Category: Uncategorized

1. In defense of Yoko Ono.  And Edward Hugh’s excellent update on whether the euro will survive.

2. David Warsh on Shapley.

3. Must dollar bills be stacked face up?

4. Are fruits and vegetables really really good for you?

5. Good reviews of the new Haitian art show in Nottingham.

6. John Cochrane on health care (pdf).

1. Garett Jones defends the electoral college.

2. Excellent macro post by Stephen Williamson.

3. The culture that is Japanese juggling (video).

4. Has the Japanese yen ceased to be a safe haven currency?

5. The opera boom in northern Mexico.

Get this:

Volapük didn’t die out completely. It has a bit of life today; there are a few online lessons and discussion boards. There is even a Volapük Wikipedia with over 100,000 articles. And its name lives on in the Danish expression det er det rene volapyk – “It’s pure Volapük,” or, in other words “It’s Greek to me.”

The article is here, the pointer is from Bookslut.

1. Analysis of how Bitcoin is actually used.

2. Are conservatives actually more generous than liberals?

3. Profile of Felix Salmon.

4. Can humans beat horses in marathons?  And what is special about human faces?  Interesting throughout.

5. Wedding markets in everything, assortative mating Star Trek edition.

Here is some new work by Gregory Clark (pdf):

What is the true rate of social mobility? Modern one-generation studies suggest considerable regression to the mean for all measures of status – wealth, income, occupation and education across a variety of societies. The β that links status across generations is in the order of 0.2-0.5. In that case inherited surnames will quickly lose any information about social status. Using surnames this paper looks at social mobility rates across many generations in England 1086-2011, Sweden, 1700-2011, the USA 1650-2011, India, 1870-2011, Japan, 1870-2011, and China and Taiwan 1700-2011. The underlying β for long-run social mobility is around 0.75, and is remarkably similar across societies and epochs. This implies that compete regression to the mean for elites takes 15 or more generations.

Here is NPR coverage:

“If I just know that you share a rare surname with someone who was wealthy in 1800, I can predict now that you’re nine times more likely to attend Oxford or Cambridge. You’re going to live two years longer than an average person in England. You’re going to have more wealth. You’re more likely to be a doctor. You’re more likely to be an attorney,” Clark says.

Dylan Matthews offers some charts.  For the pointer I thank Fred Rossoff.

1. The cardboard bicycle.

2. What is behind the Greek export surge?

3. Bird dysgenics?

4. What do we know about women’s pay and discrimination?

5. Will the UN be intervening into Mali?

1. Koreans win gold medal in Alphabet Olympics.

2. Russ Roberts and John Taylor on why the recovery is weak.  A new video method of teaching.

3. “Hot Dog Stuffed Crust Pizza Coming to Pizza Hut Canada.”

4. What makes a technology cool?

5. Affective computing, can computers read your moods?

6. Good and very insightful review of the educational philosophy behind MRU.

7. Jeff Sachs reviews Acemoglu and Robinson.

1. How come no one announced that Bhagwati occasionally blogs?

2. India’s schools turn to Khan Academy.

3. What would a 15-hour work week really look like?

4. Tom Murphy reviews MRU.

5. There is no great stagnation, and Thomas Edsall on TGS and Robert Gordon.

6. “If Korean women like it, it’s a success.”

In honor of the Nobel prizes to Al Roth and Lloyd Shapley, here is a primer on matching theory. Matching is a fundamental property of many markets and social institutions. Jobs are matched to workers, husbands to wives, doctors to hospitals, kidneys to patients.

The field of matching may be said to start with the Gale-Shapley deferred choice algorithm. Here is how it works, applied to men and women and marriage (n.b. the algorithm can also work for gay marriage but it’s a little easier to explain and implement with men and women). Each man proposes to his first ranked choice. Each woman keeps her top-ranked suitor but defers accepting the proposal. Each woman also rejects her lower ranked suitors. Each rejected man proposes to his second ranked choice. Each woman rejects again any lower-ranked suitors, which may include previous suitors who have now become lower-ranked. The process repeats until no further proposals are made; each woman then accepts her top-ranked suitor and the matches are made.

A similar process works when proposal receivers may accept more than one suitor, not that useful for marriage in most of the United States but very useful for when students are applying to schools and each school accepts many students.

Now what is good about this algorithm? First, Gale and Shapley proved that the algorithm converges to a solution for a very wide range of preferences. Second, the algorithm is stable in the sense that there is no man and no woman who would rather be matched to each other than to their current match. There are of course, men who would prefer to marry other women and there are women who would prefer to marry other men but no mutually preferable match is possible. Thus, the algorithm produces a stable match.

The application to men and women is somewhat fanciful, although Match.com should clearly adopt this idea!, but the application to students and schools is very real. Gale and Shapley concluded their paper by writing:

It is our opinion, however, that some of the ideas introduced here might usefully be applied to certain phases of the admissions problem.

Indeed, this is exactly what has happened. Students in New York and in Boston are now matched to schools using versions of this algorithm. Even before Gale and Shapley the algorithm had been used, without much theorizing, by doctors allocating residents to hospitals and since Gale-Shapley and Roth the idea has been used much more extensively all over the world .The algorithm, by the way, has been picked up and extended by computer scientists notably including Knuth.

I said above that the men propose to the women–this matters because when the women propose to the men you also get a stable match but it may be a somewhat different match and in general it is better to be the one proposing. Matching becomes more difficult when, as in modern times, both men and women may propose. Fortunately, in many problems, such as with students and schools, the proposers and receivers can be fixed.

Another question is whether the algorithm can be strategically manipulated. In an Impossibility Theorem with much the same flavor as Arrow’s Theorem and the Gibbard-Satterthwaite theorem, Roth and Roth and Sotomayor proved that there is always some possibility for manipulation but the G-S algorithm can be said to minimize the opportunity for strategic manipulation; in particular for the proposers, men or say students applying to schools. it is a dominant strategy to reveal one’s true preferences.

The importance of a stable matching algorithm can be seen in what happens when such algorithms are not used. In trying to allocate residents to hospitals, for example, what typically happens when a stable algorithm is not used is unraveling and chaos. Unraveling occurs when offers are made earlier and earlier in an attempt to get a jump on the competition. Prior to the currently used National Residency Matching Program, for example, hospitals were making offers to residents up to two years in advance! All kinds of chaos arose as hospitals would make exploding offers, accept now or the offer explodes! Such offers would inevitable lead to recriminations and backing out of the offers as better matches were sought.

What Roth has done is extend the Gale-Shapley algorithm to more complicated matches and to actually design such algorithms to solve real problems. In the 1970s, for example, the medical residency algorithm began to run into trouble because of a new development, the dual career couple. How to match couples, both doctors, to hospitals in the same city? By the 1990s assortative matching in the marriage market was beginning to derail matching in the doctor-hospital market! Roth was called in to solve the problem and moved from being a theorist to a market designer. Roth and Peranson designed the matching algorithm that is now used by Orthodontists, Psychologists, Pharmacists, Radiologists, Pediatric surgeons and many other medical specialties in the United States.

Most famously, Roth has worked on improving kidney allocation. I first wrote about this in 2004 (see also these posts):

Your spouse is dying of kidney disease. You want to give her one of your kidneys but tests show that it is incompatible with her immune system. Utter anguish and frustration. Is there anything that you can do? Today the answer is yes. Transplant centers are now helping to arrange kidney swaps. You give to the spouse of another donor who gives to your spouse. Pareto would be proud. Even a few three-way swaps have been conducted.

But why stop at three? What about an n-way swap? Let’s add in the possibility of an exchange that raises your spouse on the queue for a cadaveric kidney. And let us also recognize that even if your kidney is compatible with your spouse’s there may be a better match. Is there an allocation system that makes all donors and spouses better off (or at least no worse off) and that maximizes the number of beneficial swaps? In an important paper (Warning! Very technical. Requires NBER subscription.) Alvin Roth and co-authors describe just such a mechanism and show that it could save many lives. Who says efficiency is a pedestrian virtue?

Since that time we have seen many such swaps including this record of 60 people and 30 kidneys. Truly a noble match.

Minor editing Oct. 23.

Great choices. Al Roth for matching and the design of new types of markets. Lloyd Shapley for fundamental contributions to game theory and mathematical economics including the Gale-Shapley algorithm which is a cornerstone of the matching methods Al Roth pioneered. I am especially pleased about this because of Roth’s great work on improving kidney allocation. Here is Roth’s blog, Market Design and here he is giving a talk at Google. Here is what I wrote in 2010 about Roth

Roth has applied heavy-duty theory to the very practical problems of matching doctors to residency programs, children to schools, economists to departments and kidneys to patients in a way that is stable, incentive-compatible, and maximizes the gains from exchange.  In my view, Roth is the most influential economist working today. Influential among other economists?  Yes.  But what I really mean is influential in the world.

Previous posts on MR about Roth (also here). Roth’s papers.

More soon.

1. More about Mo Yan.

2. Are state-sanctioned legal highs coming to New Zealand?

3. Should there be trade in butterflies?

4. Should Europe allow and encourage larger cities?

5. Securitizing cancer research.

6. Ed Prescott on how and why taxes matter.

1. Daniel Mendelsohn on critics and criticism.

2. Good profile of Roland Fryer.

3. The economics of Gagosian.

4. Should we abolish pain?

5. Are women really more risk-averse than men?

1. The bra of the future?  (safe for work)

2. Findings about paper rejections, or why you should love your critics.

3. Good post on the Dunning-Krueger effect.

4. How penicillin reshaped sexuality.

5. Sabina Knight on Mo Yan (short podcast).

6. How Google lobbies for self-driving cars.

1. Mises on the sustainability of monetary expansion, and Brink Lindsey on the parent gap.

2. How Dirk Nowitzki was trained by his mentor, and can a shooter be too open?  Please note that links are not endorsements.

3. Problems of water policy in Haiti.

4. Barry Eichengreen on Korea.

5. Finally a new critique of Ayn Rand, and interview with Jennifer Roback Morse.