Category Archives: virus crisis

General update, April 14

Posted on by

1. Deirdre McCloskey writes,

Socialism should therefore be called “coercionism.”

. . .another good name for the system that the non-conservatives and the non-socialists among us favor would be “adultism.”

2. I am still cranky, for the same reasons as before. We still do not have results of random-sample testing to have an idea of how many people have the virus in various regions. We still do not know how viral load affects outcomes. We still do not know whether people get it from touching surfaces and then touching their faces, or whether they have to breathe near an infected person. We still are not conducting any scientific experiments. Instead, we are contemplating mass “experiments” with changing regimes for social distancing, arguing over putting at risk either more economic activity or more human lives. Worse yet, we really won’t learn anything from these “experiments.”

We still talk about political leaders “re-opening the economy,” as if the economy is theirs to re-open and individual choices will not be affected by the virus. People still expect that any and every household and business can be saved from the consequences of the virus, because government has the know-how and skill to undertake this. People still conceive of government as an infinite storehouse of riches that is disconnected from any need to obtain the wealth that it purports to distribute.

3. Ben Thompson writes,

what has been increasingly whitewashed in the story of California and Washington’s success in battling the coronavirus1 is the role tech companies played: the first work-from-home orders started around March 1st, and within a week nearly all tech companies had closed their doors; local governments followed another week later.

So, the approximate order of events was: private sector response, then local government response in the west, then response in the east and by the Federal government. But as Thompson points out, the east coast media have missed this aspect of the story.

4. Ali Hortaçsu, Jiarui Liu, and Timothy Schwieg attempt to do some epidemoiology.

we find that 4% to 14% of cases were reported across the U.S. up to March 16

The paper describes their methods. As of March 16, according to this site there were 4300 reported cases. But if the authors are correct, there were between 3000 and 100,000 actual cases.

I suspect that the ratio of unreported cases to reported cases has gone down since then, but I have no idea by how much. We now have almost 600K reported cases, and if we have between 6 and 25 times as many unreported cases, then that would mean between 3.6 million and 15 million people have had the virus.

Economists are probably building better models than epidemiologists. But random-sample testing would be much better.

General update, April 13

Posted on by

1. Tyler Cowen continues to question the caliber of the practitioners of epidemiology. I would add that

–John Ioannidis in his classic work around 2005-2007 debunking published papers was particularly hard on epidemiological research.

–Robin Hanson was quickly able to point out the problem with treating R0 as a fixed parameter.

–I am frustrated that epidemiology is determined to rely on observational data rather than experiments

–I am frustrated at the eagerness to embrace computer models regardless of the faulty data and parametrizations.

Having said all that, I am also dismayed that laymen put such pressure on epidemiologists to make forecasts. Imagine if it was your job when you see a leaf falling from a tree 40 feet overhead to place your foot on the exact spot where you “forecast” that the leaf will land. As I pointed out when Dr. Fauci forecast between 100K and 240K deaths for the U.S. that this would require the number of deaths to double no fewer than 5 times and no more than 6 times. And this was when the 3DDRR was 2.0, which meant there was no way that such a narrow forecasting range was defensible.

2. A reader recommends that I re-link to a classic essay, lenders and spenders. It clarifies the problem with deficit spending.

3. Do you know about the phenomenon at the shore known as an undertow? On rare occasions at a section of a beach, a strong current will carry people out to sea. If this happens to you, the guidance I have read says that you need to swim parallel to the shore until you no longer encounter the current. Then you can make it back to land.

Think of the economic losses from the virus as an undertow. But instead of swimming, everyone is looking at a boat, the USS Government, where sailors from Congress and the Fed are busily tying ropes, with life preservers on one end and the railing of the boat on the other. The people in the water are each waving their arms and screaming “I need a life preserver. Throw one to me.” They are so frantic that the sailors think that the only way to keep order is to keep tossing more and more life preservers.

But there is a problem. The USS Government has a big hole in the bottom, called the deficit. It is likely to sink. And at that point a school of sharks, called inflation, will arrive on the scene.

We would have been better off swimming. There are some people who really could not swim to safety, and the better swimmers should try to pitch in to help them. But we should not be attributing so much capability to the USS Government.

General update, April 12

Posted on by

1. Tyler Cowen offers some unsolicited advice from an economist to epidemiologists. More here.

I applaud epidemiologists for thinking exponentially rather than linearly. I boo them for going with computer models without seeming to appreciate how flawed data and parametric simplification make them unreliable.

I would add that the political process selects economists as advisers based on criteria that are uncorrelated, or perhaps negatively correlated, with wisdom. I could imagine the same thing happening when epidemiology mixes with politics.

2. Reader Aaron Lindsey has posted a 3DDRR spreadsheet that makes it easy to see how that indicator has behaved.

Do you want to understand how difficult it is to make epidemiological forecasts? Squint at the chart from April 1st on. Imagine a trend line from April 1 to April 6 extended to the present. The difference between that trend line and the actual behavior may seem small. But because of that difference, we may have twice as many deaths from the virus compared with what would have happened had the trend from April 1 through April 6 continued.

3. Another reader, John Alcorn, found this article.

We identified 103 possible work-related cases (14.9%) among a total of 690 local transmissions. The five occupation groups with the most cases were healthcare workers (HCWs) (22%), drivers and transport workers (18%), services and sales workers (18%), cleaning and domestic workers (9%) and public safety workers (7%). Possible work-related transmission played a substantial role in early outbreak (47.7% of early cases). Occupations at risk varied from early outbreak (predominantly services and sales workers, drivers, construction laborers, and religious professionals) to late outbreak (predominantly HCWs, drivers, cleaning and domestic workers, police officers, and religious professionals).

Their investigation looked at Asian countries other than China.

4. As economists start to think about how all this new government spending is going to be financed, you might want to re-read this post from 2010.

As of 1946, the ratio of debt to GDP was 108.67 percent. From 1947 to 1970, it fell to 27.96 percent. A substantial amount of the drop was due to the fact that the government ran a primary surplus in all but four of those years (the exceptions were 1953, 1959, 1962, and 1968), for a cumulative primary surplus of 43 percent of the 1946 debt.

I was surprised by this. I had not remembered these surpluses. One reason is that the primary surplus excludes interest payments. Including interest payments, the government mostly ran deficits, particularly in the 1960’s. Another reason may be that the U.S. only began to include Social Security surpluses in the overall Budget late in President Johnson’ second term. Had we used the “unified” budget from the beginning, the deficits would have seemed much smaller and we would have counted more surpluses.

Thanks in part to Social Security, which was running surpluses that were not included in the budgets as reported at the time, we were very fiscally responsible in the 1950s and 1960s, so we paid most of the World War II debt.

In contrast, today mainstream thinking is that “interest rates are low, so why bother worrying about the debt?” Olivier Blanchard, one of the leaders of the economics profession, takes this stance. I have never had much regard for him. Over the next decade, we’ll see who turns out to be right.

5. Tyler asks why Belgium is doing so poorly. I immediately looked for a sociological variable. It turns out that Antwerp and Brussels are two of the European cities with very high Muslim populations. The Netherlands, which has several cities that have large Muslim populations, also has a per capita death rate on the high side.

I am using Muslim population as a crude proxy for ghetto-ized living conditions, equivalent to Hispanics in New York City. I am not trying cast any ethnic aspersions on Muslims or Hispanics. What I picture is a lot of people who do not have the privilege of a social-distancing option. They cannot work in home offices or avoid living in crowded conditions. As the Wikipedia list says, “In Western Europe, Muslims generally live in major urban areas, often concentrated in poor neighborhoods of large cities.”

But Germany, which also has major cities with large Muslim populations, is doing relatively well. Berlin also has a high reliance on mass transit, which deepens the mystery of how Germany is containing the virus. This story credits early implementation of test, track and trace.

6. Some of you have expressed an interest in betting on the fate of colleges and universities. You will want to read this.

“Financially, many colleges have been struggling, facing a perfect storm which is going to be even more difficult now,” Robert Franek, editor-in-chief of the Princeton Review, told Campus Reform. “Their costs are up, but their tuition dollars are down as enrollments trend[s] down. The value of their endowments is also down, and with the economy in [a] downturn, alumni and corporate donations are likely to be less.”

The coronavirus relief bill signed by President Donald Trump on March 27 includes $14.3 billion for higher education, with $12.4 billion split between emergency grants to students and money to colleges “to address needs directly related to coronavirus” and to “defray expenses” from lost revenue, reimbursement, technology for distance learning, and payroll.

Tyler’s dire prediction for colleges is based on what he foresees as their inability to sustain the foreign enrollments that have been a crucial source of revenue. But note the huge bailout voted by Congress, even though it requires Republicans voting to give money to Democratic bastions. The higher education lobby has quietly become one of the most powerful and effective political operations in the United States.

The sociological variables

Posted on by

As we seek to understand different outcomes in different regions or countries, the temptation will be to look for explanations in terms of government policies. But I wonder how much of the differences were caused by sociological variables.

One variable might be ghetto-ization of immigrants. Some European countries have acquired large Muslim populations that have not been assimilated into the native culture. France, Sweden, and the UK come to mind, but perhaps there are others. Here in the U.S., New York has ghettos of Hispanic immigrants, and they account for a significant portion of deaths, perhaps in part because they are likely to work in occupations that require them to leave their homes. At the other end of the spectrum, Japan is notorious for not having a large immigrant population.

Another variable might be herding of the elderly. In the United States, we herd many of the elderly into nursing homes, and at least 10 percent of the deaths in this country have occurred among residents of such facilities. Perhaps living arrangements in Northern Italy produced an elderly herding effect. Japan has a very elderly population, but perhaps they live in more isolated conditions.

Are these or other sociological variables helpful in explaining the severity in Spain? What about the relatively low death rates in California and Texas?

PSST and the economic recovery

Posted on by

I keep forgetting that most people believe textbook macroeconomics instead of my preferred paradigm of Patterns of Sustainable Specialization and Trade. To understand how I think about the recovery from the virus crisis, forget everything you learned about “aggregate demand” or “aggregate supply” or anything you read in the newspapers, especially about all the things that the Fed is doing to “save” the economy. Instead, try to approach this with a fresh outlook, bringing no baggage with you.

I am going to make some points here that have the potential to offend people of all political stripes.

1. “We” didn’t kill the economy, if by “we” one is referring to the government. Most, if not all, of the actions that reduced economic activity were undertaken voluntarily by households and firms.

2. The economy is not going to “re-open” or “get back to normal” in response to government action.

3. The CARES Act and the Fed’s extraordinary interventions are more likely to hurt than to help the recovery.

Read on.

Continue reading →

Antibody testing: overcoming Bayes’ theorem

Posted on by

Taal Levi writes,

Let’s talk about why it’s critical NOT to assume you are immune to covid-19 when you have a positive antibody test.

I will argue that this problem can perhaps be overcome by requiring three positive tests in order to prove immunity.

Let’s make Levi’s assumption that 1 percent of the population actually has antibodies. Having antibodies is a good thing, because it means you already have had the virus and we can hope that this makes you immune.

For rounder numbers, assume that the test gives a false positive reading in 5 percent of cases where people don’t really have antibodies, and also a false negative reading in 5 percent of the cases when people do have antibodies.

Out of 10,000 people, 1 percent will have antibodies. That is 100 people, with the other 9900 not having antibodies.

Of the 100 people who have antibodies, 5 will falsely be reported as not having them. 95 will correctly be reported as having them.

Of the 9900 who do not have antibodies, 495 will falsely be reported as having them.

Altogether, 495 + 95 = 580 people will be reported as having antibodies, but most of these people will not have them! So you would not want to tell all 580 people that they don’t have to worry about getting infected if they go out and play. Most of them in fact can get infected.

My recommended solution to this problem would be to require a second test for those who test positive the first time. The second test also has to be positive in order to say that the person has antibodies. Assuming that the results are independent, the chances of two tests incorrectly reporting positive result is .0025, or 25 out of 10000.

That still might be too high. But we can take the people who test positive on two tests and make them take a third test. Only if this last test is also positive would you give the person freedom to roam.

Note that if the probability of a false positive depends more on the person being tested than on pure chance, this proposed solution will not work.

3DDRR update

Posted on by

Today, the overall 3DDRR continued to edge down, to 1.40, and outside of New York it declined from 1.47 to 1.42

Recall the original post on the 3DDRR.

It would be nice to see, say, 1.5 by April 7, 1.3 by April 10, 1.1 by April 13, and 1.002 from April 16 on. That would raise April 4ths total deaths of 8314 to 17,834 (exactly, right?) on April 13

Well, we missed those goals by quite a bit, and as of April 11 deaths stood at 20339. As of April 6, we were doing nicely at 1.53, and it looked like we were on track to hit 1.50 by April 7. But that did not happen.

What I would like to see over the next week is a sharp drop in the New York 3DDRR without a big surge in other places.

Tyler Cowen at Princeton, annotated

Posted on by

Tyler Cowen talks about medium and long-term consequences of the virus crisis. I give it an A+.

For a couple of days I worked on a post on the economic outlook, which I scheduled to go up tomorrow. I think you will see a lot of similarity in our views. We differ in terms of tone. Tyler sounds detached and fatalistic. I sound cranky. Below are some more detailed comments of mine, sometimes amplifying his remarks and sometimes disputing them. Continue reading →