BazermanMoore

Focalism and the Focusing Illusion 49
likely to occur concurrently (Wilson, Wheatley, Meyers, Gilbert, & Axsom, 2000). As a
consequence, people tend to overestimate both the degree to which their future
thoughts will be occupied by the focal event and the duration of their emotional response
to the event. For example, we tend to overestimate the impact of positive and
negative events, such as the wins and losses of our preferred sports team or political
candidate, on our overall happiness. We even dramatically overestimate the effects on
our happiness of being afflicted by a major medical condition.
In a similar vein, Schkade and Kahneman (1998) define the focusing illusion as the
tendency of people to make judgments based on their attention to only a subset of
available information, to overweight that information, and to underweight unattended
information. Using logic similar to that of Gilbert, Wilson, and colleagues, Schkade and
Kahneman (1998) asked college students in the Midwest and in Southern California
about their own life satisfaction and the perceived life satisfaction of others. Californians
and Midwesterners reported a similar level of life satisfaction, yet both groups
rated Californians as having greater life satisfaction than Midwesterners. Essentially,
differences between California and the Midwest, such as climate, strongly influenced
nonresidents’ judgments of residents’ life satisfaction. However, these factors did not
predict the experienced life satisfaction of citizens of the two locales. Schkade and
Kahneman argue that when students imagined how a move to the other location would
affect them, the obvious difference of weather became a salient factor, and all other life
events affecting satisfaction were out of focus.
Imagine that eight teams in any game or sport are engaged in a single elimination
tournament. Now imagine that eight people are each assigned to each team and asked
the probability that ‘‘their’’ team will win the tournament. Of course, some teams would
be better, and some would be worse, but the probabilities of the eight teams winning
should roughly add up to 100 percent.
Now let’s see what really happens in such a situation. When the 1995 National
Basketball Association championship was down to eight teams, Fox and Tversky (1998)
recruited basketball fans as research participants. Participants were asked either (1) the
probability that each team (Chicago, Indiana, Orlando, New York, Los Angeles, Phoenix,
San Antonio, and Houston) would win the championship, (2) the probability that
the winning team would come from each of the four divisions (Central [Chicago and
Indiana], Atlantic [Orlando and New York], Pacific [Los Angeles and Phoenix], and
Midwestern [San Antonio and Houston]), or (3) the probability that the winning team
would come from either the Eastern conference (comprising the Central and Atlantic
divisions) or the Western conference (comprising the Pacific and Midwestern divisions).
If the participants were well calibrated, the sum of the probabilities for the eight
teams, the sum of the probabilities for the four divisions, and the sum of the probabilities
for the two conferences should each add up to 100 percent.
The combined probabilities for the two conferences were close to the expected 100
percent; the sum added up to 102 percent. However, the sum of the probabilities of the
four divisions was 144 percent, and the sum of the probabilities of the eight teams was
218 percent. Fox and Tversky argue that when participants focus on an individual team,
they can find reasons to support that team winning the tournament; meanwhile, the
data that support other teams winning is out of focus. Similarly, Tversky and Koehler