HESA

Higher Education Strategy Associates

Category Archives: Statistics Canada

September 10

How StatsCan Measures Changes in Tuition

Every September, Statistics Canada publishes data on “average tuition fees”. It’s a standard date on the back-to-school media calendar, where everyone gets to freak out about the cost of education.  And we all take it for granted that the data StatsCan publishes is “true”.  But there are some… subtleties… to the data that are worth pointing out.

Statistics Canada collects data on tuition from individual institutions through a survey called the Tuition and Living Accommodation Survey (TLAC).  For each field of study at each institution, TLAC asks for “lower” and “upper” fees separately for Canadian and foreign students, for both graduate and undergraduate students.  Now, in provinces where the “upper” and “lower” figure are the same (eg. Newfoundland), it’s pretty simple to translate lower/upper to “average”.  In Quebec and Nova Scotia, where “upper” and “lower” are functionally equivalent to “in-province” and “out-of-province”, averages can be worked out simply by cross-referencing to PSIS enrolment data, and weighting the numbers according to place of student origin.  Everywhere else, it’s a total mess.  In Ontario, significant variation between “upper” and “lower” numbers are the norm, even inside the institution (for instance, with different tuition levels for different years of study).  Somehow, StatsCan uses some kind of enrolment weighting to produce an average, but how the weights are derived is a mystery.  Finally, in a couple of provinces where there are differences between the “lower” and “upper” figures, StatsCan chooses to use the “lower” figure as an average.  (No, I have absolutely no idea why).

But the tuition data is squeaky clean compared to the mess that is StatsCan’s data on ancillary fees.  Institutions fill in the ancillary fee part of the questionnaire every year, but usually without much reference to what was reported the year before.   Since StatsCan doesn’t have the staff to thoroughly check the information, institutional figures swing pretty wildly up and down from one year to the next, even though everyone knows perfectly well ancillary fees only ever go in one direction.

Another complication is that “average” is a central tendency – it is affected not just by posted prices, but also by year-to-year shifts in enrolments.  As students switch from cheaper to more expensive programs (e.g. out of humanities and into professional programs), average tuition rises.  As student populations grow more quickly in the more expensive provinces (e.g. Ontario) than in cheaper ones (e.g. Quebec, Newfoundland), then again average tuitions rise – even if all fees stayed exactly the same.  Both of these things are in fact happening, and are small but noticeable contributors to the “higher tuition” phenomenon.

A final complicating factor: the data on tuition and the data on enrolment by which it’s weighted come from completely different years.  Tuition is up-to-the-minute: the 2014-15 data will be from the summer of 2014; the enrolment data by which it is weighted will be 2012-3.  And, to make things even weirder, when StatsCan presents the ’14-15 data next year as a baseline against which to measure the ’15-16 data, it will be on the basis of revised figures weighted by an entirely different year’s enrolment data (2013-4).

In short, using SatsCan tuition data is a lot like eating sausages: they’re easier to digest if you don’t know how they’re made.

September 08

Some Scary Graduate Income Numbers

Last week, the Council of Ontario Universities put out a media release with the headline “Ontario University Graduates are Getting Jobs”, and trumpeted the results of the annual provincial graduates survey, which showed that 93% of undergraduates had jobs two years after graduation, and their income was $49,398.  Hooray!

But the problem – apart from the fact that it’s not actually 93% of all graduates with jobs, but rather 93% of all graduates who are in the labour market (i.e. excluding those still in school) – is that the COU release neither talks about what’s going on at the field of study level, nor places the data in any kind of historical context.  Being a nerd, I collect these things when they come out each year and put the results in a little excel sheet.  Let’s just say that when you do compare these results to earlier years, things look considerably less rosy.

Let’s start with the employment numbers, which look like this:

Figure 1: Employment Rate of Ontario Graduates 2 Years Out, Classes of 1999 to 2011

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Keep your eye on the class of 2005 – this was the last group to be measured 2 years out before the recession began (i.e. in 2007).  They had overall employment rates of about 97%, meaning that today’s numbers actually represent a 4-point drop from there.  If you really wanted to be mean about it, you could equally say that graduate unemployment in 2013 has doubled since 2007.  But look also at what’s happened to the Arts disciplines: in the first four years of the slowdown, their employment rates fell about two percentage points more than the average (though, since the class of ’09, their employment levels-out).

Still, one might think: employment rates in the 90s – not so bad, given the scale of the recession.  And maybe that’s true.  But take a look at the numbers on income:

Figure 2: Average Income (in $2013) 2 Years After Graduation, Ontario Graduating Classes from 2003-2011, Selected Disciplines

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Figure 2 is unequivocally bad news.  The average in every single discipline is below where it was for the class of 2005.  Across all disciplines, the average is down 13%.  Engineering and Computer Science are down the least, and have made some modest real gains in the last couple of years; for everyone else, the decline is in double-digits.  Business: down 11%.  Humanities: down 20%.  Physical Sciences: down 22% (more evidence that generalizations about STEM disciplines are nonsense).

Now, at this point some of you may be saying: “hey, wait a minute – didn’t you say last year that incomes 2 years out were looking about the same as they did for the class of 2005?”  Well, yes – but you may also recall that a couple of days later I called it back because Statscan did a whoopsie and said: “you know that data we said was two years after graduation?  Actually it’s three years out”.

Basically, the Ontario data is telling us that 2 years out ain’t what it used to be, and the Statscan data is telling us is that three years out is the new two; simply, it now takes 36 months for graduates to reach the point they used to reach in 24.  That’s not a disaster by any means, but it does show that – in Ontario at least – recent graduates are having a tougher time in the recession.

Tomorrow: more lessons in graduate employment data interpretation.

August 26

What Students Really Pay

In a couple of weeks, Statistics Canada will publish its annual Tuition and Living Accommodation Cost (TLAC) survey, which is an annual excuse to allow the usual suspects to complain about tuition fees.  But sticker price is only part of the equation: while governments and institutions ask students to pay for part of the educational costs, they also find ways to lessen the burden through subsidies like grants, loan remission, and tax expenditures.  And Statscan never bothers to count that stuff.

Today, we at HESA are releasing a publication called The Many Prices of Knowledge: How Tuition and Subsidies Interact in Canadian Higher Education.  Unlike any previous publication, it looks not just at a single sticker price, but rather at the many different possible prices that students face depending on their situation.  We take ten student cases (e.g. first-year dependent student in college, family income = $80,000; married university student, spousal income = $40,000; etc.), and we examine how much each student would be able to receive in grants, tax credits, and loan remission in each of the ten provinces.  It thus allows us to compare up-front net tuition (i.e. tuition minus grants) and all-inclusive net tuition (i.e. tuition minus all subsidies) not just across provinces, but also across different students within a single province.

Some nuggets:

  • On average, a first-year, first-time student attending university direct from high-school, with a family income of $40,000 or less receives $63 more in subsidies than they pay in tuition, after all subsidies – including graduate rebates – are accounted for (i.e. they pay net zero tuition on an all-inclusive basis).  If they attend college, they receive roughly $1,880 more in subsidies than they pay in tuition (i.e. -$1800 tuition);
  • A first-year, first-time student attending university from a family with $40K in Quebec, after all government subsidies, pays -$393 in all-inclusive net tuition.  In Ontario, the same student pays -$200.  But if we were to include institutional aid, the student in Ontario would likely be the one better off, since students in Ontario with entering averages over 80% regularly get $1,000 entrance awards, while students in Quebec tend not to.  For some students at least, Ontario is cheaper than Quebec;
  • On average, college students who are also single parents receive something on the order of $11,000 in non-repayable aid – that is, about $8,500 over and above the cost of tuition.   In effect, it seems to be the policy of nearly all Canadian governments to provide single parents with tuition plus the cost of raising kids in non-repayable aid, leaving the student to borrow only for his/her own living costs.

The upshot of the study is that Canada’s student aid system is indeed generous: in none of our case studies did we find a student who ended up paying more than 62% of the sticker price of tuition when all was said and done, and most paid far less.  But if that’s the case, why are complaints about tuition so rife?

Two reasons, basically.  First, Canada’s aid system may be generous, but it is also opaque.  We don’t communicate net prices effectively to students because institutions, the provinces, and Ottawa each want to get credit for their own contributions.  If you stacked all the student aid up in a comprehensible single pile, no one would get credit.  And we can’t have that.

The second reason is that Canada only provides about a third of its total grant aid at the point where students pay tuition fees.  Nearly all the rest, stupidly, arrives at the end of a year of studies.  More on that tomorrow.

June 02

Bad Memory

Some really sobering stuff in a paper I just got from Statscan called, “Job Market Realities for Post-Secondary Graduates”.  Listen to this:

  • “Graduates of a field with low unemployment and little underemployment were also likely to earn high salaries and be content with their jobs.  They were usually graduates of job-oriented fields such as engineering, teacher training, most health disciplines, business, computer science and some technologies.”
  • “A more general education in subjects with little practical application often (leads) to a lower-paid job which made little use of knowledge and skills acquired during the years of study… those who fared worst held degrees/diplomas in fine and applied arts, humanities and social sciences and some of the sciences.”
  • “Many trades, which do not require post-secondary education, pay better than some occupations held by postsecondary graduates, especially office work.”
  • “Newfoundland offered the highest starting salaries, with Saskatchewan a close second.”
  • “Half of all bachelor’s graduates planned to go back to school within two years.”

Enraging what decades of neo-liberalism has done to our education system, huh?  Why can’t we go back to the 70s when everyone had a job, humanities and social science graduates weren’t undervalued and everyone had a job?

Oh, wait, hang on.  This survey is from the 1970s!  In fact, all of this is from the two-year follow-up of the university and college graduating classes of 1976 (the forerunner of the current National Graduates Survey).

Turns out the 1970s weren’t quit the bonanza that some folks like Generation Squeeze like to make it out.  For the class of 1976 in Ontario, the unemployment rate 2 years out for university graduates was 8%.  For the class of 2010, it was 5%.  Average salary 2 years out for the class of 1976 was $14,600, or $47,300 in 2012 dollars.  For the class of 2012, the equivalent figure was $49,277.  In 1978, 80% of recent grads said their job had a relationship with their field of study.  In 2012?  82%.

I could go on here, but you get the picture.  There’s very little going on for graduates in the labour market that wasn’t going on forty years ago.  Back then, we were also in a resource boom, and trades looked good compared to Arts and Science.  Jobs in Newfoundland and Saskatchewan looked pretty good compared to jobs in Ontario (we don’t know about Quebec because back during the first PQ government, Quebec institutions weren’t allowed to participate in national studies like this).  This is just a phase we go through.

Of course, some people may look at this result and see stagnation.  Graduates only getting a $2,000 raise in 40 years!   But this is to miss the point almost entirely.  In 1978, the participation rate at Canadian universities was around 10%; we’re now just over 30%.  That is to say, even accounting for population growth, there are three times as many young people getting salaries which, on average, are the same as the coddled, easy-going graduates of the mid-70s.

Nostalgia makes us look at the past with rose-coloured glasses.  But it’s no basis for making policy.  Look past the soft-focus gauze and the rantings of the hell-in-a handbasket crowd: the fact is, our grads are doing as well as they have at any time in the last 40 years.  We should celebrate that.

May 30

Valuing Foreign Degrees

There was an interesting Statscan paper out yesterday that made some fascinating observations about education, immigration, and human capital.  With the totally hip title, The Human Capital Model of Selection and the Economic Outcomes of Immigrants (authors: Picot, Hou and Qiu), it’s a good example both of what Statscan-type analyses do well, and do poorly.

At one level, it’s a very good study.  It uses the Longitudinal Administrative Databank (Statscan’s coolest database – it’s a longitudinal 20% sample of all of the country’s taxfilers) to follow the fates of newcomers to Canada in terms of earnings.  What they find is that in the first few years after entry, the very large wage premiums that “economic class” immigrants (as opposed to “family class”) with degrees used to have over immigrants without degrees has shrunk substantially.  However, over the longer term, the study also finds that educated immigrants have a much steeper earnings slope than those with less education – which is to say that if you shift the lens from “what are immigrants’ labour market experiences in their first three years in Canada”, to “what are immigrants’ labour market experiences in the first ten-to-fifteen years in Canada”, you get a much different, and more positive story.

Now, a lot of people want to know why immigrants with degrees aren’t doing as well in the short term, even if the decline in long-term fortunes isn’t as severe as first thought.  The authors don’t answer this question, but many others have come up with hypotheses.  When you hear stories about immigrants doing worse than they used to in the labour market, even holding education constant, it’s easy to jump to conclusions.  Canadian immigration since the 1980s has increasingly been from Asian countries, so it’s easy enough to conjure up some racism-related theories about the decline.  But I want to point something else out.  Below I reproduce a table from a this recent UNESCO report on higher education systems in Asia.  It shows the distribution of university professors by various levels of qualifications.

Table 1: Highest Level of Higher Education Instructors’ Academic Attainment, Selected Asian Countries

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Here’s the problem: Should we really assume that a Bachelor’s degree from Indonesia confers the same skills that one from the US or Europe does?  Probably not.  And yet every single Statscan study that looks at education, immigration, and earnings assumes that a degree is a degree, no matter where it’s earned. I understand why they would do that; how else would one judge equivalencies? And yet choosing to ignore it doesn’t help either.  The reason today’s university-educated immigrants are doing worse than the ones of 30 years ago may simply be that they have lower average levels of skills because of where they went to school.

None of this is to suggest racism isn’t a factor in deteriorating incomes for new immigrants, or that Canadian employers aren’t ridiculous and discriminatory in their demands that new hires have “Canadian experience”.  It’s simply to say that degrees aren’t all made the same, and it would be nice if some of our research on the subject acknowledged this.

May 23

New Data on Student Debt: the 2010 National Graduates Survey

The National Graduates Survey figures on debt for the class of 2010 were (quietly) released yesterday.  Unlike the employment data they released a few weeks ago, this data actually *is* comparable to results from previous surveys.  It is thus a good way to check on whether/how student debt is actually reaching “out of sight” levels.

So, let’s start with some interprovincial comparisons.

Average Government Student Loan Debt at Graduation, Borrowers Only, By Province and Type of Institution, Class of 2010

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The national average government debt among borrowers was $22,300 for university graduates, and $14,000 for college graduates.  However, this conceals some pretty wild differences between provinces, especially at the university level where the provincial means extend from $11,900 in Quebec to $35,000 in New Brunswick.  Of particular interest is the fact that Ontario, the province with the highest tuition, actually has among the lowest levels of debt (indeed, between 2000 and 2010, it fell nearly 17% in real terms).

Looking at the data over time, the next two figures show how government student loan debt has evolved:

Incidence and Mean Amount of Government Student Loan Debt at Graduation, Bachelor’s Degree Borrowers Only, 1982-2010

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Incidence and Mean Amount of Government Student Loan Debt at Graduation, College Borrowers Only, 1982-2010

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The takeaway here: despite steadily rising tuition, the percentage of students taking out need-based loans to finance their education hit a thirty-year low in 2010.  Debt was still high, but in real dollars was below where it was in 2000.

Now, while need-based government debt has been falling, non-need-based (or at least, not necessarily need-based) private debt has been rising.  Private debt is a mish-mash of credit card debt (which most surveys suggest is pretty small), private bank loan debt, and debt to family members – the last of these is presumably fairly soft debt in the sense that it is available on highly negotiable terms and there is a reasonable chance of some form of debt forgiveness.  Incidence of all forms of these debt combined has risen from 19% to 26% among bachelor’s graduates since 2010 (16 to 22% among college grads), and average debt from these sources (among those with any amount of such debt) has risen from $13,170 to $17,700 for bachelor’s graduates ($8,300 to $10,000 for college graduates).

It’s not clear what to make of the private debt figures.  For the 15% of the student population that has both public and private debt, one assumes that the recourse to private debt is indicative that for this part of the student body, the existing student aid packages are inadequate.  This is a group we should be pretty concerned about.  As for the other 11% who only have private debt, it’s hard to say what the issue is.  Why are they choosing private money over public money?  Are they actually fairly well-off, and hence ineligible for aid?  We simply don’t know.

In any case, as a result of this increase in non-public debt, total debt is up very slightly, as we see in the figure below.  But while the averages of debt are up, the incidence is down – from 53% to 50% on the university side, and from 49% to 43% on the college side.  And this, recall, in a period where participation rates were growing sharply.

Average Total Debt at Graduation, Borrowers Only, By Type of Institution, Classes of 2000, 2005 and 2010

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So: government debt down, private debt up.  Incidence of total debt down slightly, average debt up slightly.  Any way you look at it, the basic picture on student debt is right where it’s been for the last decade.  And meanwhile, interest rates have fallen, and after-tax incomes have risen.

I know facts never get in the way of a good story, but: There.  Is.  No.  Crisis.  Period.

May 14

Trends in Applications

Some interesting trend data to review from Ontario today.

First, there’s the fact that applications from secondary schools have dropped by 3% this year, from 92,892 to 89,609 (as of the February snapshot, which for most purposes is as good as the final numbers, since something like 95% of all applicants apply before the end-of-January line).  This is a moderately big deal since it’s the first time since the double cohort that numbers have fallen.

Figure 1: Applications from Secondary Schools by Year, Ontario, 2004-14

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Some university officials have waved this away as being a result of declining population, but there’s no evidence that the population of 18 year-olds has fallen by 3%.  Statscan hasn’t published data for 2014 yet, but between 2010 and 2013 the number of 18 year-olds actually increased by 2%, even though the agency’s population projections had suggested their numbers would fall somewhat.  In the chart below, which shows the ratio of secondary school applicants to 18-year-olds over time, I average Statscan’s projection with the actual annual increase for the past four years, and assume a fall of 1.6% in 2014. So even accounting for population change, university applicant numbers are still down.

Figure 2: Applications from Secondary School as a Percentage of 18-Year-Olds, Ontario, 2004-14

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The fact that the percentage of 18 year-olds attending Ontario universities has fallen is notable, but we shouldn’t overstate the implications.  In the first place, it hasn’t fallen far – just back to where it was in 2012.  Second, these numbers are only for Ontario applicants; they don’t include all the many international students whose numbers are still rising.  Fact is, most institutions will be OK for awhile yet.

More interesting, perhaps, is what’s going on with applications by field of study.  Check out, for instance, what’s happening with the “big four” fields, which account for slightly over 70% of all enrolments.  Applications to Arts subjects have been falling for some time; in 2003, 35% of all applications were to Arts Faculties, now it is just 27% (albeit of a much larger applicant pool – in absolute numbers they are about where they were in 2003).  Science and Business have more or less kept their share of enrolments steady over time, while Engineering has seen its share grow from 8% to 11%.  That might not sound like much, but in absolute terms it represents an increase of 81%, from 5,515, to 9,984.

Figure 3: Arts, Science, Business, and Engineering Applications as Percentage of Total, Ontario, 2004-14

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But look a little more closely at the data, at some of the smaller fields of study, and you can see some really amazing shifts in numbers.  Nursing, by some distance, is the “hot” discipline (not surprising, given the 100% placement rate and the $50K plus starting salaries), with applications increasing by close to 150%.  Social Work has seen applications double, and Math applications are up almost 90%.  Fine Arts applicant numbers have stayed very stable over the past decade; only Journalism has seen a major negative shock, with applications down by over a third from their 2008 peak.

Changes in Application Numbers, Selected Fields of Study, Ontario, 2004-14, Indexed to 2004

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The disciplinary enrolment shifts are of significantly more importance than 1-year changes in total enrolments.  They show that, over time, students do in fact respond to changes in labour market conditions, but that it may take a few years for the response to be evident.  Quite properly, students might want to see sustained evidence of change before committing to a different field of study.  And that’s a good thing, whatever the usual Labour Market whiners might say.

April 08

Early NGS Results: The Caveats

Yesterday, I showed you some charts on graduate outcomes indicating that the kids were – mostly – alright: employment steady, Full-time employment steady, graduate incomes steady, etc.  But there are three significant reasons to be cautious about over-interpreting these results.

The first is that this year’s NGS was conducted differently from previous iterations.  In previous years, the survey was conducted two years after graduation.  This year, the survey was done three years out, with graduates being interviewed in 2013 about what their situation was in 2012, to try to keep the 2-year time frame.  This creates an array of small biases in responses, though whether it creates over- or under-estimation of employment and income is hard to say.

The second caveat has to do with the survey response rate.  In 2000, the NGS response rate was 70%; this year’s response rate was 49%, which has to be one of the lowest ever seen in a Statscan survey.  Partly, this is probably an artefact of waiting an extra year to survey students, and partly it’s that students are getting harder to follow (when you survey on landlines, the caller eats the cost – on cell phones, part of the cost burden falls on the respondent, which can’t be good for response rates).

The third problem is the trickiest.  When Statscan reports income and employment figures, it does so only for those students who do not enrol in programs leading to further certification.  This eliminates some problematic data from people who are either still in school, or who have gained an additional credential (which is good), but at the same time it creates problems because the proportion excluded changes over the economic cycle.

Percentage of College and Bachelor’s Graduates Seeking Additional Certifications Within 2 Years of Graduation

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The suspicious might look at this and say: “holy moley! The NGS data on income and employment ignores half of all university graduates – surely that’s where all the underemployed  barista sociology graduates are!  Skills Mismatch Bingo!”

But slow down a minute.  First, the rates at which college and university grads attempt to acquire extra credentials mirror one another; this is not clear evidence in favour of a “college-grads-have-it-better-than-university-grads”, or a “skills mismatch” proposition.

Second, it’s not at all clear that, among university grads, the phenomenon is disproportionately due to Arts grads.  Even in the best of economic times, 40% of university grads continue on to extra credentials, and they come from all across the university.  The proportions by field of study for 2005 (2010 numbers not yet available) actually showed that Science students (62%) were more likely to do so than humanities (56%) and social science (45%) grads (Fine arts was at 38%, engineering, math, and computer science grads were at 30%).

All of which is to say: while the employment and income data from NGS are technically apples-to-apples comparisons, the fact is that the basis of these comparisons varies slightly from survey to survey.  Some of the good news on graduate income and employment rates is probably due more to students choosing to take extra education rather than brave the job market.  It thus probably isn’t entirely fair to say that the 2012 data implies things are getting better for grads.

That said, you can’t twist this evidence to support the idea that there has been a radical change in the labour market for graduates.  It’s mostly as it’s always been, with a slight up-tick in people taking more than one credential.

So can we please ditch the “everything is different” narratives and get back to real issues now?

 

April 07

Early Results from the National Graduates Survey: The Good News

Some very early National Graduates Survey (NGS) results are out, and they’re mostly good news.  The NGS – for the uninitiated – surveys university and college graduates two years after graduation.  It’s closely watched for its numbers on graduate employment, income, and debt.  Statscan has been doing this now for a little over thirty years (the first one was on the class of 1982), and since 1990 it has been conducted every five years.

Usually, when Statscan does a major survey, it “launches” with an analytical report and the release of a public-use microdata file (PUMF).  This time, however, they chose to do neither, which is more than a bit weird.  It’s welcome in the sense that it gets data into the public domain more quickly, but unwelcome in the sense that the only data available is what you get via a set of highly truncated standard tables (no debt data this year, for a start) and what people can order via custom tables for hundreds – possibly thousands – of dollars.  I’ve ordered quite a bit of data, which I can hopefully share with all of you relatively soon, but for today we’re only going with what’s in the standard tables.

Are you sitting comfortably?  Then I’ll begin.

The picture on employment and immigration looks pretty good.  To be clear about what’s being shown here, NGS only releases data on graduates who finished a level of study but who did not take any further education.  In theory, this is a way of making comparisons more apples-to-apples: it avoids methodological problems of adding incomes of BA students who went on to do a 1-year Master’s degree in with students who just did a Bachelor’s degree.  It’s less than totally satisfactory, but it has the benefit of simplicity.  Anyways, here’s what the employment data looks like for college and Bachelor’s grads:

Full- and Part-time Employment Rates for College and Bachelor’s Graduates Two Years After Graduation, NGS 2005 (in 2007) and 2010 (in 2012)

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Got that?  From the height of the boom to the middle of the current “recession”, there’s essentially no difference either in terms of overall employment or in terms of full-time employment.  To the extent that there are people struggling and having a hard time finding a job, it’s business as usual: the proportion has not changed since the height of the boom (for both college and university grads, unemployment rates in both periods were 5%, with another 5% not in the labour force).

Ok, you say, but what about income?  Surely the recession has done a real number on graduates’ salaries?  Well, no.  Adjusted for inflation, there’s been a rise in median salaries of 7% for Bachelor’s graduates and 8% for college graduates.

Median Salaries of College and Bachelor’s Graduates Two Years After Graduation, NGS 2005 (in 2007) and 2010 (in 2012), in $2012

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My favourite crazy pieces of data from NGS, though, are the province-by-province figures.  Check out Newfoundland, which according to NGS now pumps out the country’s best-off college and university graduates:

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These are all good stories, worth keeping in your armoury next time someone whines about skills gaps or spouts some nonsense about a lost generation.  But there are a few caveats to this story.  I’ll deal with them tomorrow.

March 05

The Long-Term Benefits of Higher Education

A very good Statscan report came out last week, and didn’t get nearly enough attention.  Authored by the excellent Marc Frenette, it’s called, An Investment of a Lifetime? The Long-term Labour Market Outcomes Associated with a Post-Secondary Education, and it deserves a wide readership.

What Frenette did was link the 1991 census file to the Longitudinal Worker File (LWF), which integrates data from Records of Employment, annual T1 and T4 files, and some data on employers as well, for a 10% random sample of all Canadian workers.  From this, he created a sample of about 8,000 people who were born in Canada between 1955 and 1957 (i.e. who were about 35 years old at the time of the census), and who held jobs in 18 out of 20 years since then. From this, he worked out what the added value of university and college credentials were over that period.

Figure 1 shows earnings by education level.  For men between the ages of 35 and 55, the added benefit of a college education (vs. high school) was $153,000; for a university education it was $445,000 (for women, the figures were $115,000 and $280,000).  In addition to higher salaries, higher levels of education were also associated with higher levels of union membership, and lower frequency of layoffs.

Figure 1: Net Present Value of 20-Year Earnings of Canadian-Born Workers, by Level of Education

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Figure 1 isn’t exactly ground-breaking; more education = more money, and more so for men than women.  Where it gets interesting is when the results are disaggregated by gender, and attention is paid not just to means and medians but also at the distributional tails.  Figure 2 compares the wage premiums at various percentiles for female college and university graduates, over high school graduates in the equivalent percentiles.

Figure 2: Cumulative Additional 20-Year Earnings for Female College and University Graduates, at Selected Percentiles

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Figure 2 shows three things.  First, women with university degrees make more money than those with college or high school across all percentiles.  Second, that said, down around the 5th-10th percentile, the premiums are so low that it’s really not clear that women are better off with higher education.  And third, the premium for higher education really flattens out above the median – which, as Figure 3 shows, is not even vaguely the case for men.

Figure 3: Cumulative Additional 20-Year Earnings for Male College and University Graduates, at Selected Percentiles

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Crazy stuff.  Recall from Figure 1 that average gains for men were significantly higher than for women.  But Figure 2 and Figure 3 show that the median gains – those at the 50th percentile – are about the same.  The difference is that among males, the top ten percent – and especially the top five percent – are reaping astronomical rewards from higher education.

The last amazing thing in the paper has to do with how men and women with bachelor’s degrees fare comparatively in the public and private sectors.  And the numbers there are astonishing: in the bottom ten percentiles in the private sector, women are making less money, cumulatively, than their counterparts with just high-school education.  But what’s really interesting here is the fact that in the public sector, at least, women actually reap higher gains than men.

Figure 4: Median Cumulative Additional Earnings for Male and Female University Graduates in Public and Private Sectors

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Nitpickers will likely snub this study – it deals with a cohort that finished school 35 years ago, it doesn’t disaggregate by field of study, etc.  But methodologically, it points to ways to conduct future studies (we could do the same with a shorter period for 25 year-olds in the 2001 census, for instance), and substantively it gives us a lot to chew on, not only in terms of average earnings, but also with the distribution of those earnings.  Kudos to Marc for this work.

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