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  • 1
    object(stdClass)#14481 (59) {
      ["id"]=>
      string(4) "6132"
      ["title"]=>
      string(61) "Interview with Larry Summers: China, Debt, Pandemic, and More"
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    Irwin Stelzer and Jeffrey Gedmin have a wide-ranging interview with Lawrence Summers in The American Interest (May 22, 2020, "How to Fix Globalization—for Detroit, Not Davos").

    " ["fulltext"]=> string(7828) "

    As always, Summers is his habitually and incorrigibly interesting and provocative self. Here re a few of many quotable remarks. 

    China

    In general, economic thinking has privileged efficiency over resilience, and it has been insufficiently concerned with the big downsides of efficiency. Going forward we will need more emphasis on “just in case” even at some cost in terms of “just in time.” More broadly our economic strategy will need to put less emphasis on short-term commercial advantage and pay more attention to long-run strategic advantage. ...

    At the broadest level, we need to craft a relationship with China from the principles of mutual respect and strategic reassurance, with rather less of the feigned affection that there has been in the past. We are not partners. We are not really friends. We are entities that find ourselves on the same small lifeboat in turbulent waters a long way from shore. We need to be pulling in unison if things are to work for either of us. If we can respect each other’s roles, respect our very substantial differences, confine our spheres of negotiation to those areas that are most important for cooperation, and represent the most fundamental interests of our societies, we can have a more successful co-evolution that we have had in recent years. ...

    Attitudes on Globalization

    Someone put it to me this way: First, we said that you are going to lose your job, but it was okay because when you got your new one, you were going to have higher wages thanks to lower prices because of international trade. Then we said that your company was going to move your job overseas, but it was really necessary because if we didn’t do that, then your company was going to be less competitive. Now we’re saying that we have to cut the taxes on those companies and cut the calculus class from your kid’s high school, because otherwise we won’t be able to attract companies to the United States, and you have to pay higher taxes and live with fewer services. At a certain point, people say, “This whole global thing doesn’t work for me,” and they have a point.

    So we need a global agenda that is about broad popular interests rather than about corporate freedom—that is, cooperation to assure that government purposes can be served and that global threats can be met. If we have an agenda like that, we can rebuild a constituency for global dialogue.

    Government Debt

    The deepest truth about debt is that you can’t evaluate borrowing without knowing what it’s going to be used for. Borrowing to invest in ways that earn a higher return than the cost of borrowing, and provide the wherewithal for debt service with an excess leftover, is generally a good and sustainable thing. Borrowing to finance consumption, leaving no return to cover debt service, is generally an unsustainable and problematic thing. ...

    I think we need to be very careful, with respect to the expectation that we now seem to be setting of having government cover all the losses associated with the COVID period. For the life of me, I cannot understand why grants should have been made to airlines to enable them to continue to function, rather than allowing their share values to be further depressed, and allowing those who would earn substantial premiums by taking risk on airline bonds to do so, accepting the consequences of an investment gone wrong.

    Looking towards an economy that is going to be very different than the one we had before COVID, we cannot aspire to maintain every job or every enterprise with a compensation program indefinitely. So as I look at the 30 percent of GDP deficit that we are running in Quarters Three and Four of Fiscal 2020, I don’t think that can be sustained over a multi-year period.

    Enforcing Existing Tax Laws for Those With High Incomes

    We could raise well over a trillion dollars over the next decade by simply enforcing the tax law that we have against people with high incomes. Natasha Sarin and I made this case and generated a revenue estimate some time ago. If we just restored the IRS to its previous size, judged relatively to the economy; if we moved past the massive injustice represented by the fact that you’re more likely to get audited if you receive the earned income tax credit (EITC) than if you earn $300,000 a year or more; if we made plausible use of information technology and the IRS got to where the credit card companies were 20 years ago, in terms of information technology-matching; and if we required of those who make shelter investments the kind of regular reporting that we require of cleaning women, we would raise, by my estimate, over a trillion dollars [over ten years]. Former IRS Commissioner Charles Rossotti, who knows more about it than I do, thinks the figure is closer to $2 trillion. That’s where we should start.

    Coronavirus Priorities

    The real crime is not that we miscalibrated on some economic versus public health trade-off. The real crime is that we have not succeeded in generating far greater quantities of testing, far greater mechanisms for those 40 million unemployed people to do contract tracing, far more availability of well-fitting, comfortable, and safe masks, and that we’re under-investing in the development of new therapeutics and vaccines.

    When something costs $10 to $15 billion a day, you need to make decisions in new ways. We should not be waiting to see which of two tests works best. We should be producing both of them. We should not wait for vaccines to be proven before we start producing them. We should be producing all the plausible candidates. Remember, one week earlier in moving through this is worth a hundred billion dollars: two months’ worth of the annual defense budget.

    A version of this article first appeared on Conversable Economist.

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    Interview with Larry Summers: China, Debt, Pandemic, and More

    Timothy Taylor
  • 2
    object(stdClass)#14478 (59) {
      ["id"]=>
      string(4) "6109"
      ["title"]=>
      string(71) "Interview with Joshua Angrist: Education Policy and Causality Questions"
      ["alias"]=>
      string(70) "interview-with-joshua-angrist-education-policy-and-causality-questions"
      ["introtext"]=>
      string(348) "

    David A. Price interviews Joshua Angrist in Econ Focus (First Quarter 2020, Federal Reserve Bank of Richmond, pp. 18-22).

    " ["fulltext"]=> string(9408) "

    Angrist is well-known for his creativity and diligence in thinking about research design: that is, don't just start by looking at a bunch of correlations between variables, but instead think about what you might be able to infer about causality from looking at the data in a specific way. A substantial share of his recent research has focused on education policy, and that's the main focus of the interview as well.

    To get a sense of what "research design" means in this area,  consider some examples. Imagine that you want to know if a student does better from attending a public charter school. If the school is oversubscribed and holds a lottery (as often happens), then you can compare those attending the charter with those who applied but were not chosen in the lottery. Does being surrounded by high-quality peers help your education? You can look at students who were accepted to institutions like Harvard and MIT but chose not to attend, and compare them with the students that were accepted and did choose to attend. Of course, these kinds of comparisons have to be done with appropriate statistical consideration. But their results are much more plausibly interpreted as causal, not just as a set of correlations. Here are some comments from Angrist in the interview that caught my eye.

    Peer Effects in High School? 

    I think people are easily fooled by peer effects. Parag, Atila Abdulkadiroglu, and I call it "the elite illusion." We made that the title of a paper. I think it's a pervasive phenomenon. You look at the Boston Latin School, or if you live in Northern Virginia, there's Thomas Jefferson High School for Science and Technology. And in New York, you have Brooklyn Tech and Bronx Science and Stuyvesant.

    And so people say, "Look at those awesome children, look how well they did." Well, they wouldn't get into the selective school if they weren't awesome, but that's distinct from the question of whether there's a causal effect. When you actually drill down and do a credible comparison of students who are just above and just below the cutoff, you find out that elite performance is indeed illusory, an artifact of selection. The kids who go to those schools do well because they were already doing well when they got in, but there's no effect from exposure to higher-achieving peers.

    How Much Does Attending a Selective College Matter? 

    I teach undergrad and grad econometrics, and one of my favorite examples for teaching regression is a paper by Alan Krueger and Stacy Dale that looks at the effects of going to a more selective college. It turns out that if you got into MIT or Harvard, it actually doesn't matter where you go. Alan and Stacy showed that in two very clever, well-controlled studies. And Jack Mountjoy, in a paper with Brent Hickman, just replicated that for a much larger sample. There isn't any earnings advantage from going to a more selective school once you control for the selection bias. So there's also an elite illusion at the college level, which I think is more important to upper-income families, because they're desperate for their kids to go to the top schools. So desperate, in fact, that a few commit criminal fraud to get their kids into more selective schools.

    Charter Schools and Takeovers

    The most common charter model is what we call a startup — somebody decides they want to start a charter school and admits kids by lottery. But an alternative model is the takeover. Every state has an accountability system with standards that require schools to meet certain criteria. When they fail to meet these standards, they're at risk of intervention by the state. Some states, including Massachusetts, have an intervention that involves the public school essentially being taken over by an outside operator. Boston had takeovers. And New Orleans is actually an all-charter district now, but it moved to that as individual schools were being taken over by charter operators.

    That's good for research, because you can look at schools that are struggling just as much but are not taken over or are not yet taken over and use them as a counterfactual. The reason that's important is that people say kids who apply to the startups are self-selected and so they're sort of primed to gain from the charter treatment. But the way the takeover model works in Boston and New Orleans is that the outside operator inherits not only the building, but also the existing enrollment. So they can't cherry-pick applicants. What we show is that successful charter management organizations that run successful startups also succeed in takeover scenarios.

    Angrist has developed the knack of looking for these ways of interpreting a given data set, sometimes called "natural experiments." For those trying to find such examples as a basis for their own research, he says: 

    One thing I learned is that empiricists should work on stuff that's nearby. Then you can have some visibility into what's unique and try to get on to projects that other people can't do. This is particularly true for empiricists who are working outside the United States. There's a temptation to just mimic whatever the Americans and British are doing. I think a better strategy is to say, "Well, what's special and interesting about where I am?"

    Finally, as a bit of a side note, I was intrigued by Angrist's neutral-to-negative take on the potential for machine learning in econometrics:

    I just wrote a paper about machine learning applications in labor economics with my former student Brigham Frandsen. Machine learning is a good example of a kind of empiricism that's running way ahead of theory. We have a fairly negative take on it. We show that a lot of machine learning tools that are very popular now, both in economics and in the wider world of data science, don't translate well to econometric applications and that some of our stalwarts — regression and two-stage least squares — are better. But that's an area of ongoing research, and it's rapidly evolving. There are plenty of questions there. Some of them are theoretical, and I won't be answering those questions, but some are practical: whether there's any value added from this new toolkit. So far, I'm skeptical.

    Josh has written for the Journal of Economic Perspectives a few times. Interested readers might want to follow up with:

    A version of this article first appeared on Conversable Economist.

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Price interviews Joshua Angrist in Econ Focus (First Quarter 2020, Federal Reserve Bank of Richmond, pp. 18-22)." 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    Interview with Joshua Angrist: Education Policy and Causality Questions

    Timothy Taylor
  • 3
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      string(45) "There Is No Equality Without Economic Freedom"
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    The promise of freedom without responsibility is, in reality, slavery without escape. We think we do what we want when, in reality, we do what we are told.

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    There Is No Equality Without Economic Freedom

    An interventionist government’s promise of equality is the recipe for stagnation because governments can only equalize down. They can only make the rich poorer, never the poor richer, thus weakening everyone.

    Defending free will, individual initiative, and freedom does not mean that we disregard society. Society is a conscious, personal choice by which we bring together our individual needs and purposes, driven by personal initiative, and choose to invest in a way to improve our lives. This ultimately delivers better results for the vast majority.

    Society doesn’t strive to make people the same, requiring us to surrender our individual rights. Society is not created to make everyone equal, but to make each of us able to achieve our individual best.

    Society and free will are not enemies. Society and absolute power are.

    A version of this article first appeared here

     

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We think we do what we want when, in reality, we do what we are told." 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    There Is No Equality Without Economic Freedom

    Daniel Lacalle
  • 4
    object(stdClass)#14548 (59) {
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      ["title"]=>
      string(90) "Interview with Emi Nakamura: Price Dynamics, Monetary and Fiscal, and COVID-19 Adjustments"
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      string(685) "

    Douglas Clement at the Minneapolis Federal Reserve offers one of his characteristically excellent interviews, this one with Emi Nakamura, titled "On price dynamics, monetary policy, and this `scary moment in history'” (May 6, 2020, Federal Reserve Bank of Minneapolis). Here are a few of Nakamura's comments that caught my eye, but there's much more in the full interview.

    " ["fulltext"]=> string(9637) "

    On the current macroeconomic situation

    It’s a scary moment in history. I thought the Great Recession that started in 2007 was going to be the big macroeconomic event of my lifetime, but here we are again, little more than a decade later. ... More than other recessions, this particular episode feels like it fits into the classic macroeconomic framework of dividing things into “shocks” and “propagation”—mainly because in this case, it’s blindingly clear what the shock is and that it is completely unrelated to other forces in the economy. In the financial crisis, there was much more of a question as to whether things were building up in the previous decade—such as debt and a housing bubble—that eventually came to a head in the crisis. But here that’s clearly not the case.

    Price rigidity at times of macroeconomic adjustment

    You might think that it’s very easy to go out there and figure out how much rigidity there is in prices. But the reality was that at least until 20 years ago, it was pretty hard to get broad-based price data. In principle, you could go into any store and see what the prices were, but the data just weren’t available to researchers tabulated in a systematic way. ...

    Once macroeconomists started looking at data for this broad cross section of goods, it was obvious that pricing behavior was a lot more complicated in the real world than had been assumed. If you look at, say, soft drink prices, they change all the time. But the question macroeconomists want to answer is more nuanced. We know that Coke and Pepsi go on sale a lot. But is that really a response to macroeconomic phenomena, or is that something that is, in some sense, on autopilot or preprogrammed? Another question is: When you see a price change, is it a response, in some sense, to macroeconomic conditions? We found that, often, the price is simply going back to exactly the same price as before the sale. That suggests that the responsiveness to macroeconomic conditions associated with these sales was fairly limited. ... 

    One of the things that’s been very striking to me in the recent period of the COVID-19 crisis is that even with incredible runs on grocery products, when I order my online groceries, there are still things on sale. Even with a shock as big as the COVID shock, my guess is that these things take time to adjust. ... he COVID-19 crisis can be viewed as a prime example of the kind of negative productivity shock that neoclassical economists have traditionally focused on. But an economy with price rigidity responds much less efficiently to that kind of an adverse shock than if prices and wages were continuously adjusting in an optimal way.

    What's does the market learn from Fed announcements of changes in monetary policy? 

    The basic challenge in estimating the effects of monetary policy is that most monetary policy announcements happen for a reason. For example, the Fed has just lowered interest rates by a historic amount. Obviously, this was not a random event. It happened because of this massively negative economic news. When you’re trying to estimate the consequences of a monetary policy shock, the big challenge is that you don’t really have randomized experiments, so establishing causality is difficult.

    Looking at interest rate movements at the exact time of monetary policy announcements is a way of estimating the pure effect of the monetary policy action. ...  Intuitively, we’re trying to get as close as possible to a randomized experiment. Before the monetary policy announcement, people already know if, say, negative news has come out about the economy.The only new thing that they’re learning in these 30 minutes of the [time window around the monetary policy] announcement is how the Fed actually chooses to respond. Perhaps the Fed interprets the data a little bit more optimistically or pessimistically than the private sector. Perhaps their outlook is a little more hawkish on inflation. Those are the things that market participants are learning about at the time of the announcement. The idea is to isolate the effects of the monetary policy announcement from the effects of all the macroeconomic news that preceded it. Of course, you have to have very high-frequency data to do this, and most of this comes from financial markets. ...

    The results completely surprised us. The conventional view of monetary policy is that if the Fed unexpectedly lowers interest rates, this will increase expected inflation. But we found that this response was extremely muted, particularly in the short run. The financial markets seemed to believe in a hyper hyper-Keynesian view of the economy. Even in response to a significant expansionary monetary shock, there was very little response priced into bond markets of a change in expected inflation. ... 

    But, then, we were presenting the paper in England, and I recall that Marco Bassetto asked us to run one more regression looking at how forecasts by professional forecasters of GDP growth responded to monetary shocks. The conventional view would be that an expansionary monetary policy shock would yield forecasts of higher growth. When we ran the regression, the results actually went in the opposite direction from what we were expecting! An expansionary monetary shock was actually associated with a decrease in growth expectations, not the reverse! ... When Jay Powell or Janet Yellen or Ben Bernanke says, for example, “The economy is really in a crisis. We think we need to lower interest rates” ... perhaps the private sector thinks they can learn something about the fundamentals of the economy from the Fed’s announcements. This can explain why a big, unexpected reduction in interest rates could actually have a negative, as opposed to a positive, effect on those expectations.

    The Plucking Model of Unemployment

    A feature emphasized by Milton Friedman is that the unemployment rate doesn’t really look like a series that fluctuates symmetrically around an equilibrium “natural rate” of unemployment. It looks more like the “natural rate” is a lower bound on unemployment and that unemployment periodically gets “plucked” upward from this level by adverse shocks. Certainly, the current recession feels like an example of this phenomenon.

    Another thing we emphasize is that if you look at the unemployment series, it appears incredibly smooth and persistent. When unemployment starts to rise, on average, it takes a long time to get back to where it was before. This is something that isn’t well explained by the current generation of macroeconomic models of unemployment, but it’s clearly front and center in terms of many economists’ thinking about the policy responses [to COVID-19]. A lot of the policy discussions have to do with trying to preserve links between workers and firms, and my sense is the goal here is to avoid the kind of persistent changes in unemployment that we’ve seen in other recessions.

    For more on Nakamura and her work, the Journal of Economic Perspectives has a couple of articles to offer.

    A version of this article first appeared on Conversable Economist

     
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Here are a few of Nakamura's comments that caught my eye, but there's much more in the full interview." 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    Interview with Emi Nakamura: Price Dynamics, Monetary and Fiscal, and COVID-19 Adjustments

    Timothy Taylor
  • 5
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      string(42) "Evolving Choices about Easing the Shutdown"
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      string(306) "

    I'll just say up front that the question of exactly when to ease the stay-at-home orders and shutdown in response to the coronavirus is a hard one, and I don't have a firm answer. But here's a framework for thinking through the tradeoffs.

    " ["fulltext"]=> string(15823) "

    Here are a couple of figures from Joseph Pagliari in a short and aptly-titled essay," No one has all the answers for COVID-19 policy: The trade-offs are evident, but the costs involved are ambiguous" (Chicago Booth Review, May 4, 2020). 

    The horizontal axis is the total length of the stay-at-home orders. The vertical axis measures human and economic costs. The dark blue line shows that the effect of the stay-at-home order at the start has a relatively big effect on reducing COVID-19 costs (including both health costs and costs of delivering health care). However, a short stay-at-home period of, say, a couple of weeks, would have imposed a relatively small level of "Quarantine-related gross costs" shown by the black line. As the stay-at-home period gets longer, the marginal benefits to improved health are somewhat lower, and the the quarantine-related costs start rising. Government can take some actions with spending and lending to reduce these quarantine-related costs, so that "net costs" are the green line rather than the black line--but the costs still rise.

    Evolving Choices about Easing the Shutdown

    Now, combine the cost lines to get a picture of "total cost." At the start of the pandemic, the total costs were mostly the COVID-19 costs. But at some point, the quarantine-related costs get large.



    Evolving Choices about Easing the Shutdown

    Some comments:

    1) These figures obviously have a high level of generality. There are no numbers on the axes! One might plausibly say that we aren't at either the extreme left or extreme right of the diagram, but where we are in the middle is unclear. There's also no presumption in the figure that the social goal should be to choose the length of the stay-at-home order where total costs are lowest, or where the dark-blue and light-blue lines cross. Any decision would have to place a value on the health benefits being received, and that value isn't shown here. A substantial degree of humility is appropriate both for those imposing stay-at-home and shutdown orders, and also by those opposing them.

    2) Some people object to having human and economic costs on the same scale. I strongly disagree. I remember the aftermath of the Great Recession when monthly unemployment rates were 9% or  higher for more than two years. If anyone had said at that time, "Well, these are just economic costs, not all that important compared to actual human costs," they would have been pilloried--and rightly so. The unemployment rate for April 2020 was 14.7%, and it may well be higher in May. Dismissing this as "an economic cost" seems benighted.

    It's easy enough to find studies showing direct economic costs of an economic slowdown. As one example, a couple of foundations--the Well Being Trust and the Robert Graham Center--published a report on "Projected Deaths of Despair from COVID-19"(May 8, 2020). Making projections over the next decade, they write: "Across the nine different scenarios, the additional deaths of despair range from 27,644 (quick recovery, smallest impact of unemployment on deaths of despair) to 154,037 (slow recovery, greatest impact of unemployment on deaths of despair)." I don't view these estimates as definitive, but they do illustrate that the quarantine costs are not just a matter of lower incomes, but are tightly connected to tens of thousands of additional deaths, as well.

    Moreover, there are lots of health effects that these estimates don't take into account, like the  children who are missing meals because the schools are closed, or not receiving vaccinations because of the stay-at-home policy focus, or whose families are falling into poverty. From an international perspective, the United Nations published a "Policy Brief:The Impact ofCOVID-19 on children" (April 15, 2020). It points out that 188 countries around the world have interrupted school, which affects 1.5 billion children. It also points out that the economic effects of the pandemic and the shelter-in-place rules are going to tip tens of millions of children around the world--most in countries that lack substantial social welfare programs--into extreme poverty. Rates of infant mortality and maternal mortality seem certain to rise. The tradeoffs of stay-at-home policies many not look the same across all countries of the world.

    3) Some people will feel uncomfortable with the shape of  the curves in the diagrams. Why do the COVID-19 health care costs fall, while the quarantine costs rise? Actually, the shape of the curves is based on the idea that the government has at least a decent sense of what it's doing. A supporter of government actions presumably believes that an effort was made to choose approaches that started off with the biggest gains to health and the smallest costs to the rest of the economy. Critics of government actions might counter with claims that the gains to health have been modest, or that other policies could have achieved similar gains with smaller quarantine costs to the economy.

    4) One reason why quarantine costs rise is that if the stay-in-place had lasted only a week or so, then having people return to their previous jobs would have been relatively easy. But many parts of the United States are now in their ninth week of stay-in-place, with talk of another month or two to come. You can't just put the economy on hold for a few months, and then flick it back on like a light switch. I've seen news stories talking about how as government rules are loosened, workers can then return to their jobs. But after a few months, many of them will not have jobs to come back to. Moreover, my guess is that job openings and hires will plummet in the next few months, as firms struggle to find their feet. 

    5) The diagrams above suggest a very real possibility that it will be sensible social policy to dramatically ease the stay-in-place and the lockdown policies while the number of cases and deaths from coronavirus remain substantial.  I sometimes read and hear comments from people that we need to keep the stay-at-home and lockdown policies in place "until there is a vaccine," or "until there is a treatment," or "until we have universal testing and contact tracing." I'm sympathetic to the all-American desire for a techno-fix that makes all this go away. But the most optimistic timelines I've seen for a vaccine or a sure-fire treatment are measured in months, while the pessimistic timelines are measured in years or "never." I'd like to see more testing, but rearranging our lives, work, schedules, and personal interactions based on a series of test results isn't going be simple. Those who want to wait for a techno-fix need to face the question of whether they are perhaps willing to wait years, and what health and financial costs society and the economy will bear in the meantime. Personally, I am quite confident that the right policy is not to keep the stay-at-home and shutdown policies until the COVID-19 line hits zero, while ignoring other costs being imposed.

    6) Political figures often seem to have a habit of re-fighting the previous battle and becoming stuck in place, which would be an unproductive approach here. Say that you have been arguing for a shutdown, or in fact have been implementing a shutdown, and have been receiving lots of criticism for doing so.  There's a natural human/political tendency to form sides--those favoring shut-down and those opposed. People on your side support each other. Phrases like "blood on your hands" get used. Even though the situation is evolving, sides get stuck in place. This would be deeply counterproductive. When the time comes to end the shutdown, it doesn't mean that it was wrong to start it in the first place, and it's not some admission that "the anti-shutdown forces were right all along." It just means that knowledge and conditions have evolved.

    7) Although our knowledge about the coronavirus remains frustratingly inconclusive, we do seem to know a few things. For example, it seems clear that the high-risk scenarios for transmission in involve indoor settings, where people are closely-spaced, that also lots of talking, singing, or yelling. Examples include workplaces with people in close quarters, especially if they involve needing to yell over loud sounds; big group events including weddings, funerals, bars, concerts, and church services; and institutional living from nursing homes to prisons. Conversely, the transmission scenarios seem quite low for those who are outdoors, or loosely spaced, or walking by people without talking. We also know that the health risks are much greater for those who are elderly or whose systems are immuno-compromised in some way, and the risks are near-zero for children and for healthy younger people. We know that you can help to protect yourself by taking Lady Macbeth as your role model for hand-washing, and that you can help to protect others by pulling something over your mouth, especially if you've got a cough. This knowledge has some obvious implications, like placing a very heavy emphasis on limiting transmission in nursing homes. 

    8) Many people, including me, are not great at thinking about risk, and perhaps especially about low-level risks. But in a broad sense, we should be able to agree that activities with low risks of transmitting the virus should be treated differently than activities with a high risk.   sometime sread and hear comments that the stay-at-home and lockdown should be intensified in every direction, usually backed up by a what-if story: "Sure, it's just some teenagers playing tennis, but one of them might be a carrier who breathes on the ball, and then the other person touches the ball and their own mouth, and then that other person takes the virus to their grandparents in the nursing home, and then dozens of people die." It could happen, of course. But you can draw up a doomsday scenario for pretty much every setting in which someone leaves their home for any purpose, and whether there's a pandemic or not, the costs of strict rules that seek to eliminate every low-probability doomsday scenario are just too high.

    9) James H. Stock has written a useful paper "Reopening the Coronavirus-Closed Economy" (May 2020, Hutchins Center Working Paper #60, Brookings Institution), with some general guidelines. Jim emphasizes four points:

    • Non-economic NPIs play a critical role in getting people back to work. There are important non-pharmaceutical interventions that, while individually limited, collectively hold the potential to substantially reduce the spread of the virus. These include social distancing; testing, contact tracing and quarantine; wearing masks; and having adequate personal protective equipment for workers in jobs that are unavoidably high-contact. None are a silver bullet, but collectively they can reduce the probability of transmission outside the workplace and thereby make room for getting people back to work and back to something more closely resembling normal economic activity.

    • Low-contact, high-value workplaces should be reopened quickly, and returning workers must feel safe. Many jobs are either low-contact or can be made so by suitable modifications of the workplace. In some cases, those modifications are low cost, like encouraging work-from-home, while in other cases they might entail some productivity reductions to facilitate worker distancing at work. When coupled with low-contact forms of transport to work, such jobs can be reopened quickly.

    • Some high-contact activities might need to be suspended indefinitely. Certain high-contact activities might require a hiatus until a vaccine and/or effective treatment is developed. These include both economic activities (for example, live fans at professional sports) and activities with less or no economic component.

    • Avoid a second dip that could induce severe long-term damage to workers and the economy. While reopening the economy is urgently needed, doing so in a way that leads to a second wave of deaths and a subsequent second shutdown could result in damage that is lasting and profound. Such damage has largely been avoided to date because of federal fiscal support and aggressive actions of the Federal Reserve. There are reasons to be pessimistic, however, that these levels of support would either be available or as effective in a second wave of deaths and closings, which could lead to those temporarily unemployed now becoming long-term unemployed without a job to return to, waves of bankruptcies, and severe strains on credit markets.

    A version of this article first appeared on Conversable Economist.

     

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But here's a framework for thinking through the tradeoffs." 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    Evolving Choices about Easing the Shutdown

    Timothy Taylor

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