naked capitalism

We’ve followed the story of the slow but increasing and badly needed pushback against Monsanto’s predatory business practices, which force farmers to buy Monsanto seed annually, rather than re-use it. Worse, Monsanto seed has been genetically engineered so as to require the use of Monsanto herbicides and fertilizers.

And with (until recently) the seeds patent protected, farmers could be sued for having Monsanto genes in their crops. And with Monsanto having established a near monopoly in seeds, it has set prices so as to extract a higher percent of agricultural revenues than it could otherwise command. Needless to say, what is good for Monsanto is not at all good for farmers, as these excerpts from a Daily Kos post illustrates:

I am a small farmer, and I am deeply concerned about the broad power Monsanto and other seed companies wield. Their patents on life, unfair business practices, and aggressive genetic engineering of seed for commercial farming are making farmers dependent on their very expensive seed and killing the millennia-old practice of saving seed.

Since I was a child, the cotton business has been radically changed by developments like Round-Up Ready cotton. Farmers are forced by market pressures to adopt new practices, like using Monsanto seed, that are locking them into annual tithes to a monopolistic seed company. Monsanto, in particular, has forced hundreds of small seed companies out of the business with litigation and threats of litigation, and it’s no accident. Farmers are afraid to collect seeds at all, for fear that Monsanto will accuse them of patent infringement….

In visiting my husband’s family in Bangladesh, my brother-in-law complained about the lack of rice varieties available for consumption. In the past, hundreds of tasty varieties were available. Now only a very few with much less taste are on the market. These varieties, grown in the very unhealthy chemically dependent and unsustainable manner espoused by Monsanto to encourage the use of their many pesticides and herbicides, depletes the land and contaminate the waterways. Fish populations, on which the Bangladeshi population depends heavily for protein, are disappearing. Only the farm-raised varieties are in vast supply, those also being of less nutritional value and raised in polluted waters.

Monsanto’s hold on the seed market is especially problematic in that they also manufacture the chemicals with which the seeds are grown. This is forcing many farmers to use GMO seeds and unsustainable methods whether they want to or not. Neighboring farms (specifically, organic or those choosing to use non-GMO seeds) are having their seeds contaminated by the GMO varieties. Native varieties and hybrids, grown for 10,000 years and adapted to optimize local growing conditions, are bought up by Monsanto and removed from the market, denying options to farmers and consumers. Those not bought up are in danger of contamination by Terminator genes, which would lead to their extinction. The same way we protect animal species from extinction, we should protect plant species, especially the tens of thousands of food varieties, from companies like Monsanto that are consciously eliminating them. Would we allow genocide to occur in any other circumstance?

GMO crops have not been tested properly for safety. In India, farmers allowed their cattle to graze on GMO cotton plant stubble as they had grazed their cattle for millennia; all those cattle died within a few days. Many GMO varieties are neither better yielding nor requiring less fertilizer or water. They are designed to increase the use of Monsanto chemicals. These varieties are more expensive to grow, and the farmers are not allowed to save seed for the next year or the seeds have “Terminator” or “Traitor” genes to make new seeds sterile, causing them added expense. Monsanto’s methods are depleting the soil in areas already stressed.

I hope you will rein in these companies and start to restore a sense of fair play to agribusiness. Family farmers have enough to deal with without big chemical and seed companies holding them hostage.

The US courts have begun to whittle away at some of Monsanto’s efforts to monopolize seed production:

The Public Patent Foundation (PUBPAT) announced today that the United States Patent and Trademark Office has rejected four key Monsanto patents related to genetically modified crops that PUBPAT challenged last year because the agricultural giant is using them to harass, intimidate, sue – and in some cases literally bankrupt – American farmers. In its Office Actions rejecting each of the patents, the USPTO held that evidence submitted by PUBPAT, in addition to other prior art located by the Patent Office’s Examiners, showed that Monsanto was not entitled to any of the patents.
Monsanto has filed dozens of patent infringement lawsuits asserting the four challenged patents against American farmers, many of whom are unable to hire adequate representation to defend themselves in court. The crime these farmers are accused of is nothing more than saving seed from one year’s crop to replant the following year, something farmers have done since the beginning of time.

One study of the matter found that, “Monsanto has used heavy-handed investigations and ruthless prosecutions that have fundamentally changed the way many American farmers farm. The result has been nothing less than an assault on the foundations of farming practices and traditions that have endured for centuries in this country and millennia around the world, including one of the oldest, the right to save and replant crop seed.”

Raw Story describes the latest anti-Monsanto salvo, this by India :

India refused to grant permission Wednesday for the commercial cultivation of its first genetically modified (GM) food crop, citing problems of public trust and “inadequate” science.

Environment Minister Jairam Ramesh said he was imposing a moratorium on the introduction of an aubergine modified with a gene toxic to pests that regularly devastate crops across India.

“It is my duty to adopt a cautious, precautionary, principle-based approach and impose a moratorium on the release,” until scientific tests can guarantee the safety of the product, said Ramesh…

“I cannot go against science but in this case science is inadequate,” he added. “I have to be sensitive to public concerns.”

Indian regulators had approved the new aubergine back in October and its introduction would have made it the first GM foodstuff to be grown in India.

But the decision roused huge opposition and a broad spectrum of voices, including farmers, environmentalists and politicians of all stripes had urged the government to prevent its cultivation…

Ramesh said there was “no overriding food security argument” for the introduction of GM aubergines.

He said he had considered the views of different interest groups in making his decision but denied he had been pressured by members of his cabinet or by companies producing genetically modified crops.

“My conscience is clear. This is my decision and my decision alone,” he said.

India is one of the largest aubergine producers globally.

Reader John D, who pointed us to the piece, adds:

They are fighting Monsanto trying to patent the genes from their indigenous plants.

The history of GMO crops in India is like elsewhere. The first few years are great then they need more herbicide and more fertilizer to get yields and that drives the farmer into bankruptcy. India has had a rash of farmer suicides due to crop failures. They didn’t have this with indigenous seeds. The costs were much less and they could muddle through.

The concerns about safety are also legitimate. As Scientific American pointed out:

Unfortunately, it is impossible to verify that genetically modified crops perform as advertised. That is because agritech companies have given themselves veto power over the work of independent researchers.

…Under the threat of litigation, scientists cannot test a seed to explore the different conditions under which it thrives or fails. They cannot compare seeds from one company against those from another company. And perhaps most important, they cannot examine whether the genetically modified crops lead to unintended environmental side effects.

Research on genetically modified seeds is still published, of course. But only studies that the seed companies have approved ever see the light of a peer-reviewed journal. In a number of cases, experiments that had the implicit go-ahead from the seed company were later blocked from publication because the results were not flattering. “It is important to understand that it is not always simply a matter of blanket denial of all research requests, which is bad enough,” wrote Elson J. Shields, an entomologist at Cornell University, in a letter to an official at the Environmental Protection Agency (the body tasked with regulating the environmental consequences of genetically modified crops), “but selective denials and permissions based on industry perceptions of how ‘friendly’ or ‘hostile’ a particular scientist may be toward [seed-enhancement] technology.”

Some research recently raised questions on the adequacy of Monsanto’s research on the health of GMOs (a mere 90 days) and some small scale animals studies have found consumption of Monsanto GM products are associated with organ damage. One reader noted:

I am fairly well-qualified to comment on this, as both a PhD in genetics who has made hundreds of transgenic plant lines (albeit in Arabidopsis) and a former Nature editor.

I don’t doubt for a second that Monsanto has failed to adequately investigate the potential negative effects of BT toxin (MON 810 and MON 863) and bar (NK 603) overexpression and possible toxicity. This is even more warranted by the fact that these genes are being regulated by a strong viral promoter (CaMV35S) that is producing levels of these proteins that far exceed what would normally occur in a plant–even though these gene products don’t normally in plants. (Both genes are bacterial in origin.)

That’s a long winded way of saying concerns about Monsanto, from both a health and economic perspective, are far from alarmist.

One of my friends is a biomedical engineer who gave up doing science because it involved too much drawing of lines through scatter diagrams to claim the existence of relationships in order to keep the grant money coming in. She got a law degree, and worked for the National Institutes of Health, Big Pharma, a buyout firm, and served as general counsel of a public company before joining a firm with a well regarded FDA practice.

She is also the antithesis of a health food neurotic. She believes red wine and cheese are major food groups, likes chips, eats candy now and again. But if the subject of genetically modified food comes up, she will sputter for a minute or two and and bite her tongue. “That stuff should be banned. They are conducing a massive experiment on the public with no consent and no controls.” She argues that the research on the safety of GMOs are far too short in duration to conclude that they are safe. Moreover, she went to some lengths to try to avoid GMOs, and gave up, concluding it was too hard.

A new study published in the International Journal of Biological Sciences (hat tip reader Crocodile Chuck) uggests her concerns may be well founded. This study was a reanalysis of various studies performed on rats which ran for 90 days (which is actually long for this sort of research). An overview of the study:

There is a world-wide debate concerning the safety and regulatory approval process of genetically modified (GM) crops and foods [1, 2]. In order to scientifically address this issue, it is necessary to have access to toxicological tests, preferably on mammals, performed over the longest time-scales involving detailed blood and organ system analyses. Furthermore, these tests should, if possible, be in accordance with OECD guidelines. Unfortunately, this has been a challenge since usually these are regulatory tests performed confidentially by industry prior to commercialization of their GM crops, pesticides, drugs or chemicals. As a result, it is more instructive to investigate the available data that allows comparisons of several GMOs consumptions on health effects. This will allow the most appropriate statistical analyses to be performed in order to avoid possible false positive as well as false negative results. The physiological criteria used to either accept or reject any GM significant effect as relevant should be made clear. Here we discuss sex-related, temporal, linear and non-linear dose effects which are often involved in the establishment of chronic and endocrine diseases.

We investigated three different GM corn namely NK 603, MON 810 and MON 863, which were fed to rats for 90 days. The raw data have been obtained by European governments and made publically available for scrutiny and counter-evaluation. These studies constitute a model to investigate possible subchronic toxicological effects of these GM cereals in mammals and humans. These are the longest in vivo tests performed with mammals consuming these GMOs. The animals were monitored for numerous blood and organ parameters.

From the conclusion:

…. in the three GM maize varieties that formed the basis of this investigation, new side effects linked to the consumption of these cereals were revealed, which were sex- and often dose-dependent. Effects were mostly concentrated in kidney and liver function, the two major diet detoxification organs, but in detail differed with each GM type. In addition, some effects on heart, adrenal, spleen and blood cells were also frequently noted. As there normally exists sex differences in liver and kidney metabolism, the highly statistically significant disturbances in the function of these organs, seen between male and female rats, cannot be dismissed as biologically insignificant as has been proposed by others [4]. We therefore conclude that our data strongly suggests that these GM maize varieties induce a state of hepatorenal toxicity. This can be due to the new pesticides (herbicide or insecticide) present specifically in each type of GM maize, although unintended metabolic effects due to the mutagenic properties of the GM transformation process cannot be excluded.

From a Huffington Post story on the study:

Monsanto gathered its own crude statistical data after conducting a 90-day study, even though chronic problems can rarely be found after 90 days, and concluded that the corn was safe for consumption. The stamp of approval may have been premature, however….

Monsanto has immediately responded to the study, stating that the research is “based on faulty analytical methods and reasoning and do not call into question the safety findings for these products.”

The IJBS study’s author Gilles-Eric Séralini responded to the Monsanto statement on the blog, Food Freedom, “Our study contradicts Monsanto conclusions because Monsanto systematically neglects significant health effects in mammals that are different in males and females eating GMOs, or not proportional to the dose. This is a very serious mistake, dramatic for public health. This is the major conclusion revealed by our work, the only careful reanalysis of Monsanto crude statistical data.”

Seeking greater efficiency often winds up compromising safety. Why should food production be any different?

By George Washington of Washington’s Blog.

As I have repeatedly noted, mainstream economists and financial advisors have been using faulty and unrealistic models for years. See this, this, this, this, this and this.

And I have pointed out numerous times that economists and advisors have a financial incentive to use faulty models. For example, I pointed out last month:

The decision to use faulty models was an economic and political choice, because it benefited the economists and those who hired them.

For example, the elites get wealthy during booms and they get wealthy during busts. Therefore, the boom-and-bust cycle benefits them enormously, as they can trade both ways.

Specifically, as Simon Johnson, William K. Black and others point out, the big boys make bucketloads of money during the booms using fraudulent schemes and knowing that many borrowers will default. Then, during the bust, they know the government will bail them out, and they will be able to buy up competitors for cheap and consolidate power. They may also bet against the same products they are selling during the boom (more here), knowing that they’ll make a killing when it busts.

But economists have pretended there is no such thing as a bubble. Indeed, BIS slammed the Fed and other central banks for blowing bubbles and then using “gimmicks and palliatives” afterwards.

It is not like economists weren’t warning about booms and busts. Nobel prize winner Hayek and others were, but were ignored because it was “inconvenient” to discuss this “impolite” issue.

Likewise, the entire Federal Reserve model is faulty, benefiting the banks themselves but not the public.

However, as Huffington Post notes:

The Federal Reserve, through its extensive network of consultants, visiting scholars, alumni and staff economists, so thoroughly dominates the field of economics that real criticism of the central bank has become a career liability for members of the profession, an investigation by the Huffington Post has found.

This dominance helps explain how, even after the Fed failed to foresee the greatest economic collapse since the Great Depression, the central bank has largely escaped criticism from academic economists. In the Fed’s thrall, the economists missed it, too.

“The Fed has a lock on the economics world,” says Joshua Rosner, a Wall Street analyst who correctly called the meltdown. “There is no room for other views, which I guess is why economists got it so wrong.”

The problems of a massive debt overhang were also thoroughly documented by Minsky, but mainstream economists pretended that debt doesn’t matter.

And – even now – mainstream economists are STILL willfully ignoring things like massive leverage, hoping that the economy can be pumped back up to super-leveraged house-of-cards levels.

As the Wall Street Journal article notes:

As they did in the two revolutions in economic thought of the past century, economists are rediscovering relevant work.

It is only “rediscovered” because it was out of favor, and it was only out of favor because it was seen as unnecessarily crimping profits by, for example, arguing for more moderation during boom times.

The powers-that-be do not like economists who say “Boys, if you don’t slow down, that bubble is going to get too big and pop right in your face”. They don’t want to hear that they can’t make endless money using crazy levels of leverage and 30-to-1 levels of fractional reserve banking, and credit derivatives. And of course, they don’t want to hear that the Federal Reserve is a big part of the problem.

Indeed, the Journal and the economists it quotes seem to be in no hurry whatsoever to change things:

The quest is bringing financial economists — long viewed by some as a curiosity mostly relevant to Wall Street — together with macroeconomists. Some believe a viable solution will emerge within a couple of years; others say it could take decades.

Saturday, PhD economist Michael Hudson made the same point:

I think that the question that needs to be asked is how the discipline was untracked and trivialized from its classical flowering? How did it become marginalized and trivialized, taking for granted the social structures and dynamics that should be the substance and focal point of its analysis?…

To answer this question, my book describes the “intellectual engineering” that has turned the economics discipline into a public relations exercise for the rentier classes criticized by the classical economists: landlords, bankers and monopolists. It was largely to counter criticisms of their unearned income and wealth, after all, that the post-classical reaction aimed to limit the conceptual “toolbox” of economists to become so unrealistic, narrow-minded and self-serving to the status quo. It has ended up as an intellectual ploy to distract attention away from the financial and property dynamics that are polarizing our world between debtors and creditors, property owners and renters, while steering politics from democracy to oligarchy…

[As one Nobel prize winning economist stated,] “In pointing out the consequences of a set of abstract assumptions, one need not be committed unduly as to the relation between reality and these assumptions.”

This attitude did not deter him from drawing policy conclusions affecting the material world in which real people live. These conclusions are diametrically opposed to the empirically successful protectionism by which Britain, the United States and Germany rose to industrial supremacy.

Typical of this now widespread attitude is the textbook Microeconomics by William Vickery, winner of the 1997 Nobel Economics Prize:

“Economic theory proper, indeed, is nothing more than a system of logical relations between certain sets of assumptions and the conclusions derived from them… The validity of a theory proper does not depend on the correspondence or lack of it between the assumptions of the theory or its conclusions and observations in the real world. A theory as an internally consistent system is valid if the conclusions follow logically from its premises, and the fact that neither the premises nor theconclusions correspond to reality may show that the theory is not very useful, but does not invalidate it. In any pure theory, all propositions are essentially tautological, in the sense that the results are implicit in the assumptions made.”

Such disdain for empirical verification is not found in the physical sciences. Its popularity in the social sciences is sponsored by vested interests. There is always self-interest behind methodological madness. That is because success requires heavy subsidies from special interests, who benefit from an erroneous, misleading or deceptive economic logic. Why promote unrealistic abstractions, after all, if not to distract attention from reforms aimed at creating rules that oblige people actually to earn their income rather than simply extracting it from the rest of the economy?

As I have previously written, mainstream economists and financial advisors who promote flawed models are not necessarily bad people:

I am not necessarily saying that mainstream economists were intentionally wrong, or that they lied because it led to promotions or pleased their Wall Street, Fed or academic bosses.

But it is harder to fight the current and swim upstream then to go with the flow, and with so many rewards for doing so, there is a strong unconscious bias towards believing the prevailing myths. Just like regulators who are too close to their wards often come to adopt their views, many economists suffered “intellectual capture” by being too closely allied with Wall Street and the Fed.

As Upton Sinclair said:

It is difficult to get a man to understand something, when his salary depends upon his not understanding it.

Readers may recall a 2008 study that found a link between testosterone levels and same-day trading performance. A typical summary:

John Coates and Joe Herbert from the University of Cambridge shadowed 17 male traders over 8 working days as they went about their business in a mid-sized City of London trading floor (the City is the capital’s financial district for the non-Brits among us). The bulk of their work took place between 11 am and 4pm, and at these times, Coates and Herbert took saliva samples to measure how their hormone levels shifted in a real-life situation. At the end of each one, the duo recorded how much profit and loss each trader had made…..

Coates and Herbert found that the traders were significantly more charged with testosterone on days when they beat their previous monthly average, than on those when they came under it. One trader, for example, enjoyed a 6-day winning streak that saw his profits soar to twice their historic average and his daily testosterone levels rise by 76%. And on days when the traders’ morning levels of testosterone were higher than normal, they made higher profits than days when they started off with low levels.

These patterns suggested that high testosterone levels lead to high profits.

Yves here. Aargh. Because I got plugged into the Canadian Sports Mafia (a loose association of Canadian doctors and coaches who consult to, train, and treat US pro teams and individual athletes), I got to know a Canadian doctor who is a world expert on dietary supplements. He does something pretty novel. He reads all the scientific research (I say that tongue in cheek because you’d be amazed at how many products are touted as having research behind them when they don’t). What is his first screen on the research? Whether the study is any good. Most are very badly designed, with a common failing that the sample size is too small.

That fits this study in spades. 17 guys over 8 days is too few observations. The Canadian MD would seldom consider anything that had fewer than 100 participants. Moreover, these men were ALL FROM THE SAME DEALING ROOM. You could have had intra-group dynamics playing a role and muddying the findings.

And later studies questioned the relationship, but they got less coverage:

Research by myself and my colleagues found that moderately elevated levels of this hormone increased the profits of high-frequency traders – although at higher levels it can cause overconfidence and risky behaviour, morphing traders into Masters of the Universe.

What we could not say, however, was whether testosterone was having its beneficial effects by increasing the trader’s skill or merely by increasing his appetite for risk.

In a study published on Wednesday in PLoS ONE we found that testosterone had little to do with trading skill. Traders with higher testosterone did indeed do better at this type of trading, because they took more risk. But there was no link between the hormone and their trading skills, as measured by the Sharpe ratio.

But traders were told that being a higher testosterone trader makes you a better trader. Let’s consider what being told one had a higher testosterone level produced in a different context. From the BBC:

Giving women more of the male hormone testosterone can turn them into fairer and more amiable game players…

So that old fashioned business about honor may have some distant foundation. But then get a load of this:

For the study, they asked more than 120 women to pair up and play an “ultimatum” bargaining game with real money at stake.

In the game, one of the pair is the “proposer” and is tasked with suggesting to the other player – the responder – how to split the money between them.

The responder can then only accept or reject the offer.

If they reject it, neither of the pair gets any of the cash.

The researchers gave the proposers either a dummy pill or one containing testosterone, but did not tell the women which pill they had been given.

Once they had played the game, the proposers were asked to say which pill they thought they had taken.
Those who received testosterone behaved more fairly, had fewer bargaining conflicts and were better at social interactions.

However, women who thought that they had received testosterone, whether or not they actually did, behaved more unfairly than those who thought that they had received placebo, again whether or not they actually did.

The researchers, led by Ernst Fehr of the University of Zurich, Switzerland, said the results suggested a case of “mind over matter” with the brain overriding body chemistry.

The study is by Nature and is firewalled. One could argue that if some women thought they received testosterone, there might have been a defect in the study implementation (it ought to be double blind, placebo controlled, but was it? Why would some women think they knew what they had received?)

But the other media coverage reinforces the conclusion that the stereotyping of testosterone-fueled behavior trumped its real effects:

They claim the results finally dismiss the myth – sometimes even used in court – that the sex hormone testosterone is the cause of much male aggression and anti-social behaviour.

However the popular belief that it makes you more ruthless and rebellious is so strong that if people believe they are taking the hormone they tend to fulfil their beliefs.

Now we can drive a truck through the reasoning here….a study on the effects of testosterone on women being applied to men? Ahem. But it certainly suggests that an separate study on men could be very revealing.

And it further suggests an interesting line of thought: if scientists demonstrate that testosterone-driven behavior is not aggressive, can we legitimately start to redefine what real macho means?

Personally, I never liked Master of the Universe types and we’ve had twenty plus years of celebration of that sort of behavior. I’d welcome anything that could undermine they cultural mythology that depicts it as attractive.

By George Washington of Washington’s Blog.

Investors are basically rational, right?

In fact, as many studies have demonstrated, the answer is no.

But instead of wading through all of the investment psychology research, let’s look at research into people’s basic reasoning abilities. Bear with me for a minute. A study in an area unrelated to investing sheds light on people’s basic thinking processes.

Sociologists from four major research institutions investigated why so many Americans believed that Saddam Hussein was behind 9/11, years after it became obvious that Iraq had nothing to do with 9/11.

The researchers found, as described in an article in the journal Sociological Inquiry (and re-printed by Newsweek):

• Many Americans felt an urgent need to seek justification for a war already in progress

• Rather than search rationally for information that either confirms or disconfirms a particular belief, people actually seek out information that confirms what they already believe.

• “For the most part people completely ignore contrary information.”

• “The study demonstrates voters’ ability to develop elaborate rationalizations based on faulty information”

• People get deeply attached to their beliefs, and form emotional attachments that get wrapped up in their personal identity and sense of morality, irrespective of the facts of the matter.

• “We refer to this as ‘inferred justification, because for these voters, the sheer fact that we were engaged in war led to a post-hoc search for a justification for that war.

• “People were basically making up justifications for the fact that we were at war”

• “They wanted to believe in the link [between 9/11 and Iraq] because it helped them make sense of a current reality. So voters’ ability to develop elaborate rationalizations based on faulty information, whether we think that is good or bad for democratic practice, does at least demonstrate an impressive form of creativity.

An article yesterday in Alternet discussing the Sociological Inquiry article helps us to understand that the key to people’s active participation in searching for excuses for actions by the big boys is fear:

Subjects were presented during one-on-one interviews with a newspaper clip of this Bush quote: “This administration never said that the 9/11 attacks were orchestrated between Saddam and al-Qaeda.”The Sept. 11 Commission, too, found no such link, the subjects were told.

“Well, I bet they say that the commission didn’t have any proof of it,” one subject responded, “but I guess we still can have our opinions and feel that way even though they say that.”

Reasoned another: “Saddam, I can’t judge if he did what he’s being accused of, but if Bush thinks he did it, then he did it.”

Others declined to engage the information at all. Most curious to the researchers were the respondents who reasoned that Saddam must have been connected to Sept. 11, because why else would the Bush Administration have gone to war in Iraq?

The desire to believe this was more powerful, according to the researchers, than any active campaign to plant the idea.

Such a campaign did exist in the run-up to the war…

He won’t credit [politicians spouting misinformation] alone for the phenomenon, though.

“That kind of puts the idea out there, but what people then do with the idea … ” he said. “Our argument is that people aren’t just empty vessels. You don’t just sort of open up their brains and dump false information in and they regurgitate it. They’re actually active processing cognitive agents”…

The alternate explanation raises queasy questions for the rest of society.

“I think we’d all like to believe that when people come across disconfirming evidence, what they tend to do is to update their opinions,” said Andrew Perrin, an associate professor at UNC and another author of the study…

“The implications for how democracy works are quite profound, there’s no question in my mind about that,” Perrin said. “What it means is that we have to think about the emotional states in which citizens find themselves that then lead them to reason and deliberate in particular ways.”

Evidence suggests people are more likely to pay attention to facts within certain emotional states and social situations. Some may never change their minds. For others, policy-makers could better identify those states, for example minimizing the fear that often clouds a person’s ability to assess facts …

The Alternet article links to a must-read interview with psychology professor Sheldon Solomon, who explains:

A large body of evidence shows that momentarily [raising fear of death], typically by asking people to think about themselves dying, intensifies people’s strivings to protect and bolster aspects of their worldviews, and to bolster their self-esteem. The most common finding is that [fear of death] increases positive reactions to those who share cherished aspects of one’s cultural worldview, and negative reactions toward those who violate cherished cultural values or are merely different.

Fear in the Economic and Financial Arenas

Has something similar happened in the economic/financial arenas?

Congressmen Brad Sherman and Paul Kanjorski and Senator James Inhofe all say that the government warned of martial law if Tarp wasn’t passed. And Rahm Emanuel famously said:

Never let a serious crisis go to waste. What I mean by that is it’s an opportunity to do things you couldn’t do before.

Last year:

• Senator Leahy said “If we learned anything from 9/11, the biggest mistake is to pass anything they ask for just because it’s an emergency”

• The New York Times wrote:
  

  “The rescue is being sold as a must-have emergency measure by an administration with a controversial record when it comes to asking Congress for special authority in time of duress.”
  ***

  Mr. Paulson has argued that the powers he seeks are necessary to chase away the wolf howling at the door: a potentially swift shredding of the American financial system. That would be catastrophic for everyone, he argues, not only banks, but also ordinary Americans who depend on their finances to buy homes and cars, and to pay for college.

  Some are suspicious of Mr. Paulson’s characterizations, finding in his warnings and demands for extraordinary powers a parallel with the way the Bush administration gained authority for the war in Iraq. Then, the White House suggested that mushroom clouds could accompany Congress’s failure to act. This time, it is financial Armageddon supposedly on the doorstep.

  “This is scare tactics to try to do something that’s in the private but not the public interest,” said Allan Meltzer, a former economic adviser to President Reagan, and an expert on monetary policy at the Carnegie Mellon Tepper School of Business. “It’s terrible.”

Not Just Government

But it’s not just government . . .

If the too big to fails say that the world economy will crash and there will be martial law unless they are bailed out, politicians – most of whom don’t understand finance or economics – will believe them, and sound the alarm themselves.

As Karl Denninger wrote yesterday:

[AIG's CEO] left Geithner with two documents. One was a fact sheet that listed all the attributes of AIG FP [the division run by Joe Cassano that blew the company up] and argued why it should be given status as a primary dealer. The other–a bombshell that Willumstad was confident would draw Geithner’s attention–was a report on AIG’s counterparty exposure around the world, which included “2.7 trillion of notional derivative exposures, with 12,000 individual contracts.” About halfway down the page, in bold, was the detail that Willumstad hoped would strike Geithner as startling: “$1 trillion of exposures concentrated with 12 major financial institutions.”

Was that a threat?

And isn’t threatening the United States (whether directly or otherwise) something you’re not supposed to do?

Sounds like “Bail me out or I will crash everything.”

Isn’t that analagous to walking into a bank, opening one’s coat to reveal an explosives-laced belt, and saying “gimme all the money or everyone dies!”

Yves Smith has previously used a similar analogy.

Fear Among Individual Investors

Investors – as with politicians or Americans in general – believe that “when [they] come across disconfirming evidence . . . . they tend to … update their opinions”, but in reality, they cling to the beliefs they formed during certain heightened emotional states, such as fear.

Fear turns people into sheep. Once they are sheep, they will strive mightily to justify the actions of their “leaders” – whether those leaders gave trillions of dollars in bailouts or got us into war, and even if the leaders’ justifications were false.

I believe this dynamic is also playing out in the fact that many Americans assume that the government has a real plan for fixing the economy, is working as hard as it can to do so, and that – eventually – things will improve.

Just as most Americans believe “since we’re at war in Iraq, and since the government previously claimed that Saddam was behind 9/11, he must have been”, they are probably thinking “since the government gave trillions to the giant banks and said that economists have figure out how to fix things, they must have done what was needed, and things will turn around in a v-shape recovery”.

The lengths people go to rationalize a false link between Saddam and 9/11 is a great example, because it may reveal by analogy how far people will go to justify their trust in our economic leaders and in their own investment decisions.

Of course, the yearning for high returns is the other half of what drives investor psychology. But this essay focuses on fear.

A fascinating and somewhat disturbing article at the New York Review of Books by Jerome Groopman looks at what counts for progress in medical diagnosis and finds it to be more of a mixed bag than most readers would assume. This won’t come as much of a surprise to those who know a bit about the field (one of my colleagues who worked at the National Institutes of Health called it “a medieval art”). But what is a tad disconcerting is that the efforts to make medicine more scientific may not in fact be a plus.

That may sound simply bizarre to readers. Isn’t evidence based medicine a good thing? Well, maybe not.

One of the reasons this piece struck a chord with me is that some of the efforts to make medicine more scientific parallel, in their negative aspects, the push to make economics more scientific. In medicine, this means developing more rules and tools for diagnosis; in economics, the course chosen was to impose more “rigor” which meant make greater use of mathematical exposition (proof-like theoretical papers) and to have “empirical” papers centered around statistical analysis of data sets.

Now while this all may sound well and good, in fact, both are methodological choices that limit investigation. For instance, evidence based medicine seeks to gather symptoms and then use that to determine what the ailment might be. Well, the problem is these protocols have been developed from people with only one thing wrong with them. Many people who show up in doctor’s offices have multiple pathologies. So a lot of effort is being expended to develop an approach that has limited value in the field, and worse, doctors are increasingly expected to conform to it.

An analogous problem in economics is the discipline has to ignore of finesse the role of uncertainty (unknown unknowns, as opposed to risk, outcomes that can be estimated with some precision). Frank Knight and John Maynard Keynes were both leery of undue reliance on math (and both were skilled in the art) for that very reason.

Another way that the desire to systematize medicine may not represent progress is that it limits doctors’ observational methods. Doctors look at a number of elements of a patients’ condition: skin tone, energy level, the quality of their breathing. Some of these do not fit neatly into diagnostic scoring methods and are thus discarded, resulting in information loss. There is in particular in medicine a distaste for seemingly old fashioned diagnostic methods even when they are more accurate than tests. My favorite pet peeve here is mammograms. A manual breast exam, whether done by the patient herself or by an experienced examiner, is far more successful at picking up the fast moving, dangerous cancers that pose a health risk. Mammograms are in fact a lousy test, good at picking up benign or slow moving growths (the ones patients will die with rather than of) and poor at picking up the deadly type. But women are hectored to have mammograms and they are falsely treated as a gold standard. Again, the analogy in economics is the preference for using data sets, and not having much interest in analyses that include hard and qualitative data (an author might include some discussion in a narrative section of his paper, as illustration or qualification, but there is not much receptivity to using qualitative analysis to supplement data sets with gaps).

Perhaps most important, Groopman stresses that the focus on methodology is dehumanizing medicine.

The ability to recognize complex patterns is one of our highest forms of intelligence, and one both disciplines seem inclined to devalue. Admittedly, as Malcolm Gladwell demonstrated in his book Blink, this faculty can be remarkably accurate or wildly wrong. Somehow, embracing technology too often leads to a rejection of older approaches, rather than figuring out how to use the best of both methods.

From Groopman:

Carrying the Heart: Exploring the Worlds Within Us
by F. González-Crussi
Kaplan, 291 pp., $26.95

The Deadly Dinner Party and Other Medical Detective Stories
by Jonathan A. Edlow, M.D.
Yale University Press, 245 pp., $27.50

Several months ago, I led a clinical conference for interns and residents at the Massachusetts General Hospital…

The subject of the conference centered on how physicians arrive at a diagnosis and recommend a treatment—questions that are central in the two books under review. We began by discussing not clinical successes but failures. Some 10 to 15 percent of all patients either suffer from a delay in making the correct diagnosis or die before the correct diagnosis is made. Misdiagnosis, it turns out, is rarely related to the doctor being misled by technical errors, like a laboratory worker mixing up a blood sample and reporting a result on the wrong patient; rather, the failure to diagnose reflects the unsuspected errors made while trying to understand a patient’s condition.[1]

These cognitive pitfalls are part of human thinking, biases that cloud logic when we make judgments under conditions of uncertainty and time pressure. Indeed, the cognitive errors common in clinical medicine were initially elucidated by the psychologists Amos Tversky and Daniel Kahneman in their seminal work in the early 1970s.[2] At the conference, I reviewed with the residents three principal biases these researchers studied: “anchoring,” where a person overvalues the first data he encounters and so is skewed in his thinking; “availability,” where recent or dramatic cases quickly come to mind and color judgment about the situation at hand; and “attribution,” where stereotypes can prejudice thinking so conclusions arise not from data but from such preconceptions.

A physician works with imperfect information. Patients typically describe their problem in a fragmented and tangential fashion—they tell the doctor when they began to feel different, what parts of the body bother them, what factors in the environment like food or a pet may have exacerbated their symptoms, and what they did to try to relieve their condition. There are usually gaps in the patient’s story: parts of his narrative are only hazily recalled and facts are distorted by his memory, making the data he offers incomplete and uncertain. The physician’s physical examination, where he should use all of his senses to try to ascertain changes in bodily functions—assessing the tension of the skin, the breadth of the liver, the pace of the heart—yields soundings that are, at best, approximations. More information may come from blood tests, X-rays, and scans. But no test result, from even the most sophisticated technology, is consistently reliable in revealing the hidden pathology.

So a doctor learns to question the quality and significance of the data he extracts from the medical history of the patient, physical examination, and diagnostic testing. Rigorous questioning requires considerable effort to stop and look back with a discerning eye and try to rearrange the pieces of the puzzle to form a different picture that provides the diagnosis. The most instructive moments are when you are proven wrong, and realize that you believed you knew more than you did, wrongly dismissing a key bit of information that contradicted your presumed diagnosis as an “outlier,” or failing to consider in your parsimonious logic that the patient had more than one malady causing his symptoms…

I worried aloud about how changes in the delivery of health care, particularly the increasing time pressure to see more and more patients in fewer and fewer minutes in the name of “efficiency,” could worsen the pitfalls physicians face in their thinking, because clear thinking cannot be done in haste…

Like all doctors educated over the past decade, the residents had been immersed in what is called “evidence-based medicine.” This is a movement to put medical care on a sound scientific footing using data from clinical trials of treatment rather than on anecdotal results. To be sure, this shift to science is welcome, but the “evidence” from clinical trials is often limited in its application to a particular patient’s case. Subjects in clinical trials are typically “cherry-picked,” meaning that they are included only if they have a single disease and excluded if they have multiple conditions, or are receiving other medications or treatments that might mar the purity of the population under study. People are also excluded who are too young or too old to fit into the rigid criteria set by the researchers.

Yet these excluded patients are the very people who heavily populate doctors’ clinics and seek their care…

At the conference, an animated discussion followed, and I heard how changes in the culture of medicine were altering the ways that the young doctors interacted with their patients. One woman said that she spent less and less time conversing with her patients. Instead, she felt glued to a computer screen, checking off boxes on an electronic medical record to document a voluminous set of required “quality of care” measures, many of them not clearly relevant to her patient’s problems…

During my training three decades ago, the team of interns and residents would move from bedside to bedside, engaging the sick person in discussion, looking for new symptoms; the medical chart was available to review the progress to date and new tests were often ordered in search of the diagnosis. By contrast, each patient now had his or her relevant data on the screen, and the team sat around clicking the computer keyboard. It took concerted effort for the group to leave the conference room and visit the actual people in need…

The two chief residents seemed deeply engaged by their patients’ lives and struggles, yet deeply frustrated, because that dimension of medicine, what is termed “medical humanism,” was, despite much lip service, given short shrift as a consequence of the enormous change in how medical care is being restructured.

What I heard from the residents at the Massachusetts General Hospital was not confined to that noon meeting or to young physicians. A close friend in New York City told me how his wife with metastatic ovarian cancer had spent six days in the hospital without a single doctor engaging her in a genuine conversation….no one attending to her had sat down in a chair at her bedside and conversed at eye level, asking questions and probing her thoughts and feelings about what was being done to combat her cancer and how much more treatment she was willing to undergo. The doctors had hardly touched her, only briefly placing their hands on her swollen abdomen to gauge its tension. The interactions with the clinical staff were remote, impersonal, and essentially mediated through machines.

Nor were these perceptions of the change in the nature of care restricted to reports from patients and their families. They were also made by senior physicians. My wife and frequent co-writer, Dr. Pamela Hartzband, an endocrinologist, reported conversations among the clinical faculty about how a price tag was being fixed to every hour of the doctor’s day. There were monetary metrics to be met, so-called “relative value units,” which assessed your productivity as a physician strictly by measuring how much money you, as a salaried staff member, generated for the larger department. There is a compassionate, altruistic core of medical practice—sitting with a grieving family after a loved one is lost; lending your experience to a younger colleague struggling to manage a complex case; telephoning a patient and listening to how she is faring after surgery and chemotherapy for her breast cancer; extending yourself beyond the usual working day to help others because that is much of what it means to be a doctor. But not one minute of such time may be accountable for reimbursement on a bean counter’s balance sheet.[5]

Still, I wondered whether my diagnosis of the ills of modern medicine was accurate. Perhaps I was weighed down by nostalgia, my perspective a product of selective hindsight. Certainly, coldly mercenary physicians were familiar in classical narratives of illness. Tolstoy satirized “celebrity doctors” who were well paid for offering Ivan Ilych ridiculous remedies for his undiagnosed malady while ignoring his suffering. Turgenev in “The Country Doctor” depicted an unctuous provincial physician whose degree of engagement with the sick was tied to the size of their pocketbook. Molière repeatedly lampooned the folly of pompous and greedy physicians.

Such doctors have been members of the profession since its founding. And it would be naive to believe that money is not one part of the exchange between physician and patient. But only recently has medical care been recast in our society as if it took place in a factory, with doctors and nurses as shift workers, laboring on an assembly line of the ill. The new people in charge, many with degrees in management economics, believe that care should be configured as a commodity, its contents reduced to equations, all of its dimensions measured and priced, all patient choices formulated as retail purchases. The experience of illness is being stripped of its symbolism and meaning, emptied of feeling and conflict. The new era rightly embraces science but wrongly relinquishes the soul.

n his book Carrying the Heart, Dr. Frank González-Crussi, a professor of pathology at Northwestern University, has made a sharp departure from medicine as a cold world of clinical facts and figures. Rather, he asks us to return to a view of the body not as a machine but as a wondrous work of creation, where both the corporeal and the spiritual coexist. His aim, he writes, is

to increase the public’s awareness of the body’s insides. By this, I do not mean the objective facts of anatomy, for most educated people today have a general, if limited, understanding of the body’s parts and functions. I mean the history, the symbolism, the reflections, the many ideas, serious or fanciful, and even the romance and lore with which the inner organs have been surrounded historically.

This précis captures the beauty and charm of his book. I learned from González-Crussi that for centuries the stomach was considered the most noble of organs, directing all important physiological functions. The ancients, González-Crussi tells us, called the stomach “the king of viscera,” “the senate or the patrician class; the bodily parts were the rebellious plebeians.” Shakespeare repeats this fable in Coriolanus, where the stomach lectures the rest of the body’s organs about the importance of its function.

Our gastric elements were seen as having a leading part in joy and adversity, and were the seat of the soul—predating the belief that the spirit was housed in the heart or the brain. This regal position was ultimately relinquished through the observations of Dr. William Beaumont in 1822. Beaumont studied a young French-Canadian named Alexis St. Martin, who suffered an accidental musket shot to the belly. He was left with a perforation some two and a half inches in circumference, through which the doctor could look into the living stomach and perform experiments on its workings. Via this “stomach window,” the physiology of the organ was gradually deciphered, and its fabled status faded.

No part of our anatomy, González-Crussi recounts, has failed to fascinate poets, priests, and philosophers—including the working of the colon. In the chapter on feces, we learn that the Chinese had a divinity of the toilet. “This was Zi-gu, ‘the violet lady.’ She was not entirely fictional,” González-Crussi writes,

but took her origin from a flesh-and-blood woman who lived about AD 689. To her misfortune, she was made the concubine of a high government official, Li-Jing. The man’s legitimate wife, overcome by jealousy, killed Zi-gu in cold blood while she was visiting the toilet. Since then, her ghost has haunted the latrines, “a most inconvenient circumstance for anyone in a hurry.”

The colon and its product also were part of the theology of the Aztecs. They believed that excrement

was capable of bringing ills and misfortune, and associated with sin, but also powerful and beneficent, able to ward off disease, to subdue the enemy, and to transform sexual transgressions into something useful and healthy.

Gold was termed “the sun’s excrement” and the sun god Tonatiuh deposited his own feces in the form of this precious element in the earth while he passed through to the underworld.

González-Crussi also reminds us that there was an inordinate fixation on one’s bowels during the Victorian age, which honored values of order, temperance, respect for tradition, and sexual repression. Personal self-control, the mark of British culture, was at odds with that urgent process of expelling air and waste:

Perhaps no greater ambivalence has ever existed toward the bowel than in Victorian England, where this organ was viewed with simultaneous skittish embarrassment and fascination, shame and fixed interest, shy modesty and hypnotic engrossment.
A shocking consequence of this cultural tension is that one of the most proficient surgeons of the era, William Arbuthnot Lane, who devised procedures to successfully set compound fractures, concluded that without a colon, man would free himself from inner toxins and extend his health and longevity. A natural physiological function became a pseudodisease. Initially, Lane devised operations to bypass the large bowel, and he then moved on to perform total colectomies. Patients flocked to him from all over Great Britain and abroad, certain that their lives would be more salubrious and fulfilling without their large intestine.

González-Crussi treats with similar scholarship and playful insight the uterus, the penis, the lungs, and the heart. He melds history with literature, religion with science, high humor with serious concerns. The sum of his narrative shows that medicine does not exist as some absolute ideal, but is very much a product of the prevailing culture, affected by the prejudices and passions of the time…But our culture, with its worship of technology and its deference to the technocrat, risks imposing an approach to medical care that ignores the deeply felt symbolism of our body parts and our desperate search for meaning when we suffer from illness…..

Jonathan Edlow is concerned with the doctor not as poet or philosopher or priest but as detective. An emergency room physician at the Beth Israel Deaconess Medical Center, a Harvard teaching hospital in Boston where I also work…Both detective and doctor not only assemble evidence but must judiciously weigh what they have found, seeking the underlying value of each clue. The successful doctor-detective must be alert to biases that can lead him astray. This was the message of the clinical conference those months ago; and in Edlow’s tales of difficult diagnoses, we can observe detours that are due to “anchoring,” “availability,” and “attribution.”…

In his chapter “An Airtight Case,” Edlow implicitly shows why so many of the standard formulas that policymakers promulgate fall short when answers are not obvious. He describes how an office worker (whom he calls Philip Bradford) thought he had developed “the flu—the usual cough, fevers, chest pain, just feeling lousy….” What appeared to be the symptoms of a typical viral illness did not spontaneously disappear. A chest X-ray showed pneumonia, but treatment with antibiotics proved ineffective. The presumptive diagnosis changed from infection to cancer, and Bradford was told by his doctor that he needed his chest opened to resect a piece of lung and identify the tumor.

Fortunately, the patient sought a second opinion, from a senior thoracic surgeon, and the diagnosis was again thrown into doubt—the specialist believed that the problem was neither infection nor an abnormal growth. Over the ensuing months, the mysterious pneumonia spontaneously cleared up, but after a year Bradford again started coughing and running a fever. “His chest X-ray blossomed with ominous nodules,” Edlow writes, “then, as with the previous episode, after a few weeks his symptoms mysteriously vanished.”

It was the good fortune of this ill office worker with the mysterious lung problem to see Dr. Robert H. Rubin, an infectious disease specialist at the Massachusetts General Hospital….what is striking is his “low-tech” thinking: “I was immediately impressed by three aspects of the case,” Rubin recalled.

First was that Bradford appeared healthy and athletic, not the picture of someone with a chronic disease. Second, between episodes, he continued to jog over five miles with no apparent problem. And third, his physical examination was normal.

With such comments, we are a universe away from sophisticated blood tests and CT scans, and deeply rooted in the world of the physician’s five senses. The most seasoned clinicians teach that the patient tells you his diagnosis if only you know how to listen. The clinical history, beyond all other aspects of information gathering, holds the most clues. And it is this part of medicine—the patient’s narrative, the onset and tempo of the illness, the factors that exacerbated the symptoms and those that ameliorated them, the foods the patient ate, the clothing he wore, the people he worked with, the trips he took, the myriad of other events that occurred before, during, and after the malady—that are as vital as any DNA analysis or MRI investigation.

Rubin concentrated that kind of questioning and listening on Bradford. He did not quickly dispatch him for more tests, but instead sharply shifted his focus to investigate clues in Bradford’s environment that could reveal what was causing inflammation in his lungs. Edlow goes on to write in clear and fluid prose about how Rubin systematically pursued what could be the agent provocateur in the case. The lengths to which Rubin went are extraordinary, his skill in eliciting and interpreting the patient’s narrative exemplary, and certainly not part of the rushed practice of today’s clinic. I won’t spoil the end of the story; what is important is that the solution came about only by dogged thinking that required the kind of time and inquiry that is absent in much of modern medical care.

The other detective stories in Edlow’s compilation transmit the same message: we most need a discerning doctor when a diagnosis is not obvious, when the clues are confusing, when initial tests are inconclusive. No simple technology can serve as a surrogate for the probing human mind. Edlow’s book is a welcome complement to González-Crussi’s. Both show us that medicine is truly an art and a science that requires doctors both to decipher the mystery and illuminate the meaning of the body in health and disease.

I have to admit, I have a weakness for the intersection of the daft and science:

Male readers will no doubt assume that this means the original owner of the gas mask bra must strip in the case of emergency, and that that the real point of this exercise. But the bra was designed by a woman who demonstrated at the ceremony that it could be removed discreetly. Hhm, I am sure such niceties would not be observed in a bona fide emergency.

The BBC gives a recap of the ceremony:

The Ig Nobel Prizes were presented to the winners by genuine Nobel laureates….

Past winners also returned to take part in the celebrations. They included Kees Moeliker, the discoverer of homosexual necrophilia in the mallard duck, and Dr Francis Fesmire, who devised the digital rectal massage as cure for intractable hiccups.

Each new winner was permitted a maximum of 60 seconds to deliver an acceptance speech. The time limit was enforced by an intractable eight-year-old girl.

The evening also featured numerous tributes to the evening’s theme of “Risk”.

A 15-minute risk cabaret concert by the Penny-Wise Guys preceded the ceremony, during which the band paid special tribute to fraudster Bernie Madoff.

Other winners per the Boston Globe:

Veterinary medicine: Dr. Catherine Douglas and Dr. Peter Rowlinson of Newcastle University, Newcastle-Upon-Tyne, UK, for showing that cows who have names give more milk than cows that are nameless.

Peace: Dr. Stephan Bolliger, Dr. Steffen Ross, Dr. Lars Oesterhelweg, Dr. Michael Thali, and Beat Kneubuehl of the University of Bern, Switzerland, for determining — by experiment — whether it is better to be smashed over the head with a full bottle of beer or with an empty bottle.

Economics: The directors, executives, and auditors of four Icelandic banks — Kaupthing Bank, Landsbanki, Glitnir Bank, and Central Bank of Iceland — for demonstrating that tiny banks can be rapidly transformed into huge banks, and vice versa — and for demonstrating that similar things can be done to an entire national economy.

Chemistry: Javier Morales, Miguel Apátiga, and Victor M. Castaño of Universidad Nacional Autónoma de México, for creating diamonds from liquid — specifically from tequila.

Medicine: Dr. Donald L. Unger, of Thousand Oaks, California, for investigating a possible cause of arthritis of the fingers, by diligently cracking the knuckles of his left hand — but never cracking the knuckles of his right hand — every day for more than 60 years.

Physics: Katherine K. Whitcome of the University of Cincinnati, Daniel E. Lieberman of Harvard University, and Liza J. Shapiro of the University of Texas for analytically determining why pregnant women don’t tip over.

Literature: Ireland’s police service, An Garda Siochana, for writing and presenting more than 50 traffic tickets to the most frequent driving offender in the country — Prawo Jazdy — whose name in Polish means “Driver’s License.”

Mathematics: Gideon Gono, governor of Zimbabwe’s Reserve Bank, for giving people a simple, everyday way to cope with a wide range of numbers — from very small to very big — by having his bank print bank notes with denominations ranging from 1 cent to 1 hundred trillion dollars.

Biology: Fumiaki Taguchi, Song Guofu, and Zhang Guanglei of Kitasato University Graduate School of Medical Sciences in Sagamihara, Japan, for demonstrating that kitchen refuse can be reduced more than 90 percent in mass by using bacteria extracted from the feces of giant pandas.

Conspiracy theorists will have to wait until the article described in Inside Science is published to determine whether it delivers on its claims. It claims to analyze stock holding across 48 countries and alleges they are held in very few hands. But the work was done by physicists, which means they may not have understood the limits of the data they were working with.

I suspect this will wind up resembling a paper a friend studied in his graduate level statistical methods course over two decades ago (he has since gone on to a successful career in academia). Everyone in the seminar was assigned a single paper and told to analyze the techniques used and to present their findings to the class. This was the sole basis for the grade.

The paper my buddy got had already created a bit of a stir, although it had not yet been published. The author had looked at the prices at which the Fed did its daily operations (then the famed “noon buying rate”) and compared it to the results of Treasury auctions. The paper concluded the Treasury was doing a terrible job, as demonstrated in all sorts of analyses.

When my friend’s day to present came, he stood up and said, “I have only one comment to make. The Fed conducts its daily operations in transaction sizes ranging in the millions. Treasury auctions are in the billions. The Fed data is irrelevant to the Treasury analysis,” and sat down.

He received an A.

In this case, an obvious fly in ointment is many (most?) stocks are held in street name, meaning in the name of the brokerage firm or fund, not the ultimate owner. I presume it is impossible to segregate accounts where the broker has discretion to trade versus those where the clients simply trades through the securities firm.

But even if the analysis is flawed, it might stir up some interesting discussion.

From Inside Science (hat tip reader John D):

A recent analysis of the 2007 financial markets of 48 countries has revealed that the world’s finances are in the hands of just a few mutual funds, banks, and corporations. This is the first clear picture of the global concentration of financial power, and point out the worldwide financial system’s vulnerability as it stood on the brink of the current economic crisis.

A pair of physicists at the Swiss Federal Institute of Technology in Zurich did a physics-based analysis of the world economy as it looked in early 2007. Stefano Battiston and James Glattfelder extracted the information from the tangled yarn that links 24,877 stocks and 106,141 shareholding entities in 48 countries, revealing what they called the “backbone” of each country’s financial market. These backbones represented the owners of 80 percent of a country’s market capital, yet consisted of remarkably few shareholders.

“You start off with these huge national networks that are really big, quite dense,” Glattfelder said. “From that you’re able to … unveil the important structure in this original big network. You then realize most of the network isn’t at all important.”

The most pared-down backbones exist in Anglo-Saxon countries, including the U.S., Australia, and the U.K. Paradoxically; these same countries are considered by economists to have the most widely-held stocks in the world, with ownership of companies tending to be spread out among many investors. But while each American company may link to many owners, Glattfelder and Battiston’s analysis found that the owners varied little from stock to stock, meaning that comparatively few hands are holding the reins of the entire market.

“If you would look at this locally, it’s always distributed,” Glattfelder said. “If you then look at who is at the end of these links, you find that it’s the same guys, [which] is not something you’d expect from the local view.”

Matthew Jackson, an economist from Stanford University in Calif. who studies social and economic networks, said that Glattfelder and Battiston’s approach could be used to answer more pointed questions about corporate control and how companies interact….

Based on their analysis, Glattfelder and Battiston identified the ten investment entities who are “big fish” in the most countries. The biggest fish was the Capital Group Companies, with major stakes in 36 of the 48 countries studied. In identifying these major players, the physicists accounted for secondary ownership — owning stock in companies who then owned stock in another company — in an attempt to quantify the potential control a given agent might have in a market….

Glattfelder added that the internationalism of these powerful companies makes it difficult to gauge their economic influence. “[With] new company structures which are so big and spanning the globe, it’s hard to see what they’re up to and what they’re doing,” he said. Large, sparse networks dominated by a few major companies could also be more vulnerable, he said. “In network speak, if those nodes fail, that has a big effect on the network.”

The results will be published in an upcoming issue of the journal Physical Review E.

Submitted by Richard Alford, a former economist at the New York Fed. Since them, he has worked in the financial industry as a trading floor economist and strategist on both the sell side and the buy side.

The fault, dear Brutus, is not in our model, but in ourselves–apologies to W Shakespeare

The economics profession is in disarray. Internecine warfare has broken out as proponents of various models/schools of thought are attacking and being attacked by each other. The battle between the different camps has been increasingly fought in the open e.g. The Economist and blogosphere. Despite the credentials of the combatants, there is a definite “My model can beat up your model’ air to the contretemps. The best outcome would be for policymakers to avail themselves of the models while losing the modelers.

Given the complexity of the financial markets and the economy, macro policymakers must operate on the basis of either implicit or explicit model(s). Furthermore, an explicit and transparent model subject to outside examination continuous testing is preferable to implicit poorly specified models that can serve as quasi-intellectual cover for policies based on solely belief systems.

However, macroeconomic models have been oversold again, the great moderation was fleeting. While economic models are necessary, both the recent experience and well-known limitations of the models themselves indicate that models alone will not be sufficiently robust to perform as well as many including investors and the general public have been led to expect. The underlying markets and the real economy are not stable. The models by definitions are incomplete. The responses of economic agents in times of stress and crisis may differ dramatically from the behavior reflected in parameters estimated on the basis of data collected in normal times. Goodhart’s law suggests that policy changes will induce changes in the statistical relationships on which the policy is based.

In defense of the current class of models (DSGE), some economists have spoken out saying that the models evolved as they did in response to questions raised by economists. But isn’t that the problem? Macro-economic models have become more formal and mathematically elegant, but all the while the modelers both ignored important drivers of economic performance, e.g. the workings of the financial markets, and failed to communicate the limitations of the models. The models evolved reflecting the economists‘desire for elegance and tractability, but with insufficient weight given to concerns such as financial stability or external balance.

Macro-economic policy is now being executed by the same people who devised the models. At times it has appeared that some of them sought policy making positions in order to be able to demonstrate the value of the model that they created or to which they made a contribution. These model builders were quick to take credit for the great moderation, but slow to see/ blind to the risk building up in the financial system and the imbalances. This type of behavior is to be expected. There is no reason to assume that the next set of policymaker/model builders will react any more positively to “warnings” that risks not central to the model pose real threats.

The role of model builders and policymakers should be split. Given the necessity of models in the policy formation process, it would be best, if the policymakers’ judgments about which model to use or when diverge from it are not clouded by previous involvement in the development of one or another of the models that might be employed.

Submitted by Richard Smith:

This is the Black Swan gospel according to Triana. Taleb endorses it in a characteristically incendiary and intemperate foreword. He does come out all guns blazing, and you just have to go with that. Or chuck a glass of water over him, if he’s in range, I suppose.

A quick recap for anyone who has spent the last two years in a coma: Taleb put together the beginnings of a rap sheet for modern mathematical finance theory in his book “The Black Swan”, and rapidly attained worldwide celebrity when his criticisms appeared to be borne out by the recent financial crisis. The main tenet of Black Swan theory, rather dry sounding, but with dramatic consequences, is that price changes are not normally distributed (in the way that, say, human weight or height are), but follow a power law (‘fat tails’). This implies much greater extremes of price movement than those predicted under the assumption of a normal distribution. The events that cause such price moves may be perfectly intelligible in hindsight, but are not necessarily predictable: like the existence of black swans.

The point about price distributions is actually quite an old one. Paul Levy made the same observation in the 1900s; Mandelbrot’s studies of cotton prices, in the 60s, reached similar conclusions. What gives it contemporary relevance is that the finance theory underlying current regulatory practice, risk management, fund management and derivatives pricing all overwhelmingly assume that price changes are normally distributed. And they all failed at once in the recent financial crisis, when price changes were indeed far more extreme than a normal distribution implies. It doesn’t look so good for orthodox financial theory just now.

So it is a good time for Triana to review modern finance theory’s rap sheet, add items, and add more detail to the existing charges. It goes like this.

Chapter 2: modern finance theory is a crock, peddled by charlatans at business schools who have managed to seal themselves off from the usual empirical tests of a theory.

I’ll admit I don’t see what logical point there is in attacking the character of business school teachers in this manner, whether it is a correct assessment or not. However the empirical criticism really does stack up. Consider GS CFO David Viniar’s notorious comments from August 2007 when the ABS meltdown got into full swing (Ch1, p12): “We were seeing things that were 25-standard-deviation moves, several days in a row”. To which the rejoinder from an empirically-minded observer simply has to be “No you weren’t, imbecile: those observations actually mean that your models are hopelessly wrong”. There are several reasons why one can so insouciantly cheek such an august figure. If we assume Viniar means daily observations and a normal distribution, then (if the numbers I am cribbing are correct: I haven’t gone back to the equations) one should expect to wait quite a lot longer than the age of the universe to see even a 16-standard deviation event, with a 25-standard deviation event taking many, many times longer than that. I suppose I should work out the exact number of years, just to see how big of a number it is: exercise for any readers with access to an arbitrary-precision mathematical engine.

You can find an old post by Yves on the subject that helped kick off some blogosphere chat.

Even if you assume (very charitably, I grimly suspect) that Viniar is not just parroting his VaR model outputs (more on that later), and is a bit more sophisticated about his distributions, he is still goofing, big time. And if Mandelbrot, and Taleb, his follower, and Triana, his follower, are right about the kind of distribution that underlies financial market price movements, there just ain’t sech a thing as a standard deviation of price movements, nor no correlation neither. Both standard deviation and correlation are defined in terms of variance. Since variance is infinite for stable distributions (other than the normal distribution), neither standard deviation nor correlation is defined for the distribution of market prices (a Levy skew alpha stable distribution, if you want the full geeky glory). On this theory, Viniar is talking about things that just don’t exist. Not encouraging behaviour in a CFO.

So here is the bleedin’ obvious: given its track record of ultra-wild underestimates of the frequency of sharp price moves, the assumption of normal distributions in stock price changes must be among the most lavishly disconfirmed scientific hypotheses of all time. No wonder, then, that Taleb and Triana are somewhat ratty with its various obstinately blithe proponents.

Chapter 3: Is a bit of a digression. According to Triana, the quants who work at banks work mostly on bits of IT dealing infrastructure, which is useful, and less often than you might think on mathematical models used in trading. The quants tend to be physicists and engineers rather than business school graduates. Models are used in a much more sceptical, provisional way on the trading floor than they are in academia.

I’ll take his word for it. Evidently, scepticism of models doesn’t extend to the risk management department. And, uh, actually it doesn’t look as if that trading floor scepticism managed to avert 2007’s monster trading screwups, either. Except, perhaps in the case of GS, who famously hedged a lot of MBS exposure starting late in 2006, to the great indignation of folk who don’t understand where fiduciary duties stop and start for broker-dealers.

Now we get into the meaty detail chapters. The non-normalness of price distributions means that a whole bunch of financial orthodoxies are dubious on theoretical grounds, and, post meltdown, there are some nasty data points to back up the theory.

First up is the Gaussian copula (Chapter 4). This is a modelling device which was used to calculate default correlations, for MBS and other bonds, and thus to structure, price, rate, and hedge CDOs. I think we already know how well that went overall– but the detail of how the behaviour of various tranches of CDOs diverged from predicted paths during the ’07 meltdown is instructive. Triana leaves open the question of whether the Gaussian copula was adopted out of blind faith in its efficacy, or precisely because it underrated extreme events, and thus gave an excuse for assigning a high rating, and getting a good price. Were the ratings agencies knaves or fools in this respect? I doubt we’ll find out any time soon. Anyhow, from the data and testimony Triana assembles, it looks as if the Gaussian copula is dead in the water as a structured finance tool. One wonders how Remics and re-Remics are to be priced and rated. Any NC readers want to buy one?

Chapter 5: Now we are into VaR, the risk management methodology that JP Morgan gave to the world back in the early 90’s, in the sadly mistaken belief that being able to generate a firm wide “risk number” daily would be a useful contribution to financial risk management. Back then you were reasonably smug about your bank if central management actually knew what the firm’s positions were at all (vide Barings, Sumitomo, then fast forward again to SocGen in – oh dear – 2007), so VaR was pretty cool. It was later endorsed by the Basel regulatory framework. Then the paint started to flake off.

The shortcomings of VaR have been a regular topic at NC. That pesky normal distribution assumption again. Note the reminder from practitioner Irene in the discussion thread though – the officially sanctioned VaR model may use a rolling 2 year price history rather than a normal distribution. This desperate kludge has its own perverse side effects: in times of increased volatility, the models all tell banks to stay on the sidelines at the same time. Once the volatile part of the price history rolls out, the models are all happy again. This is not a commonsense way to run banking businesses.

The other perversity of that approach to VaR is that it encourages herd behaviour in volatile markets, before the banks have even made it to the sidelines. In other words, since all the models in all the banks are essentially the same model of the same data, they all start screaming ‘fire’ at the same time, with predictable consequences at the exits. All this and more is well covered by Triana: particularly the way that a long period of low volatility before 2007 meant that VaR endorsed massive positions in assets that were suddenly big loss makers, when things went sour.

Banks were Gadarene enough without VaR. VaR makes it worse.

Oh, one thing that bugs me about VaR as used is this: if price histories tell you nothing about future prices (EMH), why is it that price volatility histories tell you something about future price volatility (VaR)? I’m just asking.

Anyhow, Triana makes the challenging points, with persuasive evidence: first, VaR is perfectly useless (it works until you need it, and at that point, it packs up: it is the chocolate teapot of risk management); second, like MTM, it is actively procyclical.

Chapter 6 is a brisk injunction to business schools (specifically, Sloane) to snap out of it and start teaching useful stuff.

In Chapter 7, we get to another polemic, against the Black-Scholes option pricing model. One can’t fault the reasoning or evidence, but somehow this is the weakest part of the meat. It is built around a recent paper by Taleb and Haug in which they review the historical record on options market making and option pricing theory and announce that a) the parts of Black-Scholes theory that are correct are not original, having been long anticipated by Thorp-Bachelier option pricing b) the parts that are original are not correct (normal distributions are again assumed, and the model simply can’t accommodate non-normal ones, unlike Thorp-Bachelier) c) no practitioners actually use Black-Scholes. The key item of evidence for (c) is the ‘volatility smile’ by which options traders systematically adjust option prices, so that the implied volatility (calculated according to Black Scholes methods) of options actually increases progressively for deeper and deeper out-of-the-money options. Under Black-Scholes pricing theory the implied volatility should be constant across all option strike prices. Traders don’t do it that way: they are compensating for the way the BS model fails to accommodate fat tails. QED. And by the way, Triana adds, there’s no such thing as implied volatility anyway, just supply and demand pushing prices around.

Well, OK to all that, so call implied volatility “demand premium” or something, and concede that Black-Scholes is a roundabout way to prices that can be reached more directly under other theories. So now what? Black-Scholes has become part of banking’s infrastructure. Do we strip out all the Black Scholes models and replace them with Thorp-Bachelier models? Will it make enough of a difference to options pricing or risk management to be worth it? Triana doesn’t try to determine the ROI. Instead (in the Finale) he asks whether Merton and Scholes should be stripped of their Economic prizes, and eventually concludes that instead the RiksBank prize should be given a silly name, so that people know it is a bit of a crock. It is an amazingly lightweight way to round off an otherwise enlightening discussion. It doesn’t come off like a joke fallen flat either: just cheesy.

While I’m carping, I’ll add a comment on the style. When I started reading the book, I kept stumbling over awesome quasi-English barbarisms, such as “qualification-inundated resumes”, “dangerously faulty mathematically charged steering”; also horrific neologisms like “analyticization”, “nonenthusiastically”, “impacting” (adj., I kid you not, and repeatedly), and “scientification aroma” (my favourite – I want some – either in a spray dispenser or roll-on form, not fussy). To my relief Triana (or his copy editor) gets more of a grip in later chapters and it’s not such a terrible read in the end. Doubtless the same relief is reflected in the generous verdicts of Taleb (“lucid”), Tett (“readable”) and Skypala (“a treat”). So, do not despair if you find yourself entangled in some pretty strange thickets of verbiage early in the piece: it does get better if you plough on.

Back to Chapters 8, 9 and 10 so that we can end on a note more favourable to the book (just skip the Finale).

Chapter 8 is a good one on the way models can be used as alibis or excuses by the lazy, reckless, or incompetent. Good reading for head traders, risk managers and regulators, I’d say; and buy-siders and pension fund trustees, come to that. Chapter 9 is a quick round up of how seductive the spurious certainty of mathematical models can be, largely illustrated by LTCM and by the confusion surrounding the meaning of the VIX.

In the end, the message of the book is that quantitative finance is a delusion, and that common sense is a better starting point for risk management. Accordingly Chapter 10 is a paean to Fat Tony, the street smart invention of Taleb in “The Black Swan”, and a call to reverse the quantification of finance. The negative leg of the case is argued persuasively. It is discomfiting to recognise just how little there was to quantitative finance.

On the positive side of Traiana’s recommendation: well, you are welcome to make your own mind up about the reserves of common sense to be found in the banking industry just now.