To know why fewer women choose math and science, you need to know the principle of occupational choice.

Why are there so few women in science? Is it because the STEM fields are biased against women?

We can all agree that sexism exists, is bad, and needs to end. But in a world where all are equally welcome in every line of work, would every occupation be 50 percent female? If not, should we be measuring our progress in fighting sexism in science by the sex ratio of the scientists? My answers are no, and no.

If sexism is the only cause of women’s under-representation in science, then the environment in STEM fields today must be very bad – even worse than it was in medicine and law in the 1960s and ’70s, a time when women’s representation in these professions was increasing dramatically.

This seems unlikely. Law is claimed to be sexist even today, even though the overall sex ratio is quite balanced. And sexism is the last thing one would suspect of academic sociologists, yet there is a marked preponderance of men in the more mathematical subfields of sociology (Section #3 here). Sexism exists, but something else is going on.

Another popular hypothesis is that the distribution of mathematical abilities has a higher variance for men than for women, so that men form a majority in the upper tail. The problem is that most of us are nowhere near the upper tail in any distribution, and yet we all manage to find work. Men form a majority of electrical engineers, but also a majority of electricians. Different variances might matter at the very top (and bottom) but, again, something else is going on.

In my opinion, the key element missing from this discussion has been an understanding of occupational choice. Many people seem to assume that in a world without sexism, if two people are equally good at math they will be equally likely to enter a STEM field. This belief is false.

The basic economic principle guiding occupational choice – comparative advantage – was discovered by David Ricardo in the early 1800s. It is simple but very powerful. It helps to explain patterns of occupational choice, it gives normative guidance on what those choices should be, and it suggests policies that can help achieve these goals.

Let me illustrate with an example from my first-year economics course. Suppose there are only two subjects in high school – English and mathematics. Performance in either indicates intelligence and industry, but math performance also indicates the potential to be a good scientist, while performance in English also indicates (let’s say) the communication and empathetic skills necessary to be a good doctor.

High school boys lag behind girls in every subject but math. So let’s suppose Susan is getting 90 percent in math and 95 percent in English, while Steven is getting 90 percent in math and 85 percent in English. Who is more likely to major in science?

The choice to enter a field does not depend just on your expected success compared to others in that field. What matters is your expected success relative to what you can expect to achieve by doing something else. You are making a choice. So perhaps the best reply to our question about why so few women are in STEM is simply another question: “What else are the men in STEM going to do?”

Comparative advantage matters. A simple regression will show that students are somewhat more likely to choose a STEM field if they have good grades in math. But the ratio of their math grade to their overall average adds a lot to this regression. The same pattern is seen when the results of aptitude tests are used instead of grades.

Should we be encouraging more women to enter STEM fields? In our example, Susan is as good as Steven at math, so she will be equally good as a scientist. But what if favouring Susan for a math or science field forces Steven to seek work elsewhere? In general, the pattern of job assignments that wrings the most from our limited human resources is the one that respects comparative advantage. In our example, that means Steven should be the scientist and Susan the doctor.

Of course productivity isn’t everything, and we might still wish for greater gender balance in all fields. An understanding of comparative advantage is useful here as well. Current educational policies focus on encouraging girls in math and science. What if we put the same energy into helping boys do better in all the other subjects? This would increase the proportion of women in STEM by giving boys an alternative. At the same time it might begin to address the other major equity problem in our universities – the severe under-representation of males.

Surely this is a policy we can all support.

Dr. Carmichael is professor of economics at Queen’s University.