280 J. Monks Economics of Education Review 19 2000 279–289
uals and institutions I am able to estimate the impact of college quality on the log of hourly wages, within
institutional type and conditional upon individual charac- teristics. Conversely, I am able to estimate the returns to
other institutional characteristics conditional upon qual- ity. This is especially important in an educational
environment where the market value of a liberal arts education is under scrutiny, and where the higher costs
of private versus public colleges and universities are being questioned McPherson Schapiro, 1991.
I find strong evidence of higher earnings among the graduates of more selective institutions. There is also
evidence of a premium for attending a larger graduate degree granting university, rather than a liberal arts col-
lege, and weak evidence that graduates of private insti- tutions earn more than graduates of public institutions.
While this pattern of returns to institutional character- istics holds for most groups, there is heterogeneity in the
magnitude of the returns to institutional attributes based on race and gender. For example, it appears that males
receive a higher return to attending a graduate degree granting university and a private institution than females;
in contrast, there does not appear to be a significant dif- ference in the earnings of non-white college graduates
from public versus private institutions, while whites are penalized by the market for attending a public college
or university. Additionally, non-whites from a highly or most selective institution earn a much higher premium
than their white counterparts.
The remainder of the article is divided into four main topics. The next section outlines the sample chosen and
constructed for this study. This is followed by a descrip- tion of the underlying economic model and econometric
methodology used to estimate the earnings across college characteristics. The next section presents the results of
the regression analyses, and the final section summarizes these results.
2. Data
This study utilizes the National Longitudinal Survey of Youth. The NLSY is a survey of individuals from
1979 to 1996.
1
The respondents were aged between 14 and 22 at the beginning of the survey, in 1979, and aged
between 28 and 36 in 1993. This data set is particularly useful for this study since it tracks college-aged individ-
uals through their college years and into their early labor market experiences.
This paper exploits the Federal Interagency Commit- tee on Education FICE codes reported by NLSY
1
At the initial time of this study, the 1994 and 1996 survey responses were not available. As a result, this study only uses
the annual NLSY data from 1979 to 1993.
respondents for each spell of college attendance. Begin- ning in 1984, the NLSY asked each respondent who
reported attending a college or university the name of the three most recent colleges attended and the dates they
attended each institution. These responses were then recorded using the college or university’s FICE code.
Additionally, each respondent was asked their highest degree received and the date they received this degree.
By matching the date they received their baccalaureate degree to the college spell information I was able, in
most cases, to determine the FICE code of the respon- dent’s baccalaureate degree granting institution.
Respondents from the military and disadvantaged white subsample were excluded from the sample used
in this study Table 1. Those respondents who had not completed 16 years of schooling by 1993, the survey’s
end at the time of writing, were also excluded from the sample. In some cases 452 respondents the date that
the respondent received his baccalaureate degree could not be determined either because it was simply not
reported or because by the 1988 survey, when the NLSY first asked the respondent’s highest degree ever received,
the respondent had earned a masters degree or higher so the date of the baccalaureate degree was never reported.
For 52 of the respondents, the NLSY staff could not find a FICE code to coincide with the reported college or
university. An additional 224 individuals were excluded from the sample because their reported FICE code could
not accurately be matched to the data sets discussed below to extract the institutional characteristics.
The reported FICE code of each college graduate from the selected sample from the NLSY was matched to the
Computer Aided Science Policy Analysis and Research CASPAR database developed by Quantum Research
Corporation for the National Science Foundation NSF. The CASPAR database is a compilation of data from
surveys of universities and colleges conducted by the NSF Division of Science and Resources Studies. The
control of the institution public or private and the Car- negie classification 2-year, liberal arts, masters, doc-
toral, research or specialized were identified by match- ing the NLSY reported FICE code to this database. The
measure of college quality used in this study was taken from Barron’s Profiles of American Colleges Anon,
1987. Barron’s reports a single summary measure of sel- ectivity non-competitive, less competitive, competitive,
very
competitive, highly
competitive and
most competitive based on the entering class’s SAT and ACT
scores, class rank, high school grade point average, and the percentage of applicants who were accepted. The
1987 Barron’s selectivity ranking is used since it falls roughly into the middle of the survey years, and there is
evidence of a high degree of correlation across time in the selectivity ranking of colleges and universities
Kingston Smart, 1990. There is also evidence to sug- gest that a categorical measure of college quality is pref-
281 J. Monks Economics of Education Review 19 2000 279–289
Table 1 Sample construction
Number of persons Number of person-years
Total NLSY sample 12 686
Less the military subsample 2
1280 Less the poor white subsample
2 1643
Less highest grade completed , 16 2
7945 Less college graduation date unknown
2 452
Less college FICE code unknown 2
52 Less non-matching or two year FICE code
2 224
Chosen respondents 1087
9348 Less employment status recode not working
2 29
2 1865
Less rate of pay less than 2.93 or more than 500 2
6 2
409 Less unreported industry or occupation
2 6
Less highest grade completed 16 by 1993 2
315 2
2002 Less incomplete work history
2 3
2 89
Sample chosen 734
4977
erable to a linear measure in estimating the returns to education Kingston Smart, 1990. In some of the
cases, the reported FICE code could not be matched to the CASPAR database or to the Barron’s Profile because
the reported college was a single university branch and the NSF or Barron’s reporting unit was the entire univer-
sity system, or vice versa. There were also observations where the reported baccalaureate granting institution was
a 2-year college. The observations where these discrep- ancies occurred were excluded from the sample.
The sample resulting from the above restrictions con- tained 1087 individuals and 9348 person-year obser-
vations. Only those person-year observations following the individual’s graduation from college were included
in the sample. This sample was limited further to those observations where the primary activity was working; the
hourly rate of pay was greater than or equal to 2.93 or less than 500; valid industry and occupation were
reported; and a complete work history of experience and tenure were reported.
2
The sample was also restricted to those individuals whose highest grade completed was 16
by 1993. This focuses the investigation on earnings dif- ferentials among working college graduates who do not
continue their education by 1993 and does not address possible returns to college characteristics that may arise
due to increases in the probability of achieving a gradu- ate degree or to possible increases in employment prob-
abilities. The chosen sample has 734 individuals, 407 colleges and universities, and 4977 person-year obser-
vations.
The NLSY has a lower rate of college attendance and
2
All dollar values are constant dollar CPI-U, 198384 5 100. 2.93 represents the 198384 real dollar value of the 1993
minimum wage of 4.25.
graduation than the population at large because it over- samples blacks and Hispanics who tend to have lower
enrollment rates than whites. These over-represented subsamples were included in this study in order to more
efficiently estimate the returns to both individual and institutional characteristics across racial groups. Because
of the large number of respondents excluded from the sample, a close examination of the remaining respon-
dents is warranted. Table 2 compares summary measures of the respondents and colleges from the sample chosen
from the NLSY to the Digest of Education Statistics DES US Department of Education, 1984–1986 and
Barron’s Profiles summary measures.
A strict comparison of the respondents from the NLSY sample to the DES is not possible because the NLSY is
a sample of college graduates currently working and the DES is a survey of either current college graduates or
enrollees. However, comparisons of these two groups would likely reveal any gross misrepresentation of the
population of college graduates in the NLSY. The amount of males in the NLSY is 48, in comparison to
49 in the DES.
3
The NLSY does have a much lower percentage of white college graduates, 72, than the
DES, 85. This is likely to be attributable to the over- sampling discussed above and will be addressed in the
following empirical tests. Because of the relatively small number of respondents who attended both non-competi-
tive and most competitive institutions these categories were combined with less competitive and highly com-
petitive, respectively. This increases the frequency of each cell count and improves the efficiency of the esti-
3
The Digest of Education Statistics does not report standard errors in order to test for significance in the difference between
the variable means.
282 J. Monks Economics of Education Review 19 2000 279–289
Table 2 Comparison of NLSY to Digest of Education Statistics and Barron’s Profiles of American Colleges summary statistics
NLSY DES
Individuals: n 5 734
Percent male 48
49
a
Percent white 72
85
a,b
Average age adjusted AFQT score 1.73
NA Percent attended non or less competitive
27 NA
Percent attended competitive 45
NA Percent attended very competitive
21 NA
Percent attended highly or most competitive 6
NA Percent attended liberal arts colleges
22 16
c
Percent attended masters, doctoral or research universities 77
83
c
Percent attended public institutions 63
67
c
College and universities: NLSY
Barron’s and DES n 5 407
Percent non or less competitive 27
33 Percent competitive
44 48
Percent very competitive 20
12 Percent highly or most competitive
8 7
Percent liberal arts colleges 28
35
d
Percent masters, doctoral and research universities 69
64
d
Percent public institutions 52
28
d a
Percent of bachelor’s degrees awarded by characteristic in the 1984–1985 academic year.
b
Percent of bachelor’s degrees awarded to individuals who were white, non-Hispanic.
c
Percent of individuals enrolled in 1985 by type of institution.
d
Percent of institutions by type and control from the DES, for 1985–1986.
mated returns to these categories. There appears to be sufficient variation in the percentage of individuals who
attended each category of college selectivity. The sample from the NLSY seems to have a higher percentage of
liberal arts college graduates, 22, than the DES, 16. This may be because the NLSY is composed of college
graduates and the DES measures college attendees. If liberal arts colleges have higher graduation rates then we
ought to expect a higher percentage of college graduates attended liberal arts colleges than are currently enrolled.
Sixty-three percent of the NLSY sample attended a pub- lic institution and the DES reports a comparable 67 of
enrollees at public institutions. In summary, it appears that the sample of individuals from the NLSY is compa-
rable to the population of college students, with the noted exception of race.
A word of caution is necessary in comparing the NLSY sample of colleges to Barron’s and the DES. The
NLSY is a number of graduates weighted sample of col- leges. The probability of observing a college is directly
proportional to the number of graduates from that college relative to the population of college graduates. It is there-
fore to be expected that the sample of institutions from the NLSY will favor large, public, graduate degree grant-
ing institutions relative to the cross-section of all col- leges and universities. This comparison is made simply
to determine whether there is adequate variation in the number of each type of institution in the sample so that
I am not inadvertently estimating returns to individual colleges rather than college characteristics. There
appears to be a sufficient number of colleges in each category of selectivity, Carnegie classification and con-
trol in order to draw inferences concerning earnings dif- ferentials across these characteristics.
In addition to the institutional characteristics, I have controlled for individual attributes which determine
wages. In particular, I control for actual work experience since the age of 18 weeks of work divided by 52, and
its square, and tenure weeks at current employer divided by 52, and its square. This accounts for differences in
pre- and post-college work experience and subsequent on-the-job human capital accumulation. A respondent’s
AFQT score is used to control for differences in individ- ual academic ability. Since the Armed Services
Vocational Aptitude Battery ASVAB of tests used in the construction of the AFQT score were given at a sin-
gle point in time, differences in results may arise due to differences in the ages of the sample and not necessarily
283 J. Monks Economics of Education Review 19 2000 279–289
Table 3 Summary measures
Variable Mean
Standard deviation Minimum
Maximum Experience weeks52
7.79 3.34
0.38 18.46
Tenure weeks52 3.04
2.82 0.02
16.50 Male
0.51 0.50
0.00 1.00
White 0.80
0.40 0.00
1.00 Armed Forces Qualification Test
1.75 0.59
0.03 3.09
Public institution 0.63
0.48 0.00
1.00 Masters, doctoral or research university
0.76 0.43
0.00 1.00
Specialized institutions 0.01
0.08 0.00
1.00 Non or less competitive
0.27 0.44
0.00 1.00
Competitive 0.45
0.50 0.00
1.00 Very competitive
0.21 0.41
0.00 1.00
Highly or most competitive 0.06
0.24 0.00
1.00 1979 net family income in 10K
2.55 1.46
0.00 7.50
1979 net family income missing 0.22
0.42 0.00
1.00 Log hourly wage
2.18 0.47
1.08 6.08
Year 88.48
3.17 79.00
93.00 Number of person-year observations
4977
because of differences in academic ability. This problem is minimized by calculating the ratio of each person’s
test score to the average test score for his or her age. Finally, the 1979 net family income is used as a control
for an individual’s ability to pay.
4
Table 3 provides means, standard deviations, minimums and maximums
for all of the variables for the entire sample.
3. Model
