Economyths - ten ways economics gets it wrong Part 1

Economyths : ten ways economics gets it wrong.

David Orrell.

For Beatriz.

David Orrell is an applied mathematician and author of popular science books. He studied mathematics at the University of Alberta, and obtained his doctorate from Oxford University on the prediction of nonlinear systems. His work in applied mathematics and complex systems research has since led him to diverse areas such as weather forecasting, economics, and cancer biology. His work has been featured in the New Scientist, World Finance and the Financial Times, and on BBC Radio. He lives and works in Oxford.

INTRODUCTION.

Every dogma must have its day.

H.G. Wells (1866-1946).

The year 2008 was going to be a prosperous one for the financial markets, according to forecasters polled by Bloomberg.com at the start of the year. None foresaw a loss, and the average prediction was for a gain of 11 per cent. They were blissfully unaware that one of history's biggest financial earthquakes was already taking shape beneath their feet. By year-end the S&P 500 index was down 38 per cent, $29 trillion had slipped through the cracks appearing in global markets, and many of the foundations of the world economy lay in ruins.1 The credit crunch had a number of phases, but perhaps the pivotal event was the collapse of the financial services firm Lehman Brothers in September 2008. With over $600 billion in a.s.sets, this was the largest bankruptcy in US corporate history. Lehman was also one of the key nodes in the financial network, and its extinction sent the crisis into a new and extremely dangerous phase. Many feared that the entire global financial system would break down completely. That didn't happen, and markets eventually recovered from their near-death experience, but the aftershocks of those events are still being felt around the world.

The failure of economists to predict the credit crunch or the ensuing world recession was not atypical. As shown later, financial forecasts have an extremely poor track record of success, even when based on sophisticated mathematical models. This time, though, not only did the models fail to predict the crash - they actually helped cause it.

In the years preceding the crash, financiers had become increasingly reliant on quant.i.tative mathematical models to make their decisions. Even if models couldn't predict what exactly would happen in the future, they were supposed to be able to calculate risk. For example, in order to figure out how much risk a package of loans incurred, they needed only to make a statistical calculation using a simple formula or risk model, based on standard economic theory. This appeared to work well - so well that quant.i.tative a.n.a.lysts began to use the models to take bigger and more sophisticated bets.

Even before the crisis was in full swing, though, there were signs that the models were failing to capture the true risks of the economy. On August 11, 2007, a year before Lehman Brothers went bust, some unexpected market turbulence brought on by a decline in US house prices led one of their employees to remark that "Events that models predicted would happen only once in 10,000 years happened every day for three days."2 While that sounds most unusual, the chief financial officer at Goldman Sachs went even further: "We were seeing things that were 25-standard deviation moves, several days in a row."3 To unpack that statement, a 25-standard deviation event is something that is not expected to happen even once in the duration of the universe - let alone each day of a week.

You don't need to be a mathematician to see that the models that lay at the core of the world financial system had something seriously wrong with them. But how could so many highly-paid experts have turned out to be completely mistaken about the workings of the economy? As Queen Elizabeth said on a visit to the London School of Economics: "Why did no one see it coming?"4

Storm warnings.

Actually, not everyone was as surprised by the crisis as were the quant.i.tative a.n.a.lysts and their mathematical models. As early as 2003, the investor Warren Buffett described the complex products known as derivatives, which played a key role in the credit crunch, as "financial weapons of ma.s.s destruction." The same year, well before the collapse of Lehman sent a tsunami of destruction through the banking system, the network scientist Albert-Laszlo Barabasi warned of the potential of "cascading failures" in the economy.5 Even central bankers were heard to muse that the financial system might be less stable than it seemed. In January 2007 Jean-Claude Trichet, the European Central Bank president, observed that "We are currently seeing elements in global financial markets which are not necessarily stable ... we don't know fully where the risks are located." Some, such as author Na.s.sim Taleb and economist Nouriel Roubini, were more specific in their warnings; however, their voices were ignored or even ridiculed in the rush for profits that characterised the boom years.6 As with preceding crashes, the causes of the credit crunch have been much a.n.a.lysed and debated. The obvious lightning rod for criticism was of course the bankers themselves, who were earning fabulous salaries, and even more fabulous bonuses, for taking risks that turned out to have cataclysmic consequences for the real economy when the bets went wrong. Other culprits were the regulators, who failed to keep up with the pace of innovation in financial products; the American homeowners who took out subprime loans they could never afford to repay; the central banks, who (Trichet's comments aside) often seemed to be in denial about the extent of the problem; and the economists who designed the flawed mathematical models in the first place.

This still leaves the question of how so many people in the financial industry could have been misled about the risks they were running and unaware of the dangers. The reason, I believe, is that the fundamental a.s.sumptions that form the basis of economic theory are flawed. This means that not just the mathematical models, but the actual mental models that economists have of the economy are completely wrong.

This problem goes well beyond the calculation of financial risk. The main problem with our economic system is not that it is hard to predict, but that, despite its enormous productivity and creativity, it appears to be in a state of ill health. The economy is unfair, unstable, and unsustainable. But economic theory has no way of dealing with these issues either.

The economy is unfair. Economic theory is supposed to be about optimising the allocation of resources. However, the reality is that the rich really do get richer. In 2009 one hedge fund manager earned over $2 billion, while over a billion people earned less than $1 a day.7 That's a strange way to allocate resources.

The economy is unstable. According to theory, the "invisible hand" should keep a.s.set prices at a stable level. But in reality, a.s.sets including oil, gold, and hard currencies are subject to enormous gyrations. In late 2007 the price of oil surged to over $140 a barrel, then plunged to under $40, all in the s.p.a.ce of a few months. Oil is often called the lifeblood of the economy, but our own blood supply is much better regulated. For a while it seemed the economy was having a cardiac event.

The economy is unsustainable. According to theory, the economy can grow forever without encountering limits. The reality is that we are b.u.mping up against hard constraints due to things like over-crowding, climate change, and environmental degradation. As environmentalists point out, never-ending growth is the philosophy of a cancer cell.

Together, these problems far exceed the importance of an event like the credit crunch. The debt that the global economy is building up with the environment, or the debt of rich countries to poor countries, is of much greater concern than the debt of banks to governments or shareholders. Indeed, it may turn out that this crisis was a blessing in disguise, if it provides the impetus for us to rethink our approach to money.

Just as economic theory fails to address the shortcomings of the economy, it also fails to properly account for its good qualities, of which there are many, including enormous dynamism and productivity. A model that emphasises stability isn't very good at capturing the market's creativity - as any artist or student of rock history will know, these two qualities rarely go hand in hand. So why do we persist with an economic theory that is so obviously unfit for purpose?

Bad coin.

Economics is a mathematical representation of human behaviour, and like any mathematical model it is based on certain a.s.sumptions. I will argue, however, that in the case of economics the a.s.sumptions are so completely out of touch with reality that the result is a highly misleading caricature. The theory is less a science than an ideology. The reason why so many people are conned into thinking the a.s.sumptions reasonable is that they are based on ideas from areas like physics or engineering that are part of our 2,500-year scientific heritage dating back to the ancient Greeks. Superficially they have the look and feel of real science, but they are counterfeit coin.

Each chapter of this book begins with one of the misconceptions behind orthodox economic theory. It then goes back into the history to see where the idea came from, explains how it affects our everyday life, finds out why it persists despite evidence to the contrary, and proposes how we can change or replace it. The specific misconceptions are:* The economy can be described by economic laws * The economy is made up of independent individuals.

* The economy is stable.

* Economic risk can be easily managed using statistics.

* The economy is rational and efficient.

* The economy is gender-neutral.

* The economy is fair.

* Economic growth can continue forever.

* Economic growth will make us happy.

* Economic growth is always good.

These ideas form the basis of orthodox economic theory and affect decision-making at the individual, corporate, and societal level; but the book will show they are mistaken and present alternatives. We will find out how the economy is the emergent result of complex processes that defy reduction; how the value of your home or pension is affected by unpredictable economic storms; why the economy is not rational or fair; and why economic growth is not automatically desirable, either for our own wellbeing or that of the planet.

Before proceeding, I should address a few concerns. The first is that, faced with the above list, most economists would protest that it is an over-simplified straw-man, and that economics is far more sophisticated than that. However, what counts is less what economists say - they are skilled at deflecting criticism, and have plenty of practice - than what kinds of calculations they actually perform. No one thinks that markets are perfectly stable, or that investors are perfectly rational, or that markets are fair and everyone has access to the same information - but key components of economic theory such as the efficient market hypothesis are explicitly based on exactly these a.s.sumptions. Peer under the hood of the risk models used by banks, or the models used to allocate your pension funds or determine government policy, and you will find the same a.s.sumptions there, with at best small modifications. As we'll see, a number of so-called heterodox economists have been arguing against these a.s.sumptions for years, but until now their voices have carried little weight. We will go beyond a critique of these ideas, to explore where they came from in the first place and how they can be replaced. (I am also told that many economists do not really believe the mainstream theory, but play along in order to get publications and tenure - in which case they should enjoy this book.) Some readers might find it hard to believe that mainstream economics is as flat-out wrong as I describe it here. After all, the great strength of science is that it is supposed to be self-correcting. If a theory is flawed, then it will be replaced by a better one. Even Newton's laws of motion had to be modified with the development of quantum theory. A problem occurs, however, when no alternative is demonstrably better at making predictions, which is traditionally the acid test for a new theory. The new approaches discussed here do not amount to a single, unified replacement for orthodox theory, and nor do they claim to be much better at predicting the economy - in fact they openly acknowledge the uncertainty inherent in complex systems. That is why orthodox theory has struggled on for as long as it has, although things are beginning to change. As a Nature article ent.i.tled "Economics Needs a Scientific Revolution" put it: "We need to break away from cla.s.sical economics and develop completely different tools."8 Another possible concern is that this book is written from the perspective of an applied mathematician, whose day job is in the area of systems biology (don't tell my boss, but I never studied biology either). Some readers will prefer to get their economic a.n.a.lysis from economists, but I would argue that having a training in economics is actually a liability (which some particularly gifted people are capable of overcoming). If, as I believe, economics is an ideology, then being trained in it is effectively a way of closing your mind. Many of the new ideas that are revitalising economics come from diverse areas such as network theory, complexity, psychology, and indeed systems biology, which are far outside the standard economics curriculum. When a field is in as poor a state as economics, being an outsider is a distinct advantage because it allows you to a.n.a.lyse the problems without having to justify previous theories that you were exposed to early in your career and feel compelled to defend.

Finally, readers of my previous book on economics, The Other Side of the Coin, may note that I am discussing many of the same points in this book. I'm guilty, it's true-I did write that the economy is dangerously unstable and unbalanced, and that risk models are unreliable, before the crash. This book represents a complete updating and recrafting of those ideas in the face of what we have learnt about the economy in the last couple of years.

Enough justification. Economics, as already stated, is a mathematical model of human behaviour. The next chapter offers a brief tour through the history of such models, and asks whether there is any such thing as an economic law.

CHAPTER 1.

THE ANARCHIC ECONOMY.

Above, far above the prejudices and pa.s.sions of men soar the laws of nature. Eternal and immutable, they are the expression of the creative power; they represent what is, what must be, what otherwise could not be. Man can come to understand them: he is incapable of changing them.

Vilfredo Pareto (1897).

Spread the truth - the laws of economics are like the laws of engineering. One set of laws works everywhere.

Lawrence Summers (1991).

Economics gains its credibility from its a.s.sociation with hard sciences like physics and mathematics. But is it really possible to describe the economy in terms of mathematical laws, as economists including President Obama's economic advisor Lawrence Summers claim? Isaac Newton didn't think so. As he noted in 1721, after losing most of his fortune in the collapse of the South Sea bubble: "I can calculate the motions of heavenly bodies, but not the madness of people."

To see whether the economy is law-bound or anarchic, bear with me first for a little ancient history. It turns out that many of the ideas that form the basis of modern economics have roots that stretch back to the beginning of recorded time. That's one reason why they are proving so hard to dislodge.

The first economic forecaster, in the Western tradition, was probably the oracle at Delphi in ancient Greece. The most successful forecasting operation of all time, it lasted for almost a thousand years, beginning in the 8th century BC. The predictions were made by a woman, known as the Pythia, who was chosen from the local population as a channel for the G.o.d Apollo. Her predictions were often vague or even two-sided and therefore hard to falsify, which perhaps explains how the oracle managed to persist for such a long time (rather like Alan Greenspan).

Our tradition of numerical prediction can be said to have begun with Pythagoras. He was named after the Pythia, who in one of her more famous moments of insight had predicted his birth. (She told a gem-engraver, who was actually looking for business advice, that his wife would give birth to a boy "unsurpa.s.sed in beauty and wisdom." This was a surprise, especially because no one, including the wife, knew she was pregnant.) As a young man, Pythagoras travelled the world, learning from sages and mystics, before settling in Crotona, southern Italy, where he set up what amounted to a pseudo-religious cult that wors.h.i.+pped number. His followers believed that he was a demi-G.o.d descended directly from Apollo, with superhuman powers such as the ability to dart into the future. Joining his inner circle required great commitment: candidates had to give up all material possessions, become vegetarian ascetics, and study under a vow of silence for five years.

The Pythagoreans believed that number was the basis for the structure of the universe, and gave each number a special, almost magical significance. They are credited with a number of mathematical discoveries, including the famous theorem about right-angled triangles and the square of the hypotenuse, which we are all exposed to at school. However, their major insight, which backed up their idea that number underlay the structure of the universe, was actually about music.

If you pluck the string of a guitar, then fret it exactly halfway up and pluck it again, the two notes will differ by an octave. The Pythagoreans discovered that the notes that harmonise well together are all related by the same kind of simple mathematical ratio. This was an astonis.h.i.+ng insight, because if music, which was considered the most expressive and mysterious of art forms, was governed by simple mathematical laws, then it followed that all kinds of other things were also governed by number. As John Burnet wrote in Early Greek Philosophy: "It is not too much to say that Greek philosophy was henceforward to be dominated by the notion of the perfectly tuned string."1 The Pythagoreans believed that the entire cosmos (a word coined by Pythagoras) produced a kind of tune, the music of the spheres, which could be heard by Pythagoras but not by ordinary mortals. And their interest in number was not purely theoretical or spiritual. They developed techniques for numerical prediction, which remained secret to the uninitiated, and it is also believed that Pythagoras was involved with the design and production of the first coins to appear in his area. Money is a way of a.s.signing numbers to things, so it obviously fit with the Pythagorean philosophy that "number is all."

Rational mechanics.

If the cosmos was based on number, then it could be predicted using mathematics. The ancient Greeks developed highly complex models that could simulate quite accurately the motion of the stars, moon, and planets across the sky. They a.s.sumed that the heavenly bodies moved in circles, which were considered to be the most perfect and symmetrical of forms; and also that the circles were centred on the earth. Making this work required some fancy mathematics - it led to the invention of trigonometry - and a lot of circles. The Aristotelian version, for example, incorporated some 55 nested spheres. The final model by Ptolemy used epicycles, so that planets would go around a small circle that in turn was circling the earth.

The main application of these models was astrology. For centuries astronomy and astrology were seen as two branches of the same science. In order for astrologers to make predictions, they needed to know the positions of the celestial bodies at different times, which could be determined by consulting the model. The Ptolemaic model was so successful in this respect that it was adopted by the church, and remained almost unquestioned until the Renaissance.

Cla.s.sical astronomy was finally overturned when Isaac Newton combined Kepler's theory of planetary motion with Galileo's study of the motion of falling objects, to derive his three laws of motion and the law of gravity. Newton's insight that the force that made an apple fall to the ground, and the force that propelled the moon around the earth, were one and the same thing, was as remarkable as the Pythagorean insight that music is governed by number. In fact Newton was a great Pythagorean, and believed Pythagoras knew the law of gravity but had kept it secret.

Newton held that matter was made up of "solid, ma.s.sy, hard, impenetrable, movable particles," and his laws of motion described what he called a "rational mechanics" that governed their behaviour. It followed, then, that the motion of anything, from a cannonball to a ray of light, could be predicted using mechanics. His work therefore served as a blueprint for numerical prediction - reduce a system to its fundamental components, discover the physical laws that rule them, express as mathematical equations, and solve. Scientists from all fields, from electromagnetism to chemistry to geology, immediately adopted the Newtonian approach, to enormously powerful effect. You can hear the whisper coming from the Pythagoreans: "Spread the truth - one set of laws works everywhere."

Rational economics.

Among those to hear the whisper, if somewhat belatedly, were the new group of people calling themselves economists in the late 19th century. If Newtonian mechanics was proving so successful in other areas like physics and engineering, maybe it could also be applied to the flow of money.

The theory they developed is known as neocla.s.sical economics. Today it still forms the basis of orthodox theory, and makes up the core curriculum taught to future economists and business leaders in universities and business schools around the world.2 As a set of ideas, it might be the most powerful in modern history.

Neocla.s.sical economics is based on an explicit comparison with Newtonian physics. Just as Newton believed that matter is made up of minute particles that b.u.mp off one another but are otherwise unchanged, so neocla.s.sical theory a.s.sumes that the economy is made up of unconnected individuals who interact by exchanging goods and services and money but are otherwise unchanged. Their behaviour can be predicted using economic laws, which are as omnipresent as the laws that govern the cosmos.

To calculate the motions of the economy, one must determine the forces that make it move around. The neocla.s.sical economists based their mechanics on the idea of utility, which the philosopher Jeremy Bentham described in his "hedonic calculus" as the sum of pleasure minus pain. For example, if an apple gives you three units of pleasure, and paying for it gives you only two units of pain, then purchasing the apple will leave you one utility unit (sometimes called a util) in profit.

Leaving aside for a moment what units of measurement a util is expressed in, an obvious problem is that different people will a.s.sign different utility values to objects such as apples. The neocla.s.sical economists got around this by arguing that all that counted was the average utility. It was then possible to use utility theory to derive economic laws. As William Stanley Jevons put it in his 1871 book Theory of Political Economy, these laws were to be considered "as sure and demonstrative as that of kinematics or statics, nay, almost as self-evident as are the elements of Euclid, when the real meaning of the formulae is fully seized."

Imaginary lines.

If economics has an equivalent of Newton's law of gravity, it is the law of supply and demand. The law is ill.u.s.trated in Figure 1, which is a version of a graph first published in an 1870 essay by Fleeming Jenkin. It has since become the most famous figure in economics, and is taught at every undergraduate economics cla.s.s.

Figure 1. The law of supply and demand. The solid line shows supply, which increases with price. The dashed line shows demand, which decreases with price. The intersection of the two lines represents the point where supply and demand are in balance.

The figure shows two curving lines, which describe how price is related to supply and demand. When price is low, supply is low as well, because producers have little incentive to enter the market; but when price is high, supply also increases (solid line). Conversely, demand is lower at high prices because fewer consumers are willing to pay that much (dashed line).

The point where the two lines cross gives the unique price at which supply and demand are in perfect balance. Neocla.s.sical economists claimed that in a compet.i.tive market prices would be driven to this point, which is optimal in the sense that there is no under- or oversupply, so resources are optimally allocated. Furthermore, the price would represent a stable equilibrium. The market was therefore a machine for optimising utility.

For example, suppose that the average price for a house is 100,000 (currency units of your choice) when the market is at equilibrium. If sellers grew greedy and the price lifted temporarily to 110,000, then suppliers would respond by building more homes, and consumers by buying fewer. The net effect would be to pull prices down to their resting place, as sure as the force of gravity. Conversely, if prices fell too low, then supply would drop, demand would increase, and prices would bob back up again.

However, if demand were to increase for some structural reason, such as population growth, then the entire demand curve in Figure 1 would s.h.i.+ft up, so the equilibrium price would be higher. If supply permanently increased, say because new land opened for development, then the equilibrium price would s.h.i.+ft down along with the supply curve.

This is for just one good, and the situation becomes considerably more complicated when multiple goods and services are included, now and in the future, since consumers then have a choice on where and when to spend their money. One of the supposed triumphs of neocla.s.sical economics in the 1960s was to mathematically prove that the entire economy will still be driven to a stable and optimal equilibrium, again subject to certain a.s.sumptions. This was seen as mathematical proof of Adam Smith's "invisible hand," which maintains prices at their "natural" level, and formed the basis of General Equilibrium Models that are used to simulate the economy today.

The visibly shaking hand.

We are all familiar and comfortable with the law of supply and demand, and it is often used to explain why prices are what they are. A strange thing, though: historical data for a.s.sets like housing just doesn't look that stable or optimal. In fact it seems the invisible hand has a bad case of the shakes.

As an ill.u.s.tration, the top panel in Figure 2 shows a plot of UK house prices over about three decades. The numbers have been corrected for inflation. It shows the large ramp up in house prices from 1996 until 2009. Similar behaviour was seen in other G8 economies.

It appears from this figure that houses were much more affordable before 1985 than after 2000. However, the figure is a little misleading because affordability is a function not just of real house prices but also of mortgage rates, which were about twice as high in 1985 as they were in 2000. To correct for this, the lower panel shows the estimated typical mortgage payment, based on the prevailing interest rates. This reveals a distinct boom/bust pattern.