Girls’ comparative advantage in reading can largely explain the gender gap in math-related fields

In an earlier post, Do Boys Have a Comparative Advantage in Math and Science? I pointed to evidence showing that boys have a comparative advantage in math because they are much worse than girls at reading. (Boys do not have a large absolute advantage in math.) If people specialize in their personal comparative advantage this can easily lead to more boys than girls entering math training even if girls are equally or more talented. As I wrote earlier:

[C]onsider what happens when students are told: Do what you are good at! Loosely speaking the situation will be something like this: females will say I got As in history and English and B’s in Science and Math, therefore, I should follow my strengthens and specialize in drawing on the same skills as history and English. Boys will say I got B’s in Science and Math and C’s in history and English, therefore, I should follow my strengths and do something involving Science and Math.

A new paper in PNAS by Breda and Napp finds more evidence for the comparative advantage hypothesis. Breda and Napp look at intention to study math in ~300,000 students worldwide taking the PISA.

PISA2012 includes questions related to intentions to pursue math-intensive studies and careers. These intentions are measured through a series of five questions that ask students if they are willing (i) to study harder in math versus English/reading courses, (ii) to take additional math versus English/reading courses after school finishes, (iii) to take a math major versus a science major in college, (iv) to take a maximum number of math versus science classes, and (v) to pursue a career that involves math versus science. Our main measure of math intentions is an index constructed from these five questions and available for more than 300,000 students. It captures the desire to do math versus both reading and other sciences.

What they find is that comparative advantage (math ability relative to reading ability) explains math intentions better than actual math or reading ability. Comparative advantage is also a better predictor of math intentions than perceptions of math ability (women do perceive lower math ability relative to true ability than do men but the effect is less important than comparative advantage). In another data set the authors show that math intentions predict math education.

Thus, accumulating evidence shows that over-representation of males in STEM fields is perhaps better framed as under-representation of males in reading fields and the latter is driven by relatively low reading achievement among males.

As the gender gap in reading performance is much larger than that in math performance, policymakers may want to focus primarily on the reduction of the former. Systematic tutoring for low reading achievers, who are predominantly males, would be a way, for example, to improve boys’ performance in reading. A limitation of this approach, however, is that it will lower the gender gap in math-intensive fields mostly by pushing more boys in humanities, hence reducing the share of students choosing math.

The authors don’t put it quite so bluntly but another approach is to stop telling people to do what they are good at and instead tell them to do what pays! STEM fields pay more than the humanities so if people were to follow this advice, more women would enter STEM fields. I believe that education spillovers are largest in the STEM fields so this would also benefit society. It is less clear whether it would benefit the women.

Hat tip: Mary Clare Peate.


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