Economyths - ten ways economics gets it wrong Part 6

Emotional capital.

Of course, Iceland isn't the only country where women complain that men are responsible for all the problems; however, in this case, they actually went out and did something about it. The country has long been a world leader in measures of gender equality and female partic.i.p.ation in the work force, and when they realised what had happened to their money the women swung into action. Geir Haarde was replaced as prime minister by the world's first openly lesbian leader, Johanna Sigurardottir. Women took charge at two of the failed banks, and were given high-profile ministerial posts and positions in the Financial Supervisory Authority.

An example of the change in culture is the new investment fund set up by Audur Capital together with famous-Icelandic-singer Bjork, to focus on green start-ups. According to Halla Tomasdottir, the fund is guided by "core feminine values" that include risk awareness - "we will not invest in things we don't understand"; profit with principles - "a positive social and environmental impact"; and emotional capital - "we look at the people, at whether the corporate culture is an a.s.set or a liability."4 To anyone used to the hard-driving, high-octane, dog-eat-dog world of finance, this might all seem a bit soft and fuzzy and feathery - like Bjork in her famous swan costume, actually. It's hard to imagine Halla or her colleagues being invited to appear anytime soon on Fast Money - the manic, and very male, financial talk show on American cable TV.

So can we really say that the economy needs to become more feminine, less testosterone-driven? And - related question - is economic theory inherently biased towards a male perspective? To answer that delicate question, it's important that I first define some safe boundaries. I don't want to make the same mistake that Larry Summers made, when as president of Harvard University he implied that women didn't do as well at science and engineering because of innate biological differences.

So allow me to be perfectly clear: in the following discussion, I am not in any way implying that we men are incapable of doing economics, or should not be trusted with money, or suffer from some kind of innate biological flaw.

In fact, to be even safer, I will frame the problem as much as possible in terms of some very old concepts that predate our modern s.e.xual politics: yin and yang. Or in numerical terms, even and odd.

Odd son.

According to Greek mythology, the predictions at Delphi were originally due not to Apollo, but to the earth G.o.ddess Gaia. Her prophecies were sung out by a mythical figure referred to as Sybil. The site was guarded by Gaia's daughter, the serpent Python. However, the young G.o.d Apollo killed Python and took over the temple as his own. (His spokeswoman, the Pythia, was named after Python; as by implication was Pythagoras.) Archaeological excavations tell a similar story. From 1500 to 1100 BC, the area was occupied by Bronze Age Mycenean settlements that were devoted to Mother Earth. The new G.o.d Apollo arrived via invading societies, and began to dominate. Religious art was modified accordingly. As the mathematician Ralph Abraham put it: "the G.o.ddess submerged into the collective unconscious, while her statues underwent gender-change operations."5 Pythagoras, whose followers believed he was descended directly from Apollo, can be viewed as the human incarnation of this switch in power. The Pythagoreans compiled a list of ten opposing principles that divided phenomena into two groups: Limited Unlimited.

Odd Even.

One Plurality.

Right Left.

Male Female.

At rest In motion.

Straight Crooked.

Light Darkness.

Square Oblong.

Good Evil.

Limited and Unlimited were the two founding principles of the universe, and came together to form number. The former represented order, and was a.s.sociated with the odd numbers; the latter signified chaos and plurality, and was a.s.sociated with even numbers. The even numbers contained the number 2, which represented the initial division of the universe and was the symbol of discord and dissent.

It isn't known why the Pythagoreans chose this particular list of pairs, but there is an interesting correspondence between it and the Chinese concepts of yin and yang.6 According to the Chinese scheme, which is equally ancient, odd numbers are yang, even are yin. Light is yang, darkness yin. Male is yang, female yin. In fact, the sole striking difference between the Pythagorean list and the Chinese equivalent is that the Pythagoreans explicitly a.s.sociated one column with good and the other with evil. They believed that by a.s.sociating themselves with yang properties, they could move closer to the G.o.ds.

As we'll see, the Pythagorean list permeates traditional economics in much the same way that yin and yang permeate traditional Chinese medicine. However, instead of seeing yin and yang as two aspects of a unified whole, as in Chinese culture, economics is fundamentally dualistic and emphasises always the yang. Gender bias isn't some kind of accidental feature of economic theory; it's built right into its DNA.

Dressing as Apollo.

Ancient Greece in general wasn't a high-point for the feminist movement. The Pythagoreans did admit women into their cult, but they still a.s.sociated the female archetype with darkness and evil. Thinking about numbers, notes science writer Margaret Wertheim, was "an inherently masculine task. Mathematics was a.s.sociated with the G.o.ds, and with transcendence from the material world; women, by their nature, were supposedly rooted in this latter, baser realm."7 In Timaeus, Plato described women as originating from morally defective souls. Aristotle saw the male archetype as being active, female as pa.s.sive, and wrote in Politics that: "the male is by nature superior, and the female inferior ... the one rules, and the other is ruled." Women were capable of rational and deliberative thought, but it is "without authority."8 Unsurprisingly, they were barred from entering his Lyceum.

Scientific thought continued to be dominated by men and by a narrow kind of left-brained masculinity emphasising objectivity and detached a.n.a.lysis.9 Francis Bacon, who is credited with establis.h.i.+ng the empirical scientific method in the early 17th century, described the role of science in The Masculine Birth of Time as being to "conquer and subdue Nature" and "storm and occupy her castles and strongholds" - an activity clearly suited for "a blessed race of Heroes and Supermen."10 When the Royal Society was founded in 1660, Henry Oldenburg defined its aim as being to construct a "Masculine Philosophy" that would root out "the Woman in us."11 Things hadn't changed much in the late 19th century, when neocla.s.sical economics was in its gestation phase. To the Victorians, science was as male an activity as moustache-waxing and bare-knuckle boxing. Theories abounded that women were less rational or intelligent than men, due to biological factors such as brain size or genetics. Many university departments did not admit women until the early 20th century. Even in 1959, when C.P. Snow gave his famous lecture on The Two Cultures and the Scientific Revolution, he ignored the role of women, adding in a footnote that: "whatever we say, we don't in reality regard women as suitable for scientific careers."12 While science in general still tilts towards the yang - in the numerical scheme of the Pythagoreans, it tosses more odds than evens - economics is something of an extreme case. For example, as feminist theologian and psychologist Catherine Keller notes, there is a strong correspondence between the theory of the Newtonian atom and the male sense of self: "It is separate, impenetrable, and only extrinsically and accidentally related to the others it b.u.mps into in its void."13 This view of atoms has long been abandoned in physics, but it lives on in orthodox economics with the concept of rational economic man.

As the economist Julie A. Nelson observes, mainstream economics remains characterised by an emphasis on "detachment, mathematical reasoning, formality, and abstraction," which are culturally seen as masculine, as opposed to "methods a.s.sociated with connectedness, verbal reasoning, informality, and concrete detail, which are culturally considered feminine - and inferior."14 (When psychologist James Hillman defined the "archetypal premise in Apollo" as "detachment, dispa.s.sion, exclusive masculinity, clarity, formal beauty, farsighted aim and elitism," he could have been a.n.a.lysing an economist.15) The yang-like culture of economics - rather than anything to do with mathematical skills - may explain why female economists are so poorly represented at the higher echelons of academia; and why it took until 2009 for the n.o.bel Prize in economics to be awarded to a woman, Elinor Ostrom, who is a political scientist and not an economist.16 Actually, strictly speaking, no economist has won the n.o.bel Prize, or should be called a n.o.bel laureate. The Sveriges Riksbank Prize in Economic Sciences in Memory of Alfred n.o.bel, to use its full t.i.tle, was created in 1969, seven decades after n.o.bel's death, by a bank - the Bank of Sweden. Peter n.o.bel told author Hazel Henderson in 2004 that the bank had "infringed on the trademarked name of n.o.bel. Two thirds of the Bank's prizes in economics have gone to US economists of the Chicago School who create mathematical models to speculate in stock markets and options - the very opposite of the purposes of Alfred n.o.bel to improve the human condition."17 At least the name is easy to p.r.o.nounce, which is one reason it has caught on.

The story behind the word "laureate" is also interesting. In ancient Greece, the laurel tree was the symbol of Apollo. He is often depicted in artworks with laurels in his hair, and laurels were used as a wreath to honour heroes. Today the word has become a.s.sociated with the n.o.bel Prize, and by extension the Bank of Sweden version. So when economists crown their champions as laureates, they are dressing them up as Apollo.

The main problem with this male tilt and heroic posturing is that economic theory does more than study the economy - it also helps shape it, by endorsing and legitimising the "typical male behavior" that, although great fun for those involved, has the unfortunate side-effect of destabilising the economy not just of Iceland, but the entire world. To ill.u.s.trate this, we next present a detailed feminist critique of the 2007 subprime mortgage crisis.

Household misrule.

The word "economics" was originally derived from the Greek words oikos (household) and nomos (law), and means something like household rule. It is ironic, therefore, that economic theory lay behind the household misrule of the subprime mess.

On November 22, 1999, the ever-cheerful Texan Republican senator Phil Gramm made a particularly happy announcement. He had obtained Senate approval for a gold medal honouring Milton Friedman "for his enduring contributions to individual freedom and opportunity and for his steadfast support and efforts to champion free markets and capitalism. While many Americans will never know his name, the power of Milton Friedman's intellect has profoundly changed America and the world."18 That turned out to be no overstatement. Just ten days earlier, Gramm had advanced Friedman's (male) values in a different way - by pus.h.i.+ng through a controversial piece of legislation known as the Gramm-Leach-Bliley Act (all males). One of the few dissenters was Brooksley Born, the female chair of the Commodity Futures Trading Commission.

The Act's main function was to sc.r.a.p Depression-era regulations that separated investment banks from ordinary commercial banks and that also prevented banks from operating as insurance companies. The reasons for signing this "deregulatory bill," said Gramm, were that "government is not the answer ... We have learned that we promote economic growth and we promote stability by having compet.i.tion and freedom."19 Bill Clinton's treasury secretary at the time, the protean and ever-present Larry Summers, chimed in: "With this bill, the American financial system takes a major step forward towards the twenty-first century."

Gramm's next act, the following year, was the Commodity Futures Modernisation Act, which exempted futures and derivatives from any kind of regulation. "Taken together with the Gramm-Leach-Bliley Act," said Gramm, "the work of this Congress will be seen as a watershed, where we turned away from the outmoded, Depression-era approach to financial regulation and adopted a framework that will position our financial services industries to be world leaders into the new century."20 In fact the two bills just continued a trend towards greater deregulation that had existed since the post-war years. A clause on energy futures had helpfully been drafted by lawyers from the energy company Enron. Gramm's wife was on the board, and the company also donated $97,000 to his campaign expenses.

America therefore went into the new century stripped of all its Depression-era baggage, and ready to do some cutting-edge, innovative financial engineering. Running ahead of the pack was Enron, which enjoyed itself making vast amounts of money off the deregulated energy futures markets for about another year, before straying a little too close to the wires and incinerating itself.

Undeterred by the sight of the smoking wreckage and billions of dollars in collateral damage, financial engineers pressed ahead with other new products, including the collateralised debt obligation (CDO), and the credit default swap (CDS). Together, these would change the way that Americans think about home-owners.h.i.+p.

Financial alchemy.

In the old days, before the mortgage industry was modernised, and CDOs and CDSs were just a glimmer in a young geek's eye, the whole process of buying a house was incredibly painful. First of all, you had to come up with a sizeable deposit, around 20 per cent. Then you would have to physically go into your bank branch, and ask one of the human beings there for a loan. And to show you could pay the loan back, and ensure a successful response, you would need to provide evidence of some source of income. Like a job.

Obviously this was highly inefficient and went against the whole idea of economic freedom. It was equally bad for the bank. They would have to check your credentials, perhaps treat you like a person instead of a number etc., and at the end, a.s.suming it went through, they were stuck with a long-term, inflexible loan on their books. To them, your home wasn't a symbol of security and stability and family evenings spent sitting around the fire - it was a festering risk and a liability, and furthermore the maximum interest rates chargeable were capped by regulations.

So to help with these problems, financial inst.i.tutions went to work on the CDO, which had been around since the 1980s. A mortgage, like a bond, is a loan that is paid off through regular instalments, so it can be viewed as a financial instrument that gives a regular return in exchange for a certain risk of default. Banks can therefore trade mortgages the same way they trade other financial instruments. However, individual loans are relatively small and have a fixed payment schedule, and are therefore hard to trade, so the idea of the CDO was to bundle them all together into a large group; divide the group into tranches of varying quality; and then sell the tranches as separate instruments.

One advantage of this approach was that it got away from the whole messy problem of dealing with the details of people's lives. If a bank took owners.h.i.+p of an individual mortgage, they would feel compelled to find out something about the homeowner and their ability to repay the loan. But with a CDO, they were dealing with the average homeowner. Some of the individual loans would default, but the average loan would be fine. This meant they could relax their lending standards, at least for the right price. As one former loan officer testified: "If someone appeared uneducated, inarticulate, was a minority or was particularly old or young, I would try to include all the [additional costs] CitiFinancial offered."21 Furthermore, because the loans were divided into tranches, it was possible to achieve a kind of financial alchemy and turn even the most subprime of mortgages into a high-quality security. Suppose that a CDO bundles together a thousand mortgages. Even if, taken individually, the loans look a bit dodgy, the bank may estimate that, in all, under 10 per cent will default. No one knows at the start which will default and which won't, but that doesn't matter, because tranches are defined by pecking order. The upper-tranche investors get the first call on any income, and because the top 90 per cent of loans can be considered safe, their risk is low. Lower tranches are the first to suffer when loans go into default, but also pay a higher rate of interest as compensation, which appeals to investors such as hedge funds who are in search of yield. The same idea could be applied to any kind of loan, such as commercial property, or emerging market debt.

The CDOs therefore provided a way to take a bunch of individual loans and abstract from them new investment products with a tailored degree of risk. The process could be repeated: groups of CDOs were combined, sliced into tranches, and turned into CDO2s. Or even CDO3s. The upper tranches of lower-quality CDOs could thus be turned into financial gold. The mortgage industry became increasingly specialised, so a broker would sell mortgages, a mortgage bank would compile them together, an investment bank would transform them into an investment product, and another firm would be responsible for managing payment collection. This led to some cost efficiencies, but also had the effect of severing the connection - the bond - between mortgage supplier and homeowner, so their interests were no longer aligned.22

Give us some credit.

While CDOs made it easy to transform even the most dubious of mortgages into an easily-traded and valuable product, there were still a number of problems. The first was that banks were limited in the number of mortgages they could bundle together in this way, because of tedious banking regulations that capped the amount they could lend out. This was where Gramm's "deregulatory bill" came in. One of its effects was to permanently deregulate a then-obscure financial product known as a credit default swap (CDS).

The credit default swap was invented in the 1990s by a team at JPMorgan, and is basically a form of insurance. A bank or other inst.i.tution that owns a product such as a CDO can buy a CDS as insurance from a third party. This procedure removes the CDO risk from their balance sheets, because it is insured. They are then free to go out and create more loans.

The credit default swap is therefore similar to the insurance policy you might take out on your own home. If the house burns down, you get paid. However, there are a few key differences. One is that insurance companies are again limited by regulations that control how many policies they can write - they have to back up their liabilities with cash. This doesn't apply in the same way to credit default swaps, because they are not properly regulated. Also, you can take out insurance against your own home, but not against someone else's home. Reasons are that (a) it's weird, and (b) it might create a perverse incentive to burn the whole block down. With credit default swaps, on the other hand, multiple players can take out the same bets. This meant that the market was potentially unlimited.

While credit default swaps offered a way around balance-sheet regulations on CDOs, there still remained the problem of how to actually calculate what each of the tranches of the CDO was worth, so that it could get a credit rating and be sold at an appropriate price. To do that, the banks needed to come up with a number for the risk, i.e. the probability that many properties could go into default at the same time. And of course they needed to do it in a way that looked sufficiently technical and impressive, but was still workable.

Enter the mathematicians.

Heart-breaker.

During the 1990s, I worked for a multi-billion-dollar particle accelerator project, known as the Superconducting Super Collider, near Dallas, Texas. In 1995, the project was inconsiderately cancelled by the US government, so I and about 2,000 other people had to look for new employment. Some of the more active recruiters picking over the bones of the project were Wall Street firms looking for a.n.a.lysts. At the time, most of us thought that sounded well-paid but dull, and we couldn't quite see the connection with building particle accelerators (unless it had something to do with wasting billions of dollars).

Plenty of young physicists, engineers, and applied mathematicians did hear the siren call of cash, though, and went on to establish careers as quant.i.tative a.n.a.lysts, or "quants," and earn serious amounts of money. Their numbers roughly quadrupled between 1980 and 2005.23 But did they ever win true happiness? As one poor quant told the New York Times: "They sold their souls to the devil. I haven't met many quants who said they were in finance because they were in love with finance."24 The former trader Satyajit Das describes quants as "prisoners of Wall Street," embroiled in a "Faustian bargain." Most of the work involved routine tasks like computer programming, developing databases, and designing trading platforms, but a relatively small number of firms such as D.E. Shaw, Renaissance Technologies, and Citadel also put novel quant.i.tative techniques at the heart of their trading strategies.

One fresh recruit to the cause was a young mathematician called David X. Li. In 2000, Li published a paper that included a novel formula for valuing CDOs.25 His method was based on actuarial science - specifically, something called the broken heart syndrome. Actuaries had long known that when couples have lived together a long time, if one dies, the other has a high chance of also dying within a short time. A study showed that a partner's death increased a woman's chance of dying in the following year by a factor of two, and a man's chance of dying by a factor of six. In mathematical terms, their deaths are correlated. This had implications for the pricing of annuities.26 Li realised that company bonds and household mortgages also behave a bit like married couples, because if one dies, it increases the chances of others dying. If a large retailer goes bankrupt, for example, then many of its suppliers are also affected. If one house on the block goes into foreclosure, that slightly increases the chance that the rest of the neighbourhood will go into decline as well. Of course, the situation in the economy is more complex because the connections and correlations are far more complicated, but in principle the same kind of mathematics could be used. "Default is like the death of a company," Li later told the Wall Street Journal, "so we should model this the same way we model human life."27 Li's technique, called the Gaussian copula, provided a simple and elegant way of calculating the correlations between separate bonds or mortgages, based on historical data. There isn't much data on defaults available because it is a rare event. However, according to mainstream economic theory, the price of an instrument like a CDS is supposed to reflect the chance of a loan defaulting. By a.n.a.lysing how the market priced different securities, Li's formula could tease out the correlations between them.

As with most risk models, the Gaussian copula technique incorporated all the usual economic a.s.sumptions. One, as indicated by the name, is that it relied on the Gaussian or normal distribution, which as seen in Chapter 4 works well for games of dice, less well for financial markets. Another is that it a.s.sumed that market prices correctly reflect correlations. This is related to the efficient market idea that prices are right, and account for all relevant information. The formula also a.s.sumed that markets are stable, so that correlations do not change with time, and that the past is a good guide to the future. In particular, the model was calibrated on US housing data for a period that had never seen a nationwide housing decline. Defaults were rare and random occurrences with a low degree of correlation, and it was never foreseen that the entire market could suffer not just a few random heart attacks, but a ma.s.sive collective coronary.

Perhaps the biggest flaw in the model, though, was that it didn't account for an extraordinarily powerful force.

Itself.

The house race.

The whole point of objective, dualistic, "masculine" science is that you are supposed to a.s.sume a detached stance and distance yourself from the system under study. As Evelyn Fox Keller observes, this presupposes "an objective reality, split off from and having an existence totally independent of us as observers."28 With the economy, though, that's not easy, because you're involved. Li's formula didn't just model the credit markets, it transformed them - and in doing so, guaranteed its own failure.

In August 2004, the world's two main rating agencies, Moody's and Standard & Poor's, both adopted Li's formula as a metric for valuing CDOs (previously they had insisted on antiquated concepts like loan diversity). This effectively gave the instruments a gold stamp of approval, and removed any lingering uncertainty about their worth. The market for CDOs and CDSs promptly exploded. By the end of 2007, the value of the credit default swap market, in terms of amount insured, had reached roughly $60 trillion - about the same as world GDP. Credit default swaps evolved from a form of insurance into a tool for hedge funds to make sophisticated bets on just about anything - for example, the probability that another hedge fund or investment bank would go bust (say Bear Stearns or Lehman Brothers). Banks from all over the world joined in the game.

The net effect of all this insurance activity was to move risk off the banks' balance sheets, thus allowing them to lend even more money. This meant that credit became cheap, further fuelling the housing boom. Mortgage brokers enticed customers with cheap teaser rates that would later reset to a higher level. Because risk computations were based on historical data, the longer house prices kept rising in tandem, the lower seemed the risk. A positive feedback loop was therefore set up, in which rising prices lowered the calculated risk, which increased the supply of credit, which made loans more affordable, which drove further price increases. In reality, of course, the risk was climbing all the time, but the model couldn't see that because it didn't include the concept of a price bubble. The situation was supported by interest rates that had been set low after 9/11 and remained there, in part because China - slogan: bank of America - was lending money cheaply to the US government.

At the base of this vast international balloon of credit was the US housing market. As long as prices kept rising, everyone was making huge profits, at least on paper. In late 2006, when house prices dipped, the teaser rates started to expire, and the market began to turn, it was generally a.s.sumed that the global financial system would easily absorb any losses. As the IMF observed: "The dispersion of credit risk by banks to a broader and more diverse group of investors, rather than warehousing such risks on their balance sheets, has helped to make the banking and overall financial system more resilient."29 Instead, the whole highly-connected structure came cras.h.i.+ng down like a house of credit cards. The last one not holding the CDS was the loser. That would be companies like AIG. Or ultimately the taxpayers who bailed them out. Along with vulnerable economies around the world that were not directly involved but suffered as credit dried up. It wasn't just Iceland that turned out to be living next to a financial volcano.

So whose fault was this debacle? To blame US homeowners, or even predatory mortgage brokers, for the credit crunch is like blaming a horse for losing a race on which you've placed a huge wager: technically, it is their fault, but no one forced you to place the bet. Housing bubbles happen, but they don't usually take the whole world down with them when they pop.

Li's model also wasn't wholly to blame for the crisis. It just made the same mistakes as other conventional risk models, by a.s.suming stability and market efficiency and ignoring nonlinear reflexive effects. And again, no one forced traders to use it. As Li said: "The most dangerous part is when people believe everything coming out of it."30 The fact that the model was used in the way it was says as much about the traders, clients, and quants who used it, as it does about the formula itself.

In fact, many traders probably didn't believe it but used it anyway, either to impress gullible clients with its apparent sophistication or to offload risk. Part of the appeal of methods like VaR or the Gaussian copula is that they ignore extreme events and consistently underestimate risk, thus enabling traders to justify highly aggressive and speculative bets. Clients, on their part, want numerical risk estimates to a.s.suage their fear of the dark, and are rea.s.sured by scientific-looking formulae. Quants are happy to oblige because such formulae generate jobs. The model was therefore bound to be popular - but as discussed also in Chapter 4, whenever such a model becomes too widely adopted, it ends up influencing the market and therefore invalidating itself.31 The credit rating agencies, with the collusion of government regulators, clearly played a role in their failure to explore the limitations of the risk models. As Alan Greenspan testified to Congress in October 2008, the sector had for decades been dominated by a risk management paradigm created by n.o.bel Prize-winning economists. "The whole intellectual edifice, however, collapsed in the summer of last year."32 He added: "those of us who have looked to the self-interest of lending inst.i.tutions to protect shareholders' equity (myself especially) are in a state of shocked disbelief."

Gramm's Friedman-inspired deregulation of the markets also contributed. Bill Clinton admits that: "I very much wish now that I had demanded that we put derivatives under the jurisdiction of the Securities and Exchange Commission and that transparency rules had been observed ... That I think is a legitimate criticism of what we didn't do."33 Banks loved this deregulation because it allowed them to effectively lend out more money and make greater profits. If CDSs could only be used to insure debt that was actually held, as with usual types of insurance, then the market would never have grown so large.

The complexity and opaqueness of the products also meant that financial inst.i.tutions could charge more for their consultancy services. People who work in finance often make a point of saying that they deal with reality, because everything boils down to money in the end, but the truth is that financial products have become increasingly divorced from the real world. Someone selling derivatives contracts on equities or CDOs has no idea of the underlying businesses or properties, so can't pick up on danger signals, such as people on $18,000 a year moving into mansions. An economist or quant.i.tative a.n.a.lyst could calculate the theoretical risk of a CDO2 prospectus using a single formula; but to truly understand the underlying securities they would have had to read, according to one estimate, over a billion pages of doc.u.mentation.34 This complexity added another source of risk and uncertainty.

As with the Icelandic crisis that it helped to create, though, the problem may run even deeper. After all, you don't need to be a hardcore feminist to see that the subprime crisis exhibits some of the worst features of the yang economy:* Taking dreams of home-owners.h.i.+p, converting into abstract financial instruments, dismembering into tranches, and selling off to highest bidder - check * Reducing complex interdependencies to a single number - check * Valuing mathematical formulae over common sense - check * Figuring out ways to take maximum possible risks - check * Turning economy into giant casino ruled over by rapacious hedge funds - check * Breaking said economy - check In other words - and we have to admit this - the credit crunch really was a guy thing.

The power of yang.

Obviously many other factors were involved, and it would be terribly reductionist to blame the credit crunch solely on people with a tendency to grow facial hair. But to start with a basic observation, if there is one aspect of the crisis that everyone can agree with, it is that just about everybody involved at a senior level was a male.

Consider, for example, Goldman Sachs - one of the few Wall Street firms to have done well out of the crisis. They made money in three ways: by packaging up subprime mortgages as CDOs; by insuring them (or betting they would blow up) with credit default swaps; and then by absorbing $13 billion of federal funds when the insurer AIG collapsed. In fact, with the demise of compet.i.tors like Bear Stearns, Merrill Lynch, and Lehman Brothers, their position has never been stronger. Being far too big to fail, they also now enjoy an implicit government guarantee that they will never go bankrupt. In 2009, after showing "restraint" in response to political pressure, they paid their 31,700 employees around $16 billion in compensation and bonuses. That works out to about half a million each, though of course it's not shared equally.

Goldman Sachs was one of the first Wall Street firms to get into quant.i.tative finance, when in 1984 they hired Fischer Black - co-inventor of the Black-Scholes formula for valuing options - to explore mathematical methods for measuring risk. Even greater than their strength in mathematical models, however, is their extensive network of influential contacts. One of the more famous is former CEO Hank Paulson - treasury secretary under George W. Bush and the man responsible for administering the government bail-out funds. Perhaps the most yang-laden moment of the entire crisis was when exlinebacker Paulson (nickname at Dartmouth, "the hammer") appeared on TV to present to the American public a "non-reviewable" three-page demand for a $700 million blank cheque to bail out Wall Street firms, as if he were addressing an opponent that had just been defeated in battle. Towards the end of his term, according to Bloomberg, Paulson brought on board "a coterie of non-confirmed advisers from Goldman Sachs" on the basis that it was "necessary to quickly bring in top talent when the financial system was on the verge of collapse."35 Current Goldman alumni include William Dudley, president of the New York Federal Reserve; Robert Hormats, economic advisor to the secretary of state; Mark Patterson, chief of staff to the treasury secretary; and Gary Gensler, chairman of the Commodity Futures Trading Commission. It's no surprise that one of the firm's nicknames is Government Sachs.

The firm's secrecy rivals that of the Pythagoreans. Its head office in lower Manhattan doesn't even have a name plate. When the play-wright David Hare was researching his 2009 play The Power of Yes, he interviewed a number of bankers. As he told the Financial Times: "I would get all these people saying things like, 'I cannot talk about Goldman Sachs on the record.' And I would think to myself: 'What are you scared of? What would Goldman Sachs do?' I mean, I have talked with Palestinians who were living in a situation that was a matter of life and death. But Goldman Sachs?"36 While Goldman Sachs has many influential alumni, it's striking how few of them are women. The December 2008 issue of Bloomberg Markets magazine featured a fold-out page of 42 influential ex-partners, and eight honourable mentions. Out of all 50, only one of the ex-partners was female.37 This is not an unusual proportion - if anything Goldman appears to be relatively progressive in its efforts to include women. The stereotype of "testosterone-filled, wild-eyed traders" is accurate.38 To say that a macho culture predominates would not be an overstatement. David Hare's play has two women in a cast of twenty, but "that is probably about right. It's shocking how few women there are in finance." In his book How I Caused the Credit Crunch, Tetsuya Is.h.i.+kawa describes it as "the era of equality" when female colleagues occasionally go along to the lap-dancing clubs.39 One book by a well-known trader shows a picture of the author with sungla.s.ses, tuxedo, a gun, and a beautiful woman (also armed), looking like a poster for a James Bond film, with a caption explaining that: "In option trading you need to know your weapon inside out!"40 As ex-Goldmanite Jacki Zehner wrote: "Might this be one of many factors contributing to what is wrong with Wall Street leaders.h.i.+p today? Arguably at this moment of financial and economic crisis, after approximately $10 trillion of global wealth has vanished, women remain virtually absent at the decision-making tables that count ... In my 20 years of professional life I have seen very little to no progress for women in the financial services industry or in corporate America as a whole."41 According to Linda Tarr-Whelan, author of Women Lead the Way, women need to attain a critical ma.s.s of 30 per cent in order to have serious influence.42 It might help if pay were more balanced as well. An inquiry by the Equality and Human Rights Commission in the UK discovered a "shocking disparity" in the financial sector, with men earning bonuses five times larger than those of women.43 (Of course, such pay disparity is not just a property of the financial sector: the British Medical Foundation, for example, recently reported that male doctors earn 15,000 a year more than women, after correcting for factors other than gender.44) There is plenty of empirical evidence to suggest that groups of males tend to engage in high-risk behaviour of the sort that characterised the subprime crisis. One paper ent.i.tled "Testosterone and financial risk preferences" showed that testosterone levels are a predictor for risk-taking.45 Trader testosterone levels soar during booms and fall during crashes, which helps amplify price swings. A study by Chicago-based Hedge Fund Research found that, while women manage only about 3 per cent of total funds, these fell half as much during the crisis as those managed by men, and also out-performed them over the past decade.46 To balance your portfolio, you might want to consider having it managed by a company with women on its team. As Lu Hong and Scott E. Page wrote in The Journal of Economic Theory: "There seems to be a strong consensus that diverse groups perform better at problem solving."47 Note that these papers are not making generalisations about all men and all women, or even the average man and the average woman, who don't exist. Nor, I hope, are they saying that women are in some sense better than men. They are only making empirical observations about patterns in behaviour, which have complex causes and vary with time and context. Differences that are minor at the individual level can be amplified by group dynamics. One advantage of talking about abstract concepts like yin and yang is that we can recognise yin as being a.s.sociated with female and yang as being a.s.sociated with male, without confusing them with an individual person's gender. Margaret Thatcher and Ronald Reagan differed in X-chromosome status, but their Friedman-advised economic policies were both fairly yang (General Pinochet's Friedman-advised policies in Chile were even more yang).48 The yang quality of the financial industry is a.s.sociated with the fact that it is largely made up of men.

This may explain why, according to an international survey of 12,000 women performed by Boston Consulting Group, the financial sector is ranked worst at connecting with women customers. This is a missed opportunity, because women are playing an increasingly important role in the world economy. The trend is strongest in emerging economies such as China.49 If finance were to become less male-dominated, it might even have effects outside the industry. As Halla Tomasdottir from Iceland's Augur Capital observes: "If the inst.i.tutions are under the control of a single group - and now it is men - and they all think the same way, we are not going to make positive changes. For the first time in 100 years we have the chance to create a company, a society, a country, and hopefully a world that is more sustainable, more fair for men as well as women. If we are not going to do that now, then when will we?"50 Some hedge funds and investment banks may prefer to employ males exactly because they are more willing to take risks.51 That's fine - armies do the same. But the rest of society has the right to ring-fence these activities so they can't bring down the rest of the economy. One step, as discussed in Chapter 2, is to revisit some of that Depression-era legislation that separated investment activities from ordinary commercial banking functions.52 Another measure, which has often been discussed but has never caught on - banks describe it as unworkable, unsurprisingly - is a small global tax on financial transactions.53 The aim would be to reduce speculative activity and shrink the bloated and self-important financial sector to a point where it services the real economy, instead of dominating it.

Myths and consequences.

While the old-boy network, inst.i.tutional s.e.xism, and the under-representation of women in economics and finance are problems, however, they are not in themselves the main obstacle to a rebalancing of the economic system. Instead it is mainstream economic theory - the stuff they teach in universities. It is an entire view of the world, and pattern of thought, that reduces complexity to simple laws, and human motivations to cold calculations. It goes back to Julie Nelson's observation that economics values the "masculine" methods of "detachment, mathematical reasoning, formality, and abstraction" over the "feminine" methods a.s.sociated with "connectedness, verbal reasoning, informality, and concrete detail." Economics strives to be an impartial, detached, hard science like physics, but (in part for that reason) it condones and even glorifies a particular type of yang behaviour; and is blind to effects such as nonlinearity, fluidity, complex interdependence, and asymmetries in power. The subprime crisis, which was based on highly complex instruments such as CDOs that could be a.s.sessed only by relying on abstract mathematical tools, was a perfect example of this. As we will see in later chapters, the same emphasis on abstract theory over empirical reality is a major driver of everything from social inequality to the environmental crisis.