Two to tango? Gender differences in the decisions to publish and coauthor.
McDowell, John M. ; Singell, Larry D., Jr. ; Stater, Mark 等
I. INTRODUCTION
There is a well-developed mythology regarding the presence of
"old boy networks" and their importance in explaining gender
differences in labor market outcomes, as articulated by Saloner (1985).
Nonetheless, aside from works such as Simon and Warner (1992), there is
relatively little empirical evidence examining the impact of networks on
market outcomes, how these effects differ by gender, and whether gender
differences in network access change over time as women become more well
represented in a profession. The paucity of empirical evidence arises in
part from the difficulty of measuring the presence of such networks.
Prior work, including that of Saint-Paul (2001) and Erickson and
Jacoby (2003), has found evidence that networks facilitate the adoption
of team-oriented work practices and information sharing that increase
average worker productivity in management and professional jobs. On the
other hand, studies such as that by Marmaros and Sacerdote (2002) have
also found that women have less access to networks than their male
counterparts in both private and public sector jobs, which has been
shown to yield gender differences in job placement and other labor
market outcomes. This article considers how gender differences in
networks are manifested in a specific male-dominated profession (i.e.,
academic economists) and in a specific work-related outcome (i.e., the
decision to coauthor articles) in which access to networks is likely to
be important.
The analysis uses uniquely detailed individual and job-level data
for PhD economists included in nearly four decades of American Economic
Association (AEA) membership to examine the role of networks on the
joint decision to publish and coauthor. The unique matching process of
PhD economists between academic and nonacademic jobs and within the
hierarchy of academic departments along with the relative ease of
observing joint research provide a rare opportunity to distinguish
differential network access and measure joint production. The results
demonstrate the importance of networks in the production of research
output and that new (female) entrants into a male-dominated profession
do not have equal access to these professional networks. The results
also provide evidence that women are able to plug into networks over
time as the profession becomes more gender representative.
Our study contributes to the literature on the role of networks in
the labor market in several ways. First, the profession of academic
economist is well suited to this study, because it is made up of workers
who produce a relatively homogenous output (i.e., scholarly journal
articles) and that share a common set of job-related tasks (i.e.,
teaching, research, and service). Second, the incidence of coauthorship
is an observable outcome measure of network utilization (a phenomenon
inherently difficult to measure) in the tradition of the business
productivity literature, as found in Sabel (1993). Third, there is
extensive evidence in the literature that journal publications are
positively linked to academic salaries, as found in Siegfried and White
(1973) and Sauer (1988); that the propensity to coauthor is positively
associated with publication output, as in as found in Durden and Perri (1995) and Maske et al. (2003); that there are gender differences in
tendencies to coauthor, as shown by Ferber and Teiman (1980) and
McDowell and Smith (1992); and that there are gender differences in
professional outcomes, such as publications, salary, and promotion, as
seen in McDowell (1982), Hansen et al. (1978), Formby et al. (1993), and
Broder (1993). Cumulatively, these studies suggest that understanding
the determinants of coauthorship is important for evaluating the sources
and the extent of gender inequity in the profession.
Prior work on coauthorship behavior has analyzed patterns over time
and across disciplines. Several studies, including Hudson (1996),
McDowell and Melvin (1983), and Barnett et al. (1988), document a strong
trend toward increasing collaboration over time in economics and other
fields. McDowell and Melvin (1983) reason that this trend is due to
increasing gains to specialization and division of labor in the
profession, whereas Laband and Tollison (2000) point out the
increasingly complex quantitative nature of economic research. Hamermesh
and Oster (2002) suggest that technological advances that have lowered
the cost of long-distance communication have allowed economists to reap
consumption benefits from collaborative work.
There are several major ways this article builds on and extends
these prior studies of coauthorship. First, the data utilized contain a
richer set of observed attributes than available in prior studies, such
as Buchmueller et al. (1999), and in particular, include information on
the institutions where individual economists received their doctorates
and where they currently work. This enables us to construct observable
measures of the extent and quality of potential networks available to
academic economists. These measures are useful for assessing the impact
of network access, formation, and utilization on the publication and
coauthorship behavior of male and female economists. Therefore, the
detailed data used in this study enable us to gain insight into the
extent of gender differences in networks and resulting differences in
publishing and coauthorship, both within institutions and over time.
Second, the approach taken herein is to treat publication and
coauthorship as joint decisions in the sense that coauthorship can only
be observed among those economists who have published. In effect,
considering coauthorship behavior in isolation subjects a study to
sample selection bias if unobservable attributes that affect publication
behavior also influence coauthorship. Thus, this article estimates the
effect of observed attributes on the likelihood of coauthorship,
conditioned on unobserved attributes that determine publication and are
correlated with coauthorship (e.g., unobserved ability). This approach
has not been previously taken in the literature, and the present results
suggest that failure to account for the joint nature of the publication
and coauthorship decision can yield misleading results, particularly
with regard to gender.
Studies of gender differences in coauthorship suggest that women
tend to coauthor less than men, in part due to the propensity of
economists to coauthor with individuals of the same gender. Thus, in a
male-dominated discipline, women appear to be disadvantaged in forming
networks of potential coauthors. However, a key issue that these studies
do not address is whether the observed lower propensity of women to
coauthor can be explained to a large extent by their lower propensity to
publish, which has been documented by Hansen et al. (1978) as well as
Barbezat (1987). If so, then the disparities in promotions and salary
that women experience in the profession may reflect publishing
differences that arise from sources other than the ability to form
adequate networks of coauthors in a male-dominated profession. With a
focus on institutions where research productivity matters most, this
article extends prior work by looking at overall gender differences as
well as gender differences according to the quality and dynamics of
networks.
The base results suggest that there are no gender differences in
coauthorship conditioned on the selected sample of economists who
publish in a broad-based set of journals. However, the results suggest
that women's coauthorship opportunities differ from their male
counterparts in top departments and when a narrower set of high-quality
journals are considered, suggesting gender differences in networks.
Moreover, an Oaxaca-type decomposition of the bivariate publication and
coauthorship probabilities also shows that men derive a larger
publication benefit from coauthorship than women, which is due both to
gender differences in attributes as well as the return to those
attributes. Thus the role that networks play in research appears to have
differed for male and female economists, but time interactions also
suggest that significant differences by gender in both publication and
coauthorship tendencies have disappeared for the most recent cohort of
economists.
II. EMPIRICAL MODEL
The decisions to publish and/or coauthor may arise simultaneously
as two or more individuals collectively formulate an idea or
sequentially if a researcher decides to publish and then finds that he
or she requires collaboration to complete a project. In either case,
these two decisions are likely to be correlated because they depend on
many of the same individual, institutional, and labor market attributes.
Moreover, the decision to coauthor is observed only for those persons
who decide to and are capable of publishing. For simplicity, the
decisions to publish and coauthor are modeled as discrete outcomes,
where coauthorship is observed only for a select pool of economists who
publish.
Specifically, a random utility approach is adopted where an
individual i publishes and/or coauthors in period j if the utility of
the decision exceeds the utility of the next best opportunity. Although
the net utility from these decisions is not observed, the decisions to
publish (P) and coauthor (C) are observed and are modeled as linear
index functions:
(1a) [P.sub.ij] = [alpha] x [X.sup.P.sub.ij] +
[[epsilon].sup.P.sub.ij]
[P.sub.ij] = 1 if publish; 0 if not;
(1b) [C.sub.ij] = [beta] x [X.sup.C.sub.ij] +
[[epsilon].sup.C.sub.ij]
[C.sub.ij] = 1 if coauthor and
[P.sub.ij] = 1; 0 if not,
where the net utility of publishing and coauthoring by person i at
time j depends on observed individual and institutional attributes,
[X.sup.P.sub.ij] and [X.sup.C.sub.ij], and unobservables,
[[epsilon].sup.P.sub.ij] and [[epsilon].sup.C.sub.ij], which are assumed
to be distributed bivariate normal, [0,0,1,1,[rho]].
The coauthor decision, [C.sub.ij], is observed only if the person
published, [P.sub.ij] = 1, which can be estimated using the bivariate
log-likelihood function with sample selection proposed by Meng and
Schmidt (1985):
(2) lnL([alpha], [beta], [rho])
= [N.summation over i=1][P.sub.ij][C.sub.ij]ln[PHI] ([alpha] x
[X.sup.P.sub.ij], [beta] x [X.sup.C.sub.ij]; [rho]) + [C.sub.ij](1 -
[P.sub.ij])ln[F([alpha] x [X.sup.P.sub.ij] - [PHI]([alpha] x
[X.sup.P.sub.ij], [beta] x [X.sup.C.sub.ij]; [rho]) + (1 -
[C.sub.ij])ln[1 - F([alpha] x [X.sup.P.sub.ij])],
where [PHI] and F, respectively, denote the bivariate standard
normal cumulative density function and the univariate standard normal
cumulative density function for the errors in (1a) and (1b). The model
is identified through the nonlinearity of (2) and because the
differential role of networking in the two processes leads elements of
[X.sup.C.sub.ij] and [X.sup.P.sub.ij] to differ, as discussed in the
data section.
Estimating the coauthorship model jointly with the publishing
decision offers efficiency gains by explicitly modeling the correlation
[rho] between the error terms in (1a) with (1b). More important, the
empirical model uses the unobserved attributes that determine the
publishing decision that are likely correlated with the unobserved
attributes that determine coauthorship, to condition the marginal
responsiveness of the decision to coauthor on the observed attributes.
Thus, the censored model estimates the marginal impact of the observed
attributes, such as gender, on coauthorship conditioned on the
unobserved attributes, such as motivation or ability, that enter into
the error term of the publishing model. It follows that the estimated
effects of observed attributes (e.g., gender) on the decision to
coauthor, though based on data for AEA members, may be generalized to
broader populations that could have different propensities to publish.
III. DATA
The data used to estimate equation (2) are primarily drawn from the
1964, 1974, 1985, 1989, 1993, and 1997 AEA directories, where the sample
includes PhD economists who work in a job located in the United States.
(1) These data provide a uniquely detailed set of contemporaneous attributes of AEA members, including their current job placement, title,
and areas of interest, but provide only limited information regarding
past career history other than their degree-granting institution.
Nonetheless, whereas research output over a career depends on a host of
time-varying factors (e.g., the number and type of past jobs) that are
not observed in the AEA directories, it is reasonable to expect that
research produced over a short interval of time depends on the current
researcher attributes available in the data, such as job placement and
academic rank, that reflect previous work-related performance. Thus, the
AEA data are supplemented with information related to contemporaneous
publication activity gathered from various issues of the AEA Index of
Economic Articles for the membership years between 1964 and 1993 and
from EconLit for the 1997 AEA directories. Specifically, the decision to
publish (coauthor) is measured by a binary variable that equals 1 if an
individual is observed to publish (coauthor) in the year of the
cross-section or the subsequent year (i.e., 1964-65, 1974-75, 1985-86,
1989-90, 1993-94, 1997-98). (2)
The publication and coauthorship models share a common set of
explanatory variables with the exception of a single exclusion
restriction for each model. There are several categories for the
explanatory variables that include individual-, institution-, time-, and
market-specific controls. The individual-specific controls include
life-cycle measures along with a control for gender. The publication
model includes both age and a quadratic in post-PhD experience, thus
allowing human-capital depreciation and accumulation, respectively, to
vary over a career. In contrast, although the coauthorship model also
includes the experience measures that permit network formation to vary
nonlinearly over a career, the coauthorship equation does not explicitly
model depreciation in network utilization due to an economist's
age. In addition, a binary variable that equals 1 for female economists
is included and is interacted with network and market measures in
several specifications to examine whether women's coauthorship and
publishing opportunities and outcomes systematically differ from their
male counterparts.
Institution-specific controls include two qualitative measures of
the economist's degree-granting institution and current job. A
contemporaneous measure of PhD and current job quality is derived from
the quality-adjusted average number of publications for in-sample
economists from a given PhD institution or current job and net of the
economist's own contribution. (3) The qualitative measures are
included in both the publication and coauthorship equations because
economists who originate (place) in a more publishing-oriented PhD
program Gob) may be more likely to publish but less dependent on
coauthors. The contemporaneous average propensity to coauthor over a
two-year window around the directory date for economists from a given
PhD institution or current job, net of the economist's own
coauthorship decisions, is also included in the coauthorship equation to
reflect the institutional culture regarding coauthorship. However, the
variables controlling for coauthorship within PhD cohorts and
coauthorship within current jobs are excluded from the publication
equation because coauthorship is of secondary importance to the
propensity to publish after conditioning on institutional quality that
directly determines the propensity to publish and coauthor. (4)
The institutional measures also include several descriptive
measures of the economist's degree-granting institution and current
job. The cohort size of an economist's PhD class is measured by the
number of in-sample economists from a particular PhD institution for a
given directory date and over the previous five years. This cohort
measure is used in both models to proxy for a natural network within the
profession that arises from a shared common graduate school experience.
For academic jobs, access to a well-established stable network is
measured by a binary variable that takes on the value of 1 for those 14
institutions that have been ranked in the top 20 by four publication
rankings published in the four decades of the sample from the 1960s
through the 1990s. (5) In addition, several binary variables are
included in both the publication and coauthorship models that indicate
whether the academic economist is an administrator or nontenured lecturer or has placed in an agricultural economics, business, or other
department as opposed to an economics department, because these
academics may have different publication expectations and opportunities
to coauthor than regular economics faculty. Finally, three binary
variables are included that indicate a job in government, business, or
other nonacademic institutions, which might also indicate different
incentives or opportunities to publish and coauthor.
Several variables are included to measure market conditions. The
cohort size of market entrants, which is measured by the total number of
in-sample new PhDs in a given PhD year and the five previous years, is
used to proxy for the number of direct competitors for journal space. As
such, more market entrants should be negatively related to the
probability of publishing. However, a greater number of recently minted
PhDs might also increase the number of potential similarly situated coauthors, which could increase the probability of coauthoring. Finally,
the model includes five binary variables that equal 1 for the directory
dates 1974, 1985, 1989, 1993, and 1997, where 1964 is the excluded date.
These binary variables are included to examine whether there is any
pattern in the tendency to publish or coauthor over time that might
reflect changes in the relative valuation of these two activities within
the economics profession.
Descriptive statistics for the full sample and disaggregated by
gender are presented in Table 1. The means indicate that men are both
more likely to publish and coauthor than their female counterparts. Some
of these gender differences in the publication and coauthorship
tendencies may reflect the fact that female economists are younger and
have less experience than male economists. However, the descriptive
statistics also show that women tend to have different opportunities
than men. For example, female economists tend to place in jobs that have
a lower contemporaneous publishing productivity and are less likely to
place in top departments that have a historically high reputation. Women
also appear to more frequently place in other-related departments
relative to economics departments and in "other" nonacademic
jobs, in general. Finally, the descriptive statistics indicate that
female economists are relatively overrepresented in the more recent
sample years, which indicates that they are relatively new entrants into
the profession. Thus, although women appear to differ in both the
average propensity to publish and coauthor, the empirical analysis
examines whether such differences remain after conditioning on the
observed differences in attributes and accounting for the correlation in
the unobserved attributes related to the probability of publishing and
coauthoring.
IV. EMPIRICAL RESULTS
All AEA Members
For the total sample of AEA members, Table 2 presents the estimated
coefficients from the bivariate probit model of publication and
coauthorship, along with univariate probit results (for comparison), in
which the publication and coauthorship decisions are estimated
separately. (6) For the bivariate probit model, most of the coefficients
are significant at traditional levels including the coefficient on the
correlation coefficient ([rho]), which indicates that the decisions to
publish and coauthor are jointly determined. The negative coefficient on
9 indicates that the unobserved heterogeneity in the publication
decision (e.g., unobserved ability) is inversely related to those
unobserved factors that determine coauthorship, which suggests that
economists who are relatively inclined to publish are less dependent on
coauthors. This result supports prior findings, such as those of
McDowell and Melvin (1983), that coauthored work occurs more frequently
among relatively specialized economists who require coauthors to
publish. In addition, the sign and magnitude of the bivariate
coefficients for coauthorship frequently differ from the univariate
model, which indicates that it is important to condition for the
correlation in the unobserved heterogeneity across the joint decisions
to publish and coauthor.
The coefficients on experience and its quadratic term indicate that
the publishing and coauthorship probabilities increase at a decreasing
rate over a career. In particular, the magnitudes of the coefficients
suggest that the probability of coauthorship increases over the first 19
years of a career (e.g., to the age of 49 for the average economist),
whereas the probability of publishing increases with experience
throughout a career (e.g., to the age of 70 for the average economist).
Thus human capital and network formation appear to improve academic
productivity and collaboration, although coauthorship networks only
appear to yield more joint work during the most productive years of an
academic's career. Moreover, the coefficient on age in the
publication equation indicates that older economists tend to publish
less, conditioning on experience, indicating that depreciation of
skills, reductions in the incentives to publish over a career (e.g., the
tenure process), or increasing opportunity costs of publishing versus
alternative activities (e.g., administrative responsibilities) yield
lower research output. The joint effect of experience and age suggest
that the publication probability declines throughout a career.
The coefficients on the contemporaneous quality measures of the
economist's degree-granting institution and current job placement
have opposite signs in the publishing and coauthorship equations. In
particular, PhD institution and current job placement quality are
positive and significant in the publishing equation, indicating that
economists who originate or place in higher-quality departments are more
likely to publish. However, the results also indicate that conditioned
on publishing, both the PhD and current job quality are negatively
related to the probability of coauthoring, which suggests either that
more able economists are less dependent on coauthors or that economists
who originate from (or place in) more publishing-oriented institutions
have reward structures that provide greater incentives to produce
single-authored work. Indeed, Sauer (1988) finds evidence that
coauthored articles are discounted most heavily by top research
departments. In fact, the coefficients on the variables that measure the
contemporaneous coauthorship activity within the PhD cohort or within
the current job suggest that economists coauthor more if they originate
from or place in institutions where their colleagues are observed to
more frequently collaborate.
The results for the quality measures also highlight the importance
of estimating the coauthorship decision jointly with the publication
decision. In particular, counter to the bivariate probit results, the
univariate probit estimates indicate that economists who originate or
place in high-quality departments are more likely to coauthor. This
difference likely reflects the fact that qualitative differences among
economists affect coauthorship through two offsetting channels.
Specifically, more able economists (1) coauthor more because they
publish more, but (2) coauthor less because are they are less dependent
on coauthors. The positive sign for the quality measures in the
univariate model suggests that the impact of (1) dominates (2).
The variable that measures the number of PhDs from the
economist's PhD institution at a particular point in time is
positive and significant in the publication model but negative and
significant in the coauthorship equation. These opposing signs may
indicate that the number of institution-specific PhDs who are AEA
members is another dimension of PhD quality, which improves the
probability of publishing and reduces the dependence on coauthors. In
the publishing equation, the positive sign of the coefficient on number
of PhDs is consistent with a more developed network in the profession
that results from a shared experience. However, the negative sign for
the coefficient on the number of PhDs in the coauthorship equation is
counter to the network hypothesis, because networks might also be
expected to facilitate coauthorship. Alternatively, the coefficients on
the variable indicating a placement in a historically top-rated
department suggest that having access to a network of high-quality
colleagues significantly improves an economist's probability of
publishing and coauthoring, which supports the hypothesis that networks
improve productivity.
The results also indicate that the type of job matters for the
decision to publish and coauthor. Specifically, academic economists who
are lecturers or administrators are significantly less likely to
publish, reflecting differences in the publication incentives and
publication-related productivity for these jobs. However, conditioned on
publishing, administrators are significantly more likely to coauthor,
suggesting that the duties of academic economists who are drawn into
administration require them to rely relatively more on collaborative
activities to publish. The bivariate probit results also indicate that
although AEA members in business and other related departments are
significantly less likely to publish in economics journals, they do not
appear to coauthor less given that they publish less. In contrast,
whereas economists who place outside of academia (i.e., business,
government, or other sectors) also are predicted to be significantly
less likely to publish, they are significantly more likely to
collaborate conditioned on publishing. Thus nonacademic institutions
appear to place less emphasis on publishing, while at the same time they
may encourage (or at least not discount) collaborative publications.
The empirical findings also suggest some broad market forces or
trends in the decision to publish and coauthor. In particular, the
coefficient on cohort size of market entrants is significantly negative
in the publication equation, suggesting that increases in the number of
potential competitors for journal space reduce the probability of
publishing, whereas it is significantly positive in the coauthorship
equation, suggesting that it increases the potential number of
coauthors. The sign and magnitude of the coefficients on the
directory-year binary variables also indicate that the probability of
publishing and coauthorship has significantly increased over time, which
most likely reflects the increasing emphasis on research within the
profession, particularly at institutions that have not historically
required academic scholarship.
Finally, the results indicate that conditioned on placement, gender
is significantly related to publication output. Specifically, consistent
with the work of Johnson and Stafford (1974), female economists are
predicted to be significantly less likely to publish than their male
counterparts at comparable institutions. It is noteworthy that, whereas
the univariate probit results predict that women are also significantly
less likely to coauthor than men, the bivariate results indicate no
gender differences in the probability of coauthoring conditioned on
publishing. Thus, the results suggest that gender differences in
coauthorship within the profession, which have also been documented by
McDowell and Smith (1992), appear to be due to the fact that women are
less likely to publish than comparably placed men and not because they
have different opportunities to coauthor. However, as discussed by
Kolpin and Singell (1996), women face relatively poor opportunities in
academic institutions and, in particular, at the best academic
institutions, where networks and publishing are likely to matter most.
Therefore, the subsequent analyses focus on degree-granting institutions
and publications in the most cited journals, where networks may be
relatively ubiquitous and therefore sensitive to the growing
representation of women in the profession over time.
All PhD Granting Institutions
Nonnteractive Specifications. Table 3 replicates the specification
presented in Table 2, restricting the sample to the 7,048 academic
economists who place at degree-granting institutions. In the results
presented in Table 2, publication data have not been adjusted for
quality (i.e., any journal research output enumerated in the respective
volumes of the AEA Index of Economic Articles or EconLit is counted as a
publication), and therefore for a more direct comparison across samples,
we first consider the findings in Table 3 that relate to the results
without the quality adjustment. Overall, the results appear to be quite
robust across these two different samples. Although some coefficients on
the explanatory variables become insignificant in the smaller sample of
PhD-granting institutions, none of the coefficients that are significant
in the previous analysis experience a change in sign that is
significant, and most of the coefficients remain significant at
traditional levels. In particular, although female economists publish
significantly less than their male counterparts, they exhibit no
significant differences
in the observed propensity to coauthor, conditioned on the decision
to publish. Thus gender differences in the probability of placing in
PhD-granting economics departments, as documented by McMillen and
Singell (1994), do not appear to explain the observed research pattern
among male and female faculty.
The last two columns in Table 3 provide findings for the sample of
degree-granting institutions when the publication data are adjusted for
quality (i.e., a publication record is counted only if it is of high
quality).7 A comparison of the results with and without quality
adjustments reveal three particularly noteworthy differences. First,
with the quality-adjusted data, the coefficient on Female is
insignificant in both the publication and coauthorship equation.
Therefore, there are no apparent gender differences in the tendency to
coauthor in either a broad-based or high-quality set of journals. On the
other hand, although female economists are less likely to publish in a
broad set of journals, they are no less likely than male economists to
publish in the leading journals in economics. This evidence supports the
work of Ginther and Kahn (2004), which finds that women tend to produce
the same number of high-quality publications as their male counterparts
but tend to produce fewer lower-quality publications.
In addition, publication trends over time differ depending on
whether publications are adjusted for quality. For instance, among our
sampled AEA members, publications have generally (i.e., without quality
adjustments) increased over time, but publications adjusted for quality
have not done so. In fact, the coefficients on the time dummies are
generally negative (significantly so in 1985 and 1989), which may
reflect that journal quality measures adjust with a lag and that growth
in the number of PhD economists has made it relatively more difficult to
publish in the fixed set of select journals. Moreover, concerning
coauthorship, although the propensity to coauthor has increased over
time within both quality-adjusted and unadjusted articles, the increase
appears to be most pronounced within the quality-adjusted publications.
Thus, the general rise in publication and collaborative activity may
reflect the growth in more specialized journal outlets, which has
increased demand for specialized research skills and enhanced the
premium associated with coauthorship.
Finally, the correlation coefficient (p) continues to be negative
in the quality-adjusted specification, but unlike in the unadjusted
specification, it is now insignificant. This
result suggests that those unobserved attributes that raise the
probability of publishing in top-tier journals do not necessarily lower
the probability of coauthorship. Publication in a high-quality journal
is itself an indicator of ability (observed and unobserved). Thus the
decline in the magnitude and significance of 9 in the quality-adjusted
specification likely reflects a reduction in the level of unobserved
publishing ability that is inversely correlated with an economist's
dependence on coauthors and, thus, the decision to coauthor.
Interactive Specifications. If networks take time to establish and
the quality of networks varies across jobs, then women's
opportunities to collaborate may have changed as their representation in
the profession has increased, particularly at those departments where
there is access to high-quality coauthors. Table 4 provides the results
for a specification that examines whether the probabilities of
coauthorship and publishing differ for women over time and/or at top
departments that are likely to have the most comprehensive and
well-established networks. For brevity, only the coefficients on gender,
top department, time, and their respective interactions are presented,
because the qualitative conclusions for the excluded variables do not
differ from those in the previous specifications.
Consider first the results in Table 4, columns one and two, which
pertain to the without-quality-adjustment estimations. Although there
are no significant gender differences in the temporal trend in
coauthoring conditioned on publishing, the coefficients on the
female-time interaction terms do indicate that gender differences in the
probability of publishing have changed significantly over time.
Specifically, in terms of the probability of publishing, the estimated
effects indicate that female economists in 1964 (when women made up
roughly 3% of the profession) were not significantly different from
their male counterparts at comparable institutions. However, there was a
large influx of women into the profession starting in the early 1970s,
which corresponds with female economists having a significantly lower
publishing probability than male economists in 1974. The gender
difference in the publishing probability peaked in 1985 and thereafter
declined in magnitude, with the significant lower publishing probability
of female economists disappearing by 1993. Thus the relative research
productivity of female economists has varied over time in a pattern
suggesting that an underrepresented group's surge in entry into a
profession may be accompanied by a lag in productivity before that
group's members develop the professional capital necessary to be as
productive as those who are well established in the profession.
The coefficient on the interaction of gender with placement in a
top department is negative but insignificant in the publication
equation, indicating that women who place in top departments do not
publish less than their male colleagues net of gender-specific trends in
the probability of publishing. However, in the coauthorship equation,
the coefficient on the top department and gender interaction is negative
and highly significant. Therefore, although women outside the top
departments do not differ significantly from men in terms of the
probability of coauthorship (although the coefficient is positive),
female economists who place in the top departments are significantly
less likely to coauthor. On the other hand, the estimated effect of
being in a top department is positive and significant, indicating that
men are more likely to coauthor when they place in the best schools,
holding the contemporaneous measures of quality constant. Therefore,
male economists appear to benefit from the network of high-quality
coauthors at top departments. However, because the combined effects of
top department and its interaction with gender are not jointly
significant, women do not likewise benefit from a top placement in terms
of coauthorship opportunities. Thus when it comes to publishing in a
broad-based set of journals, it appears that women who place in the
historically best academic departments either do not have access to or
are unable to take advantage of networks to the same extent as men who
place in these departments.
The publication results for the quality-adjusted interactive
specification (column 3) differ from those for the unadjusted data
(column 1). Specifically, the quality-adjusted findings indicate that
female economists observed in 1964 are significantly more productive
than their comparably placed male colleagues. This finding may reflect
that the very early entrants from a particular group into a profession
must be relatively able to compensate for any possible disadvantages
that may be associated with being from an underrepresented group.
However, although the female-time interactions are not significant
(except for 1985), the negative coefficients on these interaction
controls suggest that the publishing propensity of female economists has
become more similar to their male counterparts over time. On the other
hand, the interaction term of female with top department is negative and
significant and this result, combined with the significant positive
coefficient on female, suggest that early female entrants published more
than their male colleagues, but only those female economists who placed
outside the top departments. This evidence is consistent with prior
findings, such as those of Kolpin and Singell (1996), that women were
initially under-placed in the profession and produced more research than
their comparably placed male colleagues at lower-ranked departments.
With respect to coauthorship, the quality-adjusted data reveal
results that are strikingly different from those found with the
unadjusted data. For instance, after quality adjustments, the estimated
effect of being in a top department is insignificant and does not differ
by gender. Therefore, with respect to the production of high-quality
articles, neither male nor female economists appear to benefit from a
potential collaboration network of high quality coauthors at top
departments, or if they do, this is offset by an incentive structure
that emphasizes more single-authored work on high-quality publications.
Although the findings do not provide evidence indicating that women
are faced with any disadvantage within top departments in terms of
coauthorship opportunities on high-quality articles, there are
significant gender differences in coauthorship. It is noteworthy,
however, that the extent of such gender differences has diminished over
time. Specifically, female economists in 1964 had a significantly higher
probability of coauthoring conditioned on publishing, which suggests
either that they were more dependent on coauthors or that they had
greater relative incentive to produce coauthored work than did males.
Thereafter, in the production of high-quality articles, female
economists generally became less reliant on collaboration and, since
around 1985, have become roughly equal to their male counterparts in
terms of their propensity to collaborate.
The observed pattern of gender differences in coauthorship is
consistent with a number of hypotheses that cannot be distinguished with
these data despite the relatively detailed controls. For example, if
women were initially underplaced within the hierarchy of academic jobs
as suggested by McMillen and Singell (1994) and Ginther and Kahn (2004),
then they might tend to publish relatively more in high-quality versus a
broader set of journals. Moreover, they might also tend to coauthor
more, both because they would be relatively able coauthors and because
lower-ranked departments may have reward structures that place less
emphasis on solo-authored work. However, as women's placement in
the hierarchy of jobs improved, their publishing and coauthoring
tendencies moved toward those of their male colleagues. Alternatively,
Ferber and Teiman (1980) find evidence indicating that articles with at
least one female coauthor had a higher acceptance rate for manuscripts.
This may reflect that women initially needed to plug into the
male-dominated network to be successful and establish themselves in the
profession or perhaps to overcome a perceived bias. This effect would
tend to diminish as women become a larger fraction of the profession and
more gender-neutral networks are established. Nonetheless, in the end,
such hypotheses are purely speculative.
Although it is not possible to directly distinguish between these
various competing hypotheses, the next section examines how the
differences in the impact of coauthorship on the publishing decision can
be decomposed into the effect of gender-differences in attributes
(observed or unobserved) versus gender differences in the return to
these attributes. However, before doing so, it is important to emphasize
that several alternative specifications (not presented) indicate that
these observed gender differences in coauthorship are not an artifact of
the exclusion restrictions and are robust to alternative identification
strategies. On the other hand, the sign and magnitude of the correlation
coefficient (P) are sensitive to both the specification and the
identification strategy and indicate, as expected, that the correlation
of the errors in the publication and coauthorship equation depend on the
explanatory variables that are assumed to explain these research
decisions.
Gender Decomposition of Coauthorship's Contribution to
Publication
The observed decision to coauthor is itself a measure of a network
that is expected to enhance research output. The prior findings,
although suggesting possible gender differences in the use of networks
over time and in better departments, indicate relatively few differences
by gender in coauthorship behavior controlling for observed attributes
and conditioned on the correlation of unobserved attributes in the
publishing and coauthorship models. However, as Ginther and Kahn (2004)
point out, the attributes of male and female economists often differ
systematically, and the return to these attributes for research differs
by gender. Thus, it is reasonable to ask whether networks facilitate
research production differently by gender based on observed and
unobserved differences in attributes or the productive return to these
attributes.
To examine this issue, separate gender-specific bivariate probit
models are estimated using the base specifications in Table 3, excluding
the gender dummy. The gender-specific coefficient estimates are used to
calculate the difference between the bivariate probability of both
publishing and coauthoring (i.e., publish = 1 and coauthor = 1) and the
bivariate probability of publishing but not coauthoring (i.e., publish =
1 and coauthor = 0) for the average male and female economist. The
difference in the joint probability of publishing with a coauthor versus
without a coauthor provides a measure of the contribution made by
coauthorship to research production, which is now allowed to differ by
gender.
For men, coauthorship's contribution to the probability of
publishing can be calculated as [DELTA][[PHI].sub.M] =
[PHI][[X.sup.P.sub.M]
[[beta].sup.P.sub.M],[X.sup.C.sub.M][[beta].sup.C.sub.M], [[rho].sub.M]]
- [PHI] [-[X.sup.P.sub.M][[beta].sup.P.sub.M],[X.sup.C.sub.M]
[[beta].sup.C.sub.M], -[[rho].sub.M]] where [PHI] is the bivariate
probability distribution, [X.sup.P.sub.M] and [X.sup.C.sub.M] are the
average male attributes, [[beta].sup.P.sub.M] and [[beta].sup.C.sub.M]
are the estimated parameters from the bivariate probit model for men,
and [[rho].sub.M] is the estimated correlation coefficient. A discussion
of this result appears in Greene (2003, p. 716). Likewise,
coauthorship's contribution to the probability of publishing for
female economists (i.e., [DELTA][[PHI].sub.F]) is calculated using mean
female attributes and the estimated parameters from the bivariate probit
model for women. It follows that the gender difference in contribution
of coauthors to the probability of publishing can be calculated as
[DELTA][[PHI].sub.MF] = [DELTA][[PHI].sub.M] - [DELTA][[PHI].sub.F].
The resulting gender decompositions of the probabilities are
summarized in Table 5. (8) For males, coauthorship's contribution
to the probability of publishing ([DELTA][[PHI].sub.M]) equals 29.5%
using the nonquality-adjusted measures and 32.9% using the
quality-adjusted measures, whereas [DELTA][[PHI].sub.F] equals 10.9% and
20.8%, respectively. It follows that [DELTA][[PHI].sub.MF] equals 18.6%
for the nonquality-adjusted specifications and 12.1% for the
quality-adjusted specifications. Thus, the findings suggest that the
publishing probability is enhanced by coauthorship relatively more for
male versus female economists and that this advantage is smaller for
publications in higher-quality journals.
This observed gender difference in the publishing benefit from
coauthorship may arise because male and female economists have different
attributes (i.e., [X.sup.P] and [X.sup.C]), receive a different
productive return to those attributes (i.e., [[beta].sup.P] and
[[beta].sup.C]), or because the correlation of the unobserved attributes
that jointly determine the decision to publish and coauthor (i.e.,
[rho]) differs by gender. Thus, it is easy to demonstrate that
[DELTA][[PHI].sub.MF] can be decomposed into male and female differences
in attributes ([DELTA][[PHI].sup.X.sub.MF]), estimated coefficients
([DELTA][[PHI].sup.[beta]sub.MF]), and correlation coefficients
([DELTA][[PHI].sup.[rho].sub.MF]), or [DELTA][[PHI].sub.MF] =
[DELTA][[PHI].sup.X.sub.MF] + [DELTA] [[PHI].sup.[beta].sub.MF] +
[DELTA][[PHI].sup.rho].sub.MF].
The decomposition of [DELTA][[PHI].sub.MF] using the
nonquality-adjusted parameter estimates indicate that
[DELTA][[PHI].sup.X.sub.MF] equals 12.1%, [DELTA]
[[PHI].sup.[beta].sub.MF] equals 10.2%, and
[DELTA][[PHI].sup.[rho].sub.MF] equals -3.7%, whereas these estimates
using the quality-adjusted parameters are 7.0%, 20.7%, and -15.6%,
respectively. Thus, using both nonquality- and quality-adjusted
parameters, the decompositions broadly show that gender differences in
both the observed attributes and the productive return to those
attributes contribute to the predicted publication advantage from
coauthorship for male versus female economists, whereas the variation
due to 0 actually reduces this male advantage.
Thus, overall the decompositions suggest that whereas female
economists do not generally coauthor differently than their male
counterparts conditioned on their attributes, there are gender
differences in the benefits from coauthorship that arise from the fact
that men and women differ in their observed and unobserved attributes as
well as the return to those attributes. Several hypotheses might account
for the apparent male publishing advantage from coauthorship and the
relative importance of the parameters, including discrimination in
promotion and hiring of women that heightens the relative importance of
publishing in the best journals for women or simply a general preference
by researchers to network and collaborate with persons of the same
gender in a male-dominated profession. Nonetheless, the information
requirements to test these hypotheses are beyond even these uniquely
detailed data.
VI. CONCLUSIONS
This article develops the first empirical model of the joint
decision to publish and coauthor. Concerning a broad set of journals,
although the analysis finds that female economists are significantly
less likely to publish than their male counterparts at comparable
institutions, the extent to which female economists have a lower
probability of publishing has varied substantially over time. Indeed, by
1993, the significant lower publishing probability of female economists
has disappeared. The analysis also finds that after controlling for
their lower observed probability of publishing, female economists are no
less likely to coauthor than their male colleagues. Moreover, any
apparent trend in gender-specific differences in the probability of
coauthorship appears to be due to temporal differences in the
probability that female economists publish relative to comparatively
placed male colleagues.
Specifications that interact gender with placement in top
departments indicate that women who place in top departments do not
publish less than their male colleagues using a broad-based measure of
publications. Nonetheless, women in top departments are found to engage
in less collaborative activity, indicating that the significant gender
difference in the probability of coauthorship seems to be attributable
to those women who place in the best academic jobs. On the other hand,
when the definition of publication is narrowed to include only
higher-quality journals, women throughout the profession (in top
departments and elsewhere) are found to publish comparably to their male
colleagues but to coauthor relatively more than men. However, the
significant gender differences in coauthorship in high-quality journals
is found to disappear over time. The combined results suggest that
initial female entrants into the profession produced a lower volume but
more quality-oriented mix of publications and that women were more
likely to coauthor if targeting better journals or if placed in less
research-oriented departments. Overall, the results suggest that
networks impact the joint decision to publish and coauthor, that these
network effects differ by gender, and that gender differences in network
access disappear over time as women become more well represented in a
profession.
Gender differences in networks could help explain a number of other
observed gender differences in opportunities among economists, including
inferior job placement, lower research output, and a smaller likelihood
of promotion for female versus male economists. Indeed, an Oaxaca-type
decomposition of the bivariate publication and coauthorship
probabilities suggests that women earn a lower publication benefit from
coauthorship than men. This gender difference arises equally from
differences in attributes and the return to those attributes for male
versus female economists.
Overall, these findings may suggest that network formation tends to
transition toward gender equality relatively slowly in a male-dominated
occupation, which supports the theoretical work of Kolpin and Singell
(1997) that suggests formal and informal organizations within the labor
market can significantly affect the relative opportunities of women for
a given occupation. Thus, although prior work suggests that women have
made substantial progress toward equality in the economics profession,
how professional interactions and resulting networks affect labor market
outcomes and the role institutions play in shaping those interactions
requires further study.
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(1.) McDowell et al. (2001) include a detailed explanation of the
data and their construction. The current data have been extended and
include economists who are AEA members in the years 1964, 1974, 1985,
1989, 1993, and 1997 (as identified in the respective AEA directories),
as well as all female AEA members who had a PhD and were working in a
job located in the United States, or 5,098 female economists.
(2.) The binary approach simplifies the analysis by avoiding the
need to model correlations across multiple publication and coauthorship
decisions. Even so, for the vast majority of economists, the two-year
interval is sufficiently short that the publication decision is truly
binary. Specifically, in the sample, the modal number of publications
among all AEA economists is 0, whereas the modal number of publications
among AEA economists who publish is 1. Nevertheless, our analysis does
not exploit all the information potentially available in the data, and
our results may not be fully applicable to exceptional academics who
annually publish multiple papers throughout a career.
(3.) This variable is measured over the two-year window around the
directory date. Publications are weighted by a journal quality measure,
which is accounted for by using the SSCI Journal Citation Reports Impact
Factor as a weight. For PhD institutions, the average quality is
institution-specific, whereas these average measures are calculated
across all non-PhD-institutions, business, government, or nonprofit placements because each specific placement has relatively few individual
observations.
(4.) Neither coauthorship variable is significant when included in
a bivariate or univariate probit model for the decision to publish.
Again, the coauthorship measure is institution-specific for PhD
institutions, whereas these average measures are calculated across all
non-PhD-granting, business, government, or nonprofit placements because
each has relatively few individual observations.
(5.) The rankings for the 1960s were drawn from Cartter (1966), the
1970s from Graves et al. (1982), for the 1980s from Scott and Mitias
(1996), and for the 1990s from Kalaitzidakis et al. (1999). Departments
that have demonstrated publication excellence over 40 years have
consistently hired and maintained a faculty who are among the best in
their field, and who are likely to be superior coauthors in addition to
being relatively well represented in professional networks (including
editor positions at journals). Thus, access to professional networks,
although available to some degree for most scholars, is likely to be
relatively greater and more immediate for faculty who place in
departments that demonstrate consistent excellence.
(6.) The bivariate probit model is estimated assuming that
observations of the same individual over time are correlated, whereas
there is no correlation between different individuals. Accounting for
this individual-specific clustering generally increases the standard
errors relative to a standard bivariate probit model with sample
selection, reflecting the fact that there are fewer independent
observations than the full 17,348 person-year observations would
suggest.
(7.) Publications are weighted by a journal quality measure, which
uses the SSCI Journal Citation Reports Impact Factor as a weight. In the
quality-adjusted data, a publication count is recorded only if it has an
average Impact Factor of 1.0 or higher, which is the minimum Impact
Factor for the top 66 rated journals in our sample.
(8.) The gender-specific bivariate probit models using both the
quality- and nonquality-adjusted coauthorship and publication measures
are available from authors upon request.
ABBREVIATION
AEA: American Economic Association
JOHN M. MCDOWELL, LARRY D. SINGELL JR., and MARK STATER *
* We particularly thank Daniel Hamermesh for his insightful
comments on an early draft of this manuscript, as well as the anonymous
referees who provided very constructive suggestions that improved the
manuscript.
McDowell: Professor, Department of Economics, Arizona State
University, Tempe, AZ 85287. Phone 1-480-965-7109, Fax 1-480-965-7048,
E-mail john.mcdowell@ asu.edu
Singell: Professor, Department of Economics, University of Oregon,
Eugene, OR 97403. Phone 1-541-346-4672, Fax 1-541-346-1243, E-mail
lsingell@uoregon.edu
Stater: Assistant Professor, Department of Public Administration
and Policy, University of Georgia, Athens, GA 30602. Phone
1-706-542-2873, Fax 1-706-583-0610, E-mail mstat@uga.edu
TABLE 1
Descriptive Statistics
Full Sample Women
Variables Mean SD Mean SD
Female 0.2939 0.4555 1.0000 0.0000
Publication 0.3666 0.4819 0.3237 0.4679
Coauthorship 0.2427 0.4287 0.2062 0.4046
Age 0.4361 0.0916 0.4157 0.0889
Experience 0.1313 0.0883 0.1046 0.0821
PhD Institution Quality 0.5368 0.3684 0.5045 0.3522
Coauthorship within PhD Cohort 0.2351 0.1097 0.2351 0.1084
Cohort size of Market Entrants 0.2746 0.1131 0.2814 0.1049
Cohort size of PhD Class 0.7709 0.6024 0.7526 0.5861
Current Job Quality 0.5048 0.5815 0.4697 0.5469
Current Job in Top Department 0.1176 0.3221 0.0985 0.2980
Coauthorship within Current Job 0.2214 0.1701 0.2193 0.1652
Administrative Position 0.0706 0.2562 0.0530 0.2240
Lecturer 0.0504 0.2187 0.1030 0.3040
AgEcon Department 0.0145 0.1194 0.0033 0.0577
Business Department 0.0858 0.2801 0.0457 0.2089
Other Department 0.0584 0.2345 0.0738 0.2614
Government Sector 0.0899 0.2861 0.0877 0.2829
Business Sector 0.1125 0.3159 0.1081 0.3105
Other Sector 0.0964 0.2952 0.1275 0.3336
Year 1974 0.1194 0.3243 0.0804 0.2720
Year 1985 0.1910 0.3931 0.1758 0.3806
Year 1989 0.1988 0.3991 0.2156 0.4113
Year 1993 0.2270 0.4189 0.2487 0.4323
Year 1997 0.2134 0.4097 0.2444 0.4298
No. observations 17,348 5,098
Men
Variables Mean SD
Female 0.0000 0.0000
Publication 0.3844 0.4865
Coauthorship 0.2579 0.4375
Age 0.4446 0.0913
Experience 0.1424 0.0884
PhD Institution Quality 0.5502 0.3741
Coauthorship within PhD Cohort 0.2351 0.1103
Cohort size of Market Entrants 0.2718 0.1163
Cohort size of PhD Class 0.7785 0.6090
Current Job Quality 0.5194 0.5948
Current Job in Top Department 0.1256 0.3314
Coauthorship within Current Job 0.2223 0.1721
Administrative Position 0.0780 0.2681
Lecturer 0.0285 0.1664
AgEcon Department 0.0191 0.1369
Business Department 0.1025 0.3034
Other Department 0.0520 0.2220
Government Sector 0.0909 0.2874
Business Sector 0.1143 0.3182
Other Sector 0.0835 0.2767
Year 1974 0.1357 0.3425
Year 1985 0.1973 0.3980
Year 1989 0.1918 0.3938
Year 1993 0.2180 0.4129
Year 1997 0.2005 0.4004
No. observations 12,250
Notes: The variables Age, Experience, and Cohort Size of PhD Class
size measures are divided by 100. The Cohort Size of Market Entrants
is divided by 10,000.
TABLE 2
Total Sample Estimation Results
Standard Probit
Variables Publications Coauthorship
Female -0.2161 *** (0.0244) -0.2339 *** (0.0262)
Age -0.0607 *** (0.0028) --
Experience 0.0560 *** (0.0049) 0.0144 *** (0.0046)
Experience Squared -0.0007 *** (0.0001) -0.0011 *** (0.0001)
PhD Institution Quality 0.2149 *** (0.0379) 0.0770 (0.0493)
Coauthorship within -- 0.6053 *** (0.1566)
PhD Cohort
Cohort Size of Market -0.0047 *** (0.0013) -0.0001 (0.0014)
Entrants
Cohort Size of PhD Class 0.0005 ** (0.0002) -0.0001 (0.0014)
Current Job Quality 0.3464 *** (0.0242) 0.1563 *** (0.0308)
Current Job In Top 0.1304 *** (0.0412) 0.1873 *** (0.0418)
Department
Coauthorship within -- 1.1022 *** (0.0984)
Current Job
Administrative Position -0.3730 *** (0.0449) -0.2861 *** (0.0491)
Lecturer -0.4251 *** (0.0518) -0.4649 *** (0.0577)
AgEcon Department 0.0444 (0.0827 0.0615 (0.0860)
Business Department -0.2214 *** (0.0385) 0.1780 *** (0.0402)
Other Department -0.2922 *** (0.0471) -0.2557 *** (0.0500)
Government Sector -0.5612 *** (0.0401) -0.3809 *** (0.0440)
Business Sector -0.9897 *** (0.0427) -0.7359 *** (0.0498)
Other Sector -0.2797 *** (0.0356) -0.1913 *** (0.0380)
Year 1974 0.1133 * (0.0621) 0.2781 *** (0.0785)
Year 1985 0.3667 *** (0.0644) 0.4981 *** (0.0832)
Year 1989 0.4729 *** (0.0650) 0.5665 *** (0.0855)
Year 1993 0.4957 *** (0.0647) 0.6109 *** (0.0852)
Year 1997 0.6309 *** (0.0650) 0.7236 *** (0.0876)
Constant 1.3847 *** (0.1070) -1.5065 *** (0.0722)
[rho] -- --
Log likelihood -9762.02 -8497.82
Bivariate Probit
Variables Publications Coauthorship
Female -0.2143 *** (0.0301) -0.0471 (0.0437)
Age -0.0611 *** (0.0036) --
Experience 0.0562 *** (0.0056) 0.0367 *** (0.0068)
Experience Squared -0.0007 *** (0.0001) -0.0010 *** (0.0002)
PhD Institution Quality 0.2144 *** (0.0447) -0.1865 *** (0.0698)
Coauthorship within -- 0.3425 (0.2415)
PhD Cohort
Cohort Size of Market -0.0047 *** (0.0015) 0.0036 * (0.0022)
Entrants
Cohort Size of PhD Class 0.0005 * (0.0003) -0.0011 *** (0.0004)
Current Job Quality 0.3446 *** (0.0294) -0.0559 (0.0465)
Current Job In Top 0.1284 *** (0.0488) 0.1100 * (0.0585)
Department
Coauthorship within -- 0.5697 *** (0.1358)
Current Job
Administrative Position -0.3731 *** (0.0518) 0.2376 *** (0.0849)
Lecturer -0.4201 *** (0.0590) -0.0619 (0.0959)
AgEcon Department 0.0439 (0.0954) 0.1587 (0.1270)
Business Department -0.2197 *** (0.0455) 0.0723 (0.0646)
Other Department -0.2894 *** (0.0586) -0.0122 (0.0796)
Government Sector -0.5606 *** (0.0480) 0.3177 *** (0.0828)
Business Sector -0.9887 *** (0.0495) 0.3726 *** (0.1132)
Other Sector -0.2790 *** (0.0438) 0.1119 * (0.0616)
Year 1974 0.1105 * (0.0627) 0.3907 *** (0.1057)
Year 1985 0.3642 *** (0.0668) 0.5607 *** (0.1211)
Year 1989 0.4710 *** (0.0676) 0.5728 *** (0.1251)
Year 1993 0.4936 *** (0.0686) 0.6689 *** (0.1264)
Year 1997 0.6287 *** (0.0692) 0.7429 *** (0.1334)
Constant 1.4021 *** (0.1343) -0.1628 (0.1565)
[rho] -0.5154 *** (0.1095)
Log likelihood -13,617
Notes: The variables Age, Experience, and Cohort Size of PhD Class size
measures are divided by 100. The Cohort Size of Market Entrants is
divided by 10,000. SEs in parentheses, and *** (**, *) indicates
significance at 1% (5%, 10%) level.
TABLE 3
Bivariate Probit Estimation Results for the Sample of PhD Institutions
Without Quality Adjustment
Variables Publications Coauthorship
Female -0.2372 *** (0.0460) -0.0312 (0.0602)
Age -0.0641 *** (0.0060) --
Experience 0.0715 *** (0.0085) 0.0375 *** (0.0090)
Experience Squared -0.0009 *** (0.0002) -0.0010 *** (0.0003)
PhD Institution Quality 0.2218 *** (0.0641) -0.2389 *** (0.0907)
Coauthorship within -- 0.3259 (0.3619)
PhD Cohort
Cohort Size of Market -0.0002 (0.0023) 0.0050 * (0.0029)
Entrants
Cohort Size of PhD -0.0002 (0.0004) -0.0007 (0.0005)
Class
Current Job Quality 0.1602 *** (0.0325) -0.0306 (0.0489)
Current Job In Top 0.1633 *** (0.0508) 0.0805 (0.0621)
Department
Coauthorship within -- 0.4828 *** (0.1632)
Current Job
Administrative Position -0.3834 *** (0.0723) 0.2499 ** (0.1089)
Lecturer -0.5003 *** (0.0807) -0.0032 (0.1444)
AgEcon Department -0.1057 (0.1038) 0.2039 (0.1284)
Business Department -0.3136 *** (0.0535) 0.1019 (0.0756)
Other Department -0.3712 *** (0.0646) -0.0246 (0.0901)
Year 1974 0.1618 ** (0.0819) 0.4299 *** (0.1327)
Year 1985 0.4527 *** (0.0928) 0.5397 *** (0.1651)
Year 1989 0.5600 *** (0.0949) 0.5450 *** (0.1712)
Year 1993 0.5940 *** (0.0978) 0.6530 *** (0.1765)
Year 1997 0.7077 *** (0.0999) 0.7276 *** (0.1882)
Constant 1.5495 *** (0.2108) -0.1760 (0.2052)
[rho] -0.5653 *** (0.1659)
Log likelihood -6542.83
With Quality Adjustment
Variables Publications Coauthorship
Female 0.0314 (0.0527) 0.0525 (0.1028)
Age -0.0526 *** (0.0073) --
Experience 0.0537 *** (0.0103) 0.0498 *** (0.0162)
Experience Squared -0.0008 *** (0.0002) -0.0014 *** (0.0006)
PhD Institution Quality 0.3128 *** (0.0706) -0.0567 (0.2456)
Coauthorship within -- -1.0691 (1.6170)
PhD Cohort
Cohort Size of Market -0.0037 (0.0024) 0.0066 (0.0052)
Entrants
Cohort Size of PhD 0.0014 *** (0.0005) -0.0018 * (0.0010)
Class
Current Job Quality 0.1843 *** (0.0343) 0.0099 (0.1085)
Current Job In Top 0.3565 *** (0.0550) -0.0720 (0.1364)
Department
Coauthorship within -- 0.2889 (0.5301)
Current Job
Administrative Position -0.0912 (0.0823) 0.0291 (0.1736)
Lecturer -0.4125 *** (0.1006) 0.0335 (0.2704)
AgEcon Department -0.4799 *** (0.1475) 0.4247 (0.4089)
Business Department -0.0449 (0.0612) 0.1151 (0.1167)
Other Department -0.3296 *** (0.0748) -0.0522 (0.1724)
Year 1974 -0.1061 (0.0955) 0.3891 ** (0.1839)
Year 1985 -0.2505 ** (0.1045) 0.6505 *** (0.2162)
Year 1989 -0.3217 *** (0.1067) 0.7492 *** (0.2176)
Year 1993 -0.1004 (0.1067) 0.8478 *** (0.2286)
Year 1997 -0.0721 (0.1100) 1.1693 *** (0.2340)
Constant 0.3922 (0.2477) 0.0067 (0.5940)
[rho] -0.3362 (0.3391)
Log likelihood -3401.15
Notes: The variables Age, Experience, and Cohort Size of PhD Class size
measures are divided by 100. The Cohort Size of Market Entrants is
divided by 10,000. SE in parentheses, and *** (**, *) indicates
significant at 1% (5%, 10%) level.
TABLE 4
Bivariate Probit Estimation Results for the Sample of PhD Institutions
with Interactions
Without Quality Adjustments
Variables Publications Coauthorship
Female 0.1016 (0.1749) 0.1179 (0.2948)
Current Job in Top 0.1718 *** (0.0571) 0.1434 ** (0.0682)
Department
Year 1974 0.2158 *** (0.0867) 0.4220 *** (0.1418)
Year 1985 0.5206 *** (0.0981) 0.5555 *** (0.1729)
Year 1989 0.6015 *** (0.1013) 0.5164 *** (0.1784)
Year 1993 0.6164 *** (0.1052) 0.6499 *** (0.1849)
Year 1997 0.7131 *** (0.1092) 0.7261 *** (0.1980)
(Female) * (Top -0.0313 (0.0928) -0.2789 *** (0.1114)
Department)
(Female) * (Year 1974) -0.4204 ** (0.2004) -0.0057 (0.3256)
(Female) * (Year 1985) -0.4789 *** (0.1930) -0.1611 (0.3181)
(Female) * (Year 1989) -0.3632 * (0.1907) 0.0338 (0.3122)
(Female) * (Year 1993) -0.2952 (0.1890) -0.0731 (0.3104)
(Female) * (Year 1997) -0.2433 (0.1901) -0.0731 (0.3095)
[rho] -0.5765 *** (0.1642)
Log likelihood -6533.31
With Quality Adjustments
Variables Publications Coauthorship
Female 0.4015 ** (0.1946) 1.1372 *** (0.4559)
Current Job in Top 0.4424 *** (0.0611) -0.0694 (0.1602)
Department
Year 1974 -0.0839 (0.1029) 0.5531 *** (0.2049)
Year 1985 -0.1618 (0.1122) 0.9201 *** (0.2406)
Year 1989 -0.3240 *** (0.1163) 1.0441 *** (0.2427)
Year 1993 -0.0465 (0.1176) 1.2065 *** (0.2707)
Year 1997 -0.0011 (0.1235) 1.6398 *** (0.3080)
(Female) * (Top -0.3472 *** (0.1007) 0.0584 (0.2057)
Department)
(Female) * (Year 1974) -0.1467 (0.2314) -0.6729 (0.4582)
(Female) * (Year 1985) -0.4473 ** (0.2213) -1.0319 ** (0.5099)
(Female) * (Year 1989) -0.0959 (0.2172) -1.1249 ** (0.4832)
(Female) * (Year 1993) -0.2768 (0.2096) -1.3209 *** (0.4888)
(Female) * (Year 1997) -0.3177 (0.2155) -1.6030 *** (0.5189)
[rho] -0.3756 (0.3603)
Log likelihood -3379.75
Notes: In addition to the interaction terms, the publication and
coauthorship specifications include the same explan-atory variable as
presented in Tables 2 and 3. SE in parentheses, and *** (**, *)
indicates significant at 1% (5%, 10%) level.
TABLE 5
Decomposition of Gender-Differences in the Benefits of Coauthorship to
the Probability of Publishing
([DELTA][[PHI].sub.M] - Without Quality Adjustments
[DELTA][[PHI].sub.F]) (0.295 - 0.109) = 0.186
[DELTA][[PHI].sup.X.sub.MF] 0.121
[DELTA][[PHI].sup.[beta].sub.MF] 0.102
[DELTA][[PHI].sup.[rho].sub.MF] -0.037
([DELTA][[PHI].sub.M]- With Quality Adjustments
[DELTA][[PHI].sub.F]) (0.329 - 0.208) = 0.121
[DELTA][[PHI].sup.X.sub.MF] 0.070
[DELTA][[PHI].sup.[beta].sub.MF] 0.207
[DELTA][[PHI].sup.[rho].sub.MF] -0.156
Notes: [DELTA][[PHI].sup.[beta].sub.M] and [DELTA][[PHO].sup.X.sub.MF]
and [DELTA][[phi].sup.[rho].sub.MF] measure the respective male-female
difference in the contribution of coauthorship to the probability of
publishing due to the coefficients, characteristics, and [rho], which
must sum to the total male-female differential, [DELTA][[PHI].sub.MF].
[DELTA][[PHI].sub.MF] also equals the contribution of coauthorship to
the probability of publishing for men, [DELTA][[PHI.sub.M] minus the
same benefit calculation for women, [DELTA][[PHI].sub.F].