One of the things post-secondary education does poorly is questioning its orthodoxies, particularly when it comes to the value of what it is the sector produces.  I’m talking in particular about graduate skills.  I mean, forget about the possibility that we could measure outcomes and relate them to specific skills and change curricula on that basis – that’s crazy talk (in universities, anyway).  I mean just the basic question: do skills matter? 

This sounds like heresy, but it’s a serious question, and the sector should be paying more attention to people who are starting to ask about it.  Let me point to the work of my colleague Dan Munro who, along with Creig Lamb, put together a nice little piece called How We Stopped Worrying and Learned to Love Robots for IRPP’s Policy Options.  The piece is a plea for increasing investment in skills in the face of automation, but the underlying point it makes is this: the skills people need is a function of the capital being deployed.  If your business leaders skimp on capital investment (and historically, this has been the case for most places and most times in Canadian history), then there’s a substantial possibility of over-skilling taking place.

Or, take another fascinating and quite important new study by Seth Benzell and Erik Brynjolfsson of MIT, bearing the substantially less-snappy title Digital Abundance and Scarce Genius: Implications for Wages, Interest Rates and Growth.  The authors begin by asking the question: if new technologies are so impressive and we are continuing to graduate ever more skilled young people, why are interest rates low, wage growth slow and investment rates flat?  What they proceed to do is a model a three-factor economy, in which production depends on capital, labour and “Genius”, with the last of these acting as a bottleneck on the other two. 

(Quick aside – the term “genius” here is potentially misleading.  They mean for it to stand to “superstar talent” of a kind which is not digitizable and is therefore inelastically supplied.  There are some other ways to think about this concept, which lead to very different interpretations and policy conclusions, but for the moment let’s stick with the authors’ preferred definition to see where it leads us). 

In their model, there are increasing returns to “genius”.  This is in line with a particular strain of economic thinking which has been around for over quite some time (for example, Robert Frank’s 1996 book The Winner-Take-All Society or the famous Sackman/Erickson/Grant article form the late 1960s documenting that the top computer programmers were worth ten times the average one).  With this constraint introduced in the system what the authors find is that raising the productivity of median- and low-skilled workers actually tends to depress wages and increase wage inequality, while raising the percentage of workers trained to “genius” level both increases average wages and decreases inequality (mainly by slashing the super-high returns of the very top earners).  What they take from this is, essentially that educational reform needs to spend a lot less time worrying about the general skill level of the masses and a lot more time on the very top couple of percent of students in order to create more “geniuses”.  The authors jump pretty quickly from this to a suggested policy response of “expand the intake of top universities”, which seems a little premature since the term “genius” is so loosely defined and even if it weren’t, the causal role of specific universities in creating said geniuses is – at best- unproven. But when you’re a prof at MIT, maybe this stuff seems natural. 

Now, the authors themselves admit that what they call “genius” might not reside in human capital in quite the way I’ve outlined here.  They also suggest some other possible bottlenecks, most of which come down to ownership/investment in “intangible capital”, which might be at least partially the product of geniuses’ work but is nevertheless conceptually quite different.  In fact, these alternative explanations collectively come pretty close to the one that Stian Westlake and Jonathan Haskel’s adopt in their frankly excellent book Capitalism Without Capital (which I reviewed back here).  But their preferred explanation is the “superstar” version. 

Either way, they key point for higher education is this: suppose bottlenecks in the economy exist in the way Benzell and Brynjolfsson say they do.  And say that by teaching differently – either by concentrating more resources on a top tier of students, or by teaching specific arrays of skills in particular ways (new combinations of STEM, Arts and business for example),  shouldn’t institutions be alive to the possibility that changing the way they teach might have far-reaching economic consequences? 

To be clear, I am not saying Benzell and Brynjolfsson are right; nor am I suggesting that it’s a great idea to go upending curriculum every time someone comes up with a new theory about wages, curricula and human capital.  I’m just suggesting that institutions might want to be alive to the possibility that their current practices might not be a magic elixir for growth and that they need to be a little more curious about the impact of their own academic practices and their long-term economic impact.  It may have a lot more impact on things like innovation and growth than another round of research funding.