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The Framing of Decisions and the

Psychology of Choice

Amos

Tversky

and Daniel Kahneman

Ecxplanations and predictions of

people's choices, in everyday life as well

as in the social sciences, are often found-

ed on the assumption of human rational-

ity. The definition of rationality has been

much debated, but there is general agree-

ment that rational choices should satisfy

some elementary requirements of con-

sistency and coherence. In this article

The majority choice in this problem is

risk averse: the prospect of certainly

saving

200

lives is more attractive than a

risky prospect of equal expected value,

that is, a one-in-three chance of saving

600

lives.

A second group of respondents was

given the cover story of problem

with a

different formulation of the alternative

programs, as follows:

Problem 2

1551:

If Program

is adopted

400

people will die.

[22 percent]

If Program

is adopted there is 113 probabil-

ity that nobody will die, and 213 probabili-

ty that

600

people will die. [78 percent]

Which of the two programs would you favor?

The majority choice in problem

risk taking: the certain death of

400

people is less acceptable than the two-in-

three chance that

600

will die. The pref-

erences in problems

and

illustrate a

common pattern: choices involving gains

are often risk averse and choices in-

volving losses are often risk taking.

However, it is easy to see that the two

problems are effectively identical. The

only difference between them is that the

outcomes are described in problem

the number of lives saved and in problem

by the number of lives lost. The change

is accompanied by a pronounced shift

from risk aversion to risk taking. We

have observed this reversal in several

groups of respondents, including univer-

sity faculty and physicians. Inconsistent

responses to problems

and

arise from

the conjunction of a framing effect with

contradictory attitudes toward risks in-

volving gains and losses. We turn now

to an analysis of these attitudes.

The Evaluation of Prospects

The major theory of decision-making

under risk is the expected utility model.

This model is based on a set of axioms,

for example, transitivity of preferences,

which provide criteria for the rationality

of choices. The choices of an individual

who conforms to the axioms can be de-

scribed in terms of the utilities of various

outcomes for that individual. The utility

of a risky prospect is equal to the ex-

pected utility of its outcomes, obtained

by weighting the utility of each possible

outcome by its probability. When faced

with a choice, a rational decision-maker

will prefer the prospect that offers the

highest expected utility

(1,

2).

Dr. Tversky is a professor of psychology at Stan-

ford University, Stanford, California 94305, and Dr.

Kahneman is a professor of psychology at the Uni-

versity of British Columbia, Vancouver, Canada

V6T

1W5.

tional choice requires that the preference

between options should not reverse with

changes of frame. Because of imperfec-

tions of human perception and decision,

however, changes of perspective often

reverse the relative apparent size of ob-

jects and the relative desirability of op-

tions.

We have obtained systematic rever-

Summary.

The psychological principles that govern the perception of decision prob-

lems and the evaluation of probabilities and outcomes produce predictable shifts of

preference when the same problem is framed in different ways. Reversals of prefer-

ence are demonstrated in choices regarding monetary outcomes, both hypothetical

and real, and in questions pertaining to the loss of human lives. The effects of frames

on preferences are compared to the effects of perspectives on perceptual appear-

ance. The dependence of preferences on the formulation of decision problems is a

significant concern for the theory of rational choice.

we describe decision problems in which

people systematically violate the re-

quirements of consistency and coher-

ence, and we trace these violations to the

psychological principles that govern the

perception of decision problems and the

evaluation of options.

decision problem is defined by the

acts or options among which one must

choose, the possible outcomes or con-

sequences of these acts, and the contin-

gencies or conditional probabilities that

relate outcomes to acts. We use the term

"decision frame" to refer to the deci-

sion-maker's conception of the acts, out-

comes,

and contingencies associated

with a particular choice. The frame that a

decision-maker adopts is controlled part-

ly by the formulation of the problem and

partly by the norms, habits, and personal

characteristics of the decision-maker.

It is often possible to frame a given de-

cision problem in more than one way.

Alternative frames for a decision prob-

lem may be compared to alternative per-

spectives on a visual scene. Veridical

perception requires that the perceived

relative height of two neighboring moun-

tains, say, should not reverse with

changes of vantage point. Similarly, ra-

sals of preference by variations in the

framing of acts, contingencies, or out-

comes. These effects have been ob-

served in a variety of problems and in

the choices of different groups of respon-

dents. Here we present selected illustra-

tions of preference reversals, with data

obtained from students at Stanford Uni-

versity and at the University of British

Columbia who answered brief question-

naires in a classroom setting. The total

number of respondents for each problem

is denoted by

and the percentage

who chose each option is indicated in

brackets.

The effect of variations in framing is

illustrated in problems

and

Problem

1521: Imagine that the

U.S.

is preparing for the outbreak of an unusual

Asian disease, which is expected to kill

600

people. Two alternative programs to combat

the disease have been proposed. Assume that

the exact scientific estimate of the con-

sequences of the programs are as follows:

If Program

is adopted, 200 people will be

saved. [72 percent]

If Program

is adopted, there is 113 probabil-

ity that

600

people will be saved, and

213 probability that no people will be

saved. 128 percent]

Which of the two programs would you favor?

SCIENCh,

VOL.

211, 30 JANUARY 1981

0036-807518110130-0453$01.5010

Copy1

-ight

1981 AAAS 453

As will be illustrated below, people ex-

hibit patterns of preference which appear

incompatible with expected utility theo-

ry. We have presented elsewhere (3) a

descriptive model, called prospect theo-

ry, which modifies expected utility theo-

ry so as to accommodate these observa-

tions. We distinguish two phases in the

choice process: an initial phase in which

acts, outcomes, and contingencies are

framed, and a subsequent phase of eval-

uation

(4).

For simplicity, we restrict the

formal treatment of the theory to choices

involving stated numerical probabilities

and quantitative outcomes, such as mon-

ey, time, or number of lives.

Consider a prospect that yields out-

come

with probability

outcome y

with probability q, and the status quo

with probability

q. According

to prospect theory, there are values v(.)

associated with outcomes, and decision

weights n(.) associated with probabili-

ties, such that the overall value of the

prospect equals n(p) v(x)

n(q) v(y). A

slightly different equation should be ap-

plied if all outcomes of a prospect are on

the same side of the zero point

(5).

In prospect theory, outcomes are ex-

pressed as positive or negative devia-

tions (gains or losses) from a neutral ref-

erence outcome, which is assigned a val-

ue of zero. Although subjective values

differ among individuals and attributes,

we propose that the value function is

commonly S-shaped, concave above the

reference point and convex below it, as

illustrated in Fig.

For example, the dif-

ference in subjective value between

gains of $10 and $20 is greater than the

subjective difference between gains of

$110 and $120. The same relation be-

tween value differences holds for the

corresponding losses. Another property

of the value function is that the response

to losses is more extreme than the re-

sponse to gains. The displeasure associ-

ated with losing a sum of money is gener-

ally greater than the pleasure associated

with winning the same amount, as is re-

flected in people's reluctance to accept

fair bets on a toss of a coin. Several stud-

ies of decision (3,

and judgment

(7)

have confirmed these properties of the

value function

(8).

The second major departure of pros-

pect theory from the expected utility

model involves the treatment of proba-

bilities. In expected utility theory the

utility of an uncertain outcome is weight-

ed by its probability; in prospect theory

the value of an uncertain outcome is mul-

tiplied by a decision weight

n(p), which

is a monotonic function of p but is not a

probability. The weighting function

Fig.

hypothetical value function.

has the following properties. First, im-

possible events are discarded, that is,

n(0)

0, and the scale is normalized so

that n(l)

1, but the function is not well

behaved near the endpoints. Second,

for low probabilities n(p) >p, but

TO))

n(l

Thus low proba-

bilities are overweighted, moderate and

high probabilities are underweighted,

and the latter effect is more pronounced

than the former. Third,

n(pq)/n(p)

n(pqv)/nQ?v) for all 0

That

is, for any fixed probability ratio q, the

ratio of decision weights is closer to

unity when the probabilities are low

than when they are high, for example,

n(. l)/n(.2)

n(.4)/n(.8). A hypothetical

weighting function which satisfies these

properties is shown in Fig. 2. The major

qualitative properties of decision weights

can be extended to cases in which the

probabilities of outcomes are subjective-

ly assessed rather than explicitly given.

In these situations, however, decision

weights may also be affected by other

characteristics of an event, such as am-

biguity or vagueness

(Y).

Prospect theory, and the scales illus-

trated in Figs.

and 2, should be viewed

as an approximate, incomplete, and sim-

plified description of the evaluation of

risky prospects. Although the properties

and n summarize a common pattern

of choice, they are not universal: the

preferences of some individuals are not

well described by an S-shaped value

function and a consistent set of decision

weights. The simultaneous measurement

of values and decision weights involves

serious experimental and statistical diffi-

culties

(10).

If n and

were linear throughout, the

preference order between options would

be independent of the framing of acts,

outcomes, or contingencies. Because of

the characteristic nonlinearities of

n and

v, however, different frames can lead to

different choices. The following three

sections describe reversals of preference

caused by variations in the framing of

acts, contingencies, and outcomes.

The

Framing

Acts

Problem

3 [N

1501:

Imagine that you Face

the following pair of concurrent decisions.

First examine both decisions, then indicate

the options you prefer.

Decision (i). Choose between:

a sure gain of

$240 [84

percent]

25%

chance to gain

$1000,

and

75%

chance to gain nothing

[

percent]

Decision (ii). Choose between:

C. a sure loss of

$750 113

percent]

75%

chance to lose

$1000,

and

25%

chance to lose nothing

[87

percent]

The majority choice in decision (i) is

risk averse: a riskless prospect is pre-

ferred to a risky prospect of equal or

greater expected value. In contrast, the

majority choice in decision (ii) is risk tak-

ing: a risky prospect is preferred to a

riskless prospect of equal expected val-

ue. This pattern of risk aversion in

choices involving gains and risk seeking

in choices involving losses is attributable

to the properties of

and n. Because the

value function is S-shaped, the value as-

sociated with a gain of $240 is greater

than 24 percent of the value associated

with a gain of $1000, and the (negative)

value associated with a loss of $750 is

smaller than 75 percent of the value asso-

ciated with a loss of $1000. Thus the

shape of the value function contributes

to risk aversion in decision (i) and to risk

seeking in decision (ii). Moreover, the

underweighting of moderate and high

probabilities contributes to the relative

attractiveness of the sure gain in

(i)

and

to the relative aversiveness of the sure

loss in (ii). The same analysis applies to

problems

and 2.

Because (i) and (ii) were presented to-

gether, the respondents had in effect to

choose one prospect from the set: A and

C, B and C, A and

B and D. The most

common pattern (A and D) was chosen

by 73 percent of respondents, while the

least popular pattern (B and C) was

chosen by only 3 percent of respondents.

However, the combination of B and

C is definitely superior to the combina-

tion A and D, as is readily seen in prob-

lem 4.

Problem

4 [N

861.

Choose between:

25%

chance to win

$240,

and

75%

chance to lose

$760. [0

per-

cent]

25%

chance to win

$250,

and

75%

chance to lose

$750. 1100

per-

cent]

When the prospects were combined

and the dominance of the second option

became obvious, all respondents chose

the superior option. The popularity of

the inferior option in problem

implies

that this problem was framed as a pair of

SCIENCE,

VOL.

211

separate choices. The respondents ap-

parently failed to entertain the possibility

that the conjunction of two seemingly

reasonable choices could lead to an un-

tenable result.

The violations of dominance observed

in problem 3 do not disappear in the

presence of monetary incentives.

dif-

ferent group of respondents who an-

swered

modified version of problem 3,

with real payoffs, produced a similar pat-

tein of choices (11). Other authors have

also reported that violations of the rules

of rational choice, originally observed

hypothetical questioris, were not elimi-

nated by payoffs

(12).

We suspect that nlariy concu~rent de-

cisions in the real world are framed inde-

pendently, and that the preference order

would often be reversed if the decisions

were combined. The respondents in

problem 3 failed to combine options, al-

though the integration was relatively

simple and was encouraged by instruc-

tions (13). The complexity of practical

problems of concurrent decisions, such

as portfolio selection, would prevent

people from integrating options without

computational aids, even

they were in-

clined to do so.

The Framing

Contingencies

The following triple of problems illus-

trates the framing of contingencies. Each

problem was presented to a different

group of respondents. Each group was

told that one participant in ten, pre-

selected at random, would actually be

playing for money. Chance events were

realized, in the respondents' presence,

by drawing a single ball from a bag con-

taining a known proportion of balls of the

winning color, and the winners were paid

immediately.

Problem 5 [N

771: Which of the following

options do you prefer'?

a sure win of $30 [78 percent]

80%

chance to win $45 [22 percent]

Problem

851: Consider the following

two.stage game. In the first stage, there is a

75% chance to end the game without winning

anything, and a 25% chance to move into the

second stage. If you reach the second stage

you have a choice between:

a sure win of $30 [74 percent]

8% chance to win $45 [26 percent]

Your choice must be made before the game

starts, i.e., before the outcome of the first

stage is known. Please indicate the option you

prefer.

Problem 7 [N

811: Which of the following

optiotns do you prefer?

25% chance to win $30 [42 percent]

2Wh chance to win $45 [58 percent]

Stated probability: p

Fig. 2.

hypothetical weighting function.

Let us examine the structure of these

problems. First, note that problems

and

are identical in terms of probabili-

ties and outcomes, because prospect

offers a .25 chance to win $30 and pros-

pect

offers a probability of .25

.80

.20 to win $45. Consistency there-

fore requires that the same choice be

made in problems

and 7. Second, note

that problem

differs from problem 5 on-

ly by the introduction of a preliminary

stage. If the second stage of the game is

reached, then problem

reduces to prob-

lem 5; if the game ends at the first stage,

the decision does not affect the outcome.

Hence there seems to be no reason to

make a different choice in problems 5

and

By this logical analysis, problem

is equivalent to problem 7 on the one

hand and problem 5 on the other. The

participants, however, responded simi-

larly to problems 5 and

but differently

to problem 7. This pattern of responses

exhibits two phenomena of choice: the

certainty effect and the pseudocertainty

effect.

'I'he contrast between problenls 5 and

7 illustrates a phenomenon discovered

by Allais (14), which we have labeled the

certainty effect: a reduction of the proba-

bility of an outcome by a constant factor

has more impact when the outcome was

initially certain than when it was merely

probable. Prospect theory attributes this

effect to the properties of

T. It is easy to

verify, by applying the equation of pros-

pect theory to problems 5 and 7, that

people for whom the value ratio v(30)l

v(45) lies between the weight ratios

~(.20)/~(.25) will pre-

and ~(.80)/~(1.0)

fer

and

contrary to ex-

pected utility theory. Prospect theory

does not predict a reversal of preference

for every individual in problems 5 and

7. It only requires that an individual who

has no preference between A and B pre-

fer

For group data, the theory

predicts the observed directional shift

of preference between the two problems.

The first stage of problem

yields the

same outcome (no gain) for both acts.

Consequently, we propose, people eval-

uate the options conditionally, as if the

second stage had been reached. In this

framing, of course, problem

reduces to

problem

More generally, we suggest

that a decision problem is evaluated con-

ditionally when (i) there is a state in

which all acts yield the same

outcorne,

such as failing to reach the second stage

of the game in problem

and (ii) the

stated probabilities of other outcoines

are coiiditioiial on the nonoccurrence of

this state.

The striking discrepancy betweell the

responses to problems

and

which are

identical in outcomes and probabilities,

could be described as a pseudocertainty

effect. The prospect yielding $30 is rela-

tively more attractive in problem

than

in problem 7, as if it had the advantage of

certainty. The sense of certainty associ-

ated with option

is illusory, however,

since the gain is in fact contingent on

reaching the second stage of the game

(15).

We have observed the certainty effect

in several sets of problems, with out-

comes ranging from vacation trips to the

loss of human lives. In the negative do-

main, certainty exaggerates the aversive-

ness of losses that are certain relative to

losses that are merely probable. In a

question dealing with the response to an

epidemic, for example, most respond-

ents found "a sure loss of 75 lives" more

aversive than "80% chance to lose 100

lives" but preferred

"Im chance to lose

75 lives" over "8% chance to lose 100

lives," contrary to expected utility theo-

ry.

We also obtained the pseudocertainty

effect in several studies where the de-

scription of the decision

problerris fa-

vored conditional evaluation. Pseudo-

certainty can be induced either by a se-

quential formulation, as in problem

by the introduction of causal contin-

gencies. In another version of the epi-

demic problem, for instance, respond-

ents were told that risk to life existed on-

ly in the event (probability

.lo) that the

disease was carried by a particular virus.

Two alternative programs were said to

yield "a sure loss of 75 lives" or "80%

chance to lose 100 lives" if the critical

virus was involved, and no loss of life in

the event (probability

.90) that the dis-

ease was carried by another virus. In ef-

fect, the respondents were asked to

choose between 10 percent chance of

losing 75 lives and 8 percent chance of

losing 100 lives, but their preferences

were the same as when the choice was

JANUARY

1981

between a sure loss of

lives and

percent chance of losing

100

lives.

conditional framing was evidently

adopted in which the contingency of the

noncritical virus was eliminated, giving

rise to a pseudocertainty effect. The cer-

tainty effect reveals attitudes toward risk

that are inconsistent with the axioms of

rational choice, whereas the pseudo-

certainty effect violates the more funda-

mental requirement that preferences

should be independent of problem de-

scription.

Many significant decisions concern ac-

tions that reduce or eliminate the proba-

bility of a hazard, at some cost. The

shape of

in the range of low probabili-

ties suggests that a protective action

which reduces the probability of a harm

from

percent to zero, say, will be val-

ued more highly than an action that re-

duces the probability of the same harm

from

percent to

percent. Indeed,

probabilistic insurance, which reduces

the probability of loss by half, is judged

to be worth less than half the price of

regular insurance that eliminates the risk

altogether

(3).

It is often possible to frame protective

action in either conditional or uncon-

ditional form. For example, an insurance

policy that covers fire but not flood could

be evaluated either as full protection

against the specific risk of fire or as a re-

duction in the overall probability of

property loss. The preceding analysis

suggests that insurance should appear

more attractive when it is presented as

the elimination of risk than when it is de-

scribed as a reduction of risk.

Slovic,

B. Fischhoff, and S. Lichtenstein, in an

unpublished study, found that a hypo-

thetical vaccine which reduces the prob-

ability of contracting a disease from

.20

.10

is less attractive

it is described as

effective in half the cases than if it is pre-

sented as fully effective against one of

two (exclusive and equiprobable) virus

strains that produce identical symptoms.

In accord with the present analysis of

pseudocertainty, the respondents valued

full protection against an identified vi-

rus more than probabilistic protection

against the disease.

The preceding discussion highlights

the sharp contrast between lay responses

to the reduction and the elimination of

risk. Because no form of protective ac-

tion can cover all risks to human welfare,

all insurance is essentially probabilistic:

it reduces but does not eliminate risk.

The probabilistic nature of insurance is

commonly masked by formulations that

emphasize the completeness of pro-

tection against identified harms, but the

sense of security that such formulations

provide is an illusion of conditional fram-

ing. It appears that insurance is bought

as protection against worry, not only

against risk, and that worry can be ma-

nipulated by the labeling of outcomes

and by the framing of contingencies. It is

not easy to determine whether people

value the elimination of risk too much or

the reduction of risk too little. The con-

trasting attitudes to the two forms of pro-

tective action, however, are difficult to

justify on normative grounds (16).

The

Framing of Outcomes

Outcomes are commonly perceived as

positive or negative in relation to a refer-

ence outcome that is judged neutral.

Variations of the reference point can

therefore determine whether a given out-

come is evaluated as a gain or as a loss.

Because the value function is generally

concave for gains, convex for losses, and

steeper for losses than for gains, shifts of

reference can change the value dif-

ference between outcomes and thereby

reverse the preference order between

options

(6).

Problems

and

illustrated

a preference reversal induced by a shift

of reference that transformed gains into

losses.

For another example, consider a per-

son who has spent an afternoon at the

race track, has already lost

$140,

and is

considering a

$10

bet on a

long shot

in the last race. This decision can be

framed in two ways, which correspond

to two natural reference points.

the

status quo is the reference point, the out-

comes of the bet are framed as a gain of

$140

and a loss of

$10.

On the other

hand, it may be more natural to view the

present state as a loss of

$140,

for the

betting day, and accordingly frame the

last bet as a chance to return to the refer-

ence point or to increase the loss to

$150.

Prospect theory implies that the latter

frame will produce more risk seeking

than the former. Hence, people who do

not adjust their reference point as they

lose are expected to take bets that they

would normally find unacceptable. This

analysis is supported by the observation

that bets on long shots are most popular

on the last race of the day (17).

Because the value function is steeper

for losses than for gains, a difference be-

tween options will loom larger when it is

framed as a disadvantage of one option

rather than as an advantage of the other

option. An interesting example of such

an effect in a

riskless context has been

noted by Thaler (18). In a debate on a

proposal to pass to the consumer some

of the costs associated with the process-

ing of credit-card purchases, representa-

tives of the credit-card industry re-

quested that the price difference be la-

beled a cash discount rather than a

credit-card surcharge. The two labels in-

duce different reference points by implic-

itly designating as normal reference the

higher or the lower of the two prices. Be-

cause losses loom larger than gains, con-

sumers are less willing to accept a sur-

charge than to forego a discount.

simi-

lar effect has been observed in

experimental studies of insurance: the

proportion of respondents who preferred

a sure loss to a larger probable loss was

significantly greater when the former

was called an insurance premium (19,

20).

These observations highlight the labil-

ity of reference outcomes, as well as

their role in decision-making. In the ex-

amples discussed so far, the neutral ref-

erence point was identified by the label-

ing of outcomes.

diversity of factors

determine the reference outcome in

everyday life. The reference outcome is

usually a state to which one has adapted;

it is sometimes set by social norms and

expectations; it sometimes corresponds

to a level of aspiration, which may or

may not be realistic.

We have dealt so far with elementary

outcomes, such as gains or losses in a

single attribute. In many situations, how-

ever, an action gives rise to a compound

outcome, which joins a series of changes

in a single attribute, such as a sequence

of monetary gains and losses, or a set of

concurrent changes in several attributes.

To describe the framing and evaluation

of compound outcomes, we use the no-

tion of a psychological account, defined

as an outcome frame which specifies (i)

the set of elementary outcomes that are

evaluated jointly and the manner in

which they are combined and (ii) a refer-

ence outcome that is considered neutral

or normal. In the account that is set up

for the purchase of a car, for example,

the cost of the purchase is not treated as

a loss nor is the car viewed as a gift.

Rather, the transaction as a whole is

evaluated as positive, negative, or neu-

tral, depending on such factors as the

performance of the car and the price of

similar cars in the market.

closely re-

lated treatment has been offered by Tha-

ler (18).

We propose that people generally

evaluate acts in terms of a minimal ac-

count, which includes only the direct

consequences of the act. The minimal

account associated with the decision to

accept a gamble, for example, includes

the money won or lost in that gamble and

excludes other assets or the outcome of

SCIENCE,

VOL.

211

previous gambles. People commonly

adopt minimal accounts because this

mode of framing (i) simplifies evaluation

and reduces cognitive strain, (ii) reflects

the intuition that consequences should

be causally linked to acts, and (iii)

matches the properties of hedonic expe-

rience, which is more sensitive to desir-

able and undesirable changes than to

steady states.

There are situations, however, in

which the outcomes of an act affect the

balance in an account that was pre-

viously set up by a related act. In these

cases, the decision at hand may be eval-

uated in terms of a more inclusive ac-

count, as in the case of the bettor who

views the last race in the context of ear-

lier losses. More generally, a sunk-cost

effect arises when a decision is referred

to an existing account in which the cur-

rent balance is negative. Because of the

nonlinearities of the evaluation process,

the minimal account and a more in-

clusive one often lead to different

choices.

Problems 8 and

illustrate another

class of situations in which an existing

account affects a decision:

Problem 8 [N

1831: Imagine that you

have decided to see a play where admission is

$10 per ticket. As you enter the theater you

discover that you have lost a $10 bill.

Would you still pay $10 for a ticket for the

play?

Yes [88 percent]

No [12 percent]

Problem

2001: Imagine that you

have decided to see a play and paid the admis-

sion price of $10 per ticket. As you enter the

theater you discover that you have lost the

ticket. The seat was not marked and the ticket

cannot be recovered.

Would you pay $10 for another ticket?

Yes [46 percent] No [54 percent]

The marked difference between the re-

sponses to problems 8 and

is an effect

of psychological accounting. We pro-

pose that the purchase of a new ticket in

problem

is entered in the account that

was set up by the purchase of the original

ticket. In terms of this account, the ex-

pense required to see the show is $20, a

cost which many of our respondents ap-

parently found excessive. In problem 8,

on the other hand, the loss of $10 is not

linked specifically to the ticket purchase

and its effect on the decision is accord-

ingly slight.

The following problem, based on ex-

amples by Savage (2, p. 103) and Thaler

(IN), further illustrates the effect of em-

bedding an option in different accounts.

Two versions of this problem were pre-

sented to different groups of subjects.

One group

93) was given the val-

ues that appear in parentheses, and the

JANUARY

1981

other group

88) the values shown

in brackets.

Problem 10: Imagine that you are about to

purchase a jacket for ($125) [$15], and a calcu-

lator for ($15) [$125]. The calculator salesman

informs you that the calculator you wish to

buy is on sale for ($10)

[$I201 at the other

branch of the store, located 20 minutes drive

away. Would you make the trip to the other

store?

The response to the two versions of

problem 10 were markedly different: 68

percent of the respondents were willing

to make an extra trip to save $5 on a $15

calculator; only

percent were willing

to exert the same effort when the price of

the calculator was $125. Evidently the

respondents do not frame problem 10 in

the minimal account, which involves on-

ly a benefit of $5 and a cost of some in-

convenience. Instead, they evaluate the

potential saving in a more inclusive ac-

count, which includes the purchase of

the calculator but not of the jacket. By

the curvature of

a discount of $5 has a

greater impact when the price of the cal-

culator is low than when it is high.

closely related observation has been

reported by Pratt, Wise, and Zeckhauser

(21), who found that the variability of the

prices at which a given product is sold by

different stores is roughly proportional to

the mean price of that product. The same

pattern was observed for both frequently

and infrequently purchased items. Over-

all, a ratio of 2

1 in the mean price of two

products is associated with a ratio of

1.86

1 in the standard deviation of the

respective quoted prices. If the effort

that consumers exert to save each dollar

on a purchase, for instance by a phone

call, were independent of price, the dis-

persion of quoted prices should be about

the same for all products. In contrast,

the data of Pratt

al.

(21) are consistent

with the hypothesis that consumers

hardly exert more effort to save

I5 on a

$150 purchase than to save $5 on a $50

purchase (18). Many readers will recog-

nize the temporary devaluation of money

which facilitates extra spending and re-

duces the significance of small discounts

in the context of a large expenditure,

such as buying a house or a car. This

paradoxical variation in the value of

money is incompatible with the standard

analysis of consumer behavior.

Discussion

In this article we have presented a se-

ries of demonstrations in which seem-

ingly inconsequential changes in the for-

mulation of choice problems caused sig-

nificant shifts of preference. The in-

consistencies were traced to the inter-

action of two sets of factors: variations

in the framing of acts, contingencies, and

outcomes, and the characteristic

non-

linearities of values and decision

weights. The demonstrated effects are

large and systematic, although by no

means universal. They occur when the

outcomes concern the loss of human

lives as well as in choices about money;

they are not restricted to hypothetical

questions and are not eliminated by mon-

etary incentives.

Earlier we compared the dependence

of preferences on frames to the depen-

dence of perceptual appearance on per-

spective. If while traveling in a mountain

range you notice that the apparent rela-

tive height of mountain peaks varies with

your vantage point, you will conclude

that some impressions of relative height

must be erroneous, even when you have

no access to the correct answer. Similar-

ly, one may discover that the relative at-

tractiveness of options varies when the

same decision problem is framed in dif-

ferent ways. Such a discovery will nor-

mally lead the decision-maker to recon-

sider the original preferences, even when

there is no simple way to resolve the in-

consistency. The susceptibility to per-

spective effects is of special concern in

the domain of decision-making because

of the absence of objective standards

such as the true height of mountains.

The metaphor of changing perspective

can be applied to other phenomena of

choice, in addition to the framing effects

with which we have been concerned here

9).

The problem of self-control is natu-

rally construed in these terms. The story

Ulysses' request to be bound to the

mast of the ship in anticipation of the ir-

resistible temptation of the Sirens' call is

often used as a paradigm case (22). In

this example of precommitment, an ac-

tion taken in the present renders inopera-

tive an anticipated future preference. An

unusual feature of the problem of

inter-

temporal conflict is that the agent who

views a problem from a particular tem-

poral perspective is also aware of the

conflicting views that future perspectives

will offer. In most other situations, deci-

sion-makers are not normally aware of

the potential effects of different decision

frames on their preferences.

The perspective metaphor highlights

the following aspects of the psychology

of choice. Individuals who face a deci-

sion problem and have a definite prefer-

ence (i) might have a different preference

in a different framing of the same prob-

lem,

(ii) are normally unaware of alterna-

tive frames and of their potential effects

on the relative attractiveness of options,

457

(iii) would wish their preferences to be

independent of frame, but (iv) are often

uncertain how to resolve detected incon-

sistencies (23). In some cases (such

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