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Recent Posts

Here are the 10 latest posts from EconLog.

EconLog April 3, 2020

The Good and Bad of Tucker Carlson

Along with a slight appreciation of Laura Ingraham.

Consistent with the spirit of my most recent post, “Socratic Grilling as a Way to Learn,” I watch the Fox News Channel a few times a week and often flip to CNN to see what they’re saying. On both networks, people spin like crazy. Which does not mean that you can’t learn from each.

I’ll give an example from last night, where I learned something important from one of Tucker Carlson’s interviews and also noticed how severely his nationalism and hostility to China can get in the way of clear thinking.

First, the good. Tucker interviewed Alex Berenson, a former reporter for the New York Times. Of course the subject was COVID-19. Berenson led with the caveat that he’s not an epidemiologist but that his expertise is another area: comparing predictions with what actually happened.

Berenson stated that a model used by the government in, I think, Washington state predicted about a week ago that the number of hospitalizations of COVID-19 patients in New York by yesterday would be about 50,000 whereas the actual number was 13,000. That’s incredibly valuable information, if true. It should cause people who follow that model to take a careful look at their model. Are they doing so? I have no idea.

Second, the bad. Later in the show, Tucker showed a segment in which an English-speaking doctor, an American, I believe, talked about how well the Chinese government had handled the crisis in Wuhan, where it originated. The doctor then went to suggest that we in American should bring over a few thousand of those Chinese doctors to help us here. Then Tucker did his signature laugh and stated that the doctor had said we should have doctors from China run our hospitals. My wife and I looked at each other like “What?” The doctor hadn’t even suggested that Chinese doctors run our hospitals. What he seemed to be saying is that we should hire them as inputs because they know a lot.

What I’ve noticed that is characteristic of Tucker: when the issue involves China or immigration, he loses his critical faculties. When it involves both, as this did to some extent, it’s almost a guarantee that he will lose his critical faculties.

I’ve not generally been a fan of Laura Ingraham but we watched her for more than a few minutes because lately she has been quite good at reminding her audience of the catastrophic costs of shutting down a huge percent of the economy. She was quite good on that yesterday. She also had on Alan Dershowitz, an emeritus professor of law at Harvard. Dershowitz made some good points about loss of liberty. As per usual, though, when he started to say things she didn’t like, Ingraham cut off the conversation pretty quickly. The particular thing here was his statement that it was not justified for some state governments to close down abortion clinics.

Note: Here’s a piece I wrote back in 2005, when I was more of a fan of Fox News Channel. I gave them 2 cheers. I think it’s now about 1.5 or maybe less.

(5 COMMENTS)

EconLog April 3, 2020

How to Win Friends and Influence People Book Club Commercial

I just shot this commercial for next week’s Book Club.  Enjoy!

 

(0 COMMENTS)

EconLog April 3, 2020

Our economy will likely reboot too slowly

My general view is that social distancing is better than an explosion of coronavirus cases. I believe we were too slow to begin social distancing, at least in hindsight. At the same time, I expect that after the worst phase of the epidemic is over we’ll do too much social distancing.

Suppose you saw a sign in a restaurant window saying, “Our restaurant has a smaller than average number of rats and cockroaches in our kitchen.” Does that make you more inclined to eat there? Obviously it should make you more inclined to eat there, but would it? Many people don’t even give any thought to rats and cockroaches in the kitchen when deciding where to eat. They’d be put off by that sign.  Gross!

The Chinese movie theatre industry was about to re-open last weekend, and then the government suddenly reversed course. This picture of a Chinese movie theatre caught my attention:

Those barriers that keep people separated obviously make the theatre safer. But I wonder if they make it seem less safe to the average filmgoer. I can picture my wife saying, “Well, if it’s so dangerous they need to separate people, then perhaps I’ll just stay home and watch Netflix.”

Our society doesn’t react very rapidly to hard to understand risks discussed by experts.  But when the risk becomes obvious, we tend to overreact. In a previous post, I argued that overreaction (from an individual risk perspective) was socially optimal in this case.  But that Chinese movie theatre picture (and the likely reaction of theatre patrons) makes me think that eventually we’ll go too far.  It would be optimal at some point to reboot our economy if we could keep the R0 factor (virus reproduction) below 1.0.  Do lots of little things like what we see in the picture above.  But I wonder if our extreme risk aversion will demand an even higher standard, closer to zero risk.

(5 COMMENTS)

EconLog April 3, 2020

Socratic Grilling as a Way to Learn

Scott Alexander, over at slatestarcodex.com, has hit a number of home runs in the last few weeks. I want to focus on his March 6 post, “Socratic Grilling.” To follow what I’m going to say, you need to read his post first. His posts are often very long, but the March 6 one is relatively short.

I’ve been practicing my own version of what Scott calls Socratic grilling since about the age of 5. I badly wanted to understand things around me. Even though I learned to read at age 5, I wasn’t much of a reader and, although we had a public library in my town of 1,200 people, it was a small library. For my first few years of reading, I focused on Hardy Boys and Nancy Drew books.

My way of learning was not to read but to ask adults around me to explain things. When I got only a few thoughts that seemed to fit, I would then adopt a position and argue it, being open to being shown that that was wrong. You could say I was a Bayesian. I found it much easier to take definite positions than to be agnostic because if I was agnostic, I was less motivated to find the truth. I’m still that way.

EconLog April 2, 2020

“This isn’t the last such crisis we’ll have”

Actually, it very likely is. The first and the last.

AFAIK, the world has never had a global pandemic where vast numbers of people stopped working out of fear of becoming infected. We have had pandemics where vast numbers of people stopped working because they were dead. But that’s nothing like what we have today.  (The Spanish flu was associated with only a very brief and mild recession.)

As for the future, who can say? We now have a company that has a million thermometers in circulation, all linked to a central database. It picked up the oncoming disaster in America well before most other people, but its warnings were ignored by the government. Now this company says that the number of high fevers in America is falling fast. We shall see.

Does anyone doubt that this is the wave of the future—connecting IT with medicine? That we’ll be able to spot epidemics in real time?  Does anyone doubt that in the future our ability to test huge numbers of people for viruses will be scaled upward dramatically? It was 102 years between the Spanish flu and this epidemic. Say it’s another 57 or 91 or 114 years until the next big one. Does anyone feel confident predicting what health care will look like that far into the future?

EconLog April 2, 2020

Tomorrow’s Reported Unemployment Rate for March

Tomorrow morning, when the Bureau of Labor Statistics reports the unemployment rate for March, don’t be surprised if it’s very low. I predict that it will be not much more than 4 percent and maybe even less. But that statistic will not really tell you much about the unemployment rate in March.

Here’s why. As the BLS explains on its web site:

Each month, highly trained and experienced Census Bureau employees contact the 60,000 eligible sample households and ask about the labor force activities (jobholding and job seeking) or non-labor force status of the members of these households during the survey reference week (usually the week that includes the 12th of the month).

Almost all the layoffs happened after March 14.

But the unemployment rate for April that will be reported on May 1, which, ironically, is known as International Workers Day? OMG!

(3 COMMENTS)

EconLog April 2, 2020

Home is Where the Zoning Is

“I don’t know how you get people back to realizing that when I buy a piece of property I have some say in what I can do on my property, but I don’t have the right to control what my neighbors do with their property.” Jenny Schuetz

 

It’s said that moving homes is one of the most stressful life experiences we can endure. This week’s episode may shed some light on why. EconTalk host Russ Roberts welcomes Jenny Schuetz, whose work focuses on land use and housing. The conversation is based in part on a recent article Schuetz wrote on what we can learn about housing from Little Women. What are these lessons Schuetz thinks we’ve missed in the 21st century? Why aren’t property rights enough to determine how land is used, and what sort(s) of housing options it might support? Why can’t we address the problem of homelessness in urban areas more effectively? And how have we turned some of our most beloved urban centers into nothing more than “museums” for the wealthy to enjoy?

 

Let’s hear what you think about these challenging issues. Use the conversation starters below to get you going.

 

 

1- What are some of the regulatory barriers to new home building Schuetz describes, and which do you  think are the most pernicious? Why?

 

2- What lesson(s) are we to learn from the Great Recession about housing, according to Schuetz? Why has the number of real estate development firms gone down since the Great Recession?

 

3- How does the bootlegger and Baptist theory apply to housing development? Schuetz says, “…the problem is: The only people who get to vote, who get to put direct political pressure on elected officials, are the people who already live there. The people who would benefit from the new housing live in another jurisdiction altogether.” What does she mean, and what are some of the consequences of this?

 

4- How are zoning and land use regulations contributing to increasing rates of homelessness? Why do both Roberts and Schuetz insist it’s NOT appropriate to blame “greedy landlords” for people not being able to afford housing? To what extent do you agree?

 

5- Roberts asks Schuetz why zoning and land use regulations have become so much more restrictive over the past several decades. How does she respond? Similarly, he asks what she thinks ought be done. How does Schuetz advocate the use of “fiscal tools” to change people’s behavior? To what extent does she convince you?

 

(0 COMMENTS)

EconLog April 2, 2020

Pandemics and the Problem of Expert Failure (cont.)

Part 3: Should Experts Have Power?

In my last two EconLog essays (here and here), I examined some of the causes of expert failure seemingly at work in the present crisis. I pointed out that we don’t know how to strike a balance among the different expert silos such as medicine and economics. And I pointed out that in many areas of expertise, state-supported professional associations enforce uniformity of opinion so that we don’t get the sort of flexible thinking and multiple perspectives we need even more urgently now than in normal times. I don’t know which epidemiological models are best. And nobody knows the best policy package. We cannot somehow escape the urgent necessity of making collective choices to fight COVID-19. In this difficult moment, we should be respectful of the extreme difficulty of formulating policy. In the midst of it all, however, we should also reflect on how very hard it has been to wisely deploy expertise in a crisis. Is there a better way?

I think we have made our lives harder – and put them at greater risk – by trying to contain expertise in officially recognized boxes controlled by the very experts ensconced within them. I refer to the “expertists template” ofcertification, professional education, and continuing education that I described in my previous essay in this series. When expertise is organized into state-supported professional organizations such as the AMA, it tends to enforce orthodoxy. And that means less pliable, flexible, and adaptive thinking. It means less tinkering and more doctrine. Oops.

The expertist template is premised on the view that knowledge is hierarchical. It starts at the top with science and cascades down to ever lower levels of the knowledge hierarchy. Mere practitioners must not question theknowledge elite. But questioning is precisely what we need in crises. In his essay, “What is Science?” Richard Feynman remarked “Science is the belief in the ignorance of experts.” When we give experts power, including the power to decide who the experts are, we choke off science. The premise of a rigid hierarchy of knowers is mistaken. The knowledge we need in normal times and crisis times alike is distributed. It’s out there in thee and me and in all our habits practices and experience. It is not a set of instructions and doctrines coming from on high. It arises of its own from our many decentralized interactions. 

Let’s take an example. The pandemic has produced a shortage of “personal protective equipment” (PPE) such as masks and gowns. What can we do? One very helpful solution comes out of a relatively small company in Ohio, Battelle. They have amachine that can clean large quantities of PPE in a hurry. The knowledge of how to do it did not come down from scientific inquiry, but up from entrepreneurial action. And yet, as I write, the knowledge elite at the FDA “has authorized Columbus-based Battelle to sterilize only 10,000 surgical masks in Ohio each day, despite their ability to sterilize up to 160,000 masks per day in Ohio alone.” The official knowledge hierarchy is squelching the sort of adaptive tinkering that we need to improvise our way out of this mess.  

This distributed quality of expertise follows from its source in the division of labor. As I said in the first essay of this series, the division of knowledge is the flip side of the division of labor. But that means that is it not some simple hierarchy dictated from on high. It is emergent, protean, and evolving. It does not cascade down, it bubbles up. 

Consider ventilators. March 24th, the FDAlifted many of restrictions on ventilators. Hospitals have been restricted to using only “FDA-cleared ventilators.” The lifting of restrictions reveals the folly of pretending that the knowledge elite can pre-decide what medical equipment is acceptable. Just as they could not reasonably have foreseen the current pandemic, they cannot reasonably foresee the many idiosyncratic particulars of time and place that might turn otherwise sensible regulations into life-threatening folly. If there had been no such restrictions in the first place, how many new emergency ventilators might have long since arrived in our hospitals? Instead, we have seen “ventilator sharing.” And can we be sure that there are no remaining restrictions that should also be lifted? You still require FDA approval; it’s just that the FDA approves more things.  

We need a better way. We need a resilient system in which local knowledge comes with local decision-making authority. But, how do we get there? Because we have had a relatively controlled and hierarchical system, markets have not had much opportunity to work up the sort of institutions and arrangements we need when choosing among experts. If we just tear down the expertist template, we will be left without guidance. Let us set to work then, at the hard task of learning how to dispense with the expertist template and return power and energy to entrepreneurialism. 

 

 


Roger Koppl is Professor of Finance in the Whitman School of Management of Syracuse University and Associate Director of Whitman’s Institute for an Entrepreneurial Society (IES).

(14 COMMENTS)

EconLog April 2, 2020

Teaching Teaching

Over the last three years, my older sons have gone from near-zero knowledge of Spanish to fluency.  Given my open disdain for foreign language education, what’s the backstory?

I started them in 9th grade because almost all good colleges impose an admission requirement of 3-4 years of foreign language instruction.  From the outset, my boys planned to demonstrate their competence on the Spanish Language AP test.  Going through the motions would not suffice; we knew my sons actually had to learn a lot of Spanish.  After a few sour months, fortunately, my sons started to like their new subject.  Then they became obsessed… in a good way.  Now they’ve taken college classes for natives in Spain and Guatemala, written a publishable paper on Mexican history using primary sources, and mostly speak Spanish to each other.

Since our emergency homeschool contains these two fluent Spanish-speakers, I thought it might be fruitful for my older sons to teach Spanish to their younger siblings.  After all, the younger ones are going to need a foreign language for college one day, too.

The catch: When Spanish instruction began last week, I realized that my older sons knew Spanish, but not how to teach.  As a result, I’m teaching teaching while they’re teaching Spanish.  Since I’ve been teaching professionally for about 25 years, its principles are second nature to me.  Yet if you’re now teaching for the first time in your life, they’re non-obvious.  Indeed, in my experience, over half of working teachers fail to internalize them.  As Morpheus admonishes in The Matrix, “Neo, sooner or later you’re going to realize, just as I did, that there’s a difference between knowing the path and walking the path.”

Principles of Effective Teaching

  1. Take the difficulty level you naturally want to use.  Now divide it by 10.  Remember: The material is only obvious to you because you are the teacher.  It is non-obvious to your students because they are the students.

  2. If you’re teaching at MIT or Caltech, you are now at the right difficulty level.  If you’re anywhere else, divide by 10 again.  Remember: Even smart people are, at first, terrible at almost everything.

  3. Don’t expects students to “figure things out for themselves.”  Start with model problems, then work through them at a snail’s pace.

  4. Once you have shown students clear model problems, assign a bunch of slightly different problems.  Tell them to get to work.  Mush!

  5. If your students do less than 75% of their problems correctly, your problems are still too hard.  Walk them through problems so easy you can’t even imagine their inability to do them.  This will improve their knowledge and your imagination.

  6. If your students do 75-94% of their problems correctly, give them more practice.  Drill, drill, drill.

  7. If your students do 95% of their problems correctly, they are ready to advance.  Even then, remember that they are likely to forget unless you periodically give them refresher work (except for highly sequential subjects).

  8. Never confuse logic with psycho-logic – and remember that psycho-logic is much more important for pedagogy.  What does that mean?  Don’t expect students to grasp that A–\B simply because A–\B.  Your job is to make truisms seem obvious to ignorant minds.  Vary your examples.  Mix it up.  Switch around.  Use repetition.  Use repetition.  Use repetition.

  9. Look at your students’ faces.  If they are bored, be more fun.  Tell jokes.  Mock yourself.  Clown around.  Playfully exaggerate all emotions.  Throw your pride aside; a teacher is an entertainer or he is a failure.

  10. Look at your students’ faces.  If they are frustrated, be more patient.  Never add negative emotion on top of negative emotion.  If a student is upset, be a model of mild-mannered stoicism.  Without fail.  Without fail.  Without fail.

  11. Look at your students’ faces.  If they feel like their efforts are pointless, sell them your subject.  Tell them what learning your subject will do for them, even if the only honest answer is, “You need this for graduation.”

  12. Look at your students’ faces.  If they don’t trust you, earn their trust.  Don’t merely avoid deception; be frank.  Don’t sugarcoat the world, even for little kids.  Unless the ugly truth will give them nightmares or get you fired, share it with equanimity.

  13. Look at your students’ faces.  If you can’t read their emotions, ask them questions.  Press them.  Find out what they already know.  Find out what confuses them.  Find out whether they are happy or sad or think you’re crazy.  Accept their answers beatifically and adjust your pedagogy to fit the students you actually have.

  14. Maintain discipline.  If you have a schedule, stick to it.  If you announce a punishment, stick to it.  If you promise a break, stick to it.  Education is for the students, but it is not a democracy.  Listen carefully to what your students stay, but only reform from a position of strength.  Don’t be generous; be magnanimous!  If you think this contradicts Principle #9, know that you are wrong.  Act like a jester – but rule like a king.

  15. All of these principles are optimized for one-on-one teaching.  If you’re teaching more students, you have to strike a balance.  You will always shortchange someone.  Sorry, that’s a classroom – another point in favor of homeschooling.

 

(5 COMMENTS)

EconLog April 1, 2020

Government Regulation of Poorer Entrepreneurs

Timothy Taylor over at Conversable Economist hits another home run with his lengthy excerpts from Harvard economist Edward Glaeser’s presidential address to the Eastern Economic Association. The speech is titled “Urbanization and Its Discontents.”

Although the whole post is well worth reading, here’s one paragraph that caught my attention:

Somewhat oddly, much of America appears to regulate low human capital entrepreneurship much more tightly than it regulates high human capital entrepreneurs. When Mark Zuckerberg started Facebook in his Harvard College dormitory, he faced few regulatory hurdles. If he had been trying to start a bodega that sold milk products three miles away, he would have needed more than ten permits. One question is whether the inequality that persists in America’s system is exacerbated by the legal and regulatory system.

I have three comments.

First, wow! Isn’t that interesting? It’s one more example of the government going after fledgling entrepreneurs trying to make a buck.

Second, sometimes when critics point out that government hurts poorer people, others conclude that the critics think government should hurt rich people too. I don’t. I’m glad that Zuckerberg was free to start Facebook. I just want everyone to be at least as free as he was. I would put a 0.9 probability on the idea that Glaeser agrees with me.

Third, this reminds me of a section in a classic 1989 article by Clive Crook in The Economist on third world economic development. The article was so good that I hired Clive to do a shorter version for the first edition of The Concise Encyclopedia of Economics, which was then called The Fortune Encyclopedia of Economics. The article, “Third World Economic Development,” is here. One of the things Clive pointed out is that a typical government policy in some African countries was to set tough price controls on the products of poor rural farmers to help the less-poor urban consumers. An excerpt:

Between 1963 and 1979 the price of consumer goods went up by a factor of twenty-two in Ghana. The price of cocoa in neighboring countries went up by a factor of thirty-six. But the price paid by the cocoa marketing board to Ghana’s farmers went up just sixfold. In real terms, therefore, the returns to cocoa farmers vanished. The country’s supposedly price-insensitive farmers responded by switching to production of other crops for subsistence, and exports of cocoa collapsed. Peru and Ghana are extreme cases, but they show in the starkest way that prices do matter in the the Third World and that rejecting market economics carries extremely high costs.

It’s not quite analogous to restrictions on poorer entrepreneurs in the United States because the U.S. restrictions hurt their putative customers as well as the entrepreneurs. Price controls on African farmers also hurt some consumers who are left out but help those who are first in line.

(8 COMMENTS)

Here are the 10 latest posts from EconTalk.

EconTalk March 30, 2020

Jenny Schuetz on Land Regulation and the Housing Market

housing-design.jpgJenny Schuetz of the Brookings Institution talks with EconTalk host Russ Roberts about zoning, boarding houses, real estate development, and the housing market.

EconTalk March 23, 2020

Azra Raza on The First Cell

The-First-Cell-198x300.jpg Author and oncologist Azra Raza talks about her book The First Cell with EconTalk host Russ Roberts. Raza argues that we have made little progress in fighting cancer over the last 50 years. The tools available to oncologists haven’t changed much–the bulk of the progress that has been made has been through earlier and earlier […]

EconTalk March 19, 2020

Tyler Cowen on the COVID-19 Pandemic

coronavirus-2-300x170.jpgEconomist and infovore Tyler Cowen of George Mason University talks with EconTalk host Russ Roberts about the political, social, and economic aspects of the COVID-19 pandemic.

EconTalk March 16, 2020

Isabella Tree on Wilding

Author and conservationist Isabella Tree talks about her book Wilding with EconTalk host Russ Roberts. Tree and her husband decided to turn their 3500 acre farm, the Knepp Castle Estate, into something wilder, a place for wild ponies, wild pigs, wild oxen, and an ever-wider variety of birds and bugs. The conversation covers the re-wilding […]

The post Isabella Tree on Wilding appeared first on Econlib.

EconTalk March 9, 2020

Richard Davies on Extreme Economies

Extreme-Economies-195x300.jpg Economist and author Richard Davies talks about his book Extreme Economies with EconTalk host Russ Roberts. The conversation explores economic life in extreme situations. Examples discussed are the Angola State Penitentiary in Louisiana, two Syrian refugee camps in Jordan, the rain forest in the Darien Gap in Panama, and Kinshasa, the largest city in the […]

EconTalk March 2, 2020

Yuval Levin on A Time to Build

A-Time-to-Build.jpg Author and political scientist Yuval Levin of the American Enterprise Institute talks about his book A Time to Build with EconTalk host Russ Roberts. Levin argues that institutions in America are less trustworthy than they have been in the past. The cause, in Levin’s view, is that the participants in these institutions no longer see […]

EconTalk February 24, 2020

Richard Robb on Willful

Willful-200x300.jpgEconomist, author, and investor Richard Robb talks about his book Willful with EconTalk host Russ Roberts. Robb is interested in what motivates and explains the choices we make. He explores alternatives to the optimizing model of economics including what he calls “for-itself” behavior–behavior that isn’t purposive. Topics discussed in this wide-ranging conversation include the nature […]

EconTalk February 17, 2020

Peter Singer on The Life You Can Save

The-Life-You-Can-Save-188x300.jpgPhilosopher and author Peter Singer of Princeton University talks about his book, The Life You Can Save with EconTalk host Russ Roberts. Singer argues that those of us in the developed world with a high standard of living can and should give/forgo some luxuries and donate instead to reduce poverty and suffering in poor countries. […]

EconTalk February 10, 2020

Marty Makary on the Price We Pay

The-Price-We-Pay-198x300.jpgPhysician and author Marty Makary of Johns Hopkins University talks about his book The Price We Pay with EconTalk host Russ Roberts. Makary highlights some of the stranger aspects of our current health care system including the encouragement of unnecessary or even harmful procedures and the predatory behavior of some hospitals who sue patients and […]

EconTalk February 3, 2020

Robert Shiller on Narrative Economics

Narrative-Economics-199x300.jpg Economist, author, and Nobel Laureate Robert Shiller of Yale University discusses his book Narrative Economics with EconTalk host Russ Roberts. Shiller proposes a novel idea–that the narratives that people believe and use to understand the world affect their economic behavior and in turn affect the macroeconomy. Shiller argues that taking these psychological effects into account […]

Here are the 10 latest posts from CEE.

CEE March 24, 2020

Harold Demsetz

Harold Demsetz made major contributions to the economics of property rights and to the economics of industrial organization. He also coined the term “the Nirvana approach.” Economists have altered it slightly but use it widely. Demsetz was one of the few top economists of his era to communicate almost entirely in words and not math. Demsetz also defended both economic freedom and civil liberties.

One of Demsetz’s most important contributions was a 1967 article, “Toward a Theory of Property Rights.” In it, he argued that property rights tend to develop where the gains from defining and enforcing those rights exceed the costs. He found confirming evidence in the presence or absence of property rights among native Americans and native Canadians, and he dismissed the idea that they were primitive people who couldn’t understand or appreciate property rights. Instead, he argued, they developed property rights in areas of North America where the property was worth defending.

Drawing on anthropological research, Demsetz noted that, although the native Canadians (Canadians often call them First Nations people) in Labrador had property rights in the early 18supth/sup century, they did not have property rights in the mid-17supth/sup century. What changed? Demsetz argued that the advent of the fur trade in the late 17supth/sup century made it more valuable to establish property rights so that the beavers were not overtrapped. By contrast, native Americans on the southwestern plains of the United States did not establish property rights; Demsetz reasoned that it was because the animals they hunted wandered over wide tracts of land and, therefore, the cost of establishing property rights was prohibitive.

In the 1960s, the dominant view in the area of economics called industrial organization was that concentration in industries was bad because it led to monopoly. In the 1970s, Demsetz challenged that view. He argued that the kind of monopoly to worry about is caused by government regulation that prohibits firms from entering an industry. He pointed to the Civil Aeronautics Board’s restrictions on entry by new airlines and the Federal Communication Commission’s hobbling of cable TV as examples. He wrote, “The legal route of monopoly runs through Washington and the state capitals.” But, he argued, if a few firms achieved a large market share through economies of scale or through superior performance, we should not worry, and the antitrust officials should not go after such firms. As long as the government doesn’t restrict new competitors, firms with a large market share will face competition in the future.

In a 1969 article, “Information and Efficiency: Another Viewpoint,” Demsetz accused fellow economist Kenneth Arrow of taking the “Nirvana approach” and recommended instead a “comparative institutions approach.” He wrote, “[T]hose who adopt the nirvana viewpoint seek to discover discrepancies between the ideal and the real and if discrepancies are found, they deduce that the real is inefficient.” Specifically, Arrow showed ways in which the free market might provide too little innovation, but then simply assumed that government intervention would get the economy closer to the optimum. Demsetz conceded that ideal government intervention might improve things, but he noted that Arrow, like many economists, had failed to show that actual government intervention would do so. Economists have slightly changed the label on Demsetz’s insight: they now refer to it as the “Nirvana fallacy.”

Another major Demsetz contribution was his thinking about natural monopoly, evidenced best in his 1968 article “Why Regulate Utilities?” In that article, Demsetz stated that the theory of natural monopoly “is deficient for it fails to reveal the logical steps that carry it from scale economies in production to monopoly price in the market place.” How so? Demsetz argued that competing providers could bid to be the single provider and that consumers, if well organized, could choose among competing providers. The competition among potential providers would prevent the winning provider from charging a monopoly price.

Economists often use negative externalities as a justification for government regulation. One standard example is pollution; in their actions, polluters do not take into account the damage imposed on others. Demsetz pointed out that governments also impose negative externalities. In the above-mentioned 1967 article on property rights, Demsetz wrote, “Perhaps one of the most significant cases of externalities is the extensive use of the military draft. The taxpayer benefits by not paying the full cost of staffing the armed services.” He added, “It has always seemed incredible to me that so many economists can recognize an externality when they see smoke but not when they see the draft.” Demsetz was a strong opponent of the draft.

One of Demsetz’s other contributions, co-authored with Armen A. Alchian, was his 1972 article “Production, Information Costs, and Economic Organization.” A 2011 article written by three Nobel Prize winners—Kenneth J. Arrow, Daniel L. McFadden, and Robert M. Solow—and three other economists—B. Douglas Bernheim, Martin S. Feldstein, and James M. Poterba, stated that this article was one of the top 20 articles publishes in the American Economic Review in the first 100 years of its existence. In it, Alchian and Demsetz proposed the idea that the reason to have firms is that team production is important and monitoring the productivity of team members is difficult. Therefore, they argued, firms, to be effective, must have people in the firm who monitor and who are residual claimants. These people, often, but not always, the owners, get some fraction of the profits of the firm and, therefore, have an incentive to monitor effectively. That helps solve the classic principal-agent problem.

In a famous 1933 book titled The Modern Corporation and Private Property, Adolf A. Berle and Gardiner C. Means had argued that diffusion of ownership in modern corporations gave managers of large corporations more control, shifting it from the owners. These managers, they argued, would use that control to benefit themselves. Demsetz and co-author Kenneth Lehn questioned that reasoning. They argued that owners would not give up control without getting something in return. If Berle and Means were correct, they wrote, then one should observe a lower rate of profit in firms with highly diffused ownership. But if Demsetz and Lehn were correct, one should see no such relationship because diffused ownership would happen where there were profitable reasons for it to happen. They wrote:

A decision by shareholders to alter the ownership structure of their firm from concentrated to diffuse should be a decision made in awareness of its consequences for loosening control over professional management. The higher cost and reduced profit that would be associated with this loosening in owner control should be offset by lower capital costs or other profit-enhancing aspects of diffuse ownership if shareholders choose to broaden ownership.

Demsetz and Lehn found “no significant relationship between ownership concentration and accounting profit rate,” just as they expected.

In a 2013 tribute to Demsetz’s co-author Alchian, economist Thomas Hubbard highlighted their 1972 article, writing:

This paper may be the most influential paper in the economics of organization, catalyzing the development of the field as we know it. It is the most-cited paper published in the AER [American Economic Review] in the past 40 years. (If one takes away finance and econometrics methods papers, it is the most-cited ‘economics’ paper, period.) It is truly a spectacular piece. It is a theory not only of firms’ boundaries, but also the firm’s hierarchical and financial structure.[1]

He was also an early defender of the rights of homosexuals. At the September 1978 Mont Pelerin Society meetings in Hong Kong, Demsetz criticized, on grounds of individual rights, the Briggs Initiative, on the November 1978 California ballot. This initiative, which California voters defeated, would have banned homosexuals from teaching in public schools.  The initiative was defeated, helped by the opposition of Demsetz’s fellow Californian Ronald Reagan.

Demsetz, a native of Chicago, earned his undergraduate degree in economics at the University of Illinois in 1953 and his Ph.D. in economics at Northwestern University in 1959. He taught at the University of Michigan from 1958 to 1960, at UCLA from 1960 to 1963, at the University of Chicago from 1963 to 1971, and then again at UCLA from 1971 until his retirement. In 2013, he was made a Distinguished Fellow of the American Economic Association.

In 1963, when Demsetz was on the UCLA faculty, a University of Chicago economist named Reuben Kessel asked him if he was happy there. Demsetz, sensing an offer in the works, answered, “Make me unhappy.” The University of Chicago did just that, and Demsetz moved to Chicago for eight productive years.

 

 

Selected Works

  1. . “Minorities in the Marketplace.” North Carolina Law Review, Vol. 43, No. 2: 271-97.

  2. . “Toward a Theory of Property Rights.” American Economic Review, Vol. 57, No. 2, (May, 1967): 347-59.

  3. . “Why Regulate Utilities?” Journal of Law and Economics,Vol. 11, No. 1, (April, 1968): 55-65.

1972 (with Armen A. Alchian). “Production, Information Costs, and Economic Organization,” American Economic Review, Vol. 62, No. 5, (December 1972): 777-95.

  1. . “Industry Structure, Market Rivalry, and Public Policy,” Journal of Law and Economics,Vol. 16, No. 1 (April, 1973): 1-9.

  2. . ‘Two Systems of Belief about Monopoly,” in Industrial Concentration: The New Learning, edited by H. J. Goldschmid, H. M. Mann and J. F. Weston, Little, Brown.

1985 (with Kenneth Lehn). “The Structure of Corporate Ownership: Causes and Consequences,” Journal of Political Economy, Vol. 93, No. 6 (December, 1985): 1155-1177.

  1. . Ownership, Control, and the Firm. Cambridge, MA: Basil Blackwell.

  2. . Efficiency, Competition, and Policy. Cambridge, MA: Basil Blackwell.


[1] Thomas N. Hubbard, “A Legend in Economics Passes,” Digitopoly, February 20, 2013. At: https://digitopoly.org/2013/02/20/a-legend-in-economics-passes/

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CEE July 19, 2019

Richard H. Thaler

 

Richard H. Thaler won the 2017 Nobel Prize in Economic Science for “his contributions to behavioral economics.”

In most of his work, Thaler has challenged the standard economist’s model of rational human beings.  He showed some of the ways that people systematically depart from rationality and some of the decisions that resulted. He has used these insights to propose ways to help people save, and save more, for retirement. Thaler also advocates something called “libertarian paternalism.”

Economists generally assume that more choices are better than fewer choices. But if that were so, argues Thaler, people would be upset, not happy, when the host at a dinner party removes the pre-dinner bowl of cashews. Yet many of us are happy that it’s gone. Purposely taking away our choice to eat more cashews, he argues, makes up for our lack of self-control. This simple contradiction between the economists’ model of rationality and actual human behavior, plus many more that Thaler has observed, leads him to divide the population into “Econs” and “Humans.” Econs, according to Thaler, are people who are economically rational and fit the model completely. Humans are the vast majority of people.

Thaler (1980) noticed another anomaly in people’s thinking that is inconsistent with the idea that people are rational. He called it the “endowment effect.” People must be paid much more to give something up (their “endowment”) than they are willing to pay to acquire it. So, to take one of his examples from a survey, people, when asked how much they are willing to accept to take on an added mortality risk of one in one thousand, would give, as a typical response, the number 10,000. But a typical response by people, when asked how much they would pay to reduce an existing risk of death by one in one thousand, was 200.

One of Thaler’s most-cited articles is Werner F. M. De Bondt and Richard Thaler (1985). In that paper they compared the stocks of “losers” and “winners.” They defined losers as stocks that had recently dropped in value and winners as stocks that had recently increased in value, and their hypothesis was that people overreact to news, driving the prices of winners too high and the prices of losers too low. Consistent with that hypothesis, they found that the portfolio of losers outperformed the portfolio of winners.

One of the issues to which Thaler applied his thinking is that of saving for retirement. In his book Misbehaving, Thaler argues that if everyone were an Econ, it wouldn’t matter whether employers’ default option was not to sign up their employees for tax-advantaged retirement accounts and let them opt in or to sign them all up and let employees opt out. There are transactions costs associated with getting out of either default option, of course, but they are small relative to the stakes involved. For that reason, argued Thaler, either option should lead to about the same percentage of employees taking advantage of the program. Yet Brigitte G. Madrian and Dennis F. Shea found[1] that before a company they studied had tried automatic enrollment, only 49 percent of employees had joined the plan. When enrollment became the default, 84 percent of employees stayed enrolled. That is a large difference relative to what most economists would have expected.

Thaler and economist Shlomo Benartzi, arguing that people tend to be myopic and heavily discount the future, helped design a private pension plan to enable people to save more. Called Save More Tomorrow, it automatically increases the percent of their gross pay that people save in 401(k) plans every time they get a pay raise. That way, people can save more without ever having to cut their current consumption expenditures. Many “Econs” were presumably already doing that, but this plan helps Humans, as well. When a midsize manufacturing firm implemented their plan, participants, at the end of four annual raises, had almost quadrupled their saving rate.

In their book Nudge, Thaler, along with co-author Cass Sunstein, a law professor, used behavioral economics to argue for “nudging” people to make better decisions. In each person, they argued, are an impulsive Doer and a farsighted Planner. In the retirement saving example above, the Doer wants to spend now and the Planner wants to save for retirement. Which preferences should be taken account of in public policy?

As noted earlier, Thaler believes in “libertarian paternalism.” In Nudge, he and Sunstein lay out the concept. The basic idea is to have the government set paternalist rules as defaults but let people choose to opt out at low cost. One example is laws requiring motorcyclists to wear helmets. That is paternalism. How to make it “libertarian paternalist?” They favorably cite New York Times columnist John Tierney’s proposal that motorcyclists who don’t want to wear helmets be required to take an extra driving course and show proof of health insurance.

In a review of Nudge, Thomas Leonard writes:

The irony is that behavioral economics, having attacked Homo Economicus as an empirically false description of human choice, now proposes, in the name of paternalism, to enshrine the very same fellow as the image of what people should want to be. Or, more precisely, what paternalists want people to be. For the consequence of dividing the self has been to undermine the very idea of true preferences. If true preferences don’t exist, the libertarian paternalist cannot help people get what they truly want. He can only make like an old fashioned paternalist, and give people what they should want.[2]

In some areas, Thaler seems to have departed from the view that long-term considerations should guide economic policy. A standard view among economists is that after a flood or hurricane, a government should refrain from imposing price controls on crucial items such fresh water, food, or plywood. That way, goes the economic reasoning, suppliers in other parts of the country have an incentive to move goods to where they are needed most and buyers will be careful not to stock up as much immediately after the flood or hurricane. In 2012, when asked about a proposed anti-price-gouging law in Connecticut, Thaler answered succinctly, “Not needed. Big firms hold prices firm. ‘Entrepreneurs’ with trucks help meet supply. Are the latter covered? If so, [the proposed law is] bad.”[3] What he was getting at is that, to some extent, we get the best of both worlds. Companies like Wal-Mart, worried about their reputation with consumers, will refrain from price gouging but will stock up in advance; one-time entrepreneurs, not worried about their reputations, will supply high-priced items to people who want them badly. But in a Marketplace interview in September 2017,[4] Thaler said, “A time of crisis is a time for all of us to pitch in; it’s not a time for all of us to grab.” He seemed to have moved from the mainstream economists’ view to the popular view.

One relatively unexplored area in Thaler’s work is how government officials show the same irrationality that many of us show and the implications of that fact for government policy.

Thaler earned his Bachelor of Arts degree with a major in economics at Case Western Reserve University in 1965, his Masters degree in economics from the University of Rochester in 1970, and his Ph.D. in economics from the University of Rochester in 1974. He was a professor at the University of Rochester’s Graduate School of Management from 1974 to 1978 and a professor at Cornell University’s Johnson School of Management from 1978 to 1995. He has been a professor at the University of Chicago’s Booth School of Business since 1995.

 

 

Selected Works

  1. . Toward a Positive Theory of Consumer Choice,” Journal of Economic Behavior and Organization 1, No. 1, pp. 39-60.

  2. . (with Werner F.M. De Bondt.) “Does the Stock Market Overreact?,” Journal of Finance, Vol. 40, pp. 793-805.

  3. . The Winner’s Curse: Paradoxes and Anomalies of Economic Life. Princeton University Press.

  4. . (with Cass R. Sunstein.) “Libertarian Paternalism,” American Economic Review, Vol. 93, No. 2, pp. 175-179.

  5. . (with Shlomo Benartzi.) “Save More TomorrowsupTM/sup: Using Behavioral Economics to Increase Employee Saving,” Journal of Political Economy, Vol. 112, No. S1, pp. S164-87.

  6. . (with Cass Sunstein.) Nudge: Improving Decisions About Health, Wealth, and Happiness, New Haven: Yale University Press.

  7. . Misbehaving: The Making of Behavioral Economics, New York: W.W. Norton.

 

 

 

[1] Brigitte C. Madrian and Dennis F. Shea, “The Power of Suggestion: Inertia in 401(k) Participation and Savings Behavior,” Quarterly Journal of Economics, Vol. CXVI, Issue 4, November 2001, pp. 1149-1187. At: https://www.ssc.wisc.edu/scholz/Teaching_742/Madrian_Shea.pdf

[2] Thomas Leonard, “Review of Richard Thaler and Cass Sunstein, Nudge: Improving Decisions about Health, Wealth, and Happiness.” Constitutional Political Economy 19(4): 356-360.

[3] http://www.igmchicago.org/surveys/price-gouging

[4] https://www.marketplace.org/shows/marketplace/09012017

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CEE May 28, 2019

William D. Nordhaus

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William D. Nordhaus was co-winner, along with Paul M. Romer, of the 2018 Nobel Prize in Economic Science “for integrating climate change into long-run macroeconomic analysis.”

Starting in the 1970s, Nordhaus constructed increasingly comprehensive models of the interaction between the economy and additions of carbon dioxide to the atmosphere, along with its effects on global warming. Economists use these models, along with assumptions about various magnitudes, to compute the “social cost of carbon” (SCC). The idea is that past a certain point, additions of carbon dioxide to the atmosphere heat the earth and thus create a global negative externality. The SCC is the net cost that using that additional carbon imposes on society. While the warmth has some benefits in, for example, causing longer growing seasons and improving recreational alternatives, it also has costs such as raising ocean levels, making some land uses obsolete. The SCC is the net of these social costs and is measured at the current margin. (The “current margin” language is important because otherwise one can get the wrong impression that any use of carbon is harmful.) Nordhaus and others then use the SCC to recommend taxes on carbon. In 2017, Nordhaus computed the optimal tax to be 31 per ton of carbon dioxide. To put that into perspective, a 31 carbon tax would increase the price of gasoline by about 28 cents.

CEE May 28, 2019

William D. Nordhaus

 

William D. Nordhaus was co-winner, along with Paul M. Romer, of the 2018 Nobel Prize in Economic Science “for integrating climate change into long-run macroeconomic analysis.”

Starting in the 1970s, Nordhaus constructed increasingly comprehensive models of the interaction between the economy and additions of carbon dioxide to the atmosphere, along with its effects on global warming. Economists use these models, along with assumptions about various magnitudes, to compute the “social cost of carbon” (SCC). The idea is that past a certain point, additions of carbon dioxide to the atmosphere heat the earth and thus create a global negative externality. The SCC is the net cost that using that additional carbon imposes on society. While the warmth has some benefits in, for example, causing longer growing seasons and improving recreational alternatives, it also has costs such as raising ocean levels, making some land uses obsolete. The SCC is the net of these social costs and is measured at the current margin. (The “current margin” language is important because otherwise one can get the wrong impression that any use of carbon is harmful.) Nordhaus and others then use the SCC to recommend taxes on carbon. In 2017, Nordhaus computed the optimal tax to be 31 per ton of carbon dioxide. To put that into perspective, a 31 carbon tax would increase the price of gasoline by about 28 cents per gallon.

Nordhaus noted, though, that there is a large amount of uncertainty about the optimal tax. For the 31 tax above, the actual optimal tax could be as little as 6 per ton or as much as 93.

Interestingly, according to Nordhaus’s model, setting too high a carbon tax can be worse than setting no carbon tax at all. According to the calibration of Nordhaus’s model in 2007, with no carbon tax and no other government controls, the present value of damages from environment damage and abatement costs would be 22.59 trillion (in 2004 dollars). Nordhaus’s optimal carbon tax would have reduced damage but increased abatement costs, for a total of 19.52 trillion, an improvement of only 3.07 trillion. But the cost of a policy to limit the temperature increase to only 1.5 C would have been 37.03 trillion, which is 16.4 trillion more than the cost of the “do nothing” option. Those numbers will be different today, but what is not different is that the cost of doing nothing is substantially below the cost of limiting the temperature increase to only 1.5 C.

One item the Nobel committee did not mention is his demonstration that the price of light has fallen by many orders of magnitude over the last 200 years. He showed that the price of light in 1992, adjusted for inflation, was less than one tenth of one percent of its price in 1800. Failure to take this reduction fully into account, noted Nordhaus, meant that economists have substantially underestimated the real growth rate of the economy and the growth rate of real wages.

Nordhaus also did pathbreaking work on the distribution of gains from innovation. In a 2004 study he wrote:

Only a minuscule fraction of the social returns from technological advances over the 1948-2001 period was captured by producers, indicating that most of the benefits of technological change are passed on to consumers rather than captured by producers.

Nordhaus earned his B.A. degree at Yale University in 1963 and his Ph.D. in economics at MIT in 1967. From 1977 to 1979, he was a member of President Carter’s Council of Economic Advisers.

 

 


Selected Works

  1. . “Economic Growth and Climate: The Case of Carbon Dioxide.” American Economic Review, Vol. 67, No. 1, pp. 341-346.

  2. . “Do Real-Output and Real-Wage Measures Capture Reality? The History of Lighting Suggests Not,” in Timothy F. Bresnahan and Robert J. Gordon, editors, The Economics of New Goods. Chicago: University of Chicago Press, 1996.

  3. . (with J. Boyer.) Warming the World: Economic Models of Global Warming. Cambridge, MA: MIT Press.

  4. . “Schumpeterian Profits in the American Economy: Theory and Measurement,” NBER Working Paper No. 10433, April 2004.

  5. . “Projections and Uncertainties about Climate Change in an Era of Minimal Climate Policies,” NBER Working Paper No. 22933.

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CEE May 28, 2019

Paul M. Romer

In 2018, U.S. economist Paul M. Romer was co-recipient, along with William D. Nordhaus, of the Nobel Prize in Economic Science for “integrating technological innovations into long-run macroeconomic analysis.”

Romer developed “endogenous growth theory.” Before his work in the 1980s and early 1990s, the dominant economic model of economic growth was one that MIT economist Robert Solow developed in the 1950s. Even though Solow concluded that technological change was a key driver of economic growth, his own model made technological change exogenous. That is, technological change was not something determined in the model but was an outside factor. Romer made it endogenous.

CEE May 28, 2019

Paul M. Romer

In 2018, U.S. economist Paul M. Romer was co-recipient, along with William D. Nordhaus, of the Nobel Prize in Economic Science for “integrating technological innovations into long-run macroeconomic analysis.”

Romer developed “endogenous growth theory.” Before his work in the 1980s and early 1990s, the dominant economic model of economic growth was one that MIT economist Robert Solow developed in the 1950s. Even though Solow concluded that technological change was a key driver of economic growth, his own model made technological change exogenous. That is, technological change was not something determined in the model but was an outside factor. Romer made it endogenous.

There are actually two very different phases in Romer’s work on endogenous growth theory. Romer (1986) and Romer (1987) had an AK model. Real output was equal to A times K, where A is a positive constant and K is the amount of physical capital. The model assumes diminishing marginal returns to K, but assumes also that part of a firm’s investment in capital results in the production of new technology or human capital that, because it is non-rival and non-excludable, generates spillovers (positive externalities) for all firms. Because this technology is embodied in physical capital, as the capital stock (K) grows, there are constant returns to a broader measure of capital that includes the new technology. Modeling growth this way allowed Romer to keep the assumption of perfect competition, so beloved by economists.

In Romer (1990), Romer rejected his own earlier model. Instead, he assumed that firms are monopolistically competitive. That is, industries are competitive, but many firms within a given industry have market power. Monopolistically competitive firms develop technology that they can exclude others from using. The technology is non-rival; that is, one firm’s use of the technology doesn’t prevent other firms from using it. Because they can exploit their market power by innovating, they have an incentive to innovate. It made sense, therefore, to think carefully about how to structure such incentives.

Consider new drugs. Economists estimate that the cost of successfully developing and bringing a new drug to market is about 2.6 billion. Once the formula is discovered and tested, another firm could copy the invention of the firm that did all the work. If that second firm were allowed to sell the drug, the first firm would probably not do the work in the first place. One solution is patents. A patent gives the inventor a monopoly for a fixed number of years during which it can charge a monopoly price. This monopoly price, earned over years, gives drug companies a strong incentive to innovate.

Another way for new ideas to emerge, notes Romer, is for governments to subsidize research and development.

The idea that technological change is not just an outside factor but itself is determined within the economic system might seem obvious to those who have read the work of Joseph Schumpeter. Why did Romer get a Nobel Prize for his insights? It was because Romer’s model didn’t “blow up.” Previous economists who had tried mathematically to model growth in a Schumpeterian way had failed to come up with models in which the process of growth was bounded.

To his credit, Romer lays out some of his insights on growth in words and very simple math. In the entry on economic growth in The Concise Encyclopedia of Economics, Romer notes the huge difference in long run well being that would result from raising the economic growth rate by only a few percentage points. The “rule of 72” says that the length of time over which a magnitude doubles can be computed by dividing the growth rate into 72. It actually should be called the rule of 70, but the math with 72 is slightly easier. So, for example, if an economy grows by 2 percent per year, it will take 36 years for its size to double. But if it grows by 4 percent per year, it will double in 18 years.

Romer warns that policy makers should be careful about using endogenous growth theory to justify government intervention in the economy. In a 1998 interview he stated:

A lot of people see endogenous growth theory as a blanket seal of approval for all of their favourite government interventions, many of which are very wrong-headed. For example, much of the discussion about infrastructure is just wrong. Infrastructure is to a very large extent a traditional physical good and should be provided in the same way that we provide other physical goods, with market incentives and strong property rights. A move towards privatization of infrastructure provision is exactly the right way to go. The government should be much less involved in infrastructure provision.[1]

In the same interview, he stated, “Selecting a few firms and giving them money has obvious problems” and that governments “must keep from taxing income at such high rates that it severely distorts incentives.”

In 2000, Romer introduced Aplia, an on-line set of problems and answers that economics professors could assign to their students and easily grade. The upside is that students are more prepared for lectures and exams and can engage with their fellow students in economic experiments on line. The downside of Aplia, according to some economics professors, is that students get less practice actually manually drawing demand and supply curves.

In 2009, Romer started advocating “Charter Cities.” His idea was that many people are stuck in countries with bad rules that make wealth creation difficult. If, he argued, an outside government could start a charter city in a country that had bad rules, people in that country could move there. Of course, this would require the cooperation of the country with the bad rules and getting that cooperation is not an easy task. His primary example of such an experiment working is Hong Kong, which was run by the British government until 1997. In a 2009 speech on charter cities, Romer stated, “Britain, through its actions in Hong Kong, did more to reduce world poverty than all the aid programs that we’ve undertaken in the last century.”[2]

Romer earned a B.S. in mathematics in 1977, an M.A. in economics in 1978, and a Ph.D. in economics in 1983, all from the University of Chicago. He also did graduate work at MIT and Queen’s University. He has taught at the University of Rochester, the University of Chicago, UC Berkeley, and Stanford University, and is currently a professor at New York University.

He was chief economist at the World Bank from 2106 to 2018.

 

 

[1] “Interview with Paul M. Romer,” in Brian Snowdon and Howard R. Vane, Modern Macroeconomics: Its Origins, Development and Current State, Cheltenham, UK: Edward Elgar, 2005, p. 690.

[2] Paul Romer, “Why the world needs charter cities,” TEDGlobal 2009.

 


Selected Works

  1. “Increasing Returns and Long-Run Growth.” Journal of Political Economy, Vol. 94, No. 5, pp. 1002-1037.
  2. “Growth Based on Increasing Returns Due to Specialization.” American Economic Review, Papers and Proceedings, Vol. 77, No. 2, pp. 56-62.
  3. “Endogenous Technological Change.” Journal of Political Economy. Vol. 98, No. 5, S71-S102.
  4. “Mathiness in the Theory of Economic Growth.” American Economic Review, Vol. 105, No. 5, pp. 89-93.

 

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CEE March 13, 2019

Jean Tirole

 

In 2014, French economist Jean Tirole was awarded the Nobel Prize in Economic Sciences “for his analysis of market power and regulation.” His main research, in which he uses game theory, is in an area of economics called industrial organization. Economists studying industrial organization apply economic analysis to understanding the way firms behave and why certain industries are organized as they are.

From the late 1960s to the early 1980s, economists George Stigler, Harold Demsetz, Sam Peltzman, and Yale Brozen, among others, played a dominant role in the study of industrial organization. Their view was that even though most industries don’t fit the economists’ “perfect competition” model—a model in which no firm has the power to set a price—the real world was full of competition. Firms compete by cutting their prices, by innovating, by advertising, by cutting costs, and by providing service, just to name a few. Their understanding of competition led them to skepticism about much of antitrust law and most government regulation.

In the 1980s, Jean Tirole introduced game theory into the study of industrial organization, also known as IO. The key idea of game theory is that, unlike for price takers, firms with market power take account of how their rivals are likely to react when they change prices or product offerings. Although the earlier-mentioned economists recognized this, they did not rigorously use game theory to spell out some of the implications of this interdependence. Tirole did.

One issue on which Tirole and his co-author Jean-Jacques Laffont focused was “asymmetric information.” A regulator has less information than the firms it regulates. So, if the regulator guesses incorrectly about a regulated firm’s costs, which is highly likely, it could set prices too low or too high. Tirole and Laffont showed that a clever regulator could offset this asymmetry by constructing contracts and letting firms choose which contract to accept. If, for example, some firms can take measures to lower their costs and other firms cannot, the regulator cannot necessarily distinguish between the two types. The regulator, recognizing this fact, may offer the firms either a cost-plus contract or a fixed-price contract. The cost-plus contract will appeal to firms with high costs, while the fixed-price contract will appeal to firms that can lower their costs. In this way, the regulator maintains incentives to keep costs down.

Their insights are most directly applicable to government entities, such as the Department of Defense, in their negotiations with firms that provide highly specialized military equipment. Indeed, economist Tyler Cowen has argued that Tirole’s work is about principal-agent theory rather than about reining in big business per se. In the Department of Defense example, the Department is the principal and the defense contractor is the agent.

One of Tirole’s main contributions has been in the area of “two-sided markets.” Consider Google. It can offer its services at one price to users (one side) and offer its services at a different price to advertisers (the other side). The higher the price to users, the fewer users there will be and, therefore, the less money Google will make from advertising. Google has decided to set a zero price to users and charge for advertising. Tirole and co-author Jean-Charles Rochet showed that the decision about profit-maximizing pricing is complicated, and they use substantial math to compute such prices under various theoretical conditions. Although Tirole believes in antitrust laws to limit both monopoly power and the exercise of monopoly power, he argues that regulators must be cautious in bringing the law to bear against firms in two-sided markets. An example of a two-sided market is a manufacturer of videogame consoles. The two sides are game developers and game players. He notes that it is very common for companies in such markets to set low prices on one side of the market and high prices on the other. But, he writes, “A regulator who does not bear in mind the unusual nature of a two-sided market may incorrectly condemn low pricing as predatory or high pricing as excessive, even though these pricing structures are adopted even by the smallest platforms entering the market.”

Tirole has brought the same kind of skepticism to some other related regulatory issues. Many regulators, for example, have advocated government regulation of interchange fees (IFs) in payment card associations such as Visa and MasterCard. But in 2003, Rochet and Tirole wrote that “given the [economics] profession’s current state of knowledge, there is no reason to believe that the IFs chosen by an association are systematically too high or too low, as compared with socially optimal levels.”

After winning the Nobel Prize, Tirole wrote a book for a popular audience, Economics for the Common Good. In it, he applied economics to a wide range of policy issues, laying out, among other things, the advantages of free trade for most residents of a given country and why much legislation and regulation causes negative unintended consequences.

Like most economists, Tirole favors free trade. In Economics for the Common Good, he noted that French consumers gain from freer trade in two ways. First, free trade exposes French monopolies and oligopolies to competition. He argued that two major French auto companies, Renault and Peugeot-Citroen, “sharply increased their efficiency” in response to car imports from Japan. Second, free trade gives consumers access to cheaper goods from low-wage countries.

In that same book, Tirole considered the unintended consequences of a hypothetical, but realistic, case in which a non-governmental organization, wanting to discourage killing elephants for their tusks, “confiscates ivory from traffickers.” In this hypothetical example, the organization can destroy the ivory or sell it. Destroying the ivory, he reasoned, would drive up the price. The higher price could cause poachers to kill more elephants. Another example he gave is of the perverse effects of price ceilings. Not only do they cause shortages, but also, as a result of these shortages, people line up and waste time in queues. Their time spent in queues wipes out the financial gain to consumers from the lower price, while also hurting the suppliers. No one wins and wealth is destroyed.

Also in that book, Tirole criticized the French government’s labor policies, which make it difficult for employers to fire people. He noted that this difficulty makes employers less likely to hire people in the first place. As a result, the unemployment rate in France was above 7 percent for over 30 years. The effect on young people has been particularly pernicious. When he wrote this book, the unemployment rate for French residents between 15 and 24 years old was 24 percent, and only 28.6 percent of percent of those in that age group had jobs. This was much lower than the OECD average of 39.6 percent, Germany’s 46.8 percent, and the Netherlands’ 62.3 percent.

One unintended, but predictable, consequence of government regulations of firms, which Tirole pointed out in Economics for the Common Good, is to make firms artificially small. When a French firm with 49 employees hires one more employee, he noted, it is subject to 34 additional legal obligations. Not surprisingly, therefore, in a figure that shows the number of enterprises with various numbers of employees, a spike occurs at 47 to 49 employees.

In Economics for the Common Good, Tirole ranged widely over policy issues in France. In addressing the French university system, he criticized the system’s rejection of selective admission to university. He argued that such a system causes the least prepared students to drop out and concluded that “[O]n the whole, the French educational system is a vast insider-trading crime.”

Tirole is chairman of the Toulouse School of Economics and of the Institute for Advanced Study in Toulouse. A French citizen, he was born in Troyes, France and earned his Ph.D. in economics in 1981 from the Massachusetts Institute of Technology.


Selected Works

 

  1. . (Co-authored with Jean-Jacques Laffont).“Using Cost Observation to Regulate Firms”. Journal of Political Economy. 94:3 (Part I). June: 614-641.

  2. . The Theory of Industrial Organization. MIT Press.

  3. . (Co-authored with Drew Fudenberg).“Moral Hazard and Renegotiation in Agency Contracts”, Econometrica, 58:6. November: 1279-1319.

  4. . (Co-authored with Jean-Jacques Laffont). A Theory of Incentives in Procurement and Regulation. MIT Press.

2003: (Co-authored with Jean-Charles Rochet). “An Economic Analysis of the Determination of Interchange Fees in Payment Card Systems.” Review of Network Economics. 2:2: 69-79.

  1. . (Co-authored with Jean-Charles Rochet). “Two-Sided Markets: A Progress Report.” The RAND Journal of Economics. 37:3. Autumn: 645-667.

2017, Economics for the Common Good. Princeton University Press.

 

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CEE November 30, 2018

The 2008 Financial Crisis

It was, according to accounts filtering out of the White House, an extraordinary scene. Hank Paulson, the U.S. treasury secretary and a man with a personal fortune estimated at 700m (380m), had got down on one knee before the most powerful woman in Congress, Nancy Pelosi, and begged her to save his plan to rescue Wall Street.

    The Guardian, September 26, 20081

The financial crisis of 2008 was a complex event that took most economists and market participants by surprise. Since then, there have been many attempts to arrive at a narrative to explain the crisis, but none has proven definitive. For example, a Congressionally-chartered ten-member Financial Crisis Inquiry Commission produced three separate narratives, one supported by the members appointed by the Democrats, one supported by four members appointed by the Republicans, and a third written by the fifth Republican member, Peter Wallison.2

It is important to appreciate that the financial system is complex, not merely complicated. A complicated system, such as a smartphone, has a fixed structure, so it behaves in ways that are predictable and controllable. A complex system has an evolving structure, so it can evolve in ways that no one anticipates. We will never have a proven understanding of what caused the financial crisis, just as we will never have a proven understanding of what caused the first World War.

There can be no single, definitive narrative of the crisis. This entry can cover only a small subset of the issues raised by the episode.

Metaphorically, we may think of the crisis as a fire. It started in the housing market, spread to the sub-prime mortgage market, then engulfed the entire mortgage securities market and, finally, swept through the inter-bank lending market and the market for asset-backed commercial paper.

Home sales began to slow in the latter part of 2006. This soon created problems for the sector of the mortgage market devoted to making risky loans, with several major lenders—including the largest, New Century Financial—declaring bankruptcy early in 2007. At the time, the problem was referred to as the “sub-prime mortgage crisis,” confined to a few marginal institutions.

But by the spring of 2008, trouble was apparent at some Wall Street investment banks that underwrote securities backed by sub-prime mortgages. On March 16, commercial bank JP Morgan Chase acquired one of these firms, Bear Stearns, with help from loan guarantees provided by the Federal Reserve, the central bank of the United States.

Trouble then began to surface at all the major institutions in the mortgage securities market. By late summer, many investors had lost confidence in Freddie Mac and Fannie Mae, and the interest rates that lenders demanded from them were higher than what they could pay and still remain afloat. On September 7, the U.S. Treasury took these two GSEs into “conservatorship.”

Finally, the crisis hit the short-term inter-bank collateralized lending markets, in which all of the world’s major financial institutions participate. This phase began after government officials’ unsuccessful attempts to arrange a merger of investment bank Lehman Brothers, which declared bankruptcy on September 15. This bankruptcy caused the Reserve Primary money market fund, which held a lot of short-term Lehman securities, to mark down the value of its shares below the standard value of one dollar each. That created jitters in all short-term lending markets, including the inter-bank lending market and the market for asset-backed commercial paper in general, and caused stress among major European banks.

The freeze-up in the interbank lending market was too much for leading public officials to bear. Under intense pressure to act, Treasury Secretary Henry Paulson proposed a 700 billion financial rescue program. Congress initially voted it down, leading to heavy losses in the stock market and causing Secretary Paulson to plead for its passage. On a second vote, the measure, known as the Troubled Assets Relief Program (TARP), was approved.

In hindsight, within each sector affected by the crisis, we can find moral hazard, cognitive failures, and policy failures. Moral hazard (in insurance company terminology) arises when individuals and firms face incentives to profit from taking risks without having to bear responsibility in the event of losses. Cognitive failures arise when individuals and firms base decisions on faulty assumptions about potential scenarios. Policy failures arise when regulators reinforce rather than counteract the moral hazard and cognitive failures of market participants.

The Housing Sector

From roughly 1990 to the middle of 2006, the housing market was characterized by the following:

  • an environment of low interest rates, both in nominal and real (inflation-adjusted) terms. Low nominal rates create low monthly payments for borrowers. Low real rates raise the value of all durable assets, including housing.
  • prices for houses rising as fast as or faster than the overall price level
  • an increase in the share of households owning rather than renting
  • loosening of mortgage underwriting standards, allowing households with weaker credit histories to qualify for mortgages.
  • lower minimum requirements for down payments. A standard requirement of at least ten percent was reduced to three percent and, in some cases, zero. This resulted in a large increase in the share of home purchases made with down payments of five percent or less.
  • an increase in the use of new types of mortgages with “negative amortization,” meaning that the outstanding principal balance rises over time.
  • an increase in consumers’ borrowing against their houses to finance spending, using home equity loans, second mortgages, and refinancing of existing mortgages with new loans for larger amounts.
  • an increase in the proportion of mortgages going to people who were not planning to live in the homes that they purchased. Instead, they were buying them to speculate. 3

These phenomena produced an increase in mortgage debt that far outpaced the rise in income over the same period. The trends accelerated in the three years just prior to the downturn in the second half of 2006.

The rise in mortgage debt relative to income was not a problem as long as home prices were rising. A borrower having difficulty finding the cash to make a mortgage payment on a house that had appreciated in value could either borrow more with the house as collateral or sell the house to pay off the debt.

But when house prices stopped rising late in 2006, households that had taken on too much debt began to default. This set in motion a reverse cycle: house foreclosures increased the supply of homes for sale; meanwhile, lenders became wary of extending credit, and this reduced demand. Prices fell further, leading to more defaults and spurring lenders to tighten credit still further.

During the boom, some people were speculating in non-owner-occupied homes, while others were buying their own homes with little or no money down. And other households were, in the vernacular of the time, “using their houses as ATMs,” taking on additional mortgage debt in order to finance consumption.

In most states in the United States, once a mortgage lender forecloses on a property, the borrower is not responsible for repayment, even if the house cannot be sold for enough to cover the loan. This creates moral hazard, particularly for property speculators, who can enjoy all of the profits if house prices rise but can stick lenders with some of the losses if prices fall.

One can see cognitive failure in the way that owners of houses expected home prices to keep rising at a ten percent rate indefinitely, even though overall inflation was less than half that amount.4Also, many house owners seemed unaware of the risks of mortgages with “negative amortization.”

Policy failure played a big role in the housing sector. All of the trends listed above were supported by public policy. Because they wanted to see increased home ownership, politicians urged lenders to loosen credit standards. With the Community Reinvestment Act for banks and Affordable Housing Goals for Freddie Mac and Fannie Mae, they spurred traditional mortgage lenders to increase their lending to minority and low-income borrowers. When the crisis hit, politicians blamed lenders for borrowers’ inability to repay, and political pressure exacerbated the credit tightening that subsequently took place

The Sub-prime Mortgage Sector

Until the late 1990s, few lenders were willing to give mortgages to borrowers with problematic credit histories. But sub-prime mortgage lenders emerged and grew rapidly in the decade leading up to the crisis. This growth was fueled by financial innovations, including the use of credit scoring to finely grade mortgage borrowers, and the use of structured mortgage securities (discussed in the next section) to make the sub-prime sector attractive to investors with a low tolerance for risk. Above all, it was fueled by rising home prices, which created a history of low default rates.

There was moral hazard in the sub-prime mortgage sector because the lenders were not holding on to the loans and, therefore, not exposing themselves to default risk. Instead, they packaged the mortgages into securities and sold them to investors, with the securities market allocating the risk.

Because they sold loans in the secondary market, profits at sub-prime lenders were driven by volume, regardless of the likelihood of default. Turning down a borrower meant getting no revenue. Approving a borrower meant earning a fee. These incentives were passed through to the staff responsible for finding potential borrowers and underwriting loans, so that personnel were compensated based on “production,” meaning the new loans they originated.

Although in theory the sub-prime lenders were passing on to others the risks that were embedded in the loans they were making, they were among the first institutions to go bankrupt during the financial crisis. This shows that there was cognitive failure in the management at these companies, as they did not foresee the house price slowdown or its impact on their firms.

Cognitive failure also played a role in the rise of mortgages that were underwritten without verification of the borrowers’ income, employment, or assets. Historical data showed that credit scores were sufficient for assessing borrower risk and that additional verification contributed little predictive value. However, it turned out that once lenders were willing to forgo these documents, they attracted a different set of borrowers, whose propensity to default was higher than their credit scores otherwise indicated.

There was policy failure in that abuses in the sub-prime mortgage sector were allowed to continue. Ironically, while the safety and soundness of Freddie Mac and Fannie Mae were regulated under the Department of Housing and Urban Development, which had an institutional mission to expand home ownership, consumer protection with regard to mortgages was regulated by the Federal Reserve Board, whose primary institutional missions were monetary policy and bank safety. Though mortgage lenders were setting up borrowers to fail, the Federal Reserve made little or no effort to intervene. Even those policy makers who were concerned about practices in the sub-prime sector believed that, on balance, sub-prime mortgage lending was helping a previously under-served set of households to attain home ownership.5

Mortagage Securities

A mortgage security consists of a pool of mortgage loans, the payments on which are passed through to pension funds, insurance companies, or other institutional investors looking for reliable returns with little risk. The market for mortgage securities was created by two government agencies, known as Ginnie Mae and Freddie Mac, established in 1968 and 1970, respectively.

Mortgage securitization expanded in the 1980s, when Fannie Mae, which previously had used debt to finance its mortgage purchases, began issuing its own mortgage-backed securities. At the same time, Freddie Mac was sold to shareholders, who encouraged Freddie to grow its market share. But even though Freddie and Fannie were shareholder-owned, investors treated their securities as if they were government-backed. This was known as an implicit government guarantee.

Attempts to create a market for private-label mortgage securities (PLMS) without any form of government guarantee were largely unsuccessful until the late 1990s. The innovations that finally got the PLMS market going were credit scoring and the collateralized debt obligation (CDO).

Before credit scoring was used in the mortgage market, there was no quantifiable difference between any two borrowers who were approved for loans. With credit scoring, the Wall Street firms assembling pools of mortgages could distinguish between a borrower with a very good score (750, as measured by the popular FICO system) and one with a more doubtful score (650).

Using CDOs, Wall Street firms were able to provide major institutional investors with insulation from default risk by concentrating that risk in other sub-securities (“tranches”) that were sold to investors who were more tolerant of risk. In fact, these basic CDOs were enhanced by other exotic mechanisms, such as credit default swaps, that reallocated mortgage default risk to institutions in which hardly any observer expected to find it, including AIG Insurance.

There was moral hazard in the mortgage securities market, as Freddie Mac and Fannie Mae sought profits and growth on behalf of shareholders, but investors in their securities expected (correctly, as it turned out) that the government would protect them against losses. Years before the crisis, critics grumbled that the mortgage giants exemplified privatized profits and socialized risks.6

There was cognitive failure in the assessment of default risk. Assembling CDOs and other exotic instruments required sophisticated statistical modeling. The most important driver of expectations for mortgage defaults is the path for house prices, and the steep, broad-based decline in home prices that took place in 2006-2009 was outside the range that some modelers allowed for.

Another source of cognitive failure is the “suits/geeks” divide. In many firms, the financial engineers (“geeks) understood the risks of mortgage-related securities fairly well, but their conclusions did not make their way to the senior management level (“suits”).

There was policy failure on the part of bank regulators. Their previous adverse experience was with the Savings and Loan Crisis, in which firms that originated and retained mortgages went bankrupt in large numbers. This caused bank regulators to believe that mortgage securitization, which took risk off the books of depository institutions, would be safer for the financial system. For the purpose of assessing capital requirements for banks, regulators assigned a weight of 100 percent to mortgages originated and held by the bank, but assigned a weight of only 20 percent to the bank’s holdings of mortgage securities issued by Freddie Mac, Fannie Mae, or Ginnie Mae. This meant that banks needed to hold much more capital to hold mortgages than to hold mortgage-related securities; that naturally steered them toward the latter.

In 2001, regulators broadened the low-risk umbrella to include AAA-rated and AA-rated tranches of private-label CDOs. This ruling helped to generate a flood of PLMS, many of them backed by sub-prime mortgage loans.7

By using bond ratings as a key determinant of capital requirements, the regulators effectively put the bond rating agencies at the center of the process of creating private-label CDOs. The rating agencies immediately became subject to both moral hazard and cognitive failure. The moral hazard came from the fact that the rating agencies were paid by the issuers of securities, who wanted the most generous ratings possible, rather than being paid by the regulators, who needed more rigorous ratings. The cognitive failure came from the fact that that models that the rating agencies used gave too little weight to potential scenarios of broad-based declines in house prices. Moreover, the banks that bought the securities were happy to see them rated AAA because the high ratings made the securities eligible for lower capital requirements on the part of the banks. Both sides, therefore, buyers and sellers, had bad incentives.

There was policy failure on the part of Congress. Officials in both the Clinton and Bush Administrations were unhappy with the risk that Freddie Mac and Fannie Mae represented to taxpayers. But Congress balked at any attempt to tighten regulation of the safety and soundness of those firms.8

The Inter-bank Lending Market

There are a number of mechanisms through which financial institutions make short-term loans to one another. In the United States, banks use the Federal Funds market to manage short-term fluctuations in reserves. Internationally, banks lend in what is known as the LIBOR market.

One of the least known and most important markets is for “repo,” which is short for “repurchase agreement.” As first developed, the repo market was used by government bond dealers to finance inventories of securities, just as an automobile dealer might finance an inventory of cars. A money-market fund might lend money for one day or one week to a bond dealer, with the loan collateralized by a low-risk long-term security.

In the years leading up to the crisis, some dealers were financing low-risk mortgage-related securities in the repo market. But when some of these securities turned out to be subject to price declines that took them out of the “low-risk” category, participants in the repo market began to worry about all repo collateral. Repo lending offers very low profit margins, and if an investor has to be very discriminating about the collateral backing a repo loan, it can seem preferable to back out of repo lending altogether. This, indeed, is what happened, in what economist Gary Gorton and others called a “run on repo.”9

Another element of institutional panic was “collateral calls” involving derivative financial instruments. Derivatives, such as credit default swaps, are like side bets. The buyer of a credit default swap is betting that a particular debt instrument will default. The seller of a credit default swap is betting the opposite.

In the case of mortgage-related securities, the probability of default seemed low prior to the crisis. Sometimes, buyers of credit default swaps were merely satisfying the technical requirements to record the underlying securities as AAA-rated. They could do this if they obtained a credit default swap from an institution that was itself AAA-rated. AIG was an insurance company that saw an opportunity to take advantage of its AAA rating to sell credit default swaps on mortgage-related securities. AIG collected fees, and its Financial Products division calculated that the probability of default was essentially zero. The fees earned on each transaction were low, but the overall profit was high because of the enormous volume. AIG’s credit default swaps were a major element in the expansion of shadow banking by non-bank financial institutions during the run-up to the crisis.

Late in 2005, AIG abruptly stopped writing credit default swaps, in part because its own rating had been downgraded below AAA earlier in the year for unrelated reasons. By the time AIG stopped selling credit default swaps on mortgage-related securities, it had outstanding obligations on 80 billion of underlying securities and was earning 1 billion a year in fees.10

Because AIG no longer had its AAA rating and because the underlying mortgage securities, while not in default, were increasingly shaky, provisions in the contracts that AIG had written allowed the buyers of credit default swaps to require AIG to provide protection in the form of low-risk securities posted as collateral. These “collateral calls” were like a margin call that a stock broker will make on an investor who has borrowed money to buy stock that subsequently declines in value. In effect, collateral calls were a run on AIG’s shadow bank.

These collateral calls were made when the crisis in the inter-bank lending market was near its height in the summer of 2008 and banks were hoarding low-risk securities. In fact, the shortage of low-risk securities may have motivated some of the collateral calls, as institutions like Deutsche Bank and Goldman Sachs sought ways to ease their own liquidity problems. In any event, AIG could not raise enough short-term funds to meet its collateral calls without trying to dump long-term securities into a market that had little depth to absorb them. It turned to Federal authorities for a bailout, which was arranged and creatively backed by the Federal Reserve, but at the cost of reducing the value of shares in AIG.

With repos and derivatives, there was moral hazard in that the traders and executives of the narrow units that engaged in exotic transactions were able to claim large bonuses on the basis of short-term profits. But the adverse long-term consequences were spread to the rest of the firm and, ultimately, to taxpayers.

There was cognitive failure in that the collateral calls were an unanticipated risk of the derivatives business. The financial engineers focused on the (remote) chances of default on the underlying securities, not on the intermediate stress that might emerge from collateral calls.

There was policy failure when Congress passed the Commodity Futures Modernization Act. This legislation specified that derivatives would not be regulated by either of the agencies with the staff most qualified to understand them. Rather than require oversight by the Securities and Exchange Commission or the Commodity Futures Trading Commission (which regulated market-traded derivatives), Congress decreed that the regulator responsible for overseeing each firm would evaluate its derivative position. The logic was that a bank that was using derivatives to hedge other transactions should have its derivative position evaluated in a larger context. But, as it happened, the insurance and bank regulators who ended up with this responsibility were not equipped to see the dangers at firms such as AIG.

There was also policy failure in that officials approved of securitization that transferred risk out of the regulated banking sector. While Federal Reserve Officials were praising the risk management of commercial banks,11risk was accumulating in the shadow banking sector (non-bank institutions in the financial system), including AIG insurance, money market funds, Wall Street firms such as Bear Stearns and Lehman Brothers, and major foreign banks. When problems in the shadow banking sector contributed to the freeze in inter-bank lending and in the market for asset-backed commercial paper, policy makers felt compelled to extend bailouts to satisfy the needs of these non-bank institutions for liquid assets.

Conclusion

In terms of the fire metaphor suggested earlier, in hindsight, we can see that the markets for housing, sub-prime mortgages, mortgage-related securities, and inter-bank lending were all highly flammable just prior to the crisis. Moral hazard, cognitive failures, and policy failures all contributed the combustible mix.

The crisis also reflects a failure of the economics profession. A few economists, most notably Robert Shiller,12warned that the housing market was inflated, as indicated by ratios of prices to rents that were high by historical standards. Also, when risk-based capital regulation was proposed in the wake of the Savings and Loan Crisis and the Latin American debt crisis, a group of economists known as the Shadow Regulatory Committee warned that these regulations could be manipulated. They recommended, instead, greater use of senior subordinated debt at regulated financial institutions.13Many economists warned about the incentives for risk-taking at Freddie Mac and Fannie Mae.14

But even these economists failed to anticipate the 2008 crisis, in large part because economists did not take note of the complex mortgage-related securities and derivative instruments that had been developed. Economists have a strong preference for parsimonious models, and they look at financial markets through a lens that includes only a few types of simple assets, such as government bonds and corporate stock. This approach ignores even the repo market, which has been important in the financial system for over 40 years, and, of course, it omits CDOs, credit default swaps and other, more recent innovations.

Financial intermediaries do not produce tangible output that can be measured and counted. Instead, they provide intangible benefits that economists have never clearly articulated. The economics profession has a long way to go to catch up with modern finance.


About the Author

Arnold Kling was an economist with the Federal Reserve Board and with the Federal Home Loan Mortgage Corporation before launching one of the first Web-based businesses in 1994.  His most recent books areSpecialization and Trade and The Three Languages of Politics. He earned his Ph.D. in economics from the Massachusetts Institute of Technology.


Footnotes

1

“A desperate plea – then race for a deal before ‘sucker goes down’” The Guardian, September 26, 2008. https://www.theguardian.com/business/2008/sep/27/wallstreet.useconomy1

 

2

The report and dissents of the Financial Crisis Inquiry Commission can be found at https://fcic.law.stanford.edu/

3

See Stefania Albanesi, Giacomo De Giorgi, and Jaromir Nosal 2017, “Credit Growth and the Financial Crisis: A New Narrative” NBER working paper no. 23740. http://www.nber.org/papers/w23740

 

4

Karl E. Case and Robert J. Shiller 2003, “Is there a Bubble in the Housing Market?” Cowles Foundation Paper 1089 http://www.econ.yale.edu/shiller/pubs/p1089.pdf

 

5

Edward M. Gramlich 2004, “Subprime Mortgage Lending: Benefits, Costs, and Challenges,” Federal Reserve Board speeches. https://www.federalreserve.gov/boarddocs/speeches/2004/20040521/

 

6

For example, in 1999, Treasury Secretary Lawrence Summers said in a speech, “Debates about systemic risk should also now include government-sponsored enterprises.” See Bethany McLean and Joe Nocera 2010, All the Devils are Here: The Hidden History of the Financial Crisis Portfolio/Penguin Press. The authors write that Federal Reserve Chairman Alan Greenspan was also, like Summers, disturbed by the moral hazard inherent in the GSEs.

 

7

Jeffrey Friedman and Wladimir Kraus 2013, Engineering the Financial Crisis: Systemic Risk and the Failure of Regulation, University of Pennsylvania Press.

 

8

See McLean and Nocera, All the Devils are Here

 

9

Gary Gorton, Toomas Laarits, and Andrew Metrick 2017, “The Run on Repo and the Fed’s Response,” Stanford working paper. https://www.gsb.stanford.edu/sites/gsb/files/fin_11_17_gorton.pdf

 

10

Talking Points Memo 2009, “The Rise and Fall of AIG’s Financial Products Unit” https://talkingpointsmemo.com/muckraker/the-rise-and-fall-of-aig-s-financial-products-unit

 

11

Chairman Ben S. Bernanke 2006, “Modern Risk Management and Banking Supervision,” Federal Reserve Board speeches. https://www.federalreserve.gov/newsevents/speech/bernanke20060612a.htm

 

12

National Public Radio 2005, “Yale Professor Predicts Housing ’Bubble’ Will Burst” https://www.npr.org/templates/story/story.php?storyId4679264

 

13

Shadow Financial Regulatory Committee 2001, “The Basel Committee’s Revised Capital Accord Proposal” https://www.bis.org/bcbs/ca/shfirect.pdf

14

See the discussion in Viral V. Acharya, Matthew Richardson, Stijn Van Nieuwerburgh and Lawrence J. White 2011, Guaranteed to Fail: Fannie Mae, Freddie Mac, and the Debacle of Mortgage Finance, Princeton University Press.

 

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CEE September 18, 2018

Christopher Sims

 

Christopher Sims was awarded, along with Thomas Sargent, the 2011 Nobel Prize in Economic Sciences. The Nobel committee cited their “empirical research on cause and effect in the macroeconomy.” The economists who spoke at the press conference announcing the award emphasized Sargent’s and Sims’ analysis of role of people’s expectations.

One of Sims’s earliest famous contributions was his work on money-income causality, which was cited by the Nobel committee. Money and income move together, but which causes which? Milton Friedman argued that changes in the money supply caused changes in income, noting that the supply of money often rises before income rises. Keynesians such as James Tobin argued that changes in income caused changes in the amount of money. Money seems to move first, but causality, said Tobin and others, still goes the other way: people hold more money when they expect income to rise in the future.

Which view is true? In 1972 Sims applied Clive Granger’s econometric test of causality. On Granger’s definition one variable is said to cause another variable if knowledge of the past values of the possibly causal variable helps to forecast the effect variable over and above the knowledge of the history of the effect variable itself. Implementing a test of this incremental predictability, Sims concluded “[T]he hypothesis that causality is unidirectional from money to income [Friedman’s view] agrees with the postwar U.S. data, whereas the hypothesis that causality is unidirectional from income to money [Tobin’s view] is rejected.”

Sims’s influential article “Macroeconomics and Reality” was a criticism of both the usual econometric interpretation of large-scale Keynesian econometric models and ofRobert Lucas’s influential earlier criticism of these Keynesian models (the so-called Lucas critique). Keynesian econometricians had claimed that with sufficiently accurate theoretical assumptions about the structure of the economy, correlations among the macroeconomic variables could be used to measure the strengths of various structural connections in the economy. Sims argued that there was no basis for thinking that these theoretical assumptions were sufficiently accurate. Such so-called “identifying assumptions” were, Sims said, literally “incredible.” Lucas, on the other hand, had not rejected the idea of such identification. Rather he had pointed out that, if people held “rational expectations” – that is, expectations that, though possibly incorrect, did not deviate on average from what actually occurs in a correctable, systematic manner – then failing to account for them would undermine the stability of the econometric estimates and render the macromodels useless for policy analysis. Lucas and his New Classical followers argued that in forming their expectations people take account of the rules implicitly followed by monetary and fiscal policymakers; and, unless those rules were integrated into the econometric model, every time the policymakers adopted a new policy (i.e., new rules), the estimates would shift in unpredictable ways.

While rejecting the structural interpretation of large-scale macromodels, Sims did not reject the models themselves, writing: “[T]here is no immediate prospect that large-scale macromodels will disappear from the scene, and for good reason: they are useful tools in forecasting and policy analysis.” Sims conceded that the Lucas critique was correct in those cases in which policy regimes truly changed. But he argued that such regime changes were rare and that most economic policy was concerned with the implementation of a particular policy regime. For that purpose, the large-scale macromodels could be helpful, since what was needed for forecasting was a model that captured the complex interrelationships among variables and not one that revealed the deeper structural connections.

In the same article, Sims proposed an alternative to large-scale macroeconomic models, the vector autoregression (or VAR). In Sims’s view, the VAR had the advantages of the earlier macromodels, in that it could capture the complex interactions among a relatively large number of variables needed for policy analysis and yet did not rely on as many questionable theoretical assumptions. With subsequent developments by Sims and others, the VAR became a major tool of empirical macroeconomic analysis.

Sims has also suggested that sticky prices are caused by “rational inattention,” an idea imported from electronic communications. Just as computers do not access information on the Internet infinitely fast (but rather, in bits per second), individual actors in an economy have only a finite ability to process information. This delay produces some sluggishness and randomness, and allows for more accurate forecasts than conventional models, in which people are assumed to be highly averse to change.

Sims’s recent work has focused on the fiscal theory of the price level, the view that inflation in the end is determined by fiscal problems—the overall amount of debt relative to the government’s ability to repay it—rather than by the split in government debt between base money and bonds. In 1999, Sims suggested that the fiscal foundations of the European Monetary Union were “precarious” and that a fiscal crisis in one country “would likely breed contagion effects in other countries.” The Greek financial crisis about a decade later seemed to confirm his prediction.

Christopher Sims earned his B.A. in mathematics in 1963 and his Ph.D. in economics in 1968, both from Harvard University. He taught at Harvard from 1968 to 1970, at the University of Minnesota from 1970 to 1990, at Yale University from 1990 to 1999, and at Princeton University from 1999 to the present. He has been a Fellow of the Econometric Society since 1974, a member of the American Academy of Arts and Sciences since 1988, a member of the National Academy of Sciences since 1989, President of the Econometric Society (1995), and President of the American Economic Association (2012). He has been a Visiting Scholar for the Federal Reserve Banks of Atlanta, New York, and Philadelphia off and on since 1994.


Selected Works

  1. . “Money, Income, and Causality.” American Economic Review 62: 4 (September): 540-552.

  2. . “Macroeconomics and Reality.” Econometrica 48: 1 (January): 1-48.

1990 (with James H. Stock and Mark W. Watson). “Inference in Linear Time Series Models with some Unit Roots.” Econometrica 58: 1 (January): 113-144.

  1. . “The Precarious Fiscal Foundations of EMU.” De Economist 147:4 (December): 415-436.

  2. . “Implications of Rational Inattention.” Journal of Monetary Economics 50: 3 (April): 665–690.

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CEE June 28, 2018

Gordon Tullock

Gordon tullock

Gordon Tullock, along with his colleague James M. Buchanan, was a founder of the School of Public Choice. Among his contributions to public choice were his study of bureaucracy, his early insights on rent seeking, his study of political revolutions, his analysis of dictatorships, and his analysis of incentives and outcomes in foreign policy. Tullock also contributed to the study of optimal organization of research, was a strong critic of common law, and did work on evolutionary biology. He was arguably one of the ten or so most influential economists of the last half of the twentieth century. Many economists believe that Tullock deserved to share Buchanan’s 1986 Nobel Prize or even deserved a Nobel Prize on his own.

One of Tullock’s early contributions to public choice was The Calculus of Consent: Logical Foundations of Constitutional Democracy, co-authored with Buchanan in 1962. In that path-breaking book, the authors assume that people seek their own interests in the political system and then consider the results of various rules and political structures. One can think of their book as a political economist’s version of Montesquieu.

One of the most masterful sections of The Calculus of Consent is the chapter in which the authors, using a model formulated by Tullock, consider what good decision rules would be for agreeing to have someone in government make a decision for the collective. An individual realizes that if only one person’s consent is required, and he is not that person, he could have huge costs imposed on him. Requiring more people’s consent in order for government to take action reduces the probability that that individual will be hurt. But as the number of people required to agree rises, the decision costs rise. In the extreme, if unanimity is required, people can game the system and hold out for a disproportionate share of benefits before they give their consent. The authors show that the individual’s preferred rule would be one by which the costs imposed on him plus the decision costs are at a minimum. That preferred rule would vary from person to person. But, they note, it would be highly improbable that the optimal decision rule would be one that requires a simple majority. They write, “On balance, 51 percent of the voting population would not seem to be much preferable to 49 percent.” They suggest further that the optimal rule would depend on the issues at stake. Because, they note, legislative action may “produce severe capital losses or lucrative capital gains” for various groups, the rational person, not knowing his own future position, might well want strong restraints on the exercise of legislative power.

Tullock’s part of The Calculus of Consent was a natural outgrowth of an unpublished manuscript written in the 1950s that later became his 1965 book, The Politics of Bureaucracy. Buchanan, reminiscing about that book, summed up Tullock’s approach and the book’s significance:

The substantive contribution in the manuscript was centered on the hypothesis that, regardless of role, the individual bureaucrat responds to the rewards and punishments that he confronts. This straightforward, and now so simple, hypothesis turned the whole post-Weberian quasi-normative approach to bureaucracy on its head. . . . The economic theory of bureaucracy was born.1

Buchanan noted in his reminiscence that Tullock’s “fascinating analysis” was “almost totally buried in an irritating personal narrative account of Tullock’s nine-year experience in the foreign service hierarchy.” Buchanan continued: “Then, as now, Tullock’s work was marked by his apparent inability to separate analytical exposition from personal anecdote.” Translation: Tullock learned from his experiences. As a Foreign Service officer with the U.S. State Department for nine years Tullock learned, up close and “personal,” how dysfunctional bureaucracy can be. In a later reminiscence, Tullock concluded:

A 90 per cent cut-back on our Foreign Service would save money without really damaging our international relations or stature.2

Tullock made many other contributions in considering incentives within the political system. Particularly noteworthy was his work on political revolutions and on dictatorships.

Consider, first, political revolutions. Any one person’s decision to participate in a revolution, Tullock noted, does not much affect the probability that the revolution will succeed. Therefore, each person’s actions do not much affect his expected benefits from revolution. On the other hand, a ruthless head of government can individualize the costs by heavily punishing those who participate in a revolution. So anyone contemplating participating in a revolution will be comparing heavy individual costs with small benefits that are simply his pro rata share of the overall benefits. Therefore, argued Tullock, for people to participate, they must expect some large benefits that are tied to their own participation, such as a job in the new government. That would explain an empirical regularity that Tullock noted—namely that “in most revolutions, the people who overthrow the existing government were high officials in that government before the revolution.”

This thinking carried over to his work on autocracy. In Autocracy, Tullock pointed out that in most societies at most times, governments were not democratically elected but were autocracies: they were dictatorships or kingdoms. For that reason, he argued, analysts should do more to understand them. Tullock’s book was his attempt to get the discussion started. In a chapter titled “Coups and Their Prevention,” Tullock argued that one of the autocrat’s main challenges is to survive in office. He wrote: “The dictator lives continuously under the Sword of Damocles and equally continuously worries about the thickness of the thread.” Tullock pointed out that a dictator needs his countrymen to believe not that he is good, just, or ordained by God, but that those who try to overthrow him will fail.”

Among modern economists, Tullock was the earliest discoverer of the concept of “rent seeking,” although he did not call it that. Before his work, the usual measure of the deadweight loss from monopoly was the part of the loss in consumer surplus that did not increase producer surplus for the monopolist. Consumer surplus is the maximum amount that consumers are willing to pay minus the amount they actually pay; producer surplus, also called “economic rent,” is the amount that producers get minus the minimum amount for which they would be willing to produce. Harberger3 had estimated that for the U.S. economy in the 1950s, that loss was very low, on the order of 0.1 percent of Gross National Product. In “The Welfare Cost of Tariffs, Monopolies, and Theft,” Tullock argued that this method understated the loss from monopoly because it did not take account of the investment of the monopolist—and of others trying to be monopolists—in becoming monopolists. These investments in monopoly are a loss to the economy. Tullock also pointed out that those who seek tariffs invest in getting those tariffs, and so the standard measure of the loss from tariffs understated the loss. His analysis, as the tariff example illustrates, applies more to firms seeking special privileges from government than to private attempts to monopolize via the free market because private attempts often lead, as if by an invisible hand, to increased competition.”

One of Tullock’s most important insights in public choice was in a short article in 1975 titled “The Transitional Gains Trap.” He noted that even though rent seeking often leads to big gains for the rent seekers, those gains are capitalized in asset prices, which means that buyers of the assets make a normal return on the asset. So, for example, if the government requires the use of ethanol in gasoline, owners of land on which corn is grown will find that their land is worth more because of the regulatory requirement. (Ethanol in the United States is produced from corn.) They gain when the regulation is first imposed. But when they sell the land, the new owner pays a price equal to the present value of the stream of the net profits from the land. So the new owner doesn’t get a supra-normal rate of return from the land. In other words, the owner at the time that the regulation was imposed got “transitional gains,” but the new owner does not. This means that the new owner will suffer a capital loss if the regulation is removed and will fight hard to keep the regulation in place, arguing, correctly, that he paid for those gains. That makes repealing the regulation more difficult than otherwise. Tullock notes that, therefore, we should try hard to avoid getting into these traps because they are hard to get out of.

Tullock was one of the few public choice economists to apply his tools to foreign policy. In Open Secrets of American Foreign Policy, he takes a hard-headed look at U.S. foreign policy rather than the romantic “the United States is the good guys” view that so many Americans take. For example, he wrote of the U.S. government’s bombing of Serbia under President Bill Clinton:

[T]he bombing campaign was a clear-cut violation of the United Nations Charter and hence, should be regarded as a war crime. It involved the use of military forces without the sanction of the Security Council and without any colorable claim of self-defense. Of course, it was not a first—we [the U.S. government] had done the same thing in Vietnam, Grenada and Panama.

Possibly Tullock’s most underappreciated contributions were in the area of methodology and the economics of research. About a decade after spending six months with philosopher Karl Popper at the Center for Advanced Studies in Palo Alto, Tullock published The Organization of Inquiry. In it, he considered why scientific discovery in both the hard sciences and economics works so well without any central planner, and he argued that centralized funding by government would slow progress. After arguing that applied science is generally more valuable than pure science, Tullock wrote:

Nor is there any real justification for the general tendency to consider pure research as somehow higher and better than applied research. It is certainly more pleasant to engage in research in fields that strike you as interesting than to confine yourself to fields which are likely to be profitable, but there is no reason why the person choosing the more pleasant type of research should be considered more noble.4

In Tullock’s view, a system of prizes for important discoveries would be an efficient way of achieving important breakthroughs. He wrote:

As an extreme example, surely offering a reward of 1 billion for the first successful ICBM would have resulted in both a large saving of money for the government and much faster production of this weapon.5

Tullock was born in Rockford, Illinois and was an undergrad at the University of Chicago from 1940 to 1943. His time there was interrupted when he was drafted into the U.S. Army. During his time at Chicago, though, he completed a one-semester course in economics taught by Henry Simons. After the war, he returned to the University of Chicago Law School, where he completed the J.D. degree in 1947. He was briefly with a law firm in 1947 before going into the Foreign Service, where he worked for nine years. He was an economics professor at the University of South Carolina (1959-1962), the University of Virginia (1962-1967), Rice University (1968-1969), the Virginia Polytechnic Institute and State University (1968-1983), George Mason University (1983-1987), the University of Arizona (1987-1999), and again at George Mason University (1999-2008). In 1966, he started the journal Papers in Non-Market Decision Making, which, in 1969, was renamed Public Choice.


Selected Works

 

  1. . The Calculus of Consent. (Co-authored with James M. Buchanan.) Ann Arbor, Michigan: University of Michigan Press.

  2. . The Politics of Bureaucracy. Public Affairs Press. Washington, D.C.: Public Affairs Press.

  3. . The Organization of Inquiry. Durham, North Carolina: Duke University Press.

  4. . “The Welfare Costs of Tariffs, Monopolies, and Theft,” Western Economic Journal, 5:3 (June): 224-232.

  5. . Toward a Mathematics of Politics. Ann Arbor, Michigan: University of Michigan Press.

  6. . “The Paradox of Revolution.” Public Choice. Vol. 11. Fall: 89-99.

1975: “The Transitional Gains Trap.” Bell Journal of Economics, 6:2 (Autumn): 671-678.

1987: Autocracy. Hingham, Massachusetts: Kluwer Academic Publishers.

  1. . Open Secrets of American Foreign Policy. New Jersey: World Scientific Publishing Co.

 


Footnotes

James M. Buchanan. 1987. The qualities of a natural economist. In Charles K. Rowley, (Ed.) (1987). Democracy and public choice. Oxford and New York: Basil Blackwell, 9-19.

 

Gordon Tullock. 2009. Memories of an unexciting life. Unfinished and unpublished manuscript. Tucson, 2009. Quoted in Charles K. Rowley and Daniel Houser. “The Life and Times of Gordon Tullock.” 2011. George Mason University. Department of Economics. Paper No. 11-56. December 20.

 

Arnold C. Harberger. 1954 “Monopoly and Resource Allocation.” American Economic Review. 44(2): 77-87.

 

Tullock. 1966. P. 14.

 

Tullock. 1966. P. 168.

 

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Econlib April 3, 2020

The Good and Bad of Tucker Carlson

Along with a slight appreciation of Laura Ingraham.

Consistent with the spirit of my most recent post, “Socratic Grilling as a Way to Learn,” I watch the Fox News Channel a few times a week and often flip to CNN to see what they’re saying. On both networks, people spin like crazy. Which does not mean that you can’t learn from each.

I’ll give an example from last night, where I learned something important from one of Tucker Carlson’s interviews and also noticed how severely his nationalism and hostility to China can get in the way of clear thinking.

First, the good. Tucker interviewed Alex Berenson, a former reporter for the New York Times. Of course the subject was COVID-19. Berenson led with the caveat that he’s not an epidemiologist but that his expertise is another area: comparing predictions with what actually happened.

Berenson stated that a model used by the government in, I think, Washington state predicted about a week ago that the number of hospitalizations of COVID-19 patients in New York by yesterday would be about 50,000 whereas the actual number was 13,000. That’s incredibly valuable information, if true. It should cause people who follow that model to take a careful look at their model. Are they doing so? I have no idea.

Second, the bad. Later in the show, Tucker showed a segment in which an English-speaking doctor, an American, I believe, talked about how well the Chinese government had handled the crisis in Wuhan, where it originated. The doctor then went to suggest that we in American should bring over a few thousand of those Chinese doctors to help us here. Then Tucker did his signature laugh and stated that the doctor had said we should have doctors from China run our hospitals. My wife and I looked at each other like “What?” The doctor hadn’t even suggested that Chinese doctors run our hospitals. What he seemed to be saying is that we should hire them as inputs because they know a lot.

What I’ve noticed that is characteristic of Tucker: when the issue involves China or immigration, he loses his critical faculties. When it involves both, as this did to some extent, it’s almost a guarantee that he will lose his critical faculties.

I’ve not generally been a fan of Laura Ingraham but we watched her for more than a few minutes because lately she has been quite good at reminding her audience of the catastrophic costs of shutting down a huge percent of the economy. She was quite good on that yesterday. She also had on Alan Dershowitz, an emeritus professor of law at Harvard. Dershowitz made some good points about loss of liberty. As per usual, though, when he started to say things she didn’t like, Ingraham cut off the conversation pretty quickly. The particular thing here was his statement that it was not justified for some state governments to close down abortion clinics.

Note: Here’s a piece I wrote back in 2005, when I was more of a fan of Fox News Channel. I gave them 2 cheers. I think it’s now about 1.5 or maybe less.

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Econlib April 3, 2020

How to Win Friends and Influence People Book Club Commercial

I just shot this commercial for next week’s Book Club.  Enjoy!

 

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Econlib April 3, 2020

Our economy will likely reboot too slowly

My general view is that social distancing is better than an explosion of coronavirus cases. I believe we were too slow to begin social distancing, at least in hindsight. At the same time, I expect that after the worst phase of the epidemic is over we’ll do too much social distancing.

Suppose you saw a sign in a restaurant window saying, “Our restaurant has a smaller than average number of rats and cockroaches in our kitchen.” Does that make you more inclined to eat there? Obviously it should make you more inclined to eat there, but would it? Many people don’t even give any thought to rats and cockroaches in the kitchen when deciding where to eat. They’d be put off by that sign.  Gross!

The Chinese movie theatre industry was about to re-open last weekend, and then the government suddenly reversed course. This picture of a Chinese movie theatre caught my attention:

Those barriers that keep people separated obviously make the theatre safer. But I wonder if they make it seem less safe to the average filmgoer. I can picture my wife saying, “Well, if it’s so dangerous they need to separate people, then perhaps I’ll just stay home and watch Netflix.”

Our society doesn’t react very rapidly to hard to understand risks discussed by experts.  But when the risk becomes obvious, we tend to overreact. In a previous post, I argued that overreaction (from an individual risk perspective) was socially optimal in this case.  But that Chinese movie theatre picture (and the likely reaction of theatre patrons) makes me think that eventually we’ll go too far.  It would be optimal at some point to reboot our economy if we could keep the R0 factor (virus reproduction) below 1.0.  Do lots of little things like what we see in the picture above.  But I wonder if our extreme risk aversion will demand an even higher standard, closer to zero risk.

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Econlib April 3, 2020

Socratic Grilling as a Way to Learn

 

Scott Alexander, over at slatestarcodex.com, has hit a number of home runs in the last few weeks. I want to focus on his March 6 post, “Socratic Grilling.” To follow what I’m going to say, you need to read his post first. His posts are often very long, but the March 6 one is relatively short.

I’ve been practicing my own version of what Scott calls Socratic grilling since about the age of 5. I badly wanted to understand things around me. Even though I learned to read at age 5, I wasn’t much of a reader and, although we had a public library in my town of 1,200 people, it was a small library. For my first few years of reading, I focused on Hardy Boys and Nancy Drew books.

My way of learning was not to read but to ask adults around me to explain things. When I got only a few thoughts that seemed to fit, I would then adopt a position and argue it, being open to being shown that that was wrong. You could say I was a Bayesian. I found it much easier to take definite positions than to be agnostic because if I was agnostic, I was less motivated to find the truth. I’m still that way.

I was also very literal and still am. So, for example, when I was about 12, the janitor of my church, an older man, took a liking to me and I liked him, and he invited me to his and his wife’s place on a Sunday afternoon. We got talking about politics, of which I knew next to nothing, and he made the claim that the newly formed New Democratic Party was communist. I said that was false. He insisted it was true. I made my mother the arbiter. I called her up and asked her if it was true. She said it was false and I handed the phone to my friend so she could tell him. I now realize that probably he was saying they were communist inclined and there was some truth to that for the more extreme members. But then he should have said that.

About 3 weeks ago, I started thinking, based on my reading, that we would have somewhere between 200,000 and 500,000 U.S. deaths from COVID-19. So I stated the minimum 200,000 number on discussions of various people’s Facebook posts, hoping to have people argue back and say I was either overstating or understating. One person who disagreed with me and thought I was too pessimistic was my friend and co-author Charley Hooper. So I called him a few weeks ago to find out why. He walked me through his reasoning, based on the Diamond Princess cruise ship data, and I kind of filled in some of my own numbers, to come up with my position.

In the midst of it, I made a bet. Whereas my co-blogger Bryan Caplan bets to make people stand by their claims and his George Mason University colleague Alex Tabarrok says, “A bet is a tax on bulls**t,” my motivation is somewhat different. There’s an overlap: I want to make other people stand by their claims. But I also want to make myself stand by my claims. In other words, I want to tax my own thing that rhymes with pullkit. I want to motivate myself to get the right answer. And both prepping for the bet and making the bet motivate me. Before the bet, I think carefully with money at stake. After the bet, I’m more motivated to keep thinking.

I think sometimes friends on Facebook who think they know me are surprised. I’ll make a casual assertion, when there’s no money at stake, and then wait and see what other FB friends, many of whom are very smart and very thoughtful, will say. I’ve been doing that particularly with the COVID-19 issue. After seeing what they say, I sometimes thank them for the thoughtful discussion because I learned from it. In one case recently that was not about COVID-19 per se but, instead, was about Donald Trump’s handling of it, the comments caused me to completely switch my position. I explained to one of the other commenters that that did not motivate me to delete the post because there was a lot of good learning that went on, for me certainly and probably for other readers.

One friend recently said on his own post on FB, in no uncertain terms, that people who are not epidemiologists should, essentially, quit opining about the epidemiology of the COVID-19 issue. What rubbed me the wrong way was not mainly the anger with which he expressed it. More fundamentally, it went against my Socratic way of learning.

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Econlib April 2, 2020

“This isn’t the last such crisis we’ll have”

Actually, it very likely is. The first and the last.

AFAIK, the world has never had a global pandemic where vast numbers of people stopped working out of fear of becoming infected. We have had pandemics where vast numbers of people stopped working because they were dead. But that’s nothing like what we have today.  (The Spanish flu was associated with only a very brief and mild recession.)

As for the future, who can say? We now have a company that has a million thermometers in circulation, all linked to a central database. It picked up the oncoming disaster in America well before most other people, but its warnings were ignored by the government. Now this company says that the number of high fevers in America is falling fast. We shall see.

Does anyone doubt that this is the wave of the future—connecting IT with medicine? That we’ll be able to spot epidemics in real time?  Does anyone doubt that in the future our ability to test huge numbers of people for viruses will be scaled upward dramatically? It was 102 years between the Spanish flu and this epidemic. Say it’s another 57 or 91 or 114 years until the next big one. Does anyone feel confident predicting what health care will look like that far into the future?

Don’t get me wrong, I believe we will face major medical challenges in the future. There’s a growing risk of antibiotic resistant bacteria. Perhaps a deadly flu will jump from animals to humans. But it’s dangerous to assume that we know what form the next emergency will take.

We’d be smarter not to be reactive, focusing all our planning on a repeat of the coronavirus. Maybe we should focus our thinking on a wider range of possible crises. We should be trying to prevent terrorists from using bioweapons, or AI run amok, or accidental nuclear war, or asteroid strikes. I don’t know what the next global crisis will look like, but I very much doubt it will be a replay of the crisis of 2020.

Look for something totally unexpected, coming out of the blue.

And remember, the US government was almost completely unprepared, despite numerous warnings from experts.

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Econlib April 2, 2020

Tomorrow’s Reported Unemployment Rate for March

Tomorrow morning, when the Bureau of Labor Statistics reports the unemployment rate for March, don’t be surprised if it’s very low. I predict that it will be not much more than 4 percent and maybe even less. But that statistic will not really tell you much about the unemployment rate in March.

Here’s why. As the BLS explains on its web site:

Each month, highly trained and experienced Census Bureau employees contact the 60,000 eligible sample households and ask about the labor force activities (jobholding and job seeking) or non-labor force status of the members of these households during the survey reference week (usually the week that includes the 12th of the month).

Almost all the layoffs happened after March 14.

But the unemployment rate for April that will be reported on May 1, which, ironically, is known as International Workers Day? OMG!

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Econlib April 2, 2020

Home is Where the Zoning Is

“I don’t know how you get people back to realizing that when I buy a piece of property I have some say in what I can do on my property, but I don’t have the right to control what my neighbors do with their property.” Jenny Schuetz

 

It’s said that moving homes is one of the most stressful life experiences we can endure. This week’s episode may shed some light on why. EconTalk host Russ Roberts welcomes Jenny Schuetz, whose work focuses on land use and housing. The conversation is based in part on a recent article Schuetz wrote on what we can learn about housing from Little Women. What are these lessons Schuetz thinks we’ve missed in the 21st century? Why aren’t property rights enough to determine how land is used, and what sort(s) of housing options it might support? Why can’t we address the problem of homelessness in urban areas more effectively? And how have we turned some of our most beloved urban centers into nothing more than “museums” for the wealthy to enjoy?

 

Let’s hear what you think about these challenging issues. Use the conversation starters below to get you going.

 

 

1- What are some of the regulatory barriers to new home building Schuetz describes, and which do you  think are the most pernicious? Why?

 

2- What lesson(s) are we to learn from the Great Recession about housing, according to Schuetz? Why has the number of real estate development firms gone down since the Great Recession?

 

3- How does the bootlegger and Baptist theory apply to housing development? Schuetz says, “…the problem is: The only people who get to vote, who get to put direct political pressure on elected officials, are the people who already live there. The people who would benefit from the new housing live in another jurisdiction altogether.” What does she mean, and what are some of the consequences of this?

 

4- How are zoning and land use regulations contributing to increasing rates of homelessness? Why do both Roberts and Schuetz insist it’s NOT appropriate to blame “greedy landlords” for people not being able to afford housing? To what extent do you agree?

 

5- Roberts asks Schuetz why zoning and land use regulations have become so much more restrictive over the past several decades. How does she respond? Similarly, he asks what she thinks ought be done. How does Schuetz advocate the use of “fiscal tools” to change people’s behavior? To what extent does she convince you?

 

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Econlib April 2, 2020

Pandemics and the Problem of Expert Failure (cont.)

Part 3: Should Experts Have Power?

In my last two EconLog essays (here and here), I examined some of the causes of expert failure seemingly at work in the present crisis. I pointed out that we don’t know how to strike a balance among the different expert silos such as medicine and economics. And I pointed out that in many areas of expertise, state-supported professional associations enforce uniformity of opinion so that we don’t get the sort of flexible thinking and multiple perspectives we need even more urgently now than in normal times. I don’t know which epidemiological models are best. And nobody knows the best policy package. We cannot somehow escape the urgent necessity of making collective choices to fight COVID-19. In this difficult moment, we should be respectful of the extreme difficulty of formulating policy. In the midst of it all, however, we should also reflect on how very hard it has been to wisely deploy expertise in a crisis. Is there a better way?

I think we have made our lives harder – and put them at greater risk – by trying to contain expertise in officially recognized boxes controlled by the very experts ensconced within them. I refer to the “expertists template” ofcertification, professional education, and continuing education that I described in my previous essay in this series. When expertise is organized into state-supported professional organizations such as the AMA, it tends to enforce orthodoxy. And that means less pliable, flexible, and adaptive thinking. It means less tinkering and more doctrine. Oops.

The expertist template is premised on the view that knowledge is hierarchical. It starts at the top with science and cascades down to ever lower levels of the knowledge hierarchy. Mere practitioners must not question theknowledge elite. But questioning is precisely what we need in crises. In his essay, “What is Science?” Richard Feynman remarked “Science is the belief in the ignorance of experts.” When we give experts power, including the power to decide who the experts are, we choke off science. The premise of a rigid hierarchy of knowers is mistaken. The knowledge we need in normal times and crisis times alike is distributed. It’s out there in thee and me and in all our habits practices and experience. It is not a set of instructions and doctrines coming from on high. It arises of its own from our many decentralized interactions. 

Let’s take an example. The pandemic has produced a shortage of “personal protective equipment” (PPE) such as masks and gowns. What can we do? One very helpful solution comes out of a relatively small company in Ohio, Battelle. They have amachine that can clean large quantities of PPE in a hurry. The knowledge of how to do it did not come down from scientific inquiry, but up from entrepreneurial action. And yet, as I write, the knowledge elite at the FDA “has authorized Columbus-based Battelle to sterilize only 10,000 surgical masks in Ohio each day, despite their ability to sterilize up to 160,000 masks per day in Ohio alone.” The official knowledge hierarchy is squelching the sort of adaptive tinkering that we need to improvise our way out of this mess.  

This distributed quality of expertise follows from its source in the division of labor. As I said in the first essay of this series, the division of knowledge is the flip side of the division of labor. But that means that is it not some simple hierarchy dictated from on high. It is emergent, protean, and evolving. It does not cascade down, it bubbles up. 

Consider ventilators. March 24th, the FDAlifted many of restrictions on ventilators. Hospitals have been restricted to using only “FDA-cleared ventilators.” The lifting of restrictions reveals the folly of pretending that the knowledge elite can pre-decide what medical equipment is acceptable. Just as they could not reasonably have foreseen the current pandemic, they cannot reasonably foresee the many idiosyncratic particulars of time and place that might turn otherwise sensible regulations into life-threatening folly. If there had been no such restrictions in the first place, how many new emergency ventilators might have long since arrived in our hospitals? Instead, we have seen “ventilator sharing.” And can we be sure that there are no remaining restrictions that should also be lifted? You still require FDA approval; it’s just that the FDA approves more things.  

We need a better way. We need a resilient system in which local knowledge comes with local decision-making authority. But, how do we get there? Because we have had a relatively controlled and hierarchical system, markets have not had much opportunity to work up the sort of institutions and arrangements we need when choosing among experts. If we just tear down the expertist template, we will be left without guidance. Let us set to work then, at the hard task of learning how to dispense with the expertist template and return power and energy to entrepreneurialism. 

 

 


Roger Koppl is Professor of Finance in the Whitman School of Management of Syracuse University and Associate Director of Whitman’s Institute for an Entrepreneurial Society (IES).

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Econlib April 2, 2020

Teaching Teaching

Over the last three years, my older sons have gone from near-zero knowledge of Spanish to fluency.  Given my open disdain for foreign language education, what’s the backstory?

I started them in 9th grade because almost all good colleges impose an admission requirement of 3-4 years of foreign language instruction.  From the outset, my boys planned to demonstrate their competence on the Spanish Language AP test.  Going through the motions would not suffice; we knew my sons actually had to learn a lot of Spanish.  After a few sour months, fortunately, my sons started to like their new subject.  Then they became obsessed… in a good way.  Now they’ve taken college classes for natives in Spain and Guatemala, written a publishable paper on Mexican history using primary sources, and mostly speak Spanish to each other.

Since our emergency homeschool contains these two fluent Spanish-speakers, I thought it might be fruitful for my older sons to teach Spanish to their younger siblings.  After all, the younger ones are going to need a foreign language for college one day, too.

The catch: When Spanish instruction began last week, I realized that my older sons knew Spanish, but not how to teach.  As a result, I’m teaching teaching while they’re teaching Spanish.  Since I’ve been teaching professionally for about 25 years, its principles are second nature to me.  Yet if you’re now teaching for the first time in your life, they’re non-obvious.  Indeed, in my experience, over half of working teachers fail to internalize them.  As Morpheus admonishes in The Matrix, “Neo, sooner or later you’re going to realize, just as I did, that there’s a difference between knowing the path and walking the path.”

Principles of Effective Teaching

  1. Take the difficulty level you naturally want to use.  Now divide it by 10.  Remember: The material is only obvious to you because you are the teacher.  It is non-obvious to your students because they are the students.

  2. If you’re teaching at MIT or Caltech, you are now at the right difficulty level.  If you’re anywhere else, divide by 10 again.  Remember: Even smart people are, at first, terrible at almost everything.

  3. Don’t expects students to “figure things out for themselves.”  Start with model problems, then work through them at a snail’s pace.

  4. Once you have shown students clear model problems, assign a bunch of slightly different problems.  Tell them to get to work.  Mush!

  5. If your students do less than 75% of their problems correctly, your problems are still too hard.  Walk them through problems so easy you can’t even imagine their inability to do them.  This will improve their knowledge and your imagination.

  6. If your students do 75-94% of their problems correctly, give them more practice.  Drill, drill, drill.

  7. If your students do 95% of their problems correctly, they are ready to advance.  Even then, remember that they are likely to forget unless you periodically give them refresher work (except for highly sequential subjects).

  8. Never confuse logic with psycho-logic – and remember that psycho-logic is much more important for pedagogy.  What does that mean?  Don’t expect students to grasp that A–\B simply because A–\B.  Your job is to make truisms seem obvious to ignorant minds.  Vary your examples.  Mix it up.  Switch around.  Use repetition.  Use repetition.  Use repetition.

  9. Look at your students’ faces.  If they are bored, be more fun.  Tell jokes.  Mock yourself.  Clown around.  Playfully exaggerate all emotions.  Throw your pride aside; a teacher is an entertainer or he is a failure.

  10. Look at your students’ faces.  If they are frustrated, be more patient.  Never add negative emotion on top of negative emotion.  If a student is upset, be a model of mild-mannered stoicism.  Without fail.  Without fail.  Without fail.

  11. Look at your students’ faces.  If they feel like their efforts are pointless, sell them your subject.  Tell them what learning your subject will do for them, even if the only honest answer is, “You need this for graduation.”

  12. Look at your students’ faces.  If they don’t trust you, earn their trust.  Don’t merely avoid deception; be frank.  Don’t sugarcoat the world, even for little kids.  Unless the ugly truth will give them nightmares or get you fired, share it with equanimity.

  13. Look at your students’ faces.  If you can’t read their emotions, ask them questions.  Press them.  Find out what they already know.  Find out what confuses them.  Find out whether they are happy or sad or think you’re crazy.  Accept their answers beatifically and adjust your pedagogy to fit the students you actually have.

  14. Maintain discipline.  If you have a schedule, stick to it.  If you announce a punishment, stick to it.  If you promise a break, stick to it.  Education is for the students, but it is not a democracy.  Listen carefully to what your students stay, but only reform from a position of strength.  Don’t be generous; be magnanimous!  If you think this contradicts Principle #9, know that you are wrong.  Act like a jester – but rule like a king.

  15. All of these principles are optimized for one-on-one teaching.  If you’re teaching more students, you have to strike a balance.  You will always shortchange someone.  Sorry, that’s a classroom – another point in favor of homeschooling.

 

(5 COMMENTS)

Econlib April 1, 2020

Government Regulation of Poorer Entrepreneurs

Timothy Taylor over at Conversable Economist hits another home run with his lengthy excerpts from Harvard economist Edward Glaeser’s presidential address to the Eastern Economic Association. The speech is titled “Urbanization and Its Discontents.”

Although the whole post is well worth reading, here’s one paragraph that caught my attention:

Somewhat oddly, much of America appears to regulate low human capital entrepreneurship much more tightly than it regulates high human capital entrepreneurs. When Mark Zuckerberg started Facebook in his Harvard College dormitory, he faced few regulatory hurdles. If he had been trying to start a bodega that sold milk products three miles away, he would have needed more than ten permits. One question is whether the inequality that persists in America’s system is exacerbated by the legal and regulatory system.

I have three comments.

First, wow! Isn’t that interesting? It’s one more example of the government going after fledgling entrepreneurs trying to make a buck.

Second, sometimes when critics point out that government hurts poorer people, others conclude that the critics think government should hurt rich people too. I don’t. I’m glad that Zuckerberg was free to start Facebook. I just want everyone to be at least as free as he was. I would put a 0.9 probability on the idea that Glaeser agrees with me.

Third, this reminds me of a section in a classic 1989 article by Clive Crook in The Economist on third world economic development. The article was so good that I hired Clive to do a shorter version for the first edition of The Concise Encyclopedia of Economics, which was then called The Fortune Encyclopedia of Economics. The article, “Third World Economic Development,” is here. One of the things Clive pointed out is that a typical government policy in some African countries was to set tough price controls on the products of poor rural farmers to help the less-poor urban consumers. An excerpt:

Between 1963 and 1979 the price of consumer goods went up by a factor of twenty-two in Ghana. The price of cocoa in neighboring countries went up by a factor of thirty-six. But the price paid by the cocoa marketing board to Ghana’s farmers went up just sixfold. In real terms, therefore, the returns to cocoa farmers vanished. The country’s supposedly price-insensitive farmers responded by switching to production of other crops for subsistence, and exports of cocoa collapsed. Peru and Ghana are extreme cases, but they show in the starkest way that prices do matter in the the Third World and that rejecting market economics carries extremely high costs.

It’s not quite analogous to restrictions on poorer entrepreneurs in the United States because the U.S. restrictions hurt their putative customers as well as the entrepreneurs. Price controls on African farmers also hurt some consumers who are left out but help those who are first in line.

(8 COMMENTS)

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