What does the COVID-19 epidemic teach us about the role of government?

by
Eric Kramer
My articles My booksMy videos
Follow on:

What lessons should we draw about the role of government from the COVID-19 epidemic?  I want to address this question in a few posts.  I’m going to start by examining a blog post by the libertarian philosopher Jason Brennan.  Brennan makes the following claims:

1. Many medical journals published misleading papers based on bad statistical analysis and incomplete data; in particular the case fatality rate may have been overestimated because the total number of people infected was not (and still is not) known
2. Many of the models used by researchers are “quite poor”
3. Intellectual standards are low in medical research, the flawed papers accepted by medical journals would have been immediately rejected at economics journals
4. Government has acted on this bad research and closed down the economy, inflicting severe harm on many people for unclear gains
5. Government is responsible for the fact that better data was not available, because government failed to increase testing capacity and failed to undertake the types of studies that would have enabled researchers to estimate the key parameters needed for rational policymaking (such as the case fatality rate)
6. Government decisions that are not made competently and in good faith are “presumed to lack authority (there is no obligation to obey it) and legitimacy (there is no moral permission to enforce it).”
7. Because governments have acted on bad data and bad models in implementing the shutdown, government actions lack authority and legitimacy.
8. The fact that government had to act quickly on the basis of bad information is irrelevant, or at least not dispostive.

I want to respond to these claims, especially his normative claims (6, 7, and 8), but I start with his criticism of medical researchers.

First, I believe it has been well known since early in the epidemic that crude case fatality rates are biased up because we do not know the true prevalence of the disease due to inadequate testing.  It was also known that crude case fatality rates early in the epidemic are biased down because there are people who are currently infected but have yet not died.  I believe that many researchers tried to deal with these statistical issues as well as many, many others.  I believe I have seen papers that published a range of estimates for the number of deaths based on different assumptions about these biases, although I am not going to go back and look for them.  Of course, I am sure that some bad papers were published.  This happens even when researchers are not facing a public health emergency.  But Brennan does not show that most papers published were bad.  In fact, he does not cite a single paper that used naive statistical methods.

Second, his claim that many of the models used are “quite poor” is unsubstantiated.  Again, I am sure that people made debatable modeling choices, and some people no doubt made errors in their analysis or misleading claims about their results.  Brennan does not provide any evidence that this was common, or that government policy depended on this.

Brennan apparently believes that intellectual standards are low in medical journals, at least relative to economics journals.  Again, he offers no evidence.  Of course, no doubt there are problems in some fields of medical research and epidemiology (nutrition studies are arguably pretty close to worthless, for example).  Many medical researchers understand this and are trying to correct it.  And it is also true that there are problems with empirical work in economics.  See Gelman here; many, many other citations could be given.  I note that the IHME model, which has been criticized for its methods and seems to be highly inaccurate in its predictions, was apparently developed by economists.  The only specific methodological flaw that Brennan points to is a failure to account for heterogeneity in R0.  But economists estimate models without heterogeneity in R0.  See here.  The use of simplifying assumptions and imperfect statistical tools is inevitable, especially under the severe time constrains imposed by a looming epidemic.  Empirical work is hard, researchers aren’t super human.

As an economist, I would love to believe that economists are geniuses with high intellectual standards, perfect models, and excellent statistical techniques.  I think we do have our professional strengths.  Nonetheless, Brennan’s attack on medical/epidemiological research and glorification of economics seems to me to be unwarranted and unhelpful.

Moving on . . .

Brennan seems to believe that bad research exaggerating the danger from COVID-19 led governments to overreact and implement excessively restrictive policies.  Again, he presents no evidence for this.  Many people believe that governments under-reacted, at least in the sense that they took too long to respond to the epidemic, and that this allowed the disease to spread to the point that standard test/trace/isolate methods were ineffective.  

What about Brennan’s moral claims?  He acknowledges that “in principle, governments can restrict our freedom to stop the spread of disease.”  But then he adds that “appealing to abstract principles is not enough to justify their actions. We need to know whether they made these particular decisions competently and in good faith, on the basis of good information.”

Here is an alternative view (one that, incidentally, I believe most economists would subscribe to):  

Ideally, governments should act on the basis of the available information.  This information might suggest waiting and collecting more information, or it might suggest acting on the basis of information known to be limited and highly imperfect.  There is no requirement to act on the basis of “good information”, especially in an emergency.  Government should act on the information it has.

What happens when government does not act rationally on the basis of the available information, or when it does not act in good faith?  The short answer is, we should focus on the merits of the policy the government adopts, not on the imperfect decisionmaking process.  If the government adopts a good policy for bad reasons, we should support it.  For example, suppose that government officials naively focused on the crude case fatality rate to make decisions about COVID-19, without making adjustments for the fact that many cases of infection and many deaths have not been reported.  That would be poor decision making, but if those errors happen to cancel out, it could be that government made the right decision by accident.  In this case, the policy should remain in force.  On the other hand, if the government adopts a bad policy for good reasons, we should try to repeal or improve it.

Brennan rejects the argument that government was justified in acting on the basis of imperfect information in an emergency.  Here are his responses and my comments:

First, governments could have collected better data earlier, before they shut the world down.

Sure, but if the shutdown is justified, shouldn’t we keep it in place?  Blaming the government may be fun, but is it constructive?

Second, few governments are trying to collect good data now. It’s one thing to shut down in an abundance of caution, but they should subsequently do mass, randomized testing for antibodies so we can determine the real infection fatality rate. (That is, collect the right data the right way.) Why isn’t this being done en masse?

I believe almost all public health experts and economists agree with this, and that the government is trying to organize this kind of testing.  But until this is done, there is no reason to change policy unless a different policy is justified based on the data we have on hand.  Again, blaming the government is fun, but is it constructive?

Third, the argument that we are in the midst of a potential disaster and so had to act out of an abundance of precaution relied on things like the WHO estimates and other early models and estimates, all of which relied on the wrong kind of data (testing current viral shedding) collected the wrong way (mostly testing people who present themselves as sick). As I’ve been saying, none of you would get a paper published in a third-rate journal with that kind of data, and if I presented a paper using it, you would tear me apart.

We need to decide what policy to support on the basis of the studies that are currently available, recognizing to the extent possible their biases and limitations.  The fact (if it is a fact) that some papers would not have been published in an econ journal is completely irrelevant.  Criticizing may be fun . . .

Fourth, whatever plausibility this argument may have, what about the contrary argument that the bigger the stakes, the better the information you must have?

I am unfamiliar with this argument, and it seems obviously wrong.  What does seem to be true is that, all else equal, the higher the stakes involved in a decision, the more effort you should expend collecting information.  But this does not show that decisions should be delayed to collect additional information, it does not show that “better information” is required when stakes are high, and it certainly does not show that, in the case at hand, the government should have delayed acting in the face of a potentially severe epidemic.