Hiring Freezes & Endowment Hoarding

Some days ago I learnt that a job offer to a promising postdoc I advise evaporated. Not unexpected in these times, but disappointing nevertheless . There are now about 300 Universities with hiring pauses or freezes in place.

For Universities that are tuition driven, this is understandable. For those with large endowments of which a large portion are unrestricted this is puzzling. It is true that about 75% of all US university  endowment funds are invested in equities and these have declined since the start of the pandemic. But, the 3 month treasury rate is, at the time I write this, at 0.22%. Why aren’t they borrowing? More generally, why don’t we see consumption smoothing?

An interesting paper by Brown, Dimmock, Kang, and Weisbenner (2014) documents how University endowments respond to shocks. They write:

Our primary finding is that university endowments respond asymmetrically to contemporaneous positive and negative financial shocks. In response to contempo- raneous positive shocks, endowments tend to leave current payouts unchanged. Such behavior is consistent with endowments following their stated payout policies, which are based on past endowment values and not current returns, in order to smooth payouts (e.g., pay out 5 percent of the past three-year average of endowment values).

However, following contemporaneous negative shocks, endowments actively reduce payout rates. Unlike their response to positive shocks, this behavior is inconsistent with endowments following their standard smoothing rules. This asymmetry in the response to positive and negative shocks is especially strong if we explicitly control for the payout rate that is implied by the universities’ stated payout rules (something we do for a subsample of the endowments for which we have sufficient information to precisely document their payout rules). We also fail to find consistent evidence that universities change endowment payouts to offset shocks to other sources of university revenues. These findings, which we confirm through several robustness checks, suggest that endowments’ behavior differs from that predicted by several normative models of endowment behavior.

They argue that their data supports the idea that Universities are engaged in endowment hoarding, i.e.,  maintenance of the endowment is treated as an end in itself. The Association for American Universities argues that endowment hoarding is a myth, see item 9 at this link.  Their response confirms the 3 year average rule but is silent on the asymmetric response to shocks reported above.

More generally, one might ask what is the purpose of a University endowment? Hansmann (1990) offers an interesting discussion of why a University even has an endowment (other enterprises are run through a mixture of debt and equity).  Tobin (1974) articulated one for modeling purposes which I suspect captures what many have in mind:

The trustees of an endowed institution are the guardians of the future against the claims of the present. Their task is to preserve equity among generations. The trustees of an endowed university … assume the institution to be immortal.

If one takes the principle of intergenerational equity seriously, then, would it not make sense to borrow from a better future into a worse present? Unless, of course, it is expected that the future will be even worse than today.

Effects of a Partially Effective Vaccine

The race to publish COVID-19 related papers is on, and I am already behind. Instead, I will repurpose a paper by Eduard Talamas and myself on networks and infections which is due out in GEB.

It is prompted by the following question: if you are given the option to distribute—without cost to you or anyone else—a perfectly safe but only moderately effective vaccine for a viral infection, should you? That we’ve posed it means the answer must be no or at least maybe not.

Unsurprisingly, it has to do with incentives. When the risk of becoming infected from contact declines, individuals tend to be less circumspect about coming into contact with others. This is risk compensation, first suggested by Charles Adams  in 1879 and popularized by Sam Peltzman in the 1970’s.

Therefore, the introduction of a vaccine has two effects. On the one hand, it reduces the probability that an individual becomes infected upon contact. On the other hand, it decreases individuals’ incentives to take costly measures to avoid contact. If the second effect outweighs the first, there will be an increase in infections upon the introduction of a moderately effective vaccine.

These are statements about infection rates not welfare. Individuals make trade-offs. In this case between the risk of infection and the costs of avoiding it. Therefore, observing that an individual’s infection probability will increase upon introduction of a partially effective vaccine is insufficient to argue against introduction.

In our paper, Eduard and I show that the introduction of a vaccine whose effectiveness falls below some threshold could make everyone worse off, even when each individual is perfectly rational and bears the full cost of becoming infected. If the vaccine is highly effective, this outcome is reversed. This is because risky interactions can be strategic complements. An individual’s optimal amount of risky interactions can be increasing in the amount of risky interactions that others take.

To illustrate, call two individuals that engage in risky interactions partners. Every risky interaction that Ann’s partner Bob has with Chloe affects Ann’s incentives to have risky interactions with Chloe in two countervailing ways. It increases Chloe’s infection probability. But it also increases the probability that Ann is infected conditional on Chloe being infected—because if Chloe is infected, chances are that Ann’s partner Bob is also infected. Given that a risky interaction between Ann and Chloe only increases the probability that Ann becomes infected when Chloe is infected and Ann is not, the combination of these effects can lead to an increase in Ann’s incentives to engage with Chloe and her partners when Bob engages with Chloe.

One might ask, given the huge trove of papers on epidemiological models, this effect must have been identified before and discussed? No, or at least not as far as we could tell. This is because we depart from from a standard feature of these models. We allow agents to strategically choose their partners— instead of only allowing them to choose the number of partners, and then having matches occur uniformly at random.