APPLIED COGNITIVE PSYCHOLOGY
Appl. Cognit. Psychol. 17: 1113–1127 (2003)
Published online in Wiley InterScience
(www.interscience.wiley.com) DOI: 10.1002/acp.989
How Has the 9/11 Terrorist Attack Influenced
Decision Making?
KATIUSCIA SACCO1*, VALENTINA GALLETTO1
and ENRICO BLANZIERI2
1
Center for Cognitive Science, University of Turin, Italy
Department of Information and Communication Technology, University of Trento, Italy
2
SUMMARY
This paper investigates the effects of September 11, 2001 terrorists’ attack on decision making. It
was hypothesized that after terrorists’ attacks people would make more conservative and less risky
decisions, as a way of compensating for the feelings of insecurity caused by the disaster. Prospect
Theory is used as theoretical framework. This theory has successfully accounted for decision making
under normal circumstances. To verify whether and how the terrorists’ attack against the USA
influenced individual decision making processes, two samples of Italian university students were
tested, one month and six months after the disaster. The results show the emergence of two
tendencies, which are absent during ‘normal’ historical periods: a strong, long-term lasting search
for security when the outcome of a decision is perceived as a gain, and a medium-term risk avoiding
behavior in the loss domain. Copyright # 2003 John Wiley & Sons, Ltd.
The events of September 11, 2001, as well as having caused a series of human and material
disasters, have produced many consequences both on the economical and at the
psychological level; the aim of this paper is to explore whether such events have affected
the cognitive processes at the basis of everyday decision making. Indeed, the assumption is
that the heuristics used by people in everyday life hinge not only on personal experiences,
but are also influenced by major social events. It is already known that judgments are
influenced by the ‘visibility’ of events directly or indirectly experienced (Liechtenstein,
Slovic, Fischhoff, Lyman, & Coombes, 1978). Similarly, the proposal of this study is that
social and cultural changes do affect the psychological mechanisms underlining cognitive
performance. Therefore, decision making should be influenced by the events which
characterize our history. In this sense, the terrorist attacks of September 11th 2001 present
a unique opportunity to study how human decision making is influenced by social events
of international echo.
Prospect Theory (PT), proposed by Kahneman and Tversky (1979), is used as
theoretical framework. The conjecture of the research is that changes in cognition
following the attack on the USA have resulted in a phenomenon of risk aversion,
*Correspondence to: Katiuscia Sacco, Dipartimento di Psicologia, via Po 14, 10123 Torino, Italy.
E-mail: [email protected]
Copyright # 2003 John Wiley & Sons, Ltd.
1114
K. Sacco et al.
detectable in subjects’ performance in classical decision making tasks. That would imply
that the value and the weight functions proposed by standard PT’s algorithms describing
the way people tend to make decisions should include parameters that can change over
time in response to socio-cultural events. To test this assumption two experiments have
been carried out, the first one month after the tragedy and the second six months after it. As
there is no experimental data on the same groups of subjects before 9/11, a direct
comparison with the results obtained after the terrorist attack is virtually impossible. Thus,
performance of participants tested here is compared with those reported by Kahneman and
Tversky (1979) as a normative sample. However, since the two groups are drawn from
different countries and have been exposed to a plethora of other historical events and
social experiences, a validation of PT made in more recent years and on an Italian sample
is needed. Indeed, the studies conducted by Lauriola (2000) and by Lauriola and Levin
(2001a, 2001b) show that the previsions of PT actually hold for Italian subjects a couple of
years before 9/11.
First, various indicators of economic trends, observed in US and Europe, are used as a
basis for setting up the predictions. Second, along with a presentation of PT relevant
assumptions, the work of Lauriola and colleagues is analyzed. Third, the experiments,
their results, and the comparison with the original results obtained by Kahneman and
Tversky are presented. Besides, the results obtained after 9/11 are compared with the
previsions of the Cumulative Prospect Theory (CPT). A general discussion ends the
paper.
ECONOMIC DECISION MAKING FOLLOWING
THE TERRORIST ATTACKS
The attacks of 9/11 had severe consequences for the economy. One month later, a UN
source (2001) reported forecasts of a global decrease in Gross Domestic Product due to
direct destruction, indirect disruption of activities and a decrease in confidence:
The downward shift in the confidence of consumers and business is the third aspect of
the impact [ . . . ]. The direct economic consequences of eroding confidence will be
heightened risk aversion by business investors and a withholding of household spending
by consumers. The nervousness and apprehension of investors and consumers may lead
not only to depressed demand in the short-to medium run, but also to reduced expansion
of supply capacity and lower potential long-term growth. (pp. 3–4)
UNCTAD (2002) reported that 20% of corporate executives from the world’s 1,000
largest firms said that investment abroad (Foreign Direct Investment, FDI) would
decline after the attacks. Although FDI decision-makers do not seem to be largely
influenced by the events, an acceleration of the downturn of FDI was present in the
economic figures.
European Central Bank data from the Euro area in the aftermath of the attacks suggested
a tendency towards safer portfolio decisions by investors (ECB, 2001). M3 is an aggregate
statistic whose components are currency in circulation, overnight deposits, short-terms
deposits and marketable instruments:
The recent strong growth of M3 confirmed the earlier assessment that the environment
of relatively high financial market uncertainty in the aftermath of the 11 September
Copyright # 2003 John Wiley & Sons, Ltd.
Appl. Cognit. Psychol. 17: 1113–1127 (2003)
How has 9/11 influenced decision making?
1115
terrorist attacks in the United States has induced portfolio shifts into liquid and
relatively safe short-term assets included in M3. (ECB, 2001, p. 5)
The same source indicated that the effect was transient: ‘The worldwide recovery in
stock markets seemed, to a large extent, to stem from the dissipation of the uncertainty
which had manifested itself after 11 September’ (p. 31).
As described above, the effect of 9/11 attacks was not only on directly related economic
activities, such as the airline industry. For example, in Italy, newspapers reported that
National Lottery ticket sales decreased by 25% between 29 September 2001 and 6 January
2002. This decrease resulted in the worst sales of lottery tickets for 17 years (La Stampa,
2002, January 6). These changes indicates that the attacks had a real economic impact,
related to psychological uncertainty: ‘[ . . . ] This shift in confidence was caused not only
by the one-off psychological shock of the attacks, but also by a sudden escalation of
uncertainties about future actions and reactions. [ . . . ]’ (UN, 2001, pp. 3–4).
All the cited market trends observed in the US and Europe show how economic
phenomena might be influenced by cognitive factors operating at a collective level. The
suggestion of this study is that the attack against the USA can be viewed as a huge shared
loss, which at the same time, represented a strong menace for the future.
VALIDATION OF PROSPECT THEORY OVER TIME AND COUNTRIES
Prospect Theory (PT), proposed by Kahneman and Tversky (1979), is considered as the
current best explanation of decision making under conditions of uncertainty. PT states that
decisions in risky situations are made based on values assigned to gain and losses with
respect to a reference point and decision weights. Among the various predictions
descending from PT, here the focus is on the so-called ‘framing effect’ (Tversky &
Kahneman, 1986), which is to be tested in the experiments presented in this paper. Indeed,
the experiments by Kahneman and Tversky cited in this paragraph are exactly the same
type as those used in Experiment 1 of this paper.
Probability weighting
Decision weights tend to overestimate small probabilities and underestimate moderate and
high probabilities. In order to demonstrate this tendency, Kahneman and Tversky (1979)
carried out an experiment on two groups of subjects. Subjects dealing with problem 1 were
asked to choose between two alternatives of gain: the first was a small probability (0.001)
of winning a large amount of money ($5000), while the second was a sure gain of a small
amount of money ($5). Subjects dealing with problem 2 were asked to choose between
two alternatives of loss: the first was a small probability (0.001) of losing a large amount of
money ($5000), while the second was a sure loss of a small amount of money ($5). The
two problems are structurally similar, as both choices in both problems have the same
expected value of 5. Nonetheless, 75% of the subjects preferred the uncertain gain in
problem 1, showing an overestimation of low probabilities of gain, while 80% of the
subjects preferred the sure loss in problem 2, showing an overestimation of low
probabilities of sustaining a big loss. The authors commented that the former bias is
probably responsible for the success of national lotteries; while the latter is responsible for
the tendency to pay large amounts of money for insurance against highly improbable
accidents.
Copyright # 2003 John Wiley & Sons, Ltd.
Appl. Cognit. Psychol. 17: 1113–1127 (2003)
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K. Sacco et al.
Reference point
Decisions are influenced by the nature of the mental representation of the problem. In
particular, if the reference point leads the outcome to be perceived as a potential gain, then
the value function is concave and people tend to make conservative decisions. On the other
hand, if the reference point leads the outcome to be perceived as a loss, then the value
function is convex and people tend to make risky decisions. To test these assumptions,
Kahneman and Tversky (1979) carried out an experiment with two groups of subjects.
Group 1 dealt with a ‘gain problem’ like the following ‘In addition to whatever you own,
you have been given $1000. Choose between a 0.50 chance of winning $1000 or a sure
gain of $500’. Group 2 dealt with a ‘loss problem’ like the following ‘In addition to
whatever you own, you have been given $2000. Choose between a 0.50 chance of losing
$1000 or a sure loss of $500’. In this experiment, the expected value for the alternatives of
the two problems is the same, i.e. 500. However, 84% of group 1 preferred the sure gain,
showing risk aversion when dealing with profit options, while 70% of group 2 preferred
the possible loss, showing risk seeking when dealing with loss options. The authors
concluded that, as values are always determined with respect to a reference point,
decisions change as the reference point changes.
Since the first experiments by Kahneman and Tversky, several types of tests have
confirmed the predictions of PT (for reviews, see Edwards, 1996, and Levy, 1992). More
recently, Tversky and Kahneman (1992) proposed the Cumulative Prospect Theory (CPT)
whose functional forms for the weights overcome some theoretical problems of PT, e.g.
the violation of ‘stochastic dominance’ (see Levy & Levy, 2002, 2002a). Among the
various validations of PT, the research conducted by Lauriola (2000) and by Lauriola and
Levin (2001a, 2001b) is particularly relevant here, since the participants involved in their
studies resemble those involved in the experiments presented in this paper both for
nationality (Italians) and for the time of testing (recent years). Lauriola and Levin (2001a,
2001b) submitted to 76 Italian participants the classical choice tasks between a risky
prospect and a sure prospect. The study was an investigation into the role of individual
differences and ambiguity in risk attitude. They used a 2 6 5 factorial design: 2
domains (gain and loss), 6 amounts of money for the sure prospect (1, 10, 100, 1,000,
10,000, 100,000 1,000 ITL) and 5 probabilities for the risky prospect (0.02, 0.25, 0.5,
0.75, 0.98. ). Therefore, given an amount X the tasks are: in the gain domain, choosing
between a risky prospect (X/p, p) and a sure prospect (X,1) with p ¼ 0.02, 0.25, 0.5, 0.75,
0.98 and in the loss domain, choosing between a risky prospect (X/p, p) and a sure
prospect (X,1) with p ¼ 0.02, 0.25, 0.5, 0.75, 0.98. As their main interest was to study
individual differences, they did not report the results for each task and they used ANOVA
techniques to outline the relation between factors and personality measures. However, in
the data presented in Lauriola (2000), the percentages of aggregate numbers of riskseeking choices for each amount are reported. To assess the validity of PT previsions for
Italian subjects, in the present study, following Wakker (2003), the values of CPT for each
task of the factorial design have been computed using the original parameterization of
Tversky and Kahneman (1992). The prevision of CPT is made by examining the
differences between the CPT values of the risky prospect and those of the sure prospect.
If the difference is positive the prevision is towards the risky one, otherwise it is towards
the sure one. Since the direct comparison for each task is prevented by the aggregate nature
of the available empirical results, the median of each difference has been calculated for all
the tasks. The definition of the median guarantees that there is an equal number of samples
Copyright # 2003 John Wiley & Sons, Ltd.
Appl. Cognit. Psychol. 17: 1113–1127 (2003)
How has 9/11 influenced decision making?
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Table 1. A comparison of the results of Lauriola (2000) with CPT previsions, sums converted in
dollars using the 1999 exchange rate (1 USD ¼ 1564 ITL)
Amount
X of the
certain
prospect
(1,000
ITL)
1
10
100
1,000
10,000
100,000
Losses domain 5 tasks
A ¼ (X/p, p) against
B ¼ (X,1) with
p ¼ 0.02, 0.25, 0.5, 0.75, 0.98
Gains domain 5 tasks
A ¼ (X/p, p) against
B ¼ (X,1) with
p ¼ 0.02, 0.25, 0.5, 0.75, 0.98
Percentage of
risk-seeking
choices (A%)
for losses
(Lauriola,
2000)
Percentage of
risk-seeking
choices (A%)
for gains
(Lauriola,
2000)
44
35
41
50
51
70
Median of:
CPT value
for A (risky
prospect)
minus CPT
value for B
(certain
prospect)
0.099806
0.757106
5.743237
43.56691
330.4888
2507.014
48
38
31
22
16
18
All the 10 tasks
Median of:
CPT value
for A (risky
prospect)
minus CPT
value for B
(certain
prospect)
B% for
gains
minus
A% for
losses
Median of:
CPT values
for A (risky
prospect)
minus CPT
value for B
(certain
prospect)
0.07278
0.55212
4.18828
31.7714
241.01
1828.25
4
3
10
28
35
52
0.00067
0.00506
0.0384
0.29131
2.20981
16.7631
that are below and above the median itself. This gives a measure of the way subjects’
choices should be biased in the prevision of CPT. Assuming that the differences among the
CPT values give a measure of the distribution of choices, the pattern of prevision is
reproduced by the data as shown in Table 1.
It is worth noting that CPT consistently predicts the risky choice for the losses and the
sure one for the gains, with the inversion for the small probabilities p ¼ 0.02, so previsions
are never homogeneous for each amount, and that can explain the relatively small value of
the percentages. As the amount of money increases, the values of the CPT previsions get
stronger and stronger and the inversion effect becomes more evident. This permits one to
conclude that for subjects more similar to those tested in the present experiments (i.e.,
Italians) and tested in recent times, the prevision of CPT actually holds.
These applications of PT were made under conditions of relative stability in international affairs. Some attempts of analyzing decision making during national and international crises have been made by focusing on the protagonists of such crises (e.g., Haas,
2001; McDermott & Kugler, 2001; Roberts, 1988). However, to the best of our knowledge,
there is no published work to date on the indirect influence of historical events upon
decision making processing.
Here, the question is how a dramatic event such as the 9/11 terrorist attack against USA,
creating a climate of international insecurity, has influenced decision making processes,
and how its effects can be interpreted within the PT framework. Starting from the
indicators of economic decrease, the proposal is that decision making in the aftermath
of the collapse of the World Trade Center might be guided by a search for security, and
therefore become more conservative. Specifically, the perceived uncertainty about the
future might lead to a generalized risk aversion and to a greater search for security. As a
consequence, the expectation is that two of the main assumptions of PT, namely the
overestimation of a low probability of winning when the outcome is positive, and the
preference for taking risky decisions when the outcome is a loss, might not be supportable
Copyright # 2003 John Wiley & Sons, Ltd.
Appl. Cognit. Psychol. 17: 1113–1127 (2003)
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K. Sacco et al.
in the aftermath of September 11th. These predictions have been tested with two
experiments, conducted one month and six months after the dramatic event, respectively.
EXPERIMENT 1
The aim of Experiment 1 is to establish whether and how the value and weight functions
proposed by PT changed after the terrorist attacks. The method of hypothetical choices
devised by Kahneman and Tversky (1979) is used, replicating four of their problems. The
structure of problems 1 and 2 is that reported in the ‘Probability weighting’ paragraph in
the previous section; Kahneman and Tversky found a systematic tendency to overestimate
very low probabilities of winning in the first problem, and to overestimate the probability
of suffering a large loss in the second problem. The structure of problems 3 and 4 is that
reported in the ‘Reference point’ paragraph in the previous section; Kahneman and
Tversky found a tendency to avoid risk when the outcome of the decision is perceived as a
gain, and to make risky decisions when the outcome is perceived as a loss. In problems 3
and 4 the probabilities are high, hence the distortion effect determined by the overestimation of the very low probabilities is absent.
All these problems show the trend of the decision curve; they have been selected to
verify the possible changes in this trend, in line with the hypothesis proposed in this paper
that after a disastrous event, like the 9/11 terrorist attack, a change occurs on the decision
curve in the direction of a search for certainty both in the gain domain and in the loss
domain. The percentage results obtained after 9/11 are compared with the original ones by
Kahneman and Tversky (1979); besides, the results are compared with the analytical
previsions made by the Cumulative Prospect Theory (Tversky & Kahneman, 1992).
Method
Participants
A sample of seventy-four adults aged between 19 and 44 years old (mean age ¼ 22 years;
standard deviation ¼ 5) was tested. They were all students of Science of Communication at
the University of Turin, and took part in the test voluntarily. There was a balanced
proportion of males and females.
Design
Four problems, cited above, were selected among those devised by Kahneman and
Tversky (1979). The original amounts of money were transformed into equivalent
amounts of Italian lire, taking into account inflation since the original study. The
participants were randomly assigned to solve one of the four problems (see Table 2).
Materials
Each participant received a sheet of paper: on one side blank spaces had to be filled in with
age and gender; on the other side one of the four problems was printed.
Procedure
The participants were tested collectively in a University classroom. They were told they
were participating in a research study on decision making. They were asked to imagine
Copyright # 2003 John Wiley & Sons, Ltd.
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How has 9/11 influenced decision making?
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Table 2. Problems used in Experiment 1
Problem
1
2
3
4
Type of choice
You are asked to choice between:
A) One possibility out of 1,000 to win £ 30,000,000
B) A sure winning of £ 30,000
You are asked to choice between:
A) One possibility out of 1,000 to lose £ 30,000,000
B) A sure loss of £ 30,000
In addition to whatever you own, you have been given £ 6,000,000.
You are now asked to choose between:
A) A 50% probability of winning £ 6,000,000
B) A sure winning of £ 3,000,000
In addition to whatever you own, you have been given £ 12,000,000.
You are now asked to choose between:
A) A 50% probability of losing £ 6,000,000
B) A sure loss of £ 3,000,000
Table 3. Expected values and cumulative prospect theory previsions for the tasks of Experiment 1,
sums converted using the average exchange rate of September–October 2001 (EUR ¼ 0.863
USD ¼ 1936.27 ITL)
Problem Prospect
1
2
3
4
A
B
A
B
A
B
A
B
Expected
value (Liras)
30,000,000
30,000,000
30,000,000
30,000,000
3,000,000
3,000,000
3,000,000
3,000,000
Problem
type
Probable gain
Sure gain
Probable loss
Sure loss
Probable gain
Sure gain
Probable loss
Sure loss
Probability
X (Liras)
CPT
value
0.001
30,000,000 61,80176262
1
30,000 9,795490724
0.001 30,000,000 80,96644325
1
30,000 22,03985413
0.5
6,000,000 436,3575514
1
3,000,000 563,6716569
0.5
6,000,000 1059,641734
1
3,000,000 1268,261228
CPT
prevision
A
B
B
A
that they were actually faced with the choice described in the problem, and to indicate the
decision they would make in such a case.
Results
Table 3 shows the expected values for responses to each problem and the CPT previsions
computed using the same procedure used recently by Wakker (2003). Note that no matter
how the alternative is expressed, be it as probable or sure, the expected values in each
problem are exactly the same for both alternatives.
Table 4 shows the percentages of responses in each category for problems 1 and 2, and 3
and 4. The response given by the majority of the subjects is underlined. The asterisk
indicates values that differ significantly from chance levels (a 50/50 split), using a
binomial test.
Despite the expected values being the same for each problem, people show a decision
making bias depending upon the reference point. This confirms the underlying assumption
of PT: people do not compute expected values in order to make their choices; rather, they
treat gains and losses differently. The first difference between Sacco et al.’s results and
those of Kahneman and Tversky arises in problem 1. In Kahneman and Tversky’s data
Copyright # 2003 John Wiley & Sons, Ltd.
Appl. Cognit. Psychol. 17: 1113–1127 (2003)
1120
K. Sacco et al.
Table 4. Experiment 1: Percentages of responses for each of the alternatives in problems 1 and 2, 3
and 4
Kahneman and Tversky results
Response
Problem
1
2
3
4
(gain)
(loss)
(gain)
(loss)
Sacco et al. results
Response
A (Probable)
B (Sure)
A (Probable)
B (Sure)
CPT prevision
75*
20*
16*
70*
25*
80*
84*
30*
44
32*
33*
42
56
68*
67*
53
A
B
B
A
people preferred the probable gain, showing an overestimation of low probabilities of
winning, while here this effect is absent. Moreover, most of the participants seem to prefer
the sure gain. This suggests that, after a large scale negative historical event, people tend to
lose trust in the possibility of winning. The second difference emerged in problem 4. In
Kahneman and Tversky, people preferred the probable loss, showing a tendency to make
risky decisions when the outcome was perceived as a loss; again, here this tendency is
absent. Moreover, most of the participants tested one month after 9/11 preferred the sure
loss. Globally considered, these results suggest a tendency to look for certainty and to
avoid bigger losses, even when the probability of such a loss is very low.
EXPERIMENT 2
The aim of Experiment 2 is to investigate the long-term effects of the terrorist attack on
decision making processes, by testing a sample of adult participants different from but
comparable to those tested in Experiment 1, six months after the dramatic event. To the
best of our knowledge, during the months that intervened between the first experiment and
the second one, no relevant event of social scope occurred in our country.
Here again, the method of hypothetical choices devised by Kahneman and Tversky
(1979) is used; ten problems, originally conceived by these authors,were replicated. Four
of these are similar to the problems of the Experiment 1, as they involve a choice between
a probable outcome and a sure outcome. The other six involve choosing between a less
probable outcome and a more probable outcome. These problems have been selected to
verify the possible search for certainty in the outcomes of choice.
Method
Participants
A sample of one hundred adults aged between 18 and 45 years old (mean age ¼ 23.8,
standard deviation ¼ 4.62) was tested. They were all students of Science of Communication at the University of Turin, and took part to the experiment voluntarily.
Design
The following ten problems (see Table 5), which are similar to those devised by Kahneman
and Tversky (1979), were constructed. The original amounts of money were transformed
into equivalent amounts of Italian lire and into equivalent amounts of Euro: the subjects of
Copyright # 2003 John Wiley & Sons, Ltd.
Appl. Cognit. Psychol. 17: 1113–1127 (2003)
How has 9/11 influenced decision making?
1121
Table 5. Problems used in Experiment 2
Problem
1
2
3
4
5
6
7
8
9
10
Type of choice
You are asked to choose between:
A) An 80% probability of winning £ 6,000,000 (s 3,100)
B) A sure winning of £ 4,500,000 (s 2,325)
You are asked to choose between:
A) A 20% probability of losing £ 6,000,000 (s 3,100)
B) A 25% probability of losing £ 4,500,000 (s 2,325)
You are asked to choose between:
A) A 20% probability of winning £ 6,000,000 (s 3,100)
B) A 25% probability of winning £ 4,500,000 (s 2,325)
You are asked to choose between:
A) A 20% probability of losing £ 6,000,000 (s 3,100)
B) A 25% probability of losing £ 4,500,000 (s 2,325)
You are asked to choose between:
A) A 45% probability of winning £ 9,000,000 (s 4,650)
B) A 90% probability of winning £ 4,500,000 (s 2,325)
You are asked to choose between:
A) A 45% probability of losing £ 9,000,000 (s 4,650)
B) A 90% probability of losing £ 4,500,000 (s 2,325)
You are asked to choose between:
A) A 1 in a 1,000 possibility of winning £ 9,000,000 (s 4,650)
B) A 2 in a 1,000 possibility of winning £ 4,500,000 (s 2,325)
You are asked to choose between:
A) A 1 in a 1,000 possibility of losing £ 9,000,000 (s 4,650)
B) A 2 in a 1,000 possibility of losing £ 4,500,000 (s 2,325)
In addition to whatever you own, you have been given £ 1,500,000 (s 775).
You are asked to choose between:
A) A 50% probability of winning £ 1,500,000 (s 775)
B) A sure winning of £ 750,000 (s 390)
In addition to whatever you own, you have been given £ 3,000,000 (s 1,550).
You are asked to choose between:
A) A 50% probability of losing £ 1,500,000 (s 775)
B) A sure loss of £ 750,000 (s 390)
this experiment were tested during the period of double currency of lire and Euro. Inflation
since the original study was taken into account.
The problems were arranged according to four different orders and, for each problem,
the alternatives were presented in two different orders (AB, BA), thus producing eight
experimental conditions. The participants were randomly assigned to one of the eight
conditions.
Materials and Procedure
The same as Experiment 1.
Results
Table 6 shows the expected values for responses to each problem and CPT previsions
computed following Wakker (2003). In problems 1 and 2, and in problems 3 and 4, the
expected values differ according to whether winning and losing are probable or sure and
Copyright # 2003 John Wiley & Sons, Ltd.
Appl. Cognit. Psychol. 17: 1113–1127 (2003)
Copyright # 2003 John Wiley & Sons, Ltd.
10
9
8
7
6
5
4
3
2
1
Problem
A
B
A
B
A
B
A
B
A
B
A
B
A
B
A
B
A
B
A
B
Prospect
Problem type
Probable gain
Sure gain
Probable loss
Sure loss
Less probable gain
More probable gain
Less probable loss
More probable loss
Less probable gain
More probable gain
Less probable loss
More probable loss
Less probable gain
More probable gain
Less probable loss
More probable loss
Probable gain
Sure gain
Probable loss
Sure loss
Expected value
(Liras and Euros)
þ £ 4,800,000; s 2,480
þ £ 4,500,000; s 2,325
£ 4,800,000; s 2,480
£ 4,500,00; s 2,325
þ £ 1,200,000; s 620
þ £ 1,125,000; s 580
£ 1,200,000; s 620
£ 1,125,000; s 580
þ £ 4,050,000; s 2,090
þ £ 4,050,000; s 2,090
£ 4,050,000; s 2,090
£ 4,050,000; s 2,090
þ £ 9,000; s 4.65
þ £ 9,000; s 4.65
£ 9,000; s 4.65
£ 9,000; s 4.65
þ £ 750,000; s 390
þ £ 750,000; s 390
£ 750,000; s 390
£ 750,000; s 390
0,8
1
0,8
1
0,2
0,25
0,2
0,25
0,45
0,9
0,45
0,9
0,001
0,002
0,001
0,002
0,5
1
0,5
1
Probability
6,000,000
4,500,000
6,000,000
4,500,000
6,000,000
4,500,000
6,000,000
4,500,000
9,000,000
4,500,000
9,000,000
4,500,000
9,000,000
4,500,000
9,000,000
4,500,000
1,500,000
750,000
1,500,000
750,000
X (Liras)
639,1247029
816,8393435
1583,663125
1837,888523
274,3651898
237,4902675
608,4731381
539,4543743
594,1424928
581,3576824
1430,118617
1424,186226
21,72789769
17,81235965
28,46570261
24,79155146
130,6711898
168,7965428
317,3192391
379,7922212
CPT value
A
B
B
A
B
A
B
A
A
B
CPT
prevision
Table 6. Expected values and cumulative prospect theory previsions for the tasks of experiment 2, sums converted using the average exchange rate of January–
February 2002 (EUR ¼ 0.877 USD ¼ 1936.27 ITL)
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How has 9/11 influenced decision making?
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Table 7. Experiment 2: Percentages of responses for each of the alternatives in problems 1 and 2, 9
and 10
Kahneman and Tversky results
Response
Sacco et al. results
Response
Problem
A (probable)
B (sure)
A (probable)
B (sure)
CPT prevision
1 (gain)
2 (loss)
9 (gain)
10 (loss)
20*
92*
16*
69*
80*
8*
84*
31*
24*
83*
23*
60
76*
17*
77*
40
B
A
B
A
Table 8. Experiment 2: Percentages of responses for each of the alternatives in problems 3 and 4, 5
and 6, 7 and 8
Kahneman and Tversky results
Response
Problem
A
(less probable)
B
(more probable)
3 (gain)
4 (loss)
5 (gain)
6 (loss)
7 (gain)
8 (loss)
65*
42
14*
92*
73*
30*
35*
58
86*
8*
27*
70*
Sacco et al. results
Response
A
B
(less probable) (more probable)
48
46
19*
82*
31*
57
51
54
81*
18*
69*
43
CPT prevision
A
B
A
B
A
B
less probable or more probable, respectively. Instead, in problems 5 and 6, 7 and 8, 9 and
10, no matter how the alternative is expressed, be it as probable or sure, and as less
probable or more probable, the expected values in each problem are exactly the same for
both alternatives.
Table 7 shows the percentages of responses in each category for problems 1 and 2, and 9
and 10, that is the problems in which the alternatives are expressed as probable or sure;
Table 8 shows the percentages of responses in each category for problems 3 and 4, 5 and 6,
7 and 8, that is the problems in which the alternatives are expressed as less probable or
more probable. The response given by the majority of the subjects is underlined and the
asterisk indicates values that differ significantly from chance levels (a 50/50 split), using a
binomial test.
For problems 1 and 2, the expected values differ according to whether gain and loss are
probable or sure; from a normative point of view, people should choose the alternative with
a higher expected value when the outcome is perceived as a gain, and the alternative with a
lower expected value when the outcome is perceived as a loss. Nevertheless, Kahneman
and Tversky’s results, as well as those obtained by Sacco et al. six months after 9/11, show
that people prefer the sure gain, i.e. the gamble that has a lower expected value, and the
probable loss, i.e. the gamble that has a higher expected value.
In problems 9 and 10, despite the expected values being the same for each of the
alternatives, people show a preference and treat gains and losses differently. In both
Copyright # 2003 John Wiley & Sons, Ltd.
Appl. Cognit. Psychol. 17: 1113–1127 (2003)
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K. Sacco et al.
problems the results are similar to those obtained by Kahneman and Tversky. If these
results are compared with those of problems 3 and 4 of the previous experiment, one can
see that: (a) the tendency to make conservative decisions when the outcome is perceived as
a gain has remained intact after the terrorist attack and (b) while most participants tested
one month after the terrorist attack preferred the sure loss, six months after the event most
of them seem to return to prefer risky decisions in the loss domain, choosing the alternative
where the amount of money at stake is larger.
For problems 3 and 4, the expected values differ according to whether gain and loss are
less probable or more probable: from a normative point of view, people should choose the
alternative with the higher expected value when the outcome is perceived as a gain, i.e. the
less probable winning, and the alternative with the lower expected value when the outcome
is perceived as a loss, i.e. the more probable loss. In problem 3 Sacco et al.’s results differ
from those obtained by Kahneman and Tversky: while in the latter’s data people preferred
a less probable but larger gain, such a tendency disappeared in Sacco et al.’s results. The
results of problem 4 are similar to those obtained by Kahneman and Tversky: when the
difference between the probabilities (0.20 and 0.25) is small, a greater number of
participants choose the alternative in which the amount of money at stake is smaller,
although in both cases such a difference is not statistically significant.
In problems 5 and 6, 7 and 8, it is worth noting that, despite the expected values being
the same for each alternative in each problem, people show a decision making bias
depending upon the reference point, and they treat gains and losses differently. In
problems 5 and 6, Sacco et al.’s results are similar to those obtained by Kahneman and
Tversky: most people choose the alternative in which the probability of winning is
substantial, almost certain (0.90), even if the gain is smaller, and they prefer the prospect
where the loss is larger but less probable (0.45). Note that for problems 5 and 6 CPT fails
to predict both Sacco et al.’s results and Kahneman and Tversky results, providing another
anomaly that should be further investigated.
In problems 7 and 8 Sacco et al.’s results differ from those obtained by Kahneman and
Tversky. In problem 7, Kahneman and Tversky’s participants preferred the alternative
offering the larger but less probable gain, whereas participants tested six months after 9/11
show an opposite tendency, preferring the more probable gain, even if the probabilities of
winning are very small (0.001 and 0.002) in both alternatives. In problem 8, Kahneman
and Tversky’s data show that people prefer the alternative where the loss is more probable
but smaller; such a preference is not present in Sacco et al.’s data.
Globally considered, the results of Experiment 2 suggest a long lasting and strong
tendency towards the search for certainty in the gain domain, while the tendency towards
risk taking in the loss domain seems to gradually re-appear. In all the problems that involve
the gain domain participants tested six months after 9/11 choose the alternative that offers
a greater probability of winning or a certain gain, whereas they tend to avoid more
probable or sure losses.
The results obtained after 9/11 are summarized in Figure 1, which show the percentages
of responses for each of the alternatives in the problems of Experiment 1 and Experiment
2, respectively.
In Experiment 1 the choice of the alternative that offers a sure outcome prevail both in
the gain domain and in the loss domain. In Experiment 2 the search for certainty remains
in the gain domain; in the loss domain, however, there is a preference for risky decisions,
that is decisions that involve losing a larger amount of money, so avoiding more probable
or sure losses.
Copyright # 2003 John Wiley & Sons, Ltd.
Appl. Cognit. Psychol. 17: 1113–1127 (2003)
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Figure 1. Sacco et al. results: percentages of responses for each of the alternatives of gain or loss in
problems of Experiment 1 and Experiment 2
GENERAL DISCUSSION AND CONCLUSIONS
The results obtained after 9/11 are in line with the assumption that a shared loss biases
decision making in favor of a search for security: this bias seems to be long-term lasting in
the gain domain and medium-term lasting in the loss domain.
The results of the first experiment seem to contradict PT. In particular, the results
obtained one month after the terrorist attack, compared to those published earlier, show
two important differences. Firstly, the overestimation of low probabilities of gain is absent.
Secondly, the tendency towards risk taking in the loss domain disappears. It looks like the
reflection effect vanished. Indeed, the value function for losses seemed to no longer mirror
the value function for gain; rather, the two functions are similar. However, Sacco et al.’s
results do not distribute in a balanced way among the utility-equivalent options either.
Therefore, the proposal is that the experience of a shared loss and the ensuing threat to
peace lead people to distrust easy gains and to try to avoid further losses in the future. This
caused participants tested one month after the terrorist attack to make a more conservative
weighting of low probabilities of gain, as well as to overemphasize the probability of
losing, both when the probability is low, and when it is higher. Technically, the main
change occurs on the weighting function in the domain of losses. People do not only value
the outcomes in terms of gains and losses, but they also attribute different weights to them.
The weighting function for gains would be below ¼ p in the domain of gains, and above it
in the domain of losses. This change would be responsible for (a) the disappearance of the
overestimation of low probabilities of gains, and (b) the search for certainty in the domain
Copyright # 2003 John Wiley & Sons, Ltd.
Appl. Cognit. Psychol. 17: 1113–1127 (2003)
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K. Sacco et al.
of losses. Indeed, the overestimation of the probability of losing prevents the effect of
avoiding sure losses, so that instead of a loss, which in an unsure context is perceived as
more probable, people tend to choose a sure loss of a smaller value. In other words, the
decision weight of the probability of losing increases, preventing the tendency to avoid
sure losses. This is consistent with the phenomenon of probability neglect caused by that
was recently connected with terrorism acts: ‘When probability neglect is at work, people’s
attention is focused on the bad outcome itself, and they are inattentive to the fact that it is
unlikely to occur’ (Sunstein, 2003, p. 122).
One interpretation of these findings is that people are more conservative after disastrous
events. This possibility is fascinating in the context of the ongoing debate on human
rationality (see Stanovich & West, 2000). The trends in economics described, as well as
Sacco et al.’s experimental data, suggest that the events of 9/11 did cause the outcomes of
the decision making process to move closer to those expected from rational choices. In the
first experiment the majority of participants opt for the sure alternative in all four problems
and, within the two pairs of problems, they opt for the alternatives which are similar to
each other. In the second experiment the majority of participants opt for the sure
alternative or for the most probable one in all the problems where the outcome of the
choice is perceived as a gain, even when the difference between the probabilities of the
two alternatives, that is less probable or more probable gain, is very small. However, six
months after the attack, the tendency towards risk taking in the loss domain seems to
appear again: in many cases, most of the participants favor the alternative in which the loss
is larger, but probable rather than sure, or less probable rather than more probable. It can
be speculated that individuals, in order to face a future that remains uncertain, prefer to
secure a gain, and they therefore tend to avoid sure losses.
Since the experiments conducted by Sacco et al. aimed at exploring the indirect
consequences of 9/11 upon decision making, it remains possible that any observed effect is
not linked directly to the tragedy. In particular, it could be argued that some economic
consequence of the 9/11 event, rather than the event itself, could have affected our
participants’ performances in the second experiment. Although one cannot exclude this
possibility, it seems that a shaken sense of personal safety and security, more than
economic factors, has lead people to save money and pay down debts. This is what Mosley
and Amposah (2003) stated about Americans, basing their claim on a report of the
Washington Post Poll (Morin, 2002, May 3), which refers that in May 2002 40% of the
Americans were still feeling unsafe, exactly the same percentage as that immediately after.
This seems to enforce the suggestions proposed in this paper.
ACKNOWLEDGEMENTS
This research has been supported by M.I.U.R. of Italy, FIRB project (research code:
RBAUO1JEYW_001). We thank the reviewers and David T. Field for insightful comments
and suggestions.
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