HESA

Higher Education Strategy Associates

Category Archives: Data

October 10

More PIAAC: The Canadian Story

Yesterday I offered my thoughts on some of the highlights from the international portion of the PIAAC release; today I want to focus on the Canadian results. 

Figure 1 shows the overall literacy scores, by province.

Figure 1: Literacy Scores by Province, PIAAC

 

 

 

 

 

 

 

 

 

 

 

 

At first glance, PIAAC doesn’t seem to be telling us anything we didn’t already know from years of PISA & TIMSS surveys.  Alberta comes first, the Atlantic is mostly a mess, and everybody else is kind of in-between.  But look a little more closely at the data, and a different story emerges.  Remember that PISA and TIMSS are single-cohort snapshots of kids with identical amounts of education; PIAAC is a mashup of multiple cohorts, each with quite different educational patterns.  Because they are measuring such different things, similarities may simply be coincidental.

So let’s see what happens when we try to standardize for age and education.  Figure 2 shows PIAAC literacy scores, by province, for the 25-34 age cohort who possess a university degree:

Figure 2: Literacy Scores by Province, University Graduates Aged 25-34

 

 

 

 

 

 

 

 

 

 

 

 

At face value, Figure 2 is pretty exciting if you’re from the Atlantic.  I mean, hey, OECD says one year of schooling is equal to seven points on the PIAAC scale – which implies that Islanders with university degrees, on average, have literacy rates equal to about three years of extra education over the left-coasters.  But because of sample sizes, these numbers come with pretty big confidence intervals: PEI and Nova Scotia are outside the margin of error for BC and Saskatchewan, but not for anyone else.  The other six are all essentially equal.

Now take a look at the result for college graduates, aged 25-34:

Figure 3: Literacy Scores by Province, College Graduates Aged 25-34

 

 

 

 

 

 

 

 

 

 

 

 

There’s a similar pattern here, but the gaps at either end are bigger, and confidence intervals don’t help quite as much.  BC through Manitoba are all within each others’ margin of error.  Put PEI and Alberta are genuinely ahead of everyone else, except BC; Newfoundland and Saskatchewan come out looking bad no matter what.

Here’s what you should take from this:

1)   Alberta’s overall high PIAAC scores are due less to its own education system, and more to its ability to attract talent from elsewhere.  That’s the only way you can reconcile their own scores with what we know about their PSE access rates, and the performance shown in the second and third figures above.

2)   Saskatchewan needs to ask some hard questions.  Really hard.

3)   PEI is… odd.  This doesn’t look like a fluke.  But then, if they’ve got all these great skills, why is their economy such a basket case?

4)   Newfoundland is Newfoundland.  Decades of relative poverty will take its toll.

5)   Don’t get fooled by small differences – the other six provinces are essentially indistinguishable from one another.

More tomorrow.

October 02

A New Study on Postdocs

There’s an interesting study on postdocs out today, from the Canadian Association of Postdoctoral Scholars (CAPS) and MITACS.  The report provides a wealth of data on postdocs’ demographics, financial status, likes, dislikes, etc.  It’s all thoroughly interesting and well worth a read, but I’m going to restrict my comments to just two of the most interesting results.

The first has to do, specifically, with postdocs’ legal status.  In Quebec, they are considered students. Outside Quebec, it depends: if their funding comes from internal university funds, they are usually considered employees; but, if their funding is external, they are most often just “fellowship holders” – an indistinct category which could mean a wide variety of things in terms of access to campus services (are they students?  Employees?  Both?  Neither?).  Just taxonomically, the whole situation’s a bit of a nightmare, and one can certainly see the need for greater clarity and consistently if we ever want to make policy on postdocs above the institutional level.

The second – somewhat jaw-dropping – point of interest is the table on page 27, which examines postdocs’ training.

Level of Training Received or Available, in % (The 2013 Canadian Postdoc Survey, Table 3, pg. 27)

 

 

 

 

 

 

 

 

 

 

 

 

 

As the authors note, being trainees is what makes postdocs a distinct group – it’s basically the only thing that distinguishes them from research associates.  So what should we infer from the fact that only 18% of postdocs report receiving any formal training for career development, 15% for research ethics, and 11% on either presentation skills or grant/proposal writing?  If there’s a smoking gun on the charge that Canadian universities view postdocs as cheap academic labour, rather than as true academics-in-waiting, this table is it.

All of this information is, of course, important; however, this study’s value goes beyond its presentation of new data.  One of its most important lessons comes from the fact that a couple of organizations just decided to get together and collect data on their own.  Too often in this country, we turn our noses up at anything other than the highest-quality data, but since no one wants to pay for quality (how Canadian is that?), we just wring our hands hoping StatsCan will eventually sort it out it for us.

But to hell with that.  StatsCan’s broke, and even when it had money it couldn’t get its most important product (PSIS) to work properly.  It’s time the sector got serious about collecting, packaging, and – most importantly – publishing its own data, even if it’s not StatsCan quality.  This survey’s sample selection, for instance, is a bit on the dodgy side – but who cares?  Some data is better than none.  And too often, “none” is what we have.

CAPS/MITACS have done everyone a solid by spending their own time and money to improve our knowledge base about some key contributors to the country’s research effort.  They deserve both to be commended and widely imitated.

October 01

How the Zero-Tuition Crew Could Learn to Love Tax Credits

So, let’s say you’re among those who clings to the idea that tuition isn’t just a massive give-away to upper-income families.  Let’s say you really, really believe that tuition – sticker-price tuition, none of these “net price calculations”, thank you very much – affects access.  How would you go about gathering evidence for your point of view?

Ideally, of course, there would be some data showing that, as fees went up, participation went down.  Problem is, the data doesn’t show this.  To wit:

Tuition + Ancillary Fees (in $2013) and Participation Rates, Canada, 1993-94 to 2012-13

 

 

 

 

 

 

 

 

 

 

 

 

Well, OK then.  Maybe if you’re desperate to prove a point, you might relax your scruples about counting grants against tuition.  Maybe it’s all the extra student aid pouring into the system which has made a difference?

Tuition + Ancillary Fees (in $2013), Net Fees (i.e. Minus Grants) and Participation Rates, Canada, 1993-94 to 2012-13

 

 

 

 

 

 

 

 

 

 

 

 

Well, no.  Damn!  Now what?

Well, here’s one possibility.  Check this out:

Real Tuition + Ancillary Fees, Minus Grants and Tax Credits, as a Percentage of Average After-Tax Family Income

 

 

 

 

 

 

 

 

 

 

 

 

If you add grants and tax credits, and adjust for inflation, and then adjust for median family income, you get to the point where you realize that, in fact,  fees were more or less constant in terms of affordability over the last decade or so.  So voila!  That damnable rise in tuition fees that so inconveniently accompanied the increase in participation rates?  Turns out it didn’t happen – at least if you properly count subsidies.  In fact, one could now convincingly argue that the lack of a relationship between fees and participation is a huge hoax, and that the rise in participation was actually fuelled by the massive infusion of tax credits and grants over the past fifteen years, which effectively netted out the impact of tuition.

There’s a slight problem with all this, of course.  And it’s that the zero-tuition crowd has a long track record of claiming that subsidies have no effect whatsoever, because sticker price is the only thing that matters.  No one thinks tax credits have any effect on participation, and the more hardcore of the zero-tuition crowd don’t believe grants matter either (True story: a long-time student leader informed me the other day that the whole concept of net tuition was bogus, and that grants should never be included in discussions about affordability, because “grants don’t reduce tuition, they just help you pay for it”.  Yes, really).

So the zero-tuition crowd has three choices here:

  • They can keep their beliefs about subsidies, but accept that participation has risen along with tuition, and admit that, perhaps, their views on tuition are wrong.
  • They can renounce everything they’ve ever said about subsidies, run with the idea that affordability has not been deteriorating, and arguing that this is what has fuelled the rise in participation.
  • Ignore all empirical evidence, and continue their evidence-free approach to the whole question.

No prizes for guessing which is likeliest.

September 19

Cultural Determinants of Data Acquisition Costs

I saw a fascinating piece in the New York Times awhile back.  It was about a trend at American universities, asking applicants if they were gay or not.  Apparently, these institutions believe that by asking students this question, they are sending a message that they are a gay-positive environment.

Interesting.

Americans think that transparency about identity is the path to utopia.  Enrolment statistics by race?  They’ve got them.  Indeed, they are required to keep such statistics, because of a clutch of laws designed to monitor whether or not Blacks (and, to a lesser extent, Latinos and America Indians) are being discriminated against.

In Canada, the rule of thumb is simple: on forms used for administrative purposes, you can’t compel anyone to reveal data about identity, beyond what is strictly necessary to achieve the purpose for which the information is being collected.  So, on applications to universities and colleges, asking people’s names and addresses is about as far as you can go (provinces have different standards on whether you can ask gender – some say you can’t).  Asking about ethnicity, or aboriginal status?  Totally verboten.  Whereas in the US it’s mandatory.

What that means is that, in Canada, acquiring any data about students – other than raw numbers – requires voluntary surveys.  And those can get expensive: done centrally through StatsCan (and its levels of quality standards) they cost millions; even if you just get a decent-sized consortium together to do something, it will run into hundreds of thousands once you count everyone’s labour costs.  You can get it down into the tens of thousands if you go with an electronic survey, but then there are response bias issues (you can correct for them, but it requires someone to have already done a decent survey to begin with – and with the loss of the census long form, it’s not clear that we have such a survey).

Of course, even Canada is at least somewhat ahead of, say, France.  There, the local conception of nationalism means that state agencies are forbidden from classifying citizens as anything other than citizens.  Blanc, beur, noir: they’re all French according to the government, and its socially unacceptable to classify them as anything else.  A morally attractive stance, perhaps, but what it means is that the French have real trouble measuring social inequality in ways that matter.

All of this is simply to say, if you’ve ever wondered why we don’t have statistics on ethnicity the way the Americans do, it’s this: they assume racial bias exists and keep stats to measure it.  We assume that racial bias exists, and so try to mask parts of individuals’ identities to prevent it.

September 13

Financing Canadian Universities: A Self-Inflicted Wound (Part 5)

We’ve covered a lot of ground in the last few days.  Back on Tuesday, we asked the question why faculty-student ratios could fall by 20% over two decades when per-student income had jumped by 40% over the same period.  The best way to sum up the answer is with the following graph:

Changes in Total and Operating Income per Student, Academic Salary Mass, and Student-Teacher Ratios, Indexed to 1992

 

 

 

 

 

 

 

 

 

 

 

 

The top line is total income per FTE student.  That rose 40% between 1992 and 2010, most of it in a few glorious years in the late 1990s.  The next line is operating income per student, which only rose 20% per student over the same period. That’s still good, of course, but it does mean that other parts of the university were receiving money at a faster rate than the operating budget was.

Now let’s look at academic compensation.  Despite an increase in the operating budget, total academic compensation (i.e., salaries + benefits) fell.  All of that fall happened prior to about 2002 – since then, the two have moved more or less in tandem.  What that means is that a lot of money within operating budgets was being moved into other areas.  As we saw on Wednesday and Thursday, the big “culprits” were scholarships, utilities, and, to a lesser extent, central administration.

Finally, there’s the faculty:student ratio, which fell more or less in lockstep with academic salary mass until 2001.  After that, individual faculty salaries began to rise.  Thus, even as total academic salaries stabilized, that amount bought ever fewer professors, because their real salaries were rising.

And that’s basically the story.  Billions of dollars went into the academy in the last twenty years, coming from students, government, and other sources.  But a disproportionate amount of that money went into non-operating areas (such as research).  And a disproportionate amount of operating money went into areas other than academic salaries.  And average faculty wages rose substantially in real terms.

That, ladies and gentlemen, is how faculty:student ratios can fall by 20% while income per student rises 40%.  And it’s worth underlining here: virtually all of this has to do with changing priorities within the academy, not changes in government policy.  It was universities who urged the new focus on research.  It was universities which made the decision to favour other spending categories over academic salaries.  It was the academic community as a whole which decided to pay more money to fewer professors, rather than keep salaries stable and hire more staff.  No one made the academy do this.  It’s a self-inflicted wound.

We have met the enemy, and he is us.

September 11

Financing Canadian Universities: A Curious Story (Part 3)

Yesterday, we saw that Canadian student-faculty ratios rose by 24% between 1992 and 2010, even though operating grants per student went up by 20%.  The cause, it turned out, was a combination of individual academic salaries rising, while aggregate academic wages fell, as a proportion of operating grants.  What we didn’t do yesterday was ponder why academic salary mass didn’t keep up with operating grants, and where the money went as a result.

Figure 1 – Operating Expenditures by Category, 1992-2010, in Real 2011 Dollars

 

 

 

 

 

 

 

 

 

 

 

 

Figure 1 shows that the two biggest categories under operating expenditures are “academic salaries”, and “other salaries and wages”.  Throw in benefits – compensation under another name – and these three categories make up about two-thirds of total operating expenditures.

With so many categories, it’s a little difficult to see exactly how much each category increased over time in Figure 1, so in Figure 2 we simply show growth indexed to 1992 levels.

Figure 2 – Growth in Expenditure Categories, 1992=100

 

 

 

 

 

 

 

 

 

 

 

 

Of the six major expenditure categories, academic salaries increased the least, by some margin – just 37% in real dollars, not quite enough to keep up with growth in student numbers.  Non-academic salaries – the next largest category – increased by 70%.  But growth for benefits, “other instruction & research”, and “other” (a catch-all category including travel, utilities, and externally contracted services) was all over 100%.

For reasons of legibility, Figure 2 excludes two line items that were in Figure 1.  The first is library expenditures, which are actually pretty trivial in the big picture (1.7% of operating expenditures).  The other is scholarships, which are excluded because they would have broken the scale.  Here’s what happened to scholarships between 1992 and 2010:

Figure 3 – Total Scholarships Expenditures, 1992-2010, in 2011 Dollars

 

 

 

 

 

 

 

 

 

 

 

 

This is one of those things universities just don’t get credit for.  Scholarships (a term which here includes both need and merit-based aid) increased by more than seven-fold, after inflation.  Based on previous research HESA has conducted, I estimate that between 55 and 60% of this money went to graduate students, which is consistent with large institutions’ increasing emphasis on research and graduate studies.

Another way to look at this question is to look simply at changing shares of total operating income, which we do below in Figure 4.

Figure 4 – Change in Shares of Operating Budgets by Category, 1992-2010

 

 

 

 

 

 

 

 

 

 

 

 

Although spending in all categories rose between 1990-2012, some spending categories “gained share”, while others lost it.  The biggest losers were faculty, as academic salary mass fell by 9 percentage points as a share of the operating budget.  Had they kept their share constant, there would have been another $1.6 billion in money for academic salaries.

But the “culprits” were not the oft-scapegoated bogeymen of “administration”.   Rather, the line items that significantly gained share were actually scholarships, non-wage benefits, and “other” (mainly utilities and externally contracted services).  This is not a story often heard on campus.  But it’s the truth.

September 10

Financing Canadian Universities: A Curious Story (Part 2)

So yesterday we noted how universities’ per-student income had increased 40%.  But we also noted that it’s a universally acknowledged truth that pretty much everyone in higher ed will swear up and down that things are worse than ever, always doing more with less, etc.  Is there a way to reconcile these competing notions without simply coming to the conclusion that profs and administrators are delusional/greedy?

Well, sort of.  Let’s start with Figure 1.

Figure 1 – Income per FTE Student and Student-Teacher Ratio

 

 

 

 

 

 

 

 

 

 

 

 

The blue line (left axis) just highlights you what I showed you yesterday – that per-student expenditures jumped from $23,000 to $33,000 over the period in question.  The red line (right axis) shows something different: the ratio of FTE students to FT professors.  This, weirdly enough, also increased over our period.  In fact, the ratio went up by 24%, from just below 18:1 to a shade over 22:1.

This is, pretty much, bananas; indeed, it’s a pretty stunning indictment of higher education as a whole.  Per FTE student income rose by 40%, and not only was that money not used to reduce student-teacher ratios, but the ratio actually deteriorated by 25%.  How is this possible?

Well, one reason is that the operating budget grew more slowly than other types of income.  Operating funds were up 82% over our period; research money, on the other hand, increased 178%.

Figure 2 – University Income by Fund1992-2010

 

 

 

 

 

 

 

 

 

 

 

 

But that’s not really a full answer – even if you pull out all those other income sources, operating budgets per student still rose by 20%.  So why are student-teacher ratios going up?

There are basically two reasons.  The first is that professors cost more than they used to.  Just looking at the period 2001-2009 – the period for which I happen to have data handy – average faculty salaries jumped by about 24% in real terms.  Now, that’s after a decade in which salaries stayed roughly even, or dropped a little, so the increase for 2001-09 period should be pretty close to the increase for 1992-2010.  In other words, the cost of a professor rose more or less proportionately with income per student.

Everything else being equal, that means that student:faculty ratios should have stayed roughly  the same, rather than having risen.  But here’s the second reason: everything else wasn’t equal.  Operating budgets increased twice as fast as academic salary mass, and, as a result, the percentage of operating budgets going to academic salaries fell from about 39% to 30%, mostly in the 1990s.

Figure 3 – Academic Salaries as a Percentage of Operating Budgets

 

 

 

 

 

 

 

 

 

 

 

 

So it was the combination of rising salaries and changing spending priorities that caused the rise in student ratios.  But this just begs the question: what were these new priorities?  Where did the money go? Stay tuned.

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.

September 06

Grants and Net Prices

Yesterday, we saw how tax credits lowered net prices by refunding students (or their families) roughly one out of every three dollars spent on tuition.  But that’s not the whole story, because there are a lot of university students who also get some form of non-repayable assistance (i.e. grants); for them, tuition is even lower.

Let’s start with Quebec, where net tuition after tax expenditures is a mere $1,555.  Data from the latest Aide Financiere aux Etudes annual reportadjusted for known changes in student aid expenditures, suggests that somewhere in the neighbourhood of 50-55,000 university students are receiving grants, which, on average, are worth $6,380 apiece.  Meaning that net tuition for grant recipients in Quebec is in fact negative $4,825.

In Ontario, net tuition after tax credits is $5,680.  Everyone with a family income under $160,000 is eligible for the Ontario Tuition Grant, which is (effectively) worth $1,730.  So that means that, in fact, for a considerable majority of the full-time undergraduate population, net tuition last year was is $3,950, which is lower than it’s been at any time since 1998-99.

Figure 1 – Net Real Tuition in Ontario, After Tax Credits and Tuition Rebate, 1995-96 to 2012-3

 

 

 

 

 

 

 

 

 

 

 

 

Here’s where the analysis gets tricky.  In the CSLP zone, many people receive more than one grant, mainly because of the overlap between federal and provincial aid.  But while we know the average size of each grant, there’s no method of working out how many of the 320,000 recipients of federal grants (who receive on average 1.18 federal grants each – you can get more than one) also receive one of the 250-300,000 provincial grants.

However, based on a little bit of policy analysis – and some phoning around to friends in provincial governments – I reckon that between half and 2/3 of all provincial grant recipients are getting federal aid, as well.  That would give us a ballpark of about around 430,000 total grant recipients, of which roughly two-thirds are in universities.  With roughly $1.2 billion being given out in the CSLP provinces, that suggests that the average grant recipient there receives about $2,800.

Taking that data and merging in the Quebec numbers gives us the picture we see in Figure 2: 

Figure 2 – Actual Net Costs, Canada, 2012-3

 

 

 

 

 

 

 

 

 

 

 

 

Across Canada, the sticker price of tuition and fees last year was $6,331.  As we saw yesterday, that falls to just over $4,300 when you take tax credits into account.  And that’s the real net cost for about two-thirds of the full-time student body.  But for the other third, the third that gets grants, real net tuition averages just over $1,000 – and it would appear that for a substantial proportion of these students, the actual cost is negative.

So, when the Statscan tuition numbers come out, just remember: no one actually pays the amounts Statscan reports.  Most students pay about 66% of the sticker price, and the neediest third (proportions may vary by province) pay about 17% of the sticker price.

September 05

Affordability

At some point in the next week or so, Statistics Canada will be releasing its annual statistics on tuition fees.  Hopefully it will be less of a fiasco than last year, when they released data a few days after the Quebec election, but didn’t bother to note that the planned tuition fee hike was being reversed.

What I want to do today is to put the inevitable “rising fees” stories that always accompany the Statscan release into some sort of context.  Students pay two types of fees – tuition and “ancillary fees”.  Statscan data on the latter is only marginally better than hopeless, so these fluctuating annual figures need to be treated with extreme caution; but they’re a non-negligible part of total tuition (15% or so), and so I include both in the graph below showing the evolution of total fees.

Figure 1 – Average Tuition, Canada, Nominal Dollars

 

 

 

 

 

 

 

 

 

 

 

 

Figure 1 is the graph that the zero-tuition crowd love to show: steady 5.1% annual tuition increases from 1995 to the present.  That’s actually a trick of scale – in fact, during the era of maximum government skintness (the 90s) tuition was going up about 9% per year to make up for cuts in government grants.  After 1999, the economy improved, public finances improved, and the rate of fee increase fell to just about 4%.

There is, however, a little thing called inflation.  It’s kind of important if you want to understand real prices over time.  Here’s what the tuition graph looks like if you take inflation into account.

Figure 2 – Average Nominal and Real ($2103) Tuition, Canada

 

 

 

 

 

 

 

 

 

 

 

 

This changes things a bit.  Those annual increases since 1999-2000?  Just two percent, after inflation.

But, as apparently nobody in the press or politics seems to understand, those increases in fees have been accompanied by increases in subsidies, too.  The most important of these are the increases of various forms of tax credits.  Say what you want about them – they reduce the actual cost of education by about a third.  Their value is eroding slightly at the moment due to inflation, but they are still worth $2,220 to the average Canadian student.

Figure 3 – Average Nominal and Real ($2013) Tuition plus Net Real Tuition Canada

 

 

 

 

 

 

 

 

 

 

 

 

Finally, if we’re looking at affordability, we also need to take into consideration a measure of ability-to-pay, because cost on its own is meaningless.  Televisions cost more than they did, say, 40 years ago, but no one thinks they’re “less affordable”, because incomes have risen even more quickly.  So to compare affordability across time, what we need to do is look at cost over time with respect to a measure of purchasing power, such as average family after-tax income.  Which I do, below.

Figure 4 – Real Net Tuition as a Percentage of Average After-Tax Family Income

 

 

 

 

 

 

 

 

 

 

 

 

So, is tuition less affordable than it was?  Well, a bit, yes.  Fifteen years ago, it took up 4.8% of average, after-tax income; now, it takes up 5.2%.  But calling it a crisis, the way the usual suspects routinely do, is a bit of a stretch.

And we haven’t even taken into account need-based student aid yet.  We’ll do that tomorrow.

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