Universities are characterised, compared with other tertiary education providers, as having a significant amount of resources dedicated to research activities. Typically, an elite university will direct 40-50% of its academic resources towards research. This is despite the fact that university research is cash-flow negative even after all government grants and commercial revenue are taken into account. As a rule, an optimistic expectation would be that for every two dollars spent on research you may get one dollar back as either grants or revenue. Typically, it is closer to 3:1. The financial viability of universities rests on its ability to generate teaching revenue. Teaching undergraduates and postgraduate coursework students. Curiously, a strong link between the university research undertaken and the courses being taught is not necessary to ensure strong student enrolments and financial viability. The reason for this is the key role research plays in generating strong reputational benefits for the university.
Reputational benefits gained through elite research activities has two important benefits for universities.
The first is the benefit of lekking behaviour – in humans we see this behaviour in the general rule that people like being around successful people. This is why social A-lists exist. More generally as animal behaviour, a lek is a gathering of individuals for the purposes of competitive display – competitive signalling. For universities, A-list researchers attract other high quality researchers and also crucially high quality teachers. Why is this important for attracting high quality teachers? Academics themselves are generally seen to be sensitive to reputational influences of their peer group. High quality teachers will be hesitant to join to a university who’s reputation is ambiguous (uncertainty as to rank). The solution is to have an unambiguous reputational signal. However, the signal needs to overcome the problems of asymmetric information associated with the observation (‘measurement’) of quality. It is for this reason that research reputation trumps teaching reputation. Research reputation is a less ambiguous signal as a result of the strength of external validation – active peer review in both academic and public domains (media). Teaching reputation is harder to validate outside the university in which it occurs, leading to the problem of asymmetric information.
The second is associated with the idea of universities being a ‘club good’. Club goods are artificially scarce goods that are excludable but non-rivalrous, giving rise to positive network externalities. For club goods with network externalities linked with social prestige, direct advertising to boost reputation can lead to the opposite effect. As Rory Sutherland noted in the Forward of the 2014 Behavioral Economics Guide :
“In fact, the idea that advertising is always persuasive is disproved by the fact that in many categories, it acts as a discouragement. No London club (or Ivy League University) can advertise successfully, as prospective buyers would take that as a sign that the club or university has more vacancies than applicants – and it is assumed that any club worth joining is oversubscribed already.”
And here lies the problem for universities. As a ‘club good’ with ‘social network externalities’, being able to maintain the ‘belief’ of excludability is paramount. Trying to boost reputation by directly advertising to students and focusing on teaching quality cuts against the core ‘belief’ of excludability. The only alternative is to advertise quality through a signal that doesn’t imply vacancy. Consequently, universities signal reputational quality through ‘elite’ research.
The idea that universities are economic ‘club goods’ with positive social network externalities requiring a belief in excludability leads to another key policy implication. Universities will continue to signal excludability through entrance score cut-offs (such as the Australian university ATAR scores). Any attempt by universities to increase enrolments by loosening cut-off requirements will put the value of these network externalities at risk. Without this signalling, the benefits of positive social network externalities will cease to exist and consequently the organisation’s financial viability. This is possibly the key reason behind the failure of the vocational education TAFE system in Australia. The uncapping of student places in vocational education lead to the loss of the key social belief of excludability. As a result, the strong growth in the numbers of students entering universities over the last 5 years has been at the expense of the vocational educational institutions. Importantly, the human capital benefits of going to a good university are more likely to be associated the positive social network externalities of attending an institution with like-minded individuals than the actual skills or knowledge being taught.
The impact of ‘student peer effects’ on educational outcomes is large. Research into the key drivers of academic performance at Australian schools suggests that around 40% of the difference in a child’s academic performance is due to the nature and composition of the student cohort they go to school with. This effect is independent of the quality of teaching or institutional governance (public or private). Most of the remaining 60% influencing academic ability is dependent on the nature of the child’s family. The heritability of ability and socio-economic factors such as wealth and low risk environments that support learning. Private schools perform better than public schools principally because they select the best students. This selection process in turn creates the academic positive network externality of student peer effects. See the Grattan Institute’s report ‘The myth of markets in school education’. Successful private schools also create significant social network externalities associated with prestige (reputation).
Finally, this leads to a discussion of Massive Open Online Courses (MOOCs). Following from above, MOOCs which don’t generate positive social network externalities by creating a belief of excludability, either through institutional cost barriers of elite research or through student peer effects, will not be able to charge a price premium for quality. This leads to two possible outcomes: a) for-profit MOOCs providing commoditized credentialism based on minimum quality requirements (we see this happening with for-profit schools in the USA), or b) MOOCs evolving as the online interactive equivalent of university text books provided free or at a nominal cost.