Emily Eisner and Megan Lang
with reflections contributed by Karl Dunkle Werner, Gabe Englander, Scott Kaplan, and Derek Wolfson
“What can I do?” We heard that question from many men in our field in the wake of Alice Wu’s paper and, more broadly, the #MeToo movement this fall. We thought about writing a “How to be an ally” post for economists. Instead, we asked four aspiring allies in our field to find out how to be an ally for themselves, then compile that knowledge for others who would like to know.
We’ve organized the content from their numerous interviews with women and minority faculty and grad students in our field at UC Berkeley here. These are resource pages that we’ll continue to build and update over time.
We also asked all four men to write reflections on their learning throughout this process. To some, these reflections may seem all too familiar. To some they may be revelatory. Some people may disagree with what they read, or feel disempowered by the thought that white men have any role to play in improving opportunities for women and minorities in the field. Some may find that these reflections resonate deeply. The one thing that is clear is that none of us has all the answers and that people’s experiences cannot be reduced into one tidy lesson.
By offering the four reflections below, we hope to
There is not one way to be an ally just as there is not one correct way to mitigate discrimination in our field. Below are four reflections from the male graduate students we asked to help us write a blog post. We hope they spark thought and conversation. Feel free to reach out to us with any reactions or stories of your own.
Before this process, I hadn’t given thought to what my gender meant in terms of my relationship with my advisor. We are both men, and we have been able to build a strong relationship both at work and outside of it. This relationship has undoubtedly improved my education and ability to do good research.
I took for granted that every graduate student may not have a similar relationship with their mentor. But a point that came up again and again in interviews and the process of writing this blog was how the power dynamics associated with advisors and advisees were inflated by gender dynamics between these two parties. I was educated by a woman, who said that “the point here is not that women want to completely shut down informal activities with advisors, but that navigating those situations one-on-one is more fraught for them.”
I came to understand that it's an additional burden for a woman to have to think about the implications of their relationships with their advisors more seriously than I do. At the same time, advisors may face the same calculation and have difficulty in offering opportunities to advisees of different races and genders. This can have serious academic consequences. We as males need to be cognizant of this calculus; we can suggest that our advisors try to plan activities where all of their advisees can participate, and when we become professors or take on other positions, we can work to create group activities that are comfortable for and inclusive of everyone.
The first year of an econ PhD program is hard. It’s an enormous amount of math, a slew of all-day problem sets, and an endless stream of opportunities to bang your head against the wall. Sitting down with my classmates who tackled first year while raising a family was eye-opening. With large chunks of time occupied by children, problem sets and research are pushed to late nights or early mornings. Choosing when I work is a privilege I had never considered. Those with family responsibilities may have schedules precluding group-work and opportunities to compare notes. Young white guys are disproportionately free of these responsibilities, one of many factors entrenching existing disparities. There have been some attempts in the field to accommodate parents, but coming up with a solution is not easy. We need to think harder about how graduate school’s demanding workload interacts with existing social structures, making the field particularly unwelcoming for women and economists of color.
At a more individual level, my conversations with classmates highlighted how important it can be, in moments of self-doubt, to hear that other people also struggle. In our conversations, people repeatedly brought up how much an affirming word can matter, and how big a deal it is to know that other people face similar challenges. I had always considered myself implicitly supportive, available when someone tells me they need a hand. That’s not enough. I need to do a better job checking in, making sure my classmates are doing well, and celebrating their successes (in grad school and beyond).
Shortly after beginning his PhD, K remembers asking the professor who helped recruit him, “Where are all the black and African people?” K, one of only a couple of black students in the department, said that it would have been helpful if someone—a staff member, faculty, or another student—had explicitly acknowledged this fact and talked about some of the things he might expect to feel over the next 5+ years.
For example, K felt an extra layer of imposter syndrome at the beginning of his PhD program (the garden variety is familiar to many graduate students). Academic setbacks were especially painful because he feared they suggested to others that he was not accepted to his program on his merits.
K also regularly wonders how his identity influences how others interact with him. For instance, when he visited Berkeley after being accepted, a professor asked him what he scored on the math section of the GRE. Does this professor ask this question to most prospective students, or did this professor ask because K is black and African?
I had not previously considered that non-white, non-male economists have less control over how they are perceived. This lack of control creates pressure to make decisions that satisfy other people’s expectations. I don’t face this pressure. Importantly, all this time spent thinking about how one is perceived takes away attention from research. I already find graduate school to be emotionally and intellectually harrowing at times; all of us should try to relieve the additional burden that women and minority students experience. So I will reflect on the stereotypes and biases that I hold, and try not to impose them on others, especially when I am in a position of power. I will also try to take K’s advice and have more conversations that explicitly acknowledge identity and how it influences individuals’ experiences in economics.
My participation in these interviews spurred an intense inner dialogue on what it means to actually be an ally. Before, I called myself an ally but now I’m beginning to understand how to put words into action. I’ve come to the conclusion that being well-intentioned is simply not good enough.
I’ve become more cognizant of the things I get for free by being a straight, white male. I don’t have to analyze the implication of walking for a coffee with my male advisor. I don’t have to act “less feminine” to gain the respect of my peers. I don’t have to worry about uncomfortable one-on-one interviews with male faculty in private hotel rooms during the job market.
These interviews also propelled me to query my own experience and reflect on if I ever consciously or unconsciously made it difficult for women and minorities in economics. I had. Did I ever call women “dudes” or refer to groups of women as “guys”? Yes. Was I more likely to interrupt women in conversations? Probably. Did I react to research differently because the author was a woman? I hoped not but I could not be 100% sure.
Truly being an ally will be an everyday learning process. My involvement with this blog post has already spurred some formative changes but I do not know everything. As a start, I now often ask myself: “Did I read this paper/treat this person/react to seminar comments/write this email/grade this paper/conduct office hours/etc. differently because this person is a woman/minority?” If I’m not sure, I will ask a friend so I may continue learning how to be an effective ally.
We’d like to extend our profound thanks to all of the people we interviewed, to our classmates in ARE, Econ, and Haas, and to WEB. We’re all going to make mistakes, but we’re keeping this conversation open so we can learn and improve. Please join us!
This month, I had the pleasure of speaking with Alice Wu, the UC Berkeley graduate who, in her thesis, exposed the gendered and sexist language used to describe women on EJMR, a website used widely by economists to disseminate information on PhD job market candidates. During our discussion, Wu and I discussed her intellectual motivation as well as the material consequences of her work. To Wu, her thesis was an exercise in producing thorough economic research and exploring how to employ modern machine learning methods to examine economically interesting labor market interactions. However, with the explosion of her work in the news and into the consciousness of the economic field, Wu recognizes the value of her work in spurring an important conversation among economists regarding how we can make our field more inclusive.
The transcript of our conversation has been lightly edited for readability.
EE: What led you to study EJMR?
AW: Honestly, it was a bit unexpected. I was picking a research topic for my senior thesis. I had worked for David Card for a semester before and he was going to be my advisor. In a conversation while I was debating research topics, he pointed out that there was a controversy going on at the time regarding EJMR and asked whether I would be interested in studying that platform. I had taken a machine learning course where I had gotten some experience with text analysis, so I decided to see if I could employ those skills while writing my thesis.
EE: Were you familiar with EJMR as an undergrad, before coming up with your research project?
AW: I first heard about EJMR during my junior year of college at UC Berkeley. I had some friends who were also undergrads and were interested in reading online reviews of their professors, and so they found the website. These were male friends and they knew I wanted to go to graduate school in economics, so I remember them showing me and saying “look, these [are] going to be your future colleagues!” I was shocked when I saw the explicit sexual content of posts and the racism and sexism on the website. When I asked my friends who were graduate students at Cal if they knew of the website they seemed really embarrassed.
EE: What has been the most challenging part of this research project for you?
AW: The most challenging part was definitely the beginning, after I had the raw text data and had done the cleaning of the dataset. I was thinking about what to look at and the first thing that I tried was sentiment analysis, which I had used in my machine learning course. However, many of the online open-source packages that perform sentiment analysis on text are built for specific styles of text or types of documents. For example, the sentiment analysis picked out the comments about women as beautiful as “positive” comments. When I saw that the algorithm I was using picked out the comments about women’s appearance as “positive” I realized the sentiments assumed by the algorithm didn’t match the purpose of the forum. It didn’t feel right or appropriate to me to discuss people’s physical appearance on EJMR, so it seemed strange to label it as positive. At that point, I had to take a step out of the pre-existing packages and think about what I wanted to get out of the data and what my actual questions were. That was the most challenging part of the research project.
EE: It’s exciting that you were able to apply machine learning and text analysis techniques in your thesis. What was your first experience using machine learning techniques and how do you see them contributing to economics?
AW: The project I did in my machine learning class at UC Berkeley was a sentiment analysis of tweets on twitter. I looked at whether tweets were positive or negative using LASSO to pick up positive or negative terms.
The machine learning literature is very different from the economics literature in terms of what type of analysis they are performing. It seems to me that overall, people who study machine learning only care about the prediction power of a model, rather than estimating and studying the relationship between two variables of interest. For example, there is a method called the “ensemble” method in machine learning where an iterative process over multiple models is used to fit data. In the end, the ensemble method aggregates results from the different models to get the best prediction. In economics, we can’t really use this method because we wouldn’t be able to make inference. If we want to use machine learning techniques in economics, we need to be able to perform some sort of causal inference. In my project, I had to think hard about what I was measuring and what economic interpretation I could infer from the data I was looking at.
EE: Turning back to the question of sexism in economics, why do you think women are underrepresented? Do you think that the online conversations on EJMR reflect people’s day-to-day experience?
AW: There are multiple components to answering this question. The stereotype literature (which is more psychology than economics) says that young girls often think they will be more successful in humanities than in quantitative fields. That belief can guide what courses women and girls take in high school and college. Since economics requires a lot of math, many women are unprepared to actually take economics courses or go on in the field. This is an entry level issue.
However, in addition to the entry level issue, there is a “leaky pipeline” in economics (higher rate of attrition for women than for men). This poses another problem and is more a workplace issue. There is an issue in the culture of economics that might turn people away, and my paper exposes a part of that culture.
I hope that the people who post these crude and objectifying comments are not representative of the profession. But overall, the whole atmosphere and culture of a profession can be shaped by a select few people. When you have a few people standing out in a certain way, that has a big impact on the culture of the field. It doesn’t really matter who these people are but just their existence and participation is disturbing.
EE: What do you see as the main contribution of your paper?
AW: I’m really happy to see that this study has triggered an open discussion about the culture of economics and how it may impact women’s representation in the field. People are acknowledging that there’s an issue and that’s the first step to addressing it.
EE: How do you see the relationship between academic research and politics/change?
AW: The honest answer is that I didn’t think about politics at all when I was writing this originally. I was working on my senior thesis and focused on the research question itself and I didn’t see it as a political tool in any way. However I’m glad that it has sparked conversation and may induce positive change.
EE: Your paper focused on the difference in language used to describe men and women on EJMR. However, there was clearly evidence of homophobia and racism in your results. What do you make of this evidence?
AW: I see very problematic language with respect to race and homophobia but the way I designed my research question I was looking at the simple difference between language used to describe men and women. The homophobia definitely shows up in my analysis with respect to how the LGBT community are described online. However, there should be more careful analysis on these topics.
Author: Emily Eisner
Hallie Jo Gist
The gender disparity in the Economics discipline at UC Berkeley is no secret. For the undergraduates, a glance around the classroom is enough evidence of an imbalance. As a part of the nation-wide Undergraduate Women in Economics (UWE) Challenge, we attempted to quantify this apparent disparity.
The UWE challenge was inspired by Professor Claudia Goldin’s research on undergraduate women in Economics at the hypothetical "Adams College," a U.S. liberal arts college. Goldin found that women are less likely than men to enter and continue in the Economics discipline. As one of 20 randomly selected universities, UC Berkeley receives funding for research on the factors that affect the gender distribution of undergraduates in Economics. The data collection described below is a first step in this research.
Our main statistic of interest is what we call the "Goldin ratio." The Goldin ratio is the male-to-female ratio of degrees earned in a given undergraduate major, relative to the male-to-female ratio in the full undergraduate population at UC Berkeley. For example, if there is a 50-50 distribution of males and females among all undergraduates, a Goldin ratio of 2 for the Economics major implies that there are twice as many males as there are females earning an Economics BA. This ratio was calculated from information on degrees earned made available through CalAnswers. For raw numbers, please see the chart at the end of this blog.
At UC Berkeley, students interested in economics choose between three undergraduate majors - Economics (Econ), Environmental Economics and Policy (EEP), and Political Economy (Poli Econ). The Economics major is the largest undergraduate major at UC Berkeley, with an average of 470 graduating students every year over the past ten years. The Economics major is housed in the Department of Economics within the College of Letters and Sciences. The EEP major is housed in the Department of Agricultural and Resource Economics within the College of Natural Resources. The College of Natural Resources describes the EEP major as the study of "economics and political institutions that affect the development and management of natural resources and the environment." The Political Economy major studies "the relationship between politics and economics in modern societies, focusing on problems of both domestic and international policy." It is one of several majors in the International & Area Studies Academic Program within the College of Letters and Sciences. Finally, UC Berkeley also offers an undergraduate Business major housed within the Haas School of Business.
While these majors diverge in the electives offered to upper year students, there is a great deal of overlap in the prerequisites and core requirements for all four degrees. The Business major has similar prerequisites to the economics majors, but a more selective admissions process. We calculated the Goldin ratio in all four majors for the last 10 years.
Figure 1 shows the Goldin ratio for each graduating class, 2007 to 2016, in the Economics (Econ), Environmental Economics and Policy (EEP), Political Economy (Poli Econ) majors, and Business (Bus.) majors. As you can see, the annual Goldin ratios tend to be highest for students in the Economics major. This indicates that the Economics major is disproportionately male relative to the university. Moreover, this disparity is greater in the Economics major than in the other three majors. The Goldin ratios are also greater than 1 for the Business major, which tells us that the Business major is also disproportionately male relative to the university. The Goldin ratios are closer to 1 for the EEP and Poli Econ majors, indicating a more equal gender balance.
Examination of the Goldin ratio for transfer students reveals that the trend is not common to students of all educational backgrounds. Figures 2 and 3 show the Goldin ratio for students in all four majors (Econ, EEP, Poli Econ, and Bus.) who were admitted as transfer students and as new freshmen. Among students who were admitted as transfer students, the Goldin ratio tends to be greater than 1, indicating a gender disparity. Furthermore, the Goldin ratio for the past ten years has shown an overall increase, indicating that this disparity is growing. On the other hand, the overall Goldin ratio for students admitted as new freshmen has decreased over the past ten years and is approaching 1, at which point the gender distribution among economics students will be equal to that of all UC Berkeley undergraduates. This tells us that while the gender disparity in the economics majors is improving for four-year students, gender inequality is growing for transfer students.
While the preceding graphs give us a good sense of the big picture, they disguise the fact that the gender disparity in Economics at UC Berkeley varies significantly by racial group.
This is especially true in the Economics department. Figure 4 reports the Goldin ratio values computed using all UC Berkeley students graduating in the periods 2007-2011 and 2012-2016. The Goldin ratios are highest for students identifying as underrepresented minority (UM) - Black, Latinx, and Native American undergraduates. Meanwhile, with averages close to 1, the gender balance among students of Asian and Pacific Islander (PI) descent, and International students is practically at parity.
Similarly, the Goldin ratios for each five-year period are particularly high for students identifying as UM in the Business major. For students identifying as Asian and PI, the Goldin ratios are about 1, indicating a gender balance reflecting that among all Asian and PI undergraduates. For International students, the average Goldin ratios are less than 1, which implies that International women are actually over-represented in the Business major relative to the undergraduate population. This trend is true for EEP students as well, though the difference between racial groups along the lines of race is less pronounced. For Political Economy students, the five-year average Goldin ratios are about 1, indicating a much more equal gender balance across racial groups.
The difference in gender balance across racial groups prompted us to calculate a new ratio, which we call the "race ratio." The race ratio is analogous to the Goldin ratio; we look at the ratio of students of a particular racial group to students of all other racial groups. For example, if 18% of UC Berkeley’s undergraduates are of underrepresented minority (UM) racial groups, then a race ratio of 2 for UM students in the Economics major implies that only 9% of Economics BA recipients are UM students. We calculated this ratio for each of the three majors within the economics and business disciplines at UC Berkeley.
Figures 8-11 show the 2007-2016 annual race ratios for Asian/PI, white, underrepresented minority (UM), and international degree recipients in the Economics, EEP, Political Economy, and Business majors. For Economics students, there is a pronounced difference in race ratios between the four racial groups. The annual race ratios for UM students are much greater than 1 and tend to be higher than those for students of other racial groups. That is, UM students are severely underrepresented in the Economics major relative to the population of undergraduates, and this racial imbalance exists disproportionately for UM students. Furthermore, with an upward sloping trend, the graph suggests that this disparity is growing. At the other end of the spectrum, we can see that international and Asian/PI students are over-represented in the Economics major, with race ratios less than 1.
We see a similar distribution of race ratios in the Business major. However, for UM students in the Business major, the race ratios trend downward. This indicates that while UM students are underrepresented in the Business major, this inequality is becoming less pronounced. The difference in race ratio across racial groups is less dramatic for the EEP major, although the disparity is still there. Again, UM students in particular are underrepresented in the EEP major relative to the university. Within the Political Economy major, the distribution of students according to racial group is much closer to that of the university. For all four racial groups, the race ratios tend to be closer to 1 than among the other majors.
The race ratio tells us nothing about the distribution of students according to gender; neither does the Goldin ratio tell us anything about the distribution of students along the lines of race. That is, just looking at the proportions of race or gender groups blurs the inequality faced by underrepresented minority women.
We struggle to address this issue. One problem is the small number of UM women graduating with degrees in the economics discipline; this renders it difficult to make meaningful statements about annual trends in degrees earned by UM women. An average of only 9 UM women have graduated with a BA in Economics each year for the past 10 years. This fact alone is alarming.
As a starting point, we created what we’ve called an "intersectional ratio." The intersectional ratio is analogous to the Goldin ratio; it is the ratio of UM women vs. all other students, divided by this ratio in the full population of Cal undergraduates. Aggregating over two 5-year periods, we created intersectional ratios—one for the period 2007 to 2011 and another for the period 2012 to 2016. These ratios for the Economics major are summarized in Figure 12.
As you can see, the intersectional ratio is extremely high for UM women in the Economics major. This suggests that UM (Black, Latinx, and Native American) women are even more underrepresented than suggested by the race ratios or Goldin ratios.
It is clear that the economics and business disciplines at UC Berkeley suffer from gender and racial disparities. In this post, we hope to shine a light on these issues. We are not sure how or why these inequalities arise - this is a topic for future research. One possibility is that women, especially UM women, are less confident in their quantitative reasoning skills. Research suggests that women in mathematics classes experience stereotype threat, which limits their performance. To be clear, we do not mean to imply that women at UC Berkeley lack quantitative proficiency. Rather, we want to suggest that the UC Berkeley could do more to support women pursuing quantitatively rigorous degrees, and that this might promote higher numbers of women in economics and business.
However, the difference in gender and race distributions among the four majors may suggest another channel, especially when we consider that the four degrees require similar lower-division coursework. In particular, it may be that some students perceive that the Economics and Business majors do not address issues of social justice, while Political Economy and EEP do. In my own experience as an Economics student, I have often felt that the undergraduate Economics program at UC Berkeley can be used to answer questions related to social justice. Perhaps our efforts to increase the numbers of UM women in these degree programs should involve making information about the content and freedom within these majors more accessible.
For those of us involved in the UWE project at UC Berkeley, these data are just a starting point. We recognize that any attempt to promote a more equal distribution along the lines of race and gender in the economics and business departments will not be successful if we do not take an intersectional approach. Neither the Goldin ratio nor the race ratio captures the particularity of the experience of underrepresented minority women within the economics discipline. We hope that the data presented above can serve as a foundation in our effort to make the economics discipline a more equitable environment for people of all genders and races, and in particular to bring attention to the severe underrepresentation of minority women in Economics.
The research described above was conducted under the direction of Professor Martha Olney in the Economics Department at UC Berkeley. The ongoing project is funded by the nation-wide UWE Challenge.
Hallie Jo Gist is a fourth-year undergraduate Economics student at UC Berkeley. She is part of a team of undergraduates involved in the UWE project at UC Berkeley. Hallie Jo is originally from the San Francisco Bay Area.
WEB Editorial Board
Most of us have probably seen coverage (New York Times, Washington Post) of an undergraduate honors thesis written by Berkeley undergraduate economics major, Alice Wu. In her paper, Wu exposes the rampant misogyny cluttering Economics Job Market Rumors (EJMR), an anonymous forum. While it comes as no great surprise that EJMR is rife with sexist (not to mention racist and homophobic) commentary, Wu's paper uses natural language processing to quantify the extent of the vitriol - and the results are disappointing. On the site, the words most commonly associated with women include "hotter," "lesbian", and "feminazi", while the words most commonly associated with men tend to be positive ("goals", "greatest") or economics-related ("adviser", "textbook", "pricing"). At WEB, we condemn in the strongest possible terms the rampant sexism on EJMR.
The commentary and attitudes on display at EJMR represent a substantial challenge to women in economics - (explicit) bias - which can discourage women from undergoing graduate training, prevent them from entering academia upon graduation, and hamper the careers of female economists. Even though EJMR clearly does not represent the views of all economists, the anonymous trolling on the site does represent real issues in the profession, and is a "canary in the coal-mine for what happens every day" (Amitabh Chandra).
While it is undoubtedly true that not all men post on it, almost *all* women (that I know) have experienced their names be publicly associated with sexist, offensive, and untrue claims.
Furthermore, it is concerning that anybody associated with academic economics use the language described in Wu’s paper to describe women. The existence of this website sends a message to the population that economists do not take misogyny (or racism, classism, etc.) seriously.
Not personally participating in this harmful behavior cannot serve as an excuse or rationale for inaction -- especially when the language used at EJMR is viewed in the broader context of women’s experiences in the economics profession. There is mounting empirical evidence that women in economics often face uphill battles. Women get less credit for coauthored work (Sarsons 2017); despite having more readable abstracts, female economists' papers take six months longer to peer review in a top journal (Hengel 2016); and women are more likely to take on department service that does not contribute to promotion (Babcock et al 2017) The share of women by PhD cohorts has stagnated for the past decade (Daniel Paserman), and women are underrepresented in economics - even relative to other STEM fields (Bayer & Rouse 2016).
A lack of diversity in the economics field - potentially exacerbated by the kind of language found on EJMR - is a serious problem (See Bayer & Rouse 2016 for more on this). Wu's paper itself serves as a reminder of the importance of including women’s voices in economics: she brought creative methods to a sensitive topic, and sparked a much-needed conversation on gender disparity.
Economists throughout the profession have spoken out over the past few days against EJMR. The discussion among economists, across twitter and personal blogs, has extended to the state of gender disparity in economics as a whole. By rejecting discriminatory and harmful actions, senior faculty and prominent economists send a clear message to young up-and-coming economists that economics does not stand for bigotry.
We applaud the ongoing commentary that condemns the unacceptable culture at EJMR. We urge the economics profession to take advantage of this conversation and take further action. Several suggestions have already been floated.
Looking for some compelling beach reading? This month we’ve compiled a list of recent prominent papers that we’ve been itching to dig into all year. The papers listed below touch on issues related to women in the workforce, and some specifically address women in economics. Taken together, these papers illustrate the breadth of recent work explaining gendered outcomes in the labor force and demonstrate the many channels that may contribute to the gender earnings gap.
For each paper we’ve included a brief summary, and for the CSWEP Annual Report we’ve highlighted the key takeaways. Happy reading!
Can Women Have Children and a Career? IV Evidence from IVF Treatments
Petter Lundborg, Erik Plug, and Astrid Würtz Rasmussen
American Economic Review, June 2017
Recognition for Group Work: Gender Differences in Academia
American Economic Review: Papers & Proceedings, May 2017
Gender Differences in Accepting and Receiving Requests for Tasks with Low Promotability
Linda Babcock, Maria P. Recalde, Lise Vesterlund, and Laurie Weingart
American Economic Review, March 2017
Bargaining, Sorting, and the Gender Wage Gap: Quantifying the Impact of Firms on the Relative Pay of Women
David Card, Ana Rute Cardoso, and Patrick Kline
Quarterly Journal of Economics, October 2015
Women and Power: Unpopular, Unwilling, or Held Back?
Pablo Casas-Arce and Albert Saiz
Journal of Political Economy, June 2015
Report: Committee on the Status of Women in the Economics Profession
American Economic Review: Papers & Proceedings, May 2017
Authors: Fiona Burlig and Emily Eisner
In their 2017 AER paper, “Acting Wife,” Leonardo Burstyn, Thomas Fujiwara, and Amanda Pallais show that single women in MBA programs under-invest in career-improving activities when these actions are observable to their peers. The authors argue that single women face a trade-off between investment in their careers and investment in the marriage market. In the labor market, ambition, willingness to travel, and willingness to work longer hours are rewarded. On the other hand, research shows that heterosexual men often do not want spouses with higher ambition or higher earnings. This trade-off reduces the demonstrated ambition and career-investment of single heterosexual women compared to their non-single female peers.
The authors conducted a field experiment in a first-year MBA class using a survey that they were told would be used by the career center in summer internship matching. The survey, filled out on the first day of the MBA program, asked each student about their career preferences, desired compensation, desired hours, and leadership skills. The instructions on the top of the survey stated that students’ answers would be discussed in one of their first semester courses. One group of students had instructions stating that answers would be discussed anonymously, while another group’s survey instructions simply stated that answers would be discussed. Comparing the survey answers between these groups allowed the authors to measure how single women may avoid career-enhancing activities in front of peers who they may meet on the marriage market.
The results of the experiment show that single women consistently under-report their desired compensation, propensity for leadership, hours willing to work, and travel on the job compared to their non-single peers. Importantly, this under-reporting is only seen for women who thought their responses may be observable to classmates. Because the MBA students believed that survey answers would have a direct impact on their summer internship prospects, the under-reporting suggests real under-investment in career enhancing activities and predicts real under-performance.
The results of this paper are hard to dispute - the research design leaves little room for other possible explanations of the mechanism driving women to under-perform in this context. While I was not completely surprised by the results when I saw this paper, I was saddened by the fact that this marriage-market-labor-market trade-off may leave such strong marks on women’s participation in the labor market. To learn more, I emailed Amanda Pallais herself to see if she would talk with me about the paper, its inspiration, and her next steps in researching this topic.
EE: What led you to the idea that sparked this paper?
AP: My coauthors and I had read research that finds that men prefer female romantic partners who are less ambitious and successful than they are. This led us to believe that single women might face a trade-off between investment in the labor and marriage markets. Anecdotally, we also heard single women considering this trade-off and wanted to study it formally.
EE: How do you think about this work as part of the larger literature on gender norms in the labor market?
AP: We see our work as in line with this literature - gender norms can lead women to have worse labor market outcomes. One branch of literature studies the effect of having children on men and women’s labor market outcomes and tends to find that women’s careers suffer more than men’s after having a child. Our paper is related, but shows how these norms and the marriage market can affect women’s labor market success even before they are married.
EE: How has your paper been received by the public? I would imagine that it is hard to talk about these issues with some people?
AP: It hasn’t been particularly hard to talk with people about the results of our paper. It seems many people had a feeling that single women face a trade-off between the labor market and the marriage market - and it’s been nice to be able to formalize this.
EE: Have you at all considered using variation in sexual orientation to study whether non-heterosexual women and men face any similar trade-offs? Or have you thought to use non-heterosexual women as a sort of control group for the mechanism you’re identifying?
AP: We have thought about that, and would like to be able to explore the behavior of women who are not on the heterosexual marriage market. Unfortunately we don’t have data on sexual orientation, and even if we did, I don’t think we’d have enough power to identify anything given the sample size that we’re working with.
EE: Was there anything you found while writing this paper and running this experiment that particularly surprised you?
AP: The magnitude of these results was pretty surprising to me. My co-authors and I started this project to test whether single women respond to this trade-off, so we weren’t particularly surprised that they did. But the extent to which single women made themselves look less professionally appealing due to marriage market concerns was striking. For example, single women reported being willing to travel an average of seven fewer days a month when their answers would be seen by their classmates. That is a large difference, implying potentially dramatic professional sacrifices.
EE: So, what is your next step with this work?
AP: There are two branches of things that we’re interested in. One is to extend our results to different contexts such as high schools, colleges, and jobs, looking at the long run effects on women’s labor market and marriage market outcomes. The second is what policies could help mitigate the trade-off that leads women to under-invest in their careers. For example, we might think that we want to make women’s actions private, but that’s really hard to do. Something that may be more feasible would be to change some of the defaults, like going from hand-raising in-class to cold-calling. If women participate less in class because participating signals an undesirable trait to the marriage market, cold-calling might remove this signal and lead women to participate more.
While the results in this paper highlight some of the challenges in improving labor market opportunities for women, the paper also signifies an important line of work going on in economics. In order to increase equality in the labor market, we must understand the precise obstacles that women face. I look forward to seeing what other work this paper will motivate and how the discipline will respond.
Author: Emily Eisner
"The market is noisy" will be relayed to you umpteen times as you near the job market; you will hear it from professors, mentors, and loved ones that begin to spend too much time on EJMR*. However, understanding its full meaning is impossible before experiencing the market yourself. You will misinterpret and over-analyze interactions; you will be taxed - intellectually, emotionally, and physically - in ways you could never expect; and you will find delight in some of the peculiarities of the process. The intense uncertainty is not one-sided. Hiring committees also operate in a haze - trying to read your signals, reaching out to your letter writers to glean information on your preferences, and balancing this with the preferences of their colleagues and the administration.
For those less familiar with the job market, the economics profession adheres to a condensed process that features employers across academia, industry, and policy seeking to hire newly-minted economists. As women fresh off the market, we would like to pass on some reflections from our own experiences this year on the job market. We hope that a preview of what to expect and some advice on how to navigate this process will increase the enjoyable aspects of the process and decrease the stressful components.
The below advice, separated into different phases of the process, comes from graduating Cal women in Agriculture & Resource Economics, the Economics Department, and the Haas School of Business.
Preparation & Applications
The job market process formally begins with the decision to go on the market, which can be surprisingly fraught. By early August you should decide, schedule your fall practice job talks, and get your paper ready. Jobs will start getting posted in the early fall on econjobmarket.org and the AEA’s Job Openings for Economists. Most applications are due between mid October and early December. Many candidates submit well over 100 applications.
"Take time to self-reflect and come to an honest assessment of what you want for yourself in 10 years. What is most important to you: tenure at an R1? your research to directly impact policy? to specialize in working with cool datasets? to teach and mentor a generation of economists? well-paid in a cool city? Once you know your preferences, tell your letter writers about them and get them on board. Focus your job search on any job that might help you achieve your personal goal." - Anonymous
"Do good work! The better your CV, the easier the rest becomes." - Fiona Burlig
"Believe the adage, 'Every presentation is a job market presentation.' Present your job market paper (as often and early as possible) in workshops and smaller conferences (especially those in your field) during the summer and fall before the job market. I knew presenting my research would help me improve my paper but I was surprised by how many of my ASSA interviews stemmed from having made a connection with someone at a workshop/conference." - Becca Taylor
"Get advice from multiple people - especially the faculty you find most intimidating. There's someone scarier out in the world." - Fiona Burlig
"Save money for the job market. Reimbursements take a long time and there are several months between your last stipend and your first salary." - Anonymous
"Your job talk is incredibly important – practice it with audiences both in and outside your sub-field." - Anonymous
"Network early and often - the more people who have a positive impression of you, the better." - Fiona Burlig
"Buy your suits and dress shoes early in the fall. Make it a fun group activity with other job market candidates! Pant suits are preferable to skirt suits for interviews on hotel beds and fly-outs in freezing places." - Anonymous
"Don’t isolate yourself. Your cohort is not the competition; candidates at other schools are the competition. Practice your job talks and elevator pitches with one another. Discuss your anxieties. Go on walks. Take coffee breaks together. The job market requires strong mental stamina; remaining connected to your peers helps." - Sandile Hlatshwayo
"Being a good salesman is as important as the quality of your work (depends on your field though, some fields are better about this)." - Anonymous
"Writing and polishing the paper is the hardest and most stressful part, though the other/later parts take up at least as much time." - Gillian Brunet
Interviews & Fly-out Process
From early December onward, hiring committees will call to schedule interviews with you at the annual AEA meetings which are held in early January. Private sector and policy institutions sometimes schedule interviews beforehand so have your talk ready by early December. Use your network, beyond your school’s faculty, to get interviews; ask mentors to email their colleagues at your target schools on your behalf. Cawley (2016) provides a nice list of interview questions to prep for. After a flurry of interviews at the meetings, hiring committees will call to schedule on-campus "fly-out" interviews across the US and abroad. Some schools will try to book fly-outs on the same day as your interview. Discuss strategic scheduling with the placement director and your adviser. For research schools, the private sector, and policy institutions, fly-outs typically last one day. For liberal arts colleges, expect two-day fly-outs.
"You can and should actively enjoy interviews and fly-outs: you have the opportunity to discuss your work with smart people and it is actually wonderful. When people on the market in years ahead of me said this, I thought they were crazy/that I’m not extroverted enough for it to be true for me, but they were right. Channel your nervousness into excitement and enjoy the ride." - Gillian Brunet
"Take time to research each of the professors you will be meeting with during fly-outs. It’s amazing how a quick google search can translate into an interesting meeting with a professor because you’re able to talk about potential collaborations and overlap in interests." - Sandile Hlatshwayo
"Use your network. My advisor was not pushing me very hard but I got top interviews because people in my network wrote emails to R1 schools." - Anonymous
"People are looking for 'good colleagues,' which is a very holistic concept. It goes without saying that your paper is very important. However, also central is your ability to present your ideas, think on your feet, and engage in conversations about topics unrelated to your area of expertise." - Sandile Hlatshwayo
"You don’t have to go the ASSAs alone. Ask a family member, partner, close friend, or classmate on the market next year to come with you to the ASSA conference to help you get through it smoothly. This might not be for everyone, but I immensely appreciated having someone who knew me well to be my helper (e.g. brought me food, coffee, and things I forgot) and my cheerleader (e.g. cued Rocky theme song)." - Becca Taylor
"Catch up on sleep whenever you get the opportunity, buy a neck pillow for plane flights, and find shoes that are still comfortable after wearing them for 12 hours (possible even with serious foot problems - I managed it)." - Gillian Brunet
"Try to enjoy the ride and all the people you're going to meet in the next few months. It's like how you never learn more econ more quickly than you do in the first year. The job market is like that, but for networking. It will be intense, but also kind of life propelling." - Anonymous
"Buy a small travel iron, lint roller, and Febreze for when you have back to back fly-outs and no time to get your suits dry-cleaned." - Anonymous
"Expect stochasticity." - Fiona Burlig
Congratulations on your offer(s)!** Often hiring committees will call to discuss the preliminary offer with you, which is a starting point for negotiations. Everything is on the table for negotiations - salary, research budget, moving expenses, signing bonuses, teaching load, service duties, etc. Having a rough sense of your "ideal offer" in mind is helpful when entering into these conversations. Salary is probably the least flexible component of offers, but the broad "bounds" can be found in the annual Survey of the Labor Market for New Ph.D. Hires in Economics. Keep your adviser and placement director in the loop for these talks. A formal written offer will be sent following negotiations. Happy signing!
"Negotiate on the terms of your offer letter even if you don't have competing offers." - Anonymous
"Don't worry about how your decision might reflect on your advisors or on the department. And don't be dissuaded by what other people, especially fellow grad students or strangers on the internet, might think about the job you end up with. Do what is right for you, since ultimately you're the one who has to live your post-PhD life." - Anonymous
"Negotiate!" - Sandile Hlatshwayo
"Saying 'no' to places at the end can actually be really painful. No one told me this, so it was a shock. The fact that you may like multiple places that make you offers doesn’t mean you should second-guess your decision." - Gillian Brunet
"[Y]ou’ll end up somewhere that makes you happy, most likely somewhere you haven't spent more than a few minutes considering at this point in time, because that's what seems to happen to most." - Anonymous
"The final decision may come down to competing offers that take you in very different directions (e.g., a tenure-track job vs. a consulting firm). First, be clear and honest with yourself about what attracts you to each position. There are some metrics that shouldn’t feature (e.g., number of sick days or 'perceived' prestige). Second, if you’re still finding it difficult, before committing anywhere write down your gut choice on a post-it and stick it on your bathroom mirror before you go to bed. When you wake up, take a look at the post-it and then take a look at yourself in the mirror. Are you happy with your choice? If yes, great! If not, you know what to do." - Anonymous
For those of you at Cal, continue to use WEB and the connections you build through it as a resource as you navigate the job market. My experience was infinitely more enjoyable because of my fellow WEB job market candidates! If you ever want to chat, please feel free to reach out to me at firstname.lastname@example.org. As a final reminder, keep perspective during the process and try not to stress too much - you are wildly employable and the market will clear!
* EJMR stands for Economics Job Market Rumors. The website hosts a job market wiki which gives noisy information on what schools are posting jobs, when they call to schedule interviews, who is flying out, who gets offers, and who accepts offers. It is also host to less-useful conversations about particular papers, professors, schools, hot economics-related topics (e.g., machine learning), and complete randomness. Postings are anonymous, which sometimes leads to negativity and 'isms' (e.g., sexism and racism). Take what is useful from it; ignore the rest.
**If you don't match with an employer through the first round of the market, there is a 'scramble' for unmatched candidates and employers in March.
Author: Sandile Hlatshwayo
At this year's ASSA meetings I had the privilege of attending the panel Best Practices in Recruiting and Mentoring Diverse Economists. The panel was jointly hosted by the Committee on the Status of Minority Groups in the Economic Profession (CSMGEP) and the Committee on the Status of Women in the Economic Profession (CSWEP). During the two-hour-long discussion, panelists provided concrete advice for departments and research institutions working to improve diversity among their faculty. Panelists' advice ranged from improvements to the hiring process, to strengthening retention and mentorship of junior faculty and researchers.
All the panelists agreed that increasing diversity in the economics profession is imperative. To paraphrase Professor David Laibson, there are two benefits to increased diversity in the field - better research and better pedagogy. According to him, "we are impoverished as scientists because we don't have those [diverse] perspectives in the room."
Discussions of implicit bias dominated the conversation. Professor Marie Mora proposed that search and tenure committees seek training to mitigate implicit bias. However, as Professor Terra McKinnish pointed out, before such training can be effective, a critical mass of senior economists must believe that implicit bias exists. McKinnish encouraged economists to read up on the existing literature* so as to inform themselves of the implicit bias faced by women and underrepresented minorities (URMs). Laibson encouraged faculty at universities to reach out directly to their colleagues in Psychology who research implicit bias.
Another takeaway from the discussion was that passive recruitment is not sufficient. Mora suggested that departments follow up job listings on sites like JOE with advertisements and reminders emailed to actively maintained listservs. Laibson reasoned that expanding hiring searches more broadly could yield positive results. Dr. Rhonda Sharpe agreed that it could be a good idea to be more inclusive in faculty recruitment, but cautioned that this policy should be accompanied by a sincere intention on the part of the department to offer interviews. Sharpe suggested that faculty have a candid conversation about what increasing diversity will mean for their department before implementing inclusive recruitment initiatives. Notably, Sharpe posited that as a profession "we use words like 'quality' and 'fit' to exclude people, we don't use 'quality' and 'fit' to include people."
Dr. David Wilcox pointed out that hiring committees will sometimes update their search criteria mid-process based on the candidates that they have seen. He urged departmental leadership to press against this and impose prior restraint on both the overall criteria for hiring and on the set of weights used when assessing said criteria. This aligned with Mora's advice that departments think explicitly about who might be a good fit for the position they are looking to fill before setting out to recruit. Wilcox allowed that sometimes there are valid reasons a committee may decide that a change to the criteria is necessary. He cautioned that the committee should justify the change and then go back and reevaluate all the candidates based on the updated criteria
Recruitment is not the only hurdle to diversity; inclusion after a person has been hired is also very important. Laibson posited that economics as a profession can often present a culture of aggression which can be discouraging at all stages of the pipeline. Mora described a policy at the University of Texas Rio Grande Valley that provides flyout candidates an optional meeting with a member of the women’s faculty network. During these informal meetings candidates often ask questions relating to family leave, spousal hiring assistance, and other topics that may feel inappropriate to broach during a flyout. It seems to me that such meetings help support female job candidates and set a tone of inclusivity.
Inclusion is not simply a question of culture, but also of creating institutional norms that allow for retention and promotion of faculty and research staff. McKinnish argued that the more informal the flow of information, the greater the disparity in outcomes across women and underrepresented minorities. After all, when people are not as in-the-know, they can miss out on crucial opportunities. Wilcox agreed with this idea, explaining that his division has seen gains in diversity from conducting a personnel policy that is systematic and predictable, that is widely known and explainable, and that is transparent.
Wilcox pointed out that when a personnel policy is widely known, all employees know when their work is deserving of beneficial outcomes such as promotion or tenure. He refined transparency to mean that any hiring policy should "withstand the light of day". Wilcox further argued that when a promotion policy is predictable, everyone knows they will be treated equally according to their productivity and not according to their ability to negotiate or self-promote. This reminded me of a point that McKinnish had made earlier in the discussion, that women are judged differently for negotiating and advocating for themselves
Another recommendation put forth by McKinnish was to provide junior faculty with vitas from recent tenure cases to allow junior faculty to ask questions regarding expectations. She further asserted that departments should have well-documented tenure expectations. McKinnish contended that departments and institutions should be clear on how research funds may be accessed and how special considerations could be attained.
There is also an issue of mentoring that McKinnish argued as necessary to the promotion of junior faculty. According to her, most newly minted PhD’s have not been taught the necessary skills to achieve tenure. These skills include: how to pitch a paper to an editor, how to choose which journal to submit to, how to interpret and respond to reviewer feedback, how to build a professional network, and how to meet expectations in teaching, advising, and service while still meeting research goals.
With regards to mentoring, Mora recommended senior economists get involved with both minority and women’s groups. McKinnish pointed out that for a mentoring group to be successful, the mentors need to be candid, honest, and thoughtful with advice, and must be invested in mentoring. Unfortunately, she continued, people who are good at mentoring are often the same people who are good at other service work needed by the department. As such, McKinnish concluded, departments need to decide that mentoring is a priority if the mentoring program is to work well. One concrete step that McKinnish proposed was for department chairs to provide incentives for senior faculty to participate in mentoring.
The discussion shed light on the inherent tension between methods that reduce implicit bias and those that actively target women and URM economists. Despite the challenges involved in implementing practices designed to improve diversity in the profession, we at WEB strongly endorse the panel's view that diversity is incredibly important to the economics field. We hope that this panel is the first in a series of conversations across departments on the best strategies to achieve these goals.
* Existing literature on implicit bias includes Bayer & Rouse (2016) and Bertrand & Duflo (2016)
Author: Aluma Dembo
Economists have acknowledged that the undergraduate population of economics majors underrepresents women and minority groups. Less attention seems to be given to the graduate school admissions process, though disparities persist and perhaps worsen as students move into graduate school. A 2014 survey from the AEA suggests that over the last 10 years about 36% of undergraduate economics majors at top 10 ranked economics departments were female. However, only about 25% of first-year graduate students at the same institutions were female.* A similar trend holds for the top 20 institutions. These facts suggest a need for more analysis into our admissions process, and beg the question of whether our processes contribute to the "leaky pipeline."
The vast majority of people involved in admissions acknowledge the underrepresentation of women and minorities in the field. It is not individual acts of explicit bias or discrimination that seem to produce the lack of growth in representation over the last 20 years - rather it is the failure of our field to put in place systems and institutions that mitigate and counteract the implicit bias for which we are all culpable.
A large body of research by economists suggests that implicit bias generates discrimination in the labor force. For example, Bertrand and Mullainathan (2004) show that when identical resumes are assigned African-American-sounding names, applicants are called-back for an interview at only two-thirds the rate of an applicant with a white-sounding name. More recent work by Milkman, Akinola, and Chugh (2013) reveals the same gender and racial biases in an academic setting with faculty email response rates significantly higher for white and male students.
Given that implicit bias is pervasive, one can infer that the procedures we use in graduate admissions would not be free from this trap. Of course, anyone who has sat in on a conversation about recruiting female graduate students knows that the applicant pool (supply side) is highly unbalanced to begin with. This is an important issue that our field is beginning to address with efforts such as The Undergraduate Women in Economics Challenge. However, it does not preclude the need for faculty to pay attention to the application review and admission process (demand side). In fact, we need to evaluate and understand our process for building the graduate student cohorts so that we can address the supply side imbalances we face at the faculty-hiring stage.
Taking the supply side of graduate admissions as given, departments must ask themselves how they plan to build a cohort. Unfortunately, we do not currently have access to much data or research on how the admissions process works in various departments. Anecdotal evidence suggests that the guidelines given to admissions committees on how to evaluate candidates varies by department and remains vague.
Many departments employ some type of linear model that assigns value to candidates based on defined categories and produces a ranking of candidates from which the department can make admission decisions. However, evidence suggests that constructing a ranking of candidates may not be the best approach for constructing a cohort. Experimental research by Hoogendoorn et al. (2013) concludes that gender balance improves the success of teams, suggesting that departments should consider the composition of a cohort in addition to individual strengths. Scott E. Page, a professor at the University of Michigan, argues that organizations should invest in diversity to achieve their best and most productive workforce. This research implies that admissions models should consider complementarities between students.
Further, many of the measures used to evaluate applicants - GRE scores, GPA, research experience, and recommendation letters - may deliver systemic preference to certain demographic groups. Certainly statistical discrimination poses an issue - candidates from less-conventional backgrounds deliver a noisier signal than candidates that look familiar to those reviewing applications. Additionally, evidence suggests that these measures may include bias themselves. For example, Trix and Psenka (2003) find that recommendation letters written for women in the sciences tend to be shorter and to emphasize research skills less than recommendation letters for men.
More troubling, the measures and categories we use to evaluate applicant strength may not predict success in the field. The presumed objective function of an admissions committee is to admit a cohort of students who will (a) graduate and (b) go on to contribute meaningfully to the field (perhaps as measured by the prestige of the institution where they are hired). The measures used to assess applicants may be optimized to reduce attrition in the program, but may not select for future success. Informal analysis at various departments has shown that, conditional on admission, internal rankings of applicants does not predict future success in the field.
Practical steps that departments can take immediately to improve their admissions processes include collecting data on the admissions rankings of candidates and analyzing the long-term outcomes of students in their cohorts. Admissions committees, which often change year-to-year, can also record their goals and guidelines for building cohorts, so that we can evaluate and learn from past practices. Setting and communicating clear guidelines also helps to reduce bias and increase awareness of gender and racial disparity in the field. Finally, in order to take on and sustain this effort, departments should ensure that the transfer of roles (such as admissions chair) involves creating and transferring institutional memory.
When considering changes to the admissions process, matching the gender (and racial) distribution of incoming cohorts to that of the applicant pool is not the correct measure of success. It may be that female (and minority) applicants apply at lower rates because of discouragement or lack of information on how to apply, causing selection bias that would raise the average quality of female (or minority) applicants. Discussions with women currently in graduate school and in the process of applying corroborate this theory. A better measure of a successfully unbiased process is one where the expected marginal contribution of female (or minority) candidates is equal to the expected marginal contribution of male (or white) candidates. Of course, this would require establishing a measure of an individual’s contribution which, as previously discussed, is difficult in both theory and in practice. Nonetheless, collecting data on current admissions practices and considering what measures of contribution a department values are important steps towards improving the admissions processes.
Departments are intent upon contributing to a solution to the drop-off in diversity among graduate students. While there are checks in place to make sure that excellent candidates do not fall through the cracks, more can be done. With the preceding framework in mind, perhaps departments will engage with some of the fundamental questions important to improving our current systems.
* It should be noted that African Americans, and Hispanics/Latinos, Native Americans, first-generation college students, low-income students, and Pacific Islanders are also underrepresented but we have very limited data on these groups, so our analysis will pertain mainly to women. We intend our main message to extend to these other underrepresented groups.
Author: Emily Eisner
It is publicly known, though perhaps frequently underestimated, that academic economics disproportionately employs male and Caucasian economists. In their Fall 2016 Journal of Economic Perspectives paper, Amanda Bayer and Cecilia Elena Rouse construct a comprehensive argument for the need to address the persistent underrepresentation of women, African Americans, Hispanics/Latinos, and Native Americans in the economics profession. In the absence of a large and established literature on implicit biases and systemic discrimination in economics specifically, Bayer and Rouse leverage evidence of biases across a range of academic fields and career paths. The authors argue that economics may be severely behind peer fields in addressing biases and that, ultimately, more research and investment into diversity in economics is essential to the future of the field.
Bayer and Rouse present the statistic that in 2016, only 23.5 percent of tenured and tenure-track faculty in economics are women, with only 15 percent of full-professorships allocated to women. The authors note that "minority academic economists are even rarer" with only 6.3 percent of tenured and tenure-track economists identifying as African American or Hispanic, compared to about 30 percent of the overall US population.
Diversity in economics shows little improvement over time and has even gotten worse relative to other academic fields. These trends are visible in the chart below depicting the number of bachelor and doctorate degrees awarded to women and minority students over the past 20 years, presented originally by Bayer and Rouse. Additionally, hiring disparities are further exacerbated by striking gender salary gaps and publishing gaps. The authors cite that "female full professor salaries in economics as a proportion of male salaries dropped from 95 percent in 1995 to less than 75 percent in 2010," (Ceci, Ginther, Kahn, and Williams 2014). Further, female authorships only make up 13.7 percent of all economic publications since 1990. Comparing this statistic to an overall average of 27.2 percent across 21 academic disciplines shows clear evidence of underrepresentation in economics (West, Jacquet, King, Correll, and Bergstrom 2013). These facts present the state of the field as not only disparate in absolute but as having regressed over time and relative to peer academic fields.
Bayer and Rouse acknowledge that many academics participate in efforts to address diversity, and that the persistence of the issue is not for lack of intentional effort. However, studies of academia show that implicit biases and institutional discrimination form barriers to women and underrepresented minorities in many academic fields and at all stages of the academic pipeline. In their 2015 study, Milkman, Akinola, and Chugh measure that after receiving an email from fictional prospective doctoral students asking for a ten-minute meeting about research opportunities, social science faculty (which included economists) responded to 75 percent of Caucasian males' emails and only 68 percent of emails from women or minority students. Business school faculty responded to 87 percent of emails from Caucasian males and only 62 percent of emails from women or minorities. Similar studies reveal bias in the hiring of academic researchers in the sciences (Moss-Racusin et al. 2012), and in the language used in recommendation letters for academics in Psychology (Trix and Psenka 2003). Though these studies are not specific to economics, they suggest evidence of bias in academia and present opportunities for research into how economics may suffer from similar discriminatory practices.
Perhaps the strongest contribution of Bayer and Rouse's article is the in-depth evaluation of supply- and demand-side barriers to diversity in economics specifically. In addition to reviewing research on other academic fields, the authors discuss unique challenges faced by economics and debunk popular understandings of these disparities. For example, math preparation and aptitude cannot explain the gender gap in economics (Emerson, McGoldrick, and Mumford 2012). Additionally, the authors cite that women are more responsive than men to their grades in economics relative to their grades in other courses. This behavior has not been observed in other quantitative disciplines, demanding the questions of whether there are characteristics specific to economics that inhibit female students from feeling competent in the coursework (Rask and Tiefenthaler 2008). Bayer and Rouse assert that if economics alone faces this behavioral pattern, then it may be a result of advising practices or culture. Finally, a recent working paper by Heather Sarsons focuses on tenure evaluations in economics and reveals that women receive a penalty for co-authoring relative to their male peers.
Finally, Bayer and Rouse defend the importance of diversity in economics as not only an extension of equal opportunity but a means for better and more robust research production. The authors cite studies addressing the scope, quality and efficiency of producing ideas with a diverse group of academics. One key study showed that "male and female economists have different views about economic outcomes and policies, even after controlling for vintage of PhD and type of employment" (May, McGarvey and Whaples 2014). This study demonstrates the need to evaluate how the demographic composition of economists affects policy and economic outcomes for the whole of society. Bayer and Rouse call for a continuation of this work and laud the current steps being taken by the discipline already.
Author: Emily Eisner