Connecting on Wall Street
Are male and female financial analysts evaluated on the basis of different criteria?
- Wall Street is a fascinating place to study gender and performance evaluation.
- Wall Street is legendarily male-dominated, notoriously clubby and highly competitive.
- Women and men are evaluated and promoted on different criteria.
- For women, we find that performance forecast accuracy is important. For men, we find the opposite.
Why is the business world still unfriendly to women, even after decades of promoting gender — and other forms of — diversity?
Part of the answer lies in work-life balance and female attrition in the corporate world.
Many promising young women quit work when they start to have children and a large number of them find it difficult to regain the same position and momentum if and when they return.
Some argue that the problem is that women are not aggressive enough in self-promotion.
Lois Frankel writes in her book that “nice girls don’t get the corner office” because they don’t ask. Sheryl Sandberg, COO of Facebook, argues that women don’t “sit at the table” enough and that they don’t raise their hands enough.
Sandberg and other powerful women argue their positions with eloquence. These views implicitly suggest that women themselves are at least partly to blame for the problem: dropping out of the workforce and not seeking promotions are choices women make, which have negative consequences for their career path — hence, the observed glass ceiling.
Patterns on Wall Street
But there might be another factor and it has nothing to do with the choices women make. Rather, it simply reflects the fact that women and men are evaluated — and promoted — on different criteria.
I myself was surprised by this finding, after examining how stock analysts are evaluated and promoted on Wall Street.
Wall Street is a fascinating place to study gender and performance evaluation for at least three reasons. First, Wall Street is legendarily male-dominated.
After decades of promotion of gender diversity, women now account for close to 20% of Wall Street analysts — a proportion much higher than the female presence in the corporate C-suite.
Second, Wall Street is notoriously clubby. Thus, “who you know,” or your social network, can make a big difference in performance and career outcomes.
Third, Wall Street is highly competitive. The difference between success and failure is a difference between making millions of dollars and losing one’s job.
Female analysts are, on average, better educated than their male colleagues, at least as measured by the number with Ivy League degrees.
Nearly 35% of the female population on Wall Street are Ivy Leaguers, compared with 25% for men. This figure is consistent with the idea that only the most competitive female graduates enter the Wall Street labor market.
Female analysts, on average, tend to cover slightly fewer firms than men. This is perhaps a reflection of the challenges for women in maintaining work-life balance.
Surprisingly, female analysts are, on average, just as connected as their male colleagues. They share a school tie with a senior officer or board member in about 25% of the firms they cover.
Finally, there is overall no gender bias in the odds of becoming an “all-star” analyst.
“All-star” status is awarded by the influential Institutional Investor magazine based on an annual survey of thousands of investment managers who are asked to vote for the best analysts of the year (by industry).
Women account for about 15% of the overall analyst sample and they also account for about 15% of the all-star sample.
But this is where the symmetry ends. When we go on to examine analysts’ connectedness and its impact on their career advancement — that is, whether they are voted all-stars — we find an intriguing asymmetry.
For women, we find that performance forecast accuracy is important: making inaccurate forecasts hurts a female analyst’s chance of being voted an all-star.
We also find that Ivy League degrees and years of experience matter and both contribute positively to the odds of being voted an all-star. After accounting for these factors, however, connections, per se, do not matter for female analysts.
For men, however, we find almost the opposite. Connectedness remains one of the strongest factors that enhance men’s odds of being voted an all-star, even after accounting for forecast accuracy and whether an analyst attended an Ivy League school.
In fact, the latter two factors have no significant impact on men’s odds of being voted an all-star.
For women, forecast accuracy and education mattered. For men, neither factor is very important; rather, connections mattered.
Interestingly, this is not an “Ivy League” effect.
If it were, women would have the upper hand: in our sample, more of them attend Ivy Leagues than do men.
Our results show that for women it is performance or demonstrated competence (proxied by high education achievements) that matters, while for men it is soft information, such as their connections, that counts.
I am neither a feminist nor an expert on gender issues. I stumbled upon these findings reported virtually by accident as a result of my curiosity as a financial economist. But they have helped me understand a number of patterns.
For example, while 14% of Wall Street’s all-stars are women, virtually none of the top bosses in any of the big firms are.
Where did all the highly educated, highly connected and high-potential women go? They largely remain in analytical roles as “analysts,” rather than being promoted into general management, a process that entails subjective evaluations.
There is slow progress, even in the C-suite. A recent Bloomberg article reported that in 2012, the number of women CFOs at Standard and Poor’s 500 companies increased 35%, from 40 to 54, to a record high of 10.8%.
But moving to the top remains difficult.
The asymmetry in women’s success at breaking the C-suite glass ceilings is a telling indication that it is far easier for women to demonstrate technical and measurable skills than to overcome potential biases in subjective qualitative evaluations.
Editor’s note: A longer version of this article originally appeared in Finance & Development, published by the International Monetary Fund. It is reprinted with permission from the publication and author.