Do Oxbridge students earn more (and how would we know)?

As regular readers of this blog will know, I am mildly obsessed with the UK government’s LEO (Longitudinal Education Outcomes) statistical set, which provides vast amounts of easily manipulable statistical data. The set measures what the UK government increasingly considers the key educational outcome of a university education: how much graduates earn. But this is not the post I originally set out to write, and the reason why interests me, and hopefully you.

Sundial with chronophage ("time-eating" grasshopper.
Like the Corpus Christi College Cambridge chronophage, the LEO dataset eats time. (image by Rror from https://commons.wikimedia.org/wiki/File:Corpus_clock_pol.jpg)

I wanted to check one of the basic assumptions being made about discrimination in university education (especially racial discrimination): that Oxford and Cambridge graduates earn more than those from other universities and so any discrimination in their intake causes major economic disadvantage right from the start of a career.

The claim about Oxbridge students earning more has tended to be made (especially by the Sutton Trust) either based on Oxbridge over-representation in “top jobs”, e.g. in Leading People 2016 or based on graduate earnings (e.g. Earning by Degrees from 2014). But LEO data would allow us (so I thought) to look in a bit more detail. One crucial thing it’s already demonstrated is regional differences: see for example this chart (Figure 22, p. 46) from Graduate outcomes (LEO): Employment and earnings outcomes of higher education graduates by subject studied and graduate characteristics SFR 15/2018 looking at the home region (address prior to starting an undergraduate degree) of young students attending English universities.

Graph showing earnings of graduates by home region

It’s likely that this is due to students wanting to remain in a specific region after graduating, even if doing so harms their earning potential. That’s a problem if you’re comparing graduate outcomes from Oxbridge (in the most prosperous south-east of the UK) with the other Russell Group universities which have a wider geographical spread, or even the Sutton Trust’s highly selective Sutton Trust 13 universities (Birmingham, Bristol, Cambridge, Durham, Edinburgh, Nottingham, Oxford, St Andrews, Warwick, York, Imperial College London, LSE, UCL).

So what I wanted to do instead was compare Oxbridge LEO data by subject against some top London universities: I chose Imperial, King’s College London, LSE and UCL. All of these have above average attendance by ethnic minorities and are in the most prosperous region of the UK. They struck me therefore as a reasonable proxy for graduates who were willing and able to find work in London and the South-East generally.

So far, so good, but then I actually started looking at the data. This is from the most recent data currently available (Graduate outcomes (LEO): subject by provider, 2015 to 2016, https://www.gov.uk/government/statistics/graduate-outcomes-leo-subject-by-provider-2015-to-2016) and shows the median earnings for both sexes, 5 years after graduation:

Cambridge Oxford Imperial KCL LSE UCL
Architecture, Building and Planning Not available 33,900
Biological Sciences (excluding Psychology) Not available Not available 31,200 Not available Not available
Business & Administrative studies 56,300 67,200 Not available 37,400 Not available 38,400
Computer Science 46,300 55,800 60,000 40,100   41,500
Creative Arts & Design 23,800 26,400 27,000 Not available
Economics Not available Not available 61,100 Not available
Education Not available Not available 24,400
Engineering and Technology 43,700 44,800 40,700 38,000   40,700
English Studies 28,000 31,400   29,200   26,600
Historical & Philosophical Studies 33,700 37,300 28,500 Not available 30,700
Languages 37,100 36,700 29,400 Not available
Law 58,700 56,300   38,100 44,700 41,300
Mathematical Sciences Not available 50,300 Not available 37,200 55,400 49,500
Medicine and Dentistry Not available 42,900 45,300 46,400 47,100
Physical Sciences Not available 37,000 38,400 Not available Not available
Psychology Not available 31,900 39,600 30,100
Social Studies (excluding Economics) Not available Not available Not available 32,300 32,000
Subjects Allied to Medicine (excluding Nursing) Not available 36,300 30,900 34,200 36,300

 

I’ve excluded subject categories not studied at either Oxford or Cambridge (Agriculture & Related Subjects, Combined Studies, Mass Communication and Documentation, Nursing, Veterinary Science). In the table, a blank indicates that the subject isn’t studied at that university.

What is striking is how much of the time the median salary data is simply not available. Out of 18 subject categories in this table, there are 4 for which a full comparison of all the relevant data can be made.  (I’ve highlighted these in blue on the table). Even if you just restrict it to comparing Oxford with Cambridge, you can only do that for 8 out of 18 subject categories.

I’m not entirely sure why this data is missing: it’s not simply that these represent particularly small cohorts. For example, there are 100 Cambridge mathematics students whose earnings were traced. But I take it that the data is excluded because it isn’t considered by the LEO statisticians to be reliable, and I’m not second-guessing their judgement on that.

So I simply can’t tell, based on this data, whether Oxbridge students do overall earn more than comparable students from top London universities. It might still be possible for expert statisticians working with the full data set to decide that. But what my admittedly crude analysis shows is that the LEO data is not much use for potential students deciding which university to study at.

This is true even in the relatively few cases where we do have a complete set of subject/university group data from LEO. The data is still very noisy. Here’s the five-year data for computer science graduates (both sexes) from the 2008/09 and 2009/10 cohorts:

Cambridge Oxford Imperial KCL UCL
Computer Science 2008/09 51,300 43,000 51,800 38,400 43,700
Computer Science 2009/10 46,300 55,800 60,000 40,100 41,500

 

Which of these universities should you go to improve your earning potential? If you were in the 2008/2009 cohort you’d have done better by choosing Cambridge over Imperial: the median salary is slightly less, but you’d probably have saved enough money on three years living expenses in London for it not to matter. In the 2009/10 cohort the median graduate from Imperial would have earned so much more than a graduate from Cambridge that they could have paid off an entire year’s fees with the difference. From the 2008/09 cohort, the median UCL graduate earned £700 a year more than the median Oxford graduate; for the next cohort, it was £14,300 a year less.

These earnings don’t even move in synchronisation between the two cohorts, as you might expect if they reflect the wider economy: three of the universities have higher median salaries in 2009/10 and two lower. And bear in mind that this is all retrospective data: you’re potentially picking your course to start in 2019 or more likely 2020 based on this data. Which cohort is more typical?

All this suggests that the most that LEO data is likely to give you is some very broad generalisations about which subjects and universities are likely to lead to well-paid jobs. As a specific tool for deciding between a subject at comparable universities, it’s completely inadequate. The problem is, it’s only if you dig deeper into the data, in the way I’m doing, that you’re likely to spot that. I suspect that a lot of spuriously precise salary figures are going to be quoted by the government, individual universities and commentators in the future.

One thought on “Do Oxbridge students earn more (and how would we know)?

  1. Figures crashed of course, in the 2008 global financial crash, while study expenses increased.

    Overall, it is a striking tabulation based on your merthods. It also demonstrates that there has to be a much broader methodology for researching this subject and a careful broad peer reviewed analysis of outcomes.

    Like

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