Economics in the first half of the 20th century was much more of a social science. Writers such as Irving Fisher and John Maynard Keynes stressed psychological factors in their explanations of economic behavior (Loewenstein, 1992). With the mathematical revolution that began to take off in the 1940s with the likes of John Hicks and Paul Samuelson, economic agents began to be more explicitly optimizing. In the 1950s, economists who began formalizing the micro foundations of Keynes developed more rational models; for example, compare Keynes’s simple consumption function with the life-cycle hypothesis, and then with the rational expectations hypothesis of Muth, Lucas, and so on.
Eventually the models came to include agents that detractors called “hyperrational.” The aesthetic in the field became that if the agents in model A are smarter than the agents in Model B, then Model A is better than Model B. The IQ of Homo Economicus became bounded only by the IQ of the smartest economic theorist! My prediction is that this trend will be reversed in favor of an approach in which the degree of rationality bestowed to the agents depends on the context being studied. To illustrate how this can work in practice, consider the “guess the number” game first studied by Rosemarie Nagel (1995).
In this game, contestants are told to guess a number from 0 to 100, with the goal of making their guess as close as possible to two-thirds of the average guess. In a world where all the players are known to be fully rational, in the sense that they will form expectations about the guesses of others can carry out as many levels of deduction as necessary, the equilibrium in this game is zero. In any other setting, however, guessing zero is not a good strategy. Recently, I had the opportunity to play this game for quite large stakes (Thaler, 1997).
At my request, the Financial Times ran a “guess the number” game contest using the rules described above and offered two business class tickets from London to the United States as a prize (worth over $10,000). Only integer guesses were permitted. Although many contestants did guess zero or one, the most popular guesses were 33 (the right guess if everyone else chooses a number at random) and 22 (the right guess if everyone else picks 33). The average guess was 18.91 and thus the winning guess was 13. Although modeling how this game is actually played is not easy, some lessons are clear enough. An appropriate model would have to allow for two kinds of heterogeneity in sophistication.
First, agents differ in how many levels of processing they engage in (33 is one level, 22 is two levels, and so on).
Second, there is heterogeneity in how much agents think about the behavior of other agents. Agents who guess zero are sophisticated on the first dimension and naı¨ve on the second. Many economists fall into this category (due in part to the False Consensus Effect and the Curse of Knowledge!) Sophisticated economic models will have agents that are both more and less sophisticated than the agents we are used to modeling. I predict this sort of modeling will be the norm in the future.
Prof. Richard H. Thaler