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COPYRIGHT NOTICE: Edited by Richard H. Thaler: Advances in Behavioral Finance, Volume II - page 16 / 23





16 / 23



Belief Perseverance. There is much evidence that once people have formed an opinion, they cling to it too tightly and for too long (Lord, Ross, and Lepper 1979). At least two effects appear to be at work. First, people are reluctant to search for evidence that contradicts their beliefs. Second, even if they find such evidence, they treat it with excessive skepticism. Some studies have found an even stronger effect, known as confirmation bias, whereby people misinterpret evidence that goes against their hypothesis as actually being in their favor. In the context of academic finance, belief per- severance predicts that if people start out believing in the Efficient Markets Hypothesis, they may continue to believe in it long after compelling evi- dence to the contrary has emerged.

Anchoring. Kahneman and Tversky (1974) argue that when forming esti- mates, people often start with some initial, possibly arbitrary value, and then adjust away from it. Experimental evidence shows that the adjustment is often insufficient. Put differently, people “anchor” too much on the ini- tial value.

In one experiment, subjects were asked to estimate the percentage of United Nations countries that are African. More specifically, before giving a percentage, they were asked whether their guess was higher or lower than a randomly generated number between 0 and 100. Their subsequent esti- mates were significantly affected by the initial random number. Those who were asked to compare their estimate to 10, subsequently estimated 25 per- cent, while those who compared to 60, estimated 45 percent.

Availability Biases. When judging the probability of an event—the likeli- hood of getting mugged in Chicago, say—people often search their memo- ries for relevant information. While this is a perfectly sensible procedure, it can produce biased estimates because not all memories are equally retriev- able or “available,” in the language of Kahneman and Tversky (1974). More recent events and more salient events—the mugging of a close friend, say—will weigh more heavily and distort the estimate.

Economists are sometimes wary of this body of experimental evidence be- cause they believe (1) that people, through repetition, will learn their way out of biases; (2) that experts in a field, such as traders in an investment bank, will make fewer errors; and (3) that with more powerful incentives, the effects will disappear.

While all these factors can attenuate biases to some extent, there is little evidence that they wipe them out altogether. The effect of learning is often muted by errors of application: when the bias is explained, people often understand it, but then immediately proceed to violate it again in specific applications. Expertise, too, is often a hindrance rather than a help: experts, armed with their sophisticated models, have been found to

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