HESA

Higher Education Strategy Associates

Category Archives: Data

September 16

OECD data says still no underfunding

The OECD’s annual datapalooza-tastic publication Education at a Glance was released yesterday.  The pdf is available for free here.  Let me take you through a couple of the highlights around Higher Education.

For the following comparisons, I show Canada against the rest of the G7 (minus Italy because honestly, economically, who cares?), plus Australia because it’s practically our twin, Korea because it’s cool, Sweden because someone always asks about Scandinavia and the OECD average because hey that just makes sense.  First off, let’s look at attainment rates among inhabitants 25-34.  This is a standard measure to compare how countries have performed in the recent past in terms of providing access to education.

Figure 1: Attainment Rates, 25-34 years olds, selected OECD countries

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*Data for Master’s & above not provided separately for Korea and Japan, and is included in Bachelor’s

Education-fevered Korea is light-years ahead of everyone else on this measure, with 69% of its 25-34 yr old population attaining some kind of credential, but Canada is still close to the top at 59%.  In fact we’re right at the top if you look just at short-cycle (i.e. sub-baccalaureate) PSE (see previous comments here about Canada’s world-leading strengths in College education); in terms of university attainment alone, our 34% is slightly below the OECD average of 36%.

Now let’s turn to finances.  Figure 2 shows total public and private expenditure on Tertiary educational institutions.

Figure 2: Public and Private Expenditures on Tertiary Institutions, as a Percentage of GDP, Selected OECD Countries

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Canada spends 2.5% of GDP on institutions, just below the US but ahead of pretty much everybody else, more than 50% higher than the OECD average.  For those of you who have spent the last couple of years arguing how great Germany because of free tuition is and why can’t Canadian governments spend money like Germany, the answer is clearly they can.  All they would need to do is cut spending by about 30%.

(If you’re wondering how UK claims 58% of all money in higher ed comes from government when the latest data from Universities UK shows it to be 25%, the answer I think is that this is 2013 data, when only 1/3 of the shift from a mainly state-based university funding system to mainly student-based funding system had been completed)

Turning now to the issue of how that money is split between different parts of the tertiary sector, here we see Canada’s college sector standing out again: by some distance, it receives more funding than any other comparable sector in the OECD (with 0.9% of GDP in funding).  The university sector, by contrast,  gets only 1.6% of GDP, which is closer to the OECD average of 1.4%.

Figure 3: Expenditure on Tertiary Institutions, by sector, as a Percentage of GDP, selected OECD countries

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*US data not available for short-course, 2.6% is combined total

Now this is the point where some of you will jump up and say “see, Usher?  We’re only barely above the OECD average! Canadian universities aren’t as well-funded as you usually make out.”  But hold on.  We’re talking % of GDP here.  And Canada, within the OECD is a relatively rich country.  And, recall from figure 1 that out university attainment rate is below the OECD average, which means those dollars are being spread over fewer students.  So when you look just at expenditures per student in degree-level programs, you get the following:

Figure 4: Annual Expenditures per Student in $US at PPP, Degree-level Programs only, Selected OECD Countries

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Again, Canada is very close to the top of the OECD charts here: at just over $25,000 US per student we spend over 50% more per student than the OECD average (and Germany, incidentally – just sayin’).

So, yeah, I’m going to give you my little sermon again: Canada’s is not an underfunded university system by any metric that makes the remotest bit of sense.  If we’re underfunded, everyone’s underfunded, which kind of robs the term of meaning.

That doesn’t mean cuts are easy: our system is rigid and brittle and even slowing down the rate of increase of funds causes problems.  But Perhaps if we directed even a fraction of the attention we pay to “underfunding” to the problem of our universities’ brittleness we might be on our way to a better system.

I won’t hold my breath.

September 09

Some Intriguing New UK Access Data

The UK’s Higher Education Statistics Agency (also known in these parts as “the other HESA”) put out an interesting report recently on participation in higher education in England (available here).  England is of course of great interest to access researchers everywhere because its massive tuition hike in 2012 is a major natural policy experiment: if there is no clear evidence of changes in access after a tuition hike of that magnitude then we can be more confident that tuition hikes elsewhere won’t have much of an effect either (assuming students are all given loans to cover the fees as they are in England).  I’ve written about previously about some of the evidence that has come out to date back here, here, here and here: mostly the evidence has shown little to no effect on low-income students making a direct transition to university, but some effects on older students.

The new (other) HESA report is interesting.  You may have seen the Guardian headline on this, which was that since the change in fees, the percentage of state school students who proceeded to higher education by the age of 19 fell from 66% to 62% in the years either side of the policy change (note: regular state-school students make up a little over 83% of those enrolled in A-level or equivalent courses, with the rest split about equally between selective state schools and independent schools).  On the face of it, that’s a pretty bad result for those concerned about access.

But there are three other little nuggets in the report which the Guardian chose to ignore.  The first was that if you looked simply at those who took A-levels, the drop was much smaller (from 74% to 72%).  Thus the biggest drop was from those taking what are known as “A-level equivalents” (basically, applied A-levels).  The second is that among the very poorest students – that is, those who receive free school meals, essentially all of whom are in the main state sector – enrolment rates essentially didn’t move at all.  They were 21% in 2011/12, 23% in 2012/13 and 22% in 2013/14. All of this is a long way up from 13% observed in 2005, the year before students from families with incomes below £20,000 had to start paying tuition.  Third and last, the progression rate of state school students to the most selective institutions didn’t change at all, either.

So what this means is that the decline was most concentrated not on the poor in state schools but in the middle-class, and landed more on students with “alternative” credentials.  That doesn’t make a loss of access any more acceptable, but it does put a crimp in the theory that the drop was *caused* by higher tuition fees.  If “affordability” (or perceived affordability) were the issue, why would it hit middle-income students more than lower-income students?  If affordability were the issue, why would it be differentially affecting those taking alternative credentials?  There some deeper questions to answer here.

 

August 17

Measuring Teaching Quality

The Government of Ontario, in its ongoing quest to try to reform its funding formula, continues to insist that one element of the funding formula needs to relate to the issue of “teaching quality” or “quality of the undergraduate experience”.  Figuring out how to do this is of course a genuine puzzle.

There are some of course who believe that quality can only be measured in terms of inputs (i.e. funding) and not through outputs (hi, OCUFA!)  Some like the idea of sticking with existing instruments like the National Survey on Student Engagement (NSSE); others want to measure this through “hard numbers” on post-graduate outcomes like employment rates, average salaries and the like.  Still others are banging away at certain types of solutions involving testing of graduates; HEQCO’s Essential Adult Skills Initiative seems like an interesting experiment in this respect.

But there are obvious defects with each of these approaches.  The problem with the “let’s-measure-inputs-not-outputs” approach is that it’s bollocks.  The problem with the “hard numbers” approach is that unemployment and income among graduates are largely functions of location and program offerings (a pathetic medical school in Toronto would always do better than a kick-ass Arts school in Thunder Bay).  And while the testing approach is interesting, all that testing is a bit on the clunky side, and it’s not entirely clear how well the data from such exercises would actually help institutions improve themselves.

That leaves the old survey stalwarts like NSSE and CUSC.  These, to be honest, don’t tell us much about quality or paths to improvement.  They did when they were first introduced, 15-20 years ago, but each successive survey adds less and less.  To be honest, pretty much the only reason we still use them is because nobody wants to break up the time-series.  But that’s an argument against particular surveys rather than surveys in general.  Surveys are good because they are cheap and easily replicable.  We just need to find a better survey, one that measures quality more directly.

Here’s my suggestion.  What we really need to know is how many students are being exposed to good teaching practices and at what frequency.  We know from various types of research what good teaching practices are (e.g. Chickering & Gamson’s classic Seven Principles for Good Practice).  Why not ask students about whether they see those practices in the classroom?  Why not ask students how instructional time is used in practice (e.g. presenting content vs. discussion vs. group work), or what they are asked to do outside of class?  And not just in a general way across all classes, the way NSSE does it (which ends up resembling a kind of satisfaction measurement exercise and doesn’t give Deans or departmental chairs a whole lot to work with): why not do it for every single class a student takes, and link those responses to the students’ academic record?

Think about it: at an aggregate faculty or institutional level – which is all you would need to report publicly or to government – the results of such a survey would instantly become a credible source of data on teaching quality.  But more importantly,  they would provide institutions with incredible data on what’s going on inside their own classrooms.  Are certain teaching practices associated with elevated levels of dropping out, or with an upward shift in grades?  By tying the survey to individual student records on a class-by-class basis, you could know that from such a survey.  A Dean could ask intelligent questions about why one department in her faculty seem to be less likely to involve group work or interactive discussions than others, as well as see how that plays into student completion or choice of majors.  Or one could see how teaching patterns vary by age (are blended learning classes only the preserve of younger profs?).  Or, by matching descriptions of classes to other more satisfaction-based instruments like course evaluations, it would be possible to see whether certain modes of teaching or types of assignment result in higher or lower student satisfaction results – and whether or not the relationship between practices and satisfaction hold true across different disciplines (my guess is it wouldn’t in some cases, but there’s only one way to find out!)

So there you go: a student-record-linked survey with a focus on classroom experiences on a class-by-class could conceivably get us a system which a) provides reliable data for accountability purposes on “learning experiences” and b) provides institutions with vast amount of new, appropriately granular data which can help them improve their own performance.  And it could be done much more cheaply and less intrusively than wide-scale testing.

Worth a try, surely.

June 14

Affordability of Higher Education in Canada and the United States

About a decade ago, my colleague Kim Steele and I did a comparison of the affordability of public higher education in all ten Canadian provinces and fifty US states. In general, Canadian provinces did not do well; yes, Canada has lower costs for students, but its student aid system is less generous and – this is worth remembering – Americans are wealthier than we are. And so, once you adjust costs and net costs for family purchasing power, it turned out there was a substantial affordability gap in Americans’ favour.However, things have changed a lot in the intervening decade. Tuition has increased at a faster pace in the US than in Canada, and while both countries have made improvements in student aid, the gap in median household incomes has narrowed substantially due to the severity of the recession in the US. And so my colleague Jacqueline Lambert and I thought it would be fun to re-run some of those comparisons. We’ll be publishing our full 60-jurisdiction report in the fall but it seemed like it would be fun to give you some top-level comparisons right now.

First, a brief methodological note on this comparison. We take six different measures of cost (see table below) and divide each of them by each nation’s median household income. We do this because affordability by definition is a function of a household’s ability to pay – simply comparing costs, which on their own are meaningless.

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Most of this data is easily available from various official sources (email me if you’re curious).  The exception is living costs because while Canada occasionally produces student income/expenditure surveys (we at HESA have done a few of these), Americans simply don’t.  Not on a national basis, anyways.  When you hear American student aid analysts talk about “cost of attendance”, what they’re referring to are institutional estimates of costs to live on- or off-campus which form the basis of student aid need assessment.  Sometimes these estimates make sense, sometimes they are batshit crazy (do read the New America Foundation’s recent series on this issue, available here. Regardless, they’re the only data we have.

In our 2006 paper, we used US figures for on-campus housing and in Canada we used results from an Ekos survey for living expenses.  Here’s how affordability stacked up then:

Figure 1: Canada vs. US Cost Comparisons, 2002-03 
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American tuition and living costs were both 15-20% higher than Canadian ones, but once adjusted for household income they were roughly the same – education costs in both countries came out to 11% of median household income and total costs were 23-24%. Where the Americans had a real advantage was in loans: the ubiquity of loans meant that Americans were much less credit-constrained than Canadians and had to dig into their pockets much less in the short term. Result: on the most inclusive measures of affordability, Americans looked better than we did in 2002-03.

Now on to a more recent comparison, after a recession and many policy changes on both sides of the border. We’ve refined the US living cost data by using a weighted average of on-campus and off-campus housing costs, and to make the Canadian data more comparable we’ve chosen to use CSLP living cost estimates for Canada rather than actual survey data (nationally, the two are within 5% of one another, so it’s not a big change in practice). Here’s how the data looks for 2013-14:

Figure 2: Canada vs. US Cost Comparisons, 2013-14

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What happened? How does Canada now look so much more affordable? Well, not much on the income side; in fact US median household income grew slightly faster on the American side. But tuition grew a lot faster in the US than it did in Canada. So, interestingly, did American students’ living costs; in 2003 they were 18% higher than in Canada; now they are 86% higher. To some extent, the increase in US living costs is due to our methodological change of including off-campus housing costs. That said, US cost of attendance is truly rising quickly for reasons which are not entirely clear.

Some policy measures have kicked in to offset these rises. Grant dollars per student in the US have risen by over 170% in the past decade, and loans per student have risen 64%. Both these figures far outstrip the equivalent figures in Canada. But it’s not enough to close the widening cost gap. On the most inclusive measure of affordability – out-of-pocket costs after tax expenditures – Canadian families must spend 11.9% of median household income (compared to 13.1% a decade ago) while Americans must spend 20.8%, up from just 9.7% a decade ago.

Plenty of food for thought – on both sides of the border.

June 01

Early Results from the Tennessee “Free Tuition” Experiment

You may remember a blog I wrote last year concerning something called the Tennessee Promise.  Described by some as a “free tuition” program, essentially what it did was ensure that every Tennessee student enrolled in a Tennessee community college received student aid at least equal to tuition.  In the fall, the state touted that first year, direct-from high-school enrollments in Tennessee colleges had increased by fourteen percent.  But now, however, some more complete data is available in the form of the State’s annual higher education factbook, which allows us to look a little bit more deeply at what happened.

What the numbers show is something a little bit weird.  If we look just at direct from-public-high-school -to-community-college/college of technology, the numbers are actually much better than initially advertised.  In 2014, this number was 13,527; in 2015 it was 17,550, and increase of nearly 30%.  That’s quite astonishing.

However, not all of this jump in enrollment at colleges came from “new” students.  To a considerable degree, the jump in the number of community-college bound students came from cannibalizing students who would otherwise have attended 4-year colleges, as shown in the figure below.

Figure 1: Public In-State Public High School Graduate Enrolment by System, Fall 2011-Fall 2015

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So, Community College and College of Applied Technology enrollment rose by about 4,000, but enrollments in 4-year colleges fell by 2,000, meaning effectively that half the growth came from people switching from other types of higher education. Still, net growth in enrollments at all levels was about 2,000 , or 6.8%, which is pretty impressive given that growth in the three previous years combined was only about 4%.  It sure seems like there is something positive going on here.  But what?

Well, free tuition promoters would have you believe that what’s happening here is a rush of previously-excluded poor students suddenly attending because education is more affordable.  Unfortunately, we can’t directly check students’ socio-economic backgrounds, so we can’t know for sure who’s responding to these lower net prices.  However, because the factbook shows transition rate by county, we can look at different enrollment responses by county median household income. Figure 2 plots the percentage increase in enrollments in each of Tennessee’s 95 counties against their median household incomes

Figure 2: Percentage increase in college-going rate, Tennessee 2015 over 2014 by County, vs County Median Household Income

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Pretty clearly, there’s no relationship here, which at face value suggests that participation rates of students from poor counties did not increase any faster than the rates of students from richer counties.  But that’s not quite right.  Remember we are looking at percentage increases, and poorer counties tend to have lower participation rates.  Therefore, in order for the percentage increase to be the same in richer and poorer counties, the percentage point increase actually has to be larger in richer counties.  (think about:  a 10% rise for a county with 30% participation rates is 3 percentage point; for a county with a 60% part rate, a 10% rise requires a jump of 6 percentage points).

So, a pure, unsophisticated simple-stupid pre-post analysis of the Tennessee data, suggests that the Tennessee Promise appears to have i) caused a 30% increase in 2-year college-going rates among high school graduates, half of which was diverted from other types of higher education and ii) caused a 6.8% overall increase in transitions to all forms of college, but that this increase did not primarily take place due to increases of the college-going rate of students from poorer counties.

Make no mistake, this is still a very good outcome for a program that only costs $14 million per cohort per academic year; it works out to $7,000 per new student added to the post-secondary system, which is pretty cheap.  Nevertheless, it’s worth noting that those benefits don’t seem to necessarily accrue to youth from poorer backgrounds.

 

May 17

How Rich are China’s Universities?

Last week, Mike Gow at the Daxue blog linked to some interesting data recently published by the Chinese government with respect to the budgets of the country’s top universities.  It only covers those institutions which report to the Ministry of Education (and therefore misses some important institutions like the University of Science and Technology of China (which reports to the Chinese Academy of Sciences) and the Harbin Institute of Technology (which reports to the Ministry of Industry and Information Technology).  It suggests that, at the very top of the Chinese system, there are some jaw-dropping amounts of money being spent.

Let’s focus just on the C9 schools (the Chinese equivalent of the U-15/Russell Group/AAU/G-8, or at least on the seven for which data was provided).  Here is the data for 2015-16:

Table 1: Income & Enrollments of Top Chinese Universities

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*From Wikipedia.  I know, I know, but it’s all I had.

**Using the Big Mac Index to covert from RMB to USD at rate of 3.57 to 1

Now, the jaw-droppingness of these figures depends a lot on whether you think it makes more sense to compare institutional buying power based on market exchange rates or based on purchasing power parity (PPP).  For universities, which pay salaries in local currency but compete for staff and pay for journals and scientific journals in an international market, there are some good arguments either way.  It should also be noted that it’s not 100% clear what is and is not in these figures.  Does Tsinghua’s figure include the holding companies that own shares in all of Tsinghua’s spin-off businesses?  Unclear.  My guess would be that it includes income from those businesses but not the businesses themselves – but it’s hard to know for sure.

Comparing these numbers to those of top American universities is somewhat fraught, because of the way American universities account for income from their teaching hospitals.  Thus Duke reports about twice as much income per student as Harvard because one includes medical billings and the other does not; if you correct for this, the two institutions are about the same.  Correcting as best I can for teaching-hospital income, and excluding Rockefeller University because it doesn’t really have any students and excluding Caltech (which has about $1 million/student in revenue) because it’s such an outliers and would break my nice graph, the top five in the US and the top seven in China looks like this:

Figure 1: Total Income, Chinese C9 Universities vs. Top 5 US universities, in USD at PPP

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The basic point here is that Peking and Tsinghua are – on a PPP basis at least, and excluding medical income on the US side without being sure that it is excluded on the Chinese side – at least roughly in the same league as Harvard, though not quite in the same league as MIT, Stanford and Johns Hopkins.  The rest of the Chinese universities trail a bit: the poorest of these, Xi’an Jiao Tong, would be at about the level of Berkeley if you use a PPP comparison, and Florida State if you use the exchange rate.

Now let’s move to the UK, where the top five universities in terms of dollars per student are Cambridge, Imperial College, University College London, Oxford and Edinburgh.    The comparison changes quite a bit depending on whether or not one uses PPP or exchange rates.  On a PPP basis, Tsinghua and Peking would lead all UK universities; on an exchange-rate basis, they would be 5th and 6th – that is, behind Cambridge, UCL, ICL and Oxford but still ahead of Edinburgh.  Either way it suggests that, financially at least, the top Chinese universities are on a similar playing field as the top UK ones.

Figure 2: Total Income, Chinese C9 Universities vs. Top 5 UK universities, in USD at Exchange and PPP

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Next, let’s go to Canada.  Here are the top five Canadian schools compared with the top seven Chinese ones.  On a PPP basis, UBC is the only Canadian university which would crack the top seven in China.  But on an exchange-rate basis, all of our top five would come ahead of Nanjing and close to Fudan.

Figure 3: Total Income, Chinese C9 Universities vs. Top 5 Canadian universities, in USD at Exchange and PPP

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Finally, let’s take a look at Australia, where universities are frankly much less well-funded than elsewhere.  On a PPP basis, even the weakest of the C9 – Xi’an Jiao Tong – would come ahead of the best-funded Australian institutions (Australian National University).  On an exchange-rate basis, ANU would rise ahead of Xi’an Jiao Tong and Nanjing, but would still lag behind the other Chinese institutions, by a factor of 2:1 in the case of Peking and Tsunghua.

Figure 4: Total Income, Chinese C9 Universities vs. Top 5 Australian universities, in USD at Exchange & PPP

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The bottom-line is that while most Chinese universities are still a ways away from the top international standards in terms of income, expenditure, research base, etc., at the very top it seems that the C9 institutions are now very much in the global elite as far as funding is concerned.  They are not yet there as far as research output is concerned – only Peking and Tsinghua make the Times Higher Top 100 and none make the Shanghai Academic Rankings of World Universities – but that’s only a matter of time.  Rankings (and prestige) are a result of cumulative effort and financing.  Another decade with these kinds of numbers will make a very big difference indeed.

May 06

What Ottawa Spends

The Parliamentary Budget Officer did everyone a solid yesterday by publishing a really helpful compilation of federal government expenditures on higher education. According to the publication, the Government of Canada in 2013-14 spent $12.3 billion on post-secondary education (not including money for apprenticeships, training programs or labour market agreements; that includes $5.1 billion for “human capital measures”, which is mostly Canada Student Loans and Tax Expenditures of various kinds, $3.5 billion for research, three-quarters of which is from the granting councils and the remainder through various departmental programs, and $3.7 billion through the Canada Social Transfer, which is a theoretically earmarked.

The graph below shows the evolution in expenditures in nominal dollar. While the growth is therefore somewhat exaggerated because of inflation, it’s interesting to note that overall, expenditures increased by a third, from $9 billion to $12 billion, between 2005-6 and 2013-14. This would have been a very good talking point for the Tories in the last election; it’s a bit of a mystery why they didn’t use it.

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(In case you’re wondering what the bump in human capital formation spending is in 2009-10 and 2010-11, I’m pretty sure it’s the cost of the transitional measures relating to the end of the Millennium Scholarship Foundation).

The report has a nice little projection about what future expenditures in post-secondary are going to be. The PBO seems to think there’s going to be a lot of cost growth because of an upswing in student numbers. I think that’s somewhat unlikely given the demographics; on the other hand, I think there will be cost growth as an increasing number of students figure out that they are eligible for free money under the new student aid arrangements. So it’s probably a wash. In any event, here’s what’s PBO thinks the future looks like:

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The one bit of the report I find a little off is the section on who is using tax credits. The problem with analyzing the use of tax credits is that it combines parental use of tax credits with student use of tax credits. This is a problem because students are concentrated in the bottom income deciles. So if the child of a millionaire uses tax credits, it’s counted as being used by Canadians from the bottom quintile of income, which let’s be honest is a bit misleading. But still, overall, this makes a powerful point: tax expenditures are skewed to the wealthier end of society and it’s an awfully good thing that they are being phased out in order to fund poorer students.

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(Remember though: the reason tax benefits are skewed to upper quintiles isn’t because they are worth more to those individuals. These are credits, not deductions. No, the reason they are skewed is because the children of parents from upper-income quartiles are that much more likely to attend higher education and especially universities. In other words, *all* spending on higher education gets distributed this way. Which is a prime reason why education should not be free – this is the way the benefits of such a move would be skewed).

Anyways, there’s nothing special or complicated about the PBO analysis. It’s just really nice to have all this stuff well documented and presented in a straightforward manner in one place. Kudos.

(Note: I will be taking a break from blogging next week. Back on May 16)

March 21

An Orgy of Bad Policy in Saskatchewan

Two weeks from today, voters in Saskatchewan go to the polls.  You may be forgiven for not having noticed this one coming since it has barely registered in the national press.  And that’s not just because of the usual central Canadian obliviousness, or because it’s a fly-over province; it’s also because this is one of the least competitive match-ups since…. well, since the last time Brad Wall won re-election.  CBC’s poll currently gives the Saskatchewan Party a 25 point lead over the New Democrats.

Normally, when provinces go to the polls I do a detailed look at their post-secondary platforms.  It hardly seems worth it here.  Neither the Liberals nor the Greens have a chance of taking a seat so frankly, who cares?  The NDP has released a platform full of promises large and small (my particular favourite: on page 34, they pledge to put more refrigerators in public liquor stores in order to provide more cold beer options), but did not even bother to put out a costing document, which suggests not even they think they have a hope in hell of winning on April 4.  For their part, the Saskatchewan Party has put out a manifesto, which basically says “elect us and the good times will continue to roll”: no strong vision of the future, just a recounting of past glories and four small promises that add up to a total of $110M over four years.  The only manifesto I can think of that comes close to this in sheer complacency is the Liberal Red Book from the 2000 federal election.  Which, given that oil is still around $40/barrel, is quite something.

But hey, when you’re writing a daily blog, sometimes you need an easy target. So here goes:

The Saskatchewan NDP platform on PSE is pretty awful.  They want to “improve funding for post-secondary institutions” (By how much?  Who knows?  There’s no costing document).  They want to offer everyone a $1,000 rebate on tuition, which everyone knows is regressive.  They also want to convert all provincial loans, but this actually isn’t much money since Saskatchewan aid is mostly grant.  But, get this: they also want to get rid of interest on outstanding provincial loans, which is just a whole mountain of dumb since it has no effect whatever on access, and rewards people for choices they made years ago.  Offering to help borrowers in distress is sensible; a blanket interest subsidy for people who have already finished their studies implies the manifesto-writer has suffered some kind of head trauma.

Still, in some ways, the NDP platform looks good in comparison to what the Saskatchewan Party is offering.  As some of you probably know, for the past decade or so the Government of Saskatchewan has offered a generous set of tax credits to graduates who stay within the province.  Essentially, if you are a university graduate you can reduce your payable provincial taxes by $2,000/year for the first four years that you live in the province, and $4,000 per year for the next three (if you don’t earn enough in a given year to use all of that, you can carry forward to a future year; amounts are reduced slightly for college graduates).  Add to this the usual panoply of federal and provincial tax credits, and you realize that Saskatchewan graduates who stay in the province are receiving more in tax benefits than they ever pay in tuition.

If that formulation sounds familiar, it should – it’s exactly the way Ontario finally figured out it could market itself as having “free tuition” to low-income students without spending a penny.  But the Saskatchewan Party, instead of following Ontario and transferring money to a more front-ended set of incentives, has decided to double-down on the back-end.  Their big post-secondary-related pledge is to allow graduates to take up to $10,000 unused rebate money and use it as a down payment on the purchase of a house.

Yes, I am serious.  Check it out.  Page 8.

I mean, in a way, it’s genius; a twofer tax credit, combining the middle-class’ two fondest wishes: that government subsidize both their education and their house purchases.  And if you assume the basic premise that graduates need financial inducements to stay in the province, why not make that financial inducement in the form of a housing subsidy, which physically ties graduates to the province?

But in another, deeper, way it’s a travesty.  If the Saskatchewan Party has done such a fantastic job managing the economy, why does the province still need this financial inducement to get people to stay in the province?  If the argument is that “young people need a break”, why give so much to those likeliest to succeed (i.e. university grads) and nothing to those least likely (those who never make it to PSE)?

So, yeah, Saskatchewan.  Yet another province with a bi-partisan consensus that all the specified PSE goodies should go to students and graduates rather than, you know, the actual institutions who provide the education.  Raspberries all around.

March 15

ECE Contributions vs. PSE Contributions

Morning all.  Today, HESA is releasing a paper called “What We Ask of Parents: Unequal Expectations for Parental Contributions to Early-Childhood and Post-Secondary Education in Canada”, by Jacqueline Lambert, Jonathan Williams, and me.  The gist of it is: “Holy cow, we ask parents to contribute a lot more to ECE than PSE – why is that?” You can click here to read the whole report, or you can see the short version as an op-ed in today’s Globe and Mail.  What I want to show you in today’s blog is the wonky background stuff, because we’ve done a couple of things in this paper that no one has done before.

The paper is really built around the key insight that you can create “expected contribution curves” for both early-childhood education (ECE) and post-secondary education (PSE). In PSE, you can do this simply by looking at the parental contribution tables embedded in student financial aid programs, and then add in the value of tax credits.  You’ve seen me do stuff like this before, but here’s what it looks like for PSE:

Figure 1: Net-After Tax Expected Parental Contributions for Parents of Children in PSE, Canada 2015

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You can see pretty clearly what’s going on here.  Below about $15,000 the expected contribution is $0 – no contribution required, but income levels are too low for any taxes to kick in, so no tax credits, either.   As income starts to rise, net contribution falls because of the value of tax credits.  But then, expected contributions from the student aid system kick in: at about $45,000 in the case of Quebec, and around $60,000 elsewhere (as a result, despite low tuition, Quebec is the place where parents are expected to pay the most, if their income is between $45,000 and $70,000).  The exception to this is Alberta, where no parental contribution is required at all.  I’ll come back to that.

Eventually, this graph shows that contributions flatten out at a level equal to tuition and fees, which is the maximum possible contribution in this exercise.  Now, I’m pretty sure this will tick a lot of people off because at least some parents also support students for their living expenses, and we’re excluding them, and hence making contributions look smaller than they really are.  This is true – and we do it in part because actual living expenses are quite variable and difficult to model.  But that doesn’t mean we’re exaggerating the difference between expected contributions to ECE and PSE – after all, parents of children in ECE are paying for their kids’ living expenses too.  So we just call all of that a wash and focus on what parents are paying in fees to daycares and universities.

Anyways, for early childhood education you can draw very similar curves to the ones in Figure 1 by taking the average child care costs and applying the subsidies available to low income parents according to the provincial formula.  No one seems to have ever done this before in Canada, but it can be done.  You have to do it three times, because outside Quebec, prices tend to differ by the age of the child (infants are more expensive than toddlers, who are more expensive than pre-schoolers), but it is eminently doable.  Here’s what the graph looks like for infants, after tax deductions are applied:

Figure 2: Net-After Tax Expected Parental Contributions for Parents of Toddlers in ECE, Canada, 2015

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As you can see, the story for ECE contribution is quite a different from the one for PSE.  For infants, the minimum contribution is almost never zero.  In most provinces, parents hit maximum contributions at between $45,000 and $70,000 in family income – a level where parents of PSE students are usually not required to contribute a thing.  To say we as a country are inconsistent in the way we pay for these two types of education is putting it mildly.

Anyways, in the paper itself (well, in the appendices anyway) we generate province-by-province comparisons like this one below, for Alberta:

Figure 3: Effective After-Tax Required Contributions for Parents of Dependent PSE Students and Children in Child-Care, by Family Income, Alberta, 2015

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Yeah, this graph is pretty crazy.  This is what happens when you say there shouldn’t be a parental contribution to post-secondary education, which Alberta did about five years ago.  At $75,000 in family income, the gap between required parental contributions for an infant and for a university student is a little over $14,000.  Madness.

And finally, by multiplying provincial values by each province’s share of population, we can generate some national averages.  To wit:

Figure 4: Average Effective After-Tax Required Contributions for Parents of Dependent PSE Students and Infants in ECE, by Family Income, Canada, 2015

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Fun, huh?

Tomorrow: the policy implications.

February 17

Some Curious Student Loan Numbers

Every once in awhile, it’s good to go searching through statistical abstracts just to see if the patterns you take for granted can still be taken for granted.  So I recently went hunting through some CSLP annual reports and statistical abstracts to see what I could find.  And I’m glad I did, because there are some really surprising numbers in the data.

So here’s the really big take-away: the number of students borrowing from the Canada Student Loan Program rose from 365,363 in 2008-09, to 472,167 in 2012-13.  In just four years, that’s an increase of 29%.  Which is kind of staggering.  It’s therefore important to ask the question: what the heck is going on?  Where are all these new borrowers coming from?

Well, for one thing, we know it isn’t being led by a new wave of students in private, for-profit institutions.  In fact, the increase occurred across all types of institutions, with a slightly more pronounced growth among students in community colleges.

Figure 1: Growth in Number of Student Borrowers by Type of Institution, 2008-09 to 2012-13

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It’s a different story when we look at borrowing growth  by province.  Here, we see a more straightforward – and somewhat puzzling – story: borrower numbers are up fairly substantially everywhere west of the Ottawa river; however, numbers are even, or down slightly everywhere in the Atlantic (note: because we are looking only at CSLP borrowing, there is no data for Quebec, which has opted out of the program).

Figure 2: Growth in Number of Student Borrowers by Province, 2008-09 to 2012-13

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One thing that Figure 2 obscures is the relative size of the provinces, and thus the portions of growth in borrower numbers.  Ontario, where growth in borrower numbers has been 38%, actually accounts for over three-quarters (77%) of all growth in borrowing within the CSLP zone; in total, Ontario now accounts for nearly two-thirds (64%) of the CSLP loan portfolio.

You can’t explain Figure 2 in terms of economic fundamentals: neither the recession’s effects nor education costs were that different in the Atlantic.  To a considerable degree, what Figure 2 is really showing is population change: youth populations in the Atlantic are shrinking, and that is primarily why their borrower numbers are going down (Newfoundland is falling even further because of real declines in costs and – probably – because family incomes rose quickly in this period thanks to the oil boom).

To get a better look at changes in the borrower population by province, we need to look at changes in the percentage of full-time students who are borrowing.  Now, it’s difficult to do this because CSLP itself doesn’t calculate this figure, and doesn’t quite break down figures enough to do it accurately.  So below in Figure 3 what we show is the number of total borrowers (including at private vocational colleges), divided by the number of students enrolled full-time in public universities and colleges.  This will slightly overstate the percentage of students borrowing (borrowers at private colleges make up about 10% of the borrowing population, so mentally adjust the numbers downward if you would); also, the denominator is total students enrolled in the province, not originating in the province, so Nova Scotia’s figure in particular is an undercount because of all the out-of-province students there.  With those caveats in mind, here are the percentages of students borrowing across the country:

Figure 3: Percentage of Full-Time Students with Loans, by Province, 2008-09 and 2012-13

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The percentage of students borrowing grew in every province except Newfoundland, Saskatchewan, and New Brunswick. But the real story here is Ontario, where the percentage of students borrowing jumped by nine percentage points (from 44% to 53%), which led to a national rise of seven percentage points (42% to 49%). It’s not entirely clear why there was such a jump in Ontario.  The recession there was not that much more severe than elsewhere, and student costs, though high, were not rising that much more quickly than elsewhere.  Part of the answer may be that in the last couple of years the new Ontario Tuition Grant has been in effect, which enticed higher-income students into the student aid system with its outrageous $160,000 family-income cut-off line.  But that can’t be the entire story, as growth in numbers was actually fairly steady from year-to-year.

What might be going on? My guess is two things.  First, student numbers are expanding in most provinces.  Almost by necessity, if expansion is happening, it is going to happen disproportionately among those who we traditionally call “underserved” (that is, the poor, students with dependents, etc.), who by definition are more likely to be eligible for student aid.  This is to say, what we are seeing here is not evidence of a problem, but rather evidence of student aid working exactly as it should, to expand access.

The second factor is what I call delayed recognition.  Back in the 2000s, student aid eligibility for dependent students was expanded enormously.  Essentially, we went from a situation in 2003 where most families saw eligibility for student aid end at around the $85,000-$90,000 mark in family income, to one in 2006 and thereafter where the cutoff rose to about $160,000 (the number varies a bit by province and family size, but that’s roughly the scale of the change).  However, much to everyone’s surprise, take-up rates barely rose, presumably because CSLP didn’t go out of its way to advertise the changes much.  What may be happening is that families across the country – but especially in Ontario – may finally be cluing in to how much assistance they are entitled to under the post-2006 rules, and acting accordingly.  In other words, this could just be an improvement in take-up rates rather than a deterioration in family and student finances.

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