The effect of studying STEM at high school on employment and wages

Much of the literature on studying STEM (Science, Technology, Engineering, and Maths) at high school focuses on how well it prepares or motivates students to study STEM at university. There is very little consideration of what happens to student studying STEM who don't then go on to university. This 2016 article by Robert Bozick (RAND), Sinduja Srinivasan (Economic Commission for Latin America and the Caribbean), and Michael Gottfried (University of California - Santa Barbara), published in the journal Education Economics (sorry, I don't see an ungated version online) is different. They look explicitly at the employment outcomes of high school STEM studies for non-university-attending students.

Specifically, Bozick et al. use data from the Education Longitudinal Study of 2002 (ELS:2002), which includes a sample of 3473 students who did not go on to attend university-level study. For those students, they have detailed information on their employment outcomes (whereas there is no such data for the university-bound students). What they find is essentially nothing in terms of employment in STEM:

...taking advanced academic STEM courses or applied STEM courses in high school does not improve the likelihood that non-college bound youth will secure jobs in the STEM economy. In fact, there is evidence that some applied STEM courses may serve as a barrier: non-college bound youth who took IT courses in high school were less likely to find employment in the STEM economy than their peers who did not take IT courses in high school...

There is also no statistically significant effect on wages:

In terms of academic STEM courses, all of the effects for above average and advanced math and science courses are positive, but none of them are significantly different from zero. The largest effect among these courses is for advanced math, which includes Calculus and similar classes of that caliber. Relative to students who had taken average math, students who had taken advanced math have a 0.095 wage advantage in their first job and a 0.077 wage advantage in their current job, which translates to approximately $2200 and $2160 per year, respectively. Again, though, these effects are not significantly different from zero.

Looking at wages specifically in STEM jobs, they also find no effect. In other words, studying STEM at high school does not set these students up for jobs in STEM, or as Bozick et al. put it:

Our study indicates that the courses currently offered in America’s high schools are not improving the labor market prospects of non-college bound youth entering the STEM economy after finishing high school.

However, I think the authors may have been a little too negative in their interpretation. Sure, the results are statistically insignificant. That means that the results are not statistically distinguishable from zero. However, if you look at the wage premium in the quote above, the wage premium of maths is also not statistically distinguishable from an advantage of $4000 per year. That is potentially a sizeable effect, given that the average wage in the sample is around $18,000 per year.

The problem here is a lack of statistical power. Studying STEM might have an impact on employment and wages, but this sample is too small to precisely estimate the size of the effect. You might think that a sample of over 3400 is large, but it depends on context. In this case, it limits what the authors can conclude from their results. All that they can say with any reliability is that the wage premium is less than $4000 per year, which isn't saying much.

The other problem with this study is self-selection. Students were not (and cannot be) randomised into whether they went to university or not. This sample also didn't randomise students into who studied STEM. So, it is somewhat limited in terms of what it can say about the causal effect of studying STEM on employment and wages.

Overall, we're going to need a lot more research, probably including studies with some form of randomisation or quasi-randomisation, and larger sample sizes, before we conclude that studying STEM at high school is a waste of time.