Irrational Economist_ Making Decisions in a Dangerous World - Erwann Michel-Kerjan [43]
Another thing researchers can do with attentional data is try to predict from what people look at what they are likely to do. We did this in the 2002 paper, which summarizes the results in a series of “icon graphs” and associated histograms showing the frequency of various offer amounts. We sorted trials into four groups based on lookup patterns. One group (“Zero”) looked at the first stage (labeled 1) the most often. The rightmost group (“Trained”) looked at the third stage the most often; at the second stage, the second most often; and at the first stage, the least often. Looking more and more at future stages yields offer distributions that slide from the equal split of $2.50 toward the perfect equilibrium of $1.25.
Two other groups of economists have published eye-tracking results since our 2002 study.3 Nonetheless, I am a little surprised that this tool has not been used more often. Many rational choice and behavioral theories make predictions about sets of information that either must be attended to or could be ignored. This is especially true in game theory.
Sometimes these debates about why naïve choices are being made can be resolved much more rapidly by a series of carefully designed studies with eye-tracking (and response times as well) than with a much longer series of studies that use only choice data.
Economists have often wondered about decisions involving uncertainty versus risk and the distinction between the implications of evidence and the weight of evidence. American economist Daniel Ellsberg drew attention to the difficulty of modeling ambiguity (his term) using subjective probability with an elegant paradox.
In one version (Hsu et al., 2005), subjects were asked whether they would rather have $3 for sure or choose to bet $10 that the temperature was above 55 degrees or below 55 degrees in New York on a particular day (i.e., they would win $10 if they were right). Other subjects were asked a similar question, but about the temperature in Dushanbe, Tajikistan. More subjects chose to bet on New York rather than on Tajikistan.
Call the New York bet “risky” and the Dushanbe bet “ambiguous.” Subjects generally preferred to bet on either side of the New York bet (i.e., above or below) and to avoid the Dushanbe bet. This was a paradox4 because if they didn’t want to bet that Dushanbe was low, and their beliefs about Probability (low in Dushanbe) + Probability (high in Dushanbe) add to 1, they should logically have been eager to bet that Dushanbe was high.
In the same 2005 study, subjects made a long series of bets while their brains were being scanned using fMRI. The researchers found that there was more activity in the lateral orbitofrontal cortex (LOFC) and the amygdala when the subjects were making ambiguous choices than when they were making risky ones (see Figure 9.1).
The amygdala is known to be involved in very rapid reactions to potential threat (hence its role as a “vigilance” area of the brain) as well as in emotional learning and reward evaluation. The heightened activity it exhibits in response to ambiguity is consistent with the idea that the reluctance to bet on either side of a proposition under ambiguity is similar to a fear or freezing response, as if ambiguity-aversion were a fear of the economic unknown.
FIGURE 9.1 Linking Neural, Behavioral, and Lesion Data Differential bold signal brain activity in the amygdala and the lateral orbitofrontal cortex (LOFC) in response to ambiguous versus risky choices. Right panels show time courses of activity in left (L) and right (R) areas after onset of stimulus (gamble requiring evaluation).
Source: Reprinted from Science with permission.
A subject-specific choice parameter expressing the degree of ambiguity aversion was inferred from the subjects