Category Archives: Tyler Cowen is my Favorite Blogger

General update

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1. My proposal for credit lines is looking better, because the existing approaches are starting out fouled up in red tape and confusion. See the WSJ on mortgage relief. See The American Banker on paycheck protection loans (pointer from Tyler Cowen).

2. Last night, it seemed as though the Administration was considering a masks and scarves approach. But this morning. . .crickets. I guess the opposition is still strong. [UPDATE: this evening, a recommendation to wear face covering when we go out, e.g. to grocery stores.]

3. There are stories that Asian countries that have had success with their initial approaches, including masks, are now worried that they need more social distancing, because virus spread is starting to accelerate. Pointer from a reader.

4. Maybe we are practicing Hansonian medicine* in treating the virus. Tyler Cowen passes along a disturbing letter.

The letter passes along the claim that of patients put on ventilators, 80 percent or more never recover. My guess is that doctors know the characteristics of patients with an extremely low probability of recovery. Putting such patients on ventilators and caring for those patients puts health care workers at risk. At the margin, we may be costing lives.

The letter points out that if other hospital treatments are not working well, then the whole issue of keeping the hospital system from becoming overwhelmed is moot. I suspect that we get some trial-and-error learning value from hospital treatment. Maybe that trial-and-error learning value can produce a triage approach that uses hospital resources effectively. One way to achieve the goal of getting medical resources above “the curve” is to get better at figuring out who doesn’t need treatment and who cannot be treated successfully, so that resources only are used on treatment-worthy patients.

*For those of you new to this blog, Hansonian medicine refers to a meta-analysis by Robin Hanson that finds that when two populations with different intensity of use of medical care are compared, average outcomes do not differ. Hanson’s interpretation (which I am not totally on board with) is that in a population the cases where medical intervention causes harm cancel out the cases where medical intervention helps.

A general update

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I still want to participate in a movement to change the direction of the policy response to the virus crisis. The health policy leadership strikes me as inflexible and unscientific in its approach. And the macroeconomics profession is even worse. Our peacetime bureaucrats are losing the war on all fronts.

I decided after experimenting the other day that I don’t have a comparative advantage in audio-visual media. Others in the movement may prove better at that. I am thinking in terms of a different blog-like format, but more polished than this one. I do want to involve well-known thinkers I respect. I want to hear from the audience and involve them, not just talk (write) at them. Stay tuned.

Here are some comments on analysis that has recently come to my attention.

We are still nowhere on mass public face covering, but at least one country’s leader thinks it’s worth a try. And if it works there, maybe all the flak the idea gets from the health policy experts won’t stop us from trying it here.

Listening to Peter Attia and Michael Osterholm, it seems likely that our hospital system is going to run into shortages of many supplies, including medicines, masks, and chemicals necessary to carry out tests. Thanks to Tyler Cowen for the pointer.

Listening to Jay Bhattacharya and Peter Robinson, it sounds like Jay understands the principles of science. I wish somewhat like him had more power to oversee the allocation of resources for testing.

Robin Hanson found a serious error in every so-called model to predict spreading. That is, treating the spread rate, or R0, as if it were a single, physical parameter is misleading. In fact, we know that most people with the disease have R0’s well below 1, and a remarkably large fraction of cases are caused by a tiny number of super-spreaders. Robin shows that this makes it much harder to contain the virus. I trust his model more than the fancier ones out there.

I think this argues for a policy of limiting the number of people any one person can be in contact with per 10-day period. But “in contact with” may have to include doorknob effects. Of course, we still have not done the experiment to see how strong doorknob effects are.

William Galston is among at least a few people promoting the idea of a commission to investigate the government’s response to the virus crisis. I think that is a terrible idea. A commission is a symbolic gesture–an alternative to really cleaning house.

What I want to see instead is a really effective effort to lower the status of the public health experts and economic experts who created the response. Meanwhile, raise the status of outside thinkers who have been more insightful. The real commission will be what is embedded in the movement that I pray will form and in which I plan to participate.

After the 2008 financial crisis, the elites raised the status of Ben Bernanke and the Obama team without critically examining whether what they did was helpful or harmful. Not surprisingly the current Fed and the Trump economic team are pulling out the same playbook, expecting to reap the same glory.

But what have they accomplished? They have taken us much farther down the road to serfdom. We need to turn this vehicle around.

Thoughts on heterogeneity

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Tyler Cowen asks why numbers imply spread rates and death rates that are so difficult to reconcile across regions and countries.

People are feeding their elegant dashboards, nifty charts, and fancy computer models with worthless numbers. Nobody seems to want to listen to me on that. But it would not surprise me to find that all of the heterogeneity that cannot be explained by demographics and differences in treatment quality is simply an artifact of the way that numbers are collected.

Only fools claim to know precisely the true spread rates or the true death rates. We don’t even have decent ballpark estimates.

If we were to obtain data that were good enough to infer true spread rates and death rates, and these rates turn out to differ greatly across regions, then I would speculate on a combination of two factors. First, different variants of the virus, which spread and kill at different rates. Second, a highly skewed spreading phenomenon. That is, instead of every infected person proceeding to infect exactly 2.2 other people, you have a few infected persons infecting dozens of others, and most infected people infecting no one else. Put those two factors together, and you will get heterogeneity. But I emphasize that this is purely speculative. Don’t take this idea and run with it. Stop guessing. Get some facts first.

I wish someone at the CDC would take and run with the idea of obtaining scientific data, rather than guessing using the numbers that are being collected. In a scientific study, the investigator chooses who gets tested for the virus, and when the tests are conducted. The study uses the same type of test kit on every subject, preferably a test kit with a low rate of false positives and false negatives. Tests are conducted by carefully trained workers who follow very standard procedures. Before we test a large sample of people, we administer two tests to 100 people and count the number of times that we get different results on the two tests. If it is large, then we need to figure out how many tests we need to do on one person to get a reliable result.

Of the many problems with numbers as collected and reported, consider the issue of time lag. Suppose that two regions each test 1000 infected people on day 1. Region A reads and records the results a few hours later. Region B reads and records the results a week later. Suppose that the one-week spread rate is 100 percent per week, and each region then tests 1000 new infected people. Suppose that the death rate is 1 percent, and death occurs near the end of the week.

After day 8, each region has 2000 cases and 10 deaths. But region A, which reads the results quickly, will report that cases are doubling weekly and the death rate is 10/2000, or 0.5 percent. Region B, which reads the results slowly, will still report 1,000 cases, with a death rate of 1.0 percent.

Another problem is that there is very large variation in the ratio of tests to infected people, not only across regions but over time within a region. As you ramp up testing, you increase the reported spread rate and lower the reported death rate.

Almost all health agencies have chosen not to monitor this crisis scientifically. I wish I could change that.

Thinking fast and slow

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Tyler Cowen writes,

What many people do not realize is that “the speed premium” is vastly higher when a deadly virus is doubling in reach every five to seven days.

We needed a billion masks weeks ago.

But thinking is slow. Eons ago, on March 13, I wrote,

My working assumption is that American business and political elites are two weeks behind in their attempts to address the virus crisis. The steps they are taking now were necessary two weeks ago. And the steps that are needed now will not be taken for another two weeks.

Here are some predictions going forward:

1. The FDA and CDC were slow and often counterproductive in this crisis. But going forward, praise will be heaped on these experts.

2. If and when public health experts finally adopt something like the masks and scarves strategy, they will fill the journals will research papers showing that lockdowns were the key to beating this crisis.

3. No matter how special-interest-fueled, unhelpful, or even counterproductive the $2 trillion “stimulus” turns out to be, economists will fill the journals with research papers showing how it saved the economy.

My point is that it does not pay to be right about the crisis. That is playing Game 1. What pays is to be on the side of the powerful elites. That is playing Game 2. And nothing makes me feel more bitter and betrayed than seeing all the Game 2ers out there, patting each other on the back and gaining in status.

Whose status should be going up? Probably Razib Khan, who on Twitter now styles himself “Self-quarantine if you Khan.”

On March 18, Razib Khan wrote,

To be frank, most of the skeptics of the impact of coronavirus are not very smart.

How about me? On March 12, I wrote,

Even though we have no symptoms and no reason to believe we have been infected, my wife and I are going to try to do everything reasonable to reduce outside contact for a while. Call it “social distancing” or self-quarantining.

How about the former Mencius Moldbug?

On February 1–February first!–Curtis Yarvin wrote,

there is no good reason for anyone to be flying across the Pacific. The same may soon be true of the Atlantic. And certainly, no one should be flying in or out of mainland China—except via a quarantine facility. . . And Western public health authorities, though their epidemiology remains first-rate, cannot say this, or even think it, because of their internationalist intellectual doctrine, just one aspect of the great American progressive tradition of government.

If I can guarantee one thing, it is that his status will not go up. I am not saying we should drop all our existing beliefs and adopt his, but we ought to take into consideration that his view of the world made him quicker to spot the threat.

Nonbank liquidity now, solvency later

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Tyler Cowen posts an email he received that illustrates what I think most people get wrong about the appropriate policy for the crisis. Without getting into the specifics of he letter, I want to emphasize where I believe people are going wrong.

1. Worrying about bank liquidity before we worry about nonbank liquidity is exactly backward. This is not the financial crisis of 2008, where the big need for liquidity was on Wall Street. The big need now is on Main Street.

2. Worrying about solvency of the non-bank sector now, rather than worrying about liquidity, is exactly backward.

Government grants to keep individuals and businesses solvent are needed after we are ready to re-start the economy, not before. As Tyler and others have pointed out, our short-term goal is to reduce economic activity in order to slow the spread of the virus. That in turn creates a liquidity crisis for individuals who miss paychecks and businesses that miss revenue. As you know, I think we can deal with the liquidity crisis through government-backed credit lines. We should focus on the liquidity crisis now.

A solvency crisis may emerge later, particularly if the public health crisis lasts a long time, leading to an extended period of shutdowns. But the solvency crisis is not what the next few weeks are all about. Yes, a few businesses are on such thin margins that they may be insolvent now, but most can survive a few weeks provided that they have liquidity. Any business that has already become insolvent is probably not a business you can save in the long term.

3. If we are lucky, we won’t even have a solvency crisis. Suppose that in three weeks it looks like we can re-start the economy. This could happen if treatment capacity ramps up, which probably requires that we obtain success from one of the drugs we are trying. A more probable favorable scenario would be a dramatic slowdown of the virus, caused by a combination of the measures currently being taken and warmer weather. That might give us a few months’ respite, and perhaps in the meantime we can scale up hospital capacity and improve other public health policies, so that we won’t need to use shutdowns as a tool ever again.

I know this is an optimistic scenario rather than the most likely scenario. But there is no reason to rush into throwing money blindly at solving a solvency crisis that may not occur. If we wait a few weeks, we will have a better idea of the nature and scope of whatever solvency crisis lies ahead.

4. Let me add that Wall Street will clamor for Congress to do something. But a big stimulus package will make investors a little happier for a few hours, and then they will go back to watching the dashboards showing case spread rates and death rates. Congress will be told that they have to choose between plunging share prices and taking bold action today. They will take bold action today. After a few hours, we will be back to plunging share prices. Then what?

Price discrimination explains adjunct salaries?

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Tyler Cowen writes,

My immediate reaction was “Given the crowding in the sector, and that they presumably earn non-pecuniary returns from the enjoyment of teaching, shouldn’t we be taxing them at a higher rate?”

He is referring to the low salaries for adjunct professors. A college that pays different salaries to full-time faculty and adjuncts is engaging in price discrimination (actually, wage discrimination). Just as a price discriminator tries to charge based on willingness to pay, the wage discriminator tries to pay according to willingness to work. Like it or not, low pay for adjuncts is an efficient outcome.

Re-framing David Cutler’s proposal

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David Cutler writes,

Administrative costs in the health-care system are a classic public good. Payers and providers may together agree that standardizing billing codes and quality reporting would be valuable, but no single actor has an incentive to pay for standardization when others will benefit as well. For example, if insurer A chooses to harmonize its policies with insurer B, that lowers administrative costs across the board and thus fees that all insurers collectively need to pay. However, insurer A will not take these cost savings to other insurers into account. As a result, insurer A will be discouraged from investing in harmonization.

Pointer from Tyler Cowen.

As if there were no incentives anywhere for the private sector to solve this problem. But let me re-frame this from the perspective of an entrepreneur making a pitch to a venture capitalist.

“Doctors and hospitals have a big pain point in that their staff needs to fill out different claim forms for different insurance companies. CutlerMedForms has the solution. We will provide a software application that allows administrative staff to fill out a single, easy-to-understand on-line form. They simply check which insurance payer to whom to submit the bill, and our software fills out that insurance company’s form with the proper insurance codes. We estimate that providers can save $X billion of dollars in administrative costs using our software, making this a large profit opportunity for CutlerMedForms.”

Someone reading this might be skeptical that the profit opportunity actually exists. By the same token,, one should also be skeptical that the “classic public good” really exists.

Heather MacDonald’s reasoning is not sound

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Heather MacDonald writes,

Even assuming that coronavirus deaths in the United States increase by a factor of one thousand over the year, the resulting deaths would only outnumber annual traffic deaths by 2,200.

It is unsound to compare a relatively stable number (traffic deaths) to an exponential (the coronavirus). I hope that she will re-think and retract.

She writes as if increasing by a factor of 1000 is some sort of ridiculous upper bound. In fact, if we were to go ahead with business as usual and not do self-quarantining and social distancing, we would have to be darn lucky to have deaths increase only by a factor of 1000.

Lately, the number of cases in the U.S. and many European countries seems to be doubling every three days. If that pace continues, then in thirty days the number of cases will already be one thousand times what we have today. And in another two weeks, it would be 32,000 times the number of cases today.

Given this rate of spreading, one can expect that the number of deaths would double more rapidly than the number of cases. That is because the health care system would be overwhelmed. There would be too many critically ill patients to be able to treat them all.

As of Friday afternoon, there were about 2000 cases in the U.S. If 1000x were the upper bound for the spread of the virus, then we would see 2 million cases. If I thought that Americans could go about our normal business and have no more than 2 million cases, I would advocate going about our normal business. But instead, even with the actions that we have taken to date (note that these are less drastic than actions taken in several other countries), I think that holding the number of cases to 2 million would be optimistic.

I hope that I turn out to be foolishly alarmed about the way that this virus spreads. But to me, the exponential looks formidable.

Meanwhile, Tyler Cowen points to the British policy. As far as I can tell, they seem to be saying that you only need to worry about isolating known cases.

Some critics believe that the British approach will not slow the spread of the virus, and that the Brits know this. These critics see the Brits as consciously preferring to expose a large share of their population soon, on the theory that once they have immunity the crisis will be behind them.

The potential downside of that approach is that they might soon see their medical facilities overwhelmed, so that more cases become severe and fatal than otherwise might be the case. But if not, and their approach works, then they can certainly laugh at the rest of us.

Also, perhaps by the time you read this the Brits will have re-thought and retracted.

Macroeconomics of the virus crisis, 4

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Some very welcome humility from the economists on the IGM forum. They are asked whether we should think of this as mostly a demand shock or mostly a supply shock, and a lot of them refuse to take the bait.

Alesina says, “This is a new situation. We don’t have a clue.”

Duffie says, “For me, this is just too hard to entangle.”

Eichengreen says, “As someone who’s estimated lots of models designed to distinguish supply and demand shocks, good luck identifying them.”

Hall says, “I’m certain that the answer is totally uncertain.”

Schmalensee says, “Too early to call, I think. Workforce disruptions will affect demand as well as supply.”

There are others who are willing to try to pick one or the other. But some pick supply and some pick demand.

Of course, I think that the AS-AD paradigm is the wrong place to start. See my book.

Also, Tyler Cowen raises the possibility that the economy will suffer from a fragile financial system, which was fostered and joined by governments.

Macroeconomics and the virus crisis, II

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Before I get to that, Matt Ridley writes,

There are already several different strains of the virus, one of which, the L strain, looks to be more lethal than others.

What? Whoa!! Somebody needs to shout this from the rooftops. It suggests that there is no such thing as the death rate, even controlling for other factors. To me, it may suggests that we should be testing for this specific “L strain.”

Also, if there is more than one strain, does immunity to one strain not necessarily confer immunity to another? So you could get “it’ (i.e., one of them) again?

Now on to some other economists, who mostly make sense.

1. Alan Blinder writes,

If most Americans who wanted a test could get one, and if people who tested positive stayed home and sought medical attention, fear of going out wouldn’t disappear, but it would dissipate. Think of it as a super-effective form of fiscal stimulus. Test kits are ridiculously cheap compared with the GDP and job losses they might forestall.

2. Tyler Cowen writes,

Do you want to give people cash if they will just go out and spend it on entertainment or in large, crowded stores? Is that what you are hoping they will do? To what extent do we want the “transmitting sectors” to be contracting right now? Does it do much good to send consumers money they will spend on Amazon or pizza deliveries, two sectors that may do fine or even prosper during the tough times?

I do not think we should bail out shale oil producers or cruise lines. Presumably we wish to support businesses with an income gap for coronavirus reasons, but what exactly should we do? I am puzzled by the degree of certainty people seem to exhibit about this issue.

3. Timothy Taylor tells us about a quickly-published booklet edited by Richard Baldwin and Beatrice Weder di Mauro. Taylor quotes Baldwin and Eiichi Tomiura writing

the supply-chain disruptions that are likely to be caused by COVID-19 could lead to a push to repatriate supply chains. Since they [sic] supply chains were internationalised to improve productivity, their undoing would do the opposite.

I intend to download the booklet and read it. Meanwhile, I recommend Taylor’s entire post.

The booklet evidently includes some quantitative estimates of the GDP cost of the virus crisis. I am quite sure that the models used to produce those estimates are worthless. There is no way for them to estimate the cost of shifting to less-efficient supply chains. More important, nobody has a model of how leveraged financial institutions interact with the economy. Consider a cruise line that owes debt service payments on its ships or an airline that owes debt service payments on its planes. If they cannot service their debts and they have to declare bankruptcy, it is hard to calculate the effect of that on GDP. It is even harder to calculate the effect hits when the banks with the outstanding loans have to deal with the effect on their balance sheets.