This is part of a series explaining common economics misconceptions TL;DR: Breakdown of possible explanations of increase in education price. Brian Caplan is probably wrong.

A few days ago, a /r/badeconomics user asked what solution should be proposed if universities increased tuition costs to match the increase in lifetime earnings from the diploma they offer.

He proposed price controls, capping administrator salaries, encouraging trade schools and subsidies to students among other solutions. Price controls are close to a being a unilaterally bad solution to economic problems, but the goal today isn’t to bash on bad solutions. Rather, we want to understand the underlying dynamics in the price increase of education so we can judge solutions on their true merit. [footnote]Fancy way of saying “WHATS YOUR MODEL”[/footnote]

Giving a true satisfying explanation to this question require nothing short of a full unifying theory of labor economics. [footnote]That’s not it, but it seemed like good place to cite it[/footnote] So let’s first tone down the ambition and start by noting general trends. The price of a university education increased a lot in the US. In Canadian data, professional degrees have increased in price at a much faster rate.

The The share of college educated population has also been increasing.

The growth in wages have been significant and positive for college graduates but negligible or negative for those with lower education.

Possible Explanations

There are three concurrent explanations for the increase in the cost of education we’ll go over. It’s important to remember that no one of the three will explain all of education economics, so what I would like you to do is instead assign weights to each of the theories – for example, you might think the first theory explains 75%, the second 20% and the last 5%. These weights should change based on the empirical evidence you come across. For example, if you read Brian Caplan’s latest book, very one-sided book, you know he is trying to convince you to shift weights towards one of the competing explanations.

• Education could simply be a consumption good. People could be getting education because they think it’s fun or enriching to their lives. This sounds unconvincing as an explanation of the market trends, and it is, but partial explanations are helpful to understand the overall picture.

Certainly, when one sees the exploding sector of additional amenities at universities, or the fact that admissions into doctoral programs in the humanities are competitive, despite the difficult job market prospects of those programs, we should still assign a non-zero weight to this explanation.

If education is simply a consumption good, there’s not much to do except perhaps tax it as we would luxury consumption good.

• Education increases human capital. In this scenario, we assume education makes the student smarter and he gets a higher wage for the rest of his life by being better at what he’s doing. This explanation for the growth in college-educated wages is called skill biased technological change, (SBTC) which basically says that tech progress in the last 30 years has favored the highly educated becoming more productive.

If SBTC explains the dynamics, then “reducing total investment into education” as proposed in the reddit post would be a disaster. Dollars spent in education translate into higher wages for the educated and higher overall GDP. Moreover, students already under-invest in their education: simply helping prospective students fill out forms increases their enrollment by 15-25% (!!!). If we believe in SBTC, the we would want to help students who are unlikely to get an education at a young to improve those chances.

• Education can act as a market signalling mechanism. This model says that education provides no value at all, but is hard to achieve for people with low natural abilities and as such provides workers with a way to differentiate themselves from the of the labor pool.

The signalling model has an interesting prediction, called the pooling equilibrium. This says that the wage a group with a certain education commands is equal to the average skill of the people in that group.

For example, let’s say a university moves into a town: more people now go who otherwise would not have because of logistics. First, the group of people with a high school education is now on average worse, because its best people are now instead in the university group. Which implies that the high school dropout rate should increase, because completing high school to avoid university has lower value as a signal on the job market.

In the original signalling model, it’s important to note that the burden of the cost signalling dance is bore by the one emitting the signal. This would then imply that universities are simply middlemen capturing market inefficiencies by charging money for providing a signal.

Brian Caplan’s Case Against Education one-sidedly argues signalling is the biggest mechanism behind education and he recommends cutting all subsidies to education and instead promoting vocational education of practical skills instead. We’ll get to how reasonable those ideas are in the next section.

Just tell me what to think already

Not so fast.

It’s clear that both SBTC and signalling explain the overall trends well. In both models, people who attend college are more productive, have higher wages and invest in their education at the start of their lives [footnote]Which is a strong argument against education as consumption – it would happen at a higher frequency later in the lifecycle if it were a bigger factor[/footnote].

If the share of the college educated increases, then the pool of non-college educated has lower average ability and its wage should decrease. On the other hand, if SBTC explains the trends just as well – more people attend college and have higher wages because they get benefit from the advancement of human knowledge this way.

It’s worth mentionning that the best evidence we have for education being signalling is at best indirect. Books claiming education is worthless signalling, like Caplan’s, or Academically Adrift before it, are really just aggregating sort-of-related studies into a one-sided case. Even serious studies on the matter, like Bedard 2001 are measuring second-hand empirical predictions. The only serious first-hand evidence I ever found is Tyler et al. (2000) which finds that GED degrees hold signalling value, but this still says nothing about college.

Of course there’s also very serious evidence for SBTC – labor demand for high skill jobs has simply increased in the last decade.

Other serious studies find evidence for both signalling and human capital. Arrrrg.

Overall, however, I find Brian Caplan’s recommendations unwise, if only because of how they fit in with the rest of the trends in the labor market. The labor market seems to be polarizing between high and low skill jobs and recommending to invest in vocational (eg. middle skill) professions massively seems risky and unwise. This is compounded by the fact that automation of tasks seems to target middle skilled tasks, so specializing in one such task is a risky career venture. Ask truck drivers how they feel about the 15 year prospects of their middle skill profession, for instance.

Even if education is pure signalling, not subsidizing poorer students will simply decrease economic mobility and worsen inequality: only rich students will be able to afford the signal. On the other hand, if human capital exists even a little bit, then subsidizing is a good idea. So overall, if we’re thinking like good Bayesians, cutting funding to education programs seems like a bad idea.

Having more flexibility to the school system is a good idea. Education economics expert Philip Oreopoulos (2014) argues that two year programs are a large positive addition to a significant subgroup. Even if we only believe in signalling, making the signal closer to continuous, instead of grossly “bucketed” increases economic efficiency. If task automation has a large effect on the labor market, then having “mini-degrees” would help re-integrate that workforce whether we think about it as signalling or human capital.

In closing, it is my dearest hope that even well-versed readers come out of this lecture more confused about what solutions than they did before. Maybe those readers should just bite the bullet and read the Acemoglu and Autor chapter on the canonical model of labor economics instead.