The Map and the Territory Page 2

  It is important to recognize, however, that not all bubbles, when they collapse, wreak the degree of havoc experienced in 2008. As I detail in Chapter 2, the crashes of 1987 and 2000 had comparatively minimal negative effect on the economy. The severity of the destruction caused by a bursting bubble is determined not by the type of asset that turns “toxic” but by the degree of leverage employed by the holders of those toxic assets. The latter condition dictates to what extent contagion becomes destabilizing. In short, debt leverage matters—as we see in Chapter 2.

  —

  This book touches on many related issues of importance to our economic future. Writing it has taken me into some uncharted waters—some that might, because of the nature of some of my concerns about the course we are now on, prove to be uncomfortably warm. But I did not write this book in a spirit of criticism, or of pessimism. My interest in writing it was not to establish what I now think but what I now believe I can demonstrate with some reasonable degree of assurance.

  Coming out of World War II, the United States was at the top of its game. Productivity was growing rapidly. Household and business savings rates were close to 10 percent, and capital investment and residential building were booming. Moreover, even after funding our burgeoning capital investment, we still had enough savings to spare to invest beyond our borders.

  After securing our place of leadership in the economic world, we turned magnanimously to ensure that the least well off in our society shared in the good fortune of the nation as a whole. After many years of Social Security and lesser programs, such “government social benefits to persons” totaled 4.7 percent of GDP. But starting in 1965, with the additions of Medicare and Medicaid, and shortly thereafter a major increase in Social Security through benefit inflation indexation, we embarked on a truly bipartisan unprecedented four-decade rise in outlays averaging nearly 10 percent per year. The unfortunate consequence of our magnanimity, as I demonstrate in later chapters, is that these benefits have been crowding out private savings almost dollar for dollar. That loss of funding for capital investment led to slowed productivity growth, a phenomenon that would have been even worse if we had not turned to borrowing so heavily from abroad. Moreover, to fund our generosity we have foraged into every corner of our federal budget to meet the rise in social benefit spending. We are eating our seed corn, and damaging the very engine of America’s comparative strength in the world. We desperately need a change in direction. We have done it before—many times, in fact.

  A NOTE TO READERS

  Where applicable in the chapters that follow, I have included appendices in support of my conclusions, with additional explanatory text, tables, charts, and regression analyses, the most widely used statistical procedure to assist in judging economic cause and effect.11 Statistics first appear in Chapter 2 and I have accompanied that chapter’s appendix with a short primer on the interpretation of the results of regression analysis. For those uninterested in these metrics, appendices can readily be bypassed. I trust my written commentary will carry the line of reasoning of the appendices’ equations.

  A significant part of the statistical analysis in our exhibits rests on the National Income and Product Accounts of the Bureau of Economic Analysis (BEA). Shortly before we went to press, the BEA published a major revision of those accounts. While there are significant changes in the levels of many series, none importantly alter any conclusions in the forthcoming chapters.

  ONE

  ANIMAL SPIRITS

  In my early years, I lived a cloistered life, traveling only rarely outside the confines of New York City. When, in my mid-to-late teens, I was first exposed to the rest of the world, I was amazed at how similarly all varieties of people behaved. They may have hailed from different cultures and spoken different languages, but their interactions and behavior were quite familiar to a boy brought up in the canyons of New York City. As I began to travel widely, I became fascinated when businesspeople in Norway, tribal leaders in South Africa, and Chinese musicians all had remarkably similar emotional reactions to day-to-day events. They all smiled and laughed, for example, as a sign of pleasure. They all expressed fear and euphoria in a similar manner.

  As the years rolled on, I observed generation after generation of teenagers all exhibiting similar insecurities, awkwardness, and aspirations. The novels of Jane Austen, written in early nineteenth-century Britain, depicted to me a playing field of social intercourse quite familiar to everyone alive today. We humans appear to be a truly homogenous species.

  But at root, what are we? We like to describe ourselves as fundamentally driven by reason to an extent not matched by other living creatures. This is doubtless true. But we are far from the prototype depicted by neoclassical economists: that of people motivated predominantly by considerations of rational long-term self-interest. Our thinking process, as behavioral economists point out, is more intuitive than syllogistic. In the end, of course, all intellectual and hence material progress requires verification by a systematic logical process, but that is rarely the way we think day by day.

  The economics of animal spirits, broadly speaking, covers a wide range of human actions, and overlaps with much of the relatively new discipline of behavioral economics. The point is to substitute a more realistic version of behavior than the model of the wholly rationality-driven “economic man” so prominent for so long in economics courses taught in our universities.1 This more realistic view of the way people behave in their day-by-day activities in the marketplace traces a path of economic growth that is somewhat lower than would be the case if people were truly “rational” economic actors. Most of the time this issue is of little more than academic interest because all of our statistical observations and forecasts are already based on decisions that people actually made, not what those decisions would have been had people been acting more rationally. While it’s true that if people acted at the level of rationality presumed in the standard economics textbooks I was brought up with, the world’s standard of living would be measurably higher; but, in fact, they do not. From the perspective of a forecaster, the issue is thus not whether behavior is rational but whether it is sufficiently repetitive and systematic to be numerically measured and predicted.

  Can we better identify and measure those quick-reaction judgments on which we tend to base much, if not all, of our rapid-fire financial market and related decisions—“fast thinking,” in the words of Daniel Kahneman, a leading behavioral economist? I think so.

  THE LONGER PERSPECTIVE

  Consider the insights that brought us the steam engine and the electric motor, the railroad, the telegraph, atomic energy, and the integrated circuit. It was those innovations, and more, that over the past two centuries propelled civilization to the highest material standards of living ever achieved. They were all the result of human reasoning. As the seventeenth-century French mathematician Blaise Pascal is said to have put it, “Man’s greatness lies in his power of thought.” It’s Kahneman’s “slow thinking.”

  To be sure, great innovators often explain their insights as epiphanies, or intuition. But those epiphanies seem to happen only to those who have laboriously accumulated the knowledge relevant to such awakenings.2 I rank the revolution of the eighteenth century, the Enlightenment, particularly in the works of John Locke, David Hume, Adam Smith, and their followers, as the critical intellectual root of the twenty-first century’s elevated standard of living. The radical ideas of such men led to the political upheaval that changed societies previously ruled by the divine right of kings, often in complicity with the Church. Many countries reorganized under a rule of law that protected individual rights, especially property rights. By engaging our competitive self-interest, we fostered the innovations that changed the world after millennia of economic stagnation. Those were all acts of human intelligence from which the historical roots of modern capitalist economies have arisen. But that human intelligence has always existed side by side with a large strain of human irrationality.

&nbs
p; As the nineteenth century progressed and populations moved from self-sufficient farming to the increasingly complex and interactive urban-dominated economies of the modern world, the industrial business cycle emerged. It demonstrably was driven by the animal spirits we currently observe at the core of speculative booms. But because agriculture, diminishing in importance but still prominent into the 1950s, was largely dependent on weather rather than animal spirits, it was out of sync with the business cycle of nonagricultural industries and thus assuaged the ebb and flow of economic activity as a whole.

  On occasion in this book I try to supplement standard forecasting models to capture what we have always known about financial market disruption but have never integrated into those models. As I mentioned, I had always viewed animal spirits as the human propensities driven largely by random irrationalities not readily integrated into formal models of the way market economies function. September 2008 was a watershed moment for forecasters, myself included. It has forced us to find ways to incorporate into our macromodels those animal spirits that dominate finance.

  All such spirits, as I observe later, are tempered by reason to a greater or lesser degree, and hence I more formally choose to describe such marketplace behavior as “propensities.” The technologies that have driven productivity since the Enlightenment were, at root, reasoned insights. Random irrationality produces nothing. If reason were not ultimately prevailing, we could not explain the dramatic improvements in standards of living that the world has achieved in the past two centuries.

  As I will demonstrate, these reason-tempered animal spirits significantly affect macroeconomic decision making and outcomes. Newly popular behavioral economics is forcing forecasters to evaluate economic data in the context of a more complex model than that to which most of us had become accustomed.

  BEHAVIORAL ECONOMICS

  Behavioral economics is not a substitute for conventional economics, nor is it claimed to be. Daniel Kahneman, in discussing his latest book, noted that “much of the discussion . . . is about biases of intuition. However, the focus on error does not denigrate human intelligence. . . . Most of our judgments and actions are appropriate most of the time.”3

  As Colin Camerer and George Loewenstein aptly put it a decade ago:

  At the core of behavioral economics is the conviction that increasing the realism of the psychological underpinnings of economic analysis will improve economics on its own terms. . . . It does not imply a wholesale rejection of the neoclassical approach to economics based on utility maximization, equilibrium, and efficiency. . . . [Behavioral] departures are not radical . . . because they relax simplifying assumptions that are not central to the economic approach. For example, there is nothing in core neoclassical theory that specifies that people should . . . weight risky outcomes in a linear fashion, or that they must discount the future exponentially at a constant rate.4

  IDENTIFICATION

  Because human beings demonstrate similar characteristics, most, if not all, inbred propensities can be inferred by introspection and observation by every one of us. Fear, euphoria, competitive drive, and time preference, for example, are both introspectively self-evident and readily recognizable in others. Other propensities, such as inbred herding and home bias, we infer mainly by observing the behavior of others. (All of these separate propensities will be discussed shortly.)

  In classifying propensities, I do not pretend to know which are truly inbred and which just have statistical regularities that are tantamount to being inbred. I classify propensities as “inbred”—herd behavior, for example—more for convenience than insight. I use the term “inbred” to cover both truly inbred propensities and those consistencies of behavior that enable model builders to operate on that assumption. I do not contend to have covered all of the economically relevant spirits or propensities, but I do hope that I have addressed the most important of them. My ultimate purpose is defining a set of economic stabilities of human actions that are statistically measurable and hence capable of being modeled. I am fully aware that in the process I am delving into disciplines with which I have little experience, and have tried to temper my conclusions accordingly.

  PROPENSITIES

  Fear and Euphoria

  We all directly experience threats to our self and our values (fear) and the sense of well-being or elation (euphoria) triggered in the course of our pursuit of our economic interests. Fear, a major component of animal spirits, is a response to a threat to life, limb, and net worth. That emotion is decidedly inbred—no one is immune to it. But people respond to fear in different ways, and the differences are part of what defines the individuality of people. We are all alike fundamentally, but it is our individuality that makes for differences in values and our position in the hierarchy of society. Moreover, it is our individuality that creates markets, division of labor, and economic activity as we know it.

  Risk Aversion

  Risk aversion is a complex animal spirit crucial to forecasting. It reflects the ambivalent attitude people exhibit to the taking of risk. That we need to act to obtain food, shelter, and all the necessities of life is evident to all, as is the fact that we can’t necessarily know in advance how successful our actions will be. The process of choosing which risks to take and which to avoid determines the relative pricing structure of markets, which in turn guides the flow of savings into investment, the critical function of finance (an issue I address in Chapter 5).

  If risk taking is essential to living, is more risk taking better than less? If more risk were better than less risk, demand for lower quality bonds would exceed demand for riskless bonds, and high-quality bonds would yield more than low-quality bonds. They do not, from which we can infer the obvious: Risk taking is a necessary part of living, but it is not something the vast majority of us actively seek. Finding the proper balance of risks is critical to all of us in our day-to-day lives and perhaps manifests itself most obviously in finance in the management of portfolio risk.

  The extremes of zero and full risk aversion (or its obverse, full and zero risk taking) are outside all human experience. Zero risk aversion—that is, the absence of any aversion to engaging in risky actions—implies that an individual does not care about, or cannot discriminate among, objective states of risk to life and limb. Such individuals cannot (or do not choose to) recognize life-threatening events. But to acquire the staples of life requires action, that is, the taking of risks, either by an individual or by others, such as parents taking risks on a child’s behalf.

  We live our lives day by day well within these outer boundaries of risk aversion and risk taking, which can be measured approximately by financial market yield spreads with respect to both credit rating and maturity. Those boundaries are critical to forecasting. The turn in stock prices in early 2009 following the crash of 2008 was a sign of the level of human angst approaching its historical limit (see Chapter 4). The limits of angst are also evident in credit spreads, which exhibit few or no long-term historical trends. Prime railroad bonds of the immediate post‒Civil War years, for example, reflect spreads over U.S. Treasuries that are similar to our post‒World War II experience, suggesting long-term stability in the degree and spread of human risk aversion.

  I calibrate how people respond to risk in nonfinancial markets, both rationally and emotionally, with a measure I have employed for years—the share of liquid cash flow that management chooses to commit to illiquid, especially long-term, capital investments. That share is a measure of corporate managers’ degree of uncertainty and hence their willingness to take risks. In 2009, it had fallen to its lowest peacetime level since 1938. The equivalent measure of risk aversion for households is the share of household cash flow invested in homes. This measure reached its lowest postwar level in 2010. That collapse in investment, especially in long-lived assets, explains most of the recent failure of the American economy to follow a path of recovery similar to the other ten post‒World War II recoveries (see Chapter 7, “Uncertainty Undermines Inves
tment”).

  Throughout this book I delve into the role of risk aversion and uncertainty as critical determinants of economic activity. I conclude that stock prices are not only an official leading indicator of business activity but are also a major cause of that activity (see Chapter 4). Uncertainty has many of the characteristics of peering into fog. Heavy discounting of the future is tantamount to having difficulty perceiving clearly beyond a certain point, and progressively less well as distance (risk) increases. The lessening or the end of uncertainty is like the lifting of the fog.

  Time Preference

  Time preference is the self-evident propensity to value more highly a claim to an asset today than a claim to that same asset at some fixed time in the future. A promise delivered tomorrow is not as valuable as that promise conveyed today. That many buyers of Apple’s immensely popular iPhone 5 (released in September 2012) would have paid for immediate delivery to bypass a waiting list is a clear reflection of time preference. We experience this phenomenon mainly through its most visible counterpart: interest rates and savings rates (see Box 1.1). The stability of time preference over the generations can be demonstrated; indeed, in fifth-century-BC Greece, interest rates exhibited levels similar to what we see in today’s markets.5 The Bank of England’s official policy rate for the years 1694 to 1972 ranged between 2 percent and 10 percent. It surged to 17 percent during the inflationary late 1970s, but it has since returned to its single-digit historical range. It is reasonable to conclude that time preference, too, has no evident long-term trend.

  Such inferences of the stability of time preference are also consistent with behavioral economics. A famous experiment, conducted in 1972 and 1990 by Stanford psychologist Walter Mischel, concluded that the ability of children between the ages of four and six to forgo immediate gratification6 was reflected years later by the high SAT scores of those who deferred gratification as children compared with those who could not. A follow-up study of the same individuals in 2011 confirmed the response, indicating a lifelong inbred propensity to a specific level of time preference, though not the same for each individual. To forgo short-term gratification for greater rewards in the future is generally consistent with higher intelligence.