The Evolution of Money

by David Orrell

  Eugene Fama’s 1965 efficient market hypothesis assumed that markets are made up of “large numbers of rational profit-maximizers” who have access to perfect information.35 The theory claimed that market forces would drive the price of any security to its correct “intrinsic value.” Because changes were random, or driven by unpredictable news, it was impossible to beat the market: all the information was already priced in. The theory, which was essentially an updated version of Smith’s argument that market price equals intrinsic value, cemented the idea that markets are inherently rational, efficient, and optimal, with no role for the often-explosive dynamics of money and finance. While the Bubble Act had failed to outlaw bubbles, mainstream economists outlawed them in another way, by saying they had never existed. As Fama later told the New Yorker magazine, “I don’t even know what a bubble means.”36

  The efficient market hypothesis soon became the cornerstone of the risk-management and financial-engineering techniques used by banks, firms, and regulators. An example is the widely used value at risk (VaR) formula, which is used to estimate the worst-case loss that an institution could face on a given financial position. Risk can be calculated by taking historical data over a time window ranging from a few months to several years, depending on the case, and estimating the likelihood of a particular loss in the future. The model is based on the efficient market idea that prices are drawn to a stable equilibrium but are perturbed randomly by the actions of independent investors or by unexpected news. The risk of an asset can therefore be reduced to a single number based on its historical variation (the future is assumed to be statistically the same as the past). It can also be counterbalanced or “hedged” by financial derivatives that represent bets on future price changes.

  Risk can therefore in theory be engineered away: there is no need to worry about collapsing bubbles or the effect of a credit crunch or the activities of hedge funds or contagion from other markets or investor psychology or other obscure and unquantifiable risk factors or even the whole disconnect between number and fuzzy reality. In mainstream economics, the price (relative to other prices) always corresponds to the true value, and money, whose fluctuating and unpredictable force field permeates the economy, is just a distraction. As physicist J. Doyne Farmer and economist John Geanakoplos observed, “Economic theory says that there is very little to know about markets: An asset’s price is the best possible measure of its fundamental value, and the best predictor of future prices.”37 As we have noted, money objects are designed to have price and value be equivalent, and this equality is actively enforced by the issuing authority, but economists granted this property to everything else as well; rather than being special, money was just another tradable good.

  Model Risk

  The legitimacy of economics as a quantitative science was enhanced in 1969 when the Swedish central bank—in what is perhaps the ultimate example of the capture of economic thought by the finance industry—created the Sveriges Riksbank Prize in Economic Sciences in Memory of Alfred Nobel. It soon became known by the media, and economists, as the Nobel Prize in Economics. Winners would include Simon Kuznets, Kenneth Arrow, Gérard Debreu, Friedrich Hayek, Paul Samuelson, Milton Friedman, Robert Lucas, and Tom Sargent. In a classic exhibition of fence-sitting, the 2013 prize winners included both Eugene Fama, who invented the efficient market hypothesis, and behavioral economist Robert Shiller, who in 1984 famously called it “one of the most remarkable errors in the history of economic thought.”38

  Indeed, those risk models developed by economists, and given the Nobel gold medal stamp of approval, have turned out to be rather unreliable. The VaR model, for example, has failed on a regular basis, often to disastrous effect. In 2007, the CFO of Goldman Sachs complained that they “were seeing things that were 25-standard deviation moves, several days in a row.”39 A 25-standard deviation event is something that is not expected to happen even once in the duration of the universe—so if it happens several days in a row, you begin to realize there is a problem. The damage created by exploding financial derivatives the following year was enough to throw the world into a global depression.

  As Adair Turner noted in 2014, “Modern macroeconomics and finance theory failed to provide us with any forewarning of the 2008 financial crisis.”40 That was the case even at the actual time of the crisis—in 2008, according to a study by IMF economists, the consensus of forecasters was that not one of seventy-seven countries considered would be in recession the next year (forty-nine of them were).41 James Heckman of the University of Chicago said, “Everybody here was blindsided by the magnitude of what happened. But it wasn’t just here. The entire profession was blindsided.”42 Central bankers, who were heavily influenced by mainstream economic theory, were caught equally unawares.43 According to Alan Greenspan, the crisis was “almost universally unanticipated.”44 Even worse than this failure of prediction, though, is the fact that these theories and models helped cause the crisis in the first place by creating a false illusion of confidence. Modeling the economy as an inherently stable system had the perverse effect of making it unstable.

  This failure has been disputed by leading economists. Tom Sargent said in 2010 that such criticism displayed “woeful ignorance or intentional disregard for what much of modern macroeconomics is about and what it has accomplished. … It is just wrong to say that this financial crisis caught modern macroeconomists by surprise.”45 In contrast, Robert Lucas said that the reason the crisis was not predicted was because economic theory predicts that such events cannot be predicted.46 According to Fama, the efficient market hypothesis “did quite well in this episode,” and when asked whether the crisis would lead to any changes in economics, he replied, “I don’t see any.”47 But such protests and assertions sound like denial of the damaging role that economic theories played in the crisis. There is a growing awareness, at least among students and heterodox economists, that the basic concepts and assumptions of the mainstream theory are flawed—which is why, according to Cambridge University economists Ha-Joon Chang and Jonathan Aldred, their subject “is the only academic discipline in which a significant and increasing number of students are in an open revolt against the content of their degree courses.”48

  Traditional economics has long been dominated by a Pythagorean fascination with number. As Thomas Piketty wrote in his book Capital in the Twenty-First Century: “To put it bluntly, the discipline of economics has yet to get over its childish passion for mathematics and for purely theoretical and often highly ideological speculation, at the expense of historical research and collaboration with the other social sciences. … This obsession with mathematics is an easy way of acquiring the appearance of scientificity without having to answer the far more complex questions posed by the world we live in.”49 In particular, it means that money is treated as a passive placeholder, so objective number and subjective value are the same. At the heart of mainstream theory is an ideology—a sort of received consciousness—that takes money at face value, that with willed blindness doesn’t want to see what’s on the other side.

  Martin Wolf, chief economics commentator for the Financial Times, echoed Say when he observed at a 2013 conference on the teaching of economics that students are left thinking we operate in a “barter system where money acts as a veil”—as if economics exists in a Platonic world of Forms, where there is no need to dirty your hands with cash.50 This lack of interest in money might seem strange—isn’t that what economics is supposed to be about?—but it is perfectly expressed in the origin myth from economics (chapter 1), in which money is seen as just a way of facilitating barter, and by the desire to collapse the dual nature of money (chapter 2) to nothing more than an inert medium of exchange. It is particularly ironic, given that economic principles such as rationality and optimizing behavior only make sense when transactions can be reduced to number, which of course is the job of money. Mainstream economists are fond of describing people who propose alternative monetary schemes as “cranks,” but with their sanit
ized ideas about the origins and nature of money, coupled with Victorian notions of a social pseudo-physics based on the energy-like idea of utility and dreams of pristine rationality and equilibrium, they might want to look in the mirror (the main difference is that they write the textbooks).

  According to Chang and Aldred, “Part of the self-image of most academic economists today is that the core of the subject is an established, settled science.” However, while mainstream assumptions such as stability and rationality may have appealed to the subject’s Victorian founders, they are out of step with recent developments in science which show money and the economy in a very different light.

  It’s Alive

  In the preface to his Principles of Economics, the neoclassical economist Alfred Marshall wrote that “the Mecca of the economist lies in economic biology.” However, he did not pursue the metaphor very far. He continued, “Biological conceptions are more complex than those of mechanics; a volume on Foundations must therefore give a relatively large place to mechanical analogies, and frequent use is made of the term equilibrium which suggests something of a static analogy.”51

  Instead, economists built up a model of the economy in which people or firms acted like inert atoms, deprived of any life or individuality or power relationships or connection with one another. While these assumptions may have seemed reasonable at the time, as mathematical simplifications, they have found less use in life sciences such as biology and ecology. For one thing, living systems show so-called emergent behavior, which means that the macro-behavior cannot be predicted from a knowledge of individuals. An ant colony is not simply a larger version of a single ant, because ants do not behave as atomistic individuals but are embedded in a complex social organization, are in constant communication with one another, develop specialized roles, experience group dynamics, and so on. The same can be said, on a grander scale, of the human economy. When people are seen as living beings that are part of larger groups (families, communities, nations, etc.), it makes no sense to describe their behavior in terms of static utility functions, because their preferences will change with time and context.

  Nor are living systems homogeneous. As Charles Darwin knew, diversity, along with competition, is one of the drivers of evolution. If everything were the same, “survival of the fittest” would result in a draw and nothing would change. The same dynamic explains why markets are often dominated by a small number of successful firms, instead of a large number of essentially indistinguishable firms as assumed by neoclassical economics. The result of this evolutionary process is not equilibrium, but a state of dynamic change and continuous adaptation. And while competition plays an important role, so does cooperation. Diversity means that people and firms can often do more when they function as part of a team than they can individually. Ecological niches appear as a result. In this world, money is not an inert placeholder or a passive lump of metal, but a vital, active medium that circulates through the economy, changing it as it goes (box 7.2).

  Box 7.2

  Small Money

  While money is a human invention, the idea of a medium of exchange is not. A biological version is the molecule known as adenosine triphospate, or ATP, which transports energy within cells. Food energy is stored transiently in ATP and then released for such tasks as the fabrication of larger molecules such as proteins or DNA. By donating energy to certain chemical reactions, ATP makes them orders of magnitude faster. It also plays a role as a kind of signaling device, for example, for opening or closing channels in the cell wall. After use, in which it is converted to a different molecule, ATP is recycled for future use. A person’s body only contains around 50 grams of ATP at any one time, but because of the recycling we go through nearly our own weight in the stuff every day.*

  The ATP molecule has been selected by evolution as a kind of molecular currency because it has various properties, including the ability to store a large amount of energy through the arrangement of its chemical bonds; but nature could have chosen some other molecule. The system is an example of what biologists call a bow-tie network, in which multiple inputs (one side of the bow) feed into a central control unit (the knot) to produce multiple outputs (the other side of the bow). Here the knot is ATP: many components can be used as inputs to make ATP, and all cells use ATP to transport energy. The advantage of this structure is that it gives great flexibility, while allowing for a high degree of control.

  In economic exchange, money plays a similar role. In the Middle Ages, the bankers who arranged bills of exchange acted as the central control node in the network. With Bitcoin, as with the Internet, the central control comes from the operating protocol. With fiat currencies, system control of money production is dispersed to private banks rather than being centralized.

  What distinguishes money from natural systems such as ATP, though, is that money is based on number, which gives it special properties. ATP is not completely stable (it has a life span), does not multiply exponentially forever (cells can’t get rich by hoarding it), and does not have a number stamped on its side. Money is not a simple extension of natural processes, but maybe it can be redesigned to behave more like one.

  *Reginald H. Garrett and Charles M. Grisham, Biochemistry (Fort Worth, Tex.: Saunders, 1995).

  Prices can never perfectly reflect value, because value is a fuzzy quality that changes with time and context and cannot be reduced to number. It does not come down to energy-like measures of labor (Smith) or utility (Jevons). It is not objective (classical economics) or subjective (neoclassical economics), but a mix of the two. It is largely a product of culture, which means that it can change—sometimes very quickly. We do not value gold so much for its beauty, but because we are told it is valuable. If we collectively decide that unexploited forests and oceans are extremely valuable, say, for their role in maintaining the biosphere, even if we don’t perform work on them or exploit them or even see them, then they will be valuable—but that doesn’t mean their price will go up by just the right amount in some imaginary market. There is certainly feedback between prices and value—if something is expensive, then we tend to value it for that reason, and vice versa—but the two can never be equated, any more than the two sides of a coin can merge to one. The process by which market forces such as supply and demand determine a price is similar to the delicate process of measuring a quantum system—the measurement changes the system, is susceptible to distortion, and gives only an approximate description of the state. And market dynamics do not resemble the gentle, linear dynamics of a guiding hand, where everything is just right, but rather the nonlinear dynamics of a turbulent system, with states of apparent calm interrupted by moments of chaos.

  A useful comparison is with the behavior of water, whose complex thermal, biological, mechanical, and chemical properties are essential for life (our bodies are about 60 percent water). At a molecular level, water is just an oxygen atom connected to two hydrogen atoms. However the molecule’s electrical polarization means that it is in a constant, intricate, quantum mechanical dance with its neighbors, resulting in emergent behavior which could never be deduced from a knowledge of the molecular properties alone. Ditto for our human currency.

  All of this complexity and ambiguity poses something of a problem to conventional models, because it is no longer possible to make the simplifying assumptions of the Newtonian, mechanistic approach. Just as the dualistic, quantum-like nature of money mediates between exact number and fuzzy value, the quantitative and the qualitative, so economists need tools that mediate between mathematics and the living economy. In recent decades, a number of mathematical techniques such as nonlinear dynamics and complexity theory have become increasingly popular in the life sciences and are now also providing new ways to understand and visualize the flows of money that course through the economy.

  The Uncertainty Principle

  Underlying the Newtonian gold standard system was the idea that money, and through it the entire economy, could be made stable by linking it to g
old—as if the establishment of a numerical link between a currency and a physical mass would in itself turn the human economy into a mechanistic system, understandable by physical laws. The belief that markets, including currency markets, are fundamentally stable is also axiomatic to neoclassical economics. It therefore came as a major psychological blow to all concerned in 1971 when the world currency system suddenly went chaotic.

  The assumption of stability is reminiscent of Aristotelian physics, which asserted that moving objects slowed down and stopped because they were drawn to a state of equilibrium. However, living systems from the earth’s biosphere to the human economy are better viewed as operating in a state that is far from equilibrium, in the sense that the contents are constantly being churned around. Equilibrium, where it exists, is an emergent property that depends for its maintenance on the presence of self-regulating feedback loops. The key insight of James Lovelock’s Gaia theory, for example, was that what makes the earth discernibly alive, compared with other planets, is that its atmosphere is far from chemical equilibrium, but feedback loops maintain the temperature and so on in a zone suitable for life.

  In general, positive feedback amplifies perturbations, while negative feedback reduces them. Biological systems are characterized by complex networks of interacting feedback loops, which face off against one another in a kind of tug-of-war, with positive feedback allowing for rapid reaction, and negative feedback providing control. Periods of apparent stability represent a temporary truce between these opposing forces. The economy is similarly full of feedback loops. Economists have traditionally focused on the stabilizing role of negative feedback—an example is Smith’s invisible hand, which is supposed to drive prices to an equilibrium level—but positive feedback is equally important.