Women on Wall Street are just as connected as men, but their connections aren’t as helpful to their career growth as they are for their male counterparts.
Male analysts gain more from their connections with executives at the companies they cover than their female counterparts, shows new research by INSEAD Associate Professor of Finance, Lily Fang. In her paper, Gender and Connections among Wall Street Analysts, forthcoming in the Review of Financial Studies, she finds that women and men on Wall Street are just as connected as each other, but men are perceived to be better analysts because of their connections.
She measured connections by analysing alumni ties between the analysts and senior officers or board members. Women, like men, share a school tie with a senior officer or board member in about 25 percent of the firms they cover. But there is a big difference in how these connections help male and female analysts in their jobs.
While connections improve forecast accuracy for both male and female analysts , the effect is stronger for males. These ties lead to a 2 percent improvement in rankings of accuracy in general, but there is a further improvement for men of 4 percent. This is because the market reacts more favourably to their buy and sell calls. Connections improve male analysts’ recommendation impact by more than 1 percent, but not at all for female analysts.
Fang also found that connections play a different role in male and female analysts’ odds of being given the “All America Research Team” (AA) all-star title, which is awarded to those voted as top analysts by thousands of fund managers in an opinion poll organised by Institutional Investor magazine. The poll asks investors to evaluate analysts on industry knowledge, communication, responsiveness, quality of written reports and forecast accuracy. Analysts’ career prospects can be massively impacted by the AA ranking, with winners of the titles earning around three times more than those without it.
The results of the study show that while connections contribute to both men’s and women’s odds of success, they cause different outcomes when the analysts make forecast errors. For men for example, forecast errors reduce a male analyst’s chance of winning the AA title, but the more connected he is, the less negative the effect of his errors is. For female analysts, connections actually accentuate rather than attenuate the effect of forecast errors.
“We also show that the very different impact of connections on job performance was particularly pronounced among young analysts. This vastly different ability to capitalise on connections at such an early point in their career paths could explain gender gaps that exist throughout long-term career trajectories. The cycle, it seems, starts at the entry level,” said Fang.
Fang also showed that part of the difference in perceptions of male and female analysts lies in the fact that there are so few female officers and directors at the firms under coverage. While female analysts are not under-represented in the AA analyst pool, they had less female-female connections than the men had with other men. Fang observed that female analysts with a connection to a female executive at the firm under coverage reduced forecast errors by 3.8 percent and enhanced their recommendation impact by 0.7 percent. This compares to 2.1 percent when a female analyst is tied with a male executive. But again, male analysts benefit more from same-sex connections, with performance improvements nearly twice as large. Male-male connections were associated with a 7 percent reduction in forecast error and 1.1 percent increase in recommendation impact.
“Thus the value of the “old boys club” is hard to refute in our data. We believe our work reveals the bittersweet reality of the decades-long effort in pushing for gender equality. On the one hand, we should celebrate the fact that outright gender discrimination in education, hiring and promotions are on the decline. On the other hand, the evidence clearly points to a more subtle—yet perhaps more insidious—form of gender bias: men and women may be evaluated using different criteria in our subjective minds,” she added.
