Framing the problem
The question on my mind today is about best case economic outcomes. How does a country get through the Covid-19 pandemic with the least bad economic outcome? And in thinking about that question, I want to do three things.
- I want to talk about this utilizing as little ‘science’ as possible. Because I am not a scientist, avoiding the epidemiological models as much as possible makes sense.
- I want to flag policy response assumptions because this is as much an economic policy question as it is a macro question.
- I want to look at optimal outcomes and work backwards. And that means using a hypothetical best case economic outcome in a pandemic as a baseline rather than thinking of best cases in this specific instance.
Making a little room for science
The frame here, then, is, with those three parameters in place: what is the least economic disruption one could achieve in a pandemic, any pandemic? And I think the answer is: a scenario in which virus carriers are identified at the first possible instance and isolated while everyone else remains largely unaffected.
That’s not an entirely satisfactory framing, of course, because it doesn’t take into consideration how easily transmissible the virus is, how lethal it is, what the best social or health policy responses are and so on. But, more importantly, it assumes we can go into a containment strategy indefinitely, meaning so-called ‘herd immunity’ through infection isn’t the eventual best case outcome.
So, to make a little room for science, let me say that the end goal is not herd immunity through infection. That’s a scenario in which lots of people die. And an underlying assumption I have been making is that ‘loss aversion’ would drive policy responses. So, the goal is to keep the virus in check until a vaccine is developed. Is this even feasible? I don’t know. But it’s certainly what every nation on earth is hoping to achieve right now. So, it is a good baseline assumption.
My pandemic utopia
So, in my utopia, the goal is to minimize economic disruption, and to limit a loss of output and income. And to do so, you would have to maintain free movement in a world of globalization and international travel. Otherwise, you get all sorts of disruption. By definition, that means, massive testing then. if you want life to continue as normal as possible, you have to basically test everyone and you have to test them repeatedly at regular intervals until a vaccine is developed.
If anyone tests positive for the disease, they have to be quarantined and monitored. Those they have come into contact with recently will also need to go into self-isolation or quarantine. And then, repeated testing will ascertain how long it takes until they are not infectious, something that will inform the length of future quarantines and self-isolation. Otherwise, everyone can go on as usual, except that they must be tested at regular intervals, how often depending on the infectiousness of the disease.
The science from that testing will determine what minimal level of economic disruption makes sense. When you quarantine visitors from elsewhere, for how long do you isolate them? Do you erect any checkpoints inside economic areas like at state, county or province borders in nations or at national borders in the Schengen area? I don’t want to get into any of that. But, the more infectious the disease, the more disruptive containment measures will have to be.
As a baseline though, in this utopia, you will want governments to have prepared in advance for a pandemic and to be ready to respond to it by ramping up testing so that everyone can be tested repeatedly, not just anyone who wants a test. That would be the gold standard. And so, just going through this thought process outlines how important testing is and how disruptive a lack of testing always will be. If you don’t have the tests, you can’t know who has the virus. And if you don’t know who has the virus, you can’t operate an effective containment strategy without inhibiting freedom of movement.
So, the first conclusion is that a pandemic utopia cannot exist without adequate testing.
The inadequate testing utopia
Let’s say you live in Pandemic Utopia-land, where there’s adequate testing. But many other people don’t. What do you do then? You test any incoming visitors from outside Utopia-land. And then you quarantine them anyway for a set period of time that depends on how infectious the disease is and how long your own testing has already ascertained it takes to become non-infectious.
But what if your own testing is inadequate i.e. you can’t test everyone, only those who want or need a test? Then, unless you rely on herd immunity, you have to start to restrict freedom of movement.
Four things are clear to me, one from the science, two from the math(s), and one from the policy response.
First, the science says that an infectious disease will multiply out of control unless you identify carriers and isolate them. So to the degree you have substantial doubts about who a carrier is, you are forced to restrict the movement of everyone until you can either ascertain who is a carrier through testing by waiting out the incubation period or by waiting out both the incubation period and the period during which asymptomatic individuals are no longer infectious.
Second, from the science, it’s clear that, if the R0 of a disease is greater than 1, it will multiply in an uncontrolled environment. That means that, if a disease is infectious enough that one person can infect more than one person on average in a normal environment, you have to restrict movement. Otherwise, the disease will spread exponentially and rapidly. That’s simple math actually. You don’t even need to know the science to make that determination.
Third, also from the numbers, the sooner you shut things down, the less the virus will have already spread before shutdown. If the virus has an R0 of greater than one, it means that every second, every hour, every day, every week you delay in restricting movement is a second, hour, day and week the virus has to spread exponentially. And that means greater disruption and also greater death.
Fourth, psychology tells you that people will not self-regulate enough in a non-perfect testing environment to prevent the disease from spreading wildly. Every instance I have seen, from Miami beaches to Nashville bars to Swedish streets tells you that policy makers must, at a minimum, mandate stay-at-home orders to get compliance that will limit the disease spread.
So, the second conclusion is that in a non-Utopian testing environment, you must mandate movement restriction and do it as soon as possible. The earlier you do it, the less likelihood you have for exponential contagion. And, as a result, the sooner you should be able to lift restrictions in a non-Utopian testing environment without risking a second wave of exponential infection.
Hanging over all of this are two things about policy. One is that policy is almost always reactive and not pro-active. The second is that policy is usually also geared toward ‘loss aversion’ and not maximizing gain.
In terms of the reactive nature of policy, it means that almost invariably, you’re not going to have a testing Utopia. Instead you will have varying degrees of inadequate testing. And the inadequacy of the testing plus the infectiousness of the disease will determine how much the pathogen spreads before a lockdown occurs.
At the same time, countries that are more prone to reactive responses on preparation are likely to be the same ones more prone to waiting to lock down. So, that’s where you get worst case outcomes in terms of infection and death, particularly at international travel hubs like New York City, Seattle or Los Angeles. This is why we should expect the US outbreak to be worse than most any other country, because the testing has been inadequate and the lockdown measures were late.
In terms of loss aversion, it guides policy toward lockdown, even draconian lockdowns as we saw in China because the fear of death, of loss, drives policy at that juncture. The fear of loss overwhelms all other factors in making that decision. And that’s why I predicted lockdowns would come everywhere, not just China.
But once a lockdown is in place, the economic outcomes are severe. In the US, for example, we reported another 6.6 million unemployment claims as I was writing this. That’s 16.6 million claims over three weeks. The loss aversion has now turned to income deprivation and economic collapse. The fear of these losses is now overwhelming, not just in the US but globally. And it will eventually overwhelm every other decision-making factor. That tells you that lockdowns are very likely to be undone before there is a reasonable assurance testing is adequate and before we are prepared for a large second wave of infections.
I think a large second wave of infections is almost inevitable now. The economic collapse associated with these lockdowns has become so acute that it has become the single most important driver in policy making in industrialized countries.
In the most short-sighted countries (like the US), loss aversion will drive out all other considerations. And the likelihood of lifting lockdowns before measures are in place to control a second wave is high. This means greater loss of life and greater economic disruption, in my view. And so, I tend to look at worst case economic outcomes for the US as closer to baseline than best case ones.
I am going to end there. Let’s hope I am wrong. The key assumption that could prove me wrong is the one about loss aversion driving policy and crowding out all other decisions. Maybe US policy makers are more forward-looking than I assume. We will find out in due course.