The gender gap in economics is large and persistent. I've written a number of posts on this point, and on some of the initiatives that the profession is enacting to try and address the gap (see this post, and the links at the end of it). There is also a large gender gap in STEM (science, technology, engineering, and mathematics) subjects as well. However, one discipline where I haven't seen much discussion is finance.
That is addressed in this new working paper (with a non-technical summary here) by Renee Adams (University of Oxford) and Jing Xu (University of Technology Sydney). They use data from this paper by Ioannidis et al., which provides a database of standardised citations and other measures for over 160,000 scientists across 175 fields of science, in 20 disciplines. Interestingly, the list of fields includes economics (actually, several fields relate to economics) and finance. However, there is a bit of an issue with this data, as it does not include the gender of each scientist. Adams and Xu code the gender of those in the finance field manually, and use genderize.io to automatically assign gender to the others. This is a little problematic, as genderize.io doesn't deal well with some names (particularly Asian names). Adams and Xu drop those that cannot be gender classified with at least 90% certainty, leaving them with data on 126,403 scientists (including finance and economics).
With their dataset in hand, Adams and Xu then focus on the top two percent of researchers in each discipline, and compare metrics by gender. They find that:
Finance ranks 132nd out of 175 fields in terms of the representation of women among its top scientists. The percentage of women in Finance is lower than the percentage of women in economics...
Economics doesn't fare a whole lot better than finance, ranking 125th out of 175, with 11.2% of top scientists being women (compared with 10.3% for finance). Adams and Xu then look at this using a statistical model, finding that after controlling for career span:
The coefficient on finance is -0.016, which suggests a scientist in finance is 1.6% less likely to be a woman than a scientist in Economics4... we compare women’s representation in finance and STEM9 fields and find a scientist in finance is 1.8% less likely to be a woman than a scientist in STEM9 fields... we compare women’s representation in finance to their representation in all other fields. The results shows that a scientist in finance is 7.5% less likely to be female than a scientist in other fields.
So, top scientists are much less likely to be female in finance, than in economics (incidentally, 'economics4' is made up of the four economics fields: agricultural economics and policy, economics, econometrics, and economic theory), in STEM, and across all fields. However, it is their next results that are most surprising, and set finance apart. When looking at academic rank, the number of papers, citations, and other metrics of research quality, Adams and Xu find that:
On aggregate, women’s ranks are 7.7% lower than the ranks of their male peers in the same field. The gap increases to 9.3% in STEM9 fields. When we examine the gender gap in ranks in Economic4, we find the gap is much smaller (2.1%) and statistically insignificant. We also find that women in Economics4, STEM9 fields and all fields have fewer cited papers and lower total citations...
Female finance academics have 13.9% fewer cited papers but on average each of their papers has 18.6% more citations than papers by male finance academics.
So, while in most fields female academics have fewer papers and fewer citations, in finance they have fewer papers but more citations. This suggests that female finance academics are more influential within their discipline than female academics in other disciplines, and despite this, the overall representation of women in the top two percent of finance academics is lower. What explains this anomaly?
Adams and Xu don't really answer that question, but they do implicate 'ability belief' as a driver of the low representation of women in finance. They define 'ability belief' as:
...individuals’ beliefs about the importance of innate talent in their fields.
It is measured based on responses (taken from this study) to:
...the following questions:(1) Being a top scholar of [discipline] requires a special aptitude that just can’t be taught; (2) If you want to succeed in [discipline], hard work alone just won’t cut it; you need to have an innate gift or talent; (3) With the right amount of effort and dedication, anyone can become a top scholar in [discipline]; (4) When it comes to [discipline], the most important factors for success are motivation and sustained effort; raw ability is secondary. Fields in which respondents placed more weight on (1) and (2) are considered fields with higher field specific ability beliefs.
Using this measure as a predictor of women's representative in a field, Adams and Xu find that:
The coefficient on Ability belief is -0.169 and significant at the 5% level. A one standard deviation increase in Ability belief is associated with a 0.585 standard deviation decrease in women’s representation.
When women's and men's beliefs are included separately in the model, only men's beliefs are statistically significant. Adams and Xu conclude that:
These results suggest that women face greater barriers to entry into finance than men do.
Yeah, I don't understand that conclusion either. Adams and Xu don't do a good job of explaining why men's beliefs about innate ability reduce women's representation at the top of the finance discipline. I'll need that explained to me in sentences composed of very short words, I think. Nevertheless, the descriptive results are pretty damning for finance (and they don't look particularly good for economics either, to be fair). Clearly, there is more to do. Unfortunately, this paper is short of solutions.
[HT: The Conversation]
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