Untitled Diff

-1337 Removals
+1907 Additions
Gender Differences in Recognition for Group WorkGender Differences in Recognition for Group Work
Heather SarsonsHeather Sarsons, Klarita Gërxhani, Ernesto Reuben, and Arthur Schram
February 4, 2019September 15, 2019
AbstractAbstract
Does gender influence how credit for group work is allocated? Using data fromDoes gender influence how credit for group work is allocated? Using data from
academic economists’ CVs, I test whether coauthored and solo-authored publicationsacademic economists’ CVs, we test whether coauthored and solo-authored publica-
matter differently for tenure for men and women. Because coauthors are listed alpha-tions matter differently for tenure for men and women. Because coauthors are listed
betically in economics, coauthored papers do not provide specific information aboutalphabetically in economics, coauthored papers do not provide specific information
each contributor’s skills or ability. Solo-authored papers, on the other hand, provideabout each contributor’s skills or ability. Solo-authored papers, on the other hand,
a relatively clear signal of ability. I find that conditional on publication quality andprovide a relatively clear signal of ability. We find that conditional on publication
other observables, men are tenured at roughly the same rate regardless of whetherquality and other observables, men are tenured at roughly the same rate regardless of
they coauthor or solo-author. Women, however, become less likely to receive tenurewhether they coauthor or solo-author. Women, however, become less likely to receive
the more they coauthor. The result is most pronounced for women coauthoring withtenure the more they coauthor. The result is most pronounced for women coauthoring
men and less pronounced among women who coauthor with other women. An on-with men and less pronounced among women who coauthor with other women. Two
line experiment finds similar patterns when women perform male-stereotyped tasks.experiments suggest that both stereotypes surrounding a task as well as the evalua-
However, women receive equal credit for joint work with men when the task is per-tors’ gender affect who receives credit. Taken together, our results are best explained
ceived to be gender-neutral. Taken together, the results suggest that gender and stereo-by gender and stereotypes having a noticeable influence on the allocation of credit for
types influence the allocation of credit for group work.group work.
I especially thank Roland Fryer, Claudia Goldin, Larry Katz, David Laibson, and Amanda Pallais forSarsons, University of Chicago Booth (heather.sarsons@chicagobooth.edu); Gërxhani, European Uni-
their guidance and encouragement. I also thank Mitra Akhtari, Amitabh Chandra, John Coglianese, Orenversity Institute; Reuben, New York University Abu Dhabi and LISER; Schram, Amsterdam School of Eco-
Danieli, Ellora Derenoncourt, Florian Ederer, Ben Enke, Raissa Fabregas, Nicole Fortin, Peter Ganong, Ed-nomics and European University Institute. Sarsons especially thanks Roland Fryer, Claudia Goldin, Larry
ward Glaeser, Siri Isaksson, Sara Lowes, Rob McMillan, Eduardo Montero, Gautam Rao, Alex Segura, NiharKatz, David Laibson, and Amanda Pallais for their guidance and encouragement. We also thank Mitra
Shah, Peter Tu, Justin Wolfers, and participants at SOLE 2016, the Early Behavioural Economics Conference,Akhtari, Amitabh Chandra, John Coglianese, Oren Danieli, Ellora Derenoncourt, Florian Ederer, Ben Enke,
the Harvard Business School Gender Initiative, and the Harvard Inequality Seminar for helpful commentsRaissa Fabregas, Nicole Fortin, Nickolas Gagnon, Peter Ganong, Edward Glaeser, Siri Isaksson, Emir Ka-
and suggestions. This paper is intentionally solo-authored.menica, Sara Lowes, Rob McMillan, Eduardo Montero, Gautam Rao, Alex Segura, Nihar Shah, Peter Tu,
Jeroen van de Ven, Justin Wolfers, and various conference and seminar participants for their helpful com-
ments and suggestions.
11
1 Introduction1 Introduction
Do employers use gender when allocating credit for group work, particularly when in-Do employers use gender when allocating credit for group work, particularly when in-
dividual contributions are unobserved? Organizations increasingly rely on group workdividual contributions are unobserved? Organizations increasingly rely on group work
for production (Lazear and Shaw, 2007), yet there is little empirical evidence document-for production (Lazear and Shaw, 2007), yet there is little empirical evidence document-
ing how credit for group work is allocated. Unless employers can perfectly observe eaching how credit for group work is allocated. Unless employers can perfectly observe each
worker’s contribution to the team’s output, they must decide how to allocate credit with-worker’s contribution to the team’s output, they must decide how to allocate credit with-
out having full information as to what each worker did. This could leave room for demo-out having full information as to what each worker did. This could leave room for demo-
graphic characteristics, such as gender, to influence the allocation of credit.graphic characteristics, such as gender, to influence the allocation of credit.
In this paper, I test whether uncertainty over an individual’s contribution to a projectIn this paper, we test whether uncertainty over an individual’s contribution to a project
leads to differential attribution of credit that contributes to the gender promotion gap. Inleads to differential attribution of credit that contributes to the gender promotion gap. In
many industries, women are not only hired at lower rates than men are, they are alsomany industries, women are not only hired at lower rates than men are, they are also
promoted at lower rates.promoted at lower rates.
11
This paper explores whether gender differences in credit forThis paper explores whether gender differences in credit for
group work exist and whether they explain part of the promotion gap.group work exist and whether they explain part of the promotion gap.
I primarily look at the tenure decisions of academic economists to test whether genderWe primarily look at the tenure decisions of academic economists to test whether gen-
influences the allocation of credit for coauthored papers. Economics is a relevant settingder influences the allocation of credit for coauthored papers. Economics is a relevant
as there is a large tenure gap between men and women, and because the amount of coau-setting as there is a large tenure gap between men and women, and because the amount
thoring has risen dramatically in recent years (Ginther and Kahn, 2004; Hammermesh,of coauthoring has risen dramatically in recent years (Ginther and Kahn, 2004; Hammer-
2013). Using data from economists’ CVs, I track individuals’ career trajectories and com-mesh, 2013). Using data from economists’ CVs, we track individuals’ career trajectories
pare whether the trajectory is different for individuals who coauthor versus solo-author,and compare whether the trajectory is different for individuals who coauthor versus solo-
and whether there is a difference by gender.author, and whether there is a difference by gender.
Within economics, I find that men and women who solo-author most of their workWithin economics, we find that men and women who solo-author most of their work
have similar tenure rates conditional on a proxy for the quality of papers. However, anhave similar tenure rates conditional on a proxy for the quality of papers. However, an
additional coauthored paper is correlated with an 8.2% increase in tenure probability foradditional coauthored paper is correlated with an 8.2% increase in tenure probability for
men but only a 5.6% increase for women. This gap is significantly less pronounced formen but only a 5.6% increase for women. This gap is significantly less pronounced for
women who coauthor with women, suggesting that the attribution of credit is relatedwomen who coauthor with women, suggesting that the attribution of credit is related
to the gender mix of coauthors. Furthermore, a man who coauthors is no less likely toto the gender mix of coauthors. Furthermore, a man who coauthors is no less likely to
receive tenure than a comparable man who solo-authors even though there is presumablyreceive tenure than a comparable man who solo-authors even though there is presumably
more uncertainty as to how much work he did. A counterfactual exercise suggests thatmore uncertainty as to how much work he did. A counterfactual exercise suggests that
this difference in credit allocation explains 60% of the unconditional gender gap in tenurethis difference in credit allocation explains 60% of the unconditional gender gap in tenure
rates and 84% of the gap that remains after controlling for average paper quality, citations,rates and 84% of the gap that remains after controlling for average paper quality, citations,
tenure and PhD institution ranks, and field.tenure and PhD institution ranks, and field.
To ensure that I am not picking up on ability differences between men and women, ITo ensure that we are not picking up on ability differences between men and women,
control for the quality of papers using both journal rankings and citations, allowing forwe control for the quality of papers using both journal rankings and citations, allowing
11
Blau and DeVaro (2007), for example, find that across jobs, women are less likely to be promoted thanBlau and DeVaro (2007), for example, find that across jobs, women are less likely to be promoted than
men conditional on worker’s performance and ability ratings. In the UK, female managers are nearly 40%men conditional on worker’s performance and ability ratings. In the UK, female managers are nearly 40%
less likely to be promoted than male managers (Elmins et al. 2016).less likely to be promoted than male managers (Elmins et al., 2016).
22
a comparison of men and women with similar research portfolios. The results are alsofor a comparison of men and women with similar research portfolios. The results are also
robust to including other individual-level controls such as length of time to tenure androbust to including other individual-level controls such as length of time to tenure and the
the seniority of one’s coauthors, as well as tenure year, tenure institution, and primaryseniority of one’s coauthors, as well as tenure year, tenure institution, and primary field
field fixed effects.fixed effects.
I argue that these results are most consistent with a story of women receiving less creditWe argue that these results are most consistent with a story of women receiving less
for their joint work with men because of bias. To show this, I first use current CV andcredit for their joint work with men because of bias. To show this, we first use current
citation data to compare the productivity of men and women who did and did not receiveCV and citation data to compare the productivity of men and women who did and did
tenure at the institution where they initially went up for tenure. While the estimates arenot receive tenure at the institution where they initially went up for tenure. While the
imprecise, I find suggestive evidence that women who coauthor and are denied tenureestimates are imprecise, we find suggestive evidence that women who coauthor and are
produce more solo-authored papers that publish in high-ranking journals than men whodenied tenure produce more solo-authored papers that publish in high-ranking journals
are denied tenure. Data on citations show a similar result.than men who are denied tenure. Data on citations show a similar result.
I then rule out several alternative explanations for the empirical patterns. For example,We then rule out several alternative explanations for the empirical patterns. For ex-
several papers have demonstrated that selection into coauthorship in economics is notample, several papers have demonstrated that selection into coauthorship in economics
random.is not random.
22
I test for selection into coauthorship and do not find any evidence that womenWe test for selection into coauthorship and do not find any evidence that
coauthor with high ability or more senior men. I also look at the timing of coauthorshipwomen coauthor with high ability or more senior men. We also look at the timing of coau-
and find no evidence that women begin coauthoring if they have a slower start to theirthorship and find no evidence that women begin coauthoring if they have a slower start
careers. The empirical patterns are also inconsistent with taste-basted discrimination.to their careers. The empirical patterns are also inconsistent with taste-basted discrimina-
Because the CV data does not allow me to rule out the possibility that women actuallytion.
contribute less to papers that are coauthored with men, I conduct an online experimentBecause the CV data do not allow us to rule out the possibility that women actually
designed to test whether this drives credit allocation. In the experiment, I first hire indi-contribute less to papers that are coauthored with men, we conduct two experiments de-
viduals to complete quizzes on topics that are either male or female-stereotyped. I thensigned to test whether real or perceived differences in contributions drive credit allocation.
hire participants who act as “predictors” and are randomized into a solo treatment or aIn the first experiment, we first hire individuals to complete quizzes on topics that are ei-
group treatment. Predictors in the solo treatment are shown two individual’s separatether male or female-stereotyped. We then hire participants who act as “predictors” and
quiz scores while predictors in the group treatment are shown the combined score of twoare randomized into an individual treatment or a joint treatment. Predictors in the indi-
individuals. They are then asked to predict the performance of each participant on futurevidual treatment are shown two individual’s separate quiz scores while predictors in the
quizzes.joint treatment are shown the combined score of two individuals. They are then asked to
I find that in the group treatment, women are predicted to perform worse than theirpredict the performance of each participant on future quizzes.
male counterparts for male-stereotyped quizzes, suggesting that participants making theIn the joint treatment, women are predicted to perform worse than their male counter-
predictions believe that women contributed less to the combined score (that is, they per-parts for male-stereotyped quizzes, suggesting that predictors believe that women con-
formed worse). However, if pairs performed a female-stereotyped quiz, women and mentributed less to the combined score (that is, they performed worse). However, if pairs
are given equal credit. To understand whether these results are driven by participants’performed a female-stereotyped quiz, women and men are given equal credit. To under-
beliefs about the ability distributions of men and women, I randomly provide some par-stand whether these results are driven by participants’ beliefs about the ability distribu-
tions of men and women, we randomly provide some participants with the distribution of
scores on the initial quiz by gender. Women appear to be given equal credit in the female-
stereotyped quiz because participants view it as being gender-neutral. That is, they do not
22
Boschini and Sjögren (2007) test whether coauthorship patterns in economics are gender neutral. TheySee, for example, Boschini and Sjögren (2007), Garcia and Sherman (2015), and Bikard et al (2015).
find that women are more likely to solo-author than men and that gender homophily in coauthoring in-
creases with women’s representation in a field. Garcia and Sherman (2015) argue that the alphabetical pub-
lishing norms in economics influence both the types of people authors work with and the types of projects
they will work on.
33
ticipants with the distribution of scores on the initial quiz by gender. Women appear torealize that women tend to outperform men. Showing participants the gender distribution
be given equal credit in the female-stereotyped quiz because participants view it as beingof scores corrects this belief and women are then predicted to have a better performance
gender-neutral. That is, they do not realize that women tend to outperform men. Show-in future female-stereotyped quizzes but it does not affect the predicted performance gap
ing participants the gender distribution of scores corrects this belief and women are thenfor women and men performing male-stereotyped tasks.
predicted to have a better performance in future female-stereotyped quizzes. Surpris-The second experiment is conducted in a more natural setting with human resources
ingly, this treatment does not affect the predicted performance gap for women and menpersonnel. Following a similar design, we again test whether women are less likely than
performing male-stereotyped tasks.men to receive credit for good group performance. We additionally elicit the HR person-
nels’ beliefs about male and female performance and find that differences in the allocation
of credit are largely driven by differences in beliefs. We also find that male HR personnel
are more likely to hire in favor of men, and women in favor of women.
This paper replicates and builds off of the results in Sarsons (2017), which shows theThis paper replicates and builds off of the results in Sarsons (2017), which shows the
basic correlational patterns between paper composition and tenure. In this paper, I repli-basic correlational patterns between paper composition and tenure. In this paper, we
cate the results using more data and then use the C.V. data and an experiment to establish areplicate the results using more data and then use the C.V. data and two experiments to es-
channel through which gender influences the allocation of credit. The paper also relates totablish a channel through which gender influences the allocation of credit. The paper also
a large literature seeking to understand difference in labor market outcomes between menrelates to a large literature seeking to understand difference in labor market outcomes be-
and women. Factors such as productivity, personality and behavioural differences (suchtween men and women. Factors such as productivity, personality and behavioural differ-
as competition aversion), and fertility preferences have been shown to explain some differ-ences (such as competition aversion), and fertility preferences have been shown to explain
ences in career choice and progression.some differences in career choice and progression.
33
In academia in particular, studies have pointedIn academia in particular, studies have
to both supply-side factors, including differences in subject matter interest (Dynan andpointed to both supply-side factors, including differences in subject matter interest (Dy-
Rouse, 1997) and the availability of role models (Hale and Regev, 2014; Carrell, Page, andnan and Rouse, 1997) and the availability of role models (Hale and Regev, 2014; Carrell et
West, 2010); demand-side factors, such as implicit bias (Milkman, Akinola, and Chugh,al., 2010); demand-side factors, such as implicit bias (Milkman et al., 2015; Moss-Racusin et
2015; Moss-Racusin et al., 2012); and institutional factors (Antecol et al., 2018). This paperal., 2012); and institutional factors (Antecol et al., 2018). This paper directly tests whether
directly tests whether the differential treatment of work output contributes to the genderthe differential treatment of work output contributes to the gender gap.
gap.
The remainder of the paper is organized as follows. Section 2 describes the data andThe remainder of the paper is organized as follows. Section 2 describes the data and
shows that a tenure gap exists between male and female economists. In Section 3, I showshows that a tenure gap exists between male and female economists. In Section 3, we
that the tenure gap closes as women produce more solo-authored papers but does notshow that the tenure gap closes as women produce more solo-authored papers but does
close as they produce more coauthored papers. Women have a consistently lower proba-not close as they produce more coauthored papers. Women have a consistently lower
bility of tenure for each additional coauthored paper than men. I show that the results areprobability of tenure for each additional coauthored paper than men. We show that the
robust to accounting for attrition, and to using different journal rankings and definitionsresults are robust to accounting for attrition, and to using different journal rankings and
of tenure. In Section 4, I argue that the results are in line with a story in which womendefinitions of tenure. In Section 4, we argue that the results are in line with a story in which
receive less credit for joint work with men. I test alternative explanations of the relation-women receive less credit for joint work with men. We test alternative explanations of the
ship between coauthorship and tenure and argue that none can fully explain the observedrelationship between coauthorship and tenure and argue that none can fully explain the
empirical patterns. Section 5 discusses the structure and results of the experiment. Sectionobserved empirical patterns. Section 5 discusses the design and results of the experiments.
6 concludes.Section 6 concludes.
33
There is a large literature documenting gender differences in productivity, attitudes toward differentThere is a large literature documenting gender differences in productivity, attitudes toward different
types of work, and family choices. See, for example, Niederle and Vesterlund (2007), Antecol et al. (2016),types of work, and family choices. See, for example, Niederle and Vesterlund (2007), Buser et al. (2014),
Ceci et al. (2014), and Ginther and Kahn (2004).Antecol et al. (2018), Ceci et al. (2014), Reuben et al. (2017), and Ginther and Kahn (2004).
44
2 Data2 Data
To examine the relationship between paper composition and tenure, I construct a datasetTo examine the relationship between paper composition and tenure, we construct a dataset
using the CVs of economists who came up for tenure between 1985 and 2014 at one of theusing the CVs of economists who came up for tenure between 1985 and 2014 at one of the
top 35 U.S. PhD-granting universitiestop 35 U.S. PhD-granting universities
44
. The academic progression documented in the CVs. The academic progression documented in the CVs
makes it possible to evaluate the relationship between an individual’s research output andmakes it possible to evaluate the relationship between an individual’s research output and
career progression. I can then compare the degree of collaborative work and reward forcareer progression. We can then compare the degree of collaborative work and reward for
that work, and compare these results for men versus women.that work, and compare these results for men versus women.
2.1 Sample Selection and Data Overview2.1 Sample Selection and Data Overview
I include only PhD-granting institutions in the sample as tenure evaluation at these schoolsWe include only PhD-granting institutions in the sample as tenure evaluation at these
is primarily based on research output, of which I have a clear measure. Other institutionsschools is primarily based on research output, of which we have a clear measure. Other
like liberal arts colleges place greater weight on teaching ability for tenure, somethinginstitutions like liberal arts colleges place greater weight on teaching ability for tenure,
that I cannot measure. I exclude business and public policy schools for similar reasons.something that we cannot measure. We exclude business and public policy schools for
similar reasons.
55
It is reasonable to assume that the top 35 economics departments in the U.S. emphasizeIt is reasonable to assume that the top 35 economics departments in
research which is measured by the number and quality of papers one produces.the U.S. emphasize research which is measured by the number and quality of papers one
produces.
One problem in collecting tenure information is that the CVs of individuals who wentOne problem in collecting tenure information is that the CVs of individuals who went
up for tenure, were denied it, and left to industry or government are difficult to find, lead-up for tenure, were denied it, and left to industry or government are difficult to find, lead-
ing to a sample selection problem. To deal with this issue, I collected historical faculty listsing to a sample selection problem. To deal with this issue, we collected historical faculty
from 23 of the 35 schools and locate over 90% of faculty who had ever gone up for tenurelists from 23 of the 35 schools and locate over 90% of faculty who had ever gone up for
at these 23 institutions. For the remaining 12 schools that did not have historical facultytenure at these 23 institutions. For the remaining 12 schools that did not have historical
lists available, I looked at the top 75 U.S. institutions, the top 5 Canadian institutions, andfaculty lists available, we looked at the top 75 U.S. institutions, the top 5 Canadian institu-
the top 5 European institutions to locate anyone who went up for tenure at a top 35 U.S.tions, and the top 5 European institutions to locate anyone who went up for tenure at a top
school and then moved to another institution. I also checked economists’ CVs at the ma-35 U.S. school and then moved to another institution. We also checked economists’ CVs at
jor Federal Reserve Boards and other large research institutes, such as Mathematica, in thethe major Federal Reserve Boards and other large research institutes, such as Mathemat-
U.S. While there might still be a sample selection problem, I show in Section 3.2.1 that theica, in the U.S. While there might still be a sample selection problem, we show in Section
results are robust to using only the sample for which I have historical faculty lists.3.2.1 that the results are robust to using only the sample for which we have historical
From individuals’ CVs, I code where and when they received their PhDs, their em-faculty lists.
From individuals’ CVs, we code where and when they received their PhDs, their em-
ployment and publication history, and their primary and secondary fields. When lookingployment and publication history, and their primary and secondary fields. When looking
at the relationship between publications and tenure in the main analysis, I only includeat the relationship between publications and tenure in the main analysis, we only include
papers that were published up to and including the year an individual goes up for tenure.
Book chapters are not included in the paper count. In a robustness check, I include papers
that were published one and two years after tenure.
44
The list of institutions are taken from the RePEc/IDEAS Economics Department rankings. The list ofThe list of institutions are taken from the RePEc/IDEAS Economics Department rankings. The list of
schools included can be found in Appendix Aschools included can be found in Appendix C.
55
Business and policy schools might also value teaching differently and put weight on different types ofBusiness and policy schools might also value teaching differently and put weight on different types of
journals.journals.
55
To control for the quality of a person’s publications, I primarily use the “AER equiv-papers that were published up to and including the year an individual goes up for tenure.
Book chapters are not included in the paper count. In a robustness check, we include
papers that were published one and two years after tenure.
To control for the quality of a person’s publications, we primarily use the “AER equiv-
alent” ranking measure developed by Kalaitzidakis et al. (2003). This measure convertsalent” ranking measure developed by Kalaitzidakis et al. (2003). This measure converts
journal publications into their equivalent number of American Economic Review papersjournal publications into their equivalent number of American Economic Review papers.
66
.
Less than 10% of journal articles cannot be converted because the journal does not appearLess than 10% of journal articles cannot be converted because the journal does not appear
in the ranking. In these cases I give the publication a ranking of zero.in the ranking. In these cases we give the publication a ranking of zero.
77
Using the AER-equivalent measure instead of a list journal rank allows for differentUsing the AER-equivalent measure instead of a list journal rank allows for different
distances between journal ranks and for multiple journals to hold the same rank. Fordistances between journal ranks and for multiple journals to hold the same rank. For
example, the top field journals can all hold the same rank. Other journal rankings forceexample, the top field journals can all hold the same rank. Other journal rankings force
a ranking among these even though the journals might count the same amount towarda ranking among these even though the journals might count the same amount toward
tenure depending on one’s field. For robustness, I replace this paper quality measuretenure depending on one’s field. For robustness, we replace this paper quality measure
with the RePEc/IDEAS ranking of economics journals in Section 3.2.2.with the RePEc/IDEAS ranking of economics journals in Section 3.2.2.
Finally, I include citations, measured in 2015, of pre-tenure papers as a control variable.Finally, we include citations, measured in 2015, of pre-tenure papers as a control vari-
These citations were scraped from Google Scholar.able. These citations were scraped from Google Scholar.
I supplement this dataset with results from a survey designed to measure individuals’We supplement this dataset with results from a survey designed to measure individu-
beliefs about the returns to various types of papers. The survey also contains informationals’ beliefs about the returns to various types of papers. The survey also contains informa-
on how frequently individuals present their papers. The exact questions and nature of thetion on how frequently individuals present their papers. The exact questions and nature
survey are discussed in greater detail in Section 4.of the survey are discussed in greater detail in Section 4.
2.2 Construction of Tenure2.2 Construction of Tenure
To determine whether someone received tenure, I follow the guidelines on each school’sTo determine whether someone received tenure, we follow the guidelines on each school’s
website (as of 2015) as to when tenure decisions are made. The majority of schools requirewebsite (as of 2015) as to when tenure decisions are made. The majority of schools require
faculty to apply for tenure 7 years after their initial appointment. I therefore considerfaculty to apply for tenure 7 years after their initial appointment. We therefore consider
years 6-8 to be the “tenure window” in which someone applies for tenure to account foryears 6-8 to be the “tenure window” in which someone applies for tenure to account for
people who go up for tenure early or late (because of a leave of absence, for example). I as-people who go up for tenure early or late (because of a leave of absence, for example).
sume that an individual is denied tenure if s/he moves to a university ranked 5 positionsWe assume that an individual is denied tenure if s/he moves to a university ranked 5
below the initial institution during the tenure window. Similarly, I assume that an indi-positions below the initial institution during the tenure window. Similarly, we assume
vidual is denied tenure if he moves from academia to industry during the tenure window.that an individual is denied tenure if s/he moves from academia to industry during the
Defining tenure in this way accounts for the fact that some people switch institutions 2-3tenure window. Defining tenure in this way accounts for the fact that some people switch
years after their initial appointment, not because they were denied tenure but for personalinstitutions 2-3 years after their initial appointment, not because they were denied tenure
preferences, and that some people might choose to move to a comparable school around
the time of tenure even though they were offered tenure at their original institution. For
66
The American Economic Review is regarded as one of the top journals in economics. Most journalThe American Economic Review is regarded as one of the top journals in economics. Most journal
publications are therefore converted to be some fraction of an AER paper.publications are therefore converted to be some fraction of an AER paper.
77
If someone does not have any solo or coauthored papers, I set the relevant journal ranking to zero andIf someone does not have any solo or coauthored papers, we set the relevant journal ranking to zero and
include a dummy variable indicating that the individual has no solo (or coauthored) papers. This enablesinclude a dummy variable indicating that the individual has no solo (or coauthored) papers. This enables
me to keep using the full sample.us to keep using the full sample.
66
example, someone who moves from MIT to Harvard after 7 years was presumably offeredbut for personal preferences, and that some people might choose to move to a comparable
tenure at MIT but chose to move to Harvard for other reasons.school around the time of tenure even though they were offered tenure at their original
institution. For example, someone who moves from MIT to Harvard after 7 years was
presumably offered tenure at MIT but chose to move to Harvard for other reasons.
As mentioned, a person who moves 5 or fewer years after his or her initial appointmentAs mentioned, a person who moves 5 or fewer years after his or her initial appointment
is not assumed to have been denied tenure since s/he moved before the tenure windowis not assumed to have been denied tenure since s/he moved before the tenure window
starts. If someone moves before the tenure window, I use the second institution they werestarts. If someone moves before the tenure window, we use the second institution they
at to determine tenure. For example, if a person’s first job is at University A but s/hewere at to determine tenure. For example, if a person’s first job is at University A but s/he
moves to University B after three years, I use University B as the tenure institution butmoves to University B after three years, we use University B as the tenure institution but
do not start the tenure clock over. I do not restart the clock because the data shows thatdo not start the tenure clock over. We do not restart the clock because the data shows that
in over 80% of cases, the individual still appears to go up for tenure within 8 years of hisin over 80% of cases, the individual still appears to go up for tenure within 8 years of his
or her appointment at the first institution. However, I do extend this tenure clock in aor her appointment at the first institution. However, we do extend this tenure clock in a
robustness check.robustness check.
Individuals who move from an academic institution into industry before the tenureIndividuals who move from an academic institution into industry before the tenure
window are excluded from the sample.window are excluded from the sample.
2.3 Summary Statistics2.3 Summary Statistics
Table 1 presents summary statistics of the data. Approximately 68% of the full sampleTable 1 presents summary statistics of the data. Approximately 68% of the full sample
received tenure, but this masks a stark difference between men and women. Only 52% ofreceived tenure, but this masks a stark difference between men and women. Only 52% of
women received tenure while 73% of men did.women received tenure while 73% of men did.
Total Papers,Solo-authored, andCoauthoredare the number of papers in each group thatTotal Papers,Solo-authored, andCoauthoredare the number of papers in each group that
an individual had published by the time of tenure. These publication counts do not in-an individual had published by the time of tenure. These publication counts do not in-
clude books or book chapters. Papers published in non-economics journals (such as aclude books or book chapters. Papers published in non-economics journals (such as a
political science journal) are included but receive a ranking of 0 (the lowest ranking). Thepolitical science journal) are included but receive a ranking of 0 (the lowest ranking). The
results are robust to excluding publications in non-economics journals.results are robust to excluding publications in non-economics journals.
There is no statistically significant difference in the number of papers that men andThere is no statistically significant difference in the number of papers that men and
women produce. Panel B looks at differences in the quality of papers. Men are no morewomen produce. Panel B looks at differences in the quality of papers. Men are no more
likely to publish their papers in "Top 5" journals (American Economic Review, Economet-likely to publish their papers in “Top 5” journals (American Economic Review, Economet-
rica, Journal of Political Economy, Quarterly Journal of Economics, and The Review ofrica, Journal of Political Economy, Quarterly Journal of Economics, and The Review of
Economic Studies) than women. The only statistically significant productivity differenceEconomic Studies) than women. The only statistically significant productivity difference
is that men tend to publish their coauthored papers in slightly higher-ranking journals.is that men tend to publish their coauthored papers in slightly higher-ranking journals.
Specifically, men’s coauthored papers have an average ranking of 0.34 AER-equivalentsSpecifically, men’s coauthored papers have an average ranking of 0.34 AER-equivalents
while women’s coauthored papers have an average ranking of 0.30 AER-equivalents. Iwhile women’s coauthored papers have an average ranking of 0.30 AER-equivalents. We
therefore control for the quality of papers, measured using the AER-equivalent ranking astherefore control for the quality of papers, measured using the AER-equivalent ranking as
well as average citations, throughout the analysis.well as average citations, throughout the analysis.
7
Panel C displays differences in coauthoring patterns between men and women.Num-Panel C displays differences in coauthoring patterns between men and women.Num-
ber Unique CAsis the number of unique coauthors an individual has had by tenure. Menber Unique CAsis the number of unique coauthors an individual has had by tenure. Men
7
and women have roughly the same number of coauthors but there are some differences inand women have roughly the same number of coauthors but there are some differences in
the types of people men and women coauthor with. For example, women are less likely tothe types of people men and women coauthor with. For example, women are less likely to
coauthor with senior faculty and more likely to coauthor with other assistant professors.coauthor with senior faculty and more likely to coauthor with other assistant professors.
This could in part be driven by the fact that they are also more likely to coauthor withThis could in part be driven by the fact that they are also more likely to coauthor with
other women, many of whom are also junior professors.other women, many of whom are also junior professors.
For illustrative purposes, I plot the number of women and men who have variousFor illustrative purposes, we plot the number of women and men who have various
combinations of solo and coauthored papers in Figure 1, as well as the average proba-combinations of solo and coauthored papers in Figure 1, as well as the average probability
bility of receiving tenure for each paper combination in Figure 2. Most men and womenof receiving tenure for each paper combination in Figure 2. Most men and women have
have a similar combination of solo and coauthored papers. Figure 2 illustrates that in-a similar combination of solo and coauthored papers. Figure 2 illustrates that individu-
dividuals with a large number of either solo or coauthored papers are likely to receiveals with a large number of either solo or coauthored papers are likely to receive tenure.
tenure. However, Panel A suggests that women with a higher fraction of their papers thatHowever, Panel A suggests that women with a higher fraction of their papers that are
are solo-authored have a better chance of receiving tenure than women with a mix of solosolo-authored have a better chance of receiving tenure than women with a mix of solo
and coauthored papers. I examine this claim formally in the next section.and coauthored papers. We examine this claim formally in the next section.
3 Empirical Strategy and Results3 Empirical Strategy and Results
3.1 Main Results3.1 Main Results
I show three main results. I first establish that a significant tenure gap exists betweenWe show three main results. We first establish that a significant tenure gap exists between
men and women. I then show that the gap becomes more pronounced the more womenmen and women. We then show that the gap becomes more pronounced the more women
coauthor, and that women who solo-author all of their papers have comparable tenurecoauthor, and that women who solo-author all of their papers have comparable tenure
rates to men. Finally, I show that the gender of a woman’s coauthor matters. Women whorates to men. Finally, we show that the gender of a woman’s coauthor matters. Women
coauthor with other women do not suffer a coauthor penalty.who coauthor with other women do not suffer a coauthor penalty.
3.1.1 The Tenure Gap3.1.1 The Tenure Gap
Figure 3 plots the coefficientFigure 3 plots the coefficient
ˆˆ
ββ
11
from estimatingfrom estimating
TT
if stif st
11
TotPapersTotPapers
ii
22
TotPapersTotPapers
22
i
ZZ
ii
ff
ss
tt
++
if stif st
(1)(1)
separately for men and women using OLS. The dependent variable,Tseparately for men and women using OLS. The dependent variable,T
if stif st
, is an indicator, is an indicator
that individualiin fieldfat schoolsreceives tenure in yeart.TotPapersthat individualiin fieldfat schoolsreceives tenure in yeart.TotPapers
ii
is the number ofis the number of
papers (both coauthored and solo-authored) individualihas at the time he or she went uppapers (both coauthored and solo-authored) individualihas at the time he or she went up
for tenure. A quadratic in the number of papers is included to capture non-linearities infor tenure. A quadratic in the number of papers is included to capture non-linearities in
how publications matter for tenure. The vector of individual-level controls,Zhow publications matter for tenure. The vector of individual-level controls,Z
ii
, includes, includes
average journal rank (measured as average AER-equivalents), the log of total citations,
the number of years it tookito go up for tenure, and the average number of coauthors
88
oni’s papers. Tenure institution (θaverage journal rank (measured as average AER-equivalents), the log of total citations,
the number of years it tookito go up for tenure, and the total number of coauthors oni’s
papers. Tenure institution (θ
ss
), tenure year (θ), tenure year (θ
tt
), and field fixed effects (θ), and field fixed effects (θ
ff
) are also) are also included
included as tenure standards likely vary over time and by field and department.as tenure standards likely vary over time and by field and department.
The figure shows that a significant tenure gap exists between men and women evenThe figure shows that a significant tenure gap exists between men and women even
after controlling for productivity, primary field, tenure institution, and tenure year. Whileafter controlling for productivity, primary field, tenure institution, and tenure year. While
an additional paper is correlated with a 13-16 percentage point increase in tenure proba-an additional paper is correlated with a 13-16 percentage point increase in tenure proba-
bility for men and women, women are consistently 10-13 percentage points less likely tobility for men and women, women are consistently 10-13 percentage points less likely to
receive tenure than men conditional on having written the same number and quality ofreceive tenure than men conditional on having written the same number and quality of
papers. The lower intercept for women could stem from tenure committees starting with apapers. The lower intercept for women could stem from tenure committees starting with a
lower prior about women’s ability. However, if all papers were clear signals of ability andlower prior about women’s ability. However, if all papers were clear signals of ability and
tenure committees are Bayesian, we would expect the slope of the relationship betweentenure committees are Bayesian, we would expect the slope of the relationship between
papers and tenure to be steeper for women. Put differently, if men and women receivedpapers and tenure to be steeper for women. Put differently, if men and women received
equal credit for papers, the coefficient onTotPapersequal credit for papers, the coefficient onTotPapers
ii
should be significantly larger forshould be significantly larger for
women than for men.women than for men.
I provide a formal test for the difference in slopes for men and women in Column 1 ofWe provide a formal test for the difference in slopes for men and women in Column 1
Table 2, where I present the estimates fromof Table 2, where we present the estimates from
TT
if stif st
11
TotPapersTotPapers
ii
22
femfem
ii
33
(TotPapers(TotPapers
ii
×fem×fem
ii
) +β) +β
44
TotPapersTotPapers
22
i
ZZ
ii
ff
ss
tt
++
if stif st
(2)(2)
This is similar to estimating equation 1 except that I interact total papers with a femaleThis is similar to estimating equation 1 except that we interact total papers with a female
dummy,femdummy,fem
ii
rather than splitting the sample. There is no significant difference in therather than splitting the sample. There is no significant difference in the
marginal benefit of an additional paper to men and women.marginal benefit of an additional paper to men and women.
3.1.2 The Tenure Gap and Paper Composition3.1.2 The Tenure Gap and Paper Composition
To test whether coauthored papers matter differently for men and women, I separate pa-To test whether coauthored papers matter differently for men and women, we separate
pers into those that are solo-authored and those that are coauthored and estimatepapers into those that are solo-authored and those that are coauthored and estimate
TT
ifstifst
11
SS
ii
22
(fem(fem
ii
×S×S
ii
) +β) +β
33
CACA
ii
44
(fem(fem
ii
×CA×CA
ii
) +δ) +δ
11
femfem
ii
ZZ
ii
ff
ss
tt
++
ifstifst
(3)(3)
using OLS. Here,Susing OLS. Here,S
ii
andCAandCA
ii
are the number of solo-authored and coauthored papers anare the number of solo-authored and coauthored papers an
individual has at the time of tenure.individual has at the time of tenure.
The results are presented in Table 2. An additional solo-authored paper is associatedThe results are presented in Table 2. An additional solo-authored paper is associated
with a 9.7 percentage point increase in men’s tenure rates and a 15.4 percentage pointwith a 9.7 percentage point increase in men’s tenure rates and a 15.4 percentage point
increase in women’s tenure rates (who start from a lower base tenure rate). If the lowerincrease in women’s tenure rates (who start from a lower base tenure rate). If the lower
initial tenure rate for women is due to employers holding the belief that women are lowerinitial tenure rate for women is due to employers holding the belief that women are lower
9
ability, it seems that the signals from solo papers begin to outweigh the employer’s prior.ability, it seems that the signals from solo papers begin to outweigh the employer’s prior.
This is consistent with a model in which employers start with a lower prior about womenThis is consistent with a model in which employers start with a lower prior about women
9
and update as they receive clear signals about a woman’s ability, giving women full creditand update as they receive clear signals about a woman’s ability, giving women full credit
for this solo work. This is further discussed in the next section.for this solo work. This is further discussed in the next section.
If coauthored papers are an unclear signal of ability, an employer must make a judg-If coauthored papers are an unclear signal of ability, an employer must make a judg-
ment call as to how much each coauthor contributed to the paper which could lead toment call as to how much each coauthor contributed to the paper which could lead to
differential attribution of credit. Indeed, we see that while an additional coauthored pa-differential attribution of credit. Indeed, we see that while an additional coauthored pa-
per helps both men and women, men benefit much more than women. Men’s tenureper helps both men and women, men benefit much more than women. Men’s tenure
rates increase by 8.2 percentage points when they produce a coauthored paper whereasrates increase by 8.2 percentage points when they produce a coauthored paper whereas
women’s increase by 5.6 percentage points.women’s increase by 5.6 percentage points.
However, the fact that men benefit nearly as much from a coauthored paper as they doHowever, the fact that men benefit nearly as much from a coauthored paper as they do
from a solo-authored paper is at odds with the story that employers are dividing creditfrom a solo-authored paper is at odds with the story that employers are dividing credit
for projects among authors. If employers do divide credit, not all men can get 100% of thefor projects among authors. If employers do divide credit, not all men can get 100% of the
credit, particularly for those papers coauthored with other men.credit, particularly for those papers coauthored with other men.
88
This result could point toThis result could point to
an alternative mechanism. For example, if employers exhibit taste-based discrimination,an alternative mechanism. For example, if employers exhibit taste-based discrimination,
they could use joint projects as an excuse to promote men over women. I discuss and testthey could use joint projects as an excuse to promote men over women. We discuss and
several such alternative stories in Section 4.test several such alternative stories in Section 4.
The relationship between paper composition and tenure is summarized in Figure 4.The relationship between paper composition and tenure is summarized in Figure 4.
This figure plots the relationship between the fraction of an individual’s papers that areThis figure plots the relationship between the fraction of an individual’s papers that are
solo-authored and tenure, controlling for the total number of papers, citations, journalsolo-authored and tenure, controlling for the total number of papers, citations, journal
quality, number of coauthors, and tenure institution, year, and field fixed effects. Forquality, number of coauthors, and tenure institution, year, and field fixed effects. For
men, it does not matter if one coauthors or solo-authors: tenure rates are comparablemen, it does not matter if one coauthors or solo-authors: tenure rates are comparable
conditional on the quality of papers. Women who write all of their papers alone haveconditional on the quality of papers. Women who write all of their papers alone have
similar tenure rates to men. However, women who coauthor all of their papers have ansimilar tenure rates to men. However, women who coauthor all of their papers have an
approximately 37% tenure rate, substantially lower than that of men who coauthor all ofapproximately 37% tenure rate, substantially lower than that of men who coauthor all of
their papers ( 72%). The slope for women istheir papers ( 72%). The slope for women is
ˆˆ
β=0.780and is statistically significant at theβ=0.521and is statistically significant at the
1% level (s.e.=0.184).1% level (s.e.=0.158).
3.1.3 Does Coauthor Gender Matter?3.1.3 Does Coauthor Gender Matter?
The probability of receiving tenure is not lower for all women who coauthor. In Table 3, IThe probability of receiving tenure is not lower for all women who coauthor. In Table 3,
categorize coauthored papers into those written with only men, only women, or a mix ofwe categorize coauthored papers into those written with only men, only women, or a mix
men and women:of men and women:
88
It could be the case that because tenure committees are evaluating one person, they always assume thatIt could be the case that because tenure committees are evaluating one person, they always assume that
the man they evaluate deserves full credit for the paper (and we do not see the amount of credit they wouldthe man they evaluate deserves full credit for the paper (and we do not see the amount of credit they would
have given to the other man). It is impossible to evaluate such theories with these data.have given to the other man). It is impossible to evaluate such theories with these data.
1010
TT
if stif st
11
SS
ii
22
(fem(fem
ii
×S×S
ii
) +β) +β
33
CAmaleCAmale
ii
44
(fem×CAmale(fem×CAmale
ii
) +β) +β
55
CAmixCAmix
ii
66
(fem×CAmix(fem×CAmix
ii
) +β) +β
77
CAfemCAfem
ii
88
(fem(fem
ii
×CAfem×CAfem
ii
) +β) +β
99
femfem
ii
ZZ
ii
ff
ss
tt
++
if stif st
(4)(4)
As before,SAs before,S
ii
is the number of solo-authored papers individualihas at the time of tenure.is the number of solo-authored papers individualihas at the time of tenure.
CAfemCAfem
ii
is the number of coauthored papers individualihas in which all of the coauthorsis the number of coauthored papers individualihas in which all of the coauthors
are female. Similarly,CAmaleare female. Similarly,CAmale
ii
is the number of papersihas in which all of the coauthorsis the number of papersihas in which all of the coauthors
are male andCAmixare male andCAmix
ii
is the number of papersihas in which the coauthors consist of menis the number of papersihas in which the coauthors consist of men
and women.and women.
The estimated coefficients on the interaction terms show that the negative relationshipThe estimated coefficients on the interaction terms show that the negative relationship
between coauthoring and tenure for women is driven almost entirely by papers that arebetween coauthoring and tenure for women is driven almost entirely by papers that are
coauthored with men. While a coauthored paper with another man is associated with ancoauthored with men. While a coauthored paper with another man is associated with an
8.7 percentage point increase in tenure probability for a man, it is associated with a 3.18.7 percentage point increase in tenure probability for a man, it is associated with a 3.1
percentage point increase in tenure probability for a woman.percentage point increase in tenure probability for a woman.
99
An additional paper withAn additional paper with a
a woman, however, is associated with an 11.6 percentage point increase in tenure proba-woman, however, is associated with an 11.6 percentage point increase in tenure probabil-
bility for a woman. While this estimate is imprecise due to sample size, I can say that anity for a woman. While this estimate is imprecise due to sample size, we can say that an
additional coauthored paper with a woman has a more positive impact on tenure than anadditional coauthored paper with a woman has a more positive impact on tenure than an
additional coauthored paper with a man. Any explanation as to why women have loweradditional coauthored paper with a man. Any explanation as to why women have lower
tenure rates than men when they coauthor must therefore be correlated with coauthortenure rates than men when they coauthor must therefore be correlated with coauthor
gender. The estimates are robust to including all of the control variables discussed earlier.gender. The estimates are robust to including all of the control variables discussed earlier.
3.1.4 Counterfactual Analysis3.1.4 Counterfactual Analysis
I conduct a counterfactual analysis to estimate how much of the gender gap in tenure ratesWe conduct a counterfactual analysis to estimate how much of the gender gap in tenure
can be explained by the different treatment of coauthored papers. I first estimaterates can be explained by the different treatment of coauthored papers. We first estimate
TT
if stif st
11
SS
ii
22
CACA
ii
11
femfem
ii
ZZ
ii
ff
ss
tt
++
if stif st
(5)(5)
and use the estimates to predict the probability of tenure,and use the estimates to predict the probability of tenure,
ˆˆ
TT
ii
, for everyone in the sample., for everyone in the sample.
I then let the female dummyfemWe then let the female dummyfem
ii
be 0 for everyone and predict tenure rates again (callbe 0 for everyone and predict tenure rates again
this(call this
̃ ̃
TT
ii
). The difference). The difference
ˆˆ
TT
ii
̃ ̃
TT
ii
gives the gender gap in tenure rates conditional on allgives the gender gap in tenure rates conditional on all
observable characteristics but not allowing for differences in the marginal impact of soloobservable characteristics but not allowing for differences in the marginal impact of solo
99
These results again show the puzzling pattern that the amount of credit that is divided among maleThese results again show the puzzling pattern that the amount of credit that is divided among male
coauthors adds up to more than one.coauthors adds up to more than one.
1111
and coauthored papers for men and women.and coauthored papers for men and women.
1010
I then repeat this exercise using the estimates from equation 4, first letting the femaleWe then repeat this exercise using the estimates from equation 4, first letting the female
dummy equal one and then predicting tenure rates again letting the female dummy (anddummy equal one and then predicting tenure rates again letting the female dummy (and
therefore all of the interactions) equal zero. This second set of predicted tenure probabil-therefore all of the interactions) equal zero. This second set of predicted tenure probabil-
ities tells us what women’s predicted tenure rate would be if their papers were treated inities tells us what women’s predicted tenure rate would be if their papers were treated in
the same way that men’s papers are treated.the same way that men’s papers are treated.
The unconditional gender gap in tenure rates is 22 percentage points. The conditionalThe unconditional gender gap in tenure rates is 22 percentage points. The conditional
gap in tenure rates from equation 5 is approximately 16 percentage points. Thus, observ-gap in tenure rates from equation 5 is approximately 16 percentage points. Thus, observ-
able characteristics such as differences in time to tenure and paper quality account forable characteristics such as differences in time to tenure and paper quality account for
about 27% of the gap. The results from using equation 4 to predict tenure probabilitiesabout 27% of the gap. The results from using equation 4 to predict tenure probabilities
suggest that the gap would close by a further 13.5 percentage points if men and women’ssuggest that the gap would close by a further 13.5 percentage points if men and women’s
papers were treated similarly. The different assignment of credit thus accounts for ap-papers were treated similarly. The different assignment of credit thus accounts for ap-
proximately 60% of the unconditional tenure gap and 84% of the conditional gap.proximately 60% of the unconditional tenure gap and 84% of the conditional gap.
3.2 Robustness Checks3.2 Robustness Checks
One may be concerned that the results are a product of the types of productivity measuresOne may be concerned that the results are a product of the types of productivity measures
used or are affected by missing data. In this section, I show that the results are robust toused or are affected by missing data. In this section, we show that the results are robust to
using only the sample for which I have historical faculty lists, to using different journalusing only the sample for which we have historical faculty lists, to using different journal
rankings, to accounting for papers published shortly after tenure, and to using differentrankings, to accounting for papers published shortly after tenure, and to using different
measures of paper counts.measures of paper counts.
1111
3.2.1 Attrition3.2.1 Attrition
The results will be biased if the sample excludes individuals who are denied tenure andThe results will be biased if the sample excludes individuals who are denied tenure and
go into industry, government, or other institutions where I do not observe them. Thisgo into industry, government, or other institutions where we do not observe them. This
would be particularly problematic if men who go to industry after being denied tenurewould be particularly problematic if men who go to industry after being denied tenure
disproportionately coauthored their papers. If this is true, I would be overestimating thedisproportionately coauthored their papers. If this is true, we would be overestimating
benefit of coauthoring for men. I would have a similar problem if women who go tothe benefit of coauthoring for men. We would have a similar problem if women who go
industry after being denied tenure typically wrote solo-authored papers.to industry after being denied tenure typically wrote solo-authored papers.
As discussed in Section 2.1, I attempted to find such individuals by searching institu-As discussed in Section 2.1, we attempted to find such individuals by searching insti-
tions outside of the top 35 U.S. schools, federal reserves, and other research institutes. Totutions outside of the top 35 U.S. schools, federal reserves, and other research institutes.
1010
Interacting all variables except for the number of solo/coauthored papers with the female dummy doesInteracting all variables except for the number of solo/coauthored papers with the female dummy does
not substantially change the results.not substantially change the results.
1111
In Appendix Table A1, I also test whether the results vary by school rank and over time. The estimatesIn Appendix Table A1, we also test whether the results vary by school rank and over time. The esti-
suggest that the coauthoring penalty is driven largely by schools outside of the top 10, although the esti-mates suggest that the coauthoring penalty is driven largely by schools outside of the top 10, although the
mates are imprecise. The coauthorship penalty is also stronger in later years but again the estimates areestimates are imprecise. The coauthorship penalty is also stronger in later years but again the estimates are
imprecise.imprecise.
1212
further allay concerns about sample selection, I run the analysis on the sample for which ITo further allay concerns about sample selection, we run the analysis on the sample for
received historical faculty lists. These lists allow me to track who went up for tenure andwhich we received historical faculty lists. These lists allow me to track who went up for
find them even if they left academia. The results, presented in Column 1 of Table 4, do nottenure and find them even if they left academia. The results, presented in Column 1 of Ta-
change when run on the sample for which there should be very few missing observations.ble 4, do not change when run on the sample for which there should be very few missing
The coefficient on theFemale×Coauthoredinteraction is significant only at the 10% levelobservations. The coefficient on theFemale×Coauthoredinteraction is significant only at
due to the smaller sample, but the direction and magnitude do not change.the 10% level due to the smaller sample, but the direction and magnitude do not change.
3.2.2 Journal Rankings3.2.2 Journal Rankings
In the main analysis, I use a flexible journal ranking that allows multiple journals to holdIn the main analysis, we use a flexible journal ranking that allows multiple journals to hold
the same rank. However, while the economics profession largely agrees on what the “top”the same rank. However, while the economics profession largely agrees on what the “top”
journals are, rankings of field journals or lower-tier journals have changed over time. Injournals are, rankings of field journals or lower-tier journals have changed over time. In
Columns 2-4 of Table 4, I show that the results are robust to using three alternative journalColumns 2-4 of Table 4, we show that the results are robust to using three alternative
ranking metrics as controls.journal ranking metrics as controls.
In Column 2, I use the current RePEc-IDEAS journal ranking. This ranking forcesIn Column 2, we use the current RePEc-IDEAS journal ranking. This ranking forces
a linear relationship between journals and tenure but also contains a larger number ofa linear relationship between journals and tenure but also contains a larger number of
journals. The main results do not change when using this ranking.journals. The main results do not change when using this ranking.
In Column 3, I allow journal rankings to change over time. I use historical rankingsIn Column 3, we allow journal rankings to change over time. We use historical rank-
of economics journals (drawn from Laband and Piette, 1994, and combined with currentings of economics journals (drawn from Laband and Piette, 1994, and combined with
rankings) and match each paper with its journal ranking at the time it was published. Us-current rankings) and match each paper with its journal ranking at the time it was pub-
ing these rankings accounts for journals moving in rank over time as well as new journalslished. Using these rankings accounts for journals moving in rank over time as well as new
being added. The coefficient on theFemale×Coauthoredinteraction is slightly smallerjournals being added. The coefficient on theFemale×Coauthoredinteraction is slightly
but the same pattern persists. An additional coauthored paper is associated with an 8.1smaller but the same pattern persists. An additional coauthored paper is associated with
percentage point increase in tenure probability for men and a 5.6 percentage point increasean 8.1 percentage point increase in tenure probability for men and a 5.6 percentage point
for women. In section 4, I also separate papers into "Top 5s" and "non-Top 5s".increase for women. In section 4, we also separate papers into “Top 5s” and “non-Top 5s”.
Finally, in Column 4, I divide the AER-equivalent measure into deciles and control forFinally, in Column 4, we divide the AER-equivalent measure into deciles and control
the number of solo and coauthored papers an individual has in each decile. For example,for the number of solo and coauthored papers an individual has in each decile. For ex-
if an individual publishes one solo-authored paper in the AER and another in the lowest-ample, if an individual publishes one solo-authored paper in the AER and another in the
rank journal, she will have one paper in the tenth bin, one in the first bin, and zero in thelowest-rank journal, she will have one paper in the tenth bin, one in the first bin, and
others. Thus, instead of having a single coauthored or solo-authored paper rank control,zero in the others. Thus, instead of having a single coauthored or solo-authored paper
I include ten variables controlling for the quality of an individual’s solo-authored papersrank control, we include ten variables controlling for the quality of an individual’s solo-
(the number of solo papers in each AER-equivalent bin) and ten variables controlling forauthored papers (the number of solo papers in each AER-equivalent bin) and ten variables
the quality of an individual’s coauthored paper (the number of coauthored papers in eachcontrolling for the quality of an individual’s coauthored paper (the number of coauthored
AER-equivalent bin). Again, the results hold.papers in each AER-equivalent bin). Again, the results hold.
1313
3.2.3 Tenure Definition3.2.3 Tenure Definition
In the main analysis, I only consider papers that were published up to and including theIn the main analysis, we only consider papers that were published up to and including the
year that an individual goes up for tenure. If an individual goes up for tenure in 1995,year that an individual goes up for tenure. If an individual goes up for tenure in 1995, for
for example, papers published in 1996 are not included in the paper count even thoughexample, papers published in 1996 are not included in the paper count even though they
they may have been “revise and resubmits” at the time of tenure. This could affect themay have been “revise and resubmits” at the time of tenure. This could affect the results if
results if men who coauthor have several promising unpublished papers at the time ofmen who coauthor have several promising unpublished papers at the time of tenure but
tenure but women who coauthor do not, in which case I am not actually comparing peoplewomen who coauthor do not, in which case we are not actually comparing people with
with similar publication records. In Columns 5 and 6 of Table 4, I include papers that aresimilar publication records. In Columns 5 and 6 of Table 4, we include papers that are
published one and two years after a person’s tenure year in the paper count variables. Thepublished one and two years after a person’s tenure year in the paper count variables. The
magnitude of the coefficients are smaller but the results do not change: women continuemagnitude of the coefficients are smaller but the results do not change: women continue
to benefit less from coauthored papers than men do.to benefit less from coauthored papers than men do.
3.2.4 Paper Count Variable3.2.4 Paper Count Variable
While I control for journal quality, the main independent variables (number of solo andWhile we control for journal quality, the main independent variables (number of solo and
coauthored papers) may not accurately reflect how tenure committees decide on tenurecoauthored papers) may not accurately reflect how tenure committees decide on tenure
cases. For example, institutions might trade off the quantity and quality of papers incases. For example, institutions might trade off the quantity and quality of papers in
different ways. In Column 7 of Table 4, I use an alternative measure for the number ofdifferent ways. In Column 7 of Table 4, we use an alternative measure for the number
papers. Specifically, after converting each publication to its AER-equivalent, I add upof papers. Specifically, after converting each publication to its AER-equivalent, we add
the AER-equivalent measure to give the total number of "AERs" an individual has at theup the AER-equivalent measure to give the total number of “AERs” an individual has
time of tenure. For example, if an individual published two solo-authored papers andat the time of tenure. For example, if an individual published two solo-authored papers
one is worth 0.25 AERs and the other worth 0.8 AERs, the individual will have 1.05 solo-and one is worth 0.25 AERs and the other worth 0.8 AERs, the individual will have 1.05
authored AERs at the time of tenure.solo-authored AERs at the time of tenure.
Again, the patterns are the same. An additional coauthored “AER” paper is correlatedAgain, the patterns are the same. An additional coauthored “AER” paper is correlated
with an 8.9 percentage point increase in a man’s tenure probability but a 5.3 percentagewith an 8.9 percentage point increase in a man’s tenure probability but a 5.3 percentage
point increase in a woman’s tenure probability.point increase in a woman’s tenure probability.
3.3 Testing Against Other Disciplines and Coauthoring Conventions3.3 Testing Against Other Disciplines and Coauthoring Conventions
Many disciplines use different coauthoring conventions, such as listing authors in orderMany disciplines use different coauthoring conventions, such as listing authors in order
of contribution. However, these disciplines differ on several other dimensions, such as theof contribution. However, these disciplines differ on several other dimensions, such as the
fraction of women in the disciplines and what is most important for tenure (publications,fraction of women in the disciplines and what is most important for tenure (publications,
grants, conference proceedings, etc.). In Appendix A, I conduct the same analysis for agrants, conference proceedings, etc.). In Appendix A, we conduct the same analysis for a
sample of sociologists, a discipline that order authors by contribution. The sample andsample of sociologists, a discipline that order authors by contribution. The sample and re-
results are discussed in more detail in the Appendix, but I do not find evidence of womensults are discussed in more detail in the Appendix, but we do not find evidence of women
being penalized for coauthoring. What matters is being first author on a paper: being firstbeing penalized for coauthoring. What matters is being first author on a paper: being first
author is correlated with a 5% increase in tenure probability for both men and women.author is correlated with a 5% increase in tenure probability for both men and women.
1414
Because sociology differs from economics in many ways, though, it is difficult to interpretBecause sociology differs from economics in many ways, though, it is difficult to interpret
whether these results suggest that ordering authors by contribution helps eliminate biaswhether these results suggest that ordering authors by contribution helps eliminate bias
or whether the larger presence of women helps to eliminate it.or whether the larger presence of women helps to eliminate it.
4 Channels4 Channels
The previous section established three facts:The previous section established three facts:
1. For very few papers, women have a lower tenure probability than men;1. For very few papers, women have a lower tenure probability than men;
2. As women produce more solo-authored papers, their tenure probability converges2. As women produce more solo-authored papers, their tenure probability converges
to that of comparable men;to that of comparable men;
3. Women benefit less than men from work coauthored with men.3. Women benefit less than men from work coauthored with men.
There are several explanations for these patterns. In this section, I argue that the results areThere are several explanations for these patterns. In this section, we argue that the results
most consistent with a story of women receiving less credit for their joint work with menare most consistent with a story of women receiving less credit for their joint work with
rather than a story of women contributing less when they work with men. I assume thatmen rather than a story of women contributing less when they work with men. We assume
tenure committees begin with the prior that women are on average lower ability than men,that tenure committees begin with the prior that women are on average of lower ability
and that solo-authored papers provide a clear signal of one’s ability whereas coauthoredthan men, and that solo-authored papers provide a clear signal of one’s ability whereas
papers provide an unclear signal. Employers then misattribute credit for work producedcoauthored papers provide an unclear signal. Employers then misattribute credit for work
by a man and a woman as the man is assumed to be higher ability.produced by a man and a woman as the man is assumed to be of higher ability.
I first test the claim by comparing the productivity of men and women who were de-We first test the claim by comparing the productivity of men and women who were
nied tenure. I then explore and rule out several threats to this story. Specifically, I test fordenied tenure. We then explore and rule out several threats to this story. Specifically, we
ability and preference-based sorting, women receiving less exposure by presenting less,test for ability and preference-based sorting, women receiving less exposure by presenting
and taste-based discrimination. Finally, I present evidence from an experiment designedless, and taste-based discrimination. Finally, we present evidence from two experiments
to shut down the possibility that women put in less effort when working with men, anddesigned to shut down the possibility that women put in less effort when working with
find that even in this context, women receive less credit than men when they perform amen, and find additional evidence that women receive less credit than men when they
stereotypically male task. However, women receive at least as much credit as men whenperform a stereotypically male task. Moreover, the gender of the person attributing credit
they perform a stereotypically female task.matters in this context, and we also find that women receive at least as much credit as men
when they perform a stereotypically female task.
4.1 Do Men Get the Credit or Do Women Contribute Less?4.1 Do Men Get the Credit or Do Women Contribute Less?
If tenure committees hold the prior that women are lower ability than men and if solo-If tenure committees hold the prior that women are lower ability than men and if solo-
authored papers provide clear signals of ability, we will see differences in tenure rates forauthored papers provide clear signals of ability, we will see differences in tenure rates for
men and women with few publications. However, additional solo-authored publicationsmen and women with few publications. However, additional solo-authored publications
of the same quality will have a larger marginal impact on a woman’s tenure probabilityof the same quality will have a larger marginal impact on a woman’s tenure probability
than a man’s. As these clear signals begin to dominate the committee’s prior, tenure rates
between men and women will converge.
1515
than a man’s. As these clear signals begin to dominate the committee’s prior, tenure rates
between men and women will converge.
If committees are biased toward giving men more credit for work coauthored withIf committees are biased toward giving men more credit for work coauthored with
women, we would expect to see the following. Assuming that there is some fixed amountwomen, we would expect to see the following. Assuming that there is some fixed amount
of credit that can be given for a paper, a man will benefit more than a woman from jointof credit that can be given for a paper, a man will benefit more than a woman from joint
work between them. In addition, both men and women will benefit more from their coau-work between them. In addition, both men and women will benefit more from their coau-
thored work with women than their coauthored work with men, as two men who coau-thored work with women than their coauthored work with men, as two men who coau-
thor will be assumed to have contributed similarly while a woman will be assumed tothor will be assumed to have contributed similarly while a woman will be assumed to
have contributed less.have contributed less.
These two claims largely play out in the data. Table 2 shows that the marginal solo-These two claims largely play out in the data. Table 2 shows that the marginal solo-
authored paper helps women more than it helps men as they start from a lower baselineauthored paper helps women more than it helps men as they start from a lower baseline
tenure rate. Table 3 shows that men benefit the most from coauthoring with women (antenure rate. Table 3 shows that men benefit the most from coauthoring with women (an
increase in tenure probability of 9.7% when coauthoring with a woman vs. 8.7% whenincrease in tenure probability of 9.7% when coauthoring with a woman vs. 8.7% when
coauthoring with a man) although this difference is insignificant. Similarly, women ben-coauthoring with a man) although this difference is insignificant. Similarly, women ben-
efit more from coauthoring with other women than with men. One result that it is in-efit more from coauthoring with other women than with men. One result that it is in-
consistent with a story of credit allocation is the fact that the total amount of credit thatconsistent with a story of credit allocation is the fact that the total amount of credit that
can be allocated, at least when all coauthors are men, seems to add up to more than one.can be allocated, at least when all coauthors are men, seems to add up to more than one.
Men benefit as much from a coauthored paper as they do from a solo-authored paper,Men benefit as much from a coauthored paper as they do from a solo-authored paper,
suggesting that tenure committees are either making a mistake when dividing credit (forsuggesting that tenure committees are either making a mistake when dividing credit (for
example, each committee assumes that the male author under consideration for tenureexample, each committee assumes that the male author under consideration for tenure
at its school did most of the work), or that there is an alternative mechanism behind theat its school did most of the work), or that there is an alternative mechanism behind the
results. In Section 4.2, I test several potential mechanisms.results. In Section 4.2, we test several potential mechanisms.
We would see these same empirical patterns if women contribute less to projects thatWe would see these same empirical patterns if women contribute less to projects that
are joint with men. Comparing the productivity of men and women who were deniedare joint with men. Comparing the productivity of men and women who were denied
tenure helps to disentangle these two stories. If women who coauthor are given less credit,tenure helps to disentangle these two stories. If women who coauthor are given less credit,
then women who coauthor and are denied tenure should on average be more productivethen women who coauthor and are denied tenure should on average be more productive
than men who are denied tenure. If women who coauthor simply contribute less, wethan men who are denied tenure. If women who coauthor simply contribute less, we
would not expect to see productivity differences between men and women who are deniedwould not expect to see productivity differences between men and women who are denied
tenure.tenure.
I use two productivity measures to test whether women who coauthor and are deniedWe use two productivity measures to test whether women who coauthor and are de-
tenure are more productive than men: the number of solo-authored AER-equivalents annied tenure are more productive than men: the number of solo-authored AER-equivalents
individual publishes after the tenure decision and the log number of citations an individ-an individual publishes after the tenure decision and the log number of citations an indi-
ual has as of 2015.vidual has as of 2015.
121312
Individuals who leave academia and do not publish after tenureIndividuals who leave academia and do not publish after tenure
are excluded from the AER-equivalent outcome sample, but including them and settingare excluded from the AER-equivalent outcome sample, but including them and setting
their number of post-tenure papers to zero does not change the results.
1212
Citations were scraped from Google scholar in 2015.Citations were scraped from Google scholar in 2015. For the top 5 papers outcome, we do not compare
13coauthored papers as these can reflect the ability of one’s coauthors. Citation data includes both solo and
For the top 5 papers outcome, I do not compare coauthored papers as these can reflect the ability ofcoauthored papers as the data came in this structure.
one’s coauthors. Citation data includes both solo and coauthored papers as the data came in this structure.
1616
their number of post-tenure papers to zero does not change the results.
Table 5 shows the results from estimatingTable 5 shows the results from estimating
YY
if stif st
11
femfem
ii
22
FracCAFracCA
itit
33
TT
ii
44
(fem(fem
ii
×FracCA×FracCA
itit
) +β) +β
55
(fem(fem
ii
×T×T
ii
))
66
(FracCA(FracCA
itit
×T×T
ii
) +β) +β
77
(FracCA(FracCA
itit
×T×T
ii
×Fem×Fem
ii
) +X)
Z
ii
γ+θ
ff
tt
pp
++
if stif st
(6)(6)
where the outcome variableYwhere the outcome variableY
if stif st
is one of the two productivity measures described aboveis one of the two productivity measures described above
andTandT
ii
is a tenure dummy. I include a post-tenure institution fixed effect,θis a tenure dummy. We include a post-tenure institution fixed effect,θ
pp
, to account for, to account
the fact that individuals will have access to different resources depending on where theyfor the fact that individuals will have access to different resources depending on where
go after the initial tenure decision.they go after the initial tenure decision.
Column 1 shows the results from estimating equation 6 with the number of solo-Column 1 shows the results from estimating equation 6 with the number of solo-
authored AER-equivalents as the outcome. Women who are denied tenure and coauthorauthored AER-equivalents as the outcome. Women who are denied tenure and coauthor
have 0.4 more solo-authored AER-equivalents than men who are denied tenure and coau-have 0.4 more solo-authored AER-equivalents than men who are denied tenure and coau-
thor. Column 2, which has log citations as the outcome variable, shows a similar patternthor (
although the results are much noisier. Together, these results provide some suggestiveˆ
evidence that these women receive less credit for joint projects.β
2
+
ˆ
β
4
). Column 2, which has log citations as the outcome variable, shows a similar
pattern although the results are much noisier. Together, these results provide some sug-
gestive evidence that these women receive less credit for joint projects.
4.2 Alternative Stories4.2 Alternative Stories
There are other possible explanations for the above findings, not all of which can be testedThere are other possible explanations for the above findings, not all of which can be tested
with these particular data. Here I shed light on four standard and testable channels:with these particular data. Here we shed light on four standard and testable channels:
ability-based sorting, preference-based sorting, women not claiming credit for their work,ability-based sorting, preference-based sorting, women not claiming credit for their work,
and taste-based discrimination. The empirical patterns are inconsistent with all of theand taste-based discrimination. The empirical patterns are inconsistent with all of the
proposed explanations.proposed explanations.
4.2.1 Ability-Based Sorting4.2.1 Ability-Based Sorting
Employers might rationally deny women who coauthor tenure if individuals sort suchEmployers might rationally deny women who coauthor tenure if individuals sort such
that only lower ability women coauthor with men. This could arise for several reasons.that only lower ability women coauthor with men. This could arise for several reasons.
For example, if coauthoring lowers the cost of producing a paper, but women know thatFor example, if coauthoring lowers the cost of producing a paper, but women know that
they receive less credit for papers, high ability women might forego the cost savings andthey receive less credit for papers, high ability women might forego the cost savings and
choose to work alone. They know they can produce high quality papers by themselveschoose to work alone. They know they can produce high quality papers by themselves
and send the employer a clearer signal of their ability. However, if low ability womenand send the employer a clearer signal of their ability. However, if low ability women
can only produce high quality papers with the help of a high ability man, they mightcan only produce high quality papers with the help of a high ability man, they might
coauthor even if they receive less credit. High ability men will agree to coauthor withcoauthor even if they receive less credit. High ability men will agree to coauthor with
them if it reduces the cost of the paper without reducing the quality. Employers wouldthem if it reduces the cost of the paper without reducing the quality. Employers would
then know that any woman coauthoring with a man is lower ability.
1717
then know that any woman coauthoring with a man is lower ability.In what follows, we test whether women anticipate receiving less credit, whether high
In what follows, I test whether women anticipate receiving less credit, whether high
ability women sort out of coauthoring with men, and whether men coauthor with womenability women sort out of coauthoring with men, and whether men coauthor with women
whose careers begin more slowly. To do so, I first present survey evidence suggestingwhose careers begin more slowly. To do so, we first present survey evidence suggesting
that women do not know that the returns to coauthoring are lower than solo-authoring.that women do not know that the returns to coauthoring are lower than solo-authoring.
I then show that women do receive some credit for papers that publish well, suggestingWe then show that women do receive some credit for papers that publish well, suggesting
that employers might believe that there is some assortative matching. I also provide evi-that employers might believe that there is some assortative matching. We also provide
dence that even when women tend to work with men who are slightly higher ability thanevidence that even when women tend to work with men who are slightly higher ability
themselves this unequal match does not explain the gender gap in tenure.than themselves this unequal match does not explain the gender gap in tenure.
Survey Evidence on Knowledge of Returns to CoauthoringIf women know that theirSurvey Evidence on Knowledge of Returns to CoauthoringIf women know that their
returns to coauthoring with men are low, it is plausible that high ability women wouldreturns to coauthoring with men are low, it is plausible that high ability women would
choose to solo-author or only work with other women. Here I test whether women antici-choose to solo-author or only work with other women. Here we test whether women
pate receiving less credit for collaborative work using a survey conducted with economistsanticipate receiving less credit for collaborative work using a survey conducted with
currently working at the top 35 U.S. economics departments. The survey was sent to alleconomists currently working at the top 35 U.S. economics departments. The survey
professors, regardless of rank, at these institutions and received an 32% response rate.was sent to all professors, regardless of rank, at these institutions and received an 32%
The gender composition of the sample is representative of the profession today, with 89response rate. The gender composition of the sample is representative of the profession
respondents being female and 300 being male. In the survey, economists were asked thetoday, with 89 respondents being female and 300 being male. In the survey, economists
following question:were asked the following question:
Suppose a solo-authored AER increases your chance of receiving tenure by 15%. For each ofSuppose a solo-authored AER increases your chance of receiving tenure by 15%. For each of
the following, please give an estimate of how much you think the described paper would increasethe following, please give an estimate of how much you think the described paper would increase
your chance of receiving tenure.your chance of receiving tenure.
Respondents then go through five types of papers (coauthored AER, coauthored AERRespondents then go through five types of papers (coauthored AER, coauthored AER
with senior faculty, coauthored AER with junior faculty, solo-authored top field, and coau-with senior faculty, coauthored AER with junior faculty, solo-authored top field, and coau-
thored top field) and record their beliefs about the returns to these papersthored top field) and record their beliefs about the returns to these papers.
13
In Table 6, we test the difference in the mean beliefs of men and women.
1414
.There
In Table 6, I test the difference in the mean beliefs of men and women.is no statistically significant difference in the beliefs of men and women for any type of
15
There is
no statistically significant difference in the beliefs of men and women for any type of
paper. Men believe that a coauthored AER will increase their chance of receiving tenure bypaper. Men believe that a coauthored AER will increase their chance of receiving tenure by
12.1%, and women by 12.2%. Women believe that there are slightly lower returns to AER12.1%, and women by 12.2%. Women believe that there are slightly lower returns to AER
papers coauthored with senior faculty (8.8% versus 9.1% for men), but the difference is notpapers coauthored with senior faculty (8.8% versus 9.1% for men), but the difference is not
statistically significant. These results suggest that, in this context, women are unaware ofstatistically significant. These results suggest that, in this context, women are unaware of
the true returns to coauthoring.
13
We did not ask respondents about paper coauthored with men/women so that they would not be
primed to think about gender
1414
I did not ask respondents about paper coauthored with men/women so that they would not be primedBecause the survey was anonymous, the answers can not be linked to the CV data. We can therefore
to think about genderonly test for differences in means without controls.
15
Because the survey was anonymous, the answers can not be linked to the CV data. I can therefore only
test for differences in means without controls.
1818
the true returns to coauthoring.Evidence on Sorting by Ability from CVsA second test of whether women know that
C.V. Evidence on Sorting by AbilityA second test of whether women know that theythey will receive less credit for papers and sort accordingly is to look at the correlation
will receive less credit for papers and sort accordingly is to look at the correlation betweenbetween propensity to coauthor and ability. We first test whether high ability women
propensity to coauthor and ability. I first test whether high ability women are less likelyare less likely to coauthor than low ability women and then test for assortative matching
to coauthor than low ability women and then test for assortative matching among coau-among coauthors. We proxy for ability using the quality of journal that an individual’s
thors. I proxy for ability using the quality of journal that an individual’s job market paperjob market paper was published in. We assume that the job market paper is the first solo-
was published in. I assume that the job market paper is the first solo-authored paper anauthored paper an individual publishes after he or she graduates.
individual publishes after he or she graduates.
If women anticipate discrimination, ability and the fraction of one’s papers that areIf women anticipate discrimination, ability and the fraction of one’s papers that are
coauthored will be negatively correlated. High ability women should be less likely tocoauthored will be negatively correlated. High ability women should be less likely to
coauthor. In Figure 5.A I plot the coefficientscoauthor. In Figure 5.A we plot the coefficients
ˆˆ
ββ
11
andand
ˆˆ
ββ
22
from estimatingfrom estimating
FracCAFracCA
if stif st
11
aa
ii
22
(fem(fem
ii
×a×a
ii
) +β) +β
33
femfem
ii
44
TotPapersTotPapers
ii
ff
ss
tt
++
if stif st
(7)(7)
whereFracCAwhereFracCA
if stif st
is the fraction of personi’s papers that are coauthored andais the fraction of personi’s papers that are coauthored anda
ii
is personis person
i’s ability (job market paper rank). If high ability women anticipate receiving less credit,i’s ability (job market paper rank). If high ability women anticipate receiving less credit,
we expectwe expect
ˆˆ
ββ
22
<0. In Figure 5.A, however, we see that ability is uncorrelated with the<0. In Figure 5.A, however, we see that ability is uncorrelated with the
fraction of papers that are coauthored for both men and women: both estimates are precisefraction of papers that are coauthored for both men and women: both estimates are precise
zeros. There is no evidence that women along the ability distribution act strategically inzeros. There is no evidence that women along the ability distribution act strategically in
their choice to coauthor versus solo author.their choice to coauthor versus solo author.
I also find no evidence that high ability women strategically coauthor with other womenWe also find no evidence that high ability women strategically coauthor with other
rather than men. Figure 5.B plots the results from equation 7 using the fraction of paperswomen rather than men. Figure 5.B plots the results from equation 7 using the fraction
that are coauthored with women as the dependent variable. Women are more likely toof papers that are coauthored with women as the dependent variable. Women are more
coauthor with other women than men are but there is no sorting by ability.likely to coauthor with other women than men are but there is no sorting by ability.
While women do not seem to be sorting according to ability, it is possible that womenWhile women do not seem to be sorting according to ability, it is possible that women
tend to work with higher-ability or more prominent coauthors who then receive moretend to work with higher-ability or more prominent coauthors who then receive more
credit for a paper. I test for this by correlating a person’s ability with that of his or hercredit for a paper. We test for this by correlating a person’s ability with that of his or her
coauthors. While I do not have the job market paper information for all coauthors in thecoauthors. While we do not have the job market paper information for all coauthors in
dataset, I can see where the coauthors were working at the time the individual went up forthe dataset, we can see where the coauthors were working at the time the individual went
tenure. As a measure of average coauthor ability, I take the average school rank of all of anup for tenure. As a measure of average coauthor ability, we take the average school rank
individual’s pre-tenure coauthors. For example, ificoauthors withjandkandjworks atof all of an individual’s pre-tenure coauthors. For example, ificoauthors withjandk
the 5th-ranked institution andkworks at the 15th-ranked institution, the average abilityandjworks at the 5th-ranked institution andkworks at the 15th-ranked institution, the
ofi’s coauthors is 10.average ability ofi’s coauthors is 10.
I correlatei’s ability with the average ability of her coauthors in Figure 6. The line ofWe correlatei’s ability with the average ability of her coauthors in Figure 6. The line
best fit is plotted controlling for number of coauthored and solo-authored publications,of best fit is plotted controlling for number of coauthored and solo-authored publications,
time until tenure, and field, institution, and tenure year fixed effects.
Men and women both sort positively on ability but women are more likely to collab-
1919
time until tenure, and field, institution, and tenure year fixed effects.
Men and women both sort positively on ability but women are more likely to collab-
orate with individuals at more highly-ranked institutions than men are. To see whetherorate with individuals at more highly-ranked institutions than men are. To see whether
this explains the main results, I estimatethis explains the main results, we estimate
TT
if stif st
11
SS
ii
22
(fem(fem
ii
×S×S
ii
) +β) +β
33
CACA
ii
44
(fem(fem
ii
×CA×CA
ii
) +β) +β
55
rankrank
iJiJ
66
(CA(CA
ii
×rank×rank
iJiJ
) +β) +β
77
(fem(fem
ii
×CA×CA
ii
×rank×rank
iJiJ
) +β) +β
88
(fem(fem
ii
×rank×rank
iJiJ
))
99
femfem
ii
ZZ
ii
ff
ss
tt
++
if stif st
(8)(8)
whererankwhererank
iJiJ
is the average institution rank ofi’s coauthors and all other variables areis the average institution rank ofi’s coauthors and all other variables are
defined as before. The results are reported in Table 7. If men receive more credit becausedefined as before. The results are reported in Table 7. If men receive more credit because
they are coauthoring with lower ability women,they are coauthoring with lower ability women,
ˆˆ
ββ
77
should be negative. However,should be negative. However,
ˆˆ
ββ
77
isis
close to zero, indicating that the ability or prominence of one’s coauthor is not driving theclose to zero, indicating that the ability or prominence of one’s coauthor is not driving the
tenure gap for coauthoring women.tenure gap for coauthoring women.
Returns to Top PapersFor high ability women to receive no credit for their coauthoredReturns to Top PapersFor high ability women to receive no credit for their coauthored
papers, employers would have to believe that there is no assortative matching by abil-papers, employers would have to believe that there is no assortative matching by ability.
ity. Otherwise, employers would receive a signal that women who coauthor with highOtherwise, employers would receive a signal that women who coauthor with high abil-
ability men are also high ability, and be more likely to promote them. Figure 6 showsity men are also high ability, and be more likely to promote them. Figure 6 shows that
that assortative matching does occur, but it is possible that employers do not recognizeassortative matching does occur, but it is possible that employers do not recognize this.
this. I test for this by looking at how credit for top 5 publications is allocated. If employ-We test for this by looking at how credit for top 5 publications is allocated. If employ-
ers know that there is assortative matching, they should believe that women coauthoringers know that there is assortative matching, they should believe that women coauthoring
with high-ability men are also likely to be high ability.with high-ability men are also likely to be high ability.
Table 8 shows the results from estimatingTable 8 shows the results from estimating
TT
ifstifst
11
TopSTopS
ii
22
(fem(fem
ii
×TopS×TopS
ii
) +β) +β
33
TopCATopCA
ii
44
(fem(fem
ii
×TopCA×TopCA
ii
) +β) +β
55
NonTopSNonTopS
ii
66
NonTopCANonTopCA
ii
77
(fem(fem
ii
×NonTopS×NonTopS
ii
) +β) +β
88
(fem(fem
ii
×NonTopCA×NonTopCA
ii
) +β) +β
99
femfem
ii
ZZ
ii
ff
ss
tt
++
ifstifst
(9)(9)
whereTopSwhereTopS
ii
andTopCAandTopCA
ii
are the number of solo and coauthored papers that individualiare the number of solo and coauthored papers that individuali
has published in a top 5 journal. Similarly,NonTopShas published in a top 5 journal. Similarly,NonTopS
ii
andNonTopCAandNonTopCA
ii
are the number ofare the number of
solo and coauthored papers the individual has published in non-top 5 journals. In Tablesolo and coauthored papers the individual has published in non-top 5 journals. In Table
8, the “nop-top 5” interaction terms are presented in the second column.8, the “nop-top 5” interaction terms are presented in the second column.
Power becomes an issue as (1) there are relatively few people publishing in the topPower becomes an issue as (1) there are relatively few people publishing in the top
5 journals, and (2) cutting by gender means that there are even fewer women in each5 journals, and (2) cutting by gender means that there are even fewer women in each
category.category.
Table 8 shows that coauthored papers published in a top 5 journal help women muchTable 8 shows that coauthored papers published in a top 5 journal help women much
20
more than those published in non-top 5 journals. Non-top 5 coauthored papers do notmore than those published in non-top 5 journals. Non-top 5 coauthored papers do not
have any positive influence on women’s tenure probability. It seems that employers re-have any positive influence on women’s tenure probability. It seems that employers re-
20
ceive some signal when a woman publishes her coauthored papers in top journals whichceive some signal when a woman publishes her coauthored papers in top journals which
is at odds with the hypothesis that only low ability women coauthor with men.is at odds with the hypothesis that only low ability women coauthor with men.
Overall, there is little evidence that ability-based sorting is driving the results.Overall, there is little evidence that ability-based sorting is driving the results.
1615
IfIf
anything, employers seem to recognize that high ability men and women might workanything, employers seem to recognize that high ability men and women might work
together and are therefore more likely to grant these women tenure. However, their tenuretogether and are therefore more likely to grant these women tenure. However, their tenure
rate is still lower than that of high ability men.rate is still lower than that of high ability men.
4.2.2 Preference-Based Sorting4.2.2 Preference-Based Sorting
If women prefer to coauthor with senior faculty, we could reasonably expect that womenIf women prefer to coauthor with senior faculty, we could reasonably expect that women
would have lower tenure rates. Assuming senior faculty are more likely to be creditedwould have lower tenure rates. Assuming senior faculty are more likely to be credited
for a paper, the fact that most senior faculty are men would drive the correlation betweenfor a paper, the fact that most senior faculty are men would drive the correlation between
coauthoring with a man and tenure. That is, women receive less credit because they enjoycoauthoring with a man and tenure. That is, women receive less credit because they enjoy
coauthoring with senior faculty and these senior faculty are predominantly male.coauthoring with senior faculty and these senior faculty are predominantly male.
The basic summary statistics showed that women were not more likely to coauthorThe basic summary statistics showed that women were not more likely to coauthor
with senior faculty than men. However, I conduct an additional test as to whether coau-with senior faculty than men. However, we conduct an additional test as to whether
thorship with senior faculty could be driving the results. I reestimate equation 3 but con-coauthorship with senior faculty could be driving the results. We reestimate equation 3
trol for the fraction of a person’s coauthors who are senior. The results are presented inbut control for the fraction of a person’s coauthors who are senior. The results are pre-
Column 3 of Table 7. The seniority of women’s coauthors does not explain the results.sented in Column 3 of Table 7. The seniority of women’s coauthors does not explain the
Controlling for seniority, an additional coauthored paper increases a man’s probability ofresults. Controlling for seniority, an additional coauthored paper increases a man’s prob-
tenure by 8 percentage points but a woman’s by 5 percentage points.ability of tenure by 8 percentage points but a woman’s by 5 percentage points.
4.2.3 Timing of Coauthorship4.2.3 Timing of Coauthorship
It is possible that men offer to work with women who are struggling to publish. If thisIt is possible that men offer to work with women who are struggling to publish. If this is
is the case, we should see women who have few publications in the early years of theirthe case, we should see women who have few publications in the early years of their ap-
appointment being more likely to coauthor with men. I test for this possibility by lookingpointment being more likely to coauthor with men. We test for this possibility by looking
at differences in early publications and by testing whether women with a longer time lagat differences in early publications and by testing whether women with a longer time lag
between their initial appointment and first publication are more likely to coauthor withbetween their initial appointment and first publication are more likely to coauthor with
men.men.
16Appendix Figure B1 descriptively shows the timing of publications for men and women,
split by whether they received tenure at their initial tenure institution. More formally, we
15
Garcia and Serman (2015) show that there could be selection into coauthorship driven by a desire toGarcia and Serman (2015) show that there could be selection into coauthorship driven by a desire to
be first author on a paper (that is, depending on where you are in the alphabet relative to your coauthors).be first author on a paper (that is, depending on where you are in the alphabet relative to your coauthors).
This would be an issue in this setting if, for example, men are more likely to be strategic than woman andThis would be an issue in this setting if, for example, men are more likely to be strategic than woman and
are therefore more likely to be first author on a paper (which is correlated with having more citations). Iare therefore more likely to be first author on a paper (which is correlated with having more citations). We
test whether men are more likely to be first author on their papers than women and whether men have atest whether men are more likely to be first author on their papers than women and whether men have a
“higher” author position overall. I find that men in my sample are first author 57% of the time while women“higher” author position overall. We find that men in our sample are first author 57% of the time while
are first author 55% of the time (p-value = 0.907).women are first author 55% of the time (p=0.907).
2121
Figure 7 descriptively shows the timing of publications for men and women, splittest whether women have fewer publications early in their careers by estimating
by whether they received tenure at their initial tenure institution. More formally, I test
whether women have fewer publications early in their careers by estimating
YY
if stif st
11
FemFem
ii
22
TT
isis
33
(Fem(Fem
ii
×T×T
isis
) +β) +β
44
PapersPapers
ii
55
̄q ̄q
ii
ff
ss
tt
++
if stif st
(10)(10)
whereYwhereY
if stif st
is the number of years between individuali’s initial appointment andi’s firstis the number of years between individuali’s initial appointment andi’s first
post-appointment publication.post-appointment publication.
1716
I test whether women who did not receive tenure hadWe test whether women who did not receive tenure had
a longer publishing lag by interacting the female dummy term with an indicator for re-a longer publishing lag by interacting the female dummy term with an indicator for re-
ceiving tenure at schools,Tceiving tenure at schools,T
isis
. I control for the number of papers published pre-tenure. We control for the number of papers published pre-tenure
(Papers(Papers
ii
) and the average quality of those papers ( ̄q) and the average quality of those papers ( ̄q
ii
) All other variables are defined as). All other variables are defined as
before.before.
The results are presented in Table 9. Women who do not receive tenure do have aThe results are presented in Table 9. Women who do not receive tenure do have a
longer lag (approximately 0.5 years) between their first appointment and their first publi-longer lag (approximately 0.5 years) between their first appointment and their first publi-
cation although the result is noisily estimated. I test whether women with a longer lag arecation although the result is noisily estimated. We test whether women with a longer lag
more likely to coauthor with men by estimatingare more likely to coauthor with men by estimating
FracMFracM
if stif st
11
FemFem
ii
22
TT
isis
33
(Fem(Fem
ii
×T×T
isis
) +β) +β
44
YY
ii
55
(Fem(Fem
ii
×Y×Y
ii
))
66
(Fem(Fem
ii
×T×T
isis
×Y×Y
ii
) +β) +β
44
PapersPapers
ii
55
̄q ̄q
ii
ff
ss
tt
++
if stif st
(11)(11)
where the outcome variable,Ywhere the outcome variable,Y
ii
in equation 10 is used as a regressor. If men bring womenin equation 10 is used as a regressor. If men bring women
with a slow start to publishing onto their projects, we would expect to seewith a slow start to publishing onto their projects, we would expect to see
ˆˆ
ββ
55
>0.>0.
The results, presented in Column 2 of Table 9, do not support the hypothesis thatThe results, presented in Column 2 of Table 9, do not support the hypothesis that
women who struggle to publish initially are more likely to begin publishing with men.women who struggle to publish initially are more likely to begin publishing with men.
The coefficient onβThe coefficient onβ
55
is negative, suggesting that women with a longer publishing lag areis negative, suggesting that women with a longer publishing lag are
less likely to coauthor with men although this result is again insignificant.less likely to coauthor with men although this result is again insignificant.
4.2.4 Women Not Claiming Credit for Papers4.2.4 Women Not Claiming Credit for Papers
Women might be given less credit for their work if they are less likely to claim it as theirWomen might be given less credit for their work if they are less likely to claim it as their
own. For example, if women present less frequently than men, people might associate aown.
17
For example, if women present less frequently than men, people might associate a
paper with the male coauthor who presents it more. The survey discussed in Section 4.2.1paper with the male coauthor who presents it more. The survey discussed in Section 4.2.1
also asked individuals how many times per year they present their work and whetheralso asked individuals how many times per year they present their work and whether
they are more or less likely to present their coauthored papers than their coauthor. Panelthey are more or less likely to present their coauthored papers than their coauthor. Panel
B of Table 6 shows that men and women report the same likelihood of presenting theirB of Table 6 shows that men and women report the same likelihood of presenting their
joint papers relative to their coauthors. Interestingly, though, women present their solo-joint papers relative to their coauthors. Interestingly, though, women present their solo-
authored papers fewer times per year than men do. It is possible that women do not
16
We exclude papers that were published before the person’s first appointment.
1717
I exclude papers that were published before the person’s first appointment.Isaksson (2019) finds experimental evidence that women often claim less credit than men for their con-
tributions to solving puzzles.
2222
authored papers fewer times per year than men do. It is possible that women do not“advertise” their work as much as men do and this leads to women receiving less recog-
"advertise" their work as much as men do and this leads to women receiving less recogni-nition for their work in general. If this were true, though, women who solo author should
tion for their work in general. If this were true, though, women who solo author should
also be less likely to receive tenure.also be less likely to receive tenure.
4.2.5 Taste-Based Discrimination4.2.5 Taste-Based Discrimination
If some employers have a distaste for tenuring women, as in Becker (1971), we should seeIf some employers have a distaste for tenuring women, as in Becker (1971), we should see
women who write solo-authored papers being denied tenure as well. If employers cannotwomen who write solo-authored papers being denied tenure as well. If employers cannot
plausibly deny a woman who solo-authored several well-published papers, however, theyplausibly deny a woman who solo-authored several well-published papers, however, they
might be constrained to deny tenure only to those for whom they can make a reasonablemight be constrained to deny tenure only to those for whom they can make a reasonable
case. If it can be argued that a woman who coauthors did little of the work, taste-basedcase. If it can be argued that a woman who coauthors did little of the work, taste-based
discrimination could help to explain the results as employers have an excuse for denyingdiscrimination could help to explain the results as employers have an excuse for denying
tenure to coauthoring women. However, as shown in Table 3, only women who coauthortenure to coauthoring women. However, as shown in Table 3, only women who coauthor
with men have lower tenure rates. This would imply that employers have a particularwith men have lower tenure rates. This would imply that employers have a particular
distaste for tenuring women who coauthor with men, which seems unlikely.distaste for tenuring women who coauthor with men, which seems unlikely.
5 Experimental Evidence5 Experimental Evidence
In the previous section, I provided suggestive evidence that factors like sorting and taste-In the previous section, we provided suggestive evidence that factors like sorting and
based discrimination do not explain why women who coauthor with men are less likelytaste-based discrimination do not explain why women who coauthor with men are less
to receive tenure. I instead argue that the results are most consistent with women receiv-likely to receive tenure. We instead argue that the results are most consistent with women
ing less credit for joint work with men. Specifically, because coauthored signals are anreceiving less credit for joint work with men. Specifically, because coauthored papers
unclear signal of ability, women receive less credit for their joint work with men if theyare an unclear signal of ability, women receive less credit for their joint work with men
are believed to be lower ability. I cannot rule out, though, that real of perceived differ-if they are believed to be of lower ability (Correll and Ridgeway, 2003). We cannot rule
ences in effort explain the results. For example, tenure committees might hold the beliefout, though, that real or perceived differences in effort explain the results. For example,
that women contribute less or lower effort when they work with men, regardless of theirtenure committees might hold the belief that women contribute less or provide lower
beliefs about a woman’s ability. In addition, tenure committees might believe that loweffort when they work with men, regardless of their beliefs about a woman’s ability. In
ability women choose to work with high ability men even if the empirical evidence sug-addition, tenure committees might believe that low ability women choose to work with
gests otherwise.high ability men even if the empirical evidence suggests otherwise.
To shed light on whether effort or perceptions of effort and sorting are driving theTo shed light on whether different contributions to group work (or perceptions of dif-
results, I run an experiment on mTurk that is designed to shut down these channels. I alsoferential contributions) and sorting are driving the results, we run two experiments de-
test whether differences in the allocation of credit depend on whether the associated task issigned to shut down these channels. The experiments also allow us to assess the role of
male or female-stereotyped, which speaks to whether beliefs about ability are driving thebeliefs about ability more directly. The first experiment is an artefactual experiment run on
results. In a female-stereotyped or gender-neutral task, we would not expect there to bemTurk. The second is a framed field experiment for which we recruited individuals who
differences in beliefs about men and women’s abilities. Although this setting is differentwork in human resources and whose job is to recruit personnel. Although these settings
are different from academia, they provide additional evidence that gender plays a role in
2323
from academia, it provides additional evidence that gender plays a role in the allocationthe allocation of credit due to differences in beliefs about the ability of men and women.
of credit and that differences in credit are not driven by sorting or effort.The first does so in a relatively abstract setting with high control, while the second adds
5.1 Experiment Designmore context from the process of hiring candidates (see Harrison and List, 2004).
The experiment consists of two incentivized parts and follows a two-by-two randomiza-Both experiments consist of two incentivized parts. In the first step, workers are re-
tion design. In the first step, mTurk workers are recruited to complete two math quizzescruited to complete tasks individually. In the second step, designed to test whether people
(male-stereotyped) or two grammar quizzes (female-stereotyped), each containing fivemisallocate credit for joint work, another set of individuals are recruited to either predict
questions.how well the workers will do on a second set of related tasks (Experiment I) or to choose
a worker to hire to perform a second set of tasks (Experiment II). In both experiments, we
vary whether the predictors/hirers see workers’ individual scores in the first task, or the
sum of two or more individuals’ scores.
5.1 Experiment I
The first experiment consists of two incentivized parts. In the first step, mTurk workers,
henceforth referred to as “workers” are recruited to complete two related quizzes (Quiz 1
and Quiz 2).
1818
I refer to the two quizzes as Quiz 1 and Quiz 2. These workers, hereafterWe then recruit 506 mTurk participants, referred to as “predictors”, to pre-
called “quiz-takers”, received $0.30 for participating in the study as well as $0.05 for eachdict the Quiz 2 scores of a randomly-chosen man and a randomly-chosen woman on Quiz
question they answer correctly.