Collective Action and the Evolution of Social Norms

Collective Action and the Evolution of
Social Norms
Elinor Ostrom
With the publication of The Logic of Collective Action in 1965, Mancur
Olson challenged a cherished foundation of modern democratic
thought that groups would tend to form and take collective action
whenever members jointly benefitted. Instead, Olson (1965, p. 2) offered the
provocative assertion that no self-interested person would contribute to the
production of a public good: â€œ[U]nless the number of individuals in a group is
quite small, or unless there is coercion or some other special device to make
individuals act in their common interest, rational, self-interested individuals will not
act to achieve their common or group interests.â€ This argument soon became known
as the â€œzero contribution thesis.â€
The idea that rational agents were not likely to cooperate in certain
settings, even when such cooperation would be to their mutual benefit, was also
soon shown to have the structure of an n-person prisonerâ€™s dilemma
game (Hardin 1971, 1982). Indeed, the prisonerâ€™s dilemma game, along
with other social dilemmas, has come to be viewed as the canonical representation of collective action problems (Lichbach, 1996). The zero contribution
thesis underpins the presumption in policy textbooks (and many contemporary
public policies) that individuals cannot overcome collective action problems
and need to have externally enforced rules to achieve their own long-term
self-interest.
The zero contribution thesis, however, contradicts observations of everyday
life. After all, many people vote, do not cheat on their taxes, and contribute effort
y Elinor Ostrom is Co-Director, Workshop in Political Theory and Policy Analysis, Center for
the Study of Institutions, Population, and Environmental Change, Indiana University,
Bloomington, Indiana.
Journal of Economic Perspectivesâ€”Volume 14, Number 3â€”Summer 2000â€”Pages 137â€“158
to voluntary associations. Extensive fieldwork has by now established that individuals in all walks of life and all parts of the world voluntarily organize themselves so
as to gain the benefits of trade, to provide mutual protection against risk, and to
create and enforce rules that protect natural resources.1 Solid empirical evidence
is mounting that governmental policy can frustrate, rather than facilitate, the
private provision of public goods (Montgomery and Bean, 1999). Field research
also confirms that the temptation to free ride on the provision of collective benefits
is a universal problem. In all known self-organized resource governance regimes
that have survived for multiple generations, participants invest resources in monitoring and sanctioning the actions of each other so as to reduce the probability of
free riding (Ostrom, 1990).
While these empirical studies have posed a severe challenge to the zero
contribution theory, these findings have not yet been well integrated into an
accepted, revised theory of collective action. A substantial gap exists between the
theoretical prediction that self-interested individuals will have extreme difficulty in
coordinating collective action and the reality that such cooperative behavior is
widespread, although far from inevitable.
Both theorists and empirical researchers are trying to bridge this gap. Recent
work in game theoryâ€”often in a symbiotic relationship with evidence from experimental studiesâ€”has set out to provide an alternative micro theory of individual
behavior that begins to explain anomalous findings (McCabe, Rassenti and Smith,
1996; Rabin, 1993; Fehr and Schmidt, 1999; Selten, 1991; Bowles, 1998). On the
empirical side, considerable effort has gone into trying to identify the key factors
that affect the likelihood of successful collective action (Feeny et al., 1990; Baland
and Platteau, 1996; Ostrom, forthcoming).
This paper will describe both avenues of research on the underpinnings of
collective action, first focusing on the experimental evidence and potential
theoretical explanations, and then on the real-world empirical evidence. This
two-pronged approach to the problem has been a vibrant area of research that
is yielding many insights. A central finding is that the world contains multiple
types of individuals, some more willing than others to initiate reciprocity to
achieve the benefits of collective action. Thus, a core question is how potential
cooperators signal one another and design institutions that reinforce rather
than destroy conditional cooperation. While no full-blown theory of collective
action yet exists, evolutionary theories appear most able to explain the diverse
findings from the lab and the field and to carry the nucleus of an overarching
theory.
1 See Milgrom, North and Weingast (1990) and Bromley et al. (1992). An extensive bibliography by Hess
(1999) on diverse institutions for dealing with common pool resources can be searched on the web at
^http://www.indiana.edu/;workshop/wsl/wsl.html& or obtained on a CD-ROM disk.
138 Journal of Economic Perspectives
Laboratory Evidence on Rational Choice in Collective Action
Situations
Most studies by political economists assume a standard model of rational
individual actionâ€”what I will call a rational egoist. A wide range of economic
experiments have found that the rational egoist assumption works well in predicting the outcome in auctions and competitive market situations (Kagel and Roth,
1995). While subjects do not arrive at the predicted equilibrium in the first round
of market experiments, behavior closely approximates the predicted equilibrium by
the end of the first five rounds in these experiments. One of the major successes of
experimental economics is to demonstrate the robustness of microeconomic theory
for explaining market behavior.
In regard to collective action situations, on the other hand, the results are
entirely different. Linear public good experiments are widely used for examining
the willingness of individuals to overcome collective action problems. In a linear
public good experiment, each individual is endowed with a fixed set of assets and
must decide how many of these assets to contribute to a public good. When an
individual makes a contribution of, say, 10 units to the public good, each of the
participants in the group, including that individual, receive a benefit of, say, five
units apiece. In this setting, the optimal outcome for the group of players as a whole
is for everyone to contribute all of their endowments to provide the public good (if
a group of 10 people, each individual contribution of 10 will have a social payoff of
50!). However, the unique equilibrium for rational egoists in a single-shot game is
that everyone contributes zero, since each individual has access to benefits of the
public good funded by the contributions of others, without paying any costs.2
If the public goods game is played for a finite number of rounds, zero is also
the predicted equilibrium for every round. Rational egoists will reason that zero
contribution is the equilibrium in the last round, and because they expect everyone
to contribute zero in the last round, they also expect everyone to contribute zero
in the second-to-last round, and eventually by backward induction they will work
their way to the decision not to contribute to the public good in the present. Of
course, these predictions are based on the assumptions that all players are fully
rational and interested only in their own immediate financial payoff, that all players
2 In a linear public good game, utility is a linear function of individual earnings,
Ui 5 Ui @~E 2 xi! 1 A z P ~O xi!#,
where E is an individual endowment of assets, xi is the amount of this endowment contributed to provide
the good, A is the allocation formula used to distribute the group benefit to individual players, and P
is the production function. In a linear public good game, A is specified as 1/N and 0 , 1/N , P , 1
(but both of these functions vary in other types of collective action). So long as P , 1, contributing to
the collective good is never an optimal strategy for a fully self-interested player.
Elinor Ostrom 139
understand the structure of the game fully and believe that all other players are
fully rational, and that no external actor can enforce agreements between the
players.
Since the first public good experiments were undertaken by Dawes, McTavish
and Shaklee (1977), a truly huge number of such experiments has been undertaken under various conditions (see Davis and Holt, 1993; Ledyard, 1995; and
Offerman, 1997, for an overview). By now seven general findings have been
replicated so frequently that these can be considered the core facts that theory
needs to explain.
1) Subjects contribute between 40 and 60 percent of their endowments to the
public good in a one-shot game as well as in the first round of finitely repeated
games.
2) After the first round, contribution levels tend to decay downward, but
remain well above zero. A repeated finding is that over 70 percent of subjects
contribute nothing in the announced last round of a finitely repeated sequence.
3) Those who believe others will cooperate in social dilemmas are more likely
to cooperate themselves. A rational egoist in a public good game, however, should
not in any way be affected by a belief regarding the contribution levels of others.
The dominant strategy is a zero contribution no matter what others do.
4) In general, learning the game better tends to lead to more cooperation, not
less. In a clear test of an earlier speculation that it just took time for subjects to learn
the predicted equilibrium strategy in public good games, Isaac, Walker and Williams (1994) repeated the same game for 10 rounds, 40 rounds, and 60 rounds with
experienced subjects who were specifically told the end period of each design. They
found that the rate of decay is inversely related to the number of decision rounds.
In other words, instead of learning not to cooperate, subjects learn how to cooperate at a moderate level for ever-longer periods of time!
5) Face-to-face communication in a public good gameâ€”as well as in other
types of social dilemmasâ€”produces substantial increases in cooperation that are
sustained across all periods including the last period (Ostrom and Walker, 1997).3
The strong effect of communication is not consistent with currently accepted
theory, because verbal agreements in these experiments are not enforced. Thus,
communication is only â€œcheap talkâ€ and makes no difference in predicted outcomes in social dilemmas. But instead of using this opportunity to fool others into
cooperating, subjects use the time to discuss the optimal joint strategy, to extract
promises from one another, and to give verbal tongue-lashings when aggregate
contributions fall below promised levels. Interestingly, when communication is
implemented by allowing subjects to signal promises to cooperate through their
3 Even more startling, Bohnet and Frey (1999) find that simply allowing subjects to see the other persons
with whom they are playing greatly increases cooperation as contrasted to completely anonymous
situations. Further, Frank, Gilovich and Regan (1993) find that allowing subjects to have a face-to-face
discussion enables them to predict who will play cooperatively at a rate significantly better than chance.
140 Journal of Economic Perspectives
computer terminals, much less cooperation occurs than in experiments allowing
face-to-face communication.
6) When the structure of the game allows it, subjects will expend personal
resources to punish those who make below-average contributions to a collective
benefit, including the last period of a finitely repeated game. No rational egoist is
predicted to spend anything to punish others, since the positive impact of such an
action is shared equally with others whether or not they also spend resources on
punishing. Indeed, experiments conducted in the United States, Switzerland, and
Japan show that individuals who are initially the least trusting are more willing to
contribute to sanctioning systems and are likely to be transformed into strong
cooperators by the availability of a sanctioning mechanism (Fehr and GaÂ¨chter,
forthcoming). The finding that face-to-face communication is more efficacious
than computerized signaling is probably due to the richer language structure
available and the added intrinsic costs involved in hearing the intonation and
seeing the body language of those who are genuinely angry at free riders (Ostrom,
1998a).
7) The rate of contribution to a public good is affected by various contextual
factors including the framing of the situation and the rules used for assigning
participants, increasing competition among them, allowing communication, authorizing sanctioning mechanisms, or allocating benefits.
These facts are hard to explain using the standard theory that all individuals
who face the same objective game structure evaluate decisions in the same way!4 We
cannot simply resort to the easy criticism that undergraduate students are erratic.
Increasing the size of the payoffs offered in experiments does not appear to change
the broad patterns of empirical results obtained.5 I believe that one is forced by
these well-substantiated facts to adopt a more eclectic (and classical) view of human
behavior.
Building a Theory of Collective Action with Multiple Types of
Players
From the experimental findings, one can begin to put together some of the
key assumptions that need to be included in a revised theory of collective action.
4 Although the discussion here focuses on collective action and public good games in particular, a
broader range of experiments exists in which the rational egoistâ€™s prediction pans out badly. These
include the ultimatum game, the dictator game, the trust game, and common-pool resources games with
communication.
5 Most of these experiments involve ultimatum games but the findings are quite relevant. Cameron
(1995), for example, conducted ultimatum experiments in Indonesia and thereby was able to use sums
that amounted to three monthsâ€™ wages. In this extremely tempting situation, she still found that 56
percent of the Proposers allocated between 40 and 50 percent of this very substantial sum to the
Responder.
Collective Action and the Evolution of Social Norms 141
Assuming the existence of two types of â€œnorm-usingâ€ playersâ€”â€œconditional cooperatorsâ€ and â€œwilling punishersâ€â€”in addition to rational egoists, enables one to
start making more coherent sense out of the findings of the laboratory experiments
on contributions to public goods.
Conditional cooperators are individuals who are willing to initiate cooperative
action when they estimate others will reciprocate and to repeat these actions as long
as a sufficient proportion of the others involved reciprocate. Conditional cooperators are the source of the relatively high levels of contributions in one-shot or
initial rounds of prisonerâ€™s dilemma and public good games. Their initial contributions may encourage some rational egoists to contribute as well, so as to obtain
higher returns in the early rounds of the game (Kreps et al., 1982). Conditional
cooperators will tend to trust others and be trustworthy in sequential prisonerâ€™s
dilemma games as long as the proportion of others who return trust is relatively
high. Conditional cooperators tend to vary, however, in their tolerance for free
riding. Some are easily disappointed if others do not contribute, so they begin to
reduce their own contributions. As they reduce their contributions, they discourage
other conditional cooperators from further contributions. Without communication
or institutional mechanisms to stop the downward cascade, eventually only the most
determined conditional cooperators continue to make positive contributions in the
final rounds.
The first four findings are consistent with an assumption that conditional
cooperators are involved in most collective action situations. Conditional cooperators are apparently a substantial proportion of the population, given the large
number of one-shot and finitely repeated experiments with initial cooperation rates
ranging from 40 to 60 percent. Estimating that others are likely to cooperate should
increase their willingness to cooperate. Further, knowing the number of repetitions
will be relatively long, conditional cooperators can restrain their disappointment
with free riders and keep moderate levels of cooperation (and joint payoffs) going
for ever-longer periods of time.
The fifth and sixth findings depend on the presence of a third type of player
who is willing, if given an opportunity, to punish presumed free riders through
verbal rebukes or to use costly material payoffs when available. Willing punishers
may also become willing rewarders if the circle of relationships allows them to
reward those who have contributed more than the minimal level. Some conditional
cooperators may also be willing punishers. Together, conditional cooperators and
willing punishers create a more robust opening for collective action and a mechanism for helping it grow. When allowed to communicate on a face-to-face basis,
willing punishers convey a considerable level of scorn and anger toward others who
have not fully reciprocated their trust and give substantial positive encouragement
when cooperation rates are high. Even more important for the long-term sustainability of collective action is the willingness of some to pay a cost to sanction others.
The presence of these norm-using types of players is hard to dispute given the
142 Journal of Economic Perspectives
empirical evidence. The key question now is: How could these norm-using types of
players have emerged and survived in a world of rational egoists?
Emergence and Survival of Multiple Types of Players in Evolutionary Processes
Evolutionary theories provide useful ways of modeling the emergence and
survival of multiple types of players in a population. In a strict evolutionary model,
individuals inherit strategies and do not change strategies in their lifetime. In this
approach, those carrying the more successful strategies for an environment reproduce at a higher rate. After many iterations the more successful strategies come to
prominence in the population (Axelrod, 1986). Such models are a useful starting
point for thinking about competition and relative survival rates among different
strategies.6
Human evolution occurred mostly during the long Pleistocene era that lasted
for about 3 million years, up to about 10,000 years ago. During this era, humans
roamed the earth in small bands of hunter-gatherers who were dependent on each
other for mutual protection, sharing food, and providing for the young. Survival
was dependent not only on aggressively seeking individual returns but also on
solving many day-to-day collective action problems. Those of our ancestors who
solved these problems most effectively, and learned how to recognize who was
deceitful and who was a trustworthy reciprocator, had a selective advantage over
those who did not (Barkow, Cosmides and Tooby, 1992).
Evolutionary psychologists who study the cognitive structure of the human
brain conclude that humans do not develop general analytical skills that are then
applied to a variety of specific problems. Humans are not terribly skilled at general
logical problem solving (as any scholar who has taught probability theory to
undergraduates can attest). Rather, the human brain appears to have evolved a
domain-specific, human-reasoning architecture (Clark and Karmiloff-Smith, 1991).
For example, humans use a different approach to reasoning about deontic relationshipsâ€”what is forbidden, obligated, or permittedâ€”as contrasted to reasoning
about what is true and false. When reasoning about deontic relationships, humans
tend to check for violations, or cheaters (Manktelow and Over, 1991). When
reasoning about whether empirical relationships are true, they tend to use a
confirmation strategy (Oaksford and Chater, 1994). This deontic effect in human
reasoning has repeatedly been detected even in children as young as three years old
and is not associated with overall intelligence or educational level of the subject
(Cummins, 1996).
Thus, recent developments in evolutionary theory and supporting empirical
research provide strong support for the assumption that modern humans have
inherited a propensity to learn social norms, similar to our inherited propensity to
learn grammatical rules (Pinker, 1994). Social norms are shared understandings
6 For examples of strict evolutionary models involving collective action, see Nowak and Sigmund (1998),
Sethi and Somanathan (1996) and Epstein and Axtell (1996).
Elinor Ostrom 143
about actions that are obligatory, permitted, or forbidden (Crawford and Ostrom,
1995). Which norms are learned, however, varies from one culture to another,
across families, and with exposure to diverse social norms expressed within various
types of situations. The intrinsic cost or anguish that an individual suffers from
failing to use a social norm, such as telling the truth or keeping a promise, is
referred to as guilt, if entirely self-inflicted, or as shame, when the knowledge of the
failure is known by others (Posner and Rasmusen, 1999).
The Indirect Evolutionary Approach to Adaptation Through Experience
Recent work on an indirect evolutionary approach to the study of human
behavior offers a rigorous theoretical approach for understanding how preferencesâ€”including those associated with social normsâ€”evolve or adapt (GuÂ¨th and
Yaari, 1992; GuÂ¨th, 1995). In an indirect evolutionary model, players receive objective payoffs, but make decisions based on the transformation of these material
rewards into intrinsic preferences. Those who value reciprocity, fairness, and being
trustworthy add a subjective change parameter to actions (of themselves or others)
that are consistent or not consistent with their norms. This approach allows
individuals to start with a predisposition to act in a certain wayâ€”thus, they are not
rational egoists who only look forwardâ€”but it also allows those preferences to
adapt in a relatively short number of iterations given the objective payoffs they
receive and their intrinsic preferences about those payoffs.
Social dilemmas associated with games of trust, like sequential prisonerâ€™s
dilemma games, are particularly useful games for discussing the indirect evolutionary approach. In such games, if two players trust each other and cooperate, they can
both receive a moderately high payoff. However, if one player cooperates and the
other does not, then the one who did not cooperate receives an even higher payoff,
while the other receives little or nothing. For a rational egoist playing this game, the
choice is not to trust, because the expectation is that the other player will not trust,
either. As a result, both players will end up with lower payoffs than if they had been
able to trust and cooperate. When considering such games, it is useful to remember
that most contractual relationshipsâ€”whether for private or public goodsâ€”have at
least an element of this basic structure of trying to assure mutual trust. An indirect
evolutionary approach explains how a mixture of norm-users and rational egoists
would emerge in settings where standard rational choice theory assumes the
presence of rational egoists alone.
In this approach, social norms may lead individuals to behave differently in the
same objective situation depending on how strongly they value conformance with
(or deviance from) a norm. Rational egoists can be thought of as having intrinsic
payoffs that are the same as objective payoffs, since they do not value the social
norm of reciprocity. Conditional cooperators (to take only one additional type of
player for now) would be modeled as being trustworthy types and would have an
additional parameter that adds value to the objective payoffs when reciprocating
trust with trustworthiness. By their behavior and resulting interaction, however,
144 Journal of Economic Perspectives
different types of players are likely to gain differential objective returns. In a game
of trust where players are chosen from a population that initially contains some
proportion of rational egoists and conditional cooperators, the level of information
about player types affects the relative proportion of rational egoists and conditional
cooperators over time. With complete information regarding types, conditional
cooperators playing a trustworthy strategy will more frequently receive the higher
payoff, while rational egoists will consistently receive a lower payoff, since others will
not trust them.
Only the trustworthy type would survive in an evolutionary process with complete information (GuÂ¨th and Kliemt, 1998, p. 386). Viewed as a cultural evolutionary process, new entrants to the population would be more likely to adopt the
preference ordering of those who obtained the higher material payoffs in the
immediate past (Boyd and Richerson, 1985). Those who were less successful would
tend to learn the values of those who had achieved higher material rewards
(BoÂ¨rgers and Sarin, 1997).7 Where a playerâ€™s type is common knowledge, rational
egoists would not survive. Full and accurate information about all playersâ€™ types,
however, is a very strong assumption and unlikely to be met in most real world
settings.
If there is no information about player types for a relatively large population,
preferences will evolve so that only rational egoists survive.8 If information about
the proportion of a population that is trustworthy is known, and no information is
known about the type of a specific player, GuÂ¨th and Kliemt (1998) show that first
players will trust second players as long as the expected return of meeting trustworthy players and receiving the higher payoff exceeds the payoff obtained when
neither player trusts the other. In such a setting, however, the share of the
population held by the norm-using types is bound to decline. On the other hand,
if there is a noisy signal about a playerâ€™s type that is at least more accurate than
random, trustworthy types will survive as a substantial proportion of the population.
Noisy signals may result from seeing one another, face-to-face communication, and
various mechanisms that humans have designed to monitor each otherâ€™s behavior.
Evidence Testing the Indirect Evolutionary Approach
An indirect evolutionary approach is able to explain how a mixture of contingent cooperators and rational egoists would emerge in settings where traditional
7 Eshel, Samuelson and Shaked (1998) develop a learning model where a population of Altruists who
adopt a strategy of providing a local public good interacts in a local neighborhood with a population of
Egoists who free ride. In this local interaction setting, Altruistsâ€™ strategies are imitated sufficiently often
in a Markovian learning process to become one of the absorbing states. Altruists interacting with Egoists
outside a circular local neighborhood are not so likely to survive.
8 This implies that, in a game where players know only their own payoffs and not the payoffs of others,
they are more likely to behave like rational egoists. McCabe and Smith (1999) show that players tend to
evolve toward the predicted, subgame perfect outcomes in experiments where they have only private
information of their own payoffs and to cooperative outcomes when they have information about payoffs
and the moves made by other players (see also McCabe, Rassenti and Smith, 1996).
Collective Action and the Evolution of Social Norms 145
game theory predicts that only rational egoists should prevail. The first six of the
seven core findings summarized above were in part the stimulus for the development of the indirect evolutionary theory and the seventh is not inconsistent (see
below for further discussion of it). Given the recent development of this approach,
direct tests of this theory are not extensive. From the viewpoint of an indirect
evolutionary process, participants in a collective action problem would start with
differential, intrinsic preferences over outcomes due to their predispositions toward norms such as reciprocity and trust. Participants would learn about the likely
behavior of others and shift their behavior in light of the experience and the
objective payoffs they have received. Several recent experiments provide evidence
of these kinds of contingent behaviors and behavioral shifts.9
In a one-shot, sequential, double-blind prisonerâ€™s dilemma experiment, for
example, the players were asked to rank their preferences over the final outcomes
after they had made their own choice, but before they knew their partnerâ€™s
decision. Forty percent of a pool of 136 subjects ranked the cooperative outcome
(C,C) higher than the outcome if they defect while the other cooperates (D,C), and
27 percent were indifferent between these outcomes, even though their individual
payoff was substantially higher for them in the latter outcome (Ahn, Ostrom and
Walker, 1998).10 This finding confirms that not all players enter a collective action
situation as pure forward-looking rational egoists who make decisions based solely
on individual outcomes. Some bring with them a set of norms and values that can
support cooperation.
On the other hand, preferences based on these norms can be altered by bad
experiences. After 72 subjects had played 12 rounds of a finitely repeated prisonerâ€™s
dilemma game where partners were randomly matched each round, rates of
cooperation were very low and many players had experienced multiple instances
where partners had declined to cooperate, only 19 percent of the respondents
ranked (C,C) above (D,C), while 17 percent were indifferent (Ahn et al., 1999). In
this setting, the norms supporting cooperation and reciprocity were diminished,
but not eliminated, by experience.
In another version of the prisonerâ€™s dilemma game, Cain (1998) first had
players participate in a â€œdictator gameâ€â€”in which one player divides a sum of
money and the other player must accept the division, whatever it isâ€”and then a
prisonerâ€™s dilemma game. Stingy players, defined as those who retained at least 70
percent of their endowment in the earlier dictator game, tended to predict that all
players would defect in the prisonerâ€™s dilemma game. Nice players, defined as those
9 Further, Kikuchi, Watanabe and Yamagishi (1996) have found that those who express a high degree
of trust are able to predict othersâ€™ behavior more accurately than those with low levels of trust.
10 To examine the frequency of nonrational egoist preferences, a group of 181 undergraduates was
given a questionnaire containing a similar payoff structure on the first day of classes at Indiana
University in January 1999. They were asked to rank their preferences. In this nondecision setting, 52
percent reflected preferences that were not consistent with being rational egoists; specifically, 27
percent ranked the outcome (C,C) over (D,C) and 25 percent were indifferent.
146 Journal of Economic Perspectives
that gave away at least 30 percent of their endowment, tended to predict that other
nice players would cooperate and stingy players would defect. Before playing the
prisonerâ€™s dilemma game, players were told whether their opponent had been
â€œstingyâ€ or â€œniceâ€ in the dictator game. Nice players chose cooperation in the
prisonerâ€™s dilemma game 69 percent of the time when they were paired with other
nice players and 39 percent of the time when they were paired with stingy players.
Finally, interesting experimental (as well as field) evidence has accumulated
that externally imposed rules tend to â€œcrowd outâ€ endogenous cooperative behavior (Frey, 1994). For example, consider some paradoxical findings of Frohlich and
Oppenheimer (1996) from a prisonerâ€™s dilemma game. One set of groups played
a regular prisonerâ€™s dilemma game, some with communication and some without.
A second set of groups used an externally imposed, incentive-compatible mechanism designed to enhance cooperative choices. In the first phase of the experiment, the second set gained higher monetary returns than the control groups, as
expected. In the second phase of the experiment, both groups played a regular
prisonerâ€™s dilemma game. To the surprise of the experimenters, a higher level of
cooperation occurred in the control groups that played the regular prisonerâ€™s
dilemma in both phases, especially for those who communicated on a face-to-face
basis. The greater cooperation that had occurred due to the exogenously created
incentive-compatible mechanism appeared to be transient. As the authors put it
(p. 180), the removal of the external mechanism â€œseemed to undermine subsequent cooperation and leave the group worse off than those in the control group
who had played a regular… prisonerâ€™s dilemma.â€
Several other recent experimental studies have confirmed the notion that
external rules and monitoring can crowd out cooperative behavior.11 These studies
typically find that a social norm, especially in a setting where there is communication between the parties, can work as well or nearly as well at generating cooperative behavior as an externally imposed set of rules and system of monitoring and
sanctioning. Moreover, norms seem to have a certain staying power in encouraging
a growth of the desire for cooperative behavior over time, while cooperation
enforced by externally imposed rules can disappear very quickly. Finally, the worst
of all worlds may be one where external authorities impose rules but are only able
to achieve weak monitoring and sanctioning. In a world of strong external monitoring and sanctioning, cooperation is enforced without any need for internal
norms to develop. In a world of no external rules or monitoring, norms can evolve
to support cooperation. But in an in-between case, the mild degree of external
monitoring discourages the formation of social norms, while also making it attrac11 Bohnet, Frey and Huck (1999) set up a sequential prisonerâ€™s dilemma, but add a regulatory regime
where a â€œlitigation processâ€ is initiated if there is a breach of performance. Cardenas, Stranlund and
Willis (2000) describe an experiment based on harvesting from a common-pool resource conducted in
three rural villages in Columbia where exogenous but imperfect rule enforcement generated less
cooperation than allowing face-to-face communication.
Elinor Ostrom 147
tive for some players to deceive and defect and take the relatively low risk of being
caught.
The Evolution of Rules and Norms in the Field
Field studies of collective action problems are extensive and generally find that
cooperation levels vary from extremely high to extremely low across different
settings. (As discussed above, the seventh core finding from experimental research
is that contextual factors affect the rate of contribution to public goods.) An
immense number of contextual variables are also identified by field researchers as
conducive or detrimental to endogenous collective action. Among those proposed
are: the type of production and allocation functions; the predictability of resource
flows; the relative scarcity of the good; the size of the group involved; the heterogeneity of the group; the dependence of the group on the good; common understanding of the group; the size of the total collective benefit; the marginal contribution by one person to the collective good; the size of the temptation to free ride;
the loss to cooperators when others do not cooperate; having a choice of participating or not; the presence of leadership; past experience and level of social
capital; the autonomy to make binding rules; and a wide diversity of rules that are
used to change the structure of the situation (see literature cited in Ostrom,
forthcoming).
Some consistent findings are emerging from empirical field research. A frequent finding is that when the users of a common-pool resource organize themselves to devise and enforce some of their own basic rules, they tend to manage
local resources more sustainably than when rules are externally imposed on them
(for example, Tang, 1992; Blomquist, 1992; Baland and Platteau, 1996; Wade,
1994). Common-pool resources are natural or humanly created systems that generate a finite flow of benefits where it is costly to exclude beneficiaries and one
personâ€™s consumption subtracts from the amount of benefits available to others
(Ostrom, Gardner and Walker, 1994). The users of a common-pool resource face
a first-level dilemma that each individual would prefer that others control their use
of the resource while each is able to use the resource freely. An effort to change
these rules is a second-level dilemma, since the new rules that they share are a
public good. Thus, users face a collective action problem, similar in many respects
to the experiments discussed above, of how to cooperate when their immediate
best-response strategies lead to suboptimal outcomes for all. A key question now is:
How does evolutionary theory help us understand the well-established finding that
many groups of individuals overcome both dilemmas? Further, how can we understand how self-organized resource regimes, that rarely rely on external third-party
enforcement, frequently outperform government-owned resource regimes that rely
on externally enforced, formal rules?
148 Journal of Economic Perspectives
The Emergence of Self-Organized Collective Action
From evolutionary theory, we should expect some individuals to have an initial
propensity to follow a norm of reciprocity and to be willing to restrict their own use
of a common pool resource so long as almost everyone reciprocates. If a small core
group of users identify each other, they can begin a process of cooperation without
having to devise a full-blown organization with all of the rules that they might
eventually need to sustain cooperation over time. The presence of a leader or
entrepreneur, who articulates different ways of organizing to improve joint outcomes, is frequently an important initial stimulus (Frohlich, Oppenheimer and
Young, 1971; Varughese, 1999).12
If a group of users can determine its own membershipâ€”including those who
agree to use the resource according to their agreed-upon rules and excluding those
who do not agree to these rulesâ€”the group has made an important first step toward
the development of greater trust and reciprocity. Group boundaries are frequently
marked by well-understood criteria, like everyone who lives in a particular community or has joined a specific local cooperative. Membership may also be marked by
symbolic boundaries and involve complex rituals and beliefs that help solidify
individual beliefs about the trustworthiness of others.
Design Principles of Long-Surviving, Self-Organized Resource Regimes
Successful self-organized resource regimes can initially draw upon locally
evolved norms of reciprocity and trustworthiness and the likely presence of local
leaders in most community settings. More important, however, for explaining their
long-term survival and comparative effectiveness, resource regimes that have flourished over multiple generations tend to be characterized by a set of design principles. These design principles are extensively discussed in Ostrom (1990) and have
been subjected to extensive empirical testing.13 Evolutionary theory helps to explain how these design principles work to help groups sustain and build their
cooperation over long periods of time.
We have already discussed the first design principleâ€”the presence of clear
boundary rules. Using this principle enables participants to know who is in and who
is out of a defined set of relationships and thus with whom to cooperate. The
second design principle is that the local rules-in-use restrict the amount, timing,
12 Empirical studies of civil rights movements, where contributions can be very costly, find that organizers search for ways to assure potential participants of the importance of shared internal norms and
that many others will also participate (Chong, 1991). Membership in churches and other groups that
jointly commit themselves to protests and other forms of collective action is also an important factor
(Opp, Voss and Gern, 1995).
13 The design principles that characterize long-standing common-pool resource regimes have now been
subject to considerable further empirical studies since they were first articulated (Ostrom, 1990). While
minor modifications have been offered to express the design principles somewhat differently, no
empirical study has challenged their validity, to my knowledge (Morrow and Hull, 1996; Asquith, 1999;
Bardhan, 1999; Lam, 1998).
Collective Action and the Evolution of Social Norms 149
and technology of harvesting the resource; allocate benefits proportional to required inputs; and are crafted to take local conditions into account. If a group of
users is going to harvest from a resource over the long run, they must devise rules
related to how much, when, and how different products are to be harvested, and
they need to assess the costs on users of operating a system. Well-tailored rules help
to account for the perseverance of the resource itself. How to relate user inputs to
the benefits they obtain is a crucial element of establishing a fair system (Trawick,
1999). If some users get all the benefits and pay few of the costs, others become
unwilling to follow rules over time.
In long-surviving irrigation systems, for example, subtly different rules are used
in each system for assessing water fees used to pay for maintenance activities, but
water tends to be allocated proportional to fees or other required inputs (Bardhan,
1999). Sometimes water and responsibilities for resource inputs are distributed on
a share basis, sometimes on the order in which water is taken, and sometimes
strictly on the amount of land irrigated. No single set of rules defined for all
irrigation systems in a region would satisfy the particular problems in managing
each of these broadly similar, but distinctly different, systems (Tang, 1992; Lam,
1998).
The third design principle is that most of the individuals affected by a resource
regime can participate in making and modifying their rules. Resource regimes that
use this principle are both able to tailor better rules to local circumstances and to
devise rules that are considered fair by participants. The Chisasibi Cree, for
example, have devised a complex set of entry and authority rules related to the fish
stocks of James Bay as well as the beaver stock located in their defined hunting
territory. Berkes (1987, p. 87) explains that these resource systems and the rules
used to regulate them have survived and prospered for so long because effective
â€œsocial mechanisms ensure adherence to rules which exist by virtue of mutual
consent within the community. People who violate these rules suffer not only a loss
of favor from the animals (important in the Cree ideology of hunting) but also
social disgrace.â€ Fair rules of distribution help to build trusting relationships, since
more individuals are willing to abide by these rules because they participated in
their design and also because they meet shared concepts of fairness (Bowles, 1998).
In a study of 48 irrigation systems in India, Bardhan (1999) finds that the
quality of maintenance of irrigation canals is significantly lower on those systems
where farmers perceive the rules to be made by a local elite. On the other hand,
those farmers (of the 480 interviewed) who responded that the rules have been
crafted by most of the farmers, as contrasted to the elite or the government, have
a more positive attitude about the water allocation rules and the rule compliance
of other farmers. Further, in all of the villages where a government agency decides
how water is to be allocated and distributed, frequent rule violations are reported
and farmers tend to contribute less to the local village fund. Consistent with this is
the finding by Ray and Williams (1999) that the deadweight loss from upstream
farmers stealing water on government-owned irrigation systems in Maharashtra,
150 Journal of Economic Perspectives
India, approaches one-fourth of the revenues that could be earned in an efficient
water allocation and pricing regime.
Few long-surviving resource regimes rely only on endogenous levels of trust
and reciprocity. The fourth design principle is that most long-surviving resource
regimes select their own monitors, who are accountable to the users or are users
themselves and who keep an eye on resource conditions as well as on user behavior.
Further, the fifth design principle points out that these resource regimes use
graduated sanctions that depend on the seriousness and context of the offense. By
creating official positions for local monitors, a resource regime does not have to
rely only on willing punishers to impose personal costs on those who break a rule.
The community legitimates a position. In some systems, users rotate into this
position so everyone has a chance to be a participant as well as a monitor. In other
systems, all participants contribute resources and they hire monitors jointly. With
local monitors, conditional cooperators are assured that someone is generally
checking on the conformance of others to local rules. Thus, they can continue their
own cooperation without constant fear that others are taking advantage of them.
On the other hand, the initial sanctions that are imposed are often so low as
to have no impact on an expected benefit-cost ratio of breaking local rules (given
the substantial temptations frequently involved). Rather, the initial sanction needs
to be considered more as information both to the person who is â€œcaughtâ€ and to
others in the community. Everyone can make an error or can face difficult problems leading them to break a rule. Rule infractions, however, can generate a
downward cascade of cooperation in a group that relies only on conditional
cooperation and has no capacity to sanction (for example, Kikuchi et al., 1998). In
a regime that uses graduated punishments, however, a person who purposely or by
error breaks a rule is notified that others notice the infraction (thereby increasing
the individualâ€™s confidence that others would also be caught). Further, the individual learns that others basically continue to extend their trust and want only a
small token to convey a recognition that the mishap occurred. Self-organized
regimes rely more on what Margaret Levi calls â€œquasi-voluntaryâ€ cooperation than
either strictly voluntary or coerced cooperation (Levi, 1988). A real threat to the
continuance of self-organized regimes occurs, however, if some participants break
rules repeatedly. The capability to escalate sanctions enables such a regime to warn
members that if they do not conform they will have to pay ever-higher sanctions and
may eventually be forced to leave the community.
Let me summarize my argument to this point. When the users of a resource
design their own rules (Design Principle 3) that are enforced by local users or
accountable to them (Design Principle 4) using graduated sanctions (Design
Principle 5) that define who has rights to withdraw from the resource (Design
Principle 1) and that effectively assign costs proportionate to benefits (Design
Principle 2), collective action and monitoring problems are solved in a reinforcing
manner (Agrawal, 1999).
Individuals who think a set of rules will be effective in producing higher joint
Elinor Ostrom 151
benefits and that monitoring (including their own) will protect them against being
a sucker are willing to undertake conditional cooperation. Once some users have
made contingent self-commitments, they are then motivated to monitor other
peopleâ€™s behavior, at least from time to time, to assure themselves that others are
following the rules most of the time. Conditional cooperation and mutual monitoring reinforce one another, especially in regimes where the rules are designed to
reduce monitoring costs. Over time, further adherence to shared norms evolves
and high levels of cooperation are achieved without the need to engage in very
close and costly monitoring to enforce rule conformance.
The operation of these principles is then bolstered by the sixth design
principle that points to the importance of access to rapid, low-cost, local arenas
to resolve conflict among users or between users and officials. Rules, unlike
physical constraints, have to be understood to be effective. There are always
situations in which participants can interpret a rule that they have jointly made
in different ways. By devising simple, local mechanisms to get conflicts aired
immediately and resolutions that are generally known in the community, the
number of conflicts that reduce trust can be reduced. If individuals are going to
follow rules over a long period of time, some mechanism for discussing and
resolving what constitutes a rule infraction is necessary to the continuance of
rule conformance itself.
The capability of local users to develop an ever-more effective regime over time
is affected by whether they have minimal recognition of the right to organize by a
national or local government. This is the seventh design principle. While some
resource regimes have operated for relatively long times without such rights
(Ghate, 2000), participants have had to rely almost entirely on unanimity as the
rule used to change rules. (Otherwise, any temporarily disgruntled participant who
voted against a rule change could go to the external authorities to threaten the
regime itself!) Unanimity as a decision rule for changing rules imposes high
transaction costs and prevents a group from searching for better matched rules at
relatively lower costs.
Users frequently devise their own rules without creating formal, governmental
jurisdictions for this purpose. In many in-shore fisheries, for example, local fishers
devise extensive rules defining who can use a fishing ground and what kind of
equipment can be used (Acheson, 1988; Schlager, 1994). As long as external
governmental officials give at least minimal recognition to the legitimacy of such
rules, the fishers themselves may be able to enforce the rules. But if external
governmental officials presume that only they can make authoritative rules, then it
is difficult for local users to sustain a self-organized regime (Johnson and Libecap,
1982).
When common pool resources are somewhat larger, an eighth design
principle tends to characterize successful systemsâ€”the presence of governance
activities organized in multiple layers of nested enterprises. The rules appropriate for allocating water among major branches of an irrigation system, for
152 Journal of Economic Perspectives
example, may not be appropriate for allocating water among farmers along a
single distributory channel. Consequently, among long-enduring self-governed
regimes, smaller-scale organizations tend to be nested in ever-larger organizations. It is not unusual to find a large, farmer-governed irrigation system, for
example, with five layers of organization each with its own distinct set of rules
(Yoder, 1992).
Threats to Sustained Collective Action
All economic and political organizations are vulnerable to threats, and selforganized resource-governance regimes are no exception. Both exogenous and
endogenous factors challenge their long-term viability. Here we will concentrate on
those factors that affect the distribution of types of participants within a regime and
the strength of the norms of trust and reciprocity held by participants. Major
migration (out of or into an area) is always a threat that may or may not be
countered effectively. Out-migration may change the economic viability of a regime
due to loss of those who contribute needed resources. In-migration may bring new
participants who do not trust others and do not rapidly learn social norms that have
been established over a long period of time. Since collective action is largely based
on mutual trust, some self-organized resource regimes that are in areas of rapid
settlement have disintegrated within relatively short times (Baland and Platteau,
1996).
In addition to rapid shifts in population due to market changes or land
distribution policies, several more exogenous and endogenous threats have been
identified in the empirical literature (Sengupta, 1991; Bates, 1987; and literature
cited in Ostrom, 1998b; Britt, 2000). These include: 1) efforts by national governments to impose a single set of rules on all governance units in a region; 2) rapid
changes in technology, in factor availability, and in reliance on monetary transactions; 3) transmission failures from one generation to the next of the operational
principles on which self-organized governance is based; 4) turning to external
sources of help too frequently; 5) international aid that does not take account of
indigenous knowledge and institutions; 6) growth of corruption and other forms of
opportunistic behavior; and 7) a lack of large-scale institutional arrangements that
provide fair and low-cost resolution mechanisms for conflicts that arise among local
regimes, educational and extension facilities, and insurance mechanisms to help
when natural disasters strike at a local level.
Contextual variables are thus essential for understanding the initial growth
and sustainability of collective action as well as the challenges that long-surviving,
self-organized regimes must try to overcome. Simply saying that context matters is
not, however, a satisfactory theoretical approach. Adopting an evolutionary approach is the first step toward a more general theoretical synthesis that addresses
the question of how context matters. In particular, we need to address how context
affects the presence or absence of conditional cooperators and willing punishers
Collective Action and the Evolution of Social Norms 153
and the likelihood that the norms held by these participants are adopted and
strengthened by others in a relevant population.
Conclusion
Both laboratory experiments and field studies confirm that a substantial number of collective action situations are resolved successfully, at least in part. The
old-style notion, pre-Mancur Olson, that groups would find ways to act in their own
collective interest was not entirely misguided. Indeed, recent developments in
evolutionary theoryâ€”including the study of cultural evolutionâ€”have begun to
provide genetic and adaptive underpinnings for the propensity to cooperate based
on the development and growth of social norms. Given the frequency and diversity
of collective action situations in all modern economies, this represents a more
optimistic view than the zero contribution hypothesis. Instead of pure pessimism or
pure optimism, however, the picture requires further work to explain why some
contextual variables enhance cooperation while others discourage it.
Empirical and theoretical work in the future needs to ask how a large array of
contextual variables affects the processes of teaching and evoking social norms; of
informing participants about the behavior of others and their adherence to social
norms; and of rewarding those who use social norms, such as reciprocity, trust, and
fairness. We need to understand how institutional, cultural, and biophysical contexts affect the types of individuals who are recruited into and leave particular types
of collective action situations, the kind of information that is made available about
past actions, and how individuals can themselves change structural variables so as to
enhance the probabilities of norm-using types being involved and growing in
strength over time.
Further developments along these lines are essential for the development of
public policies that enhance socially beneficial, cooperative behavior based in part
on social norms. It is possible that past policy initiatives to encourage collective
action that were based primarily on externally changing payoff structures for
rational egoists may have been misdirectedâ€”and perhaps even crowded out the
formation of social norms that might have enhanced cooperative behavior in their
own way. Increasing the authority of individuals to devise their own rules may well
result in processes that allow social norms to evolve and thereby increase the
probability of individuals better solving collective action problems.
y Earlier versions of this paper have been presented at seminars at the Workshop in Political
Theory and Policy Analysis, Indiana University; Department of Political Science, Gothenburg
University; and the Beijer Institute of Ecological Economics, at the Royal Swedish Academy of
Sciences in Stockholm. I appreciate the helpful comments made by Iris Bohnet, Juan-Camilo
Cardenas, J. Bradford De Long, Bruno Frey, Werner GuÂ¨th, Roy Gardner, Steffen Huck, Alan
Krueger, Fabrice Lehoucq, Frank Maier-Rigaud, Mike McGinnis, Timothy Taylor, Jimmy
154 Journal of Economic Perspectives
Walker, and the outstanding editing by Patty Dalecki. Support by the Ford Foundation, the
MacArthur Foundation, and the National Science Foundation (Grant #SBR 9521918) is
gratefully acknowledged.
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