271 Editor’s Note



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271

Editor’s Note

I

t is rather ironic that just as rational



economic models of politics have

emerged as the most influential paradigm

in political science, experimental econo-

mists have increasingly begun to question

the descriptive validity of expected utility

theory. The rise of the behavioral econom-

ics research program owes a great deal to

psychologists Daniel Kahneman and

Amos Tversky, whose research on

systematic deviations from rationality

quickly transcended their own discipline

and significantly influenced other fields,

including management science, finance,

investment, and consumer economics.

Their work has recently begun to influence

political psychology, international

relations, and other areas of political

science. This brief summary of some of

Kahneman’s major contributions is

intended to provide a context for his

upcoming address at the 2002 APSA

meetings.

 It is impossible to do justice to the full

range of Kahneman’s research in the

limited space available here, and I restrict

my focus to his research programs on

judgment and on decision making.

1

 Each is



defined by an extraordinarily influential

article coauthored with Tversky: a 1974



Science article on “Judgment under

Uncertainty: Heuristics and Biases”

(which was followed by a 1982 anthology

with the same title with Slovic and

Tversky, and a 1979 Econometrica article

on prospect theory). One measure of the

impact of these articles is that they have

each been cited over one hundred times per

year on average during the last two

decades (Laibson and Zeckhauser 1998),

and the article on prospect theory is

reported to be the most widely cited article

ever published in Econometrica.

2

Judgment under Uncertainty:



Heuristics and Biases

Judgment involves assessments of the

probability or likely frequency of an event.

In the tradition of bounded rationality

(Simon 1955), the Kahneman/Tversky

research program on judgment posits that

people rely on a limited number of

cognitive shortcuts or judgmental heuris-

tics that simplify the complex task of

assessing probabilities in an uncertain

world. Three of the most important

heuristics are representativeness, availabil-

ity, and anchoring and adjustment. While

these heuristics are often useful and

economical, they neglect important

information relevant to probabilities and

consequently may lead to systematic and

potentially severe errors.

The representativeness heuristic refers

to assessments of the likelihood that one

object or event belongs to a particular

category based on the similarity of that

object or event to typical members of that

category. In one experiment (Tversky and

Kahneman 1974), subjects were given

brief personality descriptions of several

individuals and asked to assess, for each

description, the likelihood that it referred

to an engineer or a lawyer. In one

experimental condition subjects were told

that the descriptions were sampled

randomly from a group of 70 engineers

and 30 lawyers, and in a second experi-

mental condition the proportion of the two

professions was reversed. A rational

assessment of probabilities, following

Bayes’s law, would involve some

combination of prior probabilities (based

on the relative percentage of engineers and

lawyers) and current information (based

on the description), leading to different

probability estimates in the two experi-

mental conditions because of differences

in prior probabilities. Subjects’ estimated

probabilities were nearly identical,

however, demonstrating the tendency to

emphasize representativeness or similarity

and to neglect prior probabilities or base

rates. Similar patterns have been identified

in countless other experiments.

The influence of representativeness also

contributes to the violation of the conjunc-

tion rule in probability theory. Given two

events A and B, the probability of the

conjunction or intersection of A and B

cannot exceed the individual probability of

either A or B. In one experiment,

Kahneman and Tversky (1982) gave

subjects the following description: “Linda

is 31 years old, single, outspoken, and

very bright. She majored in philosophy.

As a student, she was deeply concerned

with issues of discrimination and social

justice, and also participated in anti-

nuclear demonstrations.” Subjects were

asked to assess the likelihood that various

statements about Linda were true, among

them being that “Linda is a bank teller”

and “Linda is a bank teller and is active in

the feminist movement.” Over 85% of

subjects believed it was more likely that

Linda was both a bank teller and a feminist

than just a bank teller, contrary to the laws

of probability.

One interesting implication of represen-

tativeness is that assessments of the

likelihood of a particular outcome might be

less than assessments of the likelihood of

the conjunction of that  outcome and a

particular causal mechanism that might

have led to it. A study in the early 1980s

found that subjects believed that “a

Russian invasion of Poland, and a

complete suspension of diplomatic



Daniel Kahneman: Judgment, Decision,

and Rationality

Jack S. Levy

Rutgers University



Daniel Kahneman is the Eugene

Higgins Professor of Psychology and

professor of psychology and public

affairs in the Woodrow Wilson

School at Princeton University.  He

will deliver the Decade of Behavior

Lecture at the Annual Meeting in

Boston on Friday, August 30 at

8:30 pm.

     The Decade of Behavior Distin-

guished Lecture Program is designed

to showcase behavioral and social

science research addressing the

goals and themes of the Decade of

Behavior initiative

. The

lecture by Kahneman is one of five

sponsored addresses held by

scholarly societies in 2002.

     A renowned scholar, Kahneman

has worked in diverse areas of

psychology, most significantly work

done with the late Amos Tversky, in

which they developed some chal-

lenges to the descriptive validity of

the rationality assumption, and

provided psychological analyses of

a number of significant facts of

judgment and choice. Their

pathbreaking work has crossed

disciplines and influenced political

psychology, international relations,

and other areas of political science.

––

Jack Levy is the Board of Gover-

nors’ Professor of Political Science

at Rutgers University and a scholar

of international relations, specializ-

ing in the causes of war, foreign

policy decision making, and

methodology.

ANNUAL MEETING FOCUS: THE DECADE OF BEHAVIOR LECTURE



272

PS June 2002

relations between the USA and the Soviet

Union sometime in 1983,” was more likely

than the suspension of diplomatic relations

alone (Plous 1993).

People use the availability heuristic

when they judge probabilities based on the

ease with which instances of the phenom-

enon in question come to mind, based on

familiarity, vividness, salience, or

emotional impact, regardless of whether

such cognitively retrievable events

constitute a representative sample of the

universe of relevant events. Television

coverage of a single act of terrorism or

airlines crash has far greater impact than

statistical evidence on peoples’ perceptions

of risk. Availability is a central mechanism

underlying many important hypotheses

about learning from the past based on

analogical reasoning. People tend to learn

from events that have a major impact,

affect the individual or society directly,

have occurred recently, and that are

observed first-hand and at a formative

period in a person’s life (Jervis 1976),

despite such events’ not necessarily

representing the class of events that one

wants to predict.

A third important judgmental heuristic

is anchoring and adjustment. Whereas

Bayes’s law prescribes the optimum way

to combine new information with prior

probabilities, evidence suggests that

people’s adjustment mechanisms are

inefficient, that initial values have a

disproportionate impact on final estimates,

that people update their beliefs more slowly

than a rational Bayesian model would

predict, and that updated probabilities

converge with true values slowly if at all.

3

Prospect Theory

Kahneman and Tversky’s research on

prospect theory has had an even greater

impact, at least in economics, than their

work on judgment. Reacting to the

hegemonic position of expected-utility as a

theory of decision under conditions of

risk, they demonstrated experimentally that

people systematically deviate from the

predictions of expected utility-theory and

some of the axioms upon which it is

based.


4

 Kahneman and Tversky (1979)

constructed prospect theory to integrate

these behavioral anomalies in rational

decision theory into an alternative theory

of risk choice.

The central analytic assumption of

prospect theory is that people define value

relative to a reference point (reference

dependence) rather than in terms of net

assets, based on evidence that people are

more sensitive to changes in assets than to

net asset levels. People give more weight

to losses from that reference point than to

comparable gains (loss aversion), and they

value what they have more than compa-

rable things not in their possession (the



endowment effect), which in turn makes

actual losses hurt more than foregone

gains. Individuals’ strong aversion to

losses, particularly to losses that are

perceived as certain (as opposed to those

that are perceived as probabilistic), induces

them to take significant risks in the hope

of avoiding loss, even though the result

may be an even greater loss and even

though the expected value of the gamble

may be considerably worse than the value

of the certain loss. The result is risk-

averse behavior with respect to gains and

risk-acceptant behavior with respect to

losses.

With value defined in terms of devia-



tions from a reference point, how people

identify their reference points and hence

“frame” a choice problem is critical. A

change in reference point may lead to a

change in preference (preference reversal)

even if the values and probabilities

associated with possible outcomes remain

unchanged. People facing decisions over

medical treatments, for example, respond

differently to a 90% survival rate than they

do to a 10% mortality rate, although the

two are logically equivalent. These



framing effects are difficult to reconcile

with rational choice, which assumes that

logically identical choice problems lead to

identical outcomes.

5

 Similarly, evidence



that an individual’s preference between

two goods can be affected by the introduc-

tion of a third alternative (which may

induce a new reference point) violates

formal utility theory’s basic assumptions

of “independence of irrelevant alterna-

tives” (Kahneman and Tversky 1982).

6

Despite the importance of framing for



choice, we know little about how people

identify their reference points. In static

situations, people often (but not always)

frame their choice problems around the

status quo. In dynamic situations, evidence

suggests that people renormalize their

reference points much more quickly after

making gains (the instant endowment



effect) than after suffering losses.

Experimental studies also show that

individual choice behavior demonstrates a

nonlinear response to probabilities, in

contrast to the linear combination of

utilities and probabilities posited by

expected-utility theory. People overweight

outcomes that are certain relative to

outcomes that are merely probable (the



certainty effect). They also overweight

small probabilities and underweight

moderate and high probabilities. This

means that, except for small probabilities,

people tend to give more weight to the

utility of a possible outcome than to its

probability of occurrence.

7

Kahneman and Tversky (1979)



developed prospect theory to integrate

these observed patterns into an alternative

theory of risky choice. They distinguish

two phases in the choice process. In the



editing phase the actor identifies the

reference point, the available options, the

possible outcomes, and the value and

probability of each of these outcomes. In

the evaluation phase she combines the

values of possible outcomes (as reflected

in an S-shaped value function, which is

characterized by concavity above the

reference point, convexity below it, and a

steeper slope on the loss side) with their

weighted probabilities (as reflected in the

probability weighting function) and then

maximizes over the product. Attitudes

toward risk are determined by the

combination of the S-shaped value

function and the probability weighting

function and not by the value function

alone. Although this combination usually

generates risk aversion for gains and risk

acceptance for losses, it can also produce

(depending on the precise shape of the two

functions) risk acceptance for gains and

risk aversion for losses when probabilities

are small, as illustrated by gambling and

insurance behavior, respectively.

These basic principles lead to a rich and

varied set of propositions about political

behavior.

8

 (1) When actors define their



reference points around the status quo,

there is a “status quo bias” that tends to

reinforce the status quo. If actors frame

their choices around a reference point that

is preferred to the status quo (an expecta-

tion or aspiration level, for example), there

is a tendency to move away from the status

quo, which is destabilizing. (2) State

leaders take more risks to maintain their

international positions, reputations, and

domestic political support against potential

losses than they do to enhance their

positions. The same is true for political

leaders and bureaucratic actors in domestic

politics. In addition, domestic publics

punish their leaders more for losses than

for the failure to make gains. (3) Because

people renormalize their reference points

after gains but not after losses, losers are

risk acceptant in their efforts to recover

losses (sunk costs matter) while winners

are risk acceptant in their efforts to defend

the new status quo against subsequent

losses, so that both sides engage in more

risk-seeking behavior than expected-value

theory predicts.  (4) People (and the law)

treat errors of commission or action as

more blameworthy than errors of omission

or inaction. Social norms against hurting

another are more compelling than norms to

help another. Similarly, both contract and

tort law distinguish between losses

incurred and gains denied, and judges are

much more reluctant to compensate people

for unrealized profits than for losses.

There are related propositions about

strategic interaction and bargaining. (5)



PS

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273

Deterring an adversary from making gains

is easier than deterring her from recover-

ing those losses or compelling her to

accept losses. (6) It is easier for political

actors to cooperate in the distribution of

gains than in the distribution of losses,

because they will take more risks and

bargain harder to minimize their share of

the costs than to maximize their share of

the gains. (7) Knowing that  “losers” in

political primaries who outperform low

expectations are often better off than

“winners” whose margins of victory are

less than expected, political actors try to

influence observers’ reference points by

lowering expectations of their own

performances and raising expectations of

their adversaries’ performances.

This is not the place for a critique of the

potential utility of prospect theory for the

study of politics.

9

 Let me note, however,



that one key set of questions concerns the

generalizability of highly controlled

laboratory studies of individual behavior

in simple choice problems to political

contexts in which the stakes are far higher;

the actors are collective decision-making

bodies rather than individuals; choices are

interactive or strategic rather than deci-

sion-theoretic; time frames are sequential

and dynamic; and key variables of interest

are difficult to measure or even conceptu-

alize along an interval-level scale that is

necessary to test the theory empirically.

10

There are also questions about the utility



of a referent-dependent theory that lacks

both a theory of the reference point and an

established methodology for identifying

reference points empirically.



Conclusion

Kahneman has made seminal contribu-

tions to the interdisciplinary study of

decision and judgment. His work is central

to the bounded rationality research

program and to ongoing debates about the

descriptive accuracy of the expected-utility

microfoundations of rational choice

models of politics. Determining whether

his theory of individual choice can be

extended to the strategic behavior of

collective actors, and tested empirically

against observed behavior in real-world

settings, remains a formidable task for

future research.

References

Farnham, Barbara. 1994. Taking Risks/



Avoiding Losses. Ann Arbor: University

of Michigan Press.

Jervis, Robert. 1976. Perception and

Misperception in International Politics.

Princeton, NJ: Princeton University Press.

Kahneman, Daniel. 1994. “New Challenges

to the Rationality Assumption.” Journal



of Institutional and Theoretical Econom-

ics 150 (1): 18–36.

——, and Amos Tversky. 1979. “Prospect

Theory: An Analysis of Decision Under

Risk.” Econometrica 47:263–91.

——, and Amos Tversky, eds. 2000. Choices,

Values, and Frames. New York: Cam-

bridge University Press.

——, Paul Slovic, and Amos Tversky, eds.

1982. Judgment Under Uncertainty:



Heuristics and Biases. New York:

Cambridge University Press.

——, Ed Diener, and Norbert Schwarz. 1999.

Well-Being: The Foundations of Hedonic

Psychology. New York: Russell Sage.

Laibson, David, and Richard Zeckhauser.

1998. “Amos Tversky and the Ascent of

Behavioral Economics.” Journal of Risk



and Uncertainty 16 (1): 7–47.

Levy, Jack S. 1997. “Prospect Theory,

Rational Choice, and International

Relations.” International Studies Quarterly

41 (1): 87–112.

——. 2000. “The Implications of Framing

and Loss Aversion for International

Conflict.” In Handbook of War Studies II,

ed. Manus I. Midlarsky. Ann Arbor:

University of Michigan Press.

McDermott, Rose. 1998. Risk-Taking in

International Politics: Prospect Theory in

American Foreign Policy. Ann Arbor:

University of Michigan Press.

Plous, Scott. 1993. The Psychology of

Judgment and Decision-making.

Philadelphia: Temple University Press.

Simon, Herbert A. 1955. “A Behavioral

Model of Rational Choice.” Quarterly



Journal of Economics 69:99–118.

Tversky, Amos, and Daniel Kahneman. 1974.

“Judgment under Uncertainty: Heuristics

and Biases.” Science 185:1124–31.

——. 1986. “Rational Choice and the

Framing of Decisions.” Journal of



Business 59: S251–78.

Notes

1. These are Kahneman’s most influential

lines of research. His more recent work on

the psychology of happiness and well-being

(Kahneman, Diener, and Schwarz 1999)

constitutes another major research program.

2. Lowenstein, Roger, “Intrinsic Value:

Outside Who Challenged Dismal Science,”



Wall Street Journal, 6 June 1996.

3. The influence of the anchor is illustrated

in one experiment in which high school

students, given five seconds to estimate the

product of 8x7x6x5x4x3x2x1, produced an

average figure that was four time higher than

for the product of 1x2x3x4x5x6x7x8

(Tversky and Kahneman 1974, 15).

4. The evidence is quite robust. Findings

of departures from rationality have been

confirmed with subjects of considerable

expertise in probability and statistics,

including medical professionals, and it has

been supported by empirical studies of

investment and insurance behavior

(Kahneman and Tversky 2000). The same

patterns have been confirmed by experimen-

tal economists who were determined to (and

expecting to) demonstrate that the findings

were the artifacts of flawed experimental

designs (Camerer 1995).

5. Tversky and Kahneman (1986, S252–

57) refer to this as the “invariance” assump-

tion. Arrow (1982, 6) labels it “extensional-

ity” and describes it as a “fundamental

element of rationality.”

6. Kahneman’s (1994) recent research on

people’s difficulty of correctly anticipating,

at the time they make decisions, the utility

they will experience from a given outcome

also has potentially profound implications for

rationalist theories of behavior.

7. Applications of prospect theory to

political science have given far more

attention to loss aversion and framing than to

probability weighting.

8. This discussion builds  on Levy (2000).

See also Farnham (1994) and McDermott

(1998).

9. See Levy (1997) and O’Neill (2001).



10. Kahneman has always been extremely

cautious about possible generalizations from

highly controlled laboratory settings to real-

world behavior.



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