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This paper shows that identical offers in an ultimatum game generate systematically different rejection rates depending on the other offers that are available to the proposer. This result casts doubt on the consequentialist practice in economics to define the utility of an action solely in terms of the consequences of the action irrespective of the set of alternatives. It means, in particular, that negatively reciprocal behavior cannot be fully captured by equity models that are exclusively based on preferences over the distribution of material payoffs. Models that take into account players' fairness intentions and distributional preferences are consistent with our data while models that focus exclusively on intentions or on the distribution of material payoffs are not. JEL-Classification: D63, C78, C91. Keywords: Fairness, reciprocity, intentions, experiments, ultimatum game. * Financial support by the Swiss National Science Foundation (Project 1214-05100.97) and by the MacArthur Foundation (Network on Economic Environments and the Evolution of Individual Preferences and Social Norms) is gratefully acknowledged. This paper is part of the EU-TMR Research Network ENDEAR (FMRX-CTP98-0238). ** Postal address: Institute for Empirical Research in Economics, Blmlisalpstrasse 10, CH-8006 Zurich. E-mail:,, WWW: 2 1.
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Institute for Empirical Research in Economics
University of Zurich
Working Paper Series
ISSN 1424-0459
forthcoming in: “Economic Inquiry”
Working Paper No. 17
On the Nature of Fair Behavior
Armin Falk, Ernst Fehr and Urs Fischbacher
August 1999
On the Nature of Fair Behavior*
Armin Falk, Ernst Fehr and Urs Fischbacher
University of Zurich∗∗
Revised Version: August 1999
This paper shows that identical offers in an ultimatum game generate systematically
different rejection rates depending on the other offers that are available to the proposer.
This result casts doubt on the consequentialist practice in economics to define the utility
of an action solely in terms of the consequences of the action irrespective of the set of
alternatives. It means, in particular, that negatively reciprocal behavior cannot be fully
captured by equity models that are exclusively based on preferences over the distribution
of material payoffs. Models that take into account players’ fairness intentions and
distributional preferences are consistent with our data while models that focus exclusively
on intentions or on the distribution of material payoffs are not.
JEL-Classification: D63, C78, C91.
Keywords: Fairness, reciprocity, intentions, experiments, ultimatum game.
* Financial support by the Swiss National Science Foundation (Project 1214-05100.97) and by
the MacArthur Foundation (Network on Economic Environments and the Evolution of Individual
Preferences and Social Norms) is gratefully acknowledged. This paper is part of the EU-TMR
Research Network ENDEAR (FMRX-CTP98-0238).
∗∗ Postal address: Institute for Empirical Research in Economics, Blümlisalpstrasse 10, CH-8006
Zurich. E-mail:,, WWW:
1. Introduction
There is by now considerable evidence that fairness considerations affect economic
behavior in many important areas. In bilateral bargaining situations anonymously
interacting agents frequently agree on rather egalitarian outcomes although the standard
model with purely selfish preferences predicts rather unequal outcomes (Güth,
Schmittberger and Schwarze 1982, Roth 1995, Camerer and Thaler 1995). In competitive
experimental labor markets with incomplete contracts, fairness considerations give rise to
efficiency wage effects that generate stable deviations from the perfectly competitive
outcome (Fehr and Falk 1999). In several questionnaire studies (e.g. Bewley 1995,
Campbell and Kamlani 1997) personal managers indicate that despite an excess supply of
labor, firms are unwilling to cut wages because they fear that pay cuts are perceived as
unfair and hostile by the workers and will, hence, destroy work morale. In principal-agent
relationships reciprocally fair behavior causes a considerable increase in the set of
enforceable contracts and, hence, large efficiency gains (Fehr, Gächter and Kirchsteiger
1997). To examine the forces that affect the perceptions of fairness and the determinants
of fair behavior is, thus, not just of philosophical or academic interest.
A common feature of fair behavior in the above cited situations is, that in response
to an act of party A that is favorable for party B, B is willing to take costly actions to
return at least part of the favor (positive reciprocity), and in response to an act that is
perceived as harmful by B, B is willing to take costly actions to reduce A’s material
payoff (negative reciprocity). This suggests that reciprocal behavior is an important
component of fairness-driven behavior. Reciprocally fair behavior has been shown to
prevail in one-shot situations and under rather high stake levels (Berg, Dickhaut and
McCabe 1995, Roth, Prasnikar, Okuno-Fujiwara, and Zamir 1991, Cameron 1995).
In this paper, we show that identical offers in an ultimatum game trigger vastly
different rejection rates depending on the other offers available to the proposer. In
particular, a given offer with an unequal distribution of material payoffs is much more
likely to be rejected if the proposer could have proposed a more equitable offer than if the
proposer could have proposed only more unequal offers. Thus, it is not just the material
payoff consequence of an offer that determines the acceptance but the set of available, yet
not chosen, offers is also decisive. This result not only casts serious doubt on the
consequentialist practice in standard economic theory that defines the utility of an action
solely in terms of the consequences of this action. It also shows that the recently
developed models of fairness by Bolton and Ockenfels (forthcoming) and Fehr and
Schmidt (forthcoming) are incomplete to the extent that they neglect
"nonconsequentialist" reasons for reciprocally fair actions. These models assume that – in
addition to their material self-interest - people also value the distributive consequences of
outcomes. The impressive feature of these models is that they are capable of predicting
correctly a wide variety of seemingly contradictory facts. For example: Why do
competitive experimental markets with complete contracts typically converge to the
predictions of the “selfish model” while in bilateral bargaining situations or in markets
with incomplete contracts stable deviations in the direction of more equitable outcomes
are the rule. However, despite their predictive success in important areas, our results
indicate that there remain legitimate doubts whether these models capture the
phenomenon of reciprocal fairness in a fully satisfactory way.
A parsimonious interpretation of our results, which is also suggested by
psychological research, can be given in terms of “intentions”.1 Identical actions by the
proposer are – depending on the available alternatives – likely to signal different
information about the intentions of the proposer. Hence, if responders do not only take
into account the distributive consequences of the proposers' actions but also the fairness of
the proposers' intentions, their responses to identical offers may differ. Viewed from this
perspective, our results suggest that fairness models should not only take into account that
many people have preferences over the distribution of payoffs but also that many people
value the fairness intentions behind actions. Models like this have been suggested by
Rabin (1993), and Dufwenberg and Kirchsteiger (1998). However, as we will see, the
recognition that intentions are important is not sufficient to account for our evidence
because distributive concerns are important as well. Ultimately, it needs a model which
combines both, preferences for distributive consequences and the role of intentions. An
attempt in this direction is made by Falk and Fischbacher (1998).
1 For a review of the psychological literature see Krebs (1970).
Before we present our experimental examination in detail, we would like to
emphasize that the attribution of intentions for the evaluation of actions is not restricted to
laboratory studies. We believe that it is also important in many real life situations. Take
for instance the case that your neighbor caused a small damage at your car either
intentionally or because of insufficient care. Most people would consider the intentionally
caused damage as the more serious offence. Another important real life example that
illustrates the importance of the attribution of intentions is the criminal law. It
distinguishes carefully between criminal activities that are committed negligently and
those committed with criminal intent. Similar distinctions are also made in the
commercial law and the labor law. The punishment associated with a failure to meet
obligations is, in general, dependent on judgments about the intention that caused the
In the next section we describe our experimental design. Section 3 presents the
results. The final section relates our findings to the literature and draws implications for
theoretical modeling.
2. Experimental Design and Procedures
To examine whether identical offers trigger different rejection rates depending on the
alternatives available to the proposer, we conducted four so-called mini-ultimatum games.
Each of 90 experimental subjects participated in all four games. The mini-ultimatum
games were extremely simple and share the same structure (see Figures 1a-d). In all
games the proposer P is asked to divide 10 points between himself and the responder R,
who can either accept or reject the offer. Accepting the offer leads to a payoff distribution
according to the proposer’s offer. A rejection implies zero payoffs for both players.
As Figures 1a-d indicate, P can choose between two allocations, x and y. In all four
games the allocation x is the same while the allocation y (the “alternative” to x) differs
from game to game. If P chooses x and R accepts this offer, P gets 8 points while R
receives 2 points. In game (a) the alternative offer y is (5/5). This game is therefore called
the (5/5)-game. Game (b) is called the (2/8)-game because the alternative offer y is to
keep 2 points and to give 8 points to R. In game (c) P has in fact no alternative at all, i.e.,
he is forced to propose an offer (8/2). We call it the (8/2)-game. Finally, in game (d) the
alternative offer is (10/0), hence it is termed (10/0)-game. In order to get sufficient data
we employed the strategy method. Every responder had to indicate his action at both
decision nodes, i.e., for the case of an x- and for the case of a y-offer, without knowing
what P had proposed.
At the beginning subjects were randomly assigned the P- or the R-role and they kept
this role in all four games. Subjects faced the games in a random order and in each game
they played against a different anonymous opponent. They were informed about the
outcome of all four games, i.e., about the choice of their opponents, only after they had
made their decision in all games. This procedure not only avoids income effects. It also
rules out that subjects’ behavior is influenced by previous decisions of their opponents.
After the end of the fourth game subjects received a show-up fee of CHF 10.- plus their
earnings from the experiment. For each point earned they received CHF -.80 so that in all
four games together CHF 32.- (about $23) were at stake. The experiment lasted
approximately 40 minutes. It was programmed and conducted with the software z-Tree
(Fischbacher 1998).
Figure 1: The mini ultimatum games
8 0 5 0
2 0 5 0
a a
r r
x y
8 0 2 0
2 0 8 0
a a
r r
x y
(a) (5/5)-game (b) (2/8)-game
8 0 8 0
2 0 2 0
a a
r r
x y
8 0 1 0 0
2 0 0 0
a a
r r
x y
(c) (8/2)-game (d) (10/0)-game
3. Predictions and Results
Since we are mainly interested in the variations of responders’ behavior across the four
games we shortly present the responder-predictions of the various models. The standard
model with selfish preferences predicts that in all games the allocation (8/2) is never
rejected. The Bolton-Ockenfels and the Fehr-Schmidt-model predict that the rejection rate
of the (8/2)-offer is the same across all games. Since these models capture people’s
dislike for inequality, they are consistent with positive rejection rates. However, since
they disregard that identical outcomes may be perceived as more or less fair, depending on
the alternatives available to the first mover, they are not consistent with different rejection
rates of the (8/2)-offer across the four games.
Intuitively, one would expect that in the (5/5)-game a proposal of (8/2) is clearly
perceived as unfair because P could have proposed the egalitarian offer (5/5). In the (2/8)-
game offering (8/2) may still be perceived as unfair but probably less so than in the (5/5)-
game because the only alternative available to (8/2) gives P much less than R. In a certain
sense, therefore, P has an excuse for not choosing (2/8) because one cannot
unambiguously infer from his unwillingness to propose an unfair offer to himself that he
wanted to be unfair to the responder. Thus, we would expect that the rejection rate of the
(8/2)-offer in the (5/5)-game is higher than in the (2/8)-game. In the (8/2)-game P has no
choice at all so that P’s behavior cannot be judged in terms of fairness. Responders can
only judge the fairness of the outcome (8/2) and if they exhibit sufficient aversion against
inequality they will reject this distribution of money. The rejection rate in the (8/2)-game
measures, therefore, subjects’ pure aversion against disadvantageous inequality. Since any
attribution of unfairness to P’s behavior is ruled out here we expect an even lower
rejection rate compared to the (2/8)-game. Finally, offering (8/2) in the (10/0)-game may
even be perceived as a fair (or less unfair) action so that the rejection rate of (8/2) is likely
to be lowest in this game.
Figure 2 presents our main result. The bars represent the percentage of responders
that reject the (8/2)-offer in the different games. The rejection rate in the (5/5)-game is
highest (44.4 percent). 26.7 percent rejected the (8/2)-offer in the (2/8)-game, 18 percent
in the (8/2)-game and 8.9 percent in the (10/0)-game. The non-parametric McNemar-test
confirms that the differences in rejection rates between the (5/5)-game and each of the
other games is statistically significant (p<.022). The same test also confirms a significant
difference between the (2/8)- and the (8/2)-game while the difference between the (8/2)
and the (10/0)-game is not significant.2
These results indicate that pure aversion against inequality plays a role because 18
percent of responders reject the (8/2)-offer when P has no choice. This is evidence against
pure intentions models like those of Rabin and Dufwenberg and Kirchsteiger. However,
the results also clearly reject the implication of the Bolton-Ockenfels and the Fehr-
Schmidt model that there are no differences in rejection rates across games. The rise in the
rejection rate from 18 to roughly 45 percent in the (5/5)-game suggests that intentions-
driven reciprocal behavior is a major factor.
Figure 2
Rejection rate of the (8/2)-offer across games
5/5 2/8 8/2 10/0
Rejection rate
2 The rejection rates of the alternative offers (5/5), (2/8) and (10/0) are as follows. Nobody
rejected the (5/5)-offer and only one subject rejected the (2/8)-offer. Almost 90 percent rejected
the offer (10/0).
Finally, we take a look at proposers’ behavior. Given the varying acceptance rates of
the (8/2)-offers it is an interesting question whether proposers anticipated the differences
in acceptance rates. Put differently, we can ask whether proposers realize that, given their
alternative offers in the different games, responders have a higher tolerance to accept the
(8/2)-offer. This would be further support for our interpretation that the fairness of an
action is not only assessed by the distributive outcome but also by the intention that drives
the action. Figure 3 provides the evidence. It shows that – when moving from the (5/5)-
game to the (2/8)-game and then to the (10/0)-game – the monotonous increase in the
acceptance rate of the (8/2)-offer is matched by a monotonous increase in the percentage
of (8/2)-choices by the proposers.3 The McNemar test indicates that the differences in the
frequencies of the (8/2)-proposal are highly significant (p < .001).
Figure 3:
Percentage and acceptance of (8/2) proposals
5/5 2/8 10/0
Relative frequency
Percentage of (8/2)-
Acceptance rate of
3 Since in the (8/2)-game proposers had no choice but to choose (8/2) such a comparison is
meaningless for the (8/2)-game.
4. Concluding Remarks
The results of our experiment clearly show that the same action by the proposer in a mini-
ultimatum game triggers very different responses depending on the alternative action
available to the proposer. This suggests that responders do not only take into account the
distributive consequences of the action by the proposer but also the intention that is
signaled by the action. Supporting evidence for this interpretation is also provided by the
experiments of Blount (1995)4, Brandts and Sola (1998), and Güth, Huck and Müller
(1998).5 At a more general level our results also call into question the consequentialist
practice in standard economic theory that defines the utility of an action solely in terms of
the material consequences of this action.
The pattern of rejections in our experiment indicates that both distributional
concerns and the attribution of fairness intentions are a driving force of reciprocally fair
behavior and that models that focus exclusively on one aspect are incomplete. Therefore,
the equity models of Bolton and Ockenfels and Fehr and Schmidt are not fully satisfactory
because they have no explicit role for intentions while the pure intentions models of
Rabin and Dufwenberg and Kirchsteiger are incomplete because they do not capture
distributional concerns in a satisfactory way. Models that combine both driving forces of
reciprocal behavior seem, therefore, most promising.
4 The results of Blount (1995) may be affected by the fact that subjects had to make decisions as a
proposer and as a responder before they knew their actual roles. After subjects had made their
decisions in both roles, the role for which they received payments was determined randomly. In
one of Blount’s treatments deception was involved. Subjects believed that there were proposers
although in fact the experimenters made the proposals. All subjects in this condition were
"randomly" assigned to the responder role.
5 There is also evidence for the view that distributive concerns alone as well as intentions alone
cannot explain nice actions in response to nice behavior (see Charness 1996). For a dissenting
view see, however, Bolton, Brandts and Ockenfels (1998).
Berg, Dickhaut and McCabe (1995): "Trust, Reciprocity, and Social History, Games and
Economic Behavior 10, pp. 122-142.
Blount, S. (1995): “When Social Outcomes Aren’t Fair: The Effect of Causal Attributions
on Preferences”, Organizational Behavior and Human Decision Process 63, 131-
Bolton, G. and Ockenfels, A. (1999): A Theory of Equity, Reciprocity and Competition,
forthcoming in American Economic Review.
Bolton, G. E., Brandts, J. and Ockenfels, A. (1998): “Measuring Motivations for the
Reciprocal Responses Observed in a Simple Dilemma Game”, Experimental
Economics 1, 207-220.
Brandts, J. and Sola, C. (1998): “Reference Points and Negative Reciprocity in Simple
Sequential Games”, Discussion Paper, Universidad Autonoma de Barcelona.
Camerer, C. and Thaler, R. (1995): ''Ultimatums, Dictators, and Manners'', Journal of
Economic Perspectives 9, 209-219.
Cameron L. (1995): "Raising the Stakes in the Ultimatum Game: Experimental Evidence
From Indonesia", Princeton University, Industrial Relations Section, Working
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Charness, G. (1996): “Attribution and Reciprocity in a Simulated Labor Market: An
Experimental Investigation”, Discussion paper, University of Berkeley.
Dufwenberg, M. and Kirchsteiger, G. (1998): "A Theory of Sequential Reciprocity'',
mimeo, CentER for Economic Research, Tilburg.
Falk, A. and Fischbacher, U. (1998): “A Theory of Reciprocity”, Discussion paper
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Fehr, E. and Falk, A. (1999): “Wage Rigidities in a Competitive Incomplete Contract
Market”, Journal of Political Economy 107, 106-134.
Fehr, E., Gächter, S., and Kirchsteiger G. (1997): ''Reciprocity as a Contract Enforcement
Device: Experimental Evidence'', Econometrica 65, 833-860.
Fehr, E. and Schmidt, K. (1997): “A Theory of Fairness, Competition and Cooperation”,
forthcoming in Quarterly Journal of Economics.
Fischbacher, U. (1998): "z-Tree. Zurich Toolbox for Readymade Economic Experiments.’
mimeo, University of Zurich.
Güth, W., Huck, S. and Müller, W. (1998): "The Relevance of Equal Splits – On a
Behavioral Discontinuity in Ultimatum Games", Discussion paper, Humboldt
University Berlin.
Güth, W., Schmittberger, R. and Schwarze, B. (1982): ''An Experimental Analysis of
Ultimatium Bargaining'', Journal of Economic Behavior and Organization 3, 367-
Krebs, D. L. (1970): "Altruism – An Examination of the Concept and a Review of the
Literature", Psychological Bulletin 73, 258-302.
Rabin, M. (1993): “Incorporating Fairness into Game Theory and Economics”, American
Economic Review 83, 1281-1302.
Roth, A., Prasnikar, V., Okuno-Fujiwara, M. and Zamir, S. (1991): ''Bargaining and
Market Behavior in Jerusalem, Ljubljana, Pittsburgh, and Tokyo: An Experimental
Study'', American Economic Review 81, 1068-1095.
Roth, A. E. (1995): “Bargaining Experiments”, J. E. Kagel and A. E. Roth (eds.):
Handbook of Experimental Economics, Princeton University Press, Princeton.
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There is strong evidence that people exploit their bargaining power in competitive markets but not in bilateral bargaining situations. There is also strong evidence that people exploit free-riding opportunities in voluntary cooperation games. Yet, when they are given the opportunity to punish free riders, stable cooperation is maintained, although punishment is costly for those who punish. This paper asks whether there is a simple common principle that can explain this puzzling evidence. We show that if some people care about equity the puzzles can be resolved. It turns out that the economic environment determines whether the fair types or the selfish types dominate equilibrium behavior.
Reviews literature relating to altruism and suggests that the study of altruism is important at 3 levels: (a) as it relates to the main goal of socialization, (b) to a core attribute of personality, and (c) to theories concerned with human nature. Independent variables associated with altruism are organized in a 2 * 4 framework on the basis of the source of experimental measurement and level of generality. Characteristics of the benefactor and characteristics of the recipient are categorized as state variables, trait variables, social roles and demographic attributes, and characteristics influenced by social norms. Research at each level is critically reviewed. Positive and negative affective states, and states induced by the observation of models are found to influence the altruism of benefactors; and dependency and interpersonal attractiveness are found to influence the altruism-eliciting capacity of recipients. Research relevant to personality traits is criticized. Effects are found for sex, age, ordinal position, social class, and nationality in relation to benefactors, and for friendship status, ingroup affiliation, and social class in relation to recipients. The normative level of analysis is criticized. (4 p. ref.) (PsycINFO Database Record (c) 2012 APA, all rights reserved)
People are reciprocal if they reward kind actions and punish unkind ones. In this paper we present a formal theory of reciprocity. It takes into account that people evaluate the kindness of an action not only by its consequences but also by its underlying intention. The theory is in line with the relevant stylized facts of a wide range of experimental games, such as the ultimatum game, the gift-exchange game, a reduced best-shot game, the dictator game, the prisoner's dilemma, and public goods games. Furthermore, it predicts that identical consequences trigger different reciprocal responses in different environments. Finally, the theory explains why outcomes tend to be fair in bilateral interactions whereas extremely unfair distributions may arise in competitive markets.
Many experimental studies indicate that people are motivated by reciprocity. Rabin [Amer. Econ. Rev. 83 (1993) 1281] develops techniques for incorporating such concerns into game theory and economics. His theory is developed for normal form games, and he abstracts from information about the sequential structure of a strategic situation. We develop a theory of reciprocity for extensive games in which the sequential structure of a strategic situation is made explicit, and propose a new solution concept—sequential reciprocity equilibrium—for which we prove an equilibrium existence result. The model is applied in several examples, and it is shown that it captures very well the intuitive meaning of reciprocity as well as certain qualitative features of experimental evidence.
We designed an experiment to study trust and reciprocity in an investment setting. This design controls for alternative explanations of behavior including repeat game reputation effects, contractual precommitments, and punishment threats. Observed decisions suggest that reciprocity exists as a basic element of human behavior and that this is accounted for in the trust extended to an anonymous counterpart. A second treatment, social history, identifies conditions which strengthen the relationship between trust and reciprocity.
We investigate experimentally whether preferences over an outcome depend on what other possible outcomes of the situation under consideration are, i.e., whether choices are “menu dependent.” In simple sequential games we analyze whether reactions to a certain benchmark outcome are influenced by changes in the payoffs of another outcome, not attainable at that time, called the “reference point.” Our data provide evidence that is favorable to the notion of menu dependence. Alterations of the reference point can lead to quantitatively significant changes in behavior at the benchmark outcome. The behavior we observe can be interpreted in terms of negative reciprocity. Journal of Economic Literature Classification Numbers: C91, C92, C72.