As well as taking issue with my analysis of the graduate labour market, Bob Birrell and his colleagues take issue, in their People and Place article, with the Universities Australia (formerly known as the AVCC) statistics on unmet demand.
The universities themselves, and the government, argue that unmet demand for university places is now minor – 13,200 was the estimate for 2007, a little more than a third of what it was three years ago. Birrell and his colleagues say that this seriously understates the true figure, because Universities Australia (UA) discounts aggregate unmet demand – the number of people who applied for a place but did not get one.
I don’t fully agree with the Birrell et al critique, but it raises important issues about how ‘unmet demand’ should be calculated. The UA methodology takes out those applicants who applied for only one or two courses, presumably on the argument that many of them could have secured a place had they been more flexible in what courses they were prepared to take. Of the remaining unsuccessful applicants, the UA then discounts the number again by the ‘state rejection factor’, ie given that a certain percentage of people who are offered a place turn it down, it is reasonable to assume that a similar percentage of unsucessful applicants would also have declined their offer had they received one. As Birrell et al point out, one likely reason for rejections is that applicants were not offered the place they wanted.
From the government/Universities Australia perspective, this discounting make sense – their object is to fill the places allocated by the government, not to meet student demand. But if student preferences count for something, as I think they should, then the official unmet demand figure is too low. Indeed, we could go further than Birrell et all and argue that even people who are actually enrolled could also be counted in ‘unmet demand’ because they are not in the course, or not in the university, that they wanted.
However, I don’t think that all demand should be met. Universities should not be obliged to take students they don’t think are suitable. If a student with an ENTER of 65 only applies for medical courses, the fact that they are rejected and turn up in ‘unmet demand’ statistics is not a system failure. The unmet demand I am concerned about is the turning down of students who would have been taken were it not for the government’s quota system.
Unmet demand on Universities Australia’s calculation is concentrated among relatively weak applicants. For students with an ENTER of 70 or above nearly all receive offers, though 16-18% of them decline those offers. As I argued towards the end of my graduate mismatch paper (pdf), we should be cautious with people with ENTERs under 70. They are more likely than higher-scoring applicants to get poor academic results if enrolled, giving us reason for concern that they either won’t finish or will be over-represented among graduates not in employment matching their formal qualifications. As Universities Australia only removes applicants with ENTERs below 53 on the grounds that they are not academically qualified, then there is an argument that their unmet demand calculation is too high. They are counting some people who are unlikely to be offered a place under any system, and who probably should find some other form of further education. Their rejection may be personally disappointing, but it is not a policy problem.
Either way, Birrell and his colleagues are right to draw attention to the fact that ‘unmet demand’ is not a straightfoward statistic like how many students actually enrol. Both the number and its significance depend heavily on assumptions about policy goals, and the Universities Australia number fits the perspective of a central controller indifferent to student preferences, rather than the perspective of those who think all (or almost all) student demand should be met, Birrell and his colleagues, and those, like me, who think that supply should be able to move in response to demand.
7 thoughts on “What is ‘unmet demand’ for university?”
where do you get the data on the critical ENTER being 70, I’ve analysed results from two degrees I’ve been involved with (over a thousand students in both cases) and I’ve found in both cases, that the data splits into three groups (average marks from one of the degrees
Actually, I saw a talk from our VC about what to do with these low ENTER score people (whom get in via the cruddy country campus the university I work at has which allows much lower entry scores than the city one).
He had a very practical solution — if these guys first do 2 years of Tafe and then go into the second year of university, then they perform no worse than those with the average ENTER scores of the city campus. ALternatively, if they go into first year (as they do now), they are a disaster. WHether you can convince students this is the best route for them is another question — particularily when there is competition amongst universities for these low Enter people.
VOA -There are some references at endnotes 26 & 27 of my paper. Generally the lower the ENTER the worse the average grades at university and the lower the rate of completion – what an ‘acceptable’ rate of failure or non-completion is would of course be open to debate from a public policy perspective (ie should we encourage people to enrol, how much should we spend?). 70 was my ballpark judgment. Scandalously in my view, there is very little published research on this important subject, and none that a would-be uni student is likely to be able to find.
You’d know the precise figure, I’m sure, but isn’t our university attendance rate over 30%? If true, that would make 70 an impossibly high cutoff, wouldn’t it? Or are you comfortable with some 65 TER people coming in at the mature-age stage?
I should make it clear that I am *not* suggesting an ENTER of 70 as a basis for a policy cut-off. I criticised the Group of Eight scholarship scheme for requring a cut-off point that would at minimum be arbitrary at the edges. I favour decentralised selection, in which all relevant information can be taken into account. My point above was just that many weaker students would struggle to be admitted in any system, and the public policy case for encouraging them as a group to pursue higher education is not strong, given the risks that they won’t finish or won’t get jobs that are any better than they could have secured anyway.
In 2007, 22% of school leavers who were offered and accepted a place had an ENTER of 70 or below. On Birrell’s calculations, comparing DEST age data with ABS population estimates, university attendance peaks at age 19 when 27-28% are enrolled. ABS Education and Work finds that in our most educated age cohort, those aged 25-34 in 2006, 29.2% had a bachelor degree or higher.
It’s clear from these figures that the attendance rate would exceed 30%, but perhaps not yet the graduation rate.
I’m sure you must be aware that decentralized selection can be exceedingly time-consuming if done properley– someone has to do the interviews, compare the resume’s and so on — either that or you push the problem onto someone else (like GAMS — not such a bad solution in my books — but it would get massively criticized if you did it for first years — I can also imagine getting students to pay to be interviewed by a 3rd party, but I know of no-one that does this, presumably for the same reason). In addition, for first years, the amount of extra information you can get is often zero (I went to high school, worked at McDonalds…), and by the time you get to 4th year, where you get some variance, marks become very good predictors (much better than other info.). It seems to me that the best you could hope for is to weight subjects differently (which we can do now anyway), although I’d be interested to see any data that shows you that it is possible to pick a better a group of 1st years in any bigger subject based on this. My bet is that even if you were willing to invest the time in doing this (as is done for mature age students), the amount of extra performance you get is very limit. I presume this is a fairly wide spread belief, which is why arbitrary cut-offs are used. Its either that or have a system like France, where you let anyone in, but thats definitely worse than a cut-off.
Conrad – By ‘decentralised’ I was opposing nationally-set cut-offs, not course cut-offs. I was defending the status quo of universities making their own decisions, except that I think far more information should be released for the benefit of potential applicants, who pay most of the cost of incorrect choices.
I should be fairly easy to use historical data to see if there are patterns of outcomes related to ENTER scores and perhaps other characteristics (such as the well-known gap between students who went to non-selective government schools and those who went to private schools, and male/female differences).
As for alternative entry mechanisms, again this should be a decentralised decision as to whether the added costs are worthwhile or not.