The gender gap in academic economics in New Zealand

Last year, this article by Ann Brower and Alex James (both University of Canterbury), published in the journal PLoS ONE, got a lot of press (see here or here, for example). Brower and James used data from the Tertiary Education Commission from the Performance Based Research Fund (PBRF) assessment rounds from 2003-2012, along with details on researchers' gender and academic rank (lecturer, senior lecturer, associate professor, professor), to infer things about the gender gap in academia in New Zealand. They found that:

...women’s odds of being ranked, and paid, as Professor or Associate Professor, (i.e. in the professoriate) are lower than men’s... However, women have lower research scores... and the average woman is 1.78 years younger than the average man...

Neither controlling separately for recent research performance with the 2012 research score, nor age using logistic regression... diminishes the gender odds ratio of being in the professoriate...

Controlling for gender, age, 2012 research score, research field, and university together only decreases the gender odds ratio of being in the professoriate to 2.2...

In other words, the log odds of a woman being an associate professor or professor, controlling for their age and research performance, are 2.2 times lower than for men. Brower and James also extended their analysis to difference in pay, and showed that similarly the pay difference wasn't explained by research performance. These are important results, although they tell us little about the underlying reasons why the gap exists.

Anyway, I didn't read the article at the time, but Thomas Lumley at StatsChat made some useful comments:

The big limitation of any analysis of this sort is the quality of the performance data.  If performance is measured poorly, then even if it really does completely explain the outcomes, it will look as if there’s a unexplained gap.  The point of this paper is that PBRF is quite a good measurement of research performance: assessed by scientists in each field, by panels convened with at least some attention to gender representation, using individual, up-to-date information.  If you believed that PBRF was pretty random and unreliable, you wouldn’t be impressed by these analyses: if PBRF scores don’t describe research performance well, they can’t explain its effect on pay and promotion well.

There could be bias in the other direction, too.  Suppose PBRF were biased in favour of men, and promotions were biased in favour of men in exactly the same way.  Adjusting for PBRF would then completely reproduce the bias in promotion, and make it look as if pay was completely fair.

Aside from those criticisms, I wondered about the pay data. It is true that pay for Lecturers and Senior Lecturers is fairly easy to infer from the collective employment agreements, but that isn't the case for Professors, who as far as I can tell, have an incredible diversity of pay rates. Measurement error on both sides of the equation creates some serious problems for the pay analysis, so let's put that aside, and focus on the analysis of academic rank.

Having finally read the article myself this week, this bit in particular caught my eye:

Breaking field into 42 subject areas shows variability amongst areas... When predicting the probability of being in the professoriate, most have a gender odds ratio above 2; in only 9 subject areas are women advantaged (i.e. have an odds ratio less than 1)...

Like me, you're probably now wondering what the nine subject areas are where Brower and James found an advantage for women. I dug into the supplementary materials (which are available at the journal article link), and I can reveal that the nine subject areas are: Nursing; Pharmacy; Economics; Pure and Applied Mathematics; Architecture, Design, Planning, and Surveying; Engineering and Technology; Anthropology and Archaeology; History, History of Art, Classics and Curatorial Studies; and Communications, Journalism and Media Studies.

That list should certainly give some pause for thought, particularly the bolded example. Given the fairly-well-established gender gap in economics (see yesterday's post, and the long list of links at the end of it, for example), how plausible are these results? What about for mathematics and engineering?

Taking a step back, the results say that women are advantaged relative to men in those nine subject areas (and the odds ratios for all nine subjects are statistically significant), controlling for age and research performance. You could still observe an unconditional difference in the proportion of women who are part of the professoriate in those subjects, if women in those subjects are disproportionately younger and/or have lower research performance than men. I don't know about mathematics or engineering, but that could possibly be the case for economics. As I noted in this 2017 post:

The top 25% ranking for New Zealand economists can be found here. Of the 66 economists in that list, only five (that's 7.6% for those of you keeping score) are women (#26 Suzi Kerr; #44 Trinh Le; #58 Anna Strutt; #59 Rhema Vaithianathan; and #61 Hatice Ozer-Balli).

Updating that list as of today, there are 74 economists in the New Zealand top 25% ranking, of which only seven are women (#25 Suzi Kerr; #43 Trinh Le; #53 Hatice Ozer Balli; #66 Gail Pacheco; #68 Anna Strutt; #70 Susan Olivia; and #73 Asha Sundaram). That's still less than 10 percent women - economics is not exactly covering itself in gender-equality glory in terms of research performance (although I would be remiss if I didn't point out that two of the seven are at Waikato, and one of the others is a Waikato PhD graduate). At least there are a few new female economists' names appearing in the list.

So, research performance among New Zealand women economists is much lower than for men. However, they don't appear to be disproportionately high in academic rank. Of the seven women in that top 25% list, Suzi Kerr and Trinh Le are at Motu (so not in Brower and James' dataset), Gail Pacheco and Anna Strutt are Professors, and Hatice Ozer Balli is an Associate Professor. Susan Olivia and Asha Sundaram are both Senior Lecturers. The proportion of men in the top 25% list who are Professors or Associate Professors seems to be much higher than for women. It beats me how economics ends up such an outlier in Brower and James' analysis. If anything, I would have expected economics to be an outlier in the other direction.

Finally, Brower and James conclude with:

Taken singly, the internal logic of each hiring or promotion decision might cohere. But taken together, they reveal a strong pattern in which a man’s odds of being ranked associate or full professor are more than double those of a woman with equivalent recent research score and age.

Except for some pretty surprising outliers.