Internal rates of return for college majors in the US

This week, my ECONS102 class covered the economics of education. Part of that topic involves understanding the private education decision - the decision an individual makes in weighing up the costs and benefits of further education, acknowledging that most of the benefits of education happen in the future, and therefore must be discounted in order to be compared to the costs, which are mostly incurred in the present or near future. As part of that topic, I get my students to evaluate the costs and benefits of their own education decision. For most students, the benefits far outweigh the costs, using a discount rate of 10 percent. However, if the discount rate were higher (and so the future was discounted more heavily), the present value of the benefits would be lower, and more of the students would end up with costs exceeding benefits. The discount rate that perfectly balances benefits and costs is called the internal rate of return (IRR). A higher internal rate of return means that the benefits outweigh the costs by more (since it requires a higher discount rate to equalise the benefits and costs).

Anyway, that is a long introduction to this 2024 article by Liang Zhang (New York University), Xiangmin Liu (Rutgers University) and Yitong Hu (New York University), published in the American Educational Research Journal (ungated version here). They estimate the distribution of internal rates of return for college majors in the US, using earnings data from the American Community Survey from 2009 to 2021. Importantly, in terms of benefits they look at the incremental (extra) earnings over and above what high school graduates earn. The costs side of the equation uses data from the National Postsecondary Student Aid Study (NPSAS).

Zhang et al. use the benefits and costs data to estimate IRRs. Overall, in their preferred specification:

...the IRR for a college education is estimated to be 9.88% for women and 9.06% for men.

However, those overall results hide a lot of heterogeneity. Looking across different majors:

...there are large variations in IRRs across college majors. Specifically, engineering and computer science majors command the highest IRRs among all majors, exceeding 13%. Additionally, a few other majors such as business, health, and math and science have higher IRRs than the overall college population, ranging from 10% to 13%. The next tier, including biology, social science, and other majors, have IRRs of 8% to 9%. Finally, education and humanities and arts majors have the lowest IRRs, especially for men in those fields.

Interestingly, on the gender difference in IRR, Zhang et al. note that:

...on average, women tend to have higher IRRs than men for college education in general. However, this does not necessarily mean that female graduates earn more than their male counterparts who are men. In fact, the opposite is true: Women in our final sample earned approximately 28% less than men among college graduates and about 33% less than men among high school graduates. The lower earnings for women among high school graduates also means that women generally have lower opportunity costs while attending college.

I still read that as saying that women gain more from a college education than men do, even if the gender wage gap means that they don't earn as much as men. The difference in IRRs between women and men would be even greater if there was no gender wage gap.

Further exploring the heterogeneity, Zhang et al. use quantile regression to evaluate the distribution of internal rates of return. The resulting distribution can then be summarised graphically, as in their Figure 2:

The axes are difficult to read on that figure, but the values are somewhat less interesting than the distributions. The x-axis shows (I believe) the decile of the earnings distribution, so this figure shows how IRRs differ between those graduates who earn at the bottom, middle, and top of the earnings distribution (overall at the top, and for each major at the bottom). The interesting ones are those that somewhat counterintuitively have lower IRRs for those at the top of the earnings distribution than for those in the middle or at the bottom (like education, engineering, and health). What is likely happening there is that, in those fields, the difference in earnings between the top earners who went to college and the top earners who have only a high school education, is less than the difference for those lower down the earnings distribution. That makes sense in engineering (top engineers without a degree might still earn a lot) and health (nurses don't necessarily require a college degree), but is less easy to explain for education. Zhang et al. describe the results, but unfortunately don't offer a good explanation for them.

Overall, and for each major, it does seem that a college education is a good investment. A nine percent return is difficult to match. There is, as you would expect, some variation between different majors, and even within majors. That variation also needs to be taken into account by anyone carefully considering the private education decision.