HESA

Higher Education Strategy Associates

Tag Archives: Growth

February 07

Innovation and Skills Redux

So, yesterday Federal Finance Minister Bill Morneau’s Advisory Council on Economic Growth released five (!) papers on innovation, skills, and a bunch of other things.  I’m sure there’s a lot of ink on these in today’s papers, mainly around proposals to raise the retirement age (which we actually did two years ago, except the Trudeau government reversed it, but now evidence-based policy FTW, as the kids say).  I’ll restrict myself to some brief thoughts about two areas in particular: innovation and skills

On Innovation:   I must admit I got a bit of a thrill reading page 9 of the report, in which the Council body-slams the innovation Minister’s ideas about geographically-based innovation “clusters”.  They’re polite about it, “applauding” the Minister for coming up with such a great idea, but then go on to say that they’ve actually read the literature and know what works, and it ain’t clusters.  Hilarious.

What do they propose instead?  Well, it’s something called “innovation marketplaces”.  What are those you ask?  Well, to quote the report they’re “centers of technology and industry activity that are developed and driven by the private sector. An innovation marketplace brings together researchers and entrepreneurs with public and private customers around a common business challenge. These marketplaces match innovation demand from corporations and governments with innovation supply from researchers and entrepreneurs. This matchmaking strengthens supply-chain relationships and the flow of information, thereby fueling further innovation.”

If you think that sounds super hand-wavy, you are not alone.  In practice, there’s some overlap with the ideas Minister Bains has been peddling for months (Artificial Intelligence!  Cleantech!) but these idea are more focussed on industry and less geographically-based, both of which are Good Things.  However, it still equates innovation with new product development, specifically in gee-whizzy tech areas, which is a Bad Thing.  (Non-gee-whizzy sectors get their due in a separate paper on growth; a Good Thing to the extent that at least the Council conceptually understands the difference between Growth Policy and Innovation Policy.  I’m yet to be convinced the Minister has such an understanding.)  So there’s some overlap in ideas but considerable differences in the kinds of programs that are supposed to get us there.

But the budget’s only a couple of weeks away.  How does this circle get squared?   Messily, I suspect.  But we’ll have to wait and see.

On Skills:  According to the report, everything is going to be solved by a new agency going by the godawful name “Futureskills Lab”.  As near as I can tell, this agency is going to be a lot like the Canadian Council on Learning was, only: i) more focused on skills than education (by “skills” they seem to mean tech skills – eight of the ten examples of skills used in the report are tech), ii) more focused on (industry-led) experimentation and dissemination and “what works” and iii) it’s also going to be handed the prize of finally sorting out all that Labour Market Information stuff that Don Drummond has been yelling about for years and no one trusts Statscan to get right.  (I kid….Don Drummond would never raise his voice).

OK, so…there’s nothing wrong with funding lots of experimentation on skills and training.  In fact, it’s a great idea.  Fantastic.  The over-focus on tech skills is <headdesk> inducing, but my guess is that reality will kick in after a year or two and we’ll get a broader and more sensible set of skills priorities.  And there’s nothing wrong with better Labour Market Information, though I’m not particularly convinced that adopting all of Drummond’s recommendations will bring us to some kind of Labour Market Nirvana. (Short version, which maybe I should elaborate in a future blog: what Drummond mostly wants is backward-looking, which is great for economic analysis, not especially helpful for job-seekers or students looking to specialize).

But why do we need a new institution to do all this?  ESDC could fund experiments and analyses thereof.  Statscan could do the LMI stuff.  What advantage does a new institution necessarily have?  I’m not saying there are no advantages: the Millennium Scholarship Foundation is an example of an arguably unnecessary institution which nonetheless was responsible for some pretty interesting policy and delivery innovations.  But the advantages are uncertain and not well-argued in the report.

And there’s another issue.  The Council is keen that FutureSkills Lab be collaborative.  Super collaborative.  Especially with the provinces.  They really like the whole Canada Institute for Health Information (CIHI) model.  Well, the thing is, the federal government did try something similar a decade ago.  It was called the Canadian Council on Learning (CCL) – remember that? It was well-intentioned, but a political disaster because the feds set it up before actually talking to the provinces, leading the latter to essentially boycott it.  More to the point, CIHI works because it is responsible (in part) to the provinces, not just the feds.  If the Council recognizes the importance of this point, it is not evident in the report, which dances back and forth between saying it should “collaborate with” the Forum of Labour Market Ministers (i.e. with provincial governments) and saying it should be “accountable” to them.

I’ll stick my neck out on this one: “accountable to” will fly, “collaborate with” will not.  If the federal government is going to take up this idea from the council, it needs to make clear to the provinces within the next few days if not hours that this is going to be 100% CIHI clone, accountable to provinces and feds and not a federal creature collaborating with provinces.  If that doesn’t happen, regardless of the merits of more experimentation and better LMI data, this idea is going to be an expensive repeat of the CCL failure.  Federalism still matters.

January 29

Universities and Economic Growth

If you read the OECD/World Bank playbook on higher education, it’s all very simple.  If you raise investments into higher education and research, growth will follow.

At the big-picture national level, this is probably true.  But it’s maddeningly inspecific.  What is the actual mechanism by which higher spending on a set of institutions translates into growth?  Is it the number of trained graduates produced?  Is it the quality or type of education they receive?  Does concentrating research in certain areas mean greater growth?  What about the balance between “pure” and “applied” research (insofar as those are useful distinctions)? What about technology transfer strategies?

Most importantly for a country like Canada: what about geography?  Is a strategy of widely distributing funds better than a strategy of concentration for spurring economic growth?  Should urban universities – nearer the centres of economic production – get more than universities in smaller conurbations?

Anyone telling you they have the definitive answer to these questions is lying.  Fact is, the literature on most of these topics is embarrassingly thin and provides little to no guidance to governments.  And the literature as it pertains to individual universities is even thinner.  Say you want an institution to “do better” at helping deliver regional economic growth: what do you ask it to do, exactly?  Here, the literature mainly consists of anecdotes of success parading as universally-applicable rules for university conduct (this European Union document is an example).  Which of course is tosh.

One solution you often see to the problem of decreased regional economic growth in smaller cities is for PSE institutions to “work more with industry”.  But if your local industry is in decline, there are limits to this strategy.  You can educate more people in a given field in order to lower the price of skilled labour.  You can get profs to work on upstream blue-sky research that will revolutionize the field, but the spillovers are enormous and the likelihood they will be captured by local business is small.  You can get your profs to work on downstream innovation with local business, but that’s not foolproof. Many companies won’t have the receptor capacity to work with you, either because they are too small or because they are too big and rely on a centralized R&D system, which more often than not is located outside the country (usually the US).

From a PSE point-of-view there’s two ways you can go from here.  There’s the route of “give us more money and we’ll give the local workforce a broader set of skills”.  But the fact that a local population has high levels of relatively generic skills does not necessarily make a region a particularly attractive place for investment.  I’m not an economic geographer, but it seems to me that one of the driving forces of the modern era is that the most profitable companies and industries are those that effectively capitalize on agglomerations of very specific types of talent.  And by and large, to get agglomerations of very specific types of talent you tend to need a large population to begin with, which is why big cities keep getting bigger.

The other option is a “place your bets” approach.  For emerging industries to find the right kinds of skills in a particular region, you have to place bets.  You have to say: “we’re going to invest in training and facilities to produce workers for X, Y, and Z industries, which at the moment do not exist in our region, and indeed may never do so.  Cape Breton University’s emphasis on renewable energy is a good example of this strategy.  It’s a bet: if they get good at this and produce enough graduates, maybe within a few years there will be enough of a talent agglomeration that business will go there and invest.

Maybe.  And maybe not.  Problem is, public universities and their government paymasters get nervous about “maybes”.  Higher education is a risk-averse industry.

Tomorrow, we’ll look at a case study in this: Southwestern Ontario.

September 09

Financing Canadian Universities: A Curious Story (Part 1)

if you pay attention to discussions of higher education funding, one of the memes that inevitably pops up revolves around the notion that higher education has been under some brutal, neo-liberal assault since… well, I’m not sure, but probably since 1995 at least, and everything is being defunded, laid on the backs of students, it’s the end of civilization, dark ages ahead, etc., etc.

Problem is, this yarn is utterly at odds with the data, which tells a very different story.  Starting today, I’d like to tell you that story.

Are you sitting comfortably?  Then I’ll begin.  Let’s jump right to Figure 1.

Figure 1 – Total University Income By Source, in Billions, 1992-2010

 

 

 

 

 

 

 

 

 

 

 

 

Now, the first time I saw Figure 1, I assumed it was in nominal dollars.  But it isn’t.  Those are real, constant dollars, folks.  And in real terms, university income more than doubled between 1998 and 2010.

Sure, the 1990s sucked – government expenditures fell in real terms, and the system only kept itself afloat through greater reliance on private income (mostly tuition).  But the 2000s were years of simply eye-popping growth.  Basically, every year, it was 6-7% growth after inflation.  If anyone in academia is puzzled as to why higher education is seen as spoiled by much of the rest of the public sector (and indeed the public-at-large), this graph is the answer.

One interesting thing about the 2000s is how the different revenue streams all went up at about the same pace.  That is, tuition income and income from private sources continued to rise after 1998, but they didn’t become a larger portion of the pie, because revenue from government was rising so quickly.  At the start and end of that period, the revenue split remained 54% government, 21% tuition, and 25% other revenue.  So much for “governments downloading costs to students”.  Student fees certainly went up, but government spending went up proportionately, too.

Ah, say the skeptics, but you’re only accounting for inflation.  What about that huge influx of students?  Surely, if we showed this data on a per-student basis, it would show the ever-deprived nature of our universities.  Well, no, as a matter of fact.  FTE numbers in universities did indeed rise, but only by about 50%.  So on a per-student basis the graph looks like this:

Figure 2 – Per-FTE University Income by Source, 1992-2000

 

 

 

 

 

 

 

 

 

 

 

 

Between 1997 and 2006, per-student funding rose by roughly 40%, from about $23,000 to $33,000 (again, this is in constant dollars).  For the rest of the decade, per student dollars remained reasonably consistent, give or take a huge hit on endowment revenue in ’08.  If I could extend that graph out to 2013 (which I can’t), you’d probably see a small drop in government funding offset by an increase in (mostly international) tuition dollars.

So why does everyone think universities are getting poorer when in fact they’re getting richer?  Tune in tomorrow.