Currency Wars: The Making of the Next Global Crisis (30 page)

Read Currency Wars: The Making of the Next Global Crisis Online

Authors: James Rickards

Tags: #Business & Economics

BOOK: Currency Wars: The Making of the Next Global Crisis
2.87Mb size Format: txt, pdf, ePub
Recently new and better economic paradigms have emerged. However, Washington and Wall Street both have a vested interest in the flawed models from the past. For Washington, Keynesianism is an excuse to expand spending and monetarism is an excuse to concentrate power at the Fed. For Wall Street, the theories of financial economics provide cover for high leverage and deceptive sales practices for off–balance sheet derivatives. On Wall Street, profits come first and good science second. If some theory, however flawed or out of date, can be trotted out with the right academic pedigree to provide a rationale for risk taking, then that is fine. If politicians and regulators are even further behind the learning curve than Wall Street, then that is fine too. As long as the profits continue on Wall Street, the hard questions will not be asked, let alone answered.
CHAPTER 10
 
Currencies, Capital and Complexity
 
“The difficulty lies, not in the new ideas, but in escaping from the old ones.”
John Maynard Keynes, 1935
 
 
 
 
 
D
espite the theoretical and real-world shortcomings of both the Keynesian multiplier and the monetarist quantity approach to money, these are still the dominant paradigms used in public policy when economic growth falters. One need look only at the Obama stimulus and the Bernanke quantitative easing programs to see the hands of John Maynard Keynes and Milton Friedman hard at work. This persistence of the old school is also one driver of the new currency war, because of the expansion of public debt. This debt can be repaid only with help from inflation and devaluation. When growth falters, taking growth from other countries through currency devaluation is irresistible. Far better solutions are needed.
Fortunately, economic science has not stood entirely still. A new paradigm has emerged in the past twenty years from several schools of thought, including behavioral economics and complexity theory, among others. This new thinking comes with a healthy dose of humility—practitioners in many cases acknowledge the limitations of what is possible with the tools at hand. The new schools avoid the triumphalism of Keynes’s claim to a “general theory” and Friedman’s dictum that inflation is “always and everywhere” monetary.
The most promising new school is complexity theory. Despite the name, complexity theory rests on straightforward foundations. The first is that complex systems are not designed from the top down. Complex systems design themselves through evolution or the interaction of myriad autonomous parts. The second principle is that complex systems have emergent properties, which is a technical way of saying the whole is greater than the sum of its parts—the entire system will behave in ways that cannot be inferred from looking at the pieces. The third principle is that complex systems run on exponentially greater amounts of energy. This energy can take many forms, but the point is that when you increase the system scale by a factor of ten, you increase the energy requirements by a factor of a thousand, and so on. The fourth principle is that complex systems are prone to catastrophic collapse. The third and fourth principles are related. When the system reaches a certain scale, the energy inputs dry up because the exponential relationship between scale and inputs exhausts the available resources. In a nutshell, complex systems arise spontaneously, behave unpredictably, exhaust resources and collapse catastrophically. When you apply this paradigm to finance, you begin to see where the currency wars are headed.
Complexity theory has a strong empirical foundation and has had wide application in a variety of natural and man-made settings, including climate, seismology and the Internet. Significant progress has been made in applying complexity to capital and currency markets. However, a considerable challenge arises when one considers the interaction of human behavior and market dynamics. The complexity of human nature sits like a turbocharger on top of the complexity of markets. Human nature, markets and civilization more broadly are all complex systems nested inside one another like so many Russian
matryoshka
dolls. An introduction to behavioral economics will provide a bridge to a broader consideration of complexity theory and how underlying dynamics may determine the fate of the dollar and the endgame in the currency wars.
Behavioral Economics and Complexity
 
Contemporary behavioral economics has its roots in mid-twentieth-century social science. Pioneering sociologists such as Stanley Milgram and Robert K. Merton conducted wide-ranging experiments and analyzed data to develop new insights into human behavior.
Robert K. Merton’s most famous contribution was the formalization of the idea of the self-fulfilling prophecy. The idea is that a statement given as true, even if initially false, can become true if the statement itself changes behavior in such a way as to validate the false premise. Intriguingly, to make his point Merton used the example of a run on the bank in the days before deposit insurance. A bank can begin the day on a sound basis with ample capital. A rumor that the bank is unsound, although false, can start a stampede of depositors trying to get their money out all at once. Even the best banks do not maintain 100 percent cash on hand, so a true bank run can force the bank to close its doors in the face of depositor demands. The bank fails by the end of the day, thus validating the rumor even though the rumor started out as false. The interaction of the rumor, the resulting behavior and the ultimate bank failure is an illustration of a positive feedback loop between information and behavior.
Merton and other leading sociologists of their time were not economists. Yet in a sense they were, because economics is ultimately the study of human decision making with regard to goods in conditions of scarcity. The sociologists cast a bright light on these decision-making processes. Former Bear Stearns CEO Alan Schwartz can attest to the power of Merton’s self-fulfilling prophecy. On March 12, 2008, Schwartz told CNBC, “We don’t see any pressure on our liquidity, let alone a liquidity crisis.” Forty-eight hours later Bear Stearns was headed to bankruptcy after frightened Wall Street banks withdrew billions of dollars of credit lines. For Bear Stearns, this was a real-life version of Merton’s thought experiment.
A breakthrough in the impact of social psychology on economics came with the work of Daniel Kahneman, Amos Tversky, Paul Slovic and others in a series of experiments conducted in the 1950s and 1960s. In the most famous set of experiments, Kahneman and Tversky showed that subjects, given the choice between two monetary outcomes, would select the one with the greater certainty of being received even though it did not have the highest expected return. A typical version of this is to offer a subject the prospect of winning money structured as a choice between: A) $4,000 with an 80 percent probability of winning, or B) $3,000 with a 100 percent probability of winning. For supporters of efficient market theory, this is a trivial problem. Winning $4,000 with a probability of 80 percent has an expected value of $3,200 (or $4,000 × .80). Since $3,200 is greater than the alternative choice of $3,000, a rational wealth-maximizing actor would chose A. Yet in one version of this, 80 percent of the participants chose B. Clearly the participants had a preference for the “sure thing” even if its theoretical value was lower. In some ways, this is just a formal statistical version of the old saying “A bird in the hand is worth two in the bush.” Yet the results were revolutionary—a direct assault on the cornerstone of financial economics.
Through a series of other elegantly designed and deceptively simple experiments, Kahneman and his colleagues showed that subjects had a clear preference for certain choices based on how they were presented, even though an alternative choice would produce exactly the same result. These experiments introduced an entirely new vocabulary to economics, including certainty (the desire to avoid losses, also called risk aversion), anchoring (the undue influence of early results in a series), isolation (undue weight on unique characteristics versus shared characteristics), framing (undue weight on how things are presented versus the actual substance) and heuristics (rules of thumb). The entire body of work was offered under the title “prospect theory,” which marked a powerful critique of the utility theory used by financial economists.
Unfortunately, behavioral economics has been embraced by policy makers to manipulate rather than illuminate behavior based on dubious premises about their superior wisdom. Bernanke’s campaign to raise inflationary “expectations” by printing money and devaluing the dollar while holding rates low is the boldest contemporary version of such manipulation, yet there are others. Orchestrated propaganda campaigns have involved off-the-record meetings of corporate CEOs with business reporters requesting that they apply a more favorable spin to business news. These attempted manipulations have their absurd side, as with the phrase “green shoots” repeated ad nauseam by cable TV cheerleaders in the spring of 2009 at a time when America was losing millions of jobs. Tim Geithner’s self-proclaimed “Recovery Summer” in 2010 is another example—that summer came and went with no recovery at all for the forty-four million on food stamps. These are all examples of what Kahneman called “framing” an issue to tilt the odds in favor of a certain result.
What Bernanke, Geithner and like-minded behavioralists in policy positions fail to see is something Merton might have easily grasped—the positive feedback effect that arises from framing without substance. If the economy is actually doing well, the message requires no framing and the facts will speak for themselves, albeit with a lag. Conversely, when reality consists of collapsing currencies, failed banks and insolvent sovereigns, talk about green shoots has at best a limited and temporary effect. The longer-term effect is a complete loss of trust by the public. Once the framing card has been played enough times without results, citizens will reflexively disbelieve everything officials say on the subject of economic growth even to the point of remaining cautious if things actually do improve. This does not represent a failure of behavioral economics so much as its misuse by policy makers.
Behavioral economics possesses powerful tools and can offer superb insights despite occasional misuse. It is at its best when used to answer questions rather than force results. Exploration of the paradox of Keynesianism is one possibly fruitful area of behavioral economic research with potential to mitigate the currency wars. Keynesianism was proposed in part to overcome the paradox of thrift. Keynes pointed out that in times of economic distress an individual may respond by reducing spending and increasing savings. However, if everyone does the same thing, distress becomes even worse because aggregate demand is destroyed, which can cause businesses to close and unemployment to rise. Keynesian-style government spending was thought to replace this shortage of private spending. Today government spending has grown so large and sovereign debt burdens so great that citizens rightly expect that some combination of inflation, higher taxation and default will be required to reconcile the debt burden with the means available to pay it. Government spending, far from stimulating more spending, actually makes the debt burden worse and may increase this private propensity to save. Here is a conundrum that behavioral economists seem well suited to explore. The result may be the discovery that short-term government austerity brightens long-run economic prospects by increasing confidence and the propensity to spend.
Complexity Theory
 
Our definition of complex systems included spontaneous organization, unpredictability, the need for exponentially greater energy inputs and the potential for catastrophic collapse. Another way to understand complexity is to contrast it with that which is merely complicated. A Swiss watch may be complicated, but it is not complex. The number and size of various gears, springs, jewels, stems and casings make it complicated. Yet the parts do not communicate with one another. They touch but do not interact. One gear does not enlarge itself because the other gears think it is a good idea. The springs do not spontaneously self-organize into a liquid metallic soup. The watch is complicated; however, complexity is much more than complication.
Complex systems begin with individual components called autonomous agents, which make decisions and produce results in the system. These agents can be marine species in the oceanic food chain or individual investors in currency markets; the dynamics are the same. To be complex, a system first requires diversity in the types of agents. If the agents are alike, nothing very interesting will happen. If they are diverse, they will respond differently to various inputs, producing more varied results.
The second element is connectedness. The idea is that the agents are connected to one another through some channel. This can consist of electrical lines in the case of a power grid or Twitter feeds in the case of a social network, but somehow the agents must have a way to contact one another.
The third element is interdependence, which means that the agents influence one another. If someone is not sure how cold it is outside and she looks out the window to see everyone wearing down coats, she might choose to wear one too. The decision is not automatic—she might choose to wear only a sweater—but in this case a decision to wear a warm coat is partly dependent on others’ decisions.
The last element is adaptation. In complex systems, adaptation means more than change; rather it refers specifically to learning. Investors who repeatedly lose money on Wall Street themes such as “buy and hold” may learn over time that they need to consider alternative strategies. This learning can be collective in the sense that lessons are shared quickly with others without each agent having to experience them directly. Agents that are diverse, connected, interdependent and adaptive are the foundation of a complex system.

Other books

Impávido by Jack Campbell
The Damned Highway by Nick Mamatas
Erica Spindler by In Silence
The Garden Path by Kitty Burns Florey
Flesh and Blood by Michael Lister