Misbehaving: The Making of Behavioral Economics by Richard H. Thaler
Authors: Richard H. Thaler
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subjects: “Suppose you owned the p bet. What is the lowest price at which you would be willing to sell it?” They also asked them the same question for the $ bet. Strangely, a majority of these subjects demanded more to give up the $ bet than the p bet, indicating they liked the $ bet more. But this means they prefer the p bet to the $ bet, and the $ bet to the p bet. Blasphemy!
Grether and Plott wanted to know what was driving these weird results, and their leading hypothesis was incentives. * If the bets were real, they conjectured, this nonsense would stop. So they ran the experiments for real money, and much to their surprise, the frequency and severity of the preference reversals actually increased. Raising the stakes made things worse.
This did not put an end to the incentive objection. But at least there was one paper to cite disputing the claim that money would solve all of the problems economists had with behavioral research. And, as we will see, this has been very much a recurring theme in the debate about the validity of experimental evidence.
Learning
The style of experiment Kahneman and Tversky ran was often faulted as a “one-shot” game. In the “real world,” economists argued, people have opportunities to learn. The idea is reasonable enough. We don’t start out life as good drivers, but most of us do learn to drive without frequent mishaps. The fact that a clever psychologist can devise a question that will lure people in the lab into making a mistake does not necessarily imply that the same mistake would be made in the “real world.” (Laboratories are thought to be unreal worlds.) Out there, people have had lots of time to practice their decision-making tasks, so they won’t make the mistakes we see in the lab.
The problem with the learning story is that it assumes that we all live in a world like the Bill Murray movie Groundhog Day . Bill Murray’s character keeps waking up and reliving the same day, over and over. Once he figures out what is going on, he is able to learn because he can vary things one at a time and see what happens. Real life is not as controlled as that, and thankfully so. But as a result, learning can be difficult.
Psychologists tell us that in order to learn from experience, two ingredients are necessary: frequent practice and immediate feedback. When these conditions are present, such as when we learn to ride a bike or drive a car, we learn, possibly with some mishaps along the way. But many of life’s problems do not offer these opportunities, which raises an interesting point. The learning and incentives arguments are, to some extent, contradictory. This first occurred to me in a public debate of sorts that I had with the British game theorist Ken Binmore.
At a conference organized for graduate students, Binmore and I were each giving one lecture a day. I was presenting new findings of behavioral economics and although Binmore was presenting unrelated work, he took the opportunity at the beginning of each of his lectures to reply to the one I had given the day before. After my first lecture, Binmore offered a version of the “low stakes” critique. He said that if he were running a supermarket, he would want to consult my research because, for inexpensive purchases, the things I studied might possibly matter. But if he were running an automobile dealership, my research would be of little relevance. At high stakes people would get stuff right.
The next day I presented what I now call the “Binmore continuum” in his honor. I wrote a list of products on the blackboard that varied from left to right based on frequency of purchase. On the left I started with cafeteria lunch (daily), then milk and bread (twice a week), and so forth up to sweaters, cars, and homes, career choices, and spouses (not more than two or three per lifetime for most of us). Notice the trend. We do small stuff often enough to learn to get it right, but when it comes to choosing a home, a
Grether and Plott wanted to know what was driving these weird results, and their leading hypothesis was incentives. * If the bets were real, they conjectured, this nonsense would stop. So they ran the experiments for real money, and much to their surprise, the frequency and severity of the preference reversals actually increased. Raising the stakes made things worse.
This did not put an end to the incentive objection. But at least there was one paper to cite disputing the claim that money would solve all of the problems economists had with behavioral research. And, as we will see, this has been very much a recurring theme in the debate about the validity of experimental evidence.
Learning
The style of experiment Kahneman and Tversky ran was often faulted as a “one-shot” game. In the “real world,” economists argued, people have opportunities to learn. The idea is reasonable enough. We don’t start out life as good drivers, but most of us do learn to drive without frequent mishaps. The fact that a clever psychologist can devise a question that will lure people in the lab into making a mistake does not necessarily imply that the same mistake would be made in the “real world.” (Laboratories are thought to be unreal worlds.) Out there, people have had lots of time to practice their decision-making tasks, so they won’t make the mistakes we see in the lab.
The problem with the learning story is that it assumes that we all live in a world like the Bill Murray movie Groundhog Day . Bill Murray’s character keeps waking up and reliving the same day, over and over. Once he figures out what is going on, he is able to learn because he can vary things one at a time and see what happens. Real life is not as controlled as that, and thankfully so. But as a result, learning can be difficult.
Psychologists tell us that in order to learn from experience, two ingredients are necessary: frequent practice and immediate feedback. When these conditions are present, such as when we learn to ride a bike or drive a car, we learn, possibly with some mishaps along the way. But many of life’s problems do not offer these opportunities, which raises an interesting point. The learning and incentives arguments are, to some extent, contradictory. This first occurred to me in a public debate of sorts that I had with the British game theorist Ken Binmore.
At a conference organized for graduate students, Binmore and I were each giving one lecture a day. I was presenting new findings of behavioral economics and although Binmore was presenting unrelated work, he took the opportunity at the beginning of each of his lectures to reply to the one I had given the day before. After my first lecture, Binmore offered a version of the “low stakes” critique. He said that if he were running a supermarket, he would want to consult my research because, for inexpensive purchases, the things I studied might possibly matter. But if he were running an automobile dealership, my research would be of little relevance. At high stakes people would get stuff right.
The next day I presented what I now call the “Binmore continuum” in his honor. I wrote a list of products on the blackboard that varied from left to right based on frequency of purchase. On the left I started with cafeteria lunch (daily), then milk and bread (twice a week), and so forth up to sweaters, cars, and homes, career choices, and spouses (not more than two or three per lifetime for most of us). Notice the trend. We do small stuff often enough to learn to get it right, but when it comes to choosing a home, a
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