70 T.C. Buchmueller et al. Economics of Education Review 14 1999 65–77
4.2.4. Early research experience If considerable practice in conducting research facili-
tates future research performance, then students who gain early research experience should be more likely to
produce acceptable dissertations within reasonable time limits and to become more successful researchers after
receiving their Ph.D.s. The COGEE survey data provide several indicators of such experience. One important
source of early research experience is work as a research assistant. As apprenticeships of sorts, these opportunities
may give students an improved understanding of the research process and, in some cases, will directly lead to
collaborative work.
We also expect individuals who submitted papers for publication prior to completing their Ph.D.s would be
more productive after doing so. The variable SUBMIT equals 1 if the individual submitted a paper for publi-
cation while in graduate school. The JELELI data allow us to construct two additional measures of pre-Ph.D.
research experience. The variable PREPUB represents the number of publications prior to leaving graduate
school. PRETOP is the number of publications in top 50 economics journals during that same time period.
9
4.2.5. Individual characteristics To estimate the effect of early research experience on
post-Ph.D. publications, it seems desirable to condition on individual aptitude. If research assistantships are
given to the best students in a department, then without adequate controls for ability, we would overstate the true
impact of the experience gained in such positions. Simi- larly, we expect that individuals who submit papers for
publications while in graduate school will have a greater than average interest in and aptitude for research.
The COGEE survey provides information on where each respondent received his or her baccalaureate degree.
We construct a variable equaling the average SAT score from the individual’s undergraduate Alma Mater.
10
Two additional variables are included to assess the plausibility of the common perception that mathematical
ability is highly correlated with success in economics graduate programs and in the profession more generally.
9
Note that a positive value for either of these publication measures does not imply that SUBMIT equals 1, because these
articles may have been written prior to entering graduate school. Similarly, SUBMIT 5 1 does not imply a positive value for
either PREPUB or PRETOP, because not all articles submitted as a graduate student will be published prior to leaving graduate
school, if at all.
10
The survey asked respondents to report their graduate rec- ord examination scores, but a high rate of non-response for this
question keeps us from using this information. The source of the SAT data is Barron’s Guide to Colleges 1990. For non-
U.S. B.A.s we impute this variable using the average for the individual’s graduate program.
SCIENCE is a dichotomous variable equal to one for all persons with a B.S. or M.S. in mathematics, science, or
engineering, and equal to 0 otherwise. The variable MATHDIS is a self-report using a five point scale of
the level of mathematics used in the dissertation Hansen, 1991, pp. 1073–1075.
A time line reported by COGEE survey respondents allows us to observe the time it took each individual to
progress through the graduate program. The variable TTPROP measures the length of time from entering the
program until the completion of an approved dissertation proposal. We choose this measure over time-to-degree
because the latter is not independent of an individual’s experience on the job market or his first job. We expect
individuals who take longer to get to the dissertation stage will tend to be less productive after receiving
their degrees.
Some demographic variables are also included in the analysis — age at time of degree, the presence of depen-
dent children at time of degree, and gender.
11
We also have data on dissertation field as categorized according
to the JEL classification scheme.
5. Descriptive analysis
5.1. Publication patterns over time: the COGEE sample and the population
We begin our empirical analysis with a description of the publishing patterns over time for the entire 1977–78
cohort of Ph.D. economists and for the members of the COGEE sample from that cohort. While only the
COGEE data contain the respondent attribute infor- mation used in the multivariate analysis discussed in
Section 6, it is nonetheless of interest to document the pattern of early career publications for the entire popu-
lation. If nothing else, Fig. 1 provides an indication of how our sample compares to the population in terms of
total publications.
We focus on the 1977–78 cohort because doing so allows us to consider a longer time series. At the time
publications data were collected for the COGEE project, 9 years of post-Ph.D. data were available for the 1977–
78 cohort, compared with 4 years for the 1982–83
11
A number of studies have focused on gender differences in professional activities and rewards. Fish and Gibbons 1989
and Broder 1993 find that female economists publish less than their male counterparts. Ferber and Teiman 1980 and McDow-
ell and Smith 1992 find that the lower productivity of women is partially explained by the combination of the propensity for
economists to choose co-authors of the same sex and the rela- tively small number of women in the profession. Blank 1991
suggests that the gender gap is partially attributable to non- neutral practices of referees.
71 T.C. Buchmueller et al. Economics of Education Review 14 1999 65–77
Fig. 1. Average number of publications per year — all publications — for the 1977–78 population and COGEE sample. h 5
Population; j 5 COGEE sample.
cohort. Our subsequent analysis of the COGEE sample distinguishes between publications prior to and after the
year in which the individual takes the first job, rather than receives the Ph.D. It is not possible, however, to
observe the year in which each member of the population of 1977–78 Ph.D.s takes his or her first job. Thus, Fig.
1 uses the year of the Ph.D. as the benchmark.
Publications prior to the year of Ph.D. are quite rare.
12
For the population, total publications increase steadily for the first three years after receipt of the Ph.D., drop
slightly and remain fairly constant in years 4, 5, and 6, and then decline. In all post-Ph.D. years, members of the
COGEE sample publish more than the average cohort member, though the temporal patterns of publications are
quite similar.
5.2. Publications across graduate program tiers and employment sectors
The relationship among graduate training, initial job placement, and subsequent publications is complex.
Before investigating the marginal effects of factors such as early research experience and personal characteristics,
12
Because some subsequent publications were undoubtedly accepted and near publication when degrees were received, this
measure understates pre-Ph.D. research output.
it is useful to establish and analyze two stylized facts. The first is that graduates of highly ranked programs
publish more than graduates of other programs. The second is that post-Ph.D. publications are related to an
economist’s occupational setting, with economists at research universities publishing more than those in other
academic and non-academic positions.
Since we can identify the Ph.D. granting department of each member of the population, we can use the entire
population to investigate the first stylized fact. Fig. 2 describes the publications records of the entire 1977–78
cohort by graduate program tier. With some exceptions, the pattern across tiers is as expected. In each year, Tier
1 graduates have more publications than do graduates in any other tier. In most years after receiving the Ph.D.,
Tier 2 graduates publish more than Tier 3 graduates, though over the entire time period the differences
between these two tiers are small. Not surprisingly, graduates of programs in Tiers 4 and 5 have the lowest
publication rates, though the relationship between the two varies from year to year.
A similar pattern is found in our COGEE sample, as shown in the upper panel of Table 2. The figures in Table
2 differ from those in Fig. 2 in several respects. First, they are for both the 1977–78 and the 1982–83 cohorts.
Second, publications are counted over the first 6 years after starting the first job as opposed to completing the
72 T.C. Buchmueller et al. Economics of Education Review 14 1999 65–77
Fig. 2. Average number of publications by graduate program tier — all publication — for 1977–78 Ph.D. cohort population.
Table 2 Publications and first job placement by graduate department tier: COGEE sample
Tier 1 Tier 2
Tier 3 Tiers 4,5
Publications Percentage publishing 1
70.0 80.4
78.3 67.6
or more articles Total publications
3.7 4.7 3.2 3.1
3.3 3.3 1.8 2.2
Percentage publishing 1 50.0
56.7 65.2
50.0 or more in top 50
journals Total top 50 publications
1.9 2.9 1.4 1.7
1.4 1.7 0.6 1.1
Job placement percentage
distribution AcademicPh.D.
57.5 45.4
56.5 14.7
Academicother 16.3
24.7 30.4
47.1 Non-academic
26.3 29.9
13.0 38.2
N 80
97 23
34 Note: Standard deviations in parentheses.
Ph.D.. An additional minor difference is that Tiers 4 and 5 are combined because of small cell sizes.
The average number of publications is highest for recipients of Tier 1 Ph.D.s, despite the fact that Tier 1
does not have the highest percentage of graduates pub- lishing at least 1 article. Graduates of Tier 2 and 3 pro-
grams have similar publication records; for some meas- ures the Tier 2 mean is higher, for others the Tier 3 mean
is higher. Tiers 4 and 5 are lower than the others on all four publication measures reported in Table 2.
Is it possible that economists with Tier 1 Ph.D.s are more productive than others because they obtain jobs
that are conducive to greater research output? To explore this possibility, the lower panel of Table 2 presents the
cross-tabulation of employment sector by tier of Ph.D. The figures show that programs in Tiers 1 and 3 place
73 T.C. Buchmueller et al. Economics of Education Review 14 1999 65–77
Table 3 COGEE sample publications by employment sector
AcademicPh.D. Academicother
Non-Academic Percentage publishing 1 or
84.3 70.0
63.6 more articles
Total publications 4.3 4.3
2.1 2.6 2.3 3.0
Percentage publishing 1 or 67.6
45.0 34.8
more in top 50 journals Total top 50 publications
2.3 2.7 0.8 1.2
0.8 1.4 N
108 60
66 Note: Standard deviations in parentheses.
roughly 57
percent of
their graduates
in the
AcademicPh.D. sector, whereas Tier 2 programs place 45 percent. Tiers 4 and 5 have the lowest placement rate
in the AcademicPh.D. sector 15 percent and the high- est placement rate in the Non-Academic sector 38
percent.
The connections between publications and employ- ment are described in Table 3 and in Fig. 3. Ph.D. econ-
omists in the AcademicPh.D. sector publish more than their counterparts in the other two sectors. For all four
measures reported in Table 3, differences between the AcademicPh.D. sector and the other two sectors com-
bined are statistically significant at the P 5 0.01 level. The small differences in publication rates between the
Non-Academic and AcademicOther sectors are not stat- istically significant at conventional levels. Similarly, Fig.
Fig. 3. Average publications by employment sector — all publications — for 1977–78 cohort COGEE sample.
3 shows that economists in the AcademicPh.D. sector publish successively more each year through year six,
whereas the patterns for the other two sectors are more erratic. Given these patterns and our small sample size,
we define just two sectors of employment — the AcademicPh.D. sector and the other two sectors com-
bined — in the remainder of our analysis.
6. Regression results
