Phil Magness is a Senior Research Fellow at the American Institute for Economic Research.
He is the author of numerous works on economic history, taxation, economic inequality, the history of slavery, and education policy in the United States.
- Phillip MagnessSenior Research Fellow at the American Institute for Economic Research
Welcome to Policy McComas. A data focused conversation on tradeoffs.
I’m Carlos Kavala from the Saban Center for Policy at the University of Texas at Austin.
We have with us today Philip Magnus, senior research fellow at the American Institute for Economics Research.
He’s the author of numerous works in economic history, taxation and Equality in Education Policy and been right and
has been writing extensively about global health. Thanks for joining us. Thanks for having me.
So let’s let’s go back to March. One of the things we’ve been trying to do is to go back to what we thought when
and how the with information we had at that point. So, you know, even if it was before March, when
were you started to be like, huh, this is happening and what are we gonna do about
it? What was your sort of wake in any moment on it? Yeah. See, the first sign that I noticed
anything about it really coming into kind of a serious direction very
into February, The New York Times really started ramping up its coverage
of Koepp it and I noticed it at the time. I wasn’t expecting, you know, anything
near like what we had at the moment or the lockdowns or anything that followed. But I noticed that
suddenly there their attention had shifted pretty intensely to that subject. And then some
of that was actually sounding kind of a fairly alarmist direction. So this is probably around February
moment when I knew this was serious, when I knew that we should kind of buckle in for
a very long policy response was actually I think it was on March 12th
and that was the day not the government did anything was the day that the NBA canceled
the remainder of the season. Yeah, it’s it’s incredible that,
again, by individuals and reacted to sometimes faster and start internalizing,
there’s a little bit quicker than a government, right? Exactly. Governments, the lagging indicator here.
Right. Right. So so the NBA does it. And what do you start looking at in terms of data or models or
what? Catch your attention in terms of the information available for that decision. So
we saw on March 16th was the big day that major decisions were made both in the United States
and the UK. And that was the day that the Imperial College Niall Ferguson model came out.
And, you know, everyone remembers that. That’s the one that predicted two point two million deaths in the US. Five
hundred thousand in the UK. And it’ll be over by last year. You remember
that. But I actually I can remember now from a top my head by when they predicted 2.2 million deaths in the US. So
it was it was a little bit unclear. And the model they were claiming,
one version of it stated by the end of the year, but that he also gave some public comments to reporters
that it ended indicated slightly different timeframes. But I think the assumption has generally
been by. By the end of 2020. OK. OK. And and yes, this is that
was the model that somehow changed course on the UK response rate. In case
you know me on the path that Sweden had decided to follow and that
model came in and change might not only change what the UK did, but I think it was very influential in our
decision across the states here. Right, right. Right. Yeah. Here we have quotes from Anthony
Algy and Deborah Burke saying that they they had just received the new model from the UK
and it was predicting this disastrous scenario here. So it ends up being a major thing that shifts
them as well as the UK government, the Imperial College, sexually advising. So it’s something that at
face value, I think the model prediction as perhaps assumed that that was the best science
we had at the time. How would you take that information and think
about what to do and think about the options on the table? Right. And I think the main options that table at that point in time,
we’re like, well, we can try to do this the way Sweden is doing or we can try to do this the way
notor literally had done or what we decided experiment and locking down. So what should we
be looking at? Even taking that assface started it at point 2.2 billion. That’s prediction. How do
we go about making that decision? Well, my my first reaction to this and this is
probably within the days after the Imperial College model came out, is we had to look at the track
record of this group. This group of scientists, because they used an older model that was
from the influenza epidemics in the in the mid 2000s when they
adapted it over to CO. Did they state this outright? They said we’re taking our old flu model because this is the
closest thing that they thought they had decoded. So my next question is let’s look how that flu model
performed in 2005 and then 2009 when these were the avian
and swine flu years that we did have a serious response to.
But we can also evaluate against the way that the model performed in action.
And it turns out if you go dig up the articles, they were predicting hundreds of thousands of deaths with each of these pandemics,
and it ends up being a tiny fraction of that. So that immediately tells me
that maybe we shouldn’t put as much stock in this specific model that
governments actually did. And then the second question that we need to ask is, you know, these models
are based on inputs in back in March, even till very recently, we didn’t
have much in the way of reliable data on the nature of this new disease.
We knew that it was deadly. We knew that it spread very clearly in nursing homes because, you know, in Washington state,
the first outbreak in the US was in nursing homes. We knew out of Italy that
elderly populations were especially vulnerable and that had been where the majority of the deaths had occurred
by far and Italy. But we didn’t know the infection fatality rate. We still don’t
have a clear piece of evidence about that. And then testing was also so bad.
I mean, it was just kind of like a crapshoot. You didn’t really know what was going on. And yet
all these things are necessary to kind of calibrate the parameters of the type of modeling
that they employed there. And that raises a huge red flag for me. That that’s
that’s kind of science. Flying blind into the wind and
not really knowing what’s going to going to happen. And yet pretending as if you have almost like this pretense
of knowledge that you can project not only weeks out, but years out,
the epidemiological pattern of this disease and all using a model that hasn’t performed
all that well in the past. Right. But so one would try to justify
what we did by looking at that and say, OK, we don’t know enough. There’s lots of unknowns here. We don’t have enough testing.
We don’t have enough information. But under a combination of parameters and a combination of assumptions,
we’re facing 2.2 million deaths. Right. So but there’s something else that was missing
in that discussion when when deciding, let’s say to you, and then that’s the tradeoff
calculation. So, again, we can sit here and let this ride and,
you know, we’re going to kill 2.2 million people and or we can can do something that is extremely
intrusive, extremely right. Just like unpredictable in its nature. And what was gonna do
and what’s going to generate. So. So as as the lock announced our role again, what
were the things that you would think immediately? Obvious destruction. OK, well, the job market is going to suffer and I’m going to go.
But how were you thinking about that side, that the tradeoffs that we’re starting to face, the immediate
tradeoffs that come to mind is we know from past economic recessions and depressions,
there’s an extensive literature on this that it actually has clear effects in
both increases in substance abuse, increases in depression, which leads to suicide,
all sorts of ill health effects associated with economic downturns. We know this from 2008
when when the last major recession happened. Suicides, speed spiked,
alcoholism went up, substance abuse went up. And this is a just a natural
response that people have when when there are massive job losses and poor prospects for the future.
So we can reliably predict that something like that is going to happen. And guess what? It has
started to play out that way. We know from some states that we’re not hot of coded. They were
even reporting suicide rates that are are matching or exceeding what
they’re localized, coded right. Happened to be. So that kind of a downturn
is immediately evident, as is something that has to be as part of the tradeoff. Then you start
looking at secondary and and third order effects that are taking place
in response to this policy. So we lock down society in response to code.
But that also included the cancelation of what were called elective procedures in many hospitals.
It shut down the remainder of the medical industry so it could Rio oriented focus toward
Coatbridge beds. We wouldn’t lose our hospital capacity for a Kogut mitigation. But
what does that mean? It could be anything from someone who is at an early stage of cancer
now has to delay treatment for several months, and that could have
serious severe effects on their their expected lifespan. Not maybe this year, but many years from
now could be anything from elective surgeries that pertain very closely
to the quality of life. So elective surgery is not. It’s not like getting a plastic
surgeon to fix your nose or something. It could be a hip replacement. It could be a
joint repair. It could be something that treats a medical problem that’s not severe now.
But when you get into old age, it’s going to very, very clearly rack up and cause you problems
if you don’t treat it now. And what that implies is that some of the toll of
this is going to not be fully felt until 10, 20, 30 years from
now. For many people, they’re going to find diminished quality of life and maybe
even lifespan itself because of treatments that were delayed in response to the lockdowns.
So you start thinking about all these different conditions that come about, and it’s
suddenly a very severe aggregating problem that’s not at all considered in the models. It’s
not this isn’t part of the calculations that someone like Imperial College is
making. This is the cost side of a decision that’s almost
occurring in a vacuum. And so you’re adding those things up as
difficult, of course. But but at the same time, I think we’re true to the two sides in very different
ways. Right. One side, B, have a lot of uncertainty. Let’s stick to point to a space value and get
a side less than even talk about it. Let’s not even debate that. Let’s let’s try to
add up the things that we’re going to do. And one of the things that you write a lot from
from I want to say like economic freedom point of view, I’m not at these. You’re right. And
the one thing that bothered me and I want to take your take on it is that the notion that
governments start coming in and say, we’ve got to decide what’s essential. It’s not essential. Right. And that’s sort
of our inability to understand how, you know, the economic age of context and how things are connected
to to define what’s essential nonessential. It’s scary. And,
you know, the implications of that is it’s just incredible and surprises me, actually, that we didn’t suffer
more of a disruption. But then when you start
defining things as essential versus nonessential, that’s a political decision. That is
the governor or the mayor of some state or city coming in and saying, we know that
this type of business is necessary, but these other types of business are not. And we found this in the United
States, some things that were legal in Ohio where illegal just across
the border in Michigan. So the Michigan government governor deemed a gardening supplies
non non-essential. So they had to rope off that section of the store, whereas the crop just across
the border, you could drive five minutes up the road. If you live near the border, you could be in Ohio. And suddenly
it’s a very different situation because they made it on political lines. We saw this internationally
as well. There was a kind of a quirky story of a
store that sits on the border between the Netherlands and Belgium. And the half of the store that
was on the Belgium side was all roped off to only essential items, whereas the half of the store
on the on the Netherlands side was basically open, you know, with social
distancing and all the usual precautions in place. But you could sell things in one half
of the store and not the other half the store. And you will get this on its face. It’s just kind of absurd.
So I started looking a bit into some of the history of where do we get this definition of essential versus nonessential
because it is putting it in the hands of the politicians rather than any scientific basis. And
if we go back to previous pandemics where they’ve adopted policies to
try to curtail business hours. So the famous one being the Spanish flu in 1917,
there was not an essential versus nonessential distinction that was made. The measure that they used
there was and we found this in city by city by city, they keep going back to it,
whether a store or facility or restaurant or public place was congested.
So they were they were concerned about the number of people, not what the the service or product
being sold happened to be, which I think even though that’s not a perfect response,
it’s a better basis to actually go by. You want to focus on the transmissibility of the disease,
not whether people are choosing to buy gardening supplies or food or toilet paper or whatever it happens
to be. Right. Like shutting down the dog groomer seems to be like a really bad idea. Right.
Versus interacting on one dog. That’s not that’s not super clever. Yeah, we we we tried
to spend some time thinking here about about measuring the stability of different activities and trying to
look at a tradeoff between that activity, employment and GDP and provide that information to some
local governments here. But again, there was no appetite for that. There was this sort of like dichotomy either.
OK, let’s either open or or or close and that they use of these emergent
emergency powers to say shelter in place, stay home somehow was was seen as the
the. I want to say the what’s the word in the word you that sort of empathetic,
the right thing to do for for every individual. You wrote a little bit about this as well on like this notion
that we chose a course of action that some people think that Reverdy now is
is hurting the most vulnerable. Right. Right. You see, the lockdown is going to hurt the most vulnerable. Our our candidate
for Senate here in Texas a while. I’ll go back to Iraq. Just Texas yesterday tweeted yesterday about how Texas
is really hurting the vulnerable by opening the economy. Is it the reverse of that? Right. Here
is the exact opposite of that. You get two effects here. You know, when they impose
the lockdowns, what types of businesses are hurt the most? It’s the small businesses.
It’s the local one shop operations. It’s the one shop, cafe or restaurant. And a lot
of these are owned by you know, they’re owned by just a single person in
the community. They’re not a big chain that’s nationwide. Meanwhile, Wal-Mart and Target
and all these these national chains that do fall under the essential goods exemptions,
they provide groceries. And I’m not saying that they should be shut down any quite the opposite of that. But but
they’re going to be fine through this. And in fact, the business is going to probably shift toward them just like it
shifted toward Amazon online. But the businesses that are going to hurt the most are those
that do not have a national political presence or even a statewide political presence
to kind of malet a an opposition to this
politically induced presence to try and put them under lockdown. Then the second thing of that,
whenever you enact a lockdown, you are inviting enforcement, you’re inviting
agents of the state. And this is police, it’s bureaucrats, it’s regulators, whatever it happens to be,
you’re giving them a power to come in and say anyone that violated this lockdown
is now subject to either fine or arrest or imprisonment, imprisonment, all the usual things we do
when we make something illegal. You have to expect that it’s going to be enforced as it usually
is by the government. They’re going to send the police and regulators out. Well, what do we know about enforcement
in general, even separate apart from Cobbett patterns in police
enforcement patterns and regulatory enforcement tend to overwhelmingly
be focused upon those that are least able to defend themselves. People that don’t have access to
high dollar attorneys don’t have corporate lobbyists. In other words, the most vulnerable
members of society. Often that means poor people and racial and ethnic minorities.
And we know from several weeks of coded enforcement. And we
started to get some data out of New York City on this in particular. They started to release the numbers
of how many people they had arrested for violating the lockdown. And then they did the racial
breakdown. It turned out over 80 percent. Reader, African-American or Hispanic.
And this is a very large, diverse city, but they all happen to be all the arrests happened to be
in. And just basically to racial and ethnic groups. Something is not right. There
are some things a very discriminatory there in the way that this is being enforced. It’s
almost as if they’re going into the poorer neighborhoods and then the minority neighborhoods looking for
lock down violators. Meanwhile, in the in the wealthy neighborhood in downtown Manhattan, it’s
kind of looking the other way. And this is it’s almost a public choice, if that is, you
know, that who’s going to be able to hire an attorney who’s going to be able to
call attention to abusive enforcement and then who isn’t? And at the same time, at the same
time, the most vulnerable, the four have more of an incentive to go out and
and not obey the lockdown because. Exactly. Because the market demands a benefit of working
a day is much higher for them right then and for professor sitting at home, still working like me, where
you know, life. So so that the word I like that. Was it some
a lot of epidemiologists and some health officials using the word, oh, does any convenience. Right.
Right. It might be an inconvenience for me, maybe for you. But for a lot of people, it’s not an inconvenience. It was like the
stripe of their livelihoods. Right. And so that the sentence of that word is
just unbelievable. Yeah. Yeah. And we saw we saw that all over is the blue chip Twitter mafia.
You want to call on that? Most of these are people that are academics or they’re reporters.
They’re they’re middle class, upper middle class people who are able to work for home.
They can work from home. But if you worked in the service industry, if you worked in retail
jobs that are more commonly associated with, you know, minimum wage jobs
and this is your only source of livelihood or income, and you can no longer go to work because your business is
shut down. You can’t sit there and watch Netflix all day and continue to collect your salary
and do asume meeting to teach your class. Your livelihood is cut off. All right.
So. So we did it right. So we did all the mistakes of of
of not really considering lots of different tournaments. One of the things that I think was very, very
not fair to the public is the fact that the goalposts shifted as well. Why we had very much we had.
Right. We had this idea that maybe you’re going to do this for like two weeks to flatten the curve. That was the
term that went viral with the idea of letting the curve. There’s not an idea of changing the total number of infections,
just like smoothing the pass, slowing the rate of infection so that we don’t overall
capacity. And maybe I think the target in the beginning, people probably hoped that was like, oh, it’s going to be a two week thing,
which I hope not at like a deal if it’s like extended holiday two weeks.
Right. But what with two weeks became three months. And they go post
started thinking, well, now we just know about that. And the curve is about somehow eradicating the disease.
Right. What was dynamic at you? Did you saw that led to this sort of shifting and the goals of the politicians
here? Yeah. It’s almost like they sold the bill of goods to start off with it because it was all about
flattening the curve. That was the meme circulating around the Internet. It was the talking point
of Anthony Algy and all these public health officials. We’re gonna do this for a couple of weeks
because we need to flatten the curve to preserve our hospitals. And just just as you said, that that passes by,
that deadline passes. And so what we need to extend it from April 1st,
April 15th, April 15th, the March to May 15th, May 15th to June. And so on.
So it’s been just kicking the goalpost even further down the
line. And even to the point that I was reading an article in The New York Times yesterday
where they were trying to compare the European response, the Western European response to the American
response. And now all of a sudden, the talking point is that Italy and Spain
actually did something right. Because even though they had a sharper peak
and the total number of deaths, they also had a sharper decline. And then they had this overlaid with a chart of the
United States that has a milder peak and a milder decline. And I’m sure you’re thinking, wait a minute,
this looks a lot like the flat and the curve argument that you were using back in March. And
now you’re saying that this is wrong. It’s it’s it’s almost like this this internal disconnect
of where they’re searching for a justification for the lock down rather than making
the lock down based on unsound science itself. Right. Right. And
here you are again. Right. Because we we we are in the middle of June now. And and places like Texas
where I live, where we are, did not have a first wait. So Texas, I think the reality is that you are
not talking about a second wave. We just did now have a very mild number of cases in Texas, throughout
Texas, those the state the lowest death per capita of any significant state. Right.
And then guess what? Yeah, we we move out of a two month lockdown to say, listen, we can just hold on
the line here. So let’s say you don’t have enough cases to keep shut down forever into a vaccine comes up. It’s not an option.
Right. It’s not. It’s been it’s been it’s been opened up and life goes back to normal. If you look at
all the ability data. Texas seems to be back to a normal level of activity.
And fair enough. There’s some claim that there’s the growth in cases of gross
hospitalizations which weren’t expected. Right? That’s exactly. There’s no fighting that. That’s just. No,
no, no. Avoiding that. You see, again, I think a lot of the same
type of rhetoric of like, well, see, that was a mistake. To open it up was like, well, what was the alternative? Right.
You see all the alternate. The alternative across a
similar comparison you see between Europe and the US. Now you see the hard hit blue states
in the Northeast. They did arrive like, wait a second. New York has a thousand. That’s four million.
Texas has 70. Right. But anyway, I’m not saying that Texas
has to get to a thousand. I think now we learned so much more. Right. So I actually just moved it to that part that we did
all day. Now we’re here in June and we learn a lot more about uncertainty. We had a beginning that
might have been uncomfortable and B, politicians sort of, you know,
panic and opt for lockdown type strategy. What do we know now? How do you see what we know now
and what we’re going to go doing moving forward? What was the biggest point of data that’s been added
into our our mix, or I guess more so confirms the early signs of it was just how disproportionately
this disease affects the elderly. And it seems even to the point. So it’s a very severe
risk among the elderly. It’s a very mild risk among younger people
and healthier people and of the younger people that have died from it.
There’s overwhelming evidence that there are people with other medical conditions that exacerbate it,
just tragic and horrible in its own right. I don’t want to downplay that, but we
very clearly know that this is a disease that disproportionately affects the elderly.
What does that tell us? What it tells us that that maybe we need to consider different approaches to our policy
responses, that we’re not there back in March, the foremost among those being the nursing home
issue. So I’ve done a little bit of data work. Unfortunately, the states are not
very good at keeping these records. But Massachusetts, which is where I live,
has I gather that they actually have really robust daily data on
uncovered cases and the fatalities that come out of this. And they started back in early April. They started
tracking the daily deaths in nursing homes as opposed to the general population.
And they discovered something really quite early on. So back in April is about 50 percent of all deaths
in Cobbett in Massachusetts were in nursing homes, nursing homes that accounted for.
I think there’s a population of about 50 thousand people in a state of seven million is
a tiny portion of the population, is accounting for half of all COVA deaths. And that number
is increased. It’s it’s now hovering around 63, 64 percent of
COVA deaths in Massachusetts are from nursing homes alone. So this is telling me something very, very
pronounce. It says that we not only have an acute vulnerability among elderly people,
but it’s also an acute vulnerability among elderly people in a certain type of scenario,
a certain type of facility. So that tells me you need a policy response, targeting and figuring out
a way to lessen the susceptibility of nursing homes. And that could be
maybe that could include you have tighter restrictions on entry and exit into them. Maybe
it could include spreading out or dispersing the population at the nursing home. A big one
that’s come up. A lot of states adopted these these bizarre policies that require nursing homes to readmit
coated patients and they end up being carriers that bring it into an otherwise secure facility.
And next thing you know, half of the residents have contracted the disease, all sorts of things
that could have been done for nursing home homes and still should be done. But we’re basically omitted
from this general top down, one size fits all approach that we took back in March.
And then the final complication of this, you know, we talked about the Neal Ferguson Imperial College model,
which is all premised upon agent based interactions as a simulation model in
the general population. What happens if we do business as usual and people contact
five people in the course of their day going to work and school and stuff? We closed down work. We closed
down school. Maybe that reduces to 2 and that limits the number of interaction. Such it’s a
sophisticated model, but it’s a general population model. You go back to the 2005 paper
where they first developed this model and they say quite explicitly, we do not account
for group residences such as nursing homes, prisons and care facilities.
So the model that we based, all this policy response on this, the sophisticated
agent based simulation for the general population, did not even account for the one area
that’s turned out to be far and away the single biggest cause of Copan deaths.
Another way of saying that is the model that Neil Ferguson and the Bureau College used. It predicted
a certain type of deaths, but they are not the types of deaths that we are actually see. So
that tells me maybe we need to step back and reevaluate even that even the core
empirical basis that we made these decisions on and and taking new knowledge,
abandoned lockdowns entirely and went to a more focused policy that looks at nursing homes,
deals with the nursing home problem. Nursing home problem is a very, very sad one, because
it does seem. Nobody in the Western world has been able to deal with acts correctly like
Little Sweden. You know, I think the response to it has been very measured. But they did a bad job with our
homes. I feel like in Germany, pretty much every country outside of Asia
where I don’t think they have this, the system of nursing homes are parents. Right. Yet somehow.
I don’t know. It’s hard to say the exact understand why the death rate in Asia was not as bad as in the Western
world, but it’s just like tragic. But but that tells us about the different
response moving forward here. Exactly. For sure. And and
so you’re also talking about one thing that you talked about, wrote about it is about
the idea of going back to do. Ferguson, unfortunately, is claiming victory, somehow claiming that
the treatment, in fact, that I would like to call of of the lockdown. So so
some folks will go out there and say the lockdown saved 3.1 million people. And that was the right
shot of of the nature, sort of. I wouldn’t call a paper. It could be the blog
that was supposed to be. How do we think about that? Yes. Yes.
This is a major problem with the epidemiology literature. And this is something I love as a social scientist, just
for an intellectual exercise to look at this stuff, even though the implications are very profound.
So one of the great problems of empirical social sciences, as you referred to, is
inferring causality, detecting causality. It’s really easy to
figure out that two things correlate with each other to trends to correlate. But but proving that one caused
the other is such a statistical conundrum. And this is something that social
scientists have been working on for millennia. If you figure out how
do you track whether one. Variable
causes the other to happen. How do you separate these two things? And the statistical tools
that we have for inferring these are very sophisticated, but they’re also relatively
in their infancy. This is something that emerged basically in the late 20th, early 21st century,
the most advanced causal inference techniques that we have. And they’re very prominent in political science and economics.
Some of the physical sciences as tools that are just now starting to be explored. But if you look
at the epidemiology literature, it’s almost non-existent. They aren’t using causal inference.
So that that’s the study if you want to go our blog posts in nature. What they did is
they took their own model, the Imperial College model, and they projected the number of deaths
that they assumed would happen without the lockdowns. And then they just take they should do a suppression exercise.
They take the difference between that, the actual deaths we have. They say, aha, we saved three million people
or we saved two hundred thousand people here and there. That’s not social science.
That’s about the same level of sophistication as when Donald Trump
tweeted before March 20, 20 years as the stock market’s rising, therefore, I caused it.
So that’s the problem when I see this is a major deficiency of the epidemiology
literature right now I’m working on a separate paper. It’s kind of a review of all the studies
that claim to prove the lockdown effectiveness to see if they have a causal inference mechanism
in there. Do they use difference in difference? Do they go even a little more sophisticated,
use like a synthetic control to create a counterfactual that they can judge something against?
And very, very few papers have even awareness of that. And the ones that do, I think
are been to two or three synthetic controlled studies so far. One was on Sweden
and its conclusion was that the lockdowns did not work. They were ineffective. The counterfactual was
no different than what Sweden happened. The other was on Wisconsin that looked at the date
when the Wisconsin sharp. There was a sharp discontinuity in the policy. So you got to a treatment
effect on an exact date. Easy to isolate. We can see if there’s a spike
in deaths afterwards. And quite the opposite. Wisconsin’s been on a continuous downward
trend since then. So the only studies that have really looked at this that have robust causal
inferences are coming up with the exact opposite conclusion from these mathematical models
that just assume by subtracting reality from their own projections that they must have caused it.
And the other thing missing and all those is going to be also the fact that it’s not enough to look at at a point in time
because of luck, even if they’re locked down, even if I give you the lock down, somehow stop
all disease spread while he gets to introduce and later on.
So so so the only way that I think lugged down could effectively get rid of of of
debts would be by locking down entirely without an interactions and to have an effect that might seems
pretty tantalizing, which is just not saying that simple, implausible. So do you once
you look over a period of a year or Xie’s are you? That’s when I
think you going to be able to say something more clear by, let’s say, the Sweden experiment versus the others going to native countries,
for example, or any of that. That’s that’s that’s not
yet available. But but it’s it’s unfortunate how how the claims are too quick because they’re
coming in and trying to justify new lockdowns coming about. Right. So
they’re using that information. They see Texas should lock down now because that’s the only way
to save lives. It’s like this bizarre default position that we always go to the lockdowns.
Here’s another discovery that just kind of shocked me. This was a big aha moment when working in some of
this literature. You know, I’m an economic historian by background and training. I like
to look at past events to compare to that’s both hundreds of years ago where recent history
and I found this paper came from four leading epidemiologists at Johns Hopkins
University. It was published in 2006. And this was in the midst of some of the influenza
discussions that were happening around them. They were also really concerned about bioterrorism. So like
an outbreak of al-Qaeda using chemical or biological agents
to cause an attack is a big, big point of attention. But they asked the Johns Hopkins team,
what are the policy interventions in this paper that summarize? Basically, all the literature
had a stunning conclusion in it. It said that wide-scale what they called were quarantine’s or what we
call lockdowns. Now the language is shifting. It’s a wide-scale society. Wide quarantines
or lockdowns should be taken out of consideration entirely because
there’s no evidence that they work. This is all just theoretical models. We don’t
have any clear cases from past pandemics. There’s no natural experiment that has shown
these things are justified. It’s all just existing in this theoretical world of epidemiology
models that have just assumed it to be the case. So this
is kind of a stunning revelation. It shows that not only are critics of the lockdown existing
outside of the field of medicine and epidemiology, there are internal critics
to epidemiology who have been saying quite consistently for some time that
we don’t really know what we’re doing here when we’re enacting these policies. And yet you have
a political culture, a media culture, basically public choice of facts. What is the media like
to do? What’s the same thing that happens? yaller in Texas. You know, hurricanes on the Gulf Coast. What happens whenever
there’s a hurricane in the Gulf? CNN and the whole news crew descends on the coast
and are there standing out in the middle of the storm trying to predict the disaster.
The media is very, very susceptible to hype. It’s very susceptible to alarmist claims.
And walked aliens are very synchronised to addressing alarmist claims. So they that
they tend to get preferenced in the public discussion by
reporters, news crews that are all about showing the flashy shot of the
disaster happening and not really interested in the measured policy discussion that needs to take
place to deal with something like this. So let’s start to talk a little bit about speculate, I guess,
on on what why? Why is it that that I feel that our elites fail as
miserably because the media is doing what they do, which is like if you beat your leads. Right. That’s what they
do. And that’s always been unfortunate. It’s not a new phenomenon. I think maybe
now we’d like to talk about social media being like a sort of potential lies in more.
That’s sort of like feeling the flames that that that media likes to look at clickbait
to someone. But that’s not only a new phenomenon with social media. But the elites
typically are more into measured responses for water pollution crises.
And, you know, any other measure of political. Any idea of
a quality choice? So what happened? Why is different here? Why? Why? You know, I would blame
our field as well as academics. Economists. I think were incredibly silent
at first. They did a lot of good work after in terms of like, oh, can I work with, you know, condoms are better
modelers and epidemiologists so quickly like models that like to see what actually is a little weird.
But the first time in the beginning when lockdowns had been considered, it was silent deciles
across that leads. And what other Republican governors or Democratic governors, they locked everybody
down. Think one stood out, which is South Carolina governor. Right. Right. Yeah. Very few.
So why how is that? How do we get there? Yeah. So I keep going back to
it in my mind, as we look across both the physical and social sciences we have been dealing
with, something is referred to as the replication crisis in data for decades.
This is a well-known phenomenon. It exists in in economics, biology, physics,
you name it. And this is the problem of of a wheat’s intellectual elites in the academy
publish work, including in top journals, that other scholars
come back and they just try to replicate it, trying to run the same test. And they find out based on the available information,
it can’t be done. And there’s been very little correction that’s taken place on that.
I think this is a problem across multiple fields, but it really kind of burst
into the open at the outset of the coffee crisis because everyone was like, okay, well this
is the epidemiologists turf will defer to them. We’ll let them
call the shots early on. And we’re going to sit back. We’re going to have to wait to weigh
in. And part of that said, there there’s some humility built into that. But but the problem
here is when you have epidemiology, it turns out to also be afflicted by a replication crisis of its own,
also be afflicted by bad data of its own that basically just let it run
wild with some some really suspect work. And, you know, I hate to keep harping
on the the Imperial College model. But, you know, it’s the major model that’s driving
world decisions. It’s the one that other countries are replicating. And it turns out to
just be a bad model. Just be very ill suited for the situation
that we encounter. And yet there was like this deference that we have to give it over to the epidemiologists
to run with it, complicate that even further. We seen this in the subsequent
months as there’s almost been like a self-inflicted discrediting of the science by
all these changing standards. The changing goalposts we were talking about, even if anything,
as simple as advice. You know, we heard the other day, Anthony Algy basically admitted that the government
lied about bask- recommendations back in March, February and March.
They were discouraging people from buying NASA, not because that was what
the medicine said, but they were trying to preserve the masks supply for the hospitals and allies, saying, oh, now
we we have enough masks. We can reverse courses. That may be some sort of
a political a shrewd political trick. It does not help the condition
of science in the public’s mind. It undermines the respect
and trust that we were supposed to place and people that are exercising expertise and we see this
up and down the epidemiology profession. The other one that’s come out is when we had the BlackLivesMatter
protests pop up. And I think there are some there are some very legitimate
causes that people are protesting here, that the murderer, George FOID, is horrific.
And I think almost all Americans were in agreement that it was horrific. It reflects a real
serious, substantive problem with our police culture that I support addressing
that. I think most people, most reasonable people think that we need some sort of solution, too.
Nonetheless, those protests burst out into the open and kind of an uncontrolled way. They kind of happened
in defiance of the lockdowns. And very unexpectedly, it’s a spontaneous emergence.
Well, what did the epidemiologist do in response to that? The very same people who were scolding
and finger wagging at just everyday life actions
of going to your barber shop or going out to the store in public only two weeks prior
changed their tune. They became political messengers rather than scientific messengers
and started carving out all of these like really tendentious excuses of why the current
wave of protests was not as vulnerable to takeover it as
as we had all been. Just two weeks prior. So they sent a very inconsistent message there,
even to the point where some of the most prominent epidemiologists at University of Washington
and Yale University were did two very pronounced outspoken epidemiologists
that had been up until just a few days before the Black Lives Matter. Protests broke out,
scolding people for violating the lockdown for going out in public. This is a time
of a public health crisis and we must all do our part. But they politically sympathized with the
BlackLivesMatter protest. So just in the course of a couple of days, they completely flipped their message.
And I you know, I’m not judging sympathizing with BlackLivesMatter as a protest, cause that’s valid.
But I would judge a scientific expert who is predicating his or her
own advice and whether we should shelter in place strictly on whether they politically
agree with the reason to violate the shelter-in-place or not. And again, Nate,
the interesting part of it is like the movement being very critical of the way we force rules.
Yeah. Yes. We’ll meet a half weeks prior to say, you know, us have these rules that have to be forced
by police. Right. Right. And you saw that. So before George Point,
there was another kind of viral video that circulated and it was of an African-American man
on a bus in Philadelphia. And he wasn’t wearing a mask, even though there was no no rule in place.
Said he had to wear a mask, but some transit police decided don’t. You’re not wearing a mask. You
need to go and dragging the guy off the bus and slamming him to the ground. It’s horrific to
watch. You’re sitting there thinking, wait a minute. This is actually the same problem. And
two weeks ago, you all you epidemiologists were okay with this type of enforcement.
And now you’re saying that you recognize the problem. That’s it’s telling me that your message
as a scientific community is not rooted in science at all. So let’s
wrap up by again speculating about the future here. Yeah. So
it seems to me that that this episode is going to have a lot of
consequences to a lot of our institutions. And yes, there’s all the obvious financial
consequences to all of us are going to suffer. And universities are in dire trouble. I see I see
one of your books about cracks in the ivory tower. And I really enjoyed the book, even though it’s very critical
of my business. You’re justifiably critical of my business. So that’s that’s great.
There’ll be a lot of adjustments and things that we’re gonna have to do. And
but I think the two institutions that I’m thinking about this a science generally speaking, I started doing your first or just science
generally speaking and and governance, the fact that we all of a sudden realized that
safeguards that we had about about dictatorial powers that come in, you know, that we don’t allow
atoms. Have they had it by just calling an emergency? Right. Call it an emergency.
Apparently can put me on house arrest for three weeks. Three months. I basically sent a suspension of our democracy
effectively. Effectively. Right. And so policies with
enormous consequences there were not legislated. There were just done by fiat by 50 executives
around the country. So I you know, those two things I think are gonna have
a huge rediscovery about it. So how do you see the playing out? What’s what’s your.
Well, again, it taps into the extent to which scientific expertise has
engaged the self-inflicted wound. They’ve discredited themselves as it’s almost with the old story
about the boy who cried wolf. The next time when the wolf actually comes,
people are going to be much more distrusting of that level of expertise, because
I think that I think it’s pretty clear now that the scientific
advisors, as well as the politicians overplayed their card. They overreacted with the general
sweeping policy nationwide when it should have been a much more targeted policy around
nursing homes and other things that we can maybe effectively control. So
I see a lot of mistrust emerging in the future, too, invocations
of scientific expertise as the basis of emergency. And that can have problems in both
directions. It can have problems in both undermining future attempts to
enact similar policies. But it can also make people more skeptical and more distrust distrustful when
an actual emergency does happen, a much more severe, whether it’s a pandemic or natural disaster,
it’s that they’ve kind of painted themselves into a corner now where their credibility is on the line
and and people really don’t know where to go to to trust it. And then
the second thing, and this is what really alarms me is that I think some of the way
that the protest to the book, both of BlackLivesMatter
and the lockdowns themselves have played out, have unfortunately
incentivized people of authoritarian stripe on both the far left
and the far right to really enter into the political dialog. These are people that are
reacting to heavy handed enforcement across a multitude of policies,
but they’re reacting in such ways of either saying, well, we need the police to crack down even harder
or we need to engage in violence to topple the system or topple
types of government that we don’t like. Those types of reactions, I think are fundamentally authoritarian
and premised on extremism. And I think a very unfortunately, the way
that this whole thing was played out, it’s almost like the politicians
thought that they could carefully measure and implement a lockdown
and keep extending it, extending extending it. And there’d be no consequences that we get to
the. Were we very lightly and in a managed way remove it? Well, that’s not playing out at
all. People are are basically discarding the lockdowns on themselves because they
they were extended far beyond what people were willing to countenance. And now it’s kind of a chaotic
structure and response in that chaos is unfortunately open the door to some very ugly authoritarian
tendencies. One of the one of the things that from the very beginning, I think one of the Swedish epidemiologists,
if you ever watch some of the interviews of their interviews, is I recommend, because they were they were
very level headed from the very beginning. One of the things in these old gentleman said a couple of times is that
I don’t understand what’s the plan that any of these countries are locking down have to unwind the lockdown.
Exactly. Exactly. There’s no data that will allow them to see. OK. Now we can open it up because there will
be no data on that unless a vaccine comes about. And and I think, again, that’s sort of
beyond the data on the scientific side, the aspect of social interactions and arrest that might
create and be creative. What is the plan? What is it? How do you do this? Very difficult. And we’ve
seen that not only here, but pretty much everywhere. Absolutely. Absolutely.
Phil, thank you so much for this. Thanks for all the writing you do on lots of topics of the day. You particularly
have been very used, but you’ve been read your columns the a few months and hopes to Texas
at some point. Not so distant future. Yeah, exactly. Exactly. Thanks again.
Thanks for listening to Policy McCombs.