More genetic substructure

Via Genetic Future, two more principal components analyses of SNP data. Click the genetics label for related posts.

European, Nigerian and East Asian samples from HapMap and 100 African-American samples clustered based on data from ~600,000 genetic markers. The bend toward the East Asian cluster is probably due to Native American admixture.

Alkes L. Price, Nick Patterson, et al. (2008). Effects of cis and trans Genetic Ancestry on Gene Expression in African Americans, PLoS Genetics, 4 (12) DOI: 10.1371/journal.pgen.1000294.





Resolving Finns and Swedes. Jakkula et al. (2008) The Genome-wide Patterns of Variation Expose Significant Substructure in a Founder Population, The American Journal of Human Genetics, 83 (6), 787-794 DOI: 10.1016/j.ajhg.2008.11.005.

Great MMA photos

If you like these photos, you might consider buying this book. (Or, even if you hate these pictures, you can buy the book for me -- shipping address here :-)





Genki Sudo after knocking out Royler Gracie.





Mark Coleman embraces his daughters after a loss to Fedor Emelianenko.





Wanderlei Silva after knocking out Rampage Jackson.






Rampage Jackson after knocking out Chuck Lidell.





Enson Inoue armbars Randy Couture.





Poster for Pride 10 featuring Kazushi Sakuraba.

Teaching effectiveness

The two figures below (click for larger versions) are taken from the Brookings report by Gordon, Kane and Staiger: Identifying Effective Teachers Using Performance on the Job. The report has received a lot of attention recently thanks to Malcolm Gladwell's New Yorker article. Both are worth a look if you are interested in education. The top figure shows that certification has no impact on teaching effectiveness. The second shows that effectiveness measured in the years 1 and 2 is predictive of effectiveness in the subsequent year. In this case effectiveness is defined by the average change in percentile ranking of students in the teacher's class. Good teachers help their students to improve their mastery, hence percentile ranking, relative to the average student studying the same material.






It's obvious to me that there is gigantic variation in effectiveness among teachers. Gladwell emphasizes how difficult it is to evaluate teaching capability in initial hiring, and how the single most important impact on overall school effectiveness is due to individual teachers (he also makes the analogy to scouting college QBs for pro football -- it's very hard to predict NFL performance based on college performance). The Brookings paper has many policy suggestions, but the basic idea is that if we were disciplined and data-driven we could easily determine which teachers are good and which ones are not.

New Yorker: ...One of the most important tools in contemporary educational research is “value added” analysis. It uses standardized test scores to look at how much the academic performance of students in a given teacher’s classroom changes between the beginning and the end of the school year. Suppose that Mrs. Brown and Mr. Smith both teach a classroom of third graders who score at the fiftieth percentile on math and reading tests on the first day of school, in September. When the students are retested, in June, Mrs. Brown’s class scores at the seventieth percentile, while Mr. Smith’s students have fallen to the fortieth percentile. That change in the students’ rankings, value-added theory says, is a meaningful indicator of how much more effective Mrs. Brown is as a teacher than Mr. Smith.

It’s only a crude measure, of course. A teacher is not solely responsible for how much is learned in a classroom, and not everything of value that a teacher imparts to his or her students can be captured on a standardized test.

Nonetheless, if you follow Brown and Smith for three or four years, their effect on their students’ test scores starts to become predictable: with enough data, it is possible to identify who the very good teachers are and who the very poor teachers are. What’s more—and this is the finding that has galvanized the educational world—the difference between good teachers and poor teachers turns out to be vast.

Eric Hanushek, an economist at Stanford, estimates that the students of a very bad teacher will learn, on average, half a year’s worth of material in one school year. The students in the class of a very good teacher will learn a year and a half’s worth of material. That difference amounts to a year’s worth of learning in a single year. Teacher effects dwarf school effects: your child is actually better off in a “bad” school with an excellent teacher than in an excellent school with a bad teacher. Teacher effects are also much stronger than class-size effects. You’d have to cut the average class almost in half to get the same boost that you’d get if you switched from an average teacher to a teacher in the eighty-fifth percentile. And remember that a good teacher costs as much as an average one, whereas halving class size would require that you build twice as many classrooms and hire twice as many teachers.

Hanushek recently did a back-of-the-envelope calculation about what even a rudimentary focus on teacher quality could mean for the United States. If you rank the countries of the world in terms of the academic performance of their schoolchildren, the U.S. is just below average, half a standard deviation below a clump of relatively high-performing countries like Canada and Belgium. According to Hanushek, the U.S. could close that gap simply by replacing the bottom six per cent to ten per cent of public-school teachers with teachers of average quality. After years of worrying about issues like school funding levels, class size, and curriculum design, many reformers have come to the conclusion that nothing matters more than finding people with the potential to be great teachers. But there’s a hitch: no one knows what a person with the potential to be a great teacher looks like. The school system has a quarterback problem.

In my experience as a university professor I find that most colleagues think of themselves as above-average teachers, even when they are not. Essentially no "value-added" analysis is ever done, so people can have a 30 year teaching career without ever realizing that they aren't effective in the classroom. I've done many dozens of business presentations, to venture capitalists, technology partners, customers, analysts and even potential M&A acquirers, which has helped me improve my own teaching and communication skills. Despite the business setting such meetings are 90 percent teaching -- trying to convey key points to the audience in a limited time. I'm usually there with a team and my team isn't shy about telling me afterwards what worked and what didn't work, so I've had a lot of honest feedback that most professors never get.



The New Yorker cartoon and article capture some essential aspects of teaching and communication that are not widely understood. The teacher has to be simultaneously on top of the material itself and aware of what the class is doing / thinking / confused about. The big neglected factors in teaching are the ability to be a kind of air traffic controller (or symphony conductor) for the class, and the ability to empathize with (read the mind of) an individual student, to see what, exactly, is confusing them.

Keynes

Robert Skidelsky, Keynes' biographer, writes in the Times magazine (excerpted below). Keynes had lived through the greatest of all bubbles and crashes, and saw through the convenient but deeply flawed idea of efficient markets.

As someone with a mathematical bent I was not initially drawn to Keynes' brand of economics -- my interests were in areas of modern finance like option pricing theory, volatility, stochastic models. But like Keynes I have seen a bubble up close -- first in Silicon Valley, and now, from a greater distance, the current credit crisis. What seemed to be reasonable rough approximations: efficient markets, no arbitrage conditions, stochastic processes, etc., have been revealed as terribly naive and dangerous. And so over time my views have come to resemble those described below. (See my talk on the financial crisis, and this Venn diagram.)

Although he is best known as an economist, Keynes' Treatise on Probability, written relatively early in his career, is quite good, and also stresses the idea of probability as a form of logic which goes beyond binary truth values. (See related post on E.T. Jaynes and Bayesian thinking.)

Note to commenters: I am not endorsing all "Keynsian" policy measures. I am endorsing Keynes' opinions on efficient markets, risk and the importance of psychological and sociological factors in economics -- i.e., what is discussed in the excerpt below.

NYTimes: Among the most astonishing statements to be made by any policymaker in recent years was Alan Greenspan’s admission this autumn that the regime of deregulation he oversaw as chairman of the Federal Reserve was based on a “flaw”: he had overestimated the ability of a free market to self-correct and had missed the self-destructive power of deregulated mortgage lending. The “whole intellectual edifice,” he said, “collapsed in the summer of last year.”

[Greenspan quote here.]

What was this “intellectual edifice”? As so often with policymakers, you need to tease out their beliefs from their policies. Greenspan must have believed something like the “efficient-market hypothesis,” which holds that financial markets always price assets correctly.

...By contrast, Keynes created an economics whose starting point was that not all future events could be reduced to measurable risk. There was a residue of genuine uncertainty, and this made disaster an ever-present possibility, not a once-in-a-lifetime “shock.” Investment was more an act of faith than a scientific calculation of probabilities. And in this fact lay the possibility of huge systemic mistakes.

The basic question Keynes asked was: How do rational people behave under conditions of uncertainty? The answer he gave was profound and extends far beyond economics. People fall back on “conventions,” which give them the assurance that they are doing the right thing. The chief of these are the assumptions that the future will be like the past (witness all the financial models that assumed housing prices wouldn’t fall) and that current prices correctly sum up “future prospects.” Above all, we run with the crowd. A master of aphorism, Keynes wrote that a “sound banker” is one who, “when he is ruined, is ruined in a conventional and orthodox way.” (Today, you might add a further convention — the belief that mathematics can conjure certainty out of uncertainty.)

But any view of the future based on what Keynes called “so flimsy a foundation” is liable to “sudden and violent changes” when the news changes. Investors do not process new information efficiently because they don’t know which information is relevant. Conventional behavior easily turns into herd behavior. Financial markets are punctuated by alternating currents of euphoria and panic.

Keynes’s prescriptions were guided by his conception of money, which plays a disturbing role in his economics. Most economists have seen money simply as a means of payment, an improvement on barter. Keynes emphasized its role as a “store of value.” Why, he asked, should anyone outside a lunatic asylum wish to “hold” money? The answer he gave was that “holding” money was a way of postponing transactions. The “desire to hold money as a store of wealth is a barometer of the degree of our distrust of our own calculations and conventions concerning the future. . . . The possession of actual money lulls our disquietude; and the premium we require to make us part with money is a measure of the degree of our disquietude.” The same reliance on “conventional” thinking that leads investors to spend profligately at certain times leads them to be highly cautious at others. Even a relatively weak dollar may, at moments of high uncertainty, seem more “secure” than any other asset, as we are currently seeing.

It is this flight into cash that makes interest-rate policy such an uncertain agent of recovery. If the managers of banks and companies hold pessimistic views about the future, they will raise the price they charge for “giving up liquidity,” even though the central bank might be flooding the economy with cash. That is why Keynes did not think that cutting the central bank’s interest rate would necessarily — and certainly not quickly — lower the interest rates charged on different types of loans. This was his main argument for the use of government stimulus to fight a depression. There was only one sure way to get an increase in spending in the face of an extreme private-sector reluctance to spend, and that was for the government to spend the money itself. Spend on pyramids, spend on hospitals, but spend it must.

This, in a nutshell, was Keynes’s economics. His purpose, as he saw it, was not to destroy capitalism but to save it from itself. He thought that the work of rescue had to start with economic theory itself. Now that Greenspan’s intellectual edifice has collapsed, the moment has come to build a new structure on the foundations that Keynes laid.

Ecotopia

The Times recalls the 1970s cult novel Ecotopia, by Ernest Callenbach.

The Novel That Predicted Portland

SOMETIMES a book, or an idea, can be obscure and widely influential at the same time. That’s the case with “Ecotopia,” a 1970s cult novel, originally self-published by its author, Ernest Callenbach, that has seeped into the American groundwater without becoming well known.

The novel, now being rediscovered, speaks to our ecological present: in the flush of a financial crisis, the Pacific Northwest secedes from the United States, and its citizens establish a sustainable economy, a cross between Scandinavian socialism and Northern California back-to-the-landism, with the custom — years before the environmental writer Michael Pollan began his campaign — to eat local.

White bicycles sit in public places, to be borrowed at will. A creek runs down Market Street in San Francisco. Strange receptacles called “recycle bins” sit on trains, along with “hanging ferns and small plants.” A female president, more Hillary Clinton than Sarah Palin, rules this nation, from Northern California up through Oregon and Washington.

Note that Callenbach actually lives in Berkeley, where the climate is better :-(

On the other hand, Brad DeLong was impressed by our six kinds of recycling at U Oregon.



It's easy to forget that today's widely accepted environmentalism started as a crazy fringe social movement only 35 years ago. I can clearly remember during my childhood when it suddenly became not OK to just throw trash out the window of your moving car. (Remember the crying Indian chief TV spot? See below!) This development is captured nicely in an episode of the AMC TV series Mad Men (about 1960s Madison Ave. ad men), in which Don Draper and his lovely WASP upper class family have a nice picnic in the woods, and in the final shot leave behind a pile of rubbish and beer cans sitting in the grass. I think this means that there is hope for humanity -- we'll eventually figure out that preserving the environment is in our best interest as a species.





Incidentally, Mad Men is the only thing on TV I watch regularly, aside from ultimate fighting. At a holiday party earlier in the week the show came up in conversation and I found that randomly selected literature and film professors also love it :-) Sadly, I don't know anyone on the faculty who is excited about BJ Penn versus Georges St. Pierre in January.

Snow in Eugene

A rare snowfall -- it's already starting to melt away. These were all taken from inside :-)

Confidence matters

More on confidence via Barry Ritholtz:

Which raises the question: Why [no] runs on semis or software companies? The short answer is their business model does not depend upon a belief system — of solvency, liquidity, profitability or risk management.

It wasn’t a crisis of confidence that did the iBanks in, it was a crisis of competence.

That was the element CEOs like Dick Fuld, Hank Paulson, Stan O’Neal and Jimmy Cayne failed to consider: When you are a bank, your existence depends upon the confidence of your clients, investors and counter-parties. Anything you do that puts that at risk is extremely dangerous. If you want to run lots of leverage, push the envelope, well, then, you better hope nothing else goes wrong. At 35X, you do not leave any room for error.

It is inexcusable that the investment CEOs did not seem to realize this. It was unconsionable that the firms had been purposefully put into a risk taking position in extremis. That the CEOs blamed short sellers and rumors, but exonerated themselves, only serves to emphasize their own failures, their lack of comprehension of what they had dome to themselves. It was their own incompetent stewardship that purposefully and unknowingly placed these firms at such grave danger of destruction.

Macro modelers take note: no realistic results without accounting for ape psychology.

Here's a nice video feauring the confidence men (financial CEOs) and their recent payouts:




And this (both via Barry Ritholtz):



Related: Central limit theorem and securitization.

Jaynes and Bayes

E.T. Jaynes, although a physicist, was one of the great 20th century proponents of Bayesian thinking. See here for a wealth of information, including some autobiographical essays. I recommend this article on probability, maximum entropy and Bayesian thinking, and this, which includes his recollections of Dyson, Feynman, Schwinger and Oppenheimer.

Here are the first three chapters of his book Probability Theory: the Logic of Science. The historical material in the preface is fascinating.

Jaynes started as an Oppenheimer student, following his advisor from Berkeley to Princeton. But Oppenheimer's mystical adherence to the logically incomplete Copenhagen interpretation (Everett's "philosophic monstrosity") led Jaynes to switch advisors, becoming a student of Wigner.

Edwin T. Jaynes was one of the first people to realize that probability theory, as originated by Laplace, is a generalization of Aristotelian logic that reduces to deductive logic in the special case that our hypotheses are either true or false. This web site has been established to help promote this interpretation of probability theory by distributing articles, books and related material. As Ed Jaynes originated this interpretation of probability theory we have a large selection of his articles, as well as articles by a number of other people who use probability theory in this way.

See Carson Chow for a nice discussion of how Bayesian inference is more like human reasoning than formal logic.

The seeds of the modern era could arguably be traced to the Enlightenment and the invention of rationality. I say invention because although we may be universal computers and we are certainly capable of applying the rules of logic, it is not what we naturally do. What we actually use, as coined by E.T. Jaynes in his iconic book Probability Theory: The Logic of Science, is plausible reasoning. Jaynes is famous for being a major proponent of Bayesian inference during most of the second half of the last century. However, to call Jaynes’s book a book about Bayesian statistics is to wholly miss Jayne’s point, which is that probability theory is not about measures on sample spaces but a generalization of logical inference. In the Jaynes view, probabilities measure a degree of plausibility.

I think a perfect example of how unnatural the rules of formal logic are is to consider the simple implication A -> B which means - If A is true then B is true. By the rules of formal logic, if A is false then B can be true or false (i.e. a false premise can prove anything). Conversely, if B is true, then A can be true or false. The only valid conclusion you can deduce from is that if B is false then A is false. ...

However, people don’t always (seldom?) reason this way. Jaynes points out that the way we naturally reason also includes what he calls weak syllogisms: 1) If A is false then B is less plausible and 2) If B is true then A is more plausible. In fact, more likely we mostly use weak syllogisms and that interferes with formal logic. Jaynes showed that weak syllogisms as well as formal logic arise naturally from Bayesian inference.

[Carson gives a nice example here -- see the original.]

...I think this strongly implies that the brain is doing Bayesian inference. The problem is that depending on your priors you can deduce different things. This explains why two perfectly intelligent people can easily come to different conclusions. This also implies that reasoning logically is something that must be learned and practiced. I think it is important to know when you draw a conclusion, whether you are using deductive logic or if you are depending on some prior. Even if it is hard to distinguish between the two for yourself, at least you should recognize that it could be an issue.

While I think the brain is doing something like Bayesian inference (perhaps with some kinds of heuristic shortcuts), there are probably laboratory experiments showing that we make a lot of mistakes and often do not properly apply Bayes' theorem. A quick look through the old Kahneman and Tversky literature would probably confirm this :-)

Map of science

This citation map of science (click for larger version) is from eigenfactor.org. It shows the importance of basic sciences like physics and molecular biology. Applied fields still depend on advances in basic science.

Eigenfactor score is a PageRank-like algorithm, in which citations are links. See here for more.

Orange circles represent fields, with larger, darker circles indicating larger field size as measured by Eigenfactor score™. Blue arrows represent citation flow between fields. An arrow from field A to field B indicates citation traffic from A to B, with larger, darker arrows indicating higher citation volume.

The map was creating using our information flow method for mapping large networks. Using data from Thomson Scientific's 2004 Journal Citation Reports (JCR), we partitioned 6,128 journals connected by 6,434,916 citations into 88 modules. For visual simplicity, we show only the most important links, namely those that a random surfer traverses at least once in 5000 steps, and the modules that are connected by these links.

Steve Chu, Energy Secretary

Steve Chu, currently director of LBNL, is Obama's pick for Energy Secretary. Thank goodness! Finally a big brain will run the agency that funds our national labs and basic energy research.

Chu won the Nobel prize for his work on laser cooling of trapped atoms. This technique is now a fundamental tool in atomic physics. Chu did his PhD at Berkeley under brilliant experimentalist Eugene Commins (who was still around when I was a grad student). When Chu won the Nobel my mother received several phone calls from well wishers -- "I heard your son the Berkeley PhD won the Nobel Prize in physics!" :-/ (Hsu, Chu, what's the difference?) Sorry ma, don't get your hopes up!

Chu: "I told my boss .... `Guess what? I just trapped an atom.' He said, `Great. What are you going to do with it?' I said, `I don't know, but it's great!'"

DeLong on the $20 trillion dollar mystery

Brad can't understand how a $2 trillion mortgage loss can destroy $20 trillion in value in the world's capital markets. He does a good job of laying out the mystery here:

[First list 5 factors that affect market value of capital stock:]

(1) Savings and Investment
(2) News
(3) Default Discount
(4) Liquidity Discount
(5) Risk Discount

...In the past two years the wealth that is the global capital stock has fallen in value from $80 trillion to $60 trillion. Savings has not fallen through the floor. We have had little or no bad news about resource constraints, technological opportunities, or political arrangements. Thus (1) and (2) have not been operating. The action has all been in (3), (4), and (5).

As far as (3) is concerned, the recognition that a lot of people are not going to pay their mortgages and thus that a lot of holders of CDOs, MBSs, and counterparties, creditors, and shareholders of financial institutions with mortgage-related assets has increased the default discount by $2 trillion. And the fact that the financial crisis has brought on a recession has further increased the default discount — bond coupons that won’t be paid and stock dividends that won’t live up to firm promises — by a further $4 trillion. So we have a $6 trillion increase in the magnitude of (3) the default discount. The problem is that we have a $20 trillion decline in market values.

The problem is made bigger by the fact that for (4), the Federal Reserve, the European Central Bank, and the Bank of England have flooded the market with massive amounts of high-quality liquid claims on governments’ treasuries, and so have reduced the liquidity discount — not increased it — by an amount that I estimate to be roughly $3 trillion. Thus (3) and (4) together can only account for a $3 trillion decrease in market value. The rest of that decline in the value of global capital — all $17 trillion of it — thus comes by arithmetic from (5): a rise in the risk discount. There has been a massive crash in the risk tolerance of the globe’s investors.

Thus we have an impulse — a $2 trillion increase in the default discount from the problems in the mortgage market — but the thing deserving attention is the extraordinary financial accelerator that amplified $2 trillion in actual on-the-ground losses in terms of mortgage payments that will not be made into an extra $17 trillion of lost value because global investors now want to hold less risky portfolios than they wanted two years ago.

From my standpoint, the puzzle is multiplied by the fact that we economists have what we regard as pretty good theories about (4) and (5), and yet those theories do not seem to work at all....

...Things are even worse as far as the risk discount is concerned. Our models predict that in normal times, with the ability to diversify portfolios that exists today, the risk discount on assets like corporate equities should be around 1% per year. It is more like 5% per year in normal times — and more like 10% per year today. And our models for why the risk discount has taken such a huge upward leap in the past year and a half are little better than simple handwaving and just-so stories. Our current financial crisis remains largely a mystery: a $2 trillion impulse in lost value of securitized mortgages has set in motion a financial accelerator that we do not understand at any deep level but that has led to ten times the total losses in financial wealth of the impulse.

Short answer for physicists: phase transition in investor sentiment. People woke up one day and realized that the black box utility called "finance" (on which society relies so heavily) may not actually work properly. So they lost confidence, which is hard to regain. The importance of confidence is clear once we admit that most of the workings of financial markets are indeed a black box -- few people understand what is really going on. The same is true for individual companies -- we assume management knows what it is doing, until we realize otherwise. We might have a similar sudden shift in societal risk attitudes if, for instance, it were suddenly revealed (e.g., by the explosion of a submarine taking San Diego with it) that nuclear reactor and weapon designs were faulty and that random megaton explosions should be expected every decade or so.***

(Oh, and there's also the matter of CDS markets, a big amplifier of uncertainty and systemic risk which Brad doesn't mention at all.)

Some of this is explained in my talk. See also this paper for references to agent-based simulations which exhibit phase transitions in sentiment (bubbles and crashes). The intellectual toolkit of neoclassicals like Brad tends to focus on equilibrium ideas, which are unable to explain such phenomena. More discussion here on Arnold King's blog. I also recommend Bill Janeway.

Final technical point: it is very wrong to back out the implied total market capitalization from trades executed by a minority of distressed agents. A market cap extracted this way will inevitably exhibit wild fluctuations. Confidence in this quantity relies on particularly unwarranted efficient market assumptions: that markets (even in periods of dislocation) are the best forecasters of real economic value (discounted future cash flows).

*** You might try to accommodate events into a story of weakly efficient markets -- we received a shock or infusion of information (news) that caused a sudden revaluation. But the story doesn't work so when well the actual news is "financial markets are highly unreliable" or "nobody really understands this system as it is too complex" -- if that's the news, how efficient are / were markets? :-/

The fate of an honest intellectual

Good thing I am not as courageous as Norman Finkelstein. I do remember the Sokal hoax, though :-) See academic trends in pictures for more fun!

The basic lesson deserves emphasis: most people -- even intellectuals, professors and, yes, scientists -- are not careful thinkers. They are not good at overcoming the emotional and psychological barriers that prevent the falsification of cherished beliefs. Science is good training, but all too often not sufficient.

My Chomsky story. I accidentally came across a copy of At War with Asia in the Page House library (Caltech) when I was a student. I had no idea who Chomsky was, I knew nothing yet of linguistics, but the book was powerful and affecting. Years later as a Junior Fellow I emailed Chomsky (a former Junior Fellow) at MIT and invited him to one of our formal Monday dinners. He declined to come to dinner, as his relationship with some of the senior fellows was contentious, but wanted to come to lunch and meet some of the younger people. We had a wonderful time, and I discovered he has a pretty good sense of humor :-)

Note: I don't have any particular expertise on the matters related to Finkelstein's career or scholarship. But the story below rings true to me.

The Fate of an Honest Intellectual

Noam Chomsky

Excerpted from Understanding Power, The New Press, 2002, pp. 244-248

I'll tell you another, last case—and there are many others like this. Here's a story which is really tragic. How many of you know about Joan Peters, the book by Joan Peters? There was this best-seller a few years ago [in 1984], it went through about ten printings, by a woman named Joan Peters—or at least, signed by Joan Peters—called From Time Immemorial. It was a big scholarly-looking book with lots of footnotes, which purported to show that the Palestinians were all recent immigrants [i.e. to the Jewish-settled areas of the former Palestine, during the British mandate years of 1920 to 1948]. And it was very popular—it got literally hundreds of rave reviews, and no negative reviews: the Washington Post, the New York Times, everybody was just raving about it. Here was this book which proved that there were really no Palestinians! Of course, the implicit message was, if Israel kicks them all out there's no moral issue, because they're just recent immigrants who came in because the Jews had built up the country. And there was all kinds of demographic analysis in it, and a big professor of demography at the University of Chicago [Philip M. Hauser] authenticated it. That was the big intellectual hit for that year: Saul Bellow, Barbara Tuchman, everybody was talking about it as the greatest thing since chocolate cake.Well, one graduate student at Princeton, a guy named Norman Finkelstein, started reading through the book. He was interested in the history of Zionism, and as he read the book he was kind of surprised by some of the things it said. He's a very careful student, and he started checking the references—and it turned out that the whole thing was a hoax, it was completely faked: probably it had been put together by some intelligence agency or something like that. Well, Finkelstein wrote up a short paper of just preliminary findings, it was about twenty-five pages or so, and he sent it around to I think thirty people who were interested in the topic, scholars in the field and so on, saying: "Here's what I've found in this book, do you think it's worth pursuing?"

Well, he got back one answer, from me. I told him, yeah, I think it's an interesting topic, but I warned him, if you follow this, you're going to get in trouble—because you're going to expose the American intellectual community as a gang of frauds, and they are not going to like it, and they're going to destroy you. So I said: if you want to do it, go ahead, but be aware of what you're getting into. It's an important issue, it makes a big difference whether you eliminate the moral basis for driving out a population—it's preparing the basis for some real horrors—so a lot of people's lives could be at stake. But your life is at stake too, I told him, because if you pursue this, your career is going to be ruined.

Well, he didn't believe me. We became very close friends after this, I didn't know him before. He went ahead and wrote up an article, and he started submitting it to journals. Nothing: they didn't even bother responding. I finally managed to place a piece of it in In These Times, a tiny left-wing journal published in Illinois, where some of you may have seen it. Otherwise nothing, no response. Meanwhile his professors—this is Princeton University, supposed to be a serious place—stopped talking to him: they wouldn't make appointments with him, they wouldn't read his papers, he basically had to quit the program. ...

He's now living in a little apartment somewhere in New York City, and he's a part-time social worker working with teenage drop-outs. Very promising scholar—if he'd done what he was told, he would have gone on and right now he'd be a professor somewhere at some big university. ...

But let me just go on with the Joan Peters story. Finkelstein's very persistent: he took a summer off and sat in the New York Public Library, where he went through every single reference in the book—and he found a record of fraud that you cannot believe. Well, the New York intellectual community is a pretty small place, and pretty soon everybody knew about this, everybody knew the book was a fraud and it was going to be exposed sooner or later. The one journal that was smart enough to react intelligently was the New York Review of Books—they knew that the thing was a sham, but the editor didn't want to offend his friends, so he just didn't run a review at all. That was the one journal that didn't run a review.

...We approached the publishers and asked them if they were going to respond to any of this, and they said no—and they were right. Why should they respond? They had the whole system buttoned up, there was never going to be a critical word about this in the United States. But then they made a technical error: they allowed the book to appear in England, where you can't control the intellectual community quite as easily.

Well, as soon as I heard that the book was going to come out in England, I immediately sent copies of Finkelstein's work to a number of British scholars and journalists who are interested in the Middle East—and they were ready. As soon as the book appeared, it was just demolished, it was blown out of the water. Every major journal, the Times Literary Supplement, the London Review, the Observer, everybody had a review saying, this doesn't even reach the level of nonsense, of idiocy. A lot of the criticism used Finkelstein's work without any acknowledgment, I should say—but about the kindest word anybody said about the book was "ludicrous," or "preposterous." ...

Still, in the universities or in any other institution, you can often find some dissidents hanging around in the woodwork—and they can survive in one fashion or another, particularly if they get community support. But if they become too disruptive or too obstreperous—or you know, too effective—they're likely to be kicked out. The standard thing, though, is that they won't make it within the institutions in the first place, particularly if they were that way when they were young—they'll simply be weeded out somewhere along the line. So in most cases, the people who make it through the institutions and are able to remain in them have already internalized the right kinds of beliefs: it's not a problem for them to be obedient, they already are obedient, that's how they got there. And that's pretty much how the ideological control system perpetuates itself in the schools—that's the basic story of how it operates, I think.

Help! -- climate change

Some of the readers of this blog know much more about climate change than I do. Could someone please comment on this web page of Eric Baum's, in which he claims the evidence for human causation is weak and that state of the art climate models are shoddy? (Excerpts below.) Baum is a brilliant guy -- former theoretical physicist and AI researcher. I've recommended his book on AI here before.

Greenhouse Gas global warming (as opposed to other sources) should be measured in the tropical troposphere, because the models say that is the signature of greenhouse gas warming: the tropical troposphere should warm at roughly twice the surface rate. To verify this, see for example Figure 9.1, p675, Vol 1 IPCC Report. http://www.ipcc.ch/pdf/assessment-report/ar4/wg1/ar4-wg1-chapter9.pdf (The whole report can be found at http://www.ipcc.ch/ipccreports/ar4-wg1.htm .)
This was always an embarrassment for global warmists, because the troposphere has never warmed much, but in the last few years its cooled. The tropical troposphere has now not warmed at all. See http://www.climateaudit.org/?p=3048 for the graph of temperature according to three satellite series since 1978.

The Radiosonde (weather balloon) data series is an independent measurement of the tropical troposphere temperature. It goes back to 1958 and is presumably extremely reliable, because all they are doing is sending thermometers up in balloons. You can see the time series at: http://www.climateaudit.org/wp-content/uploads/2008/06/hadat42.gif The graph is flat, and the most recent data point is the coldest.

...This shows that the IPCC's GCM's (Global Circulation Models) are wrong. Not that it can be too surprising that the GCM's are worthless since p 596 of the IPCC 4th report cautiously admitted they didn't know whether their GCM's had more data points or free parameters! Yet the GCM's are absolutely central to any argument for expecting warming by more than a few tenths of a degree by 2100, and to the amazingly porous argument the IPCC report gives to demonstrate man caused the alleged observed warming.

...The IPCC 4th report says "attribution of anthropogenic climate change is understood to mean demonstration that a detected change... is not consistent with alternative, physically plausible explanations."[p668] But the report contains several alternative possibilities that are said to be "not understood" or whose magnitude is said to be "largely unknown". For example, two are mentioned just in the last paragraph of 1.4.3. (p108): unknown large feedbacks from changes in solar irradiance, and the effects of galactic cosmic rays. Actually, as I point out in the above few paragraphs, cosmic rays seem to explain climate fluctuations extremely well. The IPCC devotes considerable space to the strawman that solar activity could directly affect the earth's temperature, but ignores the actual indirect means by which solar variation seems to affect temperature. Global Warmists routinely attack the strawman of direct solar effect any time the subject is raised.

Also, Mars, Jupiter, Triton, Neptune, and Pluto have recently been observed warming, suggesting some cause external to the earth, but none of them are mentioned anywhere in the 987 pages of the 4th Report. Another physically plausible explanation for recent warming (if indeed warming has actually occurred) as remarked by Lindzen would be thermal transfer from the deep oceans. The oceans and atmosphere are turbulent fluids prone to exchange heat in unpredictable ways over a wide range of time scales simply because chaotic systems do that kind of thing, which the computer models of the IPCC are completely inadequate to simulate.

Its also worth noting that intuitive physics (and pencil and paper calculation) says that greenhouse gas warming scales logarithmically. The theoretical reason for the effect is that CO2 molecules (for example) absorb and reflect certain wavelengths. But they only do it in certain wavelengths. Once you've got some molecules of CO2 in the air, the effect of each next molecule is less than the one before, because those wavelengths are already getting scattered, and mostly heat is already only getting out in other wavelengths. So even if you believed everything else, one's expectation would be that we've already seen the substantial majority of all the warming we will ever see, if we quintuple the CO2 from here. To believe otherwise, you have to rely in detail on the GCM's prediction of positive feedbacks, that they are not competent to calculate, to predict warming in the future that is several times greater than anything we've seen before.

Resolution of population genetic structure

How much can we resolve the substructure of a population with a given amount of data? The paper below gives a quantitative answer. With current technology, we should have no problem resolving even small national populations (see italicized text in quote below), with nearest neighbor FST as small as .0001 (i.e., 99.99 percent of variation is within-group and only .01 percent between groups)! According to this Table of European, Nigerian and East Asian FSTs, the FST between France and Spain is .0008, whereas between Nigeria and Japan it is about .19 .

Within the European + HapMap sample analyzed here, over 100 statistically significant PCA vectors were identified. That is, there is a >100 dimensional space within which structure can be teased out. (However, the largest single vector accounts for only a percent of total variation, and the integral over all 100 vectors is probably only a few percent.) Norwegians and Swedes could be resolved with 90 percent accuracy. Note the Patterson et al. paper was written before this recent analysis, which confirms their theoretical predictions of sensitivity. (Figure below.)



The first author, Nick Patterson (profiled here), is a mathematician turned cryptographer turned quant (Renaissance) turned bioinformaticist.

Population Structure and Eigenanalysis

Nick Patterson et al. (Broad Institute of Harvard and MIT)

Abstract
Current methods for inferring population structure from genetic data do not provide formal significance tests for population differentiation. We discuss an approach to studying population structure (principal components analysis) that was first applied to genetic data by Cavalli-Sforza and colleagues. We place the method on a solid statistical footing, using results from modern statistics to develop formal significance tests. We also uncover a general “phase change” phenomenon about the ability to detect structure in genetic data, which emerges from the statistical theory we use, and has an important implication for the ability to discover structure in genetic data: for a fixed but large dataset size, divergence between two populations (as measured, for example, by a statistic like FST) below a threshold is essentially undetectable, but a little above threshold, detection will be easy. This means that we can predict the dataset size needed to detect structure.



...Another implication is that these methods are sensitive. For example, given a 100,000 marker array and a sample size of 1,000, then the BBP threshold for two equal subpopulations, each of size 500, is FST = .0001. An FST value of .001 will thus be trivial to detect. To put this into context, we note that a typical value of FST between human populations in Northern and Southern Europe is about .006 [15]. Thus, we predict: most large genetic datasets with human data will show some detectable population structure.

Be kind to your creditors

The Atlantic has a long interview with Gao Xiqing, president of the China Investment Corporation, which manages about $200 billion of the country’s foreign assets. CIC makes most of the high-visibility investments, like buying stakes in Blackstone and Morgan Stanley. Gao was a professor in China, then earned a law degree at Duke and practiced here before returning to China.

...His office, in one of the more tasteful new glass-walled high-rises in Beijing, itself seems less Chinese than internationally “fusion”-minded in its aesthetic and furnishings. Bonsai trees in large pots, elegant Japanese-looking arrangements of individual smooth stones on display shelves, Chinese and Western financial textbooks behind the desk, with a photo of Martin Luther King Jr. perched among the books. Two very large, very thin desktop monitors read out financial data from around the world. As we spoke, Western classical music played softly from a good sound system.

Gao dressed and acted like a Silicon Valley moneyman rather than one from Wall Street—open-necked tattersall shirt, muted plaid jacket, dark slacks, scuffed walking shoes. Rimless glasses. His father was a Red Army officer who was on the Long March with Mao. As a teenager during the Cultural Revolution, Gao worked on a railroad-building gang and in an ammunition factory. He is 55, fit-looking, with crew-cut hair and a jokey demeanor rather than an air of sternness. ...

About the financial crisis of 2008: We are not quite at the bottom yet. Because we don’t really know what’s going to happen next. Everyone is saying, “Oh, look, the dollar is getting stronger!” [As it was when we spoke.] I say, that’s really temporary. It’s simply because a lot of people need to cash in, they need U.S. dollars in order to pay back their creditors. But after a short while, the dollar may be going down again. I’d like to bet on that!

The overall financial situation in the U.S. is changing, and that’s what we don’t know about. It’s going to be changed fundamentally in many ways.

Think about the way we’ve been living the past 30 years. Thirty years ago, the leverage of the investment banks was like 4-to-1, 5-to-1. Today, it’s 30-to-1. This is not just a change of numbers. This is a change of fundamental thinking.

People, especially Americans, started believing that they can live on other people’s money. And more and more so. First other people’s money in your own country. And then the savings rate comes down, and you start living on other people’s money from outside. At first it was the Japanese. Now the Chinese and the Middle Easterners.

We—the Chinese, the Middle Easterners, the Japanese—we can see this too. Okay, we’d love to support you guys—if it’s sustainable. But if it’s not, why should we be doing this? After we are gone, you cannot just go to the moon to get more money. So, forget it. Let’s change the way of living. [By which he meant: less debt, lower rewards for financial wizardry, more attention to the “real economy,” etc.]

About Wall Street jobs, wealth, and the cultural distortion of America: I have to say it: you have to do something about pay in the financial system. People in this field have way too much money. And this is not right.

...Individually, everyone needs to be compensated. But collectively, this directs the resources of the country. It distorts the talents of the country. The best and brightest minds go to lawyering, go to M.B.A.s. And that affects our country, too! Many of the brightest youngsters come to me and say, “Okay, I want to go to the U.S. and get into business school, or law school.” I say, “Why? Why not science and engineering?” They say, “Look at some of my primary-school classmates. Their IQ is half of mine, but they’re in finance and now they’re making all this money.” So you have all these clever people going into financial engineering, where they come up with all these complicated products to sell to people.

About the $700 billion U.S. financial-rescue plan enacted in October: Finally, after months and months of struggling with your own ideology, with your own pride, your self-right-eousness … finally [the U.S. applied] one of the great gifts of Americans, which is that you’re pragmatic. Now our people are joking that we look at the U.S. and see “socialism with American characteristics.” [The Chinese term for its mainly capitalist market-opening of the last 30 years is “socialism with Chinese characteristics.”]


On what might make the Chinese government start taking its dollars out of America: (I began the question by saying that China would hurt itself by pulling out dollar assets—at which he interjected, “in the short term”—and then asked about the long-term view).

Today when we look at all the markets, the U.S. still is probably the most viable, the most predictable. I was trained as a lawyer, and predictability is always very important for me.

We have a PR department, which collects all the comments about us, from Chinese newspapers and the Web. Every night, I try to pick a time when I’m in a relatively good mood to read it, because most of the comments are very critical of us. Recently we increased our holdings in Blackstone a little bit. Now we’re increasing a little bit our holdings in Morgan Stanley, so as not to be diluted by the Japanese. People here hate it. They come out and say, “Why the hell are you trying to save those people? You are the representative of the poor people eating porridge, and you’re saving people eating shark fins!” It’s always that sort of thing.


...I have great admiration of American people. Creative, hard-working, trusting, and freedom-loving. But you have to have someone to tell you the truth. And then, start realizing it. And if you do it, just like what you did in the Second World War, then you’ll be great again!

If that happens, then of course—American power would still be there for at least as long as I am living. But many people are betting on the other side.

Frequentists vs Bayesians

Noted Berkeley statistician David Freedman recently passed away. I recommend the essay below if you are interested in the argument between frequentists (objectivists) and Bayesians (subjectivists). I never knew Freedman, but based on his writings I think I would have liked him very much -- he was clearly an independent thinker :-)

In everyday life I tend to be sympathetic to the Bayesian point of view, but as a physicist I am willing to entertain the possibility of true quantum randomness.

I wish I understood better some of the foundational questions mentioned below. In the limit of infinite data will two Bayesians always agree, regardless of priors? Are exceptions contrived?

Some issues in the foundation of statistics

Abstract: After sketching the conflict between objectivists and subjectivists on the foundations of statistics, this paper discusses an issue facing statisticians of both schools, namely, model validation. Statistical models originate in the study of games of chance, and have been successfully applied in the physical and life sciences. However, there are basic problems in applying the models to social phenomena; some of the difficulties will be pointed out. Hooke’s law will be contrasted with regression models for salary discrimination, the latter being a fairly typical application in the social sciences.


...The subjectivist position seems to be internally consistent, and fairly immune to logical attack from the outside. Perhaps as a result, scholars of that school have been quite energetic in pointing out the flaws in the objectivist position. From an applied perspective, however, the subjectivist position is not free of difficulties. What are subjective degrees of belief, where do they come from, and why can they be quantified? No convincing answers have been produced. At a more practical level, a Bayesian’s opinion may be of great interest to himself, and he is surely free to develop it in any way that pleases him; but why should the results carry any weight for others? To answer the last question, Bayesians often cite theorems showing "inter-subjective agreement:" under certain circumstances, as more and more data become available, two Bayesians will come to agree: the data swamp the prior. Of course, other theorems show that the prior swamps the data, even when the size of the data set grows without bounds-- particularly in complex, high-dimensional situations. (For a review, see Diaconis and Freedman, 1986.) Theorems do not settle the issue, especially for those who are not Bayesians to start with.

My own experience suggests that neither decision-makers nor their statisticians do in fact have prior probabilities. A large part of Bayesian statistics is about what you would do if you had a prior.7 For the rest, statisticians make up priors that are mathematically convenient or attractive. Once used, priors become familiar; therefore, they come to be accepted as "natural" and are liable to be used again; such priors may eventually generate their own technical literature. ...

It is often urged that to be rational is to be Bayesian. Indeed, there are elaborate axiom systems about preference orderings, acts, consequences, and states of nature, whose conclusion is-- that you are a Bayesian. The empirical evidence shows, fairly clearly, that those axioms do not describe human behavior at all well. The theory is not descriptive; people do not have stable, coherent prior probabilities.

Now the argument shifts to the "normative:" if you were rational, you would obey the axioms, and be a Bayesian. This, however, assumes what must be proved. Why would a rational person obey those axioms? The axioms represent decision problems in schematic and highly stylized ways. Therefore, as I see it, the theory addresses only limited aspects of rationality. Some Bayesians have tried to win this argument on the cheap: to be rational is, by definition, to obey their axioms. ...

How do we learn from experience? What makes us think that the future will be like the past? With contemporary modeling techniques, such questions are easily answered-- in form if not in substance.

·The objectivist invents a regression model for the data, and assumes the error terms to be independent and identically distributed; "iid" is the conventional abbreviation. It is this assumption of iid-ness that enables us to predict data we have not seen from a training sample-- without doing the hard work of validating the model.

·The classical subjectivist invents a regression model for the data, assumes iid errors, and then makes up a prior for unknown parameters.

·The radical subjectivist adopts an exchangeable or partially exchangeable prior, and calls you irrational or incoherent (or both) for not following suit.

In our days, serious arguments have been made from data. Beautiful, delicate theorems have been proved; although the connection with data analysis often remains to be established. And an enormous amount of fiction has been produced, masquerading as rigorous science. [!!!]

Human genetic variation, Fst and Lewontin's fallacy in pictures

In an earlier post European genetic substructure, I displayed the following graphic, illustrating the genetic clustering of human populations.




Figure: The three clusters shown above are European (top, green + red), Nigerian (light blue) and E. Asian (purple + blue).

The figure seems to contradict an often stated observation about human genetic diversity, which has become known among experts as Lewontin's fallacy: genetic variation between two random individuals in a given population accounts for 80% or more of the total variation within the entire human population. Therefore, according to the fallacy, any classification of humans into groups ("races") based on genetic information is impossible. ("More variation within groups than between groups.")

To understand this statement better, consider the F statistic of population genetics, introduced by Sewall Wright:

Fst = 1 - Dw / Db

Db and Dw represent the average number of pairwise differences between two individuals sampled from different populations (Db = "difference between") or the same population (Dw = "difference within"). Even in the most widely separated human populations Fst < .2 so Dw / Db > .8 (roughly). This may not sound like very much genetic diversity, but it is more than in many other animal species. See here for recent high statistics Fst values by nationality.

Dw / Db > .8 means that the average genetic distance measured in number of base pair differences between two members of a group (e.g., two randomly selected Europeans) is at least 80 percent of the average distance between distant groups (e.g., Europeans and Asians or Africans). In other words, if two individuals from very distant groups (e.g., a Japanese and a Nigerian) have on average N base pair differences, then two from the same group (e.g., two Nigerians or two Japanese) will on average have roughly .8 N base pair differences.

How can the Fst result ("more variation within groups than between groups") be consistent with the clusters shown in the figure? I've had to explain this on numerous occasions, always with great difficulty because the explanation requires a little mathematics. In order to make the point more accessible, I've created the figures below, which show two population clusters, each represented by an ellipsoid (blob). The different figures depict the same pair of objects, just viewed from different angles.

The blobs are constructed and arranged so that the average distance between two points (individuals) within the same cluster is almost as big as the average distance between two points (individuals) in different clusters. This is easy to achieve if the ellipsoids are big and flat (like pancakes) and placed close to each other along the flat directions. The figure is meant to show how one can have small Fst, as in humans, yet easily resolved clusters. The direction in which the gap between the clusters appears is one of the principal components in the space of human genetic variation, as recently found by bioinformaticists. The figure at the top of this post plots individuals as points in the space generated by the two largest principal components extracted from the combination of data from HapMap and from large statistics sampling of Europeans. Exhibited this way, isolated clusters ("races") are readily apparent.

The real space of genetic variation has many more than 3 dimensions, so it can't be easily visualized. But some aspects of the figures below still apply: there will be particular directions of variation over which different populations are more or less identical (orthogonal to the principal component; i.e. along the flat directions of each pancake), and there will be directions in which different populations differ radically and have little or no overlap. Note, however, that we are specifically referring to genetic variation, which may or may not translate into phenotypic variation.







Related posts: "no scientific basis for race" , metric on the space of genomes.

The existence of this clustering has been known for 40 years.

The best and the brightest: McGeorge Bundy

Bundy was the first National Security Advisor under Kennedy and Johnson (at the time the position was special assistant to the president for national security affairs), and perhaps the most infamous of Harvard Junior Fellows. Bundy, with McNamara, played a key role in shaping America's war in Vietnam.

Below, Richard Holbrooke reviews Gordon Goldstein's new book on McGeorge Bundy in the Times. (Interview with Goldstein.)

How long will it be before the architects of our war in Iraq can admit their mistake? I suspect they are surpassed by Bundy not just in intelligence but, ultimately, integrity.

NYTimes: ...Bundy was the quintessential Eastern Establishment Republican, a member of a family that traced its Boston roots back to 1639. His ties to Groton (where he graduated first in his class), Yale and then Harvard were deep. At the age of 27, he wrote, to national acclaim, the ‘memoirs” of former Secretary of War Henry L. Stimson. In 1953, Bundy became dean of the faculty at Harvard — an astonishing responsibility for someone still only 34. Even David Halberstam, who would play so important a role in the public demolition of Bundy’s reputation in his classic, “The Best and the Brightest,” admitted that “Bundy was a magnificent dean” who played with the faculty “like a cat with mice.”

As he chose his team, Kennedy was untroubled by Bundy’s Republican roots —the style, the cool and analytical mind, and the Harvard credentials were more important. “I don’t care if the man is a Democrat or an Igorot,” he told the head of his transition team, Clark Clifford. “I just want the best fellow I can get for the particular job.” And so McGeorge Bundy entered into history — the man with the glittering résumé for whom nothing seemed impossible.

Everyone knows how this story ends: Kennedy assassinated, Lyndon B. Johnson trapped in a war he chose to escalate, Nixon and Kissinger negotiating a peace agreement and, finally, the disastrous end on April 30, 1975, as American helicopters lifted the last Americans off the roof of the embassy.

...Bundy spoke only occasionally about Vietnam after he left government, but when he did, he supported the war. Yet it haunted him. He knew his own performance in the White House had fallen far short of his own exacting standards, and Halberstam’s devastating portrait of him disturbed him far more deeply than most people realized. After remaining largely silent, — except for an occasional defense of the two presidents he had served — for 30 years, Bundy finally began, in 1995, to write about Vietnam. He chose as his collaborator Gordon Goldstein, a young scholar of international affairs. Together they began mining the archives, and Goldstein conducted a series of probing interviews. Bundy began writing tortured notes to himself, often in the margins of his old memos — a sort of private dialogue with the man he had been 30 years earlier — something out of a Pirandello play. Bundy would scribble notes: “the doves were right”; “a war we should not have fought”; “I had a part in a great failure. I made mistakes of perception, recommendation and execution.” “What are my worst mistakes?” For those of us who had known the self-confident, arrogant Brahmin from Harvard, these astonishing, even touching, efforts to understand his own mistakes are far more persuasive than the shallow analysis McNamara offers in his own memoir, “In Retrospect.”

...As it happens, I was part of a small group that dined with Bundy the night before Pleiku at the home of Deputy Ambassador William J. Porter, for whom I then worked. Bundy quizzed us in his quick, detached style for several hours, not once betraying emotion. I do not remember the details of that evening — how I wish I had kept a diary! — but by then I no longer regarded Bundy as a role model for public service. There was no question he was brilliant, but his detachment from the realities of Vietnam disturbed me. In Ambassador Porter’s dining room that night were people far less intelligent than Bundy, but they lived in Vietnam, and they knew things he did not. Yet if they could not present their views in quick and clever ways, Bundy either cut them off or ignored them. A decade later, after I had left the government, I wrote a short essay for Harper’s Magazine titled “The Smartest Man in the Room Is Not Always Right.” I had Bundy — and that evening — in mind.

See also A Memory of McGeorge Bundy:

...In February, he and I overlapped briefly in Saigon, and we had one quiet talk. On my return to Washington, I learned that Mac had told the NSC staff he was optimistic about the war, but, much to my astonishment, that they they should wait to hear my very different views.

In 1968, after I wrote a critique of Vietnam policy in The Atlantic, Mac chastised me for betraying LBJ's trust. We didn't make up for eight years. By then I was running Harvard's Nieman Fellowships for journalists, and Mac came to talk to the fellows.

He was crisply articulate, but there was one persistent young man, who resembled Trotsky, needling Mac with questions about the war. Mac finally cut him off saying, "Your problem, young man, is not your intellect but your ideology."

Later, as we were clinking highballs, the Trotsky look-alike cornered Mac: " What about Vietnam?"

Bundy: "I don't understand your question."

Trotsky: "Mac, what about (italics)you(end italics) and Vietnam?"

Bundy: "I still don't understand."

Trotsky: "But Mac, you screwed it up, didn't you?"

Glacial silence. Then Bundy suddenly smiled and replied: "Yes, I did. But I'm not going to waste the rest of my life feeling guilty about it."

When he died, McGeorge Bundy was working on a book about the war whose main message was that Vietnam was a terrible mistake.

It's a loss that he did not live to write in full what he had learned from the Vietnam calamity.

I recommend The Color of Truth, Kai Bird's biography of the Bundy brothers. Bird wrote the recent biography of Oppenheimer, American Prometheus.

Atlas Shrugged, updated

Read the whole thing at McSweeney's! The original is discussed here. Via Naked Capitalism.

Anyone willing to own up to their Objectivist philosophical leanings? :-)

"I heard the thugs in Washington were trying to take your Rearden metal at the point of a gun," she said. "Don't let them, Hank. With your advanced alloy and my high-tech railroad, we'll revitalize our country's failing infrastructure and make big, virtuous profits."

"Oh, no, I got out of that suckers' game. I now run my own hedge-fund firm, Rearden Capital Management."

"What?"

He stood and adjusted his suit jacket so that his body didn't betray his shameful weakness. He walked toward her and sat informally on the edge of her desk. "Why make a product when you can make dollars? Right this second, I'm earning millions in interest off money I don't even have."

He gestured to his floor-to-ceiling windows, a symbol of his productive ability and goodness.

"There's a whole world out there of byzantine financial products just waiting to be invented, Dagny. Let the leeches run my factories into the ground! I hope they do! I've taken out more insurance on a single Rearden Steel bond than the entire company is even worth! When my old company finally tanks, I'll make a cool $877 million."

...Dagny and Hank searched through the ruins of the 21st Century Investment Bank. As they stepped through the crumbling cubicles, a trampled legal pad with a complex column of computations captured Dagny's attention. She fell to her hands and knees and raced through the pages and pages of complex math written in a steady hand. Her fingers bled from the paper cuts, and she did not care.

"What is it, Dagny?"

"Read this."

"Good God!"

"Yes, it's an experimental formula for a financial strategy that could convert static securities into kinetic profits that would increase at an almost exponential rate."

Hank studied the numbers. "The amount of debt you would need to make this work would be at least 30-to-1, but a daring, rational man who lives by his mind would be willing to take that risk!"

"Yes, and it's so complex the government could never regulate it."

Back in the day

February 15, 1999.

East Asian genetic substructure

Below are some results on East and Southeast Asian genetic substructure. As you can see, Koreans are (sort of) midway between Chinese and Japanese. It will almost certainly be possible to differentiate between different regional origins based on DNA, once larger statistics studies become available. (See European results.)

Figures: Each point is an individual, and the axes are two principal components in the space of genetic variation. Colors correspond to individuals of different Asian ancestry.






Thanks to Chao Tian of UC Davis for sending me an early draft of the paper.

Analysis of East Asia Genetic Substructure: Population Differentiation and PCA Clusters Correlate with Geographic Distribution.

C. Tian1, R. Kosoy1, A. Lee2, P. Gregersen2, J. Belmont2, M. Seldin1

1) Rowe Program Human Genetics, Univ California Sch Medicine, Davis, CA; 2) North Shore-LIJ Res Inst, Manhasset, NY, Baylor Col Med., Houston TX.

Accounting for genetic substructure within European populations has been important in reducing type 1 errors in genetic studies of complex disease. As efforts to understand complex genetic disease are expanded to other continental populations an understanding of genetic substructure within these continents will be useful in design and execution of association tests. In this study, population differentiation(Fst) and Principal Components Analyses(PCA) are examined using >200K genotypes from multiple populations of East Asian ancestry(total 298 subjects). The population groups included those from the Human Genome Diversity Panel[Cambodian(CAMB), Yi, Daur, Mongolian(MGL), Lahu, Dai, Hezhen, Miaozu, Naxi, Oroqen, She, Tu, Tujia, Naxi, and Xibo], HapMap(CHB and JPT), and East Asian or East Asian American subjects of Vietnamese(VIET), Korean(KOR), Filipino(FIL) and Chinese ancestry. Paired Fst(Wei and Cockerham) showed close relationships between CHB and several large East Asian population groups(CHB/KOR, 0.0019; CHB/JPT, 00651; CHB/VIET, 0.0065) with larger separation with FIL(CHB/FIL, 0.014). Low levels of differentiation were also observed between DAI and VIET(0.0045) and between VIET and CAMB(0.0062). Similarly, small Fst's were observed among different presumed Han Chinese populations originating in different regions of mainland of China and Taiwan(Fst < 0.0025 with CHB). For PCA, the first two PC's showed a pattern of relationships that closely followed the geographic distribution of the different East Asian populations. For example, the four "corner" groups were JPT, FIL, CAMB and MGL with the CHB forming the center group, and KOR was between CHB and JPT. Other small ethnic groups were also in rough geographic correlation with their putative origins. These studies have also enabled the selection of a subset of East Asian substructure ancestry informative markers(EASTASAIMS) that may be useful for future genetic association studies in reducing type 1 errors and in identifying homogeneous groups.

Related posts: "no scientific basis for race" , metric on the space of genomes

The value of trust

In no-arb efficient market fairy tale land, investors are assumed to be able to value a company by simply looking at its balance sheet, researching its market and business model and projecting into the future. Sound difficult? Why, yes, it's almost impossible to do, and even after a lengthy research project executed by a team of brilliant analysts there is a huge remaining uncertainty.

So what happens in the real world? Well, we apes with limited cognitive power and limited information rely on simple heuristics -- rules of thumb -- to guess what will happen in the future. That is, we say "Robert Rubin seems like a smart, careful guy, and top management at Citi must know what they are doing, and surely the market knows what it's doing, so, yeah, $40 a share seems ok with me..."

Of course, after a while we might notice some data suggesting that the leadership at Citi has been dishonest ("we are adequately capitalized" -- CEO Vikram Pandit) and ignorant of their own business operations ("what's a SIV?" -- Chairman Robert Rubin, November, 2007), and suddenly decide that NO, they DON'T KNOW WHAT THEY ARE DOING.

Yikes!: as reported on this blog, Rubin comments from November 2007.

[SIV = Structured Investment Vehicle = (roughly, see link) CDO]

"I think the problem with this SIV issue is that it's been substantially misunderstood in the press," said Rubin, who has a considerable personal stake in the fate of Citigroup. The banking firm paid him $17.3 million last year.

"The banks appear to be in fine shape," he said. "That's not a problem."

The SIV issue isn't critical for the economy, he insisted.

"It's massively less important that it's been presented," Rubin said. "It's been presented as a sort of centerpiece of what's going on. I just don't think that's right."

The cost of the evaporation of trust? $200 billion dollars in lost market capitalization in the last year. The real reason Citi melted down is that people no longer trust their senior management to meet future obligations. This senior management was left in place in Treasury's latest sweetheart deal.

Tell me an efficient market story that explains Citi's recent history and I'll sell you a slightly devalued "Nobel Prize" in financial economics along with the Brooklyn bridge. (Click below for larger image.)



Thanks to Mark Thoma for links to the articles quoted below.

Bronte Capital:

...due to the losses and the lack of risk control people stopped believing in Citigroup – and hence Citigroup dies without a bailout. It was however pretty easy to stop believing in Citigroup because nobody (at least nobody normal) can understand their accounts. I can not understand them and I am a pretty sophisticated bank analyst. I know people I think are better than me – and they can’t understand Citigroup either. So Citigroup was always a “trust us” thing and now we do not trust.

The cause of the crisis

This is a wholesale funding crisis and the cause of the crisis is plain. It is lies told by financial institutions. Financial institutions sold AAA rated paper which they almost certainly – deep in their bowels – knew was crap. They sold it to people who provide wholesale funding.

Now they need to roll their own debt. The people who would normally wholesale fund them are the same people who have had a large dose of defaulting AAAs. They no longer believe. It is “fool me once, shame on me, fool me twice, shame on you”. As I have put it the lies that destroyed Bear Stearns were not told by short sellers. They were told by Bear Stearns.

Now the problem is that no matter how many times Pandit says that Citigroup is well capitalised nobody will believe him. In answer to the Brad DeLong question – the company told lies about its mortgage book – which compounded the lies about the dodgy CDO product they sold. The lies about the mortgage book totalled $20 billion on say $43 billion of optimistically valued assets – and those lies reduced the value of Citigroup by $200 billion because they removed the trust in Citigroup.

It is one of those ironic things that when financial institutions lied in 2006 the market seemed to believe them. When they tell the truth now, nobody will listen.

Robert Rubin racks his brain about how he would have done things differently. Well one thing he would have done differently is get Citigroup to remove the culture of obfuscation – the culture that allowed it to be perceived as if it were lying even when it was telling the truth. The problem is that even Robert Rubin doesn’t have enough uncashed integrity to save Citigroup. Even Robert Rubin.

The US government is now selling systemic risk insurance.

Finally, System-Risk Insurance, by Laurence Kotlikoff and Perry Mehrling, FT

As we advocated two months back (Bagehot plus RFC: The Right Financial Fix), Uncle Sam is finally starting to sell systematic risk insurance on high-grade securities in exchange for preferred stock. This is a critical function for the U.S. government; Uncle Sam is the only player capable of hedging systemic risk because he’s the only player capable of taking actions that keep the overall economic system on the right course.

The real question now is whether the U.S. government will begin selling system-risk insurance on a routine basis and, thereby, help refloat trillions of dollars in high-grade mortgage-related securities owned by banks and other financial institutions - institutions that are in desperate need of more capital to support new lending.

Writing one-off insurance deals with a few large players, like Citigroup, is not the same as standing ready to write system-risk insurance to all players that issue conforming high-grade paper - something that’s needed to support ongoing securitization of such obligations. We stress the word “conforming,” because it’s vital for the government to begin stipulating which securities are “safe” under normal conditions and which are “toxic” and, thus, no longer to be held by financial intermediaries.

Like any insurance underwriter, Uncle Sam needs not only to know and approve what he’s insuring; he also needs to make sure there are appropriate deductibles and co-insurance provisions to limit moral hazard on the part of the insured. The moral hazard in this case is that financial institutions try to pass off low-grade loans as high-grade.

The weekend deal with Citigroup is instructive in clarifying the nature of the insurance the government should sell on an ongoing basis. The deal to support $306bn of Citigroup’s mortgage-related securities puts a floor under the value of the best such securities at about 90 cents on the dollar. This deal represents the first use of the insurance capability authorized by Section 102 of the TARP.

[90 cents on the dollar? WTF!?! Incompetent management is left in place while the taxpayer foots the bill. Why not bail out Detroit while we're at it? Note: this is clarified by a commenter -- it's 90% of current market value, not face value.]

The structure of the deal is convoluted, so it takes some probing to see precisely what insurance is being sold and for what price. We are told that Citigroup itself is on the hook for the first loss of $29bn (plus whatever loss reserves are already on its books) on the cash flows due on the $306bn in mortgages. This amounts to roughly a 10 percent deductible.

Any losses beyond $29bn will be shared by the government (90 per cent) and Citigroup (10 per cent). This is the co-insurance (co-pay) element. This insurance runs for the next 10 years, and Citigroup is paying a one-time $7bn premium for it, using preferred stock.