Monthly Archives: March 2020

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.

The case for forbearance

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I believe that the best macroeconomic response to the virus crisis would be what I call forbearance. Bank regulators would tell banks that they will be allowed to fall below minimum capital requirements. They will be allowed to write down the value of loans without having to raise capital as a result. They will be encouraged to in turn offer forbearance to borrowers, provided that there is a reasonable prospect that borrowers will be able to get repayments back on track once the crisis has passed.

Under this policy, it will be up to banks to decide which borrowers are in short-term difficulty and which borrowers are never going to recover. If I were at a bank, I would bet on airlines coming back. I would not bet on cruise ships coming back.

You can think of forbearance as a selective soft bailout. When it comes to bailing out industries, you can think of a type I and type II error. Type I error is where you let a business collapse when it could survive with some help to tide it over. A type II error is where you save a business that is really not viable.

Ordinarily, you just let the market operate, and accept the errors that it makes. But the virus crisis threatens to become a financial crisis, and in a financial crisis there will be a lot of Type I errors. These in turn will cause economic activity to fall. But if you provide indiscriminate bailouts, you will make too many Type II errors.

If you provide funds to a troubled firm, then you may commit a Type II error without realizing it. If you only provide forbearance, then you discover your Type II error when even after the crisis passes the firm cannot get back on track. So that limits the duration of the error that you make.

If you just use generic macroeconomic instruments, such as fiscal and monetary stimulus, you end up with a lot of both types of errors. That is how I judge the response to the crisis of 2008. On top of that, there was all sorts of economically useless graft, such as the “green energy” programs included in the fiscal stimulus.

I am skeptical that either quantitative easing or the stimulus actually helped. That is because I think that the “aggregate demand” paradigm is flawed. Economic activity declined because particular patterns of specialization and trade were disrupted. This will also be the case with the virus crisis. More government spending or more expansion of the Fed’s balance sheet will just socialize more of the economy. That will be of little benefit in the short run, and it will cause harm in the long run.

My working assumption continues to be that the elites are two weeks behind in dealing with this crisis. That is, what President Trump did yesterday was probably what he should have done two weeks ago. What I would like to see the top leadership do is ask the Centers for Disease Control to come up with a plan for what to do if three weeks from now the number of cases continues to double every few days with no sign of stopping. Take that plan and execute it now.

Basic econ: costs of production

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I am starting to work on filling in/updating some of these college economics topics. Students land on the site when they want to get help with their college econ courses. But I plan to include some occasional “improvements” to mainstream thinking. I did not much need to amend mainstream thinking in my first topic, costs of production.

Other things equal, when fixed costs are high, there will be only a few firms. When fixed costs are low, there will tend to be many firms. When the Internet reduced the fixed cost of becoming a publisher, because you no longer need a printing press, the number of providers of written content skyrocketed.

The two-weeks-behind hypothesis

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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.

So you can look at the news about events being canceled, telework being encouraged, and so on, and say that this is all for the good. But it would have been better to have taken these steps before, say, the Biogen conference.

So ask yourself, what are the steps that we will wish we had taken two weeks from now? Perhaps more self-quarantining by people who do not think they have been exposed.

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 of the virus crisis, 3

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First, I think that this article from MIT Technology Review is essential reading, if you have not already seen it.

According to Duane Newton, the director of clinical microbiology at the University of Michigan, the biggest limitation in diagnostics is not the technology, but rather the regulatory approval process for new tests and platforms. While this process is critical for ensuring safety and efficacy, the necessary delays often “hamper the willingness and ability of manufacturers and laboratories to invest resources into developing and implementing new tests,” he says.

Case in point: FDA rules initially prevented state and commercial labs from developing their own coronavirus diagnostic tests, even if they could develop coronavirus PCR primers on their own. So when the only available test suddenly turned out to be bunk, no one could actually say what primer sets worked.

Read the whole article.

Next, today’s WSJ has many editorials and op-eds that discuss measures to help households get through the crisis. But the most interesting piece is by Hal Scott on the financial sector. He says that after the 2008 financial crisis abated

there was growing public concern about “moral hazard”—that government backstops and guarantees created incentives for risky behavior. In response, the Dodd-Frank Act of 2010 limited the Fed’s lender-of-last-resort powers for nonbanks, an increasingly important part of the financial system. Fed loans to nonbanks can now be made only with the approval of the Treasury secretary. They must be done through a broad program, unlike the one-off rescue of AIG, and must meet heightened collateral requirements. Loans to nonbanks must be disclosed to congressional leaders within seven days and to the public within one year.

I agree that we should be concerned about the financial sector, because of the way that it can magnify an economic crisis. But just as in 2008, I would try to avoid loans to financial institutions and other forms of bailouts. Back, then, I proposed “forbearance,” meaning allowing banks to fall below regulatory capital standards for a while. I still prefer this approach. It might reduce the contraction of the financial sector without providing a direct transfer of resources from taxpayers to banks.

Commenter Jeff thought along similar lines.

I wonder if you couldn’t mitigate some of the worst effects of defaults with some kind of mass forbearance policy. After all, if Southwest no longer has the cash flow to cover the financing costs of it’s fleet, what are its creditors going to do in the middle of a public health crisis? Come and repo the jets? In order to do what with them?

Finally, the headline yesterday that stock had fallen 20 percent from their peak caused me to wonder whether that is too much. Here are the arguments for and against a sizable stock market drop.

The case for a sizable drop:

–When we have a recession, not only does GDP drop but the ratio of corporate profits to GDP also drops. This “double whammy” on profits is a reason that stocks should fall farther than the economy. Another way to think of this is to treat an index fund as a levered position in GDP. If GDP falls by X percent, then the index fund should fall by a multiple of X percent.

–A significant share of corporate profits of U.S. firms now depends on overseas activity. Some important trading partners appear likely to be hit particularly badly by both the virus and by their financial fragility.

The case against a sizable drop:

–Although trade and tourism are big industries, they are a relatively small share of the U.S. economy overall.

–This, too, shall pass. At some point, even trade and tourism will recover.

Why are polygenic scores not better?

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Start with what I said in my review of Robert Plomin’s Blueprint.

Plomin is excited by polygenic scores, a recent development in genetic studies. Researchers use large databases of DNA-sequence individuals to identify combinations of hundreds of genes that correlate with traits.

The most predictive polygenic score so far is height, which explains 17 percent of the variance in adult height… height at birth scarcely predicts adult height. The predictive power of polygenic scores is greater than any other predictors, even the height of the individuals’ parents.

One can view this 17 percent figure either as encouraging or not. It represents progress over attempts to find one or two genes that predict height, an effort that is futile. But compared to the 80 percent heritability of height it seems weak.

Plomin is optimistic that with larger sample sizes better polygenic scores will be found, but I am skeptical.

My question, to which I do not have the answer, is this: if height is 80 percent heritable, why is the statistical correlation found between genes and height only 17 percent?

I do not know any biology. But as a statistician, here is how I would go about developing a polygenic score.

1. I would work with one gender at a time. Assume we have a sample of 100,000 adults of one gender, with measurements of height and DNA sequences. I would throw out the middle 80,000 and just work with the top and bottom deciles.

2. For every gene, sum up the total number in the top decile with that gene and the total number in the bottom decile with that gene, and see where the differences are the greatest. If 8500 in the top decile have a particular gene and 1200 in the bottom decile have the gene, that is a huge difference. 7500 and 7200 would be a small difference. Take the 100 largest differences and build a score that is a weighted average of the presence of those genes.

3. To try to improve the score, see whether adding the gene with the 101st largest difference improves predictive power. My guess is that it won’t.

4. Also to try to improve the score, see whether adding two-gene interactions helps the score. That is, does having gene 1 and gene 2 make a difference other than what you would expect from having each of those genes separately? My guess is that some of these two-gene interactions will prove significant, but not many.

It seems to me that one should be able to extract most of the heritability from the data by doing this. But perhaps this approach is not truly applicable.

Another possibility is that heritability comes from factors other than DNA. Perhaps the reliance on twin studies to try to separate environmental factors from genetic factors is flawed, and the heritability of height comes in large part from environmental factors. Or perhaps DNA is not the only biological force affecting heritability, and we need to start looking for that other force.

Another possibility is that scientists are working with much smaller sample sizes. If you have a sample of one thousand, then the top decile just has one hundred cases in it, and that is not enough to pick out the important DNA differences.

As a related possibility, the effective sample sizes might be small, because of a lot of duplication. Suppose that the top decile in your sample had mostly Scandinavians, and the bottom decile had mostly Mexicans. Your score will be good at separating Scandinavians from Mexicans, but it will be of little use in predicting heights within a group of Russians or Greeks or Kenyans or Scots.

I am just throwing out wild guesses about why polygenic scores do not work very well. I probably misunderstand the problem. I wish that someone could explain it to me.

The self-quarantine decision: my thought process

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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.

This means giving up discretionary trips to the grocery store or other shopping. It means giving up going to dance sessions (that is a big sacrifice, as far as I am concerned). It means not having social meals with others. It means not going to visit our children and grandchildren (an even bigger sacrifice).

My thought process is this:

1. I would rather be in front of an exponential curve than behind it.

When I started my Internet business in April of 1994, most people had not heard of the World Wide Web, and many of those who had heard of it took a “wait and see” attitude about whether it would work out as a business environment. It only became clear that the Web was a business platform more than a year later. But by that time, it was harder to ride the curve.

A lot of people, including government leaders in most countries, are going with a “wait and see” approach before reacting to the virus. They are certainly not getting ahead of the curve. In a few weeks, the self-quarantine decision we are taking may be imposed on everyone. Meanwhile, we hope to reduce our chance of contracting the virus and becoming spreaders.

2. In an uncertain situation, I like to compare the upside and the downside. When the upside of doing something is high and the downside is low, go for it. When it’s the opposite, avoid it.

So think about the upside and the downside of going about our normal business instead of self-quarantining. The upside would be that for the next few weeks I get to dance more and spend more time with friends and family. The downside is that I contract the virus and spread it. I think that the downside, even though it is unlikely, is worse, especially becoming a spreader.

3. How long will we self-quarantine? Either we’ll get something like an “all-clear” signal in a few weeks, or, if my worst fears are correct, there will be government-imposed measures that are as strong or stronger than what we are taking.

4. If I were in government, I would, in addition to making an all-out effort to test people with pneumonia symptoms, be making a large effort to test a sample of asymptomatic people. And re-test people in that sample every few days. From a statistical perspective, random testing strikes me as necessary in order to get a reliable picture of the epidemic. I would not trust an “all-clear” signal that was not backed by evidence from random testing.

Note that this post is not about the current Administration, so please self-quarantine your political comments and take them elsewhere.

UPDATE: John Cochrane recommends an essay by Tomas Pueyo. The message is to respect the exponential curve.

Yuval Levin and TLP watch

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Yuval Levin writes,

The left wants to be sure we do not take injustices in our society for granted—that we see the ways in which the strong oppress the weak, that we take them seriously, that we never walk by them and pretend they don’t exist. . .

The right, on the other hand, wants to be sure we do not take social order for granted—that we see the ways in which our civilization protects us, enriches us, and elevates us, that we never imagine that this is all easy or natural, and never forget that, if we fail to sustain this achievement, we will all suffer for it.

He does explicitly cite The Three Languages of Politics.

The topic of the essay is education policy, and I recommend the entire essay–it is probably the best essay I have read this year. I could have selected many passages to quote.

My inadequate attempt at a summary:

1. For the past 30 years, conservatives have focused on ways to strenthen incentives for K-12 schools to improve test scores.

2. Meanwhile, the left has taken over the culture of education. Conservatives need to fight to reverse this trend.

I think that these are valid points. But the song that runs through my head comes from Carole King. “It’s too late baby, now it’s too late.”

The left takes the social justice mission of education as given. The cultural values that Levin views as important are treated as relics of a racist patriarchy that must be purged from schools.

I would say that conservatives face an uphill battle, with an emphasis on the word battle. Even the ordinarily mild-mannered and moderate Levin concludes,

this adds up to a controversial understanding of the purpose of primary and secondary education, and one that will tend to fan the flames of our culture wars. Whether we like it or not, the next phase of conservative education-policy thinking will need to be willing to do that

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.