No subject

into a variety of other disciplines. Psychologists, political scientists,
sociologists, philosophers, game theorists, biologists, and others rely
increasingly on this model to explain and predict human behavior.

The basic question we investigate in this paper is whether exposure to the
self-interest model alters the extent to which people behave in
self-interested ways. The paper is organized into two parts. In the first, we
report the results of a series of empirical studies — some our own, some by
other investigators — that support the hypothesis that economists behave in
more self-interested ways. By itself, this evidence does not demonstrate that
exposure to the self-interest model is the cause of more self-interested
behavior, although, as we will see, a case can be made for this proposition
on a priori grounds. An alternative interpretation is that economists may
simply have been more self-interested to begin with, and this difference was
one reason they chose to study economics. In the second part of the paper, we
present preliminary evidence that exposure to the self-interest model does in
fact increase self-interested behavior.  I. Do Economists Behave Differently?
A. The Free-Rider Experiments

One of the clearest predictions of the self-interest model is that people
will tend to free-ride on the efforts of others when it comes to the
provision of public or collective goods. Even people who would strongly
benefit from having, say, higher program quality on public TV have little
incentive to contribute. After all, any single individual's contribution is
far too small to alter the likelihood of achieving the desired outcome.

A study by Gerald Marwell and Ruth Ames found that students of economics are
indeed much more likely to free-ride in experiments that called for private
contributions to public goods. Their basic experiment involved a group of
subjects who were given an initial endowment of money, which they were to
allocate between two accounts, one “public,” the other “private.” Money
deposited in a subject's private account was returned dollar for dollar to
the subject at the end of the experiment. Money deposited in the public
account was first pooled, then multiplied by some factor greater than one,
and then distributed equally among all subjects.

Under these circumstances, the socially optimal behavior is for each subject
to put her entire endowment in the public account. But the individually most
advantageous strategy is to put all of it in the private account. The
self-interest model predicts that all subjects will follow the latter
strategy. Most don't. Across eleven replications of the experiment, the
average contribution to the public account was approximately 49 percent.

It was only in a twelfth replication with first-year graduate students in
economics as subjects that Marwell and Ames obtained results more nearly
consistent with the self-interest model. These subjects contributed an
average of only 20 percent of their initial endowments to the public account,
a figure significantly less than the corresponding figure for noneconomists
(p<.05).

On completion of each replication of the experiment, Marwell and Ames asked
their subjects two followup questions:

   1. What is a “fair” investment in the public good?  2. Are you concerned
about “fairness” in making your investment decision?

In response to the first question, 75 percent of the noneconomists answered
“half or more” of the endowment, and 25 percent answered “all.” In response
to question 2, almost all noneconomists answered “yes.” The corresponding
responses of the economics graduate students were much more difficult to
summarize. As Marwell and Ames wrote,

    … More than one-third of the economists either refused to answer the
question regarding what is fair, or gave very complex, uncodable responses.
It seems that the meaning of ‘fairness’ in this context was somewhat alien
for this group. Those who did respond were much more likely to say that
little or no contribution was ‘fair.’ In addition, the economics graduate
students were about half as likely as other subjects to indicate that they
were ‘concerned with fairness’ in making their decisions.

The Marwell and Ames study can be criticized on the grounds that their
noneconomist control groups consisted of high school students and college
undergraduates, who differ in a variety of ways from first-year graduate
students in any disciplinted equally of males and females. As our own
evidence will later show, there is a sharp tendency for males to behave less
cooperatively in experiments of this sort. So while the Marwell and Ames
findings are suggestive, they do not clearly establish that economists behave
differently.  B. Economists and the Ultimatum Bargaining Game

The other major study of whether economists behave differently from members
of other disciplines is by John Carter and Michael Irons (1991). These
authors measured the self-interestedness of economists by examining their
behavior in the ultimatum bargaining game. This is a simple game with two
players, an “allocator” and a “receiver.” The allocator is given a sum of
money (in these experiments, $10), and must then propose how to divide this
sum between herself and the receiver. Suppose, for example, the allocator
proposes $X for herself, the remaining $(10-X) for the receiver. Once the
allocator makes this proposal, the receiver has two choices: (1) he may
accept, in which case each player gets the amount proposed by the allocator;
or (2) he may refuse, in which case each player gets zero. The game is played
only once by the same partners.

If both players behave according to the self-interest model, the model makes
an unequivocal prediction about how the game will proceed. Assuming the money
cannot be divided into units smaller than one cent, the allocator will
propose $9.99 for herself and the remaining $0.01 for the receiver, and the
receiver will accept on the grounds that a penny is better than nothing.
Since the game will not be repeated, there is no point in the receiver
turning down a low offer in the hope of generating a better offer in the
future.

Other researchers have shown that the strategy predicted by the self-interest
model is almost never followed in practice: 50-50 splits are the most common
outcome, and most one-sided offers are rejected out of concerns about
fairness.

The research strategy employed by Carter and Irons was to compare the
performance of economics majoe viewer-supported television and the United
Way, which are shown in Figures 2 and 3, respectively.

Figure 2. Median Gift to Public Television.

Figure 3. Median Gift to the United Way.

In fairness to the self-interest model, we should note that there may be
self-interested reasons for contributing even in the case of charities like
the United Way and public television. United Way campaigns, for example, are
usually organized in the workplace and there is often considerable social
pressure to contribute. Public television fund drives often make on-the-air
announcements of donors' names and economists stand to benefit just as much
as the members of any other discipline from being hailed as community-minded
citizens. In the case of smaller, more personal charitable organizations,
there are often even more compelling self-interested reasons for giving.
After all, failure to contribute in accordance with one's financial ability
may mean outright exclusion from the substantial private benefits associated
with membership in religious groups, fraternal organizations, and the like.

An examination of economists' gifts to other charities revealed that their
median annual gift is actually slightly larger, in absolute terms, than the
median for all disciplines taken as a whole. But because economists have
significantly higher salaries than do the members of most other disciplines,
these data, like the data shown in Figures 2 and 3, tend to overstate the
relative generosity of economists. Unfortunately, we do not have direct
income measures for the respondents in our survey, but we do have the number
of years each respondent has been a practitioner in his or her discipline. In
an attempt to take income effects into account, we estimated earnings
functions (salary vs. years of experience) for each discipline using data
from a large private university. We then applied the estimated coefficients
from these earnings functions to the experience data from our survey to
impute an income estimate for each respondent in our survey. Finallyome
figures, together with our respondents' reports of their total charitable
giving to estimate the relationship between income and total giving shown in
Figure 4. In the latter exercise, all economists were dropped from the sample
on the grounds that our object was to see whether the giving pattern of
economists deviates from the pattern we see for other disciplines.

Thus, for example, in Figure 4 we see that a noneconomist with an annual
income of $44,000 (roughly, the median imputed income for architects in our
sample) is expected to give almost $900 per year to charity, while a
noneconomist with an income of $62,000 (roughly the median imputed income for
economists in our sample) is expected to give more than $1400 per year.

Figure 4. Charitable Giving vs. Imputed Income.

Using the relationship between charitable giving and income, we calculated
the expected gift for each respondent as a function of his or her imputed
income. We then calculated our measure of a discipline's generosity as the
ratio of the average value of gifts actually reported by members of the
discipline to the average value of gifts expected on the basis of the
members' imputed incomes. A discipline is thus more generous than expected if
this ratio exceeds 1.0, and less generous if it is less than 1.0. The
computed ratio for economists was 0.91, which means that economists in our
sample gave 91 percent as much as they would have been expected to give on
the basis of their imputed incomes. The performance of economists by this
measure is compared with the performance of other disciplines in Figure 5.

Figure 5. The Ratio of Average Gift to Gift Expected on the Basis of Income.

On a number of other dimensions covered in our survey, the behavior of
economists was little different from the behavior of members of other
disciplines. For example, economists were only marginally less likely than
members of other disciplines to report that they would take costly
administrative action to prosecute a student suspected of cheating.
Economists were age for the entire sample in terms of the numbers of hours
they reportedly spend in “volunteer activities.” In terms of their reported
frequency of voting in presidential elections, economists were only slightly
below the sample average.  D. Economists and the Prisoner's Dilemma

In this section we report our results from a large experimental study of how
economics majors and nonmajors perform in the prisoner's dilemma game.

Table 1 shows the monetary payoffs in dollars to two players, X and Y, in a
standard prisoner's dilemma. In Table 1, as in all prisoner's dilemmas, each
player gets a higher payoff when each cooperates than when each defects. But
when one player's strategy is fixed, the other player always gets a higher
payoff by defecting than by cooperating; and hence the dilemma. By following
individual self-interest, each player does worse than if each had cooperated.

Table 1. Monetary Payoffs for a Prisoner's Dilemma Game.

One of the most celebrated and controversial predictions of the self-interest
model is that people will always defect in one-shot prisoner's dilemmas. The
game thus provides an opportunity to examine the extent to which various
groups exhibit self-interested behavior. Accordingly, we conducted a large
one-shot prisoner's dilemma experiment involving both economics majors and
nonmajors. Many of our subjects were students recruited from courses in which
the prisoner's dilemma is an item on the syllabus. Others were given a
detailed briefing about the game.

Our subjects met in groups of three and each was told that he would play the
game once with each of the other two subjects. The payoff matrix, shown in
Table 1, was the same for each play of the game. Subjects were told that the
games would be played for real money, and that none of the players would
learn how their partners had responded in each play of the game. (More below
on how confidentiality was maintained.)

Following a period in which subjects were given an opportunity to get to know
one another, each subject wam and asked to fill out a form indicating his
response (cooperate or defect) to each of the other two players in his group.
After the subjects had filled out their forms, the results were tallied and
the payments disbursed. Each subject received a single payment that was the
sum of three separate amounts: (1) the payoff from the game with the first
partner; (2) the payoff from the game with the second partner; and (3) a term
that was drawn at random from a large list of positive and negative values.
None of these three elements could be observed separately, only their sum.

The purpose of the random term was to make it impossible for a subject to
infer from her total payment how any of the other subjects had played. It
prevented both the possibility of inferring individual choices and also of
inferring even group patterns of choice. Thus, unlike earlier prisoner's
dilemma experiments, ours did not enable the subject to infer what happened
even when each (or neither) of her partners defected.

In one version of the experiment (the “unlimited” version), subjects were
told that they could make promises not to defect, but they were also told
that the anonymity of their responses would render such promises
unenforceable. In two other versions of the experiment (the “intermediate”
and “limited” versions), subjects were not permitted to make promises about
their strategies. The latter two versions differed from one another in terms
of the length of pre-game interaction, with up to 30 minutes permitted for
the intermediate groups and no more than ten minutes for the limited groups.
All groups were given an extensive briefing on the prisoner's dilemma at the
start of the experiment and each subject was required to complete a
questionnaire at the end to verify that he or she had indeed understood the
consequences of different combinations of choices.  Results for the Sample as
a Whole

For the sample as a whole there were a total of 267 games, which means a
total of 534 choices between cooperation and defection. The choices for
economics majors and nonmajors are shown in Figure 6, where we seor economics
majors was 60.4 percent, as compared to only 38.8 percent for nonmajors.

Figure 6. Defection and Cooperation Rates for the Sample as a Whole.

Needless to say, this pattern of differences is strongly supportive of the
hypothesis that economics majors are more likely than nonmajors to behave
self-interestedly (p<.005).  Adding Control Variables

Earlier we noted that one possible explanation for the observed differences
between economics students and others is that economics students are more
likely than others to be male. To control for the possible influences of sex,
age, and experimental condition, we performed the ordinary least squares
regression reported in Table 2. Because each subject played the game twice,
the individual responses are not statistically independent. To get around
this problem, we limited our sample to the 207 subjects who either cooperated
with, or defected on, each of their two partners. The 60 subjects who
cooperated with one partner and defected on the other were deleted from the
sample. The dependent variable is the subject's choice of strategy, coded as
0 for “cooperate” and 1 for “defect.” The independent variables are “econ”
which takes the value 1 for economics majors, 0 for all others; “unlimited,”
which is 1 for subjects in the unlimited version of the experiment, 0 for all
others; “intermediate,” which is 1 for subjects in the intermediate version,
0 for all others; “limited,” which is the reference category; “sex,” coded as
1 for males, 0 for females; and “class,” coded as 1 for freshmen, 2 for
sophomores, 3 for juniors, and 4 for seniors.

Dependent variable:own response

R2 22.2% R2(adjusted) 20.3%

s 0.4402 with 207 - 6 201 degrees of freedom

SourceSum of SquaresdfMean SquareF-ratio

Regression11.142652.22911.5

Residual38.95402010.193801

VariableCoefficients.e.t-ratio

Constant0.5791270.10415.57

econ0.1688350.07802.16

unlimited0.00----

intermediate-0.0911890.0806-1.13

limited-0.3295720.0728-4.53

sex0.2399440.06423.74

class-0.0653630.0303-2.16 n.

Consistent with a variety of other findings on sex differences in
cooperation, we estimate that, other factors the same, the probability of a
male defecting is almost 0.24 higher than the corresponding probability for a
female. Even after controlling for the influence of gender, we see that the
probability of an economics major defecting is almost 0.17 higher than the
corresponding probability for a nonmajor.

The coefficients for the unlimited and intermediate experimental categories
represent effects relative to the defection rate for the limited category. As
expected, the defection rate is smaller in the intermediate category (where
subjects have more time to interact than in the limited category), and falls
sharply further in the unlimited category (where subjects are permitted to
make promises to cooperate). With subjects' permission, we tape recorded the
conversations of several of the unlimited groups, and invariably each person
promised each of his partners he would cooperate. (There would be little
point, after all, in promising to defect.)

Note, finally, that the overall defection rate declines significantly as
students progress through school. The class coefficient is interpreted to
mean that with the passage of each year the probability of defection
declines, on the average, by almost 0.07. This pattern will prove important
when we take up the question of whether training in economics is the cause of
higher defection rates for economics majors.  The Unlimited Subsample

Focusing on subjects in the unlimited subsample, we see in Figure 7 that the
difference between economics majors and nonmajors virtually disappears once
subjects are permitted to make promises to cooperate. For this subsample, the
defection rate for economics majors is 28.6 percent, for nonmajors 25.9
percent.

Figure 7. The Unlimited Subsample (Promises Permitted).  The Intermediate and
Limited Subsamples

Because the higher defection rates for economics majors are largely
attributable to the no-promises conditions of the experiment, the remainder
of our analysis focuses on subjects in the limited and intermediate
encountered by these groups are of special significance because they come
closest to approximating the conditions that characterize social dilemmas
encountered in practice. After all, people rarely have an opportunity to look
one another in the eye and promise not to litter on deserted beaches or
disconnect the smog control devices on their cars.

In Figure 8 we report the choices for the pooled limited and intermediate
groups. Comparing the entries in Figure 8 with Figure 7, we see clear
evidence of the higher defection rates of both economics majors and
nonmajors. The defection rates of 71.8 percent and 47.3 percent for economics
majors and nonmajors, respectively, differ significantly from one another at
the .01 level.

Figure 8. Defection and Cooperation Rates for the No-Promises Subsample.
Reasons for Cooperation and Defection

As part of the exit questionnaire that tested our subjects' understanding of
the payoffs associated with different combinations of choices, we also asked
them to state their reasons for making the choices they did. We hypothesized
that economists would be more inclined to construe the objective of the game
in self-interested terms, and therefore more likely to refer exclusively to
features of the game itself when describing reasons for their choices. By
contrast, we expected the noneconomists to be more open to alternative ways
of interpreting the game, and thus more likely to look to their partners for
cues about how to play. Accordingly, we expected noneconomists to refer more
often to their feelings about their partners, aspects of human nature, and so
on. This is precisely the pattern we found. Among the sample of economics
students, 31% made exclusive reference to features of the game itself in
explaining their chosen strategies, as compared with only 17% of the
noneconomists. The probability of obtaining such divergent responses by
chance is less than .05.

Another possible explanation for the economists' higher defection rates is
that economists may be more likely than others to expect their partners to
defect. The self-interest model, after all, encouragese know from other
experiments that most subjects defect if they are told that their partners
are going to defect. To investigate the role of expectations, we asked
students in an upper division public finance course in Cornell's economics
department whether they would cooperate or defect in a one-shot prisoner's
dilemma if they knew with certainty that their partner was going to
cooperate. Most of these students were economics majors in their junior and
senior years. Of the 31 students returning our questionnaires, 18 (58
percent) reported that they would defect, only 13 that they would cooperate.
By contrast, just 34 percent (14 of 41) noneconomics Cornell undergraduates
who were given the same questionnaire reported that they would defect on a
partner they knew would cooperate (p<.05). For the same two groups of
subjects, almost all respondents (30 of 31 economics students and 36 of 41
noneconomics students) said they would defect if they knew their partner
would defect. From these responses, we conclude that while expectations of
partner performance do indeed play a strong role in predicting behavior,
defection rates would remain significantly higher for economists than for
noneconomists even if both groups held identical expectations about partner
performance.  II. Why Do Economists Behave Differently?

In the preceding sections we have seen evidence that economists behave less
cooperatively than noneconomists along a variety of different dimensions.
This difference in behavior might be exclusively the result of training in
economics. Alternatively, it might exist simply because people who chose to
major in economics were different initially. Or it might be some combination
of these two effects. We now report evidence on whether training in economics
plays a causal role.  A. Comparing Upperclassmen and Underclassmen

If economics training plays a causal role in uncooperative behavior, then we
would expect defection rates in the prisoner's dilemma experiments to rise
with exposure to training in economics. Again focusing on the no-promises
subsample, the defection rates are broken down by majre 9. As shown, the
defection rate for economics majors is virtually the same for both
upperclassmen (juniors and seniors) and underclassmen (freshmen and
sophomores). By contrast, the defection rate for nonmajors is approximately
33 percent higher for underclassmen than for upperclassmen.

Figure 9. Defection Rates for Upper- and Underclassmen.

The pattern shown in Figure 9 continues to hold when we control for the
effects of other factors that influence defection rates. As the regression
equation summarized in Table 3 shows, the defection probabilities do not
differ significantly between upperclass economics majors and underclass
economics majors. For nonmajors, defection probabilities are sharply lower
than for majors in each category, and fall by more than 0.16 with the
transition to upperclass status.

Dependent variable:own response

R2 16.4%% R2(adjusted) 12.8%

s 0.4673 with 124 - 6 118 degrees of freedom

SourceSum of SquaresdfMean SquareF-ratio

Regression5.0359951.00724.61

Residual25.76241180.218325

VariableCoefficients.e.t-ratio

Constant0.6287340.1436 4.38

limited0.00----

intermediate-0.0950400.0876-1.09

sex0.2575380.08962.88

econ 1,20.00----

econ 3,4-0.0269360.1623 -0.166

nonecon 1,2-0.1510500.1426-1.06

nonecon 3,4-0.3132660.1427-2.20

Table 3. The Effect of Education Level on Defection Rates.

Thus, for students in general there is a pronounced tendency toward more
cooperative behavior with movement toward graduation, a trend that is
conspicuously absent for economics majors. On the basis of the available
evidence, we are in no position to say whether the trend for noneconomists
reflects something about the content of noneconomics courses. But regardless
of the causes of this trend, the fact that it is not present for economists
is consistent with the hypothesis that training in economics plays at least
some causal role in the lower observed cooperation rates of economists.  B.
Honesty Surveys

In a further attempt to assess whether training in economics inhibits
cooperation in social dilemmas, we posed a pair of ethical dilemmas to
students in two introductory microeconomics courses at Cornell University and
to a control group of students in an introductory astronCornell. In one
dilemma, the owner of a small business is shipped ten microcomputers but is
billed for only nine and the question is whether the owner will inform the
computer company of the error. Subjects are first asked to estimate the
chances (0 - 100%) that the owner would point out the mistake, and then, on
the same response scale, to indicate how likely they would be to point out
the error if they were the owner. The second dilemma concerns whether a lost
envelope containing $100 and bearing the owner's name and address is likely
to be returned by the person who finds it. Subjects are first asked to
imagine that they have lost the envelope and to estimate the likelihood that
a stranger would return it. They are then asked to assume that the roles are
reversed and to indicate the chances that they would return the money to a
stranger.

Students in each class completed the questionnaire on two occasions, first
during the initial week of class in September, and then during the final week
of class in December.

For each of the four questions, each student was coded as being “more honest”
if the probability checked for that question rose between September and
December; “less honest” if it fell during that period; and “no change” if it
remained the same. Our hypothesis was that even a single semester of
introductory microeconomics would have a measurable effect both on students'
expectations of the level of self-interested behavior in society and on their
own propensities to behave self-interestedly.

The first introductory microeconomics instructor (instructor A) whose
students we surveyed is a mainstream economist with research interests in
industrial organization and game theory. In class lectures, this instructor
placed heavy emphasis on the prisoner's dilemma and related illustrations of
how survival imperatives often militate against cooperation. The second
microeconomics instructor (instructor B) is a specialist in economic
development in Maoist China who did not emphasize such material to the same
degree, but did assign a  On the basis of these differences, our expectation
was that any observed effects of economics training should be stronger in
instructor A's class than in instructor B's. The results for the three
classes are summarized in Figures 10-12.

Introductory Microeconomics A (N 48)

Figure 10. Questionnaire Findings, Introductory Microeconomics A.

Introductory Microeconomics B (N 115)

Figure 11 Figure 10. Questionnaire Findings, Introductory Microeconomics B.

Introduction to Astronomy (N 30)

Figure 12. Questionnaire Findings: Introduction to Astronomy.

As Figures 10 and 11 indicate, a tendency toward more cynical responses was
observed in instructor A's introductory economics class but not in instructor
B's. In our control group of introductory astronomy students (Figure 12),
there was a weak tendency toward less cynical expectations and behavior over
the course of the semester.

It may seem natural to wonder whether the differences reflected in Figures 10
and 11 might stem in part from the fact that students chose their instructors
rather than being randomly assigned. Perhaps the ideological reputations of
the two professors were known in advance to many students, with the result
that a disproportionate number of the least cynical students chose to take
instructor B's course. Two observations, however, weigh heavily against this
interpretation. First, the average values of the initial responses to the
four questions were in fact virtually the same for both classes. And second,
note that Figures 10 and 11 record not the level of cynicism but the change
in that level between the beginning and end of the course. Figure 11 thus
tells us that even if the students in Microeconomics A were more cynical to
begin with, they became still more so during the course of the semester. This
finding is consistent with the hypothesis that emphasis on the self-interest
model tends to inhibit cooperation.  Discussion

There have been several previous attempts to discover whether economists
behave in more self-interested ways than do noneconomists. The Marwell and
Ames finding of a greater tendency to free rrtain because their samples of
economists and noneconomists were different on so many dimensions other than
academic history and interests. The Carter and Irons findings on the
ultimatum bargaining game were subject to an alternative interpretation based
on the possibility that economics majors may have held different views on how
performance in the preliminary word game affected entitlements in the
ultimatum game.

We believe our prisoner's dilemma results constitute the clearest
demonstration to date of a large difference in the extent to which economists
and noneconomists behave self-interestedly. And our survey of charitable
giving lends additional support to the hypothesis that economists are more
likely than others to free ride.

But we also emphasize that both of these exercises produced evidence that
economists behave in traditionally communitarian ways under at least some
circumstances. For example, they reported spending as much time as others in
volunteer activities, and their total gifts to charity were only slightly
less than would have been expected on the basis of their incomes. Finally, in
the unlimited version of our prisoner's dilemma experiments, where subjects
were allowed to promise to cooperate, economists were almost as likely to
cooperate as noneconomists were.

We also found evidence consistent with the view that the differences in
cooperativeness are caused in part by training in economics. First, we saw
that the gap in defection rates between economics majors and nonmajors tends
to widen as students move toward graduation. Second, we saw that introductory
microeconomics, at least if taught in a certain way, seems to affect student
attitudes toward honesty.

Clearly, our evidence for the existence of a difference between the behavior
of economists and noneconomists is more compelling than our evidence for the
causal role of economics training in creating that difference. But there is
additional indirect evidence for such a role. One of the clearest patterns to
emerge in several decades of experimental research on the that the behavior
of any given player is strongly influenced by that player's prediction about
what his partner will do. In experiments involving noneconomists, people who
expect their partners to cooperate usually cooperate themselves, and those
who expect their partners to defect almost always defect. In our experiments,
economists were 42 percent more likely than noneconomists to predict that
their partners would defect. It would be remarkable indeed if none of this
difference in outlook were the result of repeated exposure to a behavioral
model whose unequivocal prediction is that people will defect whenever
self-interest dictates.

For the sake of discussion, suppose that exposure to the self-interest model
does, in fact, cause people to behave more selfishly. Should this be a cause
for concern? To the extent that norms favoring cooperation help solve
prisoner's dilemmas and other market failures, one cost of a rise in selfish
behavior is a fall in the real value of economic output. Who bears this cost?
By conventional accounts, it is those who continue to behave cooperatively, a
troubling outcome on equity grounds. Several researchers have recently
suggested, however, that the ultimate victims of noncooperative behavior may
be the very people who practice it. Suppose, for example, that some people
always cooperate in one-shot prisoner's dilemmas while others always follow
the seemingly dominant strategy of defecting. If people are free to interact
with others of their own choosing, and if there are cues that distinguish
cooperators from defectors, then cooperators will interact selectively with
one another and earn higher payoffs than defectors. Elsewhere we have shown
that even on the basis of brief encounters involving strangers, experimental
subjects are adept at predicting who will cooperate and who will defect in
prisoner's dilemma games. If people are even better at predicting the
behavior of people they know well, it seems that the direct pursuit of
material self-interest may indeed often be self-defeating.

These observations do not challenge the obvious importance of self-interest
as a human motive. But they do suggest the need for a richer model of 20human
behavior, one that explicitly recognizes that people who hold cooperative
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