By 2005, accordingly, a good many people outside the economics profession were commenting on parallels between the housing bubble and other speculative binges. By 2006 the blogosphere was abuzz with accurate predictions of the approaching crash, and by 2007 the final plunge into mass insolvency and depression was treated in many circles as a foregone conclusion — as indeed it was by that time. Keith Brand, who founded the lively Housing–Panic blog in 2005 to publicize the approaching disaster, and kept up a running stream of acerbic commentary straight through the bubble and bust, summarized those predictions with a tag line that could serve as the epitaph for the entire housing frenzy: “Dear God, this is going to end so badly.”2
Yet it’s a matter of public record that among those who issued these warnings, economists were as scarce as hen’s teeth. Rather, most economists at the time dismissed the idea that the housing boom could be what it patently was, a disastrous speculative bubble. Nouriel Roubini, one of the few exceptions, has written wryly about the way he was dismissed as a crank for pointing out what should have been obvious to everybody else in his profession.3 For whatever reason, it was not obvious at all; the vast majority of economists who expressed a public opinion on the bubble while it was inflating insisted that the delirious rise in real estate prices was justified, and that the exotic financial innovations that drove the bubble would keep banks and mortgage companies safe from harm.
These comforting announcements were wrong. Those who made them should have known, while the words were still in their mouths, that they were wrong. No less an economic luminary than John Kenneth Galbraith pointed out many decades ago that in the financial world, the term “innovation” inevitably refers to the rediscovery of the same small collection of emotionally appealing bad ideas that always lead to economic disaster when they are applied to the real world.4 Galbraith’s books The Great Crash 1929 and A Short History of Financial Euphoria, which chronicle the repeated carnage caused by these same bad ideas in the past, can be found on the library shelves of every school of economics in North America, and anyone who reads either one can find every rhetorical excess and fiscal idiocy of the housing bubble faithfully duplicated in the great speculative binges of the past.
If the housing bubble were an isolated instance of failure on the part of the economics profession, it might be pardonable, but the same pattern of reassurance has repeated itself as regularly as speculative bubbles themselves. The same assurances were offered — in some cases, by the same economists — during the last great speculative binge in American economic life, the tech-stock bubble of 1996–2000. Identical assurances have been offered by the great majority of professional economists during every other speculative binge since Adam Smith’s time. More than two hundred years of glaring mistakes would normally be considered an adequate basis for learning from one’s errors, but in this case it has apparently been insufficient.
The Illusion of Invincibility
The problem with contemporary economics can be generalized as a blindness to potential disaster. This can be traced well outside the realm of bubble economics. Consider the self-destruction of Long Term Capital Management (LTCM) in 1998.5 LTCM was one of the first high-profile hedge funds, and made money — for a while, quite a bit of it — by staking huge amounts of other people’s funds on complex transactions based on intricate computer algorithms. It prided itself on having two Nobel laureates in economics on staff. Claims circulating on Wall Street during the firm’s glory days had it that LTCM’s computer models were so good that they could not lose money in the lifetime of this universe or three more like it.
Have you ever noticed that villains in bad science fiction movies usually get blown to kingdom come a few seconds after saying “I am invincible”? Apparently the same principle applies in economics, though the time lag is longer. It was some five years after LTCM launched its computer-driven strategy that the universe ended, slightly ahead of schedule. LTCM got blindsided by a Russian foreign-loan default that many other people saw coming, and failed catastrophically. The US government had to arrange a hurried rescue package to keep the implosion from causing a general financial panic.
Economists are not, by and large, stupid people. Many of them are extraordinarily talented; the level of mathematical skill displayed by the number-crunching “quants” in today’s brokerages and investment banks routinely rivals that in leading university physics departments. Somehow, though, many of these extremely clever people have not managed to apply their intelligence to the task of learning from a sequence of glaring and highly publicized mistakes. This is troubling for any number of reasons, but the reason most relevant just now is that economists play a leading role among those who insist that industrial economies need not trouble themselves about the impact of limitless economic growth on the biosphere and the resource base that supports all our lives. If they turn out to be as wrong about that as so many economists were about the housing bubble, they will have made a fateful leap from risking billions of dollars to risking billions of lives.
Thus it’s urgent to talk about the reasons why the economic mainstream has so often been unable to anticipate the downside. Like most of the oddities of contemporary life, this blindness to trouble has many causes. Two important ones result from peculiarities in the profession of economics as presently practiced; a third and more important reason is rooted in the fundamental assumptions that professional economists apply to the challenges of their field. The first two deserve discussion, but it’s the third that will lead into the central project of this book: the quest for economic insights that will help make sense of the challenges of industrial society’s future.
The first of the factors peculiar to the profession is that, for professional economists, being wrong is usually much more lucrative than being right. During the run-up to a speculative binge, and even more so during the binge itself, many people are willing to pay handsomely to be told that throwing their money into the speculation du jour is the right thing to do. Very few people are willing to pay to be told that they might as well flush their life’s savings down the toilet, even — indeed, especially — when this is the case. During and after the crash, by contrast, most people have enough demands on their remaining money that paying economists to say anything at all is low on the priority list.
This rule applies to professorships at universities, positions at brokerages and many of the other sources of income open to economists. When markets are rising, those who encourage people to indulge their fantasies of overnight unearned wealth will be far more popular, and thus more employable, than those who warn them of the inevitable outcome of such fantasies; when markets are plunging, and the reverse might be true, nobody’s hiring. Apply the same logic to the future of industrial society and the results are much the same: those who promote policies that allow people to get rich and live extravagantly today can count on an enthusiastic response, even if those same policies condemn industrial society to a death spiral in the decades ahead. Posterity pays nobody’s salaries today.
The second of the forces driving bad economic advice is shared with many other contemporary fields of study: economics suffers from a bad case of premature mathematization. The dazzling achievements of the natural sciences have encouraged scholars in a great many fields to ape scientific methods in the hope of duplicating their successes, or at least cashing in on their prestige. Before Isaac Newton could make sense of planetary movements, though, thousands of observational astronomers had to amass the raw data with which he worked. The same thing is true of any successful science: what used to be called “natural history,” the systematic recording of what Nature actually does, builds the foundation on which later scientists erect structures of hypothesis