Regulators are supposed to protect us from making foolish decisions. When doing so, they often believe the public interest is served by promoting “white lies’, that is, false statements that are intended to be for our own good. If fact, the short run benefits of white lies are almost always outweighed by their much bigger long run costs.
1. Early in the pandemic, experts said there was no reason for a travel ban. Presumably they were trying to prevent panic, or xenophobia, or something. But in retrospect, an international travel ban would have been helpful if instituted back in January. Indeed travel bans largely explain why some countries have mostly avoided Covid-19, although in fairness other policies such as masks and test/trace/isolate also played a big role.
2. Early in the pandemic, experts suggested that masks don’t help average people. Even then they must have known that was wrong—why else would doctors wear masks? Their white lies seem to have been motivated by a feeling that masks might make people feel overly self confident (which might be true), as well as the fear that a mask shortage might deprive health care workers of masks. Unfortunately, these “white lies” had extremely negative long run consequences.
3. More recently, Dr. Fauci suggested that it was important for the FDA to spend several weeks evaluating the Pfizer trial data before making a decision. According to experts cited by Tyler Cowen, that also seems to have been inaccurate. Alex Tabarrok suggests that the motivation seems to have been to make the public feel like the FDA was being careful:
I am getting very angry at people like Anthony Fauci who say that FDA delay is necessary or useful to alleviate vaccine hesitancy.
Fauci told Fox News that the FDA “really scrutinises the data very carefully to guarantee to the American public that this is a safe and efficacious vaccine. I think if we did any less, we would add to the already existing hesitancy on the part of many people because … they’re concerned that we went too quickly.”
The WSJ says much the same thing just with a slightly different flavor:
…this regulatory rigmarole is essentially a placebo to reassure the public it will be safe to get inoculated.
The ‘we must delay to allay’ argument is deadly and wrong.
Tabarrok points out that the effect could easily go in the opposite direction, making the public even more wary of vaccines, and Matt Yglesias is rightly skeptical of public health officials becoming amateur social psychologists:
The internet is full of conspiracy theories about almost everything. Most of the theories are unsubstantiated. Unfortunately, if our experts believe that white lies are frequently in the public interest, this will gradually erode confidence in expert opinion, breeding even more conspiracy theories.
As an analogy, deposit insurance is often useful in the midst of a financial crisis. But in the long run, the existence of deposit insurance encourages banks to take excessive risks, and this makes financial crises more likely in the long run.
Tabarrok and Yglesias are right that Dr. Fauci should not try to be an amateur psychologist. And this is true for reasons even beyond those that they cite—the fact that he’s not very good at it. Even if Fauci were an expert in knowing just how to manipulate public opinion at a point in time, the long run effect of his action would to reduce public trust in experts, with consequences much greater than any short run benefit.
When it comes to regulators, there are no “white lies”.
READER COMMENTS
Russ Abbott
Dec 5 2020 at 2:36pm
You’ve often said you opposed deposit insurance. I disagree.
1) Deposit insurance doesn’t insure banks. So it doesn’t encourage them to take more risks.
2) If insurance encourages people to take risks, do you also object to fire insurance, medical insurance, etc.? Insurance protects people from unusual negative events. It seems to me to be a good thing for people to find ways of evening out their risks. Why object to that?
Scott Sumner
Dec 5 2020 at 2:57pm
The fact that FDIC insures depositors is completely beside the point. It makes depositors equally willing to deposit money in safe banks and highly risky banks. In a free market, highly risky banks would have to pay a higher interest rate on deposits in order to attract funds.
You are correct that insurance often makes sense, and I have no objection to private deposit insurance. In general, private (unregulated) insurance companies charge higher rates to people that engage in riskier behavior. FDIC does not do that—which is precisely the problem.
Jose Pablo
Dec 6 2020 at 8:14pm
Fire insurance, car insurance and medical insurance (at least for a while and maybe again in the near future) are also mandatory and heavily regulated.
The main differences with the deposit insurance scheme are (a) that is not the direct beneficiary the one paying for the insurance and (b) that there is not a competitive market for deposit insurance.
Both differences mean that the price discovery mechanism of the deposit insurance are, very likely, inefficient. But they provide the same “wrong incentive” that the other insurances. As a matter of fact, back in March the images of “assets on fire” (yachts, rental cars …) were unusually widespread.
Scott Sumner
Dec 7 2020 at 3:12pm
I agree that the regulation of insurance often creates a moral hazard problem.
Garrett M
Dec 5 2020 at 3:00pm
Deposit insurance insures depositors, not banks. You’re correct about that. But that means depositors don’t evaluate the creditworthiness of banks, so banks don’t compete for deposits based on that. Instead they compete on yield and services. This makes the entire banking industry take on more risk than they would without deposit insurance.
Rajat
Dec 5 2020 at 5:21pm
Thinking of ‘white lies’ as being false statements intended for our own good, so many things governments say and do fall into this category that I wonder if the harm from doing so is very culture-specific. In Victoria, during our second wave, the government overnight simply imposed a mask mandate outside the home (eg outdoors, even in parks, etc) and an 8pm-5am curfew. In arguing these measures were necessary, the government gave no evidence that either of them would ‘work’ in any direct way. Rather, it seemed that the outdoor mask mandate was about instilling a new norm about mask-wearing in confined spaces and reducing ambiguity for enforcement purposes, and the curfew was about making enforcement of no at-home socialising easier to police. Nevertheless, despite grumbling, most people complied with both measures because of steep fines. Is a government that sanitises its reasons for imposing heavy-handed measures engaged in telling white lies, or are there acceptable gradations of white lies?
More generally, the whole ‘nudge’ philosophy is based on manipulating people’s choices for their own long term good. Do you have a view on that?
And moving beyond governments and regulators, many scientists involved in public discourse engage in these manipulations all the time. For example, ‘there is no safe level of alcohol consumption’, all the talk of climate change ‘tipping points’ by which time we must act or it’s all over (and yet these points keep getting deferred), that reducing household waste does anything meaningful for the environment. Etc, etc.
Scott Sumner
Dec 5 2020 at 8:23pm
I believe all white lies by experts and top officials are harmful, at least any lie on a policy question. (Obviously I don’t mind if Trump says Queen Elizabeth’s dress looks nice.)
“Nudge” is a different question. I have no objection with firms making signing up for pensions the default option, and having people opt if they choose.
The harm I refer to doesn’t come from the paternalism, it comes from the dishonesty, and the way that lying corrodes trust in experts.
BC
Dec 5 2020 at 8:30pm
“many scientists involved in public discourse engage in these manipulations all the time.”
Yes, they are all examples of “white lies” that have eroded trust in experts. Public policy combines facts with value judgements. Experts have expertise in facts, but their value judgements deserve no more weight than anyone else’s. Unfortunately, too many scientists (and other experts) involved in public discourse try to “nudge” policy in the direction favored by their own values by telling “white lies” about the scientific facts. Once a scientist earns a reputation for “shading” his factual claims to nudge the public towards particular policy outcomes, the public becomes skeptical of that scientist’s factual claims. When too many scientists engage in such nudging, scientists as a group lose credibility. The problem is made even worse when people assert that, “We need to follow The Science,” when they really mean that we need to favor their particular value judgements.
One can retain one’s credibility as an expert by decoupling factual questions from value judgements or one can try to use one’s status as an expert to preference one’s value judgements over those of others. But, one can’t do both, at least not in the long term.
Alan Goldhammer
Dec 5 2020 at 7:38pm
Fauci, Tyler and Alex are reading things into the FDA actions that are not there. FDA is simply doing the job they are paid to do. Reviewers worked over the Thanksgiving holiday to analyze data and prepare the briefing materials for the upcoming Advisory Committee meetings on both mRNA vaccines. FDA made the right call to require a full two months worth of safety data on these vaccines. This is a new vaccine technology that was first in humans only a few months ago. Even the two developers of the Pfizer/BioNTech vaccine (Turkish-Germans) said this was the correct approach. They were recently interviewed by Kara Swisher and said that things were going well in terms of the regulatory reviews.
If Fauci should not play a social psychologist, than economists should not either. The vaccines will be approved and get rolled out. Don’t underestimate the manufacturing and logistics difficulties here. Making does for a 40K clinical trial and far different from scaling up to produce tens of millions of doses a month and making sure that each does is manufactured to exacting specifications. mRNA is a fragile molecule and there is a lot that can go wrong if system controls are not firmly in place.
All this criticism is unwarranted and IMO a waste of time.
Scott Sumner
Dec 5 2020 at 8:25pm
The data can be reviewed in 48 hours. People will die because of the sluggish approval process.
Alan Goldhammer
Dec 6 2020 at 9:29am
Scott – you are just wrong about this. The data submissions contain both safety and efficacy data and are not trivial to review. In addition the manufacturing process has to be looked at. There is a report in the paper today that the initial lots of vaccine promised will be smaller than originally reported. I’ve not seen any further information on what the choke point is. Both companies have been sourcing raw materials for scale ups for some time now and as I noted in the original post, there are bound to be difficulties in manufacturing that will disqualify certain lots from distribution. This, and not the FDA review process, it what will dictate how many people get immunized and when. As one whose career was spent in this area, I’m skeptical that the promised amounts of vaccine will be delivered according to the timelines. I hope to be proven wrong.
Jon Murphy
Dec 6 2020 at 10:54am
Isn’t it odd that scientific journals and authors can peer-review these same studies in less than 48 hours, publish them in 72, but the government regulators (relying on the accuracy of these reports) take a month to review?
In other words, I wonder how you can defend the accuracy of the papers you report on which have review processes far less than 48 hours while at the same time saying that decisions based on those very reports “are not trivial to review.”
Scott Sumner
Dec 6 2020 at 3:28pm
I find this claim from Tyler’s blog post To be far more persuasive than your claim:
“As a Johns Hopkins scientist who has conducted more than 100 clinical studies and reviewed thousands more from the scientific community at large, I can assure you that the agency’s review can be done within 24 to 48 hours without cutting any corners. They just need to work harder.”
I’ve looked at many statistical studies, and can’t imagine why it would take more than 48 hours. They are not doing the study, just reviewing the data analysis.
As for manufacturing, they should have been evaluating that weeks ago, when it was clear the trial was almost over. There’s no sense of urgency in the government.
Max More
Dec 6 2020 at 9:43pm
WHY is efficacy data required? That was not the case until 1962. In that year, the Harris-Kefauver amendment greatly added to the power of the FDA. And added an increasingly large burden in terms of the cost and time to get drugs approved. It’s almost as if you hadn’t read Milton Friedman or other economists on this! The FDA is far too powerful. Strip it back to pre-1962 levels, for a start. Require it to accept drug approvals by agencies in other civilized countries (such as the UK which approved COVID-19 vaccines more quickly). Preferable, abolish this death-dealing agency. Let pharmaceutical companies balance profit seeking with fear of class-action lawsuits. FDA bureaucrats have nothing to gain from speeding up approval.
Jon Murphy
Dec 5 2020 at 9:30pm
This is the very problem of expert failure. When people want “the experts” to guide policy, then they are necessarily asking “the experts” to be amateur psychologists (and economists, educators, transporters, politicians, sociologists, theologians, etc etc etc). “The experts” must substitute their own amateur judgements on these matters and multitudes more.
E. Harding
Dec 5 2020 at 10:20pm
Ironically, Western experts more than a hundred years ago knew both travel bans and masks worked when fighting pandemics (e.g., when advising the Chinese government during the 1911 Manchurian plague). A whole boatload of knowledge that the West taught China then was completely forgotten in the West over the following century, but was remembered in China.
Michael S.
Dec 6 2020 at 6:33am
“Regulators are supposed to protect us from making foolish decisions.”
Let’s not buy into this framing. Regulation, insofar it’s any different from legislation, is a return to the idea of a (paternalistic) sovereign who aims for good stewardship of ‘his’ assets (subjects), rather than expressing the will of the citizens. The whole mental outlook is different.
It’s bad enough the executive has hijacked the deliberation process of rule making. We should grant it exactly zero latitude in promoting its positions. I will it attack lawmakers for promoting their ideas in a one-sided way, that would be naive. I would totally apply a much higher standard to the executive.
AMT
Dec 6 2020 at 1:38pm
Ok let’s think about this example:
The answer to this question is binary, either yes it’s helpful for average citizens to wear a mask, or no it is not.
If it was a white lie to initially say the answer was no, then, if people now believe it was a lie, they must now believe the correct answer is yes; they should wear a mask. That is the logical conclusion. But is that what happened? No.
The people who are critical of mask wearing/the CDC/Fauci are critical because they just follow Trump and other conspiracy theorists who say the virus is a fraudulent hoax. They were never going to believe anything the real experts said. It was all fake news, no matter whether the experts initially said the answer to the mask question was yes or no. Like Tabarrok correctly pointed out, “More science won’t end science denialism.” There was no possibility to lead, or to nudge those people. Thus, there were no negative long run consequences, because nothing the experts said could ever matter to Trump’s supporters. The deniers’ “truth” is instead found from sources like a “doctor” touted by Trump who claims we just need hydroxycholorquine, but also to watch out for those demons having sex with you in your sleep and aliens and reptilians who run the government.
https://www.thedailybeast.com/stella-immanuel-trumps-new-covid-doctor-believes-in-alien-dna-demon-sperm-and-hydroxychloroquine
I do think that the CDC harmed it’s reputation by initially saying people shouldn’t masks, but not among the people that are currently ignoring their advice to wear masks and social distance.
Scott Sumner
Dec 6 2020 at 3:33pm
I suspect that when you talk to these people they will cite cases where the “experts” changed their minds, as when the refused to criticize the BLM protests, or changed their minds on travel bans, or changed their minds on masks, as evidence that expert opinion is politicized and should not be trusted.
Once you discount expert opinion, you are basically free to indulge in “motivated reasoning” to your heart’s content.
AMT
Dec 6 2020 at 9:21pm
Yes, these people will likely give examples of where experts changed their minds, but that is purely a post hoc justification for their predetermined views regarding the “hoax.” They already viewed experts as politicized, and were determined to completely discount expert opinion from the start, before any experts changed their minds on anything. Trump called it a hoax before mask advice changed and the George Floyd BLM protests.
https://www.nbcnews.com/politics/donald-trump/trump-calls-coronavirus-democrats-new-hoax-n1145721
And it is pretty hard to say that experts were “wrong” to change their opinion on a travel ban. If you perform any kind of cost-benefit analysis, the decision obviously hinges on how widespread the outbreak is, rather than changing scientific understanding, so it really takes some motivated reasoning to discount experts based on that.
And still, Fauci barely even seemed to hesitate to support the travel bans.
https://www.snopes.com/fact-check/fauci-china-restrictions/
Jon Murphy
Dec 7 2020 at 11:11am
AMT-
There will certainly be people on the extremes of any situation. There are people who, no matter what, will not trust “the experts.” And, on the opposite side of the spectrum, there are people who unquestioningly do whatever “the experts” say. There is often significant overlap between these two groups as they will often pick and choose which “experts” they listen to, which is why I keep putting the word in quotation marks.
However, Scott is making an argument on the margin. The marginal purchaser of expert opinion does consider reputation when deciding what advice to listen to. When someone like Fauci comes out and states that he deliberately misled on the mask issue, it weakens the marginal consumer’s faith in him as a producer of expert opinion. Thus, they are more likely to shift to other suppliers.
By way of metaphor, there are people who will, no matter what, buy food from McDonalds. And there are people who will, no matter what, not buy from McDonalds. But if it turns out McDonalds has been lying and selling tofu as “real beef” for their own good, I’ll bet my last dollar you’ll see a shift of consumers away from McDonalds.
AMT
Dec 7 2020 at 2:14pm
Sure, I can agree that in this case a small (I would say insignificant) number of people at the margin may have actually changed their response to expert advice, but a small number of people at the margin is not what I would call an “extreme” consequence, so I don’t think that’s what Scott meant.
I don’t think the “white lies” had any significant impact for public response to this pandemic, but the argument the public will be less trusting in future crises is most important. However, I can accept the argument that it might on rare occasions (but not in this situation) be best to mislead people to prevent panic and/or overreaction, because I think trust can be repaired over time and therefore it might be worth a temporary reduction in trust. So even if Scott says there are no “white lies,” I am not convinced by his argument that there were “extremely negative long run consequences.” There can very plausibly be positive consequences to “white lies.”
Jon Murphy
Dec 6 2020 at 4:32pm
I am presenting a paper at an upcoming conference where I find the expert failure Scott talks about not only severely damaged expert reliability but also had huge ripple effects throughout the rest of the economy, damaging the government’s reputation to manage a crisis on the whole. Furthermore, anecdotally, I’ll tell you that the mask-theatre of the NFL and media in general have people practicing malicious compliance with the mandates.
nobody.really
Dec 10 2020 at 4:02pm
Here’s an alternative hypothesis to Sumner’s: In today’s environment, people are prone to motivated reasoning anyway. Policy wonks like to flatter themselves by thinking that all their clever reasoning actual motivate people’s behavior. But generally, it doesn’t.
The US has a vast (and generally liberal?) anti-vax movement that predates Covid. Can we blame that on regulators’ white lies? If not, can we acknowledge that paranoid views about pubic health can arise regardless of regulators’ white lies?
Consider advertising: People pay a fortune in the effort to influence other people’s behavior. How much does advertising resemble policy wonk discussions? Not much.
In the pantheon of motivated reasoning, how ’bout this: Sumner actually has rather little evidence that people would have adopted different views in the absence of regulators’ white lies. Rather, regulators’ white lies offend SUMNER (and policy wonks in general, who are the readership of this blog). But, as a good policy wonk, Sumner does not want to advance his personal preferences as a grounds for policy. So he takes a plea for his personal preference and dresses it up in policy clothes.
Still, social scientists want to understand what DOES influence behavior. So here’s one more hypothesis: People differ in their predispositions to conspiracy theories. Perhaps a fixed percentage of the population are always susceptible to these messages. Or perhaps susceptibility relates to economic variables.
In sum, Sumner claims that, when people express skepticism about what experts say following a white lie, we’re observing a stimulus-response pattern. I’m questioning whether the alleged “response” actually bears any measurable relationship to the amount of stimulus. As any battered spouse will tell you, you can always find an alleged excuse for the beating–yet the beatings seem kind of regular, even if the excuses vary. That’s a sign that the alleged response has no bearing to the alleged stimulus–even if the abuser claims the contrary. In social science, a person’s statement about their own motivations may not be a sound measure of their motivations.
robc
Dec 6 2020 at 2:34pm
Great post!
Not sure if you saw this, but it disagrees with your last sentence in point 1.
https://www.frontiersin.org/articles/10.3389/fpubh.2020.604339/full
Scott Sumner
Dec 6 2020 at 3:37pm
That’s wildly implausible. Are we to believe that 4000 people died in Wuhan and hardly any in the rest of China due to inherent differences? It had to be policy.
How about Australia and New Zealand?
I’m not buying that explanation.
robc
Dec 6 2020 at 3:45pm
I havent done it (yet) but their math should be easy to verify. Its been out a few weeks and havent heard a retraction.
Jon Murphy
Dec 6 2020 at 4:27pm
That’s not encouraging. Nature published a paper where the data cited in the paper were flat out wrong, this was brought to their attention, and they refused to issue a retraction. There are a ton of real bad studies out there being accepted uncritically.
robc
Dec 7 2020 at 8:46am
Yeah, I get that. Its not discouraging, on the other hand. I would hope any good studies would avoid having retractions.
So its just basically meaningless.
I have been meaning to grab their raw data (I believe it was available) and run some simple correlations, to see if I get reasonably the same results. The devil is in the details, and they did some “cleaning” on the data, but if the same correlations roughly show up in the raw data then their cleaning wasn’t manipulation to get to certain results.
What always worries me is if the results only show up in the cleaned data. That doesn’t mean the cleaning is wrong, it just is a red flag, to me. The cleaning should highlight results that exist in the raw and make possible issues with the raw data less of a problem, not create new questions.
Jon Murphy
Dec 7 2020 at 12:01pm
Ideally. Also bad studies avoid having retractions, too. My personal philosophy as a scientific reviewer is a paper should be rejected or retracted only if there are serious logical, empirical, or ethical issues with it. For example, I recently recommended a paper for publication even though I found their argument unconvincing. The reasoning was solid and empirical method standard, but I felt they were making too many assumptions that were unsupported by the literature. But that debate should be held in the journals, not by referees.
My point in all this is that just because something is published, we still need to examine it critically. Like Scott, I’m suspicious of the conclusions your linked paper reaches. Prima facie, it doesn’t seem right.
To be clear, I do not think you are just accepting things uncritically just because they’re published. Rather, I’m just making a broader comment on retractions.
robc
Dec 7 2020 at 9:21am
Digging into some of the tables in that study, and the country one is interesting. I was looking for what countries were the big outliers.
There were 3 columns in the table (Table 1), deaths as of 8/31, projected deaths by model at “end of first wave”, projected deaths by model as of 8/31.
Ignoring that 2nd column for now, to me it looks like the model might overfit the data between 1 and 3. Almost every country was within 10%, seemed a little too tight to me. However, the big one off percentage-wise that I have seen is Australia (since you mentioned them): The model predicted ~200 deaths instead of the actual ~600, so the model doesn’t find Australia (or New Zealand) that odd. It is underpredicting Australian deaths by a large margin. However, the 2nd column expected a boom in deaths, it was ~1100 for end of first wave. It looks like Australia has settled in at just over 900, so it is off in the other direction for Australia.
For New Zealand, all 3 columns were 22. NZ was at 22 for a few months solid leading up to 8/31, so it was basically predicting they were done. They are at 25 now.
A few other examples for the 2nd column, a boom in deaths was predicted for both Mexico and Peru. It underestimated the first and WAY overestimated Peru deaths, having predicted they would be at over 100k, but it looks to have settled in at 40k.
Outliers make me happy, I could be wrong, but I trust the results more if there are some. The model predicts China pretty close. It way underpredicted future deaths in Belgium, unless this is considered the “second wave”. Havent dug in to figure out exactly how these things are defined. Otherwise it hit it pretty accurate, as Belgium was flat all summer long.
Their model misses pretty bad on the US in raw number terms, but it is only about 9% low in its prediction (column 3 vs column 1). Their column 2 is still below column 1, at 170k, so it missed pretty bad there. Once again, depending on what is “first wave”. I know they did US states separately, but I don’t see a table for those, they rolled it up in that table.
Anyway, that is just eyeballing it. My first impression is the predictions are a little too tight to reality, I would worry about overfitting. With 180 data points, if you throw in 180 independent variables, you can fit exactly! And have a crap model.
What I would want to see is the same data run again with Nov 30 as the end date instead of 8/31, and see if the correlations are the same, or if it is wildly different.
I also worry that the study confirms my biases so I therefore like it too much(I think Russ Roberts is rubbing off on me). On the other hand, opposite problem for you. On the gripping hand, sometime around 2025 someone will probably get to say “I told you so!”
nobody.really
Dec 10 2020 at 3:34pm
Is this an empirical statement, or a philosophical one?
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