Exp Econ (2008) 11: 122–133
DOI 10.1007/s10683-007-9172-2
Dictator game giving: altruism or artefact?
Nicholas Bardsley
Received: 6 October 2006 / Revised: 4 May 2007 / Accepted: 8 May 2007 / Published online: 29
September 2007
© Economic Science Association 2007
Abstract Experimental dictator games have been used to explore unselﬁsh behaviour.
Evidence is presented here, however, that subjects’ generosity can be reversed
by allowing them to take a partner’s money. Dictator game giving therefore does not
reveal concern for consequences to others existing independently of the environment,
as posited in rational choice theory. It may instead be an artefact of experimentation.
Alternatively, evaluations of options depend on the composition of the choice set.
Implications of these possibilities are explored for experimental methodology and
charitable donations respectively. The data favour the artefact interpretation, suggesting
that demand characteristics of experimental protocols merit investigation, and that
economic analysis should not exclude context-speciﬁc social norms.
Keywords Altruism · Artiﬁciality · Experiments · Methodology
JEL Classiﬁcation C91 · C70 · D63 · D64
Experimental economists have investigated unselﬁsh behaviour with a familiar set
of simple games (Camerer 2003, pp. 43–100). The simplest is the dictator game, in
which subjects have to decide how much, if any, of an endowment to give to another
subject, typically in a one-shot anonymous setting. Usually transfers are plentiful; it
is common for over 50% of subjects to give money away (Camerer 2003, pp. 57–
58). Several models of unselﬁshness have been put forward within the parsimonious
framework of rational choice theory. These theories compete over data from dictator
Electronic supplementary material The online version of this article
(http://dx.doi.org/10.1007/s10683-007-9172-2) contains supplementary material, which is available
to authorized users.
N. Bardsley ( )
National Centre for Research Methods, University of Southampton, Southampton, UK
e-mail: nb6@soton.ac.uk
Dictator game giving: altruism or artefact? 123
games and other experiments, and include model of inequality aversion (Bolton and
Ockenfels 1998; Fehr and Schmidt 1999), altruism (Andreoni and Miller 2002), egocentrism
(Cox et al. 2002) and Rawlsian “social welfare” preferences (Charness and
Rabin 2002). Such models continue to attract intensive research effort.
Whilst dictator giving has proven hard, though not impossible, to eradicate in the
lab, some experimentalists still express unease about the results.1 A common concern
is that people could always make anonymous donations to random strangers in
everyday life, for example by mailing cash to persons sampled from the telephone directory,
but few if any choose to do so. Transfers are made instead to family members,
speciﬁc organisations or face-to-face to people requesting money. Since we face the
dictator game all day every day, it could be argued, the experimental design would appear
to score highly on conventional standards of ex-ante external validity. It presents
a familiar set of opportunities in a task which makes minimal cognitive demands. Yet
the results appear to be misleading about the extent of faceless interpersonal altruism.
Giving is also notoriously sensitive to experimental treatments. This adds to
the uncertainty about how the results from dictator games generalise to naturallyoccurring
contexts. See, for examples, Eckel and Grossman (1996) on anonymity and
charities versus individuals as recipients, Hoffman et al. (1996) and Bohnet and Frey
(1999) on social distance, Cherry et al. (2002) on earned versus unearned income,
and Haley and Fessler (2005) on visual suggestions of observation. The evidence has
tended to be that giving is sensitive to factors for which theory makes no prediction,
or which can be explained by theory. Intriguingly, theoretically-motivated sensitivity
tests reported by Andreoni and Miller (2002), found that rational choice theory ﬁts
dictator game data surprisingly well.
On the other hand, there is evidence from related games that behaviour is also
sensitive to factors which are irrelevant according to consequentialist theories, such
as intentions. For example, in ultimatum games Falk et al. (2003) ﬁnd that respondents’
behaviour depends on payoffs to the proposer in avoided subgames.
Similar results are offered by Brandts and Solà (2001). In a variant on dictator
games, Dana et al. (2005) ﬁnd that introducing uncertainty over the recipient’s
outcomes reduces egalitarian choices even when the uncertainty can be costlessly
resolved. This result is discussed further in Sect. 3 below and seems to indicate
that much giving is not motivated by a desire for fairer outcomes for their
own sake, but for a further motive. Because of this kind of data, orthodox accounts
of social preferences might be better seen as attempts at reasonable approximations
of speciﬁc motivations, for limited domains, than at literal general
truths.
The above synopsis of the existing evidence suggests that dictators’ giving is probably
more volatile than a literal interpretation of social preference theories might
suggest, and does not translate straightforwardly into insights about behaviour in the
ﬁeld. However, the possibility still appears open that dictator game data is explained
by subjects’ underlying tastes, values, goals and so on, imparting value, whether directly
or indirectly, to the other’s payoff. The experiments reported below investigate
1I refer to remarks made by Arthur Schram at the 2003 University of Nottingham workshop on “The Role
of Experimental Methods in Economics” and discussion with Robert Sugden.
124 N. Bardsley
directly whether dictator games measure social attitudes, in this broader sense. Much,
perhaps even most, of the dictator games literature supposes that subjects arrive at the
lab with such dispositions, which then determine their satisfaction with the initial allocations.
If this process explains giving, subjects should also want to give if taking
is possible. The experiments compare dictator games to “taking” games which introduce
taking options; the proportion of subjects willing to give should be unchanged.
This prediction is quite intuitive, but is also an implication of rational choice theory,
as shown in Sect. 1 below.
In contrast with many studies of dictator games, but in common with Andreoni and
Miller (2002), the present study is a theoretically-driven sensitivity test. It focuses on
a subject’s willingness to give, in abstraction from the amount given. The treatment
manipulation is ineffective assuming that the endowment is consistently regarded as
either too selﬁsh, too generous or just right along budget lines which implement the
same price of transfers. In contrast to previous studies, therefore, it tests a basic qualitative
proposition implied by common readings of the design. The bold claim that
a given social preference theory is conﬁrmed by the data requires this postulate and
more, for there subjects’ attitudes determine a well-behaved indifference map over
outcomes. The test conducted is lenient towards weaker social preferences explanations
of giving, since it allows gifts to vary in size, as predictably occurs with any
change in the environment, without rejection of the null hypothesis. The null is only
rejected if there is evidence that some subjects’ willingness to give can be completely
eliminated by taking options.
1 Design
Three experiments were conducted, with two treatments in each. The design compares
a dictator game (treatment 1; T1) to a “taking game” (treatment 2; T2), which
introduces taking options. The treatments are represented in Fig. 1 below. Let (a,b)
represent an allocation of £a to a dictator and £b to her partner, B denote a dictator
Fig. 1 Dictator and taking game budget lines
Dictator game giving: altruism or artefact? 125
game budget line and e the endowment point. B has the same gradient and endowment
point as the budget line in T2, denoted B , but B extends to the south east
of B.2
Social preference theories posit convex indifference curves in (a,b) space. Points
on a budget line further away from the optimum in a given direction lie on progressively
lower indifference curves. Suppose a subject starting at e, facing B, gives
money because her optimum is to the northeast of e. Then she should also like to give
facing B , since an indifference curve can be tangential with a budget line, of arbitrary
length, at one point only. In experiments 1 and 2 the treatments provide identical
giving options, that is, B ∩ B = B. The population proportions giving should therefore
be equal. In experiment 3, in contrast, subjects cannot give in T2 so B ∩ B = e.
So there, if the optimum represents a positive transfer, e should be chosen from B .
The proportion of givers in T1 should therefore not exceed that choosing e in T2. In
each case the null hypothesis is that of equality of the relevant proportions, with a
two-sided alternative hypothesis.
Common procedures were as follows. The experiments were run as pen-and-paper
exercises, with dictators choosing payoffs from a table. Subjects were mixed-gender
undergraduates. Separate samples were used for each treatment to eliminate deliberate
responses to experimental manipulation. T1 and T2 were run at different times of
day for organisational reasons, with the order varied across experiments. Subjects in
one room were randomly matched with a partner in another. Subjects in the receiver
role did not have any task to perform but were fully informed; they simply awaited
the outcome. To preserve anonymity, dictators were seated apart and made their decision
privately. The experimenter issued instructions, available on the journal website,
which were also read aloud, but was not present when decisions were made.3
Assistants then administered and made payments, who were uninformed about the
design, so the experimenter and assistants were blind to individual behaviour. The
resulting double anonymity between subjects and experimenters was emphasised in
the instructions. T1’s instructions abridged T2’s, making only the changes required
to alter the choice set. As conventionally conceived, this holds the framing constant
across treatments. Basic details of each experiment are given in Sects. 2.1–2.3; for
full results and statistical signiﬁcance see Fig. 2 and Table 1 of Sect. 2 respectively.
2 Experiments 1–3
2.1 Experiment 1
Experiment 1 implemented equal endowments (£6 each) and scaled-up transfers, following
Cox et al. (2002) who provided initial evidence of dictator taking. In T1 dictators
could transfer £(0–4), in increments of £0.33p. Transfers were doubled. In T2
2Cox et al. (2002) report that when giving involves a higher transfer rate than taking, kinking the budget
line of the taking game, dictators generally take. The authors show that in that environment orthodox
indifference curves may license both taking game taking and dictator game giving, a possibility excluded
here.
3There were minor differences in script between experiments, but never across treatments within an experiment.
The principal difference is that in experiment 1 subjects had to circle a number on a decision
table, but in the other experiments they had to circle a letter. This was to strengthen the inscrutability of
the design to the assistant paying subjects.
126 N. Bardsley
Fig. 2 Frequency distributions of transfers in experiments 1–3
dictators could make the same gifts, or take up to £2 at the same rate: £1 received cost
their partner £2. Subjects also received £2 show-up fee. Experiment 1 was conducted
in June 2004, with 110 subjects. T2 was implemented before T1.
In T1 the proportion of subjects giving, p1, was 6/26. In T2 this proportion, p2,
was just 1/29. The difference in proportions, p1 − p2 ≡ d1, is signiﬁcantly different
Dictator game giving: altruism or artefact? 127
Table 1 Statistical signiﬁcance
Experiment Bootstrap conﬁdence interval for difference in
proportions
1 0.0384 ≤ d1 ≤ 0.385 (95%)
2 0.041 ≤ d1 ≤ 0.415 (90%)
3 0.079 ≤ d2 ≤ 0.667 (99%)
from zero (p < .05).4 The extent of the inconsistency is unclear, however, since few
subjects gave in T1. This problem motivated experiment 2, using more normal dictator
game parameters. Also, experiment 1 suggested that giving might be extremely
fragile; experiment 2 made taking options a smaller proportion of the choice set to
test this.
2.2 Experiment 2
Experiment 2 used transfers at a rate of £1:1 and unequal endowments. Subjects were
informed they had a show-up fee of £4 each. Dictators in both treatments were given
an additional £7. In T1 they could give £(0–7). In T2 they could give £(0–7) or take
£(0–2) of their partner’s show-up fee. Transfers were made in increments of £0.50p.
The experiment was conducted over two dates, in November and December 2004,
with 130 subjects. T1 was implemented before T2.
Results were in the same direction as for experiment 1, with 23/33 subjects giving
in T1 and 15/32 giving in T2, but only signiﬁcant at the 10% level. However,
taking options in T2 constitute a smaller proportion of the choice set. A sterner test
of dictator giving was therefore conducted next, removing strictly positive transfers
from T2.
2.3 Experiment 3
Experiment 3 also implemented £1:1 transfers and unequal endowments. Dictators
were informed they had an endowment of £10 and their partner £5. In T1, dictators
could give £(0–3). In T2, dictators could take £(0–3), but could not give. Transfers
were in increments of £0.25p. Experiment 3 was conducted in February 2005 with
120 subjects. T2 was implemented before T1.
In T1, the proportion of subjects giving was 17/31, exceeding that choosing the
status-quo in T2, p3, of 5/29. The difference in proportions, p1 − p3 ≡ d2, is highly
signiﬁcant (p < .01). The point estimate of the proportion of generous choices that
disappears across treatments, s ≡ d2/p1, is 0.69, indicating that most dictator game
givers would take, were the endowment the least selﬁsh option. The bootstrap 95%
conﬁdence interval for this estimate is 0.342 ≤ s ≤ 0.929.
4See Sect. 2, Table 1. The Z-test for equality of proportions and chi-sq test are inappropriate when frequencies
approach zero. Since alternative methods exist for calculating two-tailed p-values for Fisher’s exact
test (Agresti 1992) and it is unclear here which is preferable the bootstrap technique is used (Efron 1979).
A number of draws equal to the sample size was taken, with replacement, 10,000 times from T1 data. The
procedure was repeated with T2 data, simulating the alternative hypothesis. Two-sided conﬁdence intervals
were calculated with the percentile method, which provide the p-values in the text.
128 N. Bardsley
To summarise, the three experiments show similar indications of inconsistency
between treatments 1 and 2. In experiment 1 the difference in unselﬁsh behaviour is
signiﬁcant at the 5% level, in experiment 2 at the 10% level, and in experiment 3 at
the 1% level. The most decisive results, of experiment 3, indicate that most dictator
game givers would take presented with sufﬁcient taking options, despite being better
off initially.
3 Discussion
The reversing of generosity between treatments is inconsistent with any theory of
dictator game giving which regards underlying other-regarding motivation as causing
a desire to share the endowment, and therefore with any orthodox social preference
account.5 The evidence here is actually consistent with that presented by Andreoni
and Miller (2002), who ﬁnd in favour of rational choice altruism, since they only
examine behaviour in the giving domain. It rules out their interpretation, though,
since that is inconsistent with the observed sensitivity of giving to taking options.
Further, modiﬁcations of theory to incorporate intentions à la Rabin (1993) cannot
explain these results since they concern exchanges of harms and beneﬁts rather than
their unilateral inﬂiction studied here.
It is interesting to compare the results to those of Dana et al. (2005) who also cast
doubt on the other-regarding interpretation of dictator behaviour. The authors ﬁnd,
relative to a dictator game in which dictators choose between monetary payoffs of
$(6, 1) and $(5, 5), that fair choices atrophy when the dictator does not have full responsibility
for the other’s payoff. For example, in one variant the other’s payoff is
$1 or $5 with equal probability, but the uncertainty can be costlessly resolved before
choosing. Few subjects chose to resolve the uncertainty and most chose $6 for themselves.
The authors conclude that subjects are more concerned to seem than to be
fair, since by choosing not to know the other’s payoff they can attribute the inferior
outcome to chance; it is the transparency of responsibility in the dictator game that
causes generosity. However, the taking observed in experiments 1–3 above occurs
where dictators are transparently responsible, so this interpretation does not seem
tenable here.
One explanation of the present results is that dictator game giving is a “Hawthorne”
effect (Roethlisberger and Dickson 1939; Adair 1984; Jones 1992), that is, an artefact
of behavioural experimentation. Call this reading 1. The Hawthorne effect might
plausibly be interpreted as subjects’ reacting to experimental “demand characteristics”
(Orne 1962, 1973), meaning the cues the protocol supplies about appropriate
behaviour.6 Here, subjects might feel that the dictator game is about giving, since
they can either do nothing or give, whilst taking options could introduce a conﬂicting
message. The attitude causing the treatment effect may therefore be one towards
5List (2007) has subsequently replicated the result that willingness to give erodes with taking options.
6Given the proliferation of meanings of the term “Hawthorne effect” it is probably best avoided. The
“demand characteristics” terminology is already established in psychology and conveys better the structural
nature of the purported confound than “demand effect”, which may connote inﬂuence exerted by the
experimenter in person.
Dictator game giving: altruism or artefact? 129
the experiment, such as a desire to be a good subject. Demand characteristics do not
appear to have been much researched by economists but psychologists sometimes
claim to explore them empirically. Examples are Fernandez and Turk (1994), Davies
and Best (1996), Faith et al. (1998), Lampinen et al. (1999), and MacLeod (1999).
Reading 1 suggests that it may not be transparency alone that accounts for Dana et
al.’s (2005) data. For the introduction of actions which less directly harm the other
may alter the message the environment gives off about normal behaviour.
As with any experiment, however, alternative interpretations of results should be
considered. A second interpretation of the present data, reading 2, is that dictator
giving is subject to a “range” effect, in the sense of Parducci and Wedell’s (1986)
“range-frequency” model, according to which the rate of selection of an option is
affected by its location and frequency in the choice set. Here options have equal
frequency on subjects’ decision sheets, but the perceived kindness of an action may
depend on its location in the range available. Consider experiment 3, for example.
In treatment 2, taking £1 might be seen as kind since a subject could take up to £2.
Whilst in treatment 1, giving nothing is the least kind action available, so the same
desire to be kind, judged relative to the meanest action, would result in a positive
gift. Note that the distribution of choices in experiment 3, treatment 1, resembles
a translation to the right of the distribution in treatment 2 (Fig. 2, Experiment 3). If
perception of the kindness of an action is anchored to the available alternatives, this is
inconsistent with orthodox social preferences. It is consistent, though, with the way
kindness is incorporated into Rabin’s (1993) reciprocity model, where it is judged
relative to a reference point. In the model this point is left open, but in application it
has been speciﬁed as follows: an action is neutral if it allocates to a partner a payoff
mid-way between the highest and lowest payoff the agent could allocate them. If it
allocates more (less) than this, it is judged to be kind (unkind).
If the perceived kindness of an action is subject to a range effect generally, this
should have further economic consequences. Consider one example, closely related
to the dictator game. Many charities nowadays issue requests for regular direct debit
contributions, and/or specify a menu of donations at many different levels.7 One rationale
for this may be to exploit an interaction of the range effect and “mental accounting”
(Thaler 1999). For an extended gift menu, relative to simple open-ended
requests for one-off donations, may expand individuals’ perceptions of the choice set
pertaining to the donation decision. People may thereby come to perceive smaller
donations as more selﬁsh. A second possible consequence would be a solution to
the crowding-out puzzle of public goods theory. There, changes in others’ contributions
to a public good and changes in income produce the same outcome. That implies
strong crowding-out between individuals’ contributions given that private consumption
is a normal good, an extreme result generating puzzling comparative-static
“neutrality” results (Bergstrom et al. 1986). For example, equilibrium public good
provision is invariant to the distribution of income and the number of contributors.
7See, for example, the range of giving options the World Wildlife Organisation presents on its UK website:
http://wwf.org.uk. At the time of writing, April 2007, this site gives many options for giving, including regular
subscriptions and legacies. The one-off donation option presents the viewer with a range of donations
from £5 to £1000 with a default gift of £5.
130 N. Bardsley
However, if the desirability of a donation depends on its position within the choice
set, the consequentialism driving these results is broken.8
Finally, one might invoke stochastic choice models to explain the data, reading 3.
There are two approaches that currently predominate in the literature, models based
on Fechner’s (1966 [1860]) measurement error theory, such as that incorporated into
Quantal Response Equilibrium analysis (McKelvey and Palfrey 1995), and the ‘random
preferences’ model (Loomes and Sugden 1995). Consider ﬁrst utility measurement
error. This posits a random disturbance to an option’s underlying utility. In the
dictator game a utility function should select a dominant option depending on its
form: the lower bound of the choice set for a selﬁsh agent, the upper bound for a
perfect altruist, the equal split for a pure egalitarian and so on. The error would have
to be such that it regularly obscures the underlying difference in desirability between
giving, taking and maintaining the status quo. But payoffs here are completely transparent,
so substantial measurement error is just implausible.9 Alternatively, if the uncertainty
concerns underlying preferences themselves, we have random preferences
theory, according to which the utility function of each agent is randomly drawn from
a set of functions prior to a choice. However, by hypothesis, the same population of
utility functions is sampled in both treatments. Therefore the expectation must be that
of parity of distribution of realised utility functions. It follows that we should expect
the same frequency distributions of choices in T1 and T2, excepting the implications
of censoring and sampling variation. This is the equivalent to the hypothesis tested,
so the random preferences model makes no relevant difference in this context.
To distinguish conclusively between readings 1 and 2 further empirical work is
required. This may involve exploring subjects’ perceptions of the experiment, since
on reading 1 these drive the result. On either reading, the results conﬁrm that dictator
game giving provides no evidence of context-free pro-social behaviour or, therefore,
orthodox social preferences. The present data favour reading 1, however, since in experiment
1 the proportion exercising no restraint appears to differ across treatments:
77% give nothing in treatment 1 whilst 48% take maximally in treatment 2 (Fig. 2,
Experiment 1). Also, the equal-split allocation is non-modal in experiment 1, treatment
2, where it is the endowment. In contrast it is a pronounced modal choice in
experiments 2 and 3 where the endowment favours the dictator, suggesting it is not
focal when it constitutes the do-nothing allocation.
8Suppose, for example, that one decides to donate to a homeless person on the street. One might frame
the decision problem as how much of one’s loose change, £c, to give. Suppose one decides on the midpoint
between the most and least generous action, giving £c/2 (initial hypothesis). Now suppose that
one had £(c + 1) in coins initially (counterfactual 1). This should cause one to make a larger donation;
the mid-point gift becomes £(c + 1)/2. Now suppose instead, with initial change £c, that another person
unexpectedly donates £1 before one arrives (counterfactual 2). Donating £c/2 is still the mid-point action,
so the beneﬁciary should receive £c/2 + 1 in total, whereas in standard theory the recipient should receive
the same total contributions in both counterfactuals.
9There is also evidence that the Fechner model predicts poorly when options’ relative payoffs are transparent.
For example, Loomes and Sugden (1998) study choices over simple gambles, including pairs close
in expected value where one is dominant. There, the model predicts that noise eclipses preferences, but
subjects overwhelmingly choose the dominant gamble. Dictator game decisions are even simpler since
there is no uncertainty.
Dictator game giving: altruism or artefact? 131
4 Conclusions
Most subjects’ generosity appears to be reversible by allowing sufﬁcient opportunity
to take. Dictator game giving is therefore not explained by unselﬁshness towards
others that exists independently of the experimental context. By implication it is not
explained by orthodox microeconomic models of social preferences. Two interpretations
are offered involving different ways attitudes may depend on the experimental
choice set. On reading 1, dictator giving is a product of experimental demand characteristics
and attitudes to the experiment, with the choice set contributing to the cues
which indicate appropriate behaviour. This has methodological implications but also
potential theoretical consequences, since standard accounts of such effects invoke a
more sociological model of action than economists have traditionally employed. On
reading 2, dictator game giving stems from the sensitivity of decisions to an option’s
location in the choice set. Reading 2 points to a psychologically-enriched model of
choice. Reading 1 accommodates better the experimental data and can account for the
apparent external invalidity of the dictator game. It is therefore important to consider
its implications both for economic theory and for experimental methodology.
Regarding theory, responsiveness to demand characteristics of experiments may
indicate the role of context-speciﬁc social norms in behaviour. If so, whilst ‘one man’s
artefact is another man’s phenomenon’, the phenomenon in question would appear to
be sociological in character. For example, the concept of role obligation seems relevant
if volunteers are motivated to behave as ‘good subjects’. This coheres well with
certain facts about gift-giving which are opaque to orthodox microeconomics. For
example, for all their apparent efﬁciency compared to speciﬁc goods, cash gifts are
often regarded as inappropriate outside the family, excepting speciﬁc occasions such
as weddings (Douglas and Isherwood 1979). And where cash is given at weddings
this is only appropriate either at the behest of the couple or as part of a speciﬁc cultural
tradition—it is customary to give cash at Greek weddings, for example, but not
at British ones.
Regarding experimental methodology, scepticism about laboratory social science
sometimes centres on the supposedly ineliminable nature of demand characteristics.
Greenwood (1982) in particular offers a philosophical critique of the lab on this basis,
and similar arguments are given in Harré and Secord (1972, Chap. 3) and Dilman
(1996) for examples. This literature focuses on the older experimental traditions of
psychology. It seems that as a purely a priori argument the critique claims too much.
For if the premise holds that consensual experiments necessarily have demand characteristics,
it is still empirical whether they differ across treatments in a given case
and also empirical whether this causes a treatment effect.10 That implies a role for
empirical checks such as the current exercise. It is quite possible that the dictator
game is the most sensitive commonly-used game, but in the absence of checks this
is a matter of speculation. Orne’s (1962, 1973) studies contain suggestions for the
exploration of demand characteristics using independent empirical exercises. These
may merit adoption or adaptation for economics experiments, to provide insight into
where there are, and are not, likely to be problems.
10I owe this point to Robert Sugden. The implications of Greenwood’s critique for experimental economics
are discussed in Bardsley (2005).
132 N. Bardsley
Acknowledgements These experiments were funded by the Leverhulme Foundation Grant “The Role
of Experimental Methods in Economics.” The author acknowledges assistance from Mauro Pisu with resampling
methods and from colleagues at the University of Nottingham with experimental administration.
Comments from Arthur Schram, Robert Sugden and participants at the June 2005 meeting of the Economic
Science Association in Montreal greatly improved the paper. Any errors are the author’s responsibility.
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