One way of modeling bounded rationality is to reduce the informationprocessing capabilities of the agents; for example, in the case of the numbers game discussed earlier, by assuming that individuals will only do two steps of backward induction rather than infinite steps. This is a sensible initial approach, but we can do more that make HE dumber.
A more interesting research agenda is to attempt richer characterizations of economic agents via a better understanding of human cognition. This, I predict, will be a major area of effort over the next two decades. Some successful examples published in the last 20 years prove that this kind of work is both feasible and useful. The most significant exemplar is the “prospect theory” of Daniel Kahneman and Amos Tversky (1979). This positive theory of decision-making under uncertainty manages to capture an enormous amount of psychological wisdom in its S-shaped “value function.” The value function shows changes in material well-being on the horizontal axis, rather than levels as in expected utility theory, because humans (and other species) have a strong tendency to adapt to their environment and react only to perceived changes. The vertical axis shows happiness resulting from these changes.
The S-shape displays diminishing marginal sensitivity to both gains and losses, a basic finding in the psychology of perception (psychophysics). Finally, the loss function is steeper than the gain function, a property that has come to be known as loss aversion. Losses hurt about twice as much as gains make us feel good. These three psychological concepts yield plenty of explanatory power, having been used to explain as diverse phenomena as consumers reaction to price changes in the supermarket to the labor supply behavior of cab drivers (Camerer, forthcoming).
There are an enormous number of exciting ways in which a better understanding of human cognition could help us do better economics. I’ll suggest two here. First, there is a problem with prospect theory that cognitive psychology might help us fix; namely, the theory is incomplete. Prospect theory tells us that choices depend on the framing of a problem, but does not tell us how people will spontaneously create their own frames. By directly studying how people attack decision-making problems, we may learn more about this problem-editing process.[2]
Second, though we have given considerable attention in recent years to the implications of bounded rationality, we have spent less time studying the impact of bounded memories. A simple example is “hindsight bias”: after the fact, events that happen are thought to have been predictable. For example, one year in my class I asked my students on the first day of class (in late January) to make predictions about stock market returns for the next two months. Their forecasts were bearish: they thought it was more likely that the market would go down than up. Two months later I asked them to try to recall their earlier forecast. They remembered being bullish. Needless to say, the market rose sharply over this two month period.
This phenomenon (related to the curse of knowledge mentioned earlier) is both strong and robust, and has powerful implications for economics. Consider, for example, the role of hindsight bias in agency problems. A principal with a biased memory (that is, any real world principal) will find it very difficult to distinguish between a bad decision and a bad outcome, since an unlucky exogenous event will be thought, in hindsight, to have been predictable. Agency theory with absentminded principals (and agents) would be an exciting field of inquiry.[3]
2 Some of what we know about this problem falls into the category of “mental accounting.” For a current review of this literature, see Thaler (1999).
3 For a clever example of what absent-minded economics might look like, see Mullainathon (1999).
Prof. Richard H. Thaler
Next: Economists Will Distinguish Between Normative and Descriptive Theories
Summary: Index