Priceless: The Myth of Fair Value (and How to Take Advantage of It) (8 page)

When someone is given a free choice between A and B, he simply consults his invisible price tags and chooses the one with the higher utility. Decision making is thus reduced to numbers. This assumption leads naturally to most of the standbys of economic theory, from demand curves to the Nash equilibrium.

That brings us back to von Neumann’s contribution. Many economic choices are gambles. Given our uncertain world, the difficult and interesting choices are
always
gambles of one kind or another. It is therefore necessary to assign prices to gambles. According to von Neumann, the way to do this is to multiply each possible outcome’s subjective price by its probability, and total the results.

Von Neumann and Morgenstern maintained that every rational person uses this kind of mental math (the “expected utility model”) to make decisions, from deciding what to order for lunch to what stock to invest in. This premise became the mainspring of their economic theory, a model that economists embraced in the postwar years.

Not all economists applauded the new regime. Herbert Simon was one of the earliest, loudest, most down-to-earth critics of economics’ cult of rationality. In a review of von Neumann’s book, Simon complained that it is “impossible for the behavior of a single, isolated individual to reach any high degree of rationality.” Simon was equally harsh on the tradition that von Neumann was partly upending. “How any grown-up, bright human being can go satisfied with the neoclassical theory is kind of hard to understand,” he marveled.

Simon’s own career-keynote book,
Administrative Behavior
, was published three years after von Neumann’s. It could hardly have presented a more different picture of the “games” people play. Simon analyzed case
studies of how corporations and other hierarchies made decisions. His most enduring sound bite is that humans are “boundedly rational.” They are too busy, too ill-informed, and occasionally too boneheaded to think things through in the way that von Neumann proposed. Authentic humans don’t show the perfect, chessmaster appreciation of consequences that von Neumann’s theory demands. Instead, decision makers resort to
heuristics
, or mental shortcuts, to arrive at quick, intuitive choices.

Simon was feinting at the path that psychologists would soon take. He didn’t go there himself. For one thing, Simon did not see himself as an experimentalist. Second, he viewed human rationality as being like military intelligence: an oxymoron. Simon held that it was organizations rather than individuals that attained rationality, and thus it was organizations that interested him. These organizations were like anthills, able to muster collective “intelligence” from rather unpromising individual resources.

Ward Edwards was never entirely comfortable fitting into the organizations that so intrigued Simon. Edwards had been fired from his first job, at Johns Hopkins, for lackadaisical teaching. He then found a post with the Air Force in Denver, working for a cryptic bureau called the Intellectual Functions Section. Edwards later claimed that landing the Air Force job was the most fortunate thing that ever happened to him. It exposed him to a constant stream of decision-making problems.

Edwards once visited NORAD, the nuclear defense command center in Colorado Springs. He was curious to see how some of the world’s most momentous decisions got made. Edwards was ushered into the command center, dominated by a
Dr. Strangelove
map displaying military information collected from distant early warning radar and ships at sea. In those pre-Google days, the volume of real-time information was mesmerizing. Edwards asked the officer escorting him what was done with all that information. His escort pointed to a red telephone, apparently a direct line to the White House. Edwards asked, “Do you think the ratio of input to output information should be like that?”

Edwards had not gained much academic renown by the time he moved to the University of Michigan’s psychology department. “Michigan
was a large department, very tolerant and very open,” psychologist Barbara Tversky explained. Even in that most liberal context, Edwards stood out. He “was nutty—not really socialized.” Two associates recalled that Edwards’s “occasional colorful and forthright behavior” perpetually threatened to derail tenure.

With his free-spirted wife, Ruth (a Ph.D. student of B. F. Skinner’s), Edwards lived in bohemian splendor. At one point the couple inhabited a dusty building behind a garage, in an industrial part of Ann Arbor; at another, a ruinous farmhouse. The Edwardses raised dachshunds, one named Willy (after psychophysicist Wilhelm Wundt, of course). Dinner parties featured “Ruth’s excellent, if often exotic cooking, with the early arrivals required to light dozens of candles placed on every horizontal surface in living and dining rooms.”

Edwards is usually credited as the founder of behavioral decision theory. It was certainly he who lent the nascent field a name, in the form of the title of a 1961 paper. But others were exploring decision making, at Michigan and elsewhere.

Many of the early experiments involved gambling. A researcher needs a way of getting subjects’ attention in a psychological experiment. A small money prize, that might be won or might not, is an effective motivator. Edwards and Michigan colleague Clyde Coombs did experiments in which volunteers had to choose between gambles or assign prices to them. Sarah Lichtenstein, who took her Ph.D. under Edwards, has the impression that Coombs (“a marvelous person”) was not interested in gambling per se. Gambles simply offered a handy way of creating decision problems. Edwards “was actually interested in the economic theories of decision making.”

In deciding how much to pay for a car or whom to marry, there are always trade-offs—a process of “comparing incomparables,” in Coombs’s words. Gambles offer an obvious trade-off between the money to be won and the chance of winning it. So Coombs and Edwards would have volunteers choose between a gamble with a bigger prize and another with a better chance of winning. The psychologists sifted the stated preferences and tried to discern how people decided. A 1960 study by Coombs and D. G. Pruitt found that most of the choices could be explained by simple rules such as “Always choose the bet with the highest payoff for winning.”

Welcome to the world of bounded rationality. Anyone who followed this rule was ignoring the odds—betting on the long shots, no matter what. That policy doesn’t work well at the racetrack, and it’s not much better elsewhere.

Edwards learned poker at the Air Force job and remained an enthusiastic player at Michigan. The game provided some of his experimental supplies. One of Edwards’s best-known experiments involved two backpacks filled with equal numbers of poker chips. One of the backpacks contains mostly red chips—say, 70 percent red and 30 percent white. The other is mostly white chips, with the percentages reversed. You don’t know which backpack is which. Your task is to decide which is the mostly red backpack. To do that, you draw chips one at a time from one backpack. You must estimate the odds as you go. It’s as if you’re a bookmaker and have to quote the current point spread. Edwards had students do that as he carefully kept track of the colors of the chips drawn.

Imagine you’re drawing from backpack #1. The first chip you draw is red. That bumps up the probability that this backpack is the mostly red one. How much?

The correct answer is simpler than you might think. It’s 70 percent exactly. But this wasn’t intended as a math puzzle. Most decisions are made by gut, and Edwards wanted to see how accurate these gut instincts were. He found that guesses tended to be less than the correct value. People failed to appreciate that a single red chip could be as informative as it actually is.

This confirmed Edwards’s suspicion that people are not especially good at making decisions under uncertainty. But that is exactly what von Neumann and much of the economic profession were taking as a given.

In a 1954
Psychological Bulletin
article, Edwards sketched the von Neumann–Morgenstern model—few of his psychologist readers would have known much about it—and posed the rhetorical question of whether it had the slightest thing to do with reality. “The method of those theorists who have been concerned with the theory of decision making is essentially an armchair method,” Edwards complained. “They make assumptions, and from these assumptions they deduce theorems which can presumably be tested, though it sometimes seems unlikely the testing will ever occur.”

High among the untested assumptions was that humans behave like the fiction known as an
economic man
(
Homo economicus
) or
rational actor
or
rational maximizer
. This is a worker/capitalist/consumer/game-player concerned exclusively with personal gain. In Robert Heilbroner’s words, economic man was “a pale wraith of a creature who followed his adding machine brain wherever it led him.” That adding machine brain enabled economic men to calculate expected utility for decisions big and trivial.

“Von Neumann and Morgenstern defended this model and, thus, made it important,” Edwards wrote, “but [by] 1954 it was already clear that it . . . does not fit the facts.”

That year of 1954 was not chosen casually. It was the date of Edwards’s pivotal
Psychological Bulletin
paper, and it must also allude, in part, to what we now call Allais’ paradox. That deserves a chapter of its own.

In 1952, Leonard “Jimmie” Savage had one of the most excruciating lunches of his life. Savage was a thirty-five-year-old American in Paris attending an academic conference. Seated across the table from him was a man with the expression of a startled terrier. He was Maurice Allais, a forty-one-year-old French economist. Allais had his hair trimmed up the sides of his head, leaving a bushy flat top. Between the trick haircut and the tight smile that might be a frown, Allais’ face evoked one of those odd pictures that becomes a different face when turned upside down.

Allais had told Savage he had something to show him. It was a little test he wanted him to take. The important thing is that Savage failed the test.

Savage was a brash statistician, then at the University of Chicago. He had gone into statistics on the advice of John von Neumann himself. Visually, the most remarkable thing about him was his eyeglasses. Their lenses packed enough diopters to reveal the space behind his head. At Chicago, Savage had acquired a second mentor, Milton Friedman—founding father of the Chicago school of economics, future Nobel laureate, and veritable saint to Reagan-era capitalists. Friedman knew quite a bit of statistics for an economist. He and Savage had begun a peripatetic collaboration. Savage was attempting to devise a theory of how people make decisions. The decisions that concerned him tended to be about money. He was interested in how people assign prices to goods and services and how they make choices between them. Savage wanted to show that decisions about money were (or could be) completely logical. Friedman desired just such a theory. It would supply a firm foundation to his utopian economics of the free market.

There was one big problem with that, Allais told Savage: his theory was dead
wrong
.

Proving theories wrong was a hobby with Allais. His parents had owned a cheese shop, and he had worked eighty-hour weeks—while holding down administrative posts with the French bureau of mines—writing the iconoclastic economic works that secured his renown, and ultimately a Nobel Prize. Allais did not limit himself to disproving wrong ideas in economics. He was just then embarking on a grand quest to disprove Einstein’s theory of relativity. Allais devised a special pendulum that would one day show Einstein’s error, or so he believed. He would spend much of the 1950s attempting to demonstrate that Einstein had cribbed relativity (for what it’s worth) from that great Frenchman Henri Poincaré.

Proving that Savage’s theory was wrong was much simpler. Like a troll in a fairy tale, Allais posed three riddles.

I will use a streamlined version of the questions Allais published the following year, putting the money amounts in dollars. Though not identical to the riddles Allais posed to Savage, they will give you the flavor of his argument.

Riddle one: Which of the following would you rather have?

(a) A sure $1 million
—
or
—

(b) This gamble: We spin a wheel of fortune with 100 slots. You have an 89 percent chance of winning $1 million, a 10 percent chance of winning $2.5 million, and a 1 percent chance of winning nothing at all.

Allais believed that most people would choose (a), the sure million, over (b), which offers a small chance of ending up with nothing. Apparently, Savage agreed.

Riddle two: This time your choice is

(a) An 11 percent chance of winning $1 million
—
or
—

(b) a 10 percent chance of winning $2.5 million.

Allais thought that most people would choose (b). There isn’t much difference in the chances. You might as well go for the higher prize in
(b). Again Savage concurred. In so doing, he fell into the Frenchman’s trap.

This brings us to Riddle 3. In front of you is a sealed box. Which would you rather have?

(a) An 89 percent chance of winning whatever is in the box, and an 11 percent chance of winning $1 million instead
—
or
—

(b) An 89 percent chance of winning what’s in the box, a 10 percent chance of winning $2.5 million, and a 1 percent chance of winning nothing at all.