Econlib

Making Canada Great for the first time, by Scott Sumner

Canada has always been a rather successful country by global standards, with relatively high living standards, good human rights, lots of green space, not much civic strife, and other nice features. Canada is nice.

Now for the first time, Canada has a chance to become great :

Behind the robust health are data showing Canada transitioning to a technology juggernaut from a country defined by its dependence on fossil fuels. While the government continues to subsidize coal, gas and oil, which account for 77% of the nation’s energy needs, the correlation between the price of oil and Canadian stocks has all but disappeared since Trudeau became prime minister, according to data compiled by Bloomberg. The traditional interdependence of stocks and oil prevailed during the 10 years preceding his election. . . .

The changes coincide with the growing perception of Canada as a haven, benefiting from President Donald Trump’s xenophobic restrictions on refugees and other immigrants. The nation of 37 million recorded its biggest immigration wave in more than a century last year, admitting 321,065 people, the most since 1913 . . .

Unlike Trump, Trudeau welcomes foreign talent, and his government’s Global Skills Strategy attracted about 24,000 technology workers and other skilled employees in the two years since it started, according to government figures released in June. Companies are saying that “the two-week processing has really transformed how they make business decisions,”

As a share of its population, Canada is admitting three times as many immigrants as the US.  Meanwhile, the Trump administration is making it tougher for high-skilled immigrants to come here, even as illegal immigration increases. Here’s Noah Smith:

Now, the Trump administration has launched a new attack on H-1B workers. Denial rates for H-1B applications have soared.

Canada does have one anti-immigrant party, but it did not do well in yesterday’s election, to put it mildly:

The election’s biggest loser was Maxime Bernier, a populist leader who embraces his nickname “Mad Max” and has pushed against immigration and what he calls “extreme multiculturalism” and “climate change hysteria.” His People’s Party was shut out of Parliament with not a single candidate, including Mr. Bernier, winning a seat.

One sign of Canada’s success is that people pay almost no attention to its elections. Switzerland is another example. I pity those countries where national elections are highly consequential.

I see little evidence that President Trump is “Making America Great Again”, but as his immigration policies divert talented people to Canada, he is certainly helping to make that country great.

(6 COMMENTS)

The Public Choice Problems with Carbon Taxes, by David Henderson

Adrian College political science professor James Hanley, responding to this editorial in the Washington Post, wrote the following on Facebook and gave me permission to use it as a post.

Here’s James. (What’s in the box is what James is quoting from the Washington Post editorial.)

Advocating a carbon tax of 75, the author writes:

Electricity prices would rise 70 percent on average — though only 53 percent in the United States — and gasoline prices 5 percent to 15 percent in most places.

But that’s the picture before one considers what the money raised by a carbon tax could do. If governments recycled the revenue back to low-income and vulnerable people, and cut economically inefficient taxes — such as income taxes — a 50-per-ton carbon tax would feel to the economy more like 20 per ton. The plan would help low-income households and place a higher burden on the upper-income bracket. There could also be money for essential research and development to aid the energy transition.

Stop right there. This “simple” direct plan for controlling CO2 emissions just got really complex. IF government recycles the money back to low income people, and IF the government cuts economically inefficient taxes, THEN the plan won’t run into insurmountable political opposition or hurt the poor so badly no person could in good conscience support it.

This is like saying you’re going to cut your travel time by driving faster, and all that’s necessary is that there be no traffic, no police, and no bad weather. Just as you cannot control those things, the advocates of a carbon tax – not only outside of government but inside it – cannot control the decisions about how to distribute that money and what other tax adjustments to make.

Their theory of government is not how the thing works. Government does not rationally make all the proper adjustments that will make something work. Government is not a conscious entity that has an incentive to do any such thing, but a conglomeration of individuals with various interests in varying offices responding to the demands of various individuals. And the tug of war between all those varying interests pulls pieces off of policies here, slices there, and so on. And that additional policy on which your primary policy’s success (political or technical) is predicated has its own wholly separate legislative path to tread.

Could a carbon tax reduce CO2? Absolutely. Can it so simply be made politically palatable and unharmful to the poor? Not remotely.

That’s James.

Now this is David. I agree that a carbon tax would reduce the amount of CO2 relative to what it would have been. As regular readers of this blog know, that doesn’t mean I favor such a tax. And that’s for reasons other than public choice reasons. But James Hanley does one of the nicest jobs I’ve seen of succinctly pointing out the public choice problems with a carbon tax.

(6 COMMENTS)

The Roots of Inertia, by Bryan Caplan

Why don’t low-skilled workers try harder to better their condition?  While this might seem a neoliberal question, it weighs on Barbara Ehrenreich’s mind:

I was baffled, initially, by what seemed like a certain lack of get-up-and-go on the part of my fellow workers. Why didn’t they just leave for a better-paying job, as I did when I moved from the Hearthside to Jerry’s?

She starts with some textbook economic answers.  There’s transaction costs:

Part of the answer is that actual humans experience a little more “friction” than marbles do, and the poorer they are, the more constrained their mobility usually is. Low-wage people who don’t have cars are often dependent on a relative who is willing to drop them off and pick them up again each day, sometimes on a route that includes the babysitter’s house or the child care center… I have mentioned, too, the general reluctance to exchange the devil you know for one that you don’t know, even when the latter is tempting you with a better wage-benefit package. At each new job, you have to start all over, clueless and friendless.

And information costs:

There is another way that low-income workers differ from “economic man.” For the laws of economics to work, the “players” need to be well informed about their options…

But there are no Palm Pilots, cable channels, or Web sites to advise the low-wage job seeker. She has only the help-wanted signs and the want ads to go on, and most of these coyly refrain from mentioning numbers. So information about who earns what and where has to travel by word of mouth, and for inexplicable cultural reasons, this is a very slow and unreliable route…

Soon, however, she appeals to industrial psychology.  Employers win workers hearts and minds – what Ehrenreich calls, “the co-optative power of management, illustrated by such euphemisms as associate and team member.”  And don’t forget learned helplessness:

Drug testing is another routine indignity. Civil libertarians see it as a violation of our Fourth Amendment freedom from “unreasonable search”; most jobholders and applicants find it simply embarrassing…

There are other, more direct ways of keeping low-wage employees in their place. Rules against “gossip,” or even “talking,” make it hard to air your grievances to peers or-should you be so daring-to enlist other workers in a group effort to bring about change, through a union organizing drive, for example. Those who do step out of line often face little unexplained punishments, such as having their schedules or their work assignments unilaterally changed. Or you may be fired…

The big picture, though, is that the capitalist system breaks workers’ spirits:

So if low-wage workers do not always behave in an economically rational way, that is, as free agents within a capitalist democracy, it is because they dwell in a place that is neither free nor in any way democratic. When you enter the low-wage workplace-and many of the medium-wage workplaces as well- you check your civil liberties at the door, leave America and all it supposedly stands for behind, and learn to zip your lips for the duration of the shift. The consequences of this routine surrender go beyond the issues of wages and poverty. We can hardly pride ourselves on being the world’s preeminent democracy, after all, if large numbers of citizens spend half their waking hours in what amounts, in plain terms, to a dictatorship.

The obvious response to all of these stories, however, is: “Why don’t the same factors prevent high-skill workers from trying to better their condition?”  Let’s consider each in turn.

Transaction costs.  While high-skilled workers have fewer problems with transportation and child-care, they also have much more specific skills.  This seriously impedes job search.  To find a new job, most nuclear engineers – and many professors – would have to not just sell their homes, but move to a new city.  The high-skilled are also more likely to be in two-earner families, which makes relocation doubly disruptive.

Information costs.  Firms often publicly advertise low-skilled wages.  This is much less true for high-skilled jobs.

Hearts and minds.  High-skilled workers seem much more likely to identify with their employer – and to define themselves in terms of their work.

Learned helplessness.  Again, the indignities required for starting a high-skilled job probably exceed those for low-skilled employment, especially if you’re a government contractor.  Once hired, however, the petty indignities high-skill workers endure are admittedly lower.  (Here’s why).

The capitalist system. Almost no employer cares for kvetching, but high-skill workers probably feel freer to speak up on the job.  Off the job, however, they are probably more worried about offending bosses, co-workers, or clients.  Who cares what a waiter posts on Facebook?  In any case, why should lack of voice reduce enthusiasm for exit?

So why then don’t low-skill workers try harder to better their condition?  All of Ehrenreich’s answers prove too much.  The better story is simply that there is a distribution of desire to better your condition.  In short, human beings have heterogeneous ambition. Some burn to rise; others take life as it comes; most lie somewhere in the middle.  And though mere desire hardly ensures success, ambition usually works in the long-run.  The more you want to better your condition, the better your condition eventually tends to become.

Like Ehrenreich’s story, my story explains why low-skill workers seem “stuck.”  Unlike her, however, I can also explains why high-skill workers seem mobile.  In short, what my “heterogeneous ambition” story lacks in Social Desirability Bias, it makes up for by explaining mobility and inertia, rather than inertia alone.

(10 COMMENTS)

Will “soak the rich” make Democratic states feel blue?, by Scott Sumner

In the 2018 midterms, my congressional district in southern Orange County elected a Democrat named Katie Porter. Although she is quite progressive, she strongly opposes the new cap on deductions state and local taxes (SALT). Southern Orange County is mostly upper middle class, and this tax change hits our area harder than many other parts of the US.

Nonetheless, the cap on SALT deductions is a progressive provision in the tax code, with the higher tax burden falling overwhelmingly on the top quintile. It also makes the tax code more efficient.  As an aside, this was part of a GOP bill that also cut tax rates for affluent taxpayers. So the net effect of the tax bill was probably positive for my district.  It was certainly positive for me, and I’m a fairly typical resident.

At the national level, the Democrats are moving in a “soak the rich” direction, with both Sanders and (frontrunner) Warren proposing wealth taxes for the rich.  But how do the blue states feel about these ideas?

Liberty City, by David Henderson

DEKORNFELD: But nothing would prepare him [James Massey] for what he would find in Von Ormy because all those classes were about building city government. And in Von Ormy, the sole goal seemed to be the opposite.

This is from “The Liberty City,” episode 945 of Planet Money, October 18, 2019.

The whole thing is interesting and, at times, hilarious.

How Von Ormy, Texas started as a city:

DEKORNFELD: Art [Martinez de Vara] told people, look; San Antonio is a growing metropolis. And in the near future, they are going to try to annex us, and that will come with big city taxation. And you know what it won’t come with? Representation.

FOUNTAIN: Or, Mayor Art says, we could see the writing on the wall and come together and do this our own way.

DEKORNFELD: He says people were into it. So he circulated a petition, brought it to a county judge, and the judge ordered an election.

Getting Rich on Low Pay, by David Henderson

The key is high saving.

Here’s an amazing story about a worker on Wall Street making 40,000 a year and saving 10,500 a year in a 401(k) for 12 years. By the end, he was a millionaire.

Sam Dogen went to extremes to save that much money in such a short time. And I don’t condone his stealing food from his employer, although that “theft” [he puts it in quotation marks and so I don’t know if it was really theft] saved him only a small amount of money.

But what I always take from such stories is that if you really start to focus on what you spend and make some careful decisions, you can save a lot. Let’s say, for example, that you really do want your own room and you split a one-bedroom with a friend, paying 1,300 a month (remember that this was in 2000) rather than splitting a studio and paying 900 a month, your annual saving would have been about 4,500. (I’m also taking into account the reduced tax advantage from saving less in a 401(k)).

Here’s my version of what Sam did. Living in high-tax New York state in 1975-76 and making 20,000 gross at the University of Rochester over 12 months, I saved 9,300.

Theory and practice, by Scott Sumner

Before getting to today’s post, I’d like to correct my previous post on Brexit.  When discussing the impact of Brexit on British growth, I forgot the evidence from asset prices.  The British pound falls on news that Brexit is more likely, and falls even more on “no deal Brexit” becoming more likely.  It’s hard to quantify that evidence, but it certainly counts for something.

Alex Tabarrok discusses research by the recent winners of the Nobel Prize in Economics.  This comment is worth thinking about:

Michael Kremer wrote two of my favorite papers ever. The first is Patent Buyouts which you can find in my book Entrepreneurial Economics: Bright Ideas from the Dismal Science. The idea of a patent buyout is for the government to buy a patent and rip it up, opening the idea to the public domain. How much should the government pay? To decide this they can hold an auction. Anyone can bid in the auction but the winner receives the patent only say 10% of the time–the other 90% of the time the patent is bought by the government at the market price. The value of this procedure is that 90% of the time we get all the incentive properties of the patent without any of the monopoly costs. Thus, we eliminate the innovation tradeoff. Indeed, the government can even top the market price up by say 15% in order to increase the incentive to innovate. You might think the patent buyout idea is unrealistic. But in fact, Kremer went on to pioneer an important version of the idea, the Advance Market Commitment for Vaccines which was used to guarantee a market for the pneumococcal vaccine which has now been given to some 143 million children. Bill Gates was involved with governments in supporting the project.

Economists like to dream up optimal policy regimes.  For instance, I’ve discussed how monetary policy could be guided by the forecasts embedded in asset market prices.  One option is to peg the price of NGDP futures contracts at a level consistent with 4%/growth in NGDP.

One counterargument is that this policy is not currently politically feasible, which is true.  But these thought experiments can have value even if the hypothetical policy is not actually adopted, as we can see in the case of patent auctions.  There are many similar examples.  Thus, if carbon taxes are not politically feasible, then tradable pollution permits might be a close substitute.

In my view, monetary policy is already paying increasing attention to forecasts embedded in asset prices, and the role of market forecasts will continue to increase over time.  I doubt that central banks will ever adopt the precise policy that I’ve been advocating, but I also believe that by 2035 the Fed will be implementing policies that the market expects will result in roughly on target outcomes.  Exactly how they do that remains to be seen.

PS.  People often argue that economics is not a real science, unlike physics.  That debate is silly, as it’s not an argument about the nature of economics; it’s an argument about how we should define “science”.  But if I wanted to make that argument (and I don’t) here’s what I would point to:

In 1978, Arno Penzias and Robert Wilson were awarded Nobel Prizes in Physics for noticing that there is background radiation throughout the sky.  AFAIK, no one has ever won a Nobel Prize in Economics for this sort of random discovery.  Instead, Nobel Prizes are awarded to very distinguished economists for major theoretical breakthroughs, or else a long history of important empirical work. If there are exceptions, then please let me know.

Why can’t a single lucky discovery be worthy of a Nobel Prize in Economics?

PPS.  Please don’t tell me that the economics prize is “not a real Nobel Prize”.  That’s even more tedious than the claim that economics is not a science.

(6 COMMENTS)

Don’t Ignore the Median Voter Theorem, by David Henderson

Marc A. Thiessen writes:

With three polls showing her in the lead, Sen. Elizabeth Warren (D-Mass.) may soon eclipse former vice president Joe Biden as the front-runner for the Democratic presidential nomination. That’s great news for Republicans, because Warren has a problem: The central message of her campaign is that the economy is working for the very wealthy but it is not working for ordinary Americans. Unfortunately for her, ordinary Americans disagree.

That is great news for Republicans. But that doesn’t mean it’s great news for people who support Republicans because they don’t like left-wing economic policies. In fact it’s bad news for them.

And the reason has to do with the median voter theorem. Here’s what William F. Shughart II writes in “Public Choice,” in David R. Henderson, ed., The Concise Encyclopedia of Economics:

Studying collective decision-making by committees, Duncan Black deduced what has since been called the median-voter theorem. If voters are fully informed, if their preferred outcomes can be arrayed along one dimension (e.g., left to right), if each voter has a single most-preferred outcome, and if decisions are made by simple majority rule, then the median voter will be decisive. Any proposal to the left or right of that point will be defeated by one that is closer to the median voter’s preferred outcome. Because extreme proposals lose to centrist proposals, candidates and parties in a two-party system will move to the center, and, as a result, their platforms and campaign promises will differ only slightly. Reversing 1964 presidential hopeful Barry Goldwater’s catchphrase, majority-rule elections will present voters with an echo, not a choice. If the foregoing assumptions hold, the median voter’s preferences also will determine the results of popular referenda. As a matter of fact, anticipating that immoderate proposals will be defeated, the designers of ballot initiatives will strive to adopt centrist language, in theory moving policy outcomes closer to the median voter’s ideal point than might be expected if decisions are instead made by politically self-interested representatives.

Those 4 assumptions are quite strong and unlikely to hold up in the real world. But that doesn’t mean the median voter theorem is useless. It still has power in explaining two things: why candidates’ platforms in a general election, when 2 parties contend, will often be similar. Think of Nixon and Humphrey in 1968: that’s the first presidential election I followed somewhat closely. I remember pundits referring to them as Tweedledum and Tweedledee. (Some wags at the time referred to them as Tweedledum and Tweedledumber.) There wasn’t a huge difference between the policy positions they articulated (with one important exception: Nixon promised to end the draft.)

Or think about what happened in the Goldwater/Johnson election. Vietnam was a big issue, as the war was just getting going. Goldwater took an extreme position in favor of the war. Did Johnson go all dove? No. He was pro-war also, but less extreme. That led to the old joke that might have actually been based on an actual voter’s comment: “I was told that if I voted for Goldwater, we’d bomb North Vietnam. So I voted for Goldwater and sure enough we bombed North Vietnam.” And LBJ won with about 60% of the vote.

If a politician wants mainly to win, and if his opponent takes positions that are far from the median voter’s view, his best strategy is not to take the same views but to move towards that view. He wants to motivate his base to show up at the polls and so he’s unwise to go all the way to the opponent’s views, but he will go some of the way.

So in this case, with Elizabeth Warren being so far left, if she wins the nomination Donald Trump’s best strategy is to move further left than he would have if he had run against a more-moderate Democratic candidate. So it wouldn’t be surprising to see Trump advocate, say, a 10 or 12 an hour minimum wage, to take just one example.

The only exception would be if the politician is highly principled and if his main goal is to implement particular policies rather than to win. Does that sound like Donald Trump to you?

By the way, I posted about this 2 years ago.

(23 COMMENTS)

Trump’s Economic Policies, Part I, by David Henderson

We’ve now had over two and a half years of President Donald Trump’s economic policies. While that time is relatively short, it gives us some basis for judging those policies. I judge him in two ways: (1) as a believer in economic freedom and (2) as an economist who cares about people’s economic wellbeing. By those criteria, some of Trump’s policies have been very good indeed and some have been horrid. Specifically, the former have been the 2017 tax cut and his substantial deregulation and holding off on new regulations. The horrid policies have been those on trade, immigration, and federal government spending.

In this essay, I’ll discuss the very good indeed. Part Two, in a fortnight, will focus on the horrid.

These are the opening paragraphs of my article “Trump’s Economic Policies: An Assessment, Part 1,” Defining Ideas, October 17, 2019.

A large part of the piece is on the 2017 tax cut. The longer I’ve had to think about it, along with my own experience with it while doing my 2018 taxes, the more impressed I am by it. And I’m especially impressed by the cut in the corporate income tax rate.

Another excerpt:

One rough and ready way to estimate the net effect of all of Trump’s economic policies is to compare the growth of real GDP during his time in office with that of Obama.

Obama deserves no blame for the recession that he inherited when he entered office. That recession ended in the second quarter of 2009. Let’s stack the deck slightly in his favor by giving him credit for the growth from the second quarter of 2009 to the first quarter of 2017. I say “in his favor” because during recoveries from recessions, real GDP growth is typically high. From the second quarter of 2009 to the first quarter of 2017, real GDP grew by an annual average of 2.2%.

How about real GDP growth under Trump? He should get little to no credit for growth during the first quarter of 2017 because he was in office for only a little over 2 months of that quarter and his policies had little time to work. So let’s give him credit for real GDP growth between the first quarter of 2017 and second quarter of 2019, the latest quarter for which we have data. During that time, real GDP grew by an annual average of 2.7%, which was half a percentage point higher than the growth rate during Obama’s time in office.

That’s substantial. What makes that 0.5 extra percentage points of annual growth even more striking is that it happened years after the economic recovery occurred, and growth rates well after recoveries tend to fall.

So the good news is that the economic policy issues on which Trump has been “very good indeed” seem to have outweighed the policy issues on which he has been “horrid.”

Read the whole thing.

(20 COMMENTS)

How Crackpotted is Your Economics?, by Sarah Skwire

Courtesy of a lovely little article in Lapham’s Quarterly titled “Beware of Cranks” I have recently discovered the incredibly useful“Crackpot Index” developed in 1992 by the physicist John C. Baez as a way of computing precisely how nutty the nutty theories of various amateur mathematicians are.

Mathematicians apparently have a particular need for this kind of rating system. A similar crackpot index exists for theories specifically aboutprime numbers, and anearlier index—more narrative in style—appeared in 1962.  

It occurs to me that with relatively few alterations, any of these Crackpot Indexes could be adapted for the assessment of theoreticians in economics, which might prove useful as we enter another heated political season.

 I leave said alterations as an exercise for the comments section as my PhD is in literature, and therefore my crackpottedness is proven by assumption.

So what do you think? What should the economics Crackpot Index look like?

The Crackpot Index

John Baez

1. A -5 point starting credit.
2. 1 point for every statement that is widely agreed on to be false.
3. 2 points for every statement that is clearly vacuous.
4. 3 points for every statement that is logically inconsistent.
5. 5 points for each such statement that is adhered to despite careful correction.
6. 5 points for using a thought experiment that contradicts the results of a widely accepted real experiment.
7. 5 points for each word in all capital letters (except for those with defective keyboards).
8. 5 points for each mention of “Einstein”, “Hawkins” or “Feynmann”.
9. 10 points for each claim that quantum mechanics is fundamentally misguided (without good evidence).
10. 10 points for pointing out that you have gone to school, as if this were evidence of sanity.
11. 10 points for beginning the description of your theory by saying how long you have been working on it. (10 more for emphasizing that you worked on your own.)
12. 10 points for mailing your theory to someone you don’t know personally and asking them not to tell anyone else about it, for fear that your ideas will be stolen.
13. 10 points for offering prize money to anyone who proves and/or finds any flaws in your theory.
14. 10 points for each new term you invent and use without properly defining it.
15. 10 points for each statement along the lines of “I’m not good at math, but my theory is conceptually right, so all I need is for someone to express it in terms of equations”.
16. 10 points for arguing that a current well-established theory is “only a theory”, as if this were somehow a point against it.
17. 10 points for arguing that while a current well-established theory predicts phenomena correctly, it doesn’t explain “why” they occur, or fails to provide a “mechanism”.
18. 10 points for each favorable comparison of yourself to Einstein, or claim that special or general relativity are fundamentally misguided (without good evidence).
19. 10 points for claiming that your work is on the cutting edge of a “paradigm shift”.
20. 20 points for emailing me and complaining about the crackpot index. (E.g., saying that it “suppresses original thinkers” or saying that I misspelled “Einstein” in item 8.)
21. 20 points for suggesting that you deserve a Nobel prize.
22. 20 points for each favorable comparison of yourself to Newton or claim that classical mechanics is fundamentally misguided (without good evidence).
23. 20 points for every use of science fiction works or myths as if they were fact.
24. 20 points for defending yourself by bringing up (real or imagined) ridicule accorded to your past theories.
25. 20 points for naming something after yourself. (E.g., talking about the “The Evans Field Equation” when your name happens to be Evans.)
26. 20 points for talking about how great your theory is, but never actually explaining it.
27. 20 points for each use of the phrase “hidebound reactionary”.
28. 20 points for each use of the phrase “self-appointed defender of the orthodoxy”.
29. 30 points for suggesting that a famous figure secretly disbelieved in a theory which he or she publicly supported. (E.g., that Feynman was a closet opponent of special relativity, as deduced by reading between the lines in his freshman physics textbooks.)
30. 30 points for suggesting that Einstein, in his later years, was groping his way towards the ideas you now advocate.
31. 30 points for claiming that your theories were developed by an extraterrestrial civilization (without good evidence).
32. 30 points for allusions to a delay in your work while you spent time in an asylum, or references to the psychiatrist who tried to talk you out of your theory.
33. 40 points for comparing those who argue against your ideas to Nazis, stormtroopers, or brownshirts.
34. 40 points for claiming that the “scientific establishment” is engaged in a “conspiracy” to prevent your work from gaining its well-deserved fame, or suchlike.
35. 40 points for comparing yourself to Galileo, suggesting that a modern-day Inquisition is hard at work on your case, and so on.
36. 40 points for claiming that when your theory is finally appreciated, present-day science will be seen for the sham it truly is. (30 more points for fantasizing about show trials in which scientists who mocked your theories will be forced to recant.)
37. 50 points for claiming you have a revolutionary theory but giving no concrete testable predictions.

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Susan Houseman on Manufacturing

Economist Susan Houseman of the Upjohn Institute for Employment Research talks about the manufacturing sector with EconTalk host Russ Roberts. Houseman argues that the data surrounding both manufacturing output and employment have been misunderstood and misinterpreted. In particular, she argues that conclusions about the growth of manufacturing are driven overwhelmingly by computer production while the […]

Andrew McAfee on More from Less

Andrew McAfee of MIT’s Sloan School of Management talks about his book, More from Less, with EconTalk host Russ Roberts. McAfee argues that technology is helping developed nations use fewer resources in producing higher levels of economic output. The improvement is not just a reduction in energy per dollar of GDP but less energy in […]

Ryan Holiday on Stillness Is the Key

Ryan Holiday talks about his latest book, Stillness Is the Key, with EconTalk host Russ Roberts. Holiday explores how stillness–the cultivation of serenity and focus–can affect how we live and how we perceive life. Topics discussed include the performance artist Marina Abramovic, Winnie the Pooh, the Cuban Missile Crisis, and Michael Jordan’s Hall of Fame […]

Sabine Hossenfelder on Physics, Reality, and Lost in Math

Physicist Sabine Hossenfelder talks about her book Lost in Math with EconTalk host Russ Roberts. Hossenfelder argues that the latest theories in physics have failed to find empirical confirmation. Particles that were predicted to be discovered by the mathematics have failed to show up. Whether or not there is a multiverse has no observable consequences. […]

Dani Rodrik on Neoliberalism

Dani Rodrik of Harvard University talks about neoliberalism with EconTalk host Russ Roberts. Rodrik argues that a dogmatic embrace of markets has increased inequality and limited who benefits from economic growth. He argues for a more interventionist approach to the economy with the goal of better-paying jobs and more widely shared prosperity.

George Will on the Conservative Sensibility

George Will talks about his new book, The Conservative Sensibility, with EconTalk host Russ Roberts. Will argues for a conservative vision that embraces the dynamic nature of life. Topics discussed include the current political landscape, the American founding, James Madison’s vision of government vs. Woodrow Wilson’s, Friedrich Hayek, and of course, a little baseball.

The post George Will on the Conservative Sensibility appeared first on Econlib.

Daron Acemoglu on Shared Prosperity and Good Jobs

Economist and author Daron Acemoglu of MIT discusses with EconTalk host Russ Roberts the challenge of shared prosperity and the policies that could bring about a more inclusive economy. Acemoglu argues for the importance of good jobs over redistribution and makes the case for the policies that could lead to jobs and opportunities across skill […]

David Deppner on Leadership, Confidence, and Humility

Can a great leader or manager be humble in public? Or is exuding confidence, even when it may not be merited, a key part of leadership? In this episode of EconTalk, host Russ Roberts talks with David Deppner, CEO of Psyberware, about an email David sent Russ wondering how Russ might reconcile his passion for […]

Andrew Roberts on Churchill and the Craft of Biography

Historian Andrew Roberts talks about the life of Winston Churchill and the art of biography with EconTalk host Russ Roberts. How did Churchill deal with the mistakes he inevitably made in a long career? Was he prescient or just the right man in the right place at the right time? Was he an alcoholic? Did […]

Tyler Cowen on Big Business

Author and economist Tyler Cowen of George Mason University talks about his book, Big Business, with EconTalk host Russ Roberts. Cowen argues that big corporations in America are underrated and under-appreciated. He even defends the financial sector while adding some caveats along the way. This is a lively and contrarian look at a timely issue.

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.

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.

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 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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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.

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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Jean Tirole

.jpg "Ecole polytechnique Université Paris-Saclay [CC BY-SA 2.0 (https://creativecommons.org/licenses/by-sa/2.0)], via Wikimedia Commons") 

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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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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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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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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Division of Labor

Division of labor combines specialization and the partition of a complex production task into several, or many, sub-tasks. Its importance in economics lies in the fact that a given number of workers can produce far more output using division of labor compared to the same number of workers each working alone. Interestingly, this is true even if those working alone are expert artisans. The production increase has several causes. According to Adam Smith, these include increased dexterity from learning, innovations in tool design and use as the steps are defined more clearly, and savings in wasted motion changing from one task to another.

Though the scientific understanding of the importance of division of labor is comparatively recent, the effects can be seen in most of human history. It would seem that exchange can arise only from differences in taste or circumstance. But division of labor implies that this is not true. In fact, even a society of perfect clones would develop exchange, because specialization alone is enough to reward advances such as currency, accounting, and other features of market economies.

In the early 1800s, David Ricardo developed a theory of comparative advantage as an explanation for the origins of trade. And this explanation has substantial power, particularly in a pre-industrial world. Assume, for example, that England is suited to produce wool, while Portugal is suited to produce wine. If each nation specializes, then total consumption in the world, and in each nation, is expanded. Interestingly, this is still true if one nation is better at producing both commodities: even the less productive nation benefits from specialization and trade.

In a world with industrial production based on division of labor, however, comparative advantage based on weather and soil conditions becomes secondary. Ricardo himself recognized this in his broader discussion of trade, as Meoqui points out. The reason is that division of labor produces a cost advantage where none existed before—an advantage based simply on specialization. Consequently, even in a world without comparative advantage, division of labor would create incentives for specialization and exchange.

Origins

The Neolithic Revolution, with its move to fixed agriculture and greater population densities, fostered specialization in both production of consumer goods and military protection. As Plato put it:

A State [arises] out of the needs of mankind; no one is self-sufficing, but all of us have many wants… Then, as we have many wants, and many persons are needed to supply them, one takes a helper… and another… [W]hen these partners and helpers are gathered together in one habitation the body of inhabitants is termed a State… And they exchange with one another, and one gives, and another receives, under the idea that the exchange will be for their good. (The Republic, Book II)

This idea of the city-state, or polis, as a nexus of cooperation directed by the leaders of the city is a potent tool for the social theorist. It is easy to see that the extent of specialization was limited by the size of the city: a clan has one person who plays on a hollow log with sticks; a moderately sized city might have a string quartet; and a large city could support a symphony.

One of the earliest sociologists, Muslim scholar Ibn Khaldun (1332-1406), also emphasized what he called “cooperation” as a means of achieving the benefits of specialization:

The power of the individual human being is not sufficient for him to obtain (the food) he needs, and does not provide him with as much food as he requires to live. Even if we assume an absolute minimum of food –that is, food enough for one day, (a little) wheat, for instance – that amount of food could be obtained only after much preparation such as grinding, kneading, and baking. Each of these three operations requires utensils and tools that can be provided only with the help of several crafts, such as the crafts of the blacksmith, the carpenter, and the potter. Assuming that a man could eat unprepared grain, an even greater number of operations would be necessary in order to obtain the grain: sowing and reaping, and threshing to separate it from the husks of the ear. Each of these operations requires a number of tools and many more crafts than those just mentioned. It is beyond the power of one man alone to do all that, or (even) part of it, by himself. Thus, he cannot do without a combination of many powers from among his fellow beings, if he is to obtain food for himself and for them. Through cooperation, the needs of a number of persons, many times greater than their own (number), can be satisfied. [From Muqaddimah (Introduction), First Prefatory Discussion in chapter 1; parenthetical expression in original in Rosenthal translation]

This sociological interpretation of specialization as a consequence of direction, limited by the size of the city, later motivated scholars such as Emile Durkheim (1858-1917) to recognize the central importance of division of labor for human flourishing.

Smith’s Insight

It is common to say that Adam Smith “invented” or “advocated” division of labor. Such claims are simply mistaken, on several grounds (see, for a discussion, Kennedy 2008). Smith described how decentralized market exchange fosters division of labor among cities or across political units, rather than just within them as previous thinkers had done. Smith had two key insights: First, division of labor would be powerful even if all human beings were identical, because differences in productive capacity are learned. Smith’s parable of the “street porter and the philosopher” illustrates the depth of this insight. As Smith put it:

[T]he very different genius which appears to distinguish men of different professions, when grown up to maturity, is not upon many occasions so much the cause, as the effect of the division of labour. The difference between the most dissimilar characters, between a philosopher and a common street porter, for example, seems to arise not so much from nature, as from habit, custom, and education. (WoN, V. 1, Ch 2; emphasis in original.)

Second, the division of labor gives rise to market institutions and expands the extent of the market. Exchange relations relentlessly push against borders and expand the effective locus of cooperation. The benefit to the individual is that first dozens, then hundreds, and ultimately millions, of other people stand ready to work for each of us, in ways that are constantly being expanded into new activities and new products.

Smith gives an example—the pin factory—that has become one of the central archetypes of economic theory. As Munger (2007) notes, Smith divides pin-making into 18 operations. But that number is arbitrary: labor is divided into the number of operations that fit the extent of the market. In a small market, perhaps three workers, each performing several different operations, could be employed. In a city or small country, as Smith saw, 18 different workers might be employed. In an international market, the optimal number of workers (or their equivalent in automated steps) would be even larger.

The interesting point is that there would be constant pressure on the factory to (a) expand the number of operations even more, and to automate them through the use of tools and other capital; and to (b) expand the size of the market served with consequently lower-cost pins so that the expanded output could be sold. Smith recognized this dynamic pressure in the form of what can only be regarded today as a theorem, the title of Chapter 3 in Book I of the Wealth of Nations: “That the Division of Labor is Limited by the Extent of the Market.” George Stigler treated this claim as a testable theorem in his 1951 article, and developed its insights in the context of modern economics.

Still, the full importance of Smith’s insight was not recognized and developed until quite recently. James Buchanan presented the starkest description of the implications of Smith’s theory (James Buchanan and Yong Yoon, 2002). While the bases of trade and exchange can be differences in tastes or capacities, market institutions would develop even if such differences were negligible. The Smithian conception of the basis for trade and the rewards from developing market institutions is more general and more fundamental than the simple version implied by deterministic comparative advantage.

Division of labor is a hopeful doctrine. Nearly any nation, regardless of its endowment of natural resources, can prosper simply by developing a specialization. That specialization might be determined by comparative advantage, lying in climate or other factors, of course. But division of labor alone is sufficient to create trading opportunities and the beginnings of prosperity. By contrast, nations that refuse the opportunity to specialize, clinging to mercantilist notions of independence and economic self-sufficiency, doom themselves and their populations to needless poverty.

About the Author

Michael Munger is the Director of the PPE Program at Duke University.

Further Reading

Buchanan, James, and Yong Yoon. 2002. “Globalization as Framed by the Two Logics of Trade,” The Independent Review, 6(3): 399-405.

Durkheim, Emile, 1984. Division of Labor in Society. New York: MacMillan.

Kennedy, Gavin. 2008. “Basic Errors About the Role of Adam Smith.” April 2: http://adamsmithslostlegacy.blogspot.com/2008/04/basic-errors-about-role-of-adam-smith.html

Khaldun, Ibn. 1377. Muqaddimah (Introductory) http://www.muslimphilosophy.com/ik/Muqaddimah/

Morales Meoqui, Jorge , 2015. Ricardo’s numerical example versus Ricardian trade model: A comparison of two distinct notions of comparative advantage DOI: 10.13140/RG.2.1.2484.5527/1 Link: https://www.researchgate.net/publication/283206070_Ricardos_numerical_example_versus_Ricardian_trade_model_A_comparison_of_two_distinct_notions_of_comparative_advantage

Munger, Michael. 2007. “I’ll Stick With These: Some Sharp Observations on the Division of Labor.” Indianapolis, Liberty Fund. http://www.econlib.org/library/Columns/y2007/Mungerpins.html

Plato, n.d. The Republic. Translated by Benjamin Jowett. http://classics.mit.edu/Plato/republic.html

Roberts, Russell. 2006. “Treasure Island: The Power of Trade. Part II. How Trade Transforms Our Standard of Living.” Indianapolis, Liberty Fund. http://www.econlib.org/library/Columns/y2006/Robertsstandardofliving.html

Smith, Adam. 1759/1853. (Revised Edition). The Theory of Moral Sentiments, New Edition. With a biographical and critical Memoir of the Author, by Dugald Stewart (London: Henry G. Bohn, 1853). 7/27/2015. http://oll.libertyfund.org/titles/2620

Smith, Adam. 1776/1904. An Inquiry into the Nature and Causes of the Wealth of Nations by Adam Smith, edited with an Introduction, Notes, Marginal Summary and an Enlarged Index by Edwin Cannan (London: Methuen, 1904). Vol. 1. 7/27/2015. http://oll.libertyfund.org/titles/237

Stigler, George. 1951. “The Division of Labor is Limited by the Extent of the Market.” Journal of Political Economy. 59(3): 185-193

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