The Map and the Territory Read online

  Self-esteem

  All human motivation appears to have a basis in our never-ending quest to achieve self-esteem. Self-esteem is an inbuilt human requirement, and one that demands continued nurturing—almost all human actions in one form or another are arguably directed at bolstering self-esteem. Mark Twain put it less stentoriously: “A man cannot be comfortable without his own approval.” People perpetually seek a reaffirmation of self-worth, often through the approval of others and the gratitude of those whom we have assisted. Unless our self-esteem is nurtured, most of us fall into depression.

  PROPENSITIES: PLUSES AND MINUSES

  Some of our human propensities have both positive and negative effects on economic activity. On the positive side, an inbred propensity to compete engages the forces of self-interest and self-esteem that direct resources to their highest valued uses, as judged by the value preferences, on average, of a society as a whole. And copycat herd behavior shapes trends for goods and services that spread improvements in our quality of life. The herd propensity leads to enhanced mass production and lower real unit costs of many consumer goods and services (as well as copycat capital investments), all supporting growth of productivity and living standards. On the negative side, competitiveness at its extreme, as I noted earlier, can morph into ugliness, and even violence.

  RATIONALITY

  Most human responses to daily economic events fall into the category of intuitive or “fast” thinking. These so-called knee-jerk decisions arise from the way our mind detects familiar patterns in new situations. A virtually instantaneous first cut of analysis yields the conclusions that come to us intuitively without having to access their sources. Given time and conscious appraisal, we often revise our less thoughtful initial reactions and sometimes completely reject them.

  As our experience in a field deepens, our intuitions regarding that field become ever more perceptive. I say this with some caveats. From my own introspections and those of my acquaintances whom I have queried, I conclude that we are not consciously aware of the way our mind’s “black box” or frontal lobe works: We pour information into our mind and, with a delay, out pop epiphanies. Albert Einstein, an intellectual tower of the twentieth century, when queried about the source of his insights, described the process: “A new idea comes suddenly and in a rather intuitive way. But intuition is nothing but the outcome of earlier intellectual experience.”16 Not surprisingly, important innovative intuitions occur only to those whose mental databanks are sufficiently endowed.

  Most human responses to economic events are in the end rational, or largely so, as much of animal spirits are heavily tempered by rational oversight. Markets, even in their most euphoric or fear-driven state, do not expect global stock market averages to double or triple overnight, or wheat prices to fall to five cents a bushel.

  Animal spirits nonetheless cannot readily be classified as either rational or irrational. These are terms from the world of free choice, not the world of the hardwired determinism of inbred reactions. But to the extent that any human action is at least partially driven by “spirits,” the material outcomes are less satisfactory (in purely economic terms) than they would be under the hypothetical presumption that animal spirits did not exist and that human beings’ economic behavior was wholly rational. A fundamental insight of classical economics is that wealth and standards of living are maximized when market participants seek their own long-term self-interests. Anything short of that, by definition, is suboptimal. If the maximum growth in output per hour in the developed world over fifteen-year periods has been 3 percent (see Chapter 8) under an economy significantly affected by animal spirits, then the hypothetical growth rate of output per hour without animal spirits, of necessity, would have been much higher. If the difference were only one half of a percentage point a year, the cumulative level over, say, a fifty-year span would be more than a fourth higher at the end of that time span. Clearly the substituting of animal spirits for the hypothetical model based on rational long-term self-interest is not likely to be a trivial quantity. Knowing what the human race could do if it were fully rational at least gives us the upper bounds of possible economic achievement.

  TWO

  THE CRISIS BEGINS, INTENSIFIES, AND ABATES

  I first became fully aware of the seriousness of the developing global financial crisis with the disclosure on August 9, 2007, that BNP Paribas, a major French bank, was holding significant quantities of defaulting securitized American subprime mortgages. That disclosure was followed later that day by a massive injection of reserves by the European Central Bank (ECB). On August 10, the ECB was joined by the central banks of the United States, Japan, Australia, and Canada in the first globally coordinated action by central banks since 2001. I was stunned. Such coordination, in my experience, was implemented only when central banks perceived the risk of imminent and serious financial or economic disruption.

  For a while the official concerns were largely confined to the financial and housing sectors. In early 2007, the composition of the world’s nonfinancial corporate balance sheets and cash flows appeared in as good a shape as I can ever recall.1 After the S&P 500 closed at record highs on July 19, stock prices fell sharply in the weeks following as lackluster data on new home sales; a dismal outlook from Countrywide Financial, the largest mortgage lender; and a handful of disappointing earnings reports compounded growing fears of problems in the housing and mortgage markets.

  The markets nonetheless quickly shook off the bad news and stock prices recovered all of their losses and more, peaking at an all-time high on October 9, 2007. But the cracks were already appearing. As the crisis widened, stock prices turned down and proceeded to decline for the eleven months leading up to the Lehman failure. By the time of the Lehman default on September 15, 2008, global losses in publicly traded corporate equities stood at $16 trillion. But losses more than doubled in the weeks following the Lehman default, bringing the cumulative drop in global equity values to almost $35 trillion, a decline of more than half. Added to that were trillions of dollars of losses of equity in homes ($7 trillion in the United States alone) and losses of nonlisted corporate and unincorporated businesses that brought the global aggregate equity loss close to $50 trillion, equivalent to a staggering four fifths of 2008 global GDP.

  LIQUIDITY EVAPORATION

  The period of deep financial trauma began with the wholly unanticipated evaporation of the global supply of short-term credit in the immediate wake of the Lehman Brothers failure. Such a breakdown on so global a scale was without historical precedent.2 A run on money market mutual funds, heretofore perceived to be close to riskless, was under way within hours of the announcement of Lehman’s default,3 followed within days by a general withdrawal of trade credit that set off a spiral of global economic contraction.4 Meanwhile, the Federal Reserve had to move quickly to support the failing U.S. commercial paper market. Even the fully collateralized repurchase agreement market encountered severe and unprecedented difficulties as the quality of debt collateral was severely undermined by the collapse in the value of the counterparties’ equity buffer. With a severely diminished global equity buffer, debt burdens became oppressive. Finance was in the grip of the most dreaded of animal spirits: a fear-induced stampede.

  Particularly hard hit were the investment banks that were prone to the type of run by their creditors that had often been experienced by commercial banks prior to the onset of deposit insurance in 1933. Not only did short-term funding collapse, but, as I note in Chapter 5, customer collateral that was subject to recall fled. The institutions were led astray by the mistaken belief that the tight bid-ask spreads in financial markets at the top of the boom were an indication of a persistent availability of liquidity. That in fact was not the case. As I point out later, liquidity is a function of the state of risk aversion, and when risk aversion rises sharply, liquidity evaporates.

  While commercial banks had their share of failures,5 many of the most complex dangers emanated from the so-called s
hadow banking system—the set of financial institutions that do not accept insured deposits and hence heretofore had been largely unregulated. But not all shadow banking was devastated. Unaffiliated hedge funds, by and large, weathered the storm.* To my knowledge, none of the larger funds failed. To be sure, many of them had to liquidate after severe losses, but none defaulted on their debt.

  SHADOW BANKING

  Shadow banking is a form of financial intermediation whose funding is not supported by the traditional banking safety nets—in the United States, deposit insurance and access to central bank funding. Shadow banking includes the activities of investment banks, hedge funds, money market funds, structured investment vehicles (SIVs), and other credit intermediaries acting outside the regular banking system. Those institutions have developed in recent decades into a very substantial part of international finance and have been heavy traders in derivatives, including synthetic collateralized debt obligations and credit default swaps. Although shadow banking activities lie outside the banking system, many of these activities have been conducted by regulated banks. For example, most SIVs were organized by commercial banks. The expansion of SIVs and other off-balance-sheet conduits moved significant amounts of assets and liabilities off bank balance sheets, thereby ostensibly creating more robust capital levels. But as the crisis loomed, SIVs that carried the name and reputation of their originating banking entities were absorbed (with their risk) back onto the banks’ balance sheets.

  The shadow banking system globally grew at an astonishing pace in the years leading up to the crisis, and appears to have changed little since. According to a November 2012 report by the Financial Stability Board,6 assets of shadow banking institutions globally grew from $26 trillion in 2002 to $62 trillion in 2007, and following a decline in 2008, reached $67 trillion by the end of 2011. As a share of total financial intermediary assets, shadow banking consistently accounted for 23 percent to 27 percent during that time frame. Of course, the assets of commercial banks grew at a nearly proportional rapid pace, and thus the shadow banking system remained slightly more than half the size of the regular banking system throughout the 2002 to 2011 period. Still, they were very large players on the financial landscape. In the United States alone, shadow banking constituted $23 trillion in assets at the end of 2011, by far the largest constituent of the global network of nonbank credit intermediaries.

  BANK CAPITAL BUFFERS

  Banking has always involved inducing depositors, or in earlier centuries note holders, to fund bank assets. In the 1840s, for example, U.S. (state) banks had to maintain a capital buffer in excess of 50 percent of assets in order to create willing holders of their notes (Exhibit 2.1). In the century that followed, the necessary capital buffer declined with the increasing consolidation of specie reserves following the Civil War. That consolidation occurred as improved rail transportation facilitated the movement of specie, and telegraphed money transfers grew as correspondent bank links expanded. Finally, in later years, the emergence of various government safety nets reduced the need for capital.

  Systemic risk in the United States is almost exclusively generated by the risks posed by financial institutions and financial markets—the concern especially being that defaults of those institutions could dismantle the financial system and, with it, the broader economy. The systemic risks posed by nonfinancial companies are far less daunting. The default of an individual nonfinancial corporation will affect its creditors, suppliers, and some of its customers, but rarely does it have an effect much beyond that. Nonfinancial corporate defaults do not have the broad contagious effect that is associated with the default of a financial institution. Moreover, nonfinancial businesses hold a much higher ratio of equity to assets than do financial institutions, typically one third to one half of the value of assets, compared with only 5 percent to 15 percent for highly liquid financial firms.

  TOO BIG TO FAIL

  The perceived systemic effect of the failure of large financial institutions is the genesis of the “too big to fail” (TBTF) or the “too big to liquidate quickly” problem. For years I have been concerned about the ever larger size of our financial institutions. More than a decade ago, I noted that “megabanks being formed by growth and consolidation are increasingly complex entities that create the potential for unusually large systemic risks in the national and international economy should they fail.”7 Federal Reserve research had been unable to find economies of scale in banking beyond a modest-sized institution.8 I often wondered as the banks increased in size throughout the globe prior to the crash and since: Had bankers discovered economies of scale that Fed research had missed?

  One highly disturbing consequence of the TBTF-bailout problem is that it is going to be difficult to convince market participants henceforth that a large financial institution in trouble should be allowed to fail. The implicit subsidy to these large institutions that such notions spawn insidiously impairs the efficiency of finance and the allocation of capital. I will address this important issue in Chapters 5 and 11.

  In retrospect it is now evident to all that the level of capital that commercial banks and especially investment banks accumulated prior to 2008 as crisis protection was inadequate. The marked increase in risk taking of a decade ago could have been guarded against wholly by increased capital. Regrettably, that did not occur and the accompanying dangers were not fully appreciated, even in the commercial banking sector. For example, in 2006, the Federal Deposit Insurance Corporation (FDIC), speaking for all U.S. bank regulators, judged that “more than 99 percent of all insured institutions met or exceeded the requirements of the highest regulatory capital standards.”9 Newly acquired capital additions accordingly remained modest.

  RISK MANAGEMENT FAILS

  But why did the large array of fail-safe buffers that were supposed to counter such developing crises fail? We had thought that we depend on our highly sophisticated global system of financial risk management to contain market breakdowns. How could these systems have failed on so broad a scale? The risk management paradigm that had as its genesis the work of several Nobel Prize winners in economics—Harry Markowitz, Robert Merton, and Myron Scholes (and Fischer Black, who would have received the award had he lived)—was so thoroughly embraced by academia, central banks, and regulators that by 2006 it had become the core of the global bank regulatory standards known as Basel II. Global banks were authorized, within limits, to apply their own company-specific risk-based models to judge their capital requirements. Most models estimated their parameters based on the last quarter century of observations. But even a sophisticated number-crunching model that covered the last five decades would not have anticipated the crisis that loomed.

  Mathematical models that calibrate risk are surely better guides to risk assessment than the “rule of thumb” judgments of a half century earlier. To this day it is hard to find fault with the conceptual framework of our models, as far as they go. The elegant options-pricing model of Black and Scholes is no less valid or useful today than when it was developed in 1973. In the growing state of euphoria in the years before the 2008 crash, private risk managers, the Federal Reserve, and other regulators failed to ensure that financial institutions were adequately capitalized, in part because we all failed to comprehend the underlying magnitude and the full extent of the risks that were about to be revealed as the post–Lehman crisis played out. In particular, we failed to fully comprehend the size of the expansion of so-called tail risk. Tail risk is financial jargon that risk managers employ to identify the class of investment outcomes that occur with very low probabilities—but that are accompanied by very large losses when they materialize (see Box 2.1). For decades, a number of unusual “once in a lifetime” phenomena were occurring much too often to be credibly described as owing purely to chance. A defining moment for me was the wholly unprecedented stock price crash on October 19, 1987, that propelled the Dow Jones Industrial Average down more than 20 percent in that single day. There was no simple probability distributi
on from which that event could be inferred. Accordingly, the negative “tail” was thought to be fat. But when those previously unvisited areas of investment outcome distributions were filled in subsequent to the Lehman default, the fat tails turned out, in fact, to be morbidly obese. As a consequence of an underestimation of these risks, risk managers failed to anticipate the amount of additional capital that would be required to serve as an adequate buffer when the financial system was jolted.

  BOX 2.1: TAIL RISK

  If people acted solely to maximize their own self-interest, their actions would produce a long-term growth path consistent with their ability to increase productivity. But lacking omniscience, the actual outcomes of their risk taking would reflect random deviations from their long-term trend. And those deviations, with enough observations, would tend to be distributed in a manner similar to successive coin tosses, following what economists call a “normal” distribution (a bell curve with tails that rapidly taper off as the probability of occurrence diminishes).

  If we introduce the realism of behavioral economics and add our propensities of euphoria and fear, we produce the business cycle that shifts observations of risk-taking outcomes from the middle parts of the distribution toward its tails. But as I demonstrate in Chapter 4, fear is a far more potent propensity than euphoria. The adjusted real-world probability distribution that emerges exhibits a tail of positive outcomes that is barely discernible, but a negative tail that is both highly visible and large.