‡ Tom Magliozzi passed away in 2014 but the show lives on in reruns, where the two brothers are still laughing.
5
California Dreamin’
Sherwin Rosen was planning to spend the summer of 1977 at Stanford and invited me to join him out west to do some more work on the value of a life. At some point that spring I learned that Kahneman and Tversky were planning to spend the academic year at Stanford. After all the inspiration their work had provided me, I could not bear the thought of leaving town just before they arrived in September.
Over spring break I flew to California to investigate housing for the summer, and at the same time try to finagle a way to stay around Stanford during the fall semester. I hoped I might get to spend some time with the complete strangers who had become my new idols. I had sent Tversky an early draft of my first behavioral paper, which at the time carried the title “Consumer Choice: A Theory of Economists’ Behavior,” with the implicit suggestion that only economists behave like Econs. He had sent a short but friendly reply saying we were clearly thinking along similar lines, but that was it. In the days before email, it was much more difficult to initiate a long-distance conversation.
I spent a few days begging and pleading around campus for some kind of visiting position, but after two days I had nothing. I was about to give up when I had a conversation with the storied health economist Victor Fuchs, who was the director of the National Bureau of Economic Research (NBER) office, where Sherwin and I would be working. I gave Victor my best song and dance about the List, heuristics and biases, prospect theory, and the Israeli gods who were about to descend on Stanford. Victor either got intrigued or just took pity on me and offered to put me on his grant for the fall semester. After I arrived at Stanford in July, Victor and I had frequent discussions about my deviant thoughts, and in time he would extend his offer to pay my salary until the following summer.
The Thaler family took a leisurely trip across the country in June, hitting national parks along the way, and the drive offered time to let my mind wander about ways to combine psychology and economics. Any topic was fair game for pondering. For instance: Suppose I will drive 300 miles today. How fast should I drive? If I drive at 70 miles per hour instead of 60, we will get to our destination 43 minutes sooner, which seems like enough time saved to risk a speeding ticket. But when I have only 30 miles left to go, I will only save 4.3 minutes by driving faster. That doesn’t seem worth it. So, should I be gradually slowing down as I get closer to my destination? That can’t be right, especially since we are going to get back in the car and drive again tomorrow. Shouldn’t I have a uniform policy for the entire trip? Hmmm, put it on the List.*
Our trip’s final detour was to Eugene, Oregon, to see Baruch Fisch-hoff and Paul Slovic, the psychologists who had originally sparked my interest in these ideas. While the family explored the town, I chatted with Baruch, Paul, and their collaborator Sarah Lichtenstein. There was also another psychologist visiting their center who, like Fisch-hoff, had studied with Kahneman and Tversky in graduate school, Maya Bar-Hillel. All of them would join my informal team of psychology tutors in the coming years.
At the end of the summer, the Kahneman and Tversky psychology clan arrived in force. Amos and his wife, Barbara, were visiting the Stanford psychology department. Danny and his future wife, the eminent psychologist Anne Treisman, were to be visiting the Center for Advanced Study in the Behavioral Sciences, located just up the hill from NBER.
Victor Fuchs arranged the lunch where Amos, Danny, and I first met. I don’t remember much about it, except that I was uncharacteristically nervous. I can only trust that the voluble Vic kept the conversation moving. More important, the lunch introduction gave me license to walk up the hill and drop in on Danny. (Tversky’s office was on campus, too far away to just drop in.) He and Tversky were finishing the paper that by now they called “Prospect Theory,” and I would sometimes wander in while they were working. The Center’s primitive phone system made it easier to walk up the hill than to call Danny to see if he was around.
Sometimes when I stopped by to see Danny I would find the two of them at work, putting together the final version of prospect theory. When they were writing, with Danny at the keyboard, they would talk though each sentence, arguing about virtually every word. Their conversations were an odd mixture of Hebrew and English. An exchange in one language might suddenly switch to the other, with no acknowledgment of the flip. Sometimes the switch to English seemed related to the use of technical terms like “loss aversion,” for which they had not bothered to invent Hebrew equivalents. But I failed to generate a viable theory for why they would switch in the other direction. It might have helped to know some Hebrew.
They spent months polishing the paper. Most academics find getting the initial ideas the most enjoyable part of research, and conducting the actual research is almost as much fun. But few enjoy the writing, and it shows. To call academic writing dull is giving it too much credit. Yet to many, dull writing is a badge of honor. To write with flair signals that you don’t take your work seriously and readers shouldn’t either.† “Prospect Theory” is hardly an easy read, but the writing was crystal clear because of their endless editing and Amos’s perennial goal of “getting it right.”
Danny and I soon began the habit of taking walks in the hills near the Center just to talk. We were equally ignorant and curious about each other’s fields, so our conversations offered many learning opportunities. One aspect of these mutual training sessions involved understanding how members of the other profession think, and what it takes to convince them of some finding.
The use of hypothetical questions offers a good example. All of Kahneman and Tversky’s research up to this point relied on simple scenarios, such as: “Imagine that in addition to everything you now own, you gain $400. Now consider the choice between a sure loss of $200 or a gamble in which you have a 50% chance to lose $400 and a 50% chance to lose nothing.” (Most choose to gamble in this situation.) As Kahneman delightfully explains in his book Thinking, Fast and Slow, they would try these thought experiments out on themselves and if they agreed on an answer they would provisionally assume that others would answer the same way. Then they would check by asking subjects, typically students.
Economists do not put much stock in the answers to hypothetical questions, or survey questions in general for that matter. Economists say they care more about what people do as opposed to what they say they would do. Kahneman and Tversky were aware of the objections, undoubtedly raised by skeptical economists they had met, but they had little choice. A key prediction of prospect theory is that people react differently to losses than they do to gains. But it is nearly impossible to get permission to run experiments in which subjects might actually lose substantial amounts of money. Even if people were willing to participate, the university committees that review experiments using human subjects might not approve the experiments.
In the published version of prospect theory, Amos and Danny included the following defense of their methods: “By default, the method of hypothetical choices emerges as the simplest procedure by which a large number of theoretical questions can be investigated. The use of the method relies on the assumption that people often know how they would behave in actual situations of choice, and on the further assumption that the subjects have no special reason to disguise their true preferences.” Essentially, they were saying that if their subjects were reasonably accurate in predicting the choices they would actually make in such cases, and their indicated choices were inconsistent with expected utility theory, then that should at least create a presumption of doubt about whether the theory is a good description of behavior.
This defense apparently satisfied the journal editor but remained a bugaboo among economists for years. Prospect theory gradually gained acceptance because it proved useful in explaining behavior in a variety of high-stakes settings where it was possible to observe actual choices, from individual investors to game show
contestants. But I don’t think any economist would have come up with this theory, even granting them Kahneman and Tversky’s psychological insights. An unwillingness to rely on hypothetical questions would have kept them from learning the nuances of behavior that Kahneman and Tversky were able to discern.
I found the idea that you could just ask people questions and take their answers seriously to be quite liberating. Up to then, the items on the List were merely thought experiments. It seemed obvious to me that if readers were confronted with one of my hypothetical examples, they would check their intuition and then agree that the behavior existed. (This was, of course, naïve.) And, although the survey method was not considered authoritative, it was surely better than a survey of my own intuitions.
A few years later I got a nice lesson on how to do this from the masters themselves. They took my clock radio and television shopping example from the List and turned it into shopping for a jacket and a calculator, and then asked people what they would do. Here it is, with two different versions indicated by the numbers in parentheses or brackets:
Imagine that you are about to purchase a jacket for ($125)[$15] and a calculator for ($15)[$125]. The calculator salesman informs you that the calculator you wish to buy is on sale for ($10)[$120] at the other branch of the store, located a twenty-minute drive away. Would you make the trip to the other store?
Sure enough, real subjects said they would be more willing to take the drive to save $10 on the cheaper item, as I had conjectured, and now there was data to support it. I soon started using this method as well, though sparingly. But Danny and I would rely almost exclusively on the answers to hypothetical questions seven years later in a project about perceptions of fairness, discussed in chapter 14.
When I was not wandering the hills with Danny, I was hunkered down at NBER with nothing to do but think. Victor Fuchs played the role of guilt-inducing Jewish mother, periodically asking me about my progress. A paradox confronted me. I had what I thought was a big idea, but research proceeds through a series of small steps. And I did not know which small steps would advance the big idea. Big ideas are fine, but I needed to publish papers to stay employed. Looking back, I had what science writer Steven Johnson calls a “slow hunch.” A slow hunch is not one of those “aha” insights when everything becomes clear. Instead, it is more of a vague impression that there is something interesting going on, and an intuition that there could be something important lurking not far away. The problem with a slow hunch is you have no way to know whether it will lead to a dead end. I felt like I had arrived on the shores of a new world with no map, no idea where I should be looking, and no idea whether I would find anything of value.
Kahneman and Tversky ran experiments, so it was natural to think that I should be running experiments, too. I reached out to the two founders of the then nascent field called experimental economics, Charlie Plott at Caltech and Vernon Smith, then at the University of Arizona. Economists traditionally have used historical data to test hypotheses. Smith and Plott were practitioners of and proselytizers for the idea that one could test economic ideas in the laboratory. I first took a trip down to Tucson to visit Smith.
Smith’s research agenda was, at least at that time, different from the one I was imagining for myself. When he and Danny shared the Nobel Prize in economics many years later, I told a reporter that the difference between their respective research agendas that won them the prize was that Smith was trying to show how well economic theory worked and Kahneman was doing the opposite.‡
At the time I visited him, Smith advocated using something he called the induced value methodology. Instead of trading actual goods or gambles, markets were created for tokens, in which each subject was given their own private value for a token. My token might be worth $8 while yours would be worth $4, meaning that these were the amounts we would receive from the experimenter if we ended up holding a token at the end of the study. Using this method, Smith was able to test economic principles such as supply and demand analysis. But I had some worries about this methodology. When you go to the store and decide whether to buy a jacket for $49, no one is telling you how much you are willing to pay for it. You have to decide that for yourself, and that value might depend on all sorts of issues such as what the retail price of the product is, how much you have already spent on clothing this month, and whether you happened to have just gotten your tax refund. Many years later I finally got around to testing my concern about this method by replacing tokens with coffee mugs, as we will see in chapter 16.
I then combined a family trip to Disneyland with a pilgrimage to Caltech to meet Charlie Plott, who was also pioneering this field (and could easily have shared the Nobel Prize with Smith). Perhaps because of the Caltech setting, Plott liked to use a wind tunnel analogy to describe what he was doing. Rather than showing that the basic principles of economics worked in the lab, he was more interested in testing what happened when the rules of the market were changed. Charlie, for whom the word garrulous seems to have been invented, was also warm and friendly.
As kind and impressive as Smith and Plott were, I was not ready to declare myself to be exclusively, or even primarily, an experimental economist. I wanted to study “behavior” and remain open-minded about the techniques I would use. I planned to run experiments when that method seemed to be the best way of observing behavior, or sometimes to just ask people questions, but I also wanted to study the behavior of people in their natural habitats . . . if I could just figure out how to do it.
At some point during my year in Stanford I decided I was going “all in” on this new venture. The University of Rochester was not an ideal venue given the intellectual proclivities of the senior faculty, who were deeply wedded to traditional economic methodology, so I looked elsewhere.§
When you interview for a job in academia you present a paper in a faculty workshop, and that presentation, along with the papers you have written, determines whether you will get the job. My “Value of a Life” paper with Rosen was already pretty widely known, and I could have played it safe by presenting some additional work on that topic, but I wanted an environment that would tolerate a little heresy, so I presented a paper about the economics of self-control, cashews and all. Any place that would hire me after hearing that paper was likely to be at least moderately open to what came next. Fortunately, offers arrived from Cornell and Duke, and I settled on Cornell. My next move would be 90 miles down the road from Rochester.
________________
* Answer: Drive the same speed the whole way. The chance of getting a ticket is proportional to the time you are driving, holding everything else constant.
† There are, of course, exceptions to this generalization. In that era, George Stigler and Tom Schelling come to mind as great writers.
‡ I was referring to Smith’s early work, cited by the Nobel committee. Later he delved into other more radical areas, including a series of experiments in which he could reliably produce an asset pricing bubble (Smith, Suchanek, and Gerry, 1998).
§ Academic insiders might wonder how I landed a job in the Rochester business school after being a student in the economics department. Universities usually do not hire their own graduates. The answer is a long story, the short version of which is that I had been teaching at the business school while a graduate student, and when my first job fell through at the last minute, Bill Meckling, the school’s dean, offered me a one-year position as a stopgap measure, and I ended up sticking around for a few more years.
6
The Gauntlet
I accepted the job at Cornell about halfway through my time at Stanford, and would start there in August 1978. I had work to do on two fronts. First, I had to produce research that showed what we could learn from the new approach I was suggesting. Second, and just as important, I had to be able to offer convincing replies to a series of one-line putdowns I would hear almost any time I presented my research. Economists had their way of doing things and would resist change, if for no
other reason than that they had invested years building their own particular corner of this edifice.
This fact was brought home to me at one early conference where I gave a talk on my recent work. During the question and answer period that followed, a well-known economist asked me a question: “If I take what you are saying seriously, what am I supposed to do? My skill is knowing how to solve optimization problems.” His point was that if I were right, and optimization models were poor descriptions of actual behavior, his toolkit would be obsolete.
His reaction was unusually candid. The more common response, for those who engaged at all, was to explain what I was doing wrong, and what obvious factors I had ignored. I soon had another list: reasons why economists could safely ignore behaviors such as those on the List. Among friends I would call this series of questions the Gauntlet, since any time I gave a talk about my work it felt like running a medieval gauntlet. Here are a few of the most important ones, along with the preliminary responses I had worked up at the time. To some extent people are still arguing about these points; you will see them reappear throughout the book.
As if
One of the most prominent of the putdowns had only two words: “as if.” Briefly stated, the argument is that even if people are not capable of actually solving the complex problems that economists assume they can handle, they behave “as if” they can.
To understand the “as if” critique, it is helpful to look back a bit into the history of economics. The discipline underwent something of a revolution after World War II. Economists led by Kenneth Arrow, John Hicks, and Paul Samuelson accelerated an ongoing trend of making economic theory more mathematically formal. The two central concepts of economics remained the same—namely, that agents optimize and markets reach a stable equilibrium—but economists became more sophisticated in their ability to characterize the optimal solutions to problems as well as to determine the conditions under which a market will reach an equilibrium.
Misbehaving: The Making of Behavioral Economics Page 5
