraction
NLS when
the treatment
is
first
strictly
identical
between
results to the
and
college attended and 21
1
1997 wave. Thus,
are dropped.
when
Further,
the treatment
and 21 observations in the B&B when implementing the radius matching estimators due
matches in the relevant range.
is
we
we
lose 7
degree college,
to outliers that did not
have
" We also assessed the impact of labor market dropouts on our estimates with a simple re-weighted linear regression
and median regression. In the first approach, we estimate a probit of whether or not we have valid wages on all of
the covariates in Table 2. We then multiplied the sampling weight by the inverse of the predicted probability in the
new weights. Linear regressions are then esrimated with these new weights. This approach led to
remarkably similar conclusions as the selection correction approach. Median regressions were estimated by
probit to get
16
Column
student
6 implements the column 2 specification but adds controls for the "best" school that the
was admitted
and Krueger 2002).
to in order to account for the richer data available to
we
Specifically,
the best school that the student
was admitted
method
is
NLS
HBCU
to
only possible in the
22.5%.
to,
SAT
This
doubles estimated impact of attending a
it
from
HBCU
attendance
However, the estimate's imprecision makes
by the other methods.
scores of
leaving the lowest quartile as the excluded group.
data and in this sample
Specifically, this approach suggests that the gains
larger than indicated
admissions committees (Dale
include indicators for the three highest quartiles of
may be
definitive
conclusions unwarranted.
Additionally,
we conducted
HBCU, which
to attending a
home
with students'
region
a
number of tests
are reported in
for
whether there was heterogeneity
Appendix Table
We
2.
in the returns
assessed whether returns differed
South versus North), their estimated propensity score,
(i.e.,
SAT
Score,
parental education, and gender. In general, there isn't substantial evidence of heterogeneity across these
The lone exception
subsamples of students.
black
women
sample
is
too
than for black
men
in the
demanding of the data
NLS
is
that the returns to attending a
sample.
It is
1970s.
suffering a
wage
relative return
HBCU
subsamples are much
larger.
conferred remarkable advantages on
Conventional estimates of the average return to college are
(Heckman, Lochner and Todd 2003). Attending
equivalent to one
appear higher for
also immediately evident that subdividing the
as the standard errors in the
Overall, these results suggest that attending an
students in the
HBCU
more year of
penalty.
schooling.
a
In contrast,
If the point estimates are
of HBCU attendance
Non-wage outcomes. Thus
in just
far
single outcome: labor market wages.
labor market considerations.
HBCU
taken
versus a
TWI
more recent
in the
HBCU
literally, there is
10%
its
per year
1970s was roughly
attendees appear to be
nearly a
-25% swing
in the
two decades.
we have
concentrated on the effect of attending a
The value of attending
The conventional wisdom
is
HBCUs,
HBCU
on
a
however, likely extends well past
that these institutions instill confidence in their
students, a sense of responsibility, and provide environments free of racism and discrimination that allow
for greater personal development.
Such environments are
likely to
have
many
benefits
beyond those
captured in wages.
Table 4 explores the effect of attending
probability of full-time employment, measures of
HBCUS
on
a
life satisfaction,
number of outcomes, including
and a
series
These wide ranging outcomes were chosen because of their economic and social relevance as well as
comparability across datasets.
dummy
variables
imputing zeros
were smaller
to all
for
The academic outcomes index
majoring
in
business,
majoring
in
is
the first principal
physical
the
of academic outcomes.
their
component of the
science/mathematics/computer
missing wage observations. Qualitative conclusions were the same, though the coefficients
as expected.
17
science/engineering, majoring in biological science/liealth, receiving a bachelor's degree,
graduate school, and receiving a graduate degree.
matching estimates and
confrnn these
gain
10%
that students
HBCU
and
from these outcomes
striking finding
is
HBCU
that
weighted
matriculation
increase in the probability of receiving a bachelor's degree.
1970s
in the
coefficients reported in the table are
from kernel
least squares
results.
The most
nearly
The
their associated bootstrapped standard eiTors. In all cases,
attending
due
is
who
to the increased probability
attend
HBCUS
TWI matriculates
are modestly
It is
is
of graduating from college. There
more
major
likely to
report similar degrees of
associated with a
evident that part of the
some evidence
is
in physical sciences.
life satisfaction.
wage
Interestingly,
There are negligible effects on
all
other outcomes.
VI.
There
TWIs. To
is
A
Focused Look
substantial quality variation
we have analyzed
this point,
that include the full
the
NLS
spectrum of HBCUs and
more focused look
four of the most
at
Most
at the
among
and
B&B, which
TWIs from
elite
Elite
HBCUs
HBCUs,
the set of 89 4-year
compared
to the thirty selective
Table
of
C&B
in all
4
that
is
5 reports
from estimating equations
1989 cohort which
(2) drops
parameters on the standardized
(colunm 2)
SAT
Howard
1989 cohort.
income variables
(3).
The
test scores are the
for elite
so that
most notable
HBCU
in the
elite
scores have a similar effect on
HBCU
HBCUs
we
take a
students.)
HBCUs
One
can only be
for the 1976
is
(1)
and 1989 cohorts
a sample of individuals
can make direct comparisons with the
patterns across the
SAT
ACT
positively associated with
the
Howard and Spelman
of attending an
approach, these four
Table 2." Column
score of less than 600 and a
in the likelihood
we
Xavier, Spellman, and Howard.
sample.
identical to those in
displayed in column
is
difference between a
in the
on the detenninants of attendance
HBCUs, column
3) in the
TWIs
the
are nationally representative data files
HBCUs: Morehouse,
C&B's sampling
due to the
among
the quality continuum. In this section,
(Importantly, the 1989 data set does not include infonnation on Spellman and
limitation of this exercise
as well as
results.
columns are quite
Evaluated
at the
similar.
The
sample mean, the
score above 800 implies a
40.1% decrease
1976 cohort and a 63.1% decrease (column
HBCU
attendance. Mother's education
is
attendance in 1989. After adjustment for the academic characteristics,
are not reliable predictors of elite
HBCU
Residing
attendance.
portion of the United States continues to be a strong predictor of
HBCU
in the southern
attendance; increasing the
probability of attendance by roughly 40%.'^
'^
Throughout the
C&B
analysis, the treatment
consistency with the other tables,
we
is
defined as enrollment
at a
HBCU,
not graduation from one.
refer to the treatment as "first college", although
due
to the
For
C&B's sampling
scheme it is possible (but unlikely) that a respondent was initially enrolled at a different college or university.
'*
The large negative coefficient on female in 1989 is related to the fact that the women's college Spellman is not
in
HBCU
Figures 3 and 4 plot the distributions of the estimated propensity scores for the
attendees from the 1976 and 1989
make
this analysis to
two
C&B
the samples consistent.
It is
This finding confirms the impression from the probit
academic credentials of these students
The poor overlap of the
the propensity score exercise
student,
it
is
apparent that
we
differ in important
distributions poses challenges for the
where we require the
will rely
selection on observables assumption
TWI
ways.
outcomes
For example, in
analysis.
students to have p-scores within 0.1 of the
on a small subset of the
may
TWI
apparent that there isn't substantial overlap across the
distributions in either year, especially in 1989.
results that the
and
Howard and Spelman were dropped from
classes, respectively.
HBCU
In this subset of the data, the
data.
be especially unlikely to be valid.
On
the other hand,
we can
use least squares functional forni assumptions to infer counterfactuals in parts of the distribution where
there
is
little
support.
infeiTing the impact of
Neither approach
HBCU
be interpreted with these important caveats
We now
measures of life
the
C&B
especially appealing, which underscores the difficulties of
is
matriculation in this sample. Consequently, the forthcoming resuhs should
in
mind.
turn to an exploration of the effect of attending elite
satisfaction,
database
is
the
HBCUs
and academic outcomes from the 1976 and 1989
availability
of detailed questions about
life
on labor market outcomes,
C&B. One major benefit
of
outcomes, beliefs, college
experiences, labor market outcomes and experiences, political and civic engagement, and more. These
rich questions can help to shed light
HBCUs. For
HBCUs
on the overall experience of students attending
both cohorts, data on the majority of outcomes was obtained
1995,
in
and non-
15 years after
graduation for the early cohort and 2 years after graduation for the later cohort, though some data such as
wages
in the
1989 cohort were collected
in
1996. Individuals without valid
wage
obsei"vations are
dropped from the sample.
Because the number of potential dependent variables
indices to better understand the experiences of
HBCU
appendix describes the specific questions used
first
principal
First, principal
set
component of
to
C&B
is
so numerous,
we
construct five
students along the following dimensions: objective
academic, subjective academic, labor market, leadership and
the
in
make up
lifestyle,
and social
interactions.
these indices. Each index
the set of variables described. This approach has
is
The data
obtained by taking
two main advantages.
components analysis reduces the dimensionality of problems by extracting the portion of a
of variables that explain the most variance within the
measured on the same
scale.
The
cost
is
that the result's
set.
Second,
meaning
it
ensures that
isn't transparent
all
variables are
and cannot easily be
applied to different settings.
Table 6 reports the results of estimating the effect of
HBCU
non-wage outcomes from kernel matching, which can be compared
the 1989 sample.
19
attendance on our set of wage and
to the results in
column
3
of Tables 3
and
4.
Column
1
includes
four
all
HBCUs
Column
1976 sample.
in the
2 also reports results from the
1976 sample but only includes students who attended Morehouse and Xavier
with the 1989 cohort,
whose
HBCUs
In the 1976 cohort,
and 11.1% more
on attending, 13.6%
significantly
major
likely to
10%
been written on these
statistically significant
likely to
more
racially
institutions
and substantively
HBCU
experience are large, which
homogenous
importance of
HBCUs
is that,
would choose
The 1989 cohort
the
zip codes.
controlling for
same college
is
HBCU
The labor market experiences
And,
HBCU
HBCU
HBCU
students are
quite positive.
much
interactions are also
are positive, but negligible.
graduates are no more likely
graduates are no
other factors,
all
is
consistent with
(Drewey and Doennan 2001). Social
large.
political, religious, civil rights, social service, or philanthropic activities.
report they
in the biological sciences
objective academic outcomes,
Students do not seem to possess a particular taste for segregation, as
to live in
major
though their subjective view of the academic experience
negative,
comparisons
less likely to attend graduate school and, conditional
On
less likely to receive a degree.
to facilitate
3.
9% more
graduates were
in business, but
Leadership and lifestyle components of the
that has
column
results are reported in
more
The
likely to
be engaged in
clearest evidence of the
students are
1
8% more
likely to
again.
reports different experiences. Students are
more
likely to
major
in
physical and
biological sciences and business. Students continue to benefit from leadership and lifestyle components of
HBCUs,
but the magnitudes of these effects are less than one-fourth of their previous levels.
other positive elements turn negative in the
outcomes are negative and
social interactions index,
cohort.
The
negative, and they
code that has a
HBCU
more
which was positive
10%
in the
is
less likely to receive a bachelor's degree.
1976 cohort,
sharply negative
tiuTis
seem
16%
to
have a
taste for segregation.
HBCU
attendance
Most
telling,
HBCU
higher fraction of blacks.
students to report they
would choose
in the
The
1989
also substantial in three of the variables that are used to
1976 and 1989. The labor market experiences of the
in
of the
The objective and subjective academic
recent cohort.
matriculates are
table demonstrates that this decline
constmct the index
zip
HBCU
Many
the
same
is
later cohort are
even more
associated with living in a
students are less likely than non-
college again, although the difference isn't
statistically significant.
Interestingly,
activities
wages.
which
HBCU
students in the later cohort are significantly
are associated with civic consciousness.
This
may
likely to be
VII. Reconciling the Differences between the 1970s
We are grateful to
between the 1970s and 1990s Results
Lani Gunier for pointing out
this possibility.
20
engaged in
partly explain the divergence in
19
A. Assessing the Difference
"
more
and 1990s
Panel
A
of Table 7 summarizes the difference
we
between the 1970s and 1990s.
in the results
examined above. The difference
reports regression results for five of the key dependent variables
is
It
that
use the stacked 1970 and 1990 data sets to estimate the following equation:
outcome!, =
(3)
Po
+
y,
X/"^=""
+
a, x,r-'°"'<''
+ ei(HBCUi,)-l(1990i,) +
where the
i
+ X l(HBCUi,) + 5
Si,,
subscript indexes an individual and the
t
subscript reveals whether the observation
1970s or 1990s college student. The parameter vectors y and a have
HBCU
interest is 9,
which
and whether the observation
observation from the 1990s.
attendance and
is
This parameter
also includes separate intercepts
HBCU
indicator and the indicator for an
(DD) estimate of
a difference in differences
is
from a
from a 1990s college attendee. The parameter of
is
associated with the interaction between the
is
is
subscripts indicating that they are
t
The equation
allowed to differ for 1970s and 1990s college attendees.
for attending a
1(1990,,)
equal to the difference of the cross-sectional
HBCU
estimates
(e.g.,
the natural logarithm of wages.
For
column 2
HBCU
in
Table
3).^"
In
column
(1), the
nationally representative
dependent variable
NLS
and
Howard and Spellman
The
decades.
first
attendees are dropped fi-om the sample, just as in
(i.e.,
same college
20%
and TWIs.
(2)
HBCU
attendance over the two
of Table
6.
decline in wages, a
HBCU
13%
attendance have declined. Specifically,
depline in the fraction of students
who would
again, and substantial declines in the leadership and social interactions indices.
other three "objective" outcomes, which measure political participation, social/civic sei-vice, and
donations to national charities,
HBCU
all
show an
increase between the
became
measure indicates
that
noteworthy that
of these estimates are economically and
B.
HBCUs
column
those where a higher value of the dependent variable
a positive) suggest that the returns to
the point estimates suggest a
The
in the relative returns to
four "objective" outcomes
would be considered
attend the
data files are used.
this regression, the
The other seven dependent variables are
samples, which focused on a subset of elite
summarize the change
results
The
B&B
C&B
taken from the 1976 and 1989
is
all
Robustness of the Result that
attendees
HBCUs
'
two
C&B
classes.
less likely to live in integrated
The non-objective
neighborhoods.
It
is
statistically significant.
Performance Worsened between the 1970s and 1990s
This subsection reports on some checks that aim to explore the robustness of the basic result that
the
economic returns
differences.
We
that the definition of
^^
The
C&B
table reports
to attending a
HBCU
declined.
Many
obvious explanations
fail to
explain the
have ensured, through the use of Federal Interagency Committee on Education codes,
HBCUs
is
consistent across data sets and over time. Moreover, the addifion of
results are not identical to the difference
on the kernel matching
results,
between the 1989 and 1976
results in
Table 6 because that
while Table 7 relies on least squares adjustment for the covariates.
21
more
control variables, such as occupational choice indicators or a richer set of academic variables,
fail to
explain the differences. Further, differential labor market dropout rates cannot explain the change.
Selection of students into (or by) colleges
but the available data
fail to
support
it.
a potential explanation with
is
For example, Table 2 demonstrates
that, if
some
intuitive appeal,
anything, selection on
observables appears to work in the opposite direction. Students with higher scores on aptitude tests and
home environments
better
Nevertheless,
are
we
more
likely to attend
the observations with non-missing
wages from the
whether the obsei-vation was from the
probabilities that the
B&B
NLS
OLS
NLS
The
B&B
and
the
is
1990s, relative to the 1970s.
on observables. Specifically, we stacked
B&B
and estimated a weighted probit for
We
1970s)."'
1990s) observations are from the
(i.e.,
NLS.
used as a weight
then calculated the predicted
These predicted probabilities are
in the fitting
of the Table
3
column
is
similar
and B&B.""
result
of
procedure
this
is
that the estimated
decHnes from -13.8% (standard eiTor of 0.050)
that this
in the
This weighting scheme aims to ensure that the distribution of observables
specification.
across the
NLS
(i.e.,
multiplied by the sampling weight and this product
2
HBCUs
further explored the role of selection
approach only increases the relative worsening of
Ahhough we cannot
between the 1970s and 1990s.
HBCU
impact of
attendance on wages in the
-18.7% (standard error of 0.056).
to
HBCU
It is
evident
attendees' labor market performance
rule out selection
on unobservables,
seems
it
reasonable to conclude that the results aren't due to differences in observable characteristics.
Another
TWIs
possibility
represented in the
due to the relatively small sample
is
that
NLS
and
B&B
To explore
differed.
this,
(2006) to obtain the current midpoint of the 25th-75th percentile
represented by the valid obser\.ations in the data
the observations."^
HBCUs
and
quaUty of the
SAT
range for
This inforaiation
is
the respondents in our analysis decreased
in
our sample,
SAT
scores in
HBCUs
and
all
TWIs were
the
HBCUs
and TWIs
only available for a subset of
SAT
Nevertheless, these data indicate that the gap in average
TWIs chosen by
and universities
the colleges
files.
sizes, the
we used US News and World Report
scores between the
between the two decades.
236.1 points higher than
Among
HBCUs
in
the 1970s and 226.2 higher in the 1990s. Thus, the available evidence suggests that the results are not due
to a
"
change
in the
The weights
composition of HBCUs and
are adjusted sampling weights,
observations and within the
throughout the paper
(e.g., in
""
This method
is
-^
We matched
92.3% of
SAT
of the
HBCU
TWl
colunm
NLS
and
B&B.
where the adjustment ensures that they sum to 1 within the NLS
The covariates in the probit are the standard controls used
(2)
of Table
3).
Lemieux (1996)
TWIs represented in the NLS. For the B&B, these numbers
many of the colleges represented in these data files do not
US News and World Report (2006). Specifically, we obtained SAT information for 29.1%
the
and 84.0% of the
respectively. UnforUinately,
information in
attendees and
attendees in the
HBCUs
the
observations.
a variant of Dinardo, Fortin, and
were 88.9%) and 82.7%),
report
B&B
TWIs between
49.0% of the
TWI
attendees in the
B&B.
22
NLS
and for 33.0% of
HBCU
attendees and
49.2%
C Did HBCUs Decline or Did TWIs Improve?
If the estimated decline is causal, the source
unlikely to be important for public policy purposes. Nevertheless,
researchers and educational practitioners to understand whether
of
HBCUs
One
potential explanation
1990s leading
answer to
this
it
it is
would be of considerable
due
is
interest to
performance
to a decline in the
question could lead to the design of
more
programs for blacks.
effective educational
some
An
or an improvement in TWIs.
HBCUs' performance
of the relative decline in
is
that
because
HBCUs
weakened between the 1970s and
financial position
of the educational environment
to a decline in the quality
intuitive appeal,
HBCUs'
at
experienced enrolhnent declines
HBCUs.
in this
This explanation has
period and
Hoxby (2000)
suggests that the nationalization of the higher education market has hurt smaller colleges and universities.
However,
Specifically on a host of input measures,
the data don't appear to support this explanation.
including financial informafion, faculty compensation, research grants received, and composition of
faculty with various degrees, there
substantial
ways (Provasnik,
evidence that the relative quality of
is little
HBCUs
has declined in
Shafer, and Snyder 2004).
Expenditures per student are perhaps the best measure of the quality of the education that these
schools provided.
Data on educational expenditures
the Higher Education General Infonnation Survey
at
HBCU
and
non-HBCU
schools
Education Data System from 1985-2004 through the
ICPSR web
site.
In
2000
expenditures per student increased from $9,423 to $1 1,996 between 1974 and 1991 at
to
$10,560
at TWIs."''
(The years 1974 and 1991 are chosen, because they are roughly
prime college attendance years of the students
in the
educational expenditures per student increased by
24.7%
is
at
TWIs.
It is
due to a decline
An
alternative explanation
is
that
at
the civil rights struggle,
campus
many Southern TWIs.
sit-ins
Further,
HBCUs
HBCUs
in the
it
respectively.) Put another
A
Educational expenditures
is
research, public
the
a greater
sum of
service,
way,
real
between 1974 and 1991, compared
It
is
HBCU attendance
also notable that the level of
effective at educating blacks
After
all,
the 1970s are not far
many TWIs were
related theory that
expenditures
between the
removed from
is
made from
23
to
not convivial places for
empirically indistinguishable
is
that
cross-racial connections.
the current funds that relate to the functions of
academic support, student services,
maintenance.
to
both the 1970s and 1990s.
has been noted that
premium on
is
and $8,468
middle of the
and boycotts, and battles over even allowing black students
society has changed so that there
instruction,
B&B,
HBCUs
in
in spending.
black students in the 1970s (Patton 2005).
^'^
and
at
TWIs became more
1970s and 1990s in ways that aren't reflected
enroll in
NLS
27.3%
measured by expenditures.
education expenditures per student was greater
available from
dollars, educational
evident that data reject the hypothesis that the decline in returns to
in their quality as
is
from 1970-1984 and the Integrated Postsecondary
institutional
support,
operation and
To
explore this possibility credibly,
experiences at TWIs. After
all
it
is
We
students between the 1970s and 1990s.
essential to
have a counteifactual for blacks' changing
TWIs became more
possible that
all, it is
effective educational institutions for
use whites' experiences at
TWIs
as a counterfactual in the
following equation:
outcome,,
(4)
=
+
where (again) the
+
Po
Tn X;,
'^•"'"''
may
indicating that they
is
0,
which
and
t
(Black,,)
+ 51(1 990,,)
subscript reveals whether the observation
references race.
and whether the observation
on whether the returns for
All
relative to whites.
Panel
r
1
s„,
The vectors y and a have
is
from
"rt" subscripts,
is
from
a
1
990 college attendee. The parameter of interest
associated with the interaction between the Black indicator and the indicator for an
is
B
only, since this
+
vaiy by race, time period, or both. The equation also includes separate intercepts
observation from the 1990s attendees.
reports
+X
x/'"'""'^'
subscript indexes an individual, the
i
a 1970s or 1990s college student,
for black students
+ an
9 l(Blacki,)-l(1990„)
HBCU
This parameter
TWI
is
a difference in differences
(DD) estimator and
attendance increased between the 1970s and 1990s for blacks,
attendees are dropped from the estimating samples in
all
specifications.
of Table 7 reports on the estimation of equation (4) for the natural logarithm of wages
is
the variable of interest available in the nationally representative data files.
The column
The column
(1) specification constrains the y and a vectors to be constant across races and periods.
(2)
one allows them to differ across decades but holds them constant across whites and blacks within a
decade
(i.e.,
in the
same survey).
In
column
(3),
they are allowed to vai-y across races but are restricted to
be constant across decades.
The column
among TWI
(3) specification suggests that
by 13.4% more than wages of whites between 1970 and 1990.
and would account for roughly two-thirds of the relative decline
Panel A. The point estimates are also positive
statistically indistinguishable
The difference
parameter vectors.
It
from
in the other
two
attendees, the
This estimate
in the
so
is
is
HBCU
attendees in
and
due
to the choices
about the y and a
important to note that F-tests lead to rejections of the hypotheses that the
just too parsimonious.
the standard error
statistically significant
zero.
parameter vectors are equal across decades (column 2) and race (column
specification
is
wages of black
specifications, but they are smaller
in the results across the three specifications is
is
wages of blacks increased
The R-squared
on the parameter of
interest.
statistic is largest in the
We
3),
column
also experimented with a
so the column (1)
(2) specification but
model
that
allowed the
parameter vectors to vary with indicators for the interaction of decade and race, but the resulting estimates
had
little
empirical content.'^^
" This model
is
too demanding of the data.
multicollinearity are an especial
concem.
As
Recall, all of our controls are indicator variables so issues of
a
measure of
24
this
problem, the standard error on the parameter of
We
we
are
left
unaware of good reasons
are
to favor either the
column
(2) or
thirds of the decline in the relative
wages of HBCU attendees
is
due
to
educating Blacks. The other produces an imprecise estimate that
explanation has
sober conclusion
(3) specifications, so
suggests that roughly two-
improvements
in
TWIs' efficacy
that the data fail to reject the possibility that
blacks between the 1970s and 1990s, but they also
fail to
at
taken literally implies that this
if
empirical backing. Both have confidence intervals with significant overlap.
little
is
column
One
with two specifications that appear to have equal standing.
TWIs became more
The
effective at educating
provide decisive evidence in favor of this
possibility.
VIII. Conclusion
Historically Black Colleges and Universities are an integral and proud part of Black histoid and
For generations, these institutions have educated Blacks and produced leaders
culture.
government,
in
business, entertainment, and the academy. Yet, their reliance on public funding and the Fordice decision
mean
that
it
more important than ever
is
to
understand the causes and consequences of matriculation
at
HBCUs.
Existing evidence on the effects of attending Historically Black Colleges and Universities has
typically concentrated
on
approach - analyzing
three large data sets with
either degree attainment or future wages. In this paper,
we
take a
more
holistic
adequate pre and post college infonnation, a student's
choice of college, and myriad social and economic outcomes to paint a rich portrait of the experiences of
black students
to attend
at Historically
Black Colleges and Universities, relative
non-HBCUs now and
to their counterparts
over time. Consistent with the charge from the high court,
who choose
we
search for
"educational justification."
The nationally representative
Several important results from this search have emerged.
reveal an important change in the returns to
associated with higher
student quality
(e.g.,
attendance.
is
a substantial
wage
penalty.
wages of HBCU graduates between
SAT
scores) improved
among
In fact, there
the
fallen behind.
HBCUs
Finally, there
is
also
some evidence of a
HBCU
is
datasets
matriculation
relative to attending a
relative
was
TWI. By
a statistically significant
two decades. Notably,
HBCU
achieving students were increasingly choosing these schools
have
In the 1970s
wages and an increased probability of graduation,
the 1990s, however, there
decline in the relative
HBCU
20%
measures of
attendees during this period, so higher
at the
same time
that the schools appear to
relative decline in the
performance of
elite
from the College and Beyond.
The analysis has unearthed some important clues
declined in this period. The data provide
interest (9)
is
more than 9 times
some
as to
why HBCUs'
support for the possibility that
larger than the one in
column
25
(1).
relative
HBCUs'
perfonnance
relative decline is
partially
due
to
improvements
in
TWIs'
efficacy in educating Blacks, but this evidence certainly isn't
number of seemingly
In contrast, the data reject a
decisive.
declines in the pre-coUege credentials of students attending
student
HBCUs.
at
This question of why
the identification of the exact channel
summary,
In
is
HBCUs' performance
to
and
in educational expenditures
declined merits further research, although
the evidence presented in this paper suggests that relative to
have disappeared on
per
unlikely to be important for policy puiposes.
have provided unique educational services
seems
intuitive explanations, including relative
HBCUs
for blacks in the 1970s.
However by
many dimensions and by some measures
retard black progress.
26
TWIs,
HBCUs may
the 1990s, this advantage
HBCU
attendance appears to
References
Angrist, Josh and Victor Lavy.
Comparisons
"Does Teacher Training Affect Pupil Learning? Evidence from Matched
Jemsalem Public
in
Journal of Labor Economics, Vol.
Schools."''
19,
2 (Apr. 2001),
343-369.
Borjas,
George
Ethnicity, Neighborhoods, and
J.
Human-Capital
Externalities.
American Economic
Review, June 1995, 85(3), pp. 365-90.
Bowen, William and Bok, Derek. 1998. The Shape of the River: Long Term Consequences of Considering
Race
Case,
in
College and University Admissions. Princeton, NJ: Princeton University Press.
Anne C and
Katz, Lawrence F. "The
Company You Keep: The
Effects of Family and
Neighborhood on Disadvantaged Youths." National Bureau of Economic Research (Cambridge,
MA) Working
Constantine,
Paper No. 3705, 1991.
1995. "The Effect of Attending Historically Black Colleges and Universities on Future
Jill.
Wages of Black
Coleman, James
SiuAQnis." Industrial
S., et al.
and Labor Relations Review,
Vol. 48, 3, 531-546.
Equality of Educational Opportunity. Washington, D.C.: Govermnent Printing
Office, 1966.
Cutler,
David
M and Glaeser, Edward L. "Are Ghettos Good or Bad," Quarterly Journal of Economics,
August
1
997,
2(3), pp. 827-72.
1 1
Dale, Stacey and Alan Krueger. 2002. "Estimating The Payoff Of Attending
An
Application
Of Selection On
Obsei"vables
And
A More
Selective College:
Unobsei"vables," Quarterly Journal of
•,,-•,
fconow/c^, 2002, 107(4,Nov), 1491-1527.
Dehejia, Rajeey H. and Sadek
Studies." The
J.
Wahba. "Propensity Score -Matching Methods
Review of Economics and Statistics. Vol
84,
1
for
Nonexperimental Causal
(Feb. 2002), 151-161.
DiNardo, N. Fortin and T. Lemieux, 1996, "Labor Market Institutions and the Distribution of Wages,
1973-1992
:
A
Semiparametric Analysis", Econometrica, Vol. 64, September, pp. 1001-1044
Donohue, James Heckman, and Petra Todd. 2002. "Social Action, Private Choice, and Philanthropy:
Understanding the Sources of Improvements
in
Quarterly Journal of Economics,
225-268
1
17(1), pp.
Black Schooling
in
Georgia, 1911-1960," The
Drewry, Heniy and Humphrey Doermann. 2001 Stand and Prosper: Private Black Colleges and Their
.
Students. Princeton, NJ: Princeton University Press.
Ehrenberg, Ronald. "Are Black Colleges Producing Today's African American Lawyers?" The Journal of
Blacks
in
Higher Education, ]4(Winter 1996-1997), pp.
Ehrenberg, Ronald and Donna Rothstein. 1994.
"Do
Confer Unique Advantages on Black Students?
Consequences: Contemporary Policy Issues
1
17-119.
Historically Black Institutions of Higher Education
in
27
An
Initial
Analysis." In Choices and
Education, Ronald Ehrenberg, ed. Ithaca,
NY: ILR
Press.
Fordham, Signithia and Ogbu, John. "Black Students' School Successes: Coping with the Burden of
'Acting White.'" The Urban Review, 1986, 18, pp. 176-206.
Fryer,
Roland
G.,
Jr.
with Paul Torelli.
"An Empirical Analysis of Acting White.'" National Bureau of
Economic Research (Cambridge,
Mark
Granovetter,
S.
MA) Working Paper No.
"The Strength of Weak
I'lzs."
1
1334, 2005.
American Journal of Sociology, 1973,
78, pp. 1360-
80.
Heckman, James. 1979. "Sample Selection Bias
as a Specification Error", Econometrica, 47(1), pp. 153-
161.
Heckman, James, Hidehiko Ichimura, and Petra Todd. "Matching
Estimator." Review of Economic Studies. Vol. 65, 2
Homans, George C. The Human Group.
New
(
as an
Econometric Evaluation
1998), 261-294.
York: Harcourt Brace, 1950.
Hoxby, Caroline. 2000. "The Effects of Geographic Integration and Increasing Competition
for College Education,"
NBER Working Paper No.
Jencks, Christopher and David Reisman. 1968. The
in the
Market
6323.
Academic Revolution. Garden
Lazear, Edward. 1999. "Culture and Language," Journal of Political
Economy
City,
NY: Doubleday.
107:6 (December 1999):
S95-S126.
Manski, Charles and David Wise. 1983. College Choice
America. Cambridge: Harvard University
in
Press.
Patton, Lori D. "Reflecting Back,
Looking Forward: Civil Rights and Student Affairs (review)" Journal
of College Student Development, Volume 46, Number
Provasnik, Stephen, Linda Shafer, and
1976
to
Thomas Snyder.
2001. National Center for Educational
1,
January/February 2005, pp. 104-108
Historically Black Colleges and Universities,
Statistics.
NCES
2004-062.
Putnam, Robert. 2000. Bowling Alone: The Collapse and Revival ofAmerican Community. Simon and
Schuster:
Roebuck,
J.
New
York, 2000.
B. and K. S. Murty (1993). Historically Black Colleges
and
Universities, Praeger Publisher.
Rosenbaum, Paul R. and Donald B. Rubin. "The Central Role of the Propensity Score
Studies for Causal Effects." Biometrika.
Vol
70,
1
in
Observational
(Apr. 1983), 41-55.
Rosenbaum, Paul R. and Donald B. Rubin. "Reducing Bias
in Observational Studies
Subclassification on the Propensity Score." Journal of the
American
Using
Statistical Association.
79, 387 (Sept. 1984), 516-524.
Rubin, Donald B. "Assignment to a Treatment Group on the Basis of a Covariate." Journal of
Educational
Statistics. Vol. 2,
1
(Spring 1977), 1-26.
Tatum, Beverly D. Wliy are All the Black Kids
Sitting Together in the Cafeteria?
28
And Other
Vol
Conversations about Race.
US News
New
York: Basic Books, 1997.
and World Report. (2006). America's Best Colleges and Universities.
U.S. Dept. of Education, National Center for Education
INFORMATION SURVEY
Statistics.
HIGHER EDUCATION GENERAL
(HEGIS) XVI: FINANCIAL STATISTICS
HIGHER EDUCATION FOR FISCAL YEAR
1981
[Computer
OF INSTITUTIONS OF
file].
Washington, DC: U.S. Dept. of Education, National Center for Education
1981.
Ann
ICPSR
version.
Statistics [producer],
Arbor, MI: Inter-university Consortium for Political and Social Research [distributor],
2005.
U.S. Dept. of Education, National Center for Education Statistics.
EDUCATION DATA SYSTEM
file].
ICPSR
Version. Washington,
Statistics [producer], 1994.
Research
Wilson, William
[distributor],
J.
(IPEDS):
Ann
INTEGRATED POSTSECONDARY
FALL ENROLLMENT ANALYSIS,
1989 [Computer
DC: U.S. Dept. of Education, National Center
for Education
Arbor, MI: Inter-university Consortium for Political and Social
2003.
The Truly Disadvantaged: The Inner
Chicago, IL: University of Chicago Press.
29
City, the Underclass,
and Public
Policy. 1987.
Appendix: Data Description
General structure of dummy variables used on right-hand side of regressions
Family income
•
dummy
Five
variables: family
income
in
1972 dollars
$8,999, greater than or equal to $9,000, and missing.
$3,000 to $5,999, $6,000 to
omitted the less than $3,000 categoi'y.
Parents' education
•
dummy
For each parent, four
variables: less than bachelor's degree, bachelor's degree,
bachelor's degree, and missing.
We omitted the
less than bachelor's
more than
degree category.
Test scores
•
For combined
SAT
scores, four
missing. For composite
missing.
We
dummy
ACT scores,
variables: less than 600,
four
omitted the lowest category
dununy
in
600
to 800, greater than 800,
and
variables: less than 11, 11 to 15, greater than 15,
and
each case.
High school grades
•
Four
variables: GPA on a four-point
We omitted the lowest categoi'y.
dummy
missing.
Binary variables
•
dummy
Three
•
NLS1972
•
Race
The
(sex, rural.
dataset contains
974
•
The
data,
scale less than 2.5,
numerous race variables collected
because
We
identified black
this variable is
from 2.5
to 3.5, greater than 3.5,
and
South, private high school)
variables: each of the binary possibilities,
not mutually consistent.
1
less than $3,000,
We
missing
and missing.
in different years. In
29 cases, these variables are
and white students using the composite race variable
in the
in the
fewest cases.
Sex
dataset contains several sex variables collected in different years. In 22 cases
whom we
identified as black, these variables are not mutually consistent.
or female according to the composite sex variable in the
•
HBCU attendance
We
investigated the effect of a student's
1
974
We
among
the students
identified students as
male
data.
first college being a historically black institution. In each wave of
were asked whether they had attended any institution of higher education since the
previous wave. If they had, they reported the name of the institution; whether it was a vocational school, a
two-year college, or a four-year college; and the first date on which they attended this school. We
the survey, students
30
compared
the dates of attendance at
all
four-year colleges reported to find the
The survey includes a unique numerical code
detemiine whether the first college was historically black. We
first
for each college;
attended, if any.
restricted our
we
four-year college
used these codes to
sample
to students
who
one four-year college. We did not use the transcript data in the NLS to
determine whether a student went to college and, if so, what college the student attended first because
transcripts are sometimes missing.
reported attending
at least
•
Wages and employment
We
computed hourly wages only
30 hours per week.
status
for full-time workers,
whom we
defined as individuals
who worked
at
least
Respondents were asked in 1986
be reported
in hourly,
to report their salary in their current or
most recent job. The wage could
how many
we
weekly, bi-weekly, monthly or yearly increments. Respondents also said
hours they worked per week in
this job.
For full-time workers
who
reported a weekly salary,
We divided biweekly
by two times the hours worked per week, monthly salaries by (52/12) times the hours worked per
week, and yearly salaries by 52 times the hours worked per week.
converted to an hourly wage by dividing the salai^ by hours worked per week.
salaries
We did not create the wage variable for individuals whose calculated wages were extremely low or high
wages. We considered a calculated wage to be too low if was less than half the federal minimum wage
in 1986 ($3.35). We also rejected as an outlier one individual whose calculated wage was more than
$14,000 per hour; all other calculated wages were less than $1,000 per hour. We converted wages to
it
1982-1984 dollars by dividing by the 1986 CPI-U.
Family income
In 1972, students
were asked, "What
is
the approximate
guardian)? Include taxable and non-taxable from
•
(or
composite father's education and composite mother's education variables in the 1974
data.
Test scores
The combined SAT score
composite
•
income before taxes of your parents
sources."
Parents' education
We used the
•
all
is
the
sum of the
reported
SAT math
and verbal scores. The data include the
ACT score.
High school grades
In 1972, students were asked, "Which of the following best describes your grades so far in high school?"
The options were: 1) mostly A, 2) about half A and half B, 3) mostly B, and so on up to 7) mostly D,
and 8) mostly below D. Call the reported number X. We approximated the student's grade point average
on a four-point scale by (9-X)/2, which works out to 4.0 for students reporting mostly A's, 3.0 for
students reporting mostly B's, and so on.
•
The
Rural
variable
is
one
if the
student reported living in a mral or fanning community.
31
•
South
The
variable
is
one
•
Private high school
The
variable
is
one
student's reported region of residence in high school
if the
if
was
in the South.
the student's high school principal or counselor described the school as private or
Catholic.
•
Post-secondary education
Respondents were asked, "As of the
first
week of Febraary
1986, what v/as your highest level of
education?" In addition, the data include transcripts from most post-secondary institutions that
respondents attended.
We
considered a respondent to have a bachelor's degree
if the
person reported
completing college or receiving a master's degree, doctorate or advanced professional degree, or
the transcripts
showed
a bachelor's degree.
We
if
any of
considered a person to have received a graduate degree
if
the person reported receiving a master's degree, doctorate or advanced professional degree, or if any of
the transcripts
showed such
To detennine whether
a degree.
a person had attended graduate school,
on post-secondaiy attendance that
we had
we began with
the self-reported information
used to identify the fust college attended. Respondents were
were you studying for?" We considered the
any time, he or she reported studying for a master's
degree, a doctorate or an advanced professional degree. In addition, any respondent who never reported
studying for a graduate degi'ee, but whose transcripts showed such a degree, was coded as having attended
asked,
"What kind of certificate,
license, diploma, or degree
respondent to have attended graduate school
if,
at
graduate school.
•
College majors
We
considered the student's major for the
the student's transcripts.
first
The data include 661
bachelor's degree received, based on the dates
six-digit
codes for college majors.
shown on
We categorized any
the 74 codes beginning with 06, 07 and 08 as a business major; any of the 53 codes beginning with
14,
27 and 40 as a major
in
of
1 1,
computer science, mathematics, physical science or engineering; and any of
the 108 codes beginning with 17, 18 and 26, plus code 190503, as a major in health or biological science.
The categorization was chosen to match as nearly as possible the much less specific categories used in
Baccalaureate and Beyond data. If a student received two bachelor's degrees on the same date, we
counted the student as having a major in a particular field if either degree showed a major in that field.
•
Utility
the
measures
were asked "how do you feel about" the following statements: "I take a positive
"I feel I am a person of worth, on an equal plane with others"; and "I am able to
do things as well as most other people." Respondents could say they agreed strongly, agreed, disagreed,
disagreed strongly, or had no opinion. We converted these questions to binai^y variables by coding "agree
strongly" and "agree" as a positive response, "disagree" and "disagree strongly" as a negative response,
and "no opinion" as missing.
In 1986, respondents
attitude
•
toward myself;
Weights
32
We used the
•
B&B
•
Race
nonresponse-adjusted weight for participants
in the
1986
fifth
follow-up survey.
1997
Respondents were asked
selection in the
1
their race in the
994 survey.
We
1993 survey; they were then asked to confirm or correct
limited the sample to students
who
this
identified themselves as black in the
1994 survey.
•
Sex
Respondents were asked
gender when
their
it
was not obvious
to the interviewer.
•
HBCU attendance
We
investigated the effect of receiving a bachelor's degree from a
indicating whether the student received a bachelor's degree from a
HBCU. The data contain a variable
HBCU, transferred from a HBCU to
variable is missing either if the student is known never to have
no information on whether the student ever attended a HBCU. We checked
this variable by merging the school codes for bachelor's degree institutions to our list of HBCUs. Among
black students, the only discrepancies were in 10 cases where the HBCU variable in the data was missing
but our list showed that the school was a HBCU. We used the results from merging tlie school codes to
The
the degree institution, or both.
attended a
HBCU
or if there
is
our
list.
•
Wages and employment
We
divided the annual salary recorded for the respondent's April 1997 job by 52 times the average
status
number of hours worked per week. The data define ftiU-time workers as non-teachers who worked at least
30 hours per week and teachers who described themselves as working full time. We rejected as outliers
three cases where the calculated hourly wage was less than half the federal minimum wage in 1997
($5.15). We found no implausibly high wages. We converted wages to 1982-1984 dollars by dividing by
the 1997CPI-U.
Family income
We
used family income
students
who were
in
1991 and converted to 1972 dollars by dividing by the annual CPI-U. For
their parents'
dependents
in 1991, total family
taxed and untaxed income was
obtained, in order of priority, from the student's financial aid application, a telephone interview of
parents, a telephone interview of the student, the student's Pell grant
students
who were
not their parents' dependents, the variable
income. This was obtained,
in
file,
or the student loan
the student's
own
file.
For
taxed and untaxed
order of priority, from the financial aid application, the student's phone
interview, the student's Pell grant
•
is
file,
or the student loan
file.
Parents' education
The data contain variables from 1994 and 1997 indicating each parent's highest level of educafion. The
only cases in which these variables disagree are where one of them is missing. We combined them.
33
•
Test scores
The data
list
•
South
The
variable
combined
is
one
SAT
scores and composite
if the parents' state
ACT scores.
of legal residence was Alabama, Arkansas, Delaware, the District
of Columbia, Florida, Georgia, Kentucky, Louisiana, Maryland, Mississippi, North Carolina, Oklahoma,
South Carolina, Tennessee, Texas, Virginia or West Virginia.
•
Private high school
The
variable
is
one
if
the student said he or she graduated
from a Catholic, other
religious, or
non-
religious private high school.
•
Post-secondary education
All students in this dataset received a bachelor's degree.
The data contains
variables listing the highest
degree a student reported receiving after the bachelor's and the highest-level degree program
student enrolled after receiving the bachelor's.
doctorate,
first
professional, post-master's certificate,
certificate or license.
program
We
classify the student as
if the variable lists a doctorate, first
master's.
We
The degrees
verified that all students
who
that
MBA,
in
can be listed in these variables
which the
are:
master's, bachelor's, associate's, and other
having received a graduate degree or attended a graduate
professional degree, post-master's certificate,
MBA or
received graduate degrees are listed as having attended a
graduate program.
•
The
College majors
dataset contains a composite variable indicating the student's major that
surveys, transcripts and financial aid records. This variable
a physical science major if this variable
lists
lists
when
We record
the major as engineering or "mathematics and other
sciences," which consist of computer science and physical sciences.
science major
was compiled from student
12 broad categories of majors.
We record a health and biological
the variable indicates a major in either "health professions" or "biological science."
We record a business major when the
variable indicates "business and
•
Weights
We
weighted by the nonresponse-adjusted weight for respondents
•
College and Beyond
•
Race
The
institutional data files contain
to students listed as black in either
two variables indicating
of these variables.
34
management."
to the
1997 survey.
the student's ethnicity.
We
limited the sample
Sex
•
From
the institutional data.
HBCU attendance
•
The four HBCUs in the College and Beyond sample are Howard University, Morehouse College,
Spelman College and Xavier University of Louisiana.
Wages and employment
•
Respondents reported
status
their annual pre-tax earned
income, including income from jobs; net income from
businesses, farms or rent; pensions; and Social Security.
They were
instructed not to include
income from
dividends and interest and not to count the income of other family members. They reported income
We
take the midpoint of each bracket except the top bracket, which
in
10
S200,000 or more. For
the top bracket, we follow Dale and Kj'ueger (2002) and use the average income shown in the 1990
census for college graduates in the appropriate cohort who earned more than $200,000 per year. We
included all individuals with reported income in our regressions.
categories.
We
is
employment
as an outcome. Respondents were asked, "Are you currently
answered yes, they were asked whether they were working "only or
mostly full-time," "some full-time and some part-time," or "only or mostly part-time." We coded only the
first of these categories as full-time employment.
also considered full-time
working
for
pay or profit?"
If they
Family income
We
used the family income variable from the
HERI
student survey; this
is
a categorical variable.
We
converted to 1972 dollars using the CPI-U.
Parents' education
•
When
a parent's education
is
listed as "attended or
graduated from college (can't
tell)",
we
categorized
the parent as having less than a bachelor's degree.
Test scores
•
We used SAT scores
from the Educational Testing Service
file
and
ACT scores
from the
institutional
data.
•
High school grades
We
obtained high school grades from the
HERI
student survey. This variable
lists
the student's average
A or A-t-. We treat D as a GPA of 1, C as a GPA
a GPA of 3, B-^ as a GPA of 3.33, A- as a GPA of
high school grade as either D, C, C+, B-, B, B-h, A-, and
of
2,
3.67,
•
C+
GPA of 2.33, B- as a GPA
A or A-^ as a GPA of 4.
as a
and
of 2.67,
B
as
South
variable is one if, when he or she applied to college, the student lived in Alabama, Arkansas,
Delaware, the District of Columbia, Florida, Georgia, Kentucky, Louisiana, Maryland, Mississippi, North
The
35
Carolina, Oklahoma, South Carolina, Tennessee, Texas, Virginia or
•
Private high school
The
variable
•
Post-secondary education
is
one
West
Virginia.
student attended a parochial or private high school.
if the
Respondents were asked
in the follow-up sui"vey whether they had received a bachelor's degree. For each
of more than 20 kinds of graduate and professional degrees, respondents were asked whether they had
studied for the degree and whether they had actually received it. We combined these responses into binary
variables indicating whether the respondent studied for or received any graduate degree.
College majors
•
The data list up to two majors for each student. We recorded a major in physical science if either major
was engineering, computer and infonnation sciences, mathematics, astronomy/atmospheric sciences,
chemisti'y, geological sciences, physics, or other physical sciences.
We recorded a major in
health or
was biological sciences, pre-med, nursing, dentistry, or health
business if either major was business and management.
biological sciences if either major
We
recorded a major
In 1989, five
total
in
major codes — 345, 734, 905, 920 and 980 - appear in the data but not in the codebook.
We assumed none of these codes represented a
Development
as an
at all,"
how much
field.
undergraduate
Respondents indicated on a one-to-five
"not
A
of 17 black students have one of these codes.
physical science, a health or biological science, or a business
•
sciences.
scale,
where
five represented "a great deal"
their undergraduate experiences helped
them develop
in
and one represented
each of 15 areas.
We kept
these variables in continuous fonn.
•
Job
satisfaction
Respondents were asked about 13 aspects of job satisfaction. In each categoi'y, they could indicate they
were "vei^ satisfied," "somewhat satisfied," or "not satisfied." We converted these variables to binary
forni by coding "vei^y satisfied" as one and "somewhat" or "not satisfied" as zero. We examined each of
the 13 binary variables separately.
variables and
•
Utility
examined
We also computed the first principal
component of the
13 binaiy
the resulting continuous variable.
measures
Respondents were asked:
"In general,
how
satisfied
would you say you
are with your life right
now?"
and
"Overall,
how
which you
satisfied
first
have you been with the undergraduate education you received
at the
school
at
enrolled?"
The possible responses were "vei7 satisfied," "somewhat satisfied," "neither satisfied nor dissatisfied,"
"somewhat dissatisfied," and "very dissatisfied." We converted these to binai-y variables by coding "veiy"
and "somewhat satisfied" as one and the remaining categories as zero.
36
Respondents were also asked, "Imagine that you had your life to live over again and were graduating
from high school. Knowing what you do now, how likely is it that you would choose the same
undergraduate school?" Possible responses were "veiy likely," "somewhat likely," and "not
converted
this to a
likely.
We
binary variable by coding "very" and "somewhat likely" as one and "not likely" as
zero.
Academic outcomes index
The
first
principal
component of the
dummy
variables for majoring in business, majoring in physical
science/mathematics/computer science/engineering, majoring
in biological science/health, receiving a
bachelor's degree, attending graduate school, and receiving a graduate degree.
Subjective academic index
The
component of the dummy variable for being satisfied with the undergraduate
duinmy variable for being likely to choose the same undergraduate school again; the
variable for reporting that anyone took a special interest in one's work at the undergraduate
first
principal
education; the
dummy
school; a variable that rates on a one-to-five scale
how much
the undergraduate education helped develop
and a variable that rates on a one-to-five scale how much the
undergraduate education helped develop knowledge of a particular field.
analytical
and problem-solving
skills;
Subjective labor market index
first principal component of duminy variables for whether the person reported being vei7 satisfied
with the following characteristics of the cuaent job: intellectual challenge, flexible schedule, high level of
The
responsibility,
low
stress,
working environment, job
security,
employer-supported child care,
fair
treatment of women and minorities, high income, good benefits, promotion cpportunides, and service to
society.
Leadership/lifestyle index
The
first
principal
component of variables
rating,
on a one-to-five
education helped develop each of the following: leadership
scale,
how much
the undergraduate
community sei'vice,
work cooperatively, ability
abilities, interest in
religious values, ability to cominunicate orally, competitiveness, ability to
to
relax or enjoy leisure, ability to write clearly and effectively, and ability to adapt to change.
Social interactions index
The
first
principal
component of variables
rating,
on a one-to-five
scale,
how much
the undergraduate
education helped develop each of the following: ability to fonn and retain friendships, ability
rapport with people of different beliefs, and ability to
•
Other outcome variables
The
other outcome variables
•
Weights
we
work and
to
have
get along with people of different races.
studied are binary in the data.
Because the College and Beyond surveys included 100% of minority students
is no need to use weights.
37
at
the sample schools, there
38
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Table 2: Determinants of
Dataset
HBCU
HBCU
Definition
Among
Attendance
NLS
'
first
college
SAT: >800
ACT: 11-15
ACT:>15
family income:
family income:
family income:
$3000-$5999
$6000-$8999
>=$9000
father's education: bachelor's
father's education: >bachelor's
mother's education: bachelor's
mother's education: >bachelor's
south
private high school
female
ObsePv/ations
pseudo R-squared
in
NLS and BB
BB
(1972)
bachelor's degree college
(1997)
bachelor's degree college
(1)
12]
(3)
-0.170
-0.012
-0.032
(0.072)
(0.112)
(0.128)
-0.320
-0.226
-0.067
(0.049)
(0.081)
(0.120)
.,
SAT: 600-800
Blacks
NLS
(1972)
-0.116
-0.306
0.130
(0.112)
(0.058)
(0.200)
-0.213
-0.296
-0.167
(0.083)
(0.062)
(0.109)
0.018
0.010
0.064
(0.079)
(0.117)
(0.089)
-0.069
-0.174
0.073
(0.077)
(0.092)
(0.099)
0.062
-0.014
-0.058
(0.088)
(0.113)
(0.063)
-0,031
-0.154
0.165
(0.144)
(0.130)
(0.087)
-0.130
-0.318
0.127
(0.112)
(0.036)
(0.110)
0.097
0.230
0.144
(0.145)
(0.182)
(0.086)
0.082
0.035
0.280
(0.133)
(0.156)
(0.115)
0.429
0.473
0.126
(0.049)
(0.060)
(0.054)
-0.065
0.099
-0.139
(0.132)
(0.153)
(0.059)
0.033
0.024
0.047
(0.053)
(0.069)
(0.057)
496
308
424
24
0.31
0.15
Notes: The tables reports the results from the estimation of probits for the probability of enrolling at a
HBCU
(column
(noted
in
1
)
and graduating from a
HBCU
(columns 2 and
3).
All of
the explanatory variables
the row headings are indicators, so the entries report the discrete change
associated with a change
in
the probability
one and the associated heteroskedastic-consistent
standard error. (The standard errors in the columns (1) and (2) are clustered by high school.) The
omitted categories are: SAT<600, ACT<1 1, family income <$3000, father's education < bachelor's,
mother's education < bachelor's. The models also include dummy variables for each category
whose value is one when the categorical variable is missing. The samples are limited to Blacks with
measured 1986 wages (NLS) or measured 1997 wages (B&B). In the B&B, 2 observations were
dropped because a regressor perfectly predicted the outcome. See the text for further details.
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.
Table
5:
Determinants of
HBCU
Attendance
Dataset
C&B
HBCU
first
Definition
Include Howard,
Spelman?
SAT: 600-800
SAT: >800
ACT: 11-15
ACT:>15
family income:
family income:
family income:
>=$9000
father's education: bachelor's
father's education: >bachelor's
college
first
C&B
(1976)
college
C&B
(1989)
college
first
no
no
(2]
(3)
-0.138
-0.620
(0.074)
(0.035)
(0.021)
-0.584
-0.512
-0.998
(0.056)
(0.075)
(0.001)
-0.315
-0.099
-0.124
(0.124)
(0.052)
(0.180)
-0.489
-0.167
-0.336
(0.039)
(0.025)
(0.108)
0.005
-0.013
-0.089
(0.067)
(0.056)
(0.106)
-0.059
-0.091
-0.264
(0.064)
(0.035)
(0.068)
-0.033
-0.105
-0.271
(0.060)
(0.042)
(0.073)
-0.064
0.152
0.011
(0.053)
(0.062)
(0.063)
-0.042
-0.085
-0.065
(0.068)
(0.046)
(0.070)
0.034
0.097
0.144
(0.052)
(0.055)
(0.068)
0.101
-0.113
0.316
(0.068)
(0.039)
(0.070)
mother's education: >bachelor's
0.350
0.357
0.327
(0.027)
(0.035)
(0.034)
south
female
in
C&B
m
-0.212
mother's education: bachelor's
private high school
Blacks
yes
$3000-$5999
$6000-$8999
Among
(1976)
-0.051
0.093
-0.031
(0.032)
(0.033)
(0.039)
-0.077
-0.337
-0.343
(0.028)
(0.034)
(0.034)
Observations
1982
1152
1414
pseudo R-squared
0.33
0.55
0.48
Notes:
The
tables reports the results from the estimation of probits for the probability of
enrolling at a
samples
HBCU among
of Blacks.
All
the
C&B 1976
(columns
and
1
of the explanatory variables (noted
2)
in
and
C&B 1989
(column 3)
the row headings) are
indicators, so the entries report the discrete change in the probability associated with a
change in value from zero to one and the associated heteroskedastic-consistent standard
error. The omitted categories are: SAT<600, ACT<1 1 family income <$3000, father's
education < bachelor's, mother's education < bachelor's. The models also include dummy
variables for each category whose value is one when the categorical variable is missing.
The samples are limited to individuals with measured 1995 annual income (C&B 1976) or
measured 1996 annual income (C&B 1989). In the C&B 1976 sample without Howard and
Spelman colleges, 202 observations were dropped because the regressors perfectly
predicted the outcome. In C&B 1989, 345 observations were dropped because the
,
regressors perfectly predicted the outcome.
See
the text for further details.
Table
6:
Effects of
HBCU
Attendance on Labor Market and Other Outcomes
C&B
Dataset
HBCU
Definition
Include Howard,
first
Spelman?
(1976)
college
C&B
first
(1976)
college
employed
full
time
subjective labor market index
C&B
first
(1989)
college
m
(1)
Labor Market Outcomes
-0.074
C&B
no
yes
Ln (Annual Income)
in
-0.032
-0.114
(0.069)
(0.145)
(0.160)
963/1019
611/711
0.099
335/468
0.513
(0.112)
(0.363)
(0.202)
110/123
24/10
100/109
0.059
0.104
0.032
(0.061)
(0.164)
(0.123)
972/1135
339/532
550/655
-0.181
Life Satisfaction
satisfied with
college
was
first
-0.046
-0.013
(0.026)
(0.044)
(0.044)
977/1137
341/536
621/716
-0.009
life
choice
would choose same college
again
leadership/lifestyle index
social interactions index
college developed
ability to
form and retain friendships
college developed ability to
have rapport w/ people of
college developed ability to
get along with other races
different beliefs
-0.084
-0.079
-0.063
(0.034)
(0.079)
(0.058)
932/1108
314/545
0.219
613/712
0.177
(0.035)
(0.086)
(0.054)
981/1132
340/534
0.417
0.633
622/717
0.152
-0.048
(0.069)
(0.157)
(0.109)
977/1132
618/717
0.220
341/530
0.357
(0.071)
(0.169)
(0.123)
976/1131
341/530
0.423
0.530
619/715
0.129
-0.177
(0.088)
(0.142)
(0.124)
966/1100
337/520
0.386
613/710
0.254
(0.088)
(0.205)
(0.116)
966/1121
0.034
337/526
0.255
614/709
(0.093)
(0.211)
(0.170)
961/1124
334/525
613/713
-0.220
-0.445
Academic Outcomes
received bachelor's degree
attended graduate school
received graduate degree
academic outcomes index
subjective
academic index
physical science major
biological science
major
-0.105
-0.047
-0.105
(0.025)
(0.068)
(0.037)
978/1138
339/539
623/718
-0.101
-0.116
-0.019
(0.033)
(0.086)
(0.059)
983/1142
342/537
623/718
-0.136
-0.149
-0.007
(0.033)
(0.082)
(0.057)
983/1142
342/537
623/718
-0.301
-0.296
-0.123
(0.066)
(0.185)
(0.110)
983/1142
342/537
0.356
623/718
0.165
(0.072)
(0.204)
(0.096)
982/1138
341/539
623/718
-0.027
-0.107
0.074
(0.028)
(0.080)
(0.042)
784/771
0.087
269/459
0.120
552/636
0.196
-0.201
business major
(0.026)
(0.051)
(0.040)
784/771
269/459
0.234
552/636
0.111
0.214
(0.021)
(0.030)
(0.028)
784/771
269/459
552/636
Other
fraction black
in
zip
code
0.022
0.081
0.156
(0.025)
(0.074)
(0.041)
902/669
315/350
602/593
Participation
political
religious
civil rig hits
social service
alumni
national cliarity
0.019
-0.032
0.216
(0.032)
(0.078)
(0.065)
983/1142
342/537
0.039
0.085
623/718
0.108
(0.036)
(0.087)
(0.062)
983/1142
342/537
623/718
0.004
0.071
0.105
(0.035)
(0.081)
(0.063)
983/1142
342/537
623/718
0.116
-0.024
-0.059
(0.029)
(0.069)
(0.063)
983/1142
623/718
-0.007
342/537
0.000
(0.036)
(0.086)
(0.056)
983/1142
342/537
623/718
-0.098
-0.168
0.148
(0.038)
(0.079)
(0.062)
983/1142
342/537
623/718
0.030
Notes: The entries report the results from propensity score matching routines. The row headings report the
dependent variables. The samples and treatment are noted in the column headings. The entries report the
unweighted impact of HBCU matriculation (graduation), relative to TWI matriculation (graduation). The propensity
score is estimated with a probit and all of the covariates used in Table 2 are included as explanatory variables.
The matching method uses a gaussian kernel with a bandwidth of 0.1. The standard errors (reported in
parentheses) are computed by bootstrapping, with propensity scores recomputed for each bootstrap sample. For
each outcome, all observations with data on that outcome are used. Indexes are first principal components of
sets of variables, normalized to have mean
and variance 1. In constructing each index, we include every
observation that has data on at least one variable in the set, by replacing any missing data with the mean of the
corresponding variable. Numbers underneath standard error are number of HBCU and TWI students,
respectively. Observations are dropped if the propensity score is not strictly between
and 1. See the text and
notes to Table 3 for more details.
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Appendix Table
1:
Summary
Basic
Statistics
Nurriber College or University
on the Historically Black Colleges and Universitie
Location
Normal,
2
Alabama A&M University
Alabama State University
3
Albany State University
Albany,
4
Alcorn State University
Alcorn State,
1
AL
Montgomery, AL
GA
5
Allen University
6
Arl<ansas Baptist College
7
Benedict College
8
Bennett College
MS
Columbia, SC
Little Rock, AR
Columbia, SC
Greensboro, NC
9
Bethune-Cookman College
Daytona Beach, FL
10
Bluefield State College
Bluefield,
11
Bowie State University
Bowie,
12
Central State University
Wilberforce,
WV
MD
OH
Cheyney, PA
Orangeburg, SC
Atlanta, GA
13
Cheyney
14
Claflin University
15
Clark Atlanta University
16
Coppin State College
Delaware State University
Baltimore,
17
18
Dillard University
New
University of Pennsylvania
Dover,
MD
DE
LA
Orleans,
19
Edward Waters College
Jacksonville,
20
Elizabeth! City State University
Elizabeth City,
21
Fayetteville State University
Fayetteville,
22
23
24
25
26
27
28
29
30
Fisk University
Nashville,
Florida A&IVI University
Tallahassee, FL
Florida IVIemorial University
Miami Gardens, FL
Type
Undergraduate
Total
Enrollment
Enrollment
5,047
6,182
Public
4,485
5,469
Public
3,228
3,649
Public
2,962
3,544
Public
624
287
624
287
Private
2,552
2,552
572
Private
572
3,090
3,090
Private
Public
Private
Private
1,708
1,708
4,020
5,319
Public
1,617
1,623
Public
1,401
1,560
Public
1,678
1,728
Private
3,667
4,469
Private
3,451
4,306
Public
3,440
3,722
Public
1,993
1,993
Private
Private
FL
839
839
NC
NC
TN
2,604
2,664
5,029
6,072
Public
864
920
Private
10,552
12,154
Public
1,945
2,004
Private
1,997
2,174
GA
Public
Fort Valley State University
Fort Valley,
Grambling State University
Grambling, LA
4,573
5,164
Public
Hampton
University
Hampton,
VA
5,325
6,309
Private
Harris-Stowe State University
St. Louis,
MO
1,662
1,662
Public
Howard
Washington,
7,164
10,930
Private
Private
University
DC
Public
Huston-Tillotson College
Auston,
TX
31
Interdenominational Theological Center
Atlanta,
32
33
34
35
36
37
38
39
40
Jackson State University
Jackson,
GA
MS
Jarvis Christian College
TX
Charlotte, NC
Frankfort, KY
Knoxville, TN
Jackson, TN
1,404
1,404
2,228
2,386
Public
300
300
Private
1,213
1,213
Private
Johnson C. Smith University
Kentucky State University
Knoxville College
Lane College
Langston University
675
Hawkins,
706
447
8,416
Public
572
572
Private
Private
Private
Langston,
OK
3,001
3,151
Public
Lemoyne-Owen College
Memphis,
TN
809
809
Private
Lincoln University
Jefferson City,
2,953
3,180
1,714
2,278
Public
895
895
707
Private
Private
MO
41
Lincoln University
Lincoln University,
42
43
44
45
46
47
48
49
50
Livingstone College
Salisbury,
Meharry Medical College
Nashville,
Miles College
Fairfield,
Mississippi Valley State University
Itta
Morehouse College
Morehouse School of Medicine
Morgan State University
Morris Brown College
Atlanta,
Morris College
Sunter,
51
Norfolk State University
52
53
54
55
56
57
58
59
60
North Carolina
61
-
6,660
A&T
State University
North Carolina Central University
Oakwood
College
Atlanta,
Public
3,029
3,029
Private
-
272
Private
5,747
6,438
Public
66
863
66
863
Private
MD
SC
VA
University
Rust College
AL
GA
TX
Rock,
Prairie
NC
NC
Huntsville,
Little
A&M
AR
View,
TX
MS
Lawrenceville, VA
Savannah, GA
Holly Springs,
Saint Paul's College
Savannah State
1,758
3,165
Durham,
Dallas,
View
1,758
Greensboro,
Philander Smith College
University
Private
2,748
Georgia
Paul Quinn College
-
Public
MS
GA
GA
Baltimore,
Norfolk,
PA
AL
Bena,
Augusta,
Paine College
Prairie
NC
TN
Private
5,337
6,096
Public
9,735
11,103
Public
6,353
8,219
Public
1,751
1,751
Private
828
790
785
828
790
785
Private
5,702
7,912
Public
970
717
970
717
Private
2,975
3,091
Public
Private
Private
Private
Selma, AL
Selma University
287
287
Private
2,565
2,762
Private
3,888
4,446
Public
Baton Rouge, LA
8,969
10,364
Public
New
2,824
3,647
Public
62
63
64
65
66
67
68
69
70
Stillman College
Tuscaloosa,
71
Talladega College
Talladega
72
73
74
75
76
77
78
79
80
Tennessee State University
Texas College
Texas Southern University
Tyler,
Tougaloo College
Tougaloo,
Shaw
Southern University
A&M
Southern University at
College
New
Orleans
Orleans,
Terrell,
Spelman College
Atlanta,
Augustine's College
Tuskegee University
University of Arkansas
SC
Orangeburg,
Southwestern Christian College
St.
NC
Raleigh,
University
South Carolina State University
LA
TX
Raleigh,
GA
NC
AL
TN
Nashville,
TX
Houston,
TX
IvIS
Tuskegee, AL
at
Pine Bluff
Pine
Shore
Columbia
Bluff,
AR
University of Maryland Eastern
Princess Anne,
University of the District of
Washington,
MD
DC
251
251
Private
2,318
2,318
Private
1,163
1,163
Private
804
368
804
368
Private
7,036
8,880
Public
794
807
Private
9,760
11,903
Public
933
933
Private
2,510
2,880
Private
3,132
3,231
Public
3,448
3,870
Public
5,169
5,363
Public
Public
Private
University of the Virgin Islands
Charlotte Amalle, VI
2,185
2,392
81
Virginia State University
Petersburg,
4,332
5,055
Public
82
Virginia
1,344
1,700
Private
83
84
Virginia University of
Private
Voorhees College
VA
Richmond, VA
Lynchburg, VA
Denmark, SC
85
86
87
88
89
West
Institute,
Union University
Lynchburg
Virginia State University
Wilberforce,
Wilberforce University
TX
Marshall,
WInston-Salem State University
WInston-Salem,
Xavier University
New
Notes: The
is
OH
Wiley College
list
of schools
is
taken from the
US Department
http ://www. ed.gov/about/inits/list/whhbcu/edlite- list.html.
2005)
WV
from the National Center
for
Education
Orleans,
NC
LA
of Education's
The
web
location data
122
709
178
709
3,455
3,491
Public
1,157
1,170
Private
Private
Private
827
827
5,264
5,566
Public
2,343
3,091
Private
site:
and enrollment Information (current as
Statlstlcs's site: http://nces.ed.gov.
:
of Fall
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