by Orlando Roncesvalles

The virus has us all riveted to our seats, watching the news, helplessly wondering what will happen next. Will we be “shut in” forcibly, as in China? Will we be more like Italy and Spain with draconian measures to keep almost all at home, not so much by force but by community efforts? Can we have something less drastic like Korea, where there is no lockdown but massive testing allows for infected people to be isolated early in the course of the epidemic. The answers are not easily found.

A thought experiment may point to how we might go about finding a reasonable approach. Suppose there were only two persons in an economy, and we cannot tell who is infected. But for sure, one of them is sick. If both go out and work, all get infected. Both die. And we have no more economy. This is the scenario if we did nothing at all to confront the virus.

If we don’t test, we can lockdown all at home, as we do now for Luzon. That effectively shuts down the economy. But at least the economy revives when a vaccine or cure is found. This means that lockdown is better than doing nothing. Lockdown at least keeps half the population alive while we wait for a vaccine or cure. Doing nothing is something like suicide, irreversible, or worse, a form of homicide.

For the duration of the virus problem, at least two policies have the same result of killing the economy. Again, we could achieve this by doing nothing at all, or by an absolute lockdown. However, the dichotomy here applies to the differing situations of Luzon and the rest of the country. Luzon is effectively on lockdown. The rest is still deciding what to do, which to some extent amounts to doing nothing (not yet anyway).

But doing nothing is not in the cards. We are neither that callous nor short-sighted, though perhaps early in the emergence of the disease there were officials who thought doing nothing was okay.

What else can be done?

If we test, we limit the economic damage to half. The healthy one goes to work; the sick stays at home.

If we’re unable or too poor to test, we could also “just take turns.” On odd days, one works; on even days, the other works. This also limits the damage to half of the economy.

This shows that the advantage of testing is not so large if somehow we can find a way to “take turns.” This requires a great deal of social cohesion because “taking turns” is pretty much the same as the much advised “social distancing” being promoted on the assumption that all are infected but asymptomatic. Still, no testing still means that half the economy is lost. What we really want is to limit the damage to much less.

And social distancing seems better than lockdown because the latter gives us a sense of helplessness, while the former at least calls upon us to go into a cooperative bayanihan spirit.

Admittedly, the above discussion is an extreme way of contrasting the various policies we might adopt. Still, doing nothing is “suicide”; the other — lockdown or social distancing — is “half a loaf.” Having said all that, can we get a better handle at “predicting” the near future?

Background facts on the epidemic
We summarize now what we think we know in terms of science and numbers. The key parameters are the rate of infection (called R) and the fatality rate (call this F).

R is defined as the average number of others that will be contaminated by an infected person. The important thing is that there is an initial number for R, known as Ro, which is the rate of infection that does not yet take into account policy or human interventions that would reduce R. Another important consideration is that so long as R>1, an epidemic outbreak will continue because the numbers of infected persons will continue to increase. Experts seem to think that Ro is 2.3; the actual R tends to fall, even if humans do nothing. This is just a mathematical thing. Once all are infected, R cannot go any higher. Any activity that breaks the infection chain, such as physical or social distancing, or a vaccine or cure, will cause R to decline. When R falls below 1, then the disease will sooner or later “peter out.”

F is the deadliness of the virus. The fatality rate is the probability that a person will die if he is infected. Various numbers have been given. WHO says it is 3.4%. In other words, an infected person has a 3.4% chance of dying from the virus (as opposed to other causes of death), though we also know that the number is an average. Young people have a lower F; so do women; so do healthier people. We might also think that F is a constant number. It is not. The experts say that F depends on whether the health care system is able to take care of the sick, through ventilators, intensive care, etc. F is higher for countries with fewer hospital beds (the Philippines ranks low in this regard, with one bed per thousamd of population, whereas advanced countries have something like 2-3 beds per thousand).

The important thing about F is that if we can “flatten the curve,” we reduce F. What does flattening the curve mean? The curve is the progression over time of infections. This depends on Ro and human interventions to reduce R. Thus, while F and R are different numbers, efforts to contain R also reduce F.

Two kinds of economic shocks
As an economist, I ask myself what economics has to offer to help solve the problem of the virus.

There is by now a consensus among economists that the virus is sufficiently problematic that they predict a major global economic recession. By historical standards, magnitudes of slowdown in global economic activity seen in 2008 (the Great Recession) seem to be applicable to the virus. Still, comparisons with the 1930s Great Depression, which was more severe, are not so far-fetched.

In the short run, economies are subject to supply and demand shocks.

A supply shock is something that disrupts the ability of firms to produce goods and services. The important thing about supply shocks is that there is little that public policy can do about it unless it was brought about by bad public policies to begin with. A freezing up of the banking system, which almost happened in 2008, is a supply shock that was partly solved by improvements in bank regulation. The supply shock of the virus arises when people get sick and can’t work, or if they’re on lockdown, or if social distancing reduces the productivity of workers. No one knows how large this supply shock is. In the mental experiment above, even if we did do something, the supply shock is a negative 50% as total output or GDP falls by half. The WHO estimate of F at 3.4% helps to set an upper bound on the size of the supply shock. If world population is lower by 3.4%, that’s a supply shock of that magnitude; but this is perhaps too high because not all are likely to be infected. But on the other hand, the supply shock can be higher because modern economies are specialized, and supply chains cut across several areas and countries affected by the virus. I would guess a supply shock of 5% to 7%.

But that’s not all. There is a demand shock that emerges when households recognize that their incomes are lower (through no fault of theirs) or when firms decide to invest less because they predict a bleaker economic outlook in the near future. The supply shock actually starts the demand shock going, but this is magnified by attempts of households to limit consumption in relation to income. Keynesian economists like to think of a multiplier on the demand side of 1.5 to 2. This means a fall in global output of 7% to 15% if governments did nothing on the economic front.

These shocks are mitigated by fiscal and monetary policies
The lessons from the Great Depression and the Great Recession are basically Keynesian. Governments have a duty to manage demand shocks, even if they can’t do much about supply shocks. A best-case scenario suggests that the demand shock is totally “absorbed.” The most common suggestions are “helicopter money,” or outright transfers to affected households. This is a combination of monetary and fiscal policies, since money has to be printed and the delivery of the money is through negative taxes, which typically require that governments go into debt. Under such a best case, the only thing that happens is the supply shock. That still means a global recession or decline in world output of 5% to 7%. This is, to emphasize, a best-guess scenario.

Guarded optimism
Forecasting isn’t a duty of economists, but we seem to demand that they do anyway.

The easy way out is to pick a guess in between the worst and best cases. Governments impose a combination of testing, isolation, and lockdowns that reduce the supply shocks. They also enact fiscal and monetary policies that negate much of the demand shock. I would venture a guardedly optimistic forecast of global recession where output declines by 10%. Individual country experience will depend on how governments manage their policy responses to the demand shock.

Key lessons
What can be concluded? The cases of Korea and Singapore suggest that preparedness is important. This can limit the supply shocks in their economies, which nonetheless will be affected by what happens to their trading partners. This suggests that globalization has inherent risks that cannot be avoided when there are pandemics.

Regardless of how prepared a country is, social interventions matter. In the case of the virus, optimism is a public bad. It is better that people assume the worst (such as all are infected, if they’re not tested) and thereby voluntarily isolate themselves from each other. We know from the mental experiment that the worst case is when the infection rate is maintained by ignorance, and when this triggers an unanticipated demand on health care systems that increases the fatality rate.

In the interim, the deus ex machina is innovation. Malthus wrongly predicted doom because he did not foresee improvements in agricultural productivity. We can easily also predict doom if a vaccine or cure is not found; but we can hope that scientific breakthroughs would save the proverbial day. ***