Misbehaving: The Making of Behavioral Economics by Richard H. Thaler Read Free Book Online Page B

day, the phrase “survey evidence” is rarely heard in economics circles without the necessary adjective “mere,” which rhymes with “sneer.” This disdain is simply unscientific. Polling data, which just comes from asking people whether they are planning to vote and for whom, when carefully used by skilled statisticians such as Nate Silver, yield remarkably accurate predictions of elections. The most amusing aspect of this anti-survey attitude is that many important macroeconomic variables are produced by surveys!
    For instance, in America the press often obsesses over the monthly announcement of the latest “jobs” data, with serious-looking economists asked to weigh in about how to interpret the figures. Where do these jobs numbers come from? They come from surveys conducted by the Census Bureau. The unemployment rate, one of the key variables in macroeconomic modeling, is also determined from a survey that asks people whether they are looking for work. Yet using published unemployment rate data is not considered a faux pas in macro-economics. Apparently economists don’t mind survey data as long as someone other than the researcher collected it.
    But in 1980, survey questions were not going to overcome the “as if” grunt. There would need to be some proper data brought to bear that demonstrated that people misbehaved in their real-life choices.
    Incentives
    Economists put great stock in incentives. If the stakes are raised, the argument goes, people will have greater incentive to think harder, ask for help, or do what is necessary to get the problem right. Kahne-man and Tversky’s experiments were typically done with nothing at stake, so for economists that meant they could be safely ignored. And if actual incentives were introduced in a laboratory setting, the stakes were typically low, just a few dollars. Surely, it was often said, if the stakes were raised, people would get stuff right. This assertion, unsupported by any evidence, was firmly believed, even in spite of the fact that nothing in the theory or practice of economics suggested that economics only applies to large-stakes problems. Economic theory should work just as well for purchases of popcorn as for automobiles.
    Two Caltech economists provided some early evidence against this line of attack: David Grether and Charlie Plott, one of my experimental economics tutors. Grether and Plott had come across research conducted by two of my psychology mentors, Sarah Lichtenstein and Paul Slovic. Lichtenstein and Slovic had discovered “preference reversals,” a phenomenon that proved disconcerting to economists. In brief, subjects were induced to say that they preferred choice A to choice B . . . and also that they preferred B to A.
    This finding upset a theoretical foundation essential to any formal economic theory, namely that people have what are called “well-defined preferences,” which simply means that we consistently know what we like. Economists don’t care whether you like a firm mattress better than a soft one or vice versa, but they cannot tolerate you saying that you like a firm mattress better than a soft one and a soft one better than a firm one. That will not do. Economic theory textbooks would stop on the first page if the assumption of well-ordered preferences had to be abandoned, because without stable preferences there is nothing to be optimized.
    Lichtenstein and Slovic elicited preference reversals when they presented subjects with a pair of gambles: one a relatively sure thing, such as a 97% chance to win $10, and the other more risky, such as a 37% chance to win $30. They called the near sure thing the “p” bet, for high probability, and the more risky gamble the “$” bet, since it offered a chance to win more money. First they asked people which gamble they preferred. Most took the p bet since they liked an almost sure win. For these subjects this means p is preferred to $. Then they asked these p bet–loving