Lying and Friendship
Sugato Chakravarty, Yongjin Ma, Sandra Maximiano∗
This version: March, 2011
Abstract
The goal of this paper is to investigate the interaction between social
ties and deceptive behavior within an experimental setting. To do so, we
implement a modified sender-receiver game in which a sender obtains a private
signal regarding the value of a state variable and sends a message related to
the value of this state variable to the receiver. The sender is allowed to be
truthful or to lie about what he has seen. The innovation in our experimental
design lies in the fact that, in contrast to the extant sender-receiver games, the
receiver can take no action – which eliminates strategic deception. A further
innovation lies in the fact that subjects (i.e., senders) are not restricted to
choose between truth telling and a unique type of lie but, instead, are allowed
to choose from a distinct set of allocations that embodies a multi-dimensional
set of potential lies. Our experimental design is, therefore, able to overcome
an existing identification problem by allowing us to disentangle lying aversion
from social preferences. We implement two treatments: one in which players
are anonymous to each other (strangers); and one in which players know
each other from outside the experimental laboratory (friends). We find that
individuals are less likely to lie to friends than to strangers; that they have
different degrees of lying aversion and that they lie according to their social
preferences. Pro-social individuals appear to be more lying averse. If they
lie, however, they are equally likely to do so with friends and strangers. The
deceptive behavior of selfish individuals mimics those of pro social types only
when subjects play with friends. Overall, in addition to social preferences,
friendship appears to be an important factor in improving our understanding
of deceptive behavior.
Chakravarty and Ma: Department of Consumer Sciences, Purdue University, West Lafayette,
IN 47907, US. Maximiano: Department of Economics, Krannert School of Management, Purdue
University, West Lafayette, IN 47907, US. Corresponding author: Sandra Maximiano, Purdue
University, Krannert School of Management, room 523. 403 West State Street. IN 47907-2056.
Phone: 765-496-8049. Email:[email protected] We thank Timothy Cason and the seminar
participants in the experimental Brown Bag seminar at Purdue, and the seminar participants
at ESA meetings in Copenhagen, 2010, at the university of Amsterdam, at the University of
Rotterdam for their helpful comments and suggestions.
∗
1
Introduction
We are all liars! We lie when it is in our best interest to do so - a fact that is
consistent with standard economic paradigm. As students, we lie about our abilities
to impress our professors; as workers we fabricate excuses for oversleeping and job
tardiness; as spouses, we may tell little “white lies” about where we were on our
way back from work or what we may have purchased on the sly; as friends, we may
comfort an overweight friend by telling her she looks wonderful; as politicians we
make unrealistic promises that we have no intention of keeping, simply to improve
our chances of being elected; as lawyers, we may fabricate far-fetched theories in
order to improve the likelihood of winning the case; as car dealers, we lie about
our inventory and other aspects of the car in order to improve our chances of
making the sale. Such examples, encompassing every aspect of our daily lives,
can go on and on. No matter what the context, the existence of private information
is a necessary condition for lying, but not necessarily a sufficient one. Just as
important, not everyone lies when lying is incentive compatible. And even if lying
is encouraged and rewarded, through perverse incentives, people often set their own
boundaries between unethical and self, or socially approved, deception, weigh the
costs and benefits of lying and, sometimes, may choose tell the truth even when it
is economically disadvantageous to do so.
Recent experimental evidence shows that this is, indeed, the case. Gneezy
(2005), for instance, finds a statistically significant level of lying aversion. Using a
sender-receiver game (Crawford and Sobel, 1982) he shows that senders are more
likely to lie the higher their own potential gains, and less likely to do so the
more lying damages the receiver’s payoffs. Other studies explore the robustness
of Gneezy (2005)’s findings. For instance, Sutter (2009) considers sophisticated
deception and reports that many people tell the truth with the intent to deceive
their partners. Hurkens and Kartik (2009) confirm the existence of lying aversion,
but they contest the role of consequences in deception that can be inferred from
Gneezy’s results. In particular, they show that in both theirs, and in Gneezy’s
experiments, subjects are one of two types: those who never lie or those who lie
whenever the outcome obtained by lying is preferred over the one obtained by telling
the truth. In subsequent work, Erat and Gneezy (2009) consider white lies and find
evidence of lying aversion independent of any social preferences over outcomes.
1
Our paper has two main goals. First, we investigate whether individual lying
behavior is sensitive to friendship ties.1 More specifically, how is an individual’s
lying aversion affected by friendship and how does friendship change the pattern of
lies he chooses to tell? We wish to underscore that although market relationships
are primarily instrumental, and economic theories are impersonal, the individuals
involved are not and, in many cases, have close personal ties. As theories of social
distance, and experimental evidence, have shown, other-regarding preferences are
stronger between physically and emotionally connected individuals than between
strangers.2 Therefore, how is the preference for fairness affected by a potentially
higher duty of honesty towards a friend? Second, we wish to characterize an accurate
description of individual lying behavior. In our view, the classification of people as
either “moral types” (never lie) or “economic types” (lie whenever the allocation
from lying is preferred) is simplistic, unrealistic, and driven mainly by design. A
large spectrum of individuals weighs the morality costs and the benefits (individual
or social depending on social preferences) from lying, and decides whether to lie
or tell the truth. Therefore, by accurately identifying these individuals, we seek to
minimize the type II error that exists in the previous classification, allowing for a
sharper inference on the intensity of lying aversion in a laboratory setting.
We use a modified sender-receiver game with four possible true states and four
possible monetary payoffs for both the sender and the receiver in each of those states.
We elicit senders’ messages for each possible true state. The sender may lie or tell the
1
Social psychologists have conducted empirical research on lying and social distance is one
dimension explored. However, this research relies on surveys and self daily reports of individuals
lying behavior thus suffering from inaccurate reporting. DePaulo et al. (1996, p.992) recognizes the
problem and writes: “because of lapses in memory and conscientiousness, participants may have
neglected to record some of their lies. There also may have been times when they did not even
realize that they had told a lie”.
2
The stream of research on the relation of social preferences and social distance is relevant
for our study. For example, Hoffman et al. (1996) investigate how social distance influences
fairness. They find that subjects have preprogrammed and unconscious rules of social exchange
behavior when they interact with other subjects. They suggest that a decrease in perceived “social
distance” increases donations in dictator games. Bohnet and Frey (1999) find that closer social
distance increases the fairness of the outcome. Polzer et al. (2009) compare allocations to friend
and stranger in an ultimatum game. They report that friend demands significantly less to reach
an agreement than stranger. Glaeser et al. (2000) match subjects at various social distances in a
trust game and find that closer social distance increase both trust and trustworthiness. Leider et al.
(2009) report that “directed altruism increases giving to friend by 52 percent relative to random
stranger”. Reuben and van Winden (2008) use between-subject design in a three-player power to
take game to investigate the effect of social distance on negative reciprocity. They find friends are
more likely to punish the proposer and more likely to coordinate their punishment.
2
truth and the sender’s message is binding. Therefore, in our experiment the receiver
has no choice to make. This way we exclude, by design, any possibility for strategic
lying by the sender. However, before subjects play the actual sender-receiver game,
we implement a modified dictator game. This first stage aims at obtaining the
ranking of preferences of senders for each of the four allocations.3 To investigate the
relationship between friendship ties and lying behavior, we consider two treatments:
(1) a treatment where subjects do not know each other (the strangers treatment)
and a treatment where pairs of friends play together (the friends treatment).
We wish to underscore that our specific two stage experimental design makes
a methodological contribution to the extant literature on lying aversion. To wit, the
modified sender-receiver game we implement in the first stage not only eliminates
strategic deception but, more importantly, also solves an identification problem4 in
the following way: It allows us to directly distinguish between lying aversion and
outcome oriented social preferences, without the need for explicitly eliciting social
preferences. So, for instance, the number of lies a subject tells is, in our experiment,
a sufficient statistic to infer the subject’s lying aversion. Recall that, in our design,
senders have to first choose among the four monetary allocations – the allocation to
be implemented in each of the four possible true states. Note that, independent of
any distributional concerns, the truth is incentive compatible only once. Therefore,
if we observe less than three lies from a given subject, we can safely infer that this
particular subject has procedural preferences, and exhibits lying aversion, at least
to a certain degree. In addition, we also capture a more accurate distribution of
lying behavior. Subjects with a high degree of lying aversion will never lie and
subjects with an intermediary degree of lying aversion will lie less than three times.
The economic types in our experiment consist of either of those individuals: those
with a sufficiently low degree of lying aversion or those who lie whenever they have
an incentive for doing so. The economic types are then expected to lie 3 out of 4
times.5 Moreover, by comparing the messages chosen in the sender-receiver game to
3
So, for instance, if the four possible allocations are denoted as A, B, C and D, one sender
may rank her preference as C, B, D, A while another sender may rank his preference as D, C, A,
B... and so on with each of the other senders. The bottom line is that each sender will reveal her
distinct ranking preference before the start of the main experiment.
4
The identification problem here refers to standard sender-receiver games being unable to
distinguish between why subjects lie – because of lying aversion or because of social preference.
5
Another way of expressing this is to say that economic liars will tell a lie whenever they have
an incentive to do so.
3
those same individuals’ ranking preferences from the modified dictator game, we can
study the relationship between the type of lies individuals decide to tell and their
respective social preferences.
Our findings are as follows. In line with the previous studies, we find that
subjects have procedural preferences and that a significant proportion of individuals
are averse to lying. However, our results indicate that individuals lie if the benefits
from lying compensate the moral costs from doing so. Our data shows that 15%
of individuals never lie, 35% are economic types and lie whenever they have an
incentive to do so, and 50% exhibit a certain degree of lying aversion that restricts
them from implementing their most preferred outcome. Also, our results show a
relationship between social preferences and lying behavior. First, fair (or, inequity
averse) subjects seem more lying averse than selfish types and, second, the different
pattern of lies is explained by the heterogeneity in individuals’ social preferences.
Conditional on gains and losses for themselves and others, individuals are more
willing to lie when lying implements an equal allocation. Related to friendship ties,
we show that friendship significantly affects behavior. First, individuals are less
likely to tell a lie in the friends treatment. In particular, we observe a significantly
higher (significant at the 0.01 level) proportion (40%) of individuals that never lie
in the friends treatment as compared to the strangers treatment (15%). Second,
despite 30% of subjects who lie to a friend (compared to 33% who lie to strangers)
whenever they have an incentive to do so, they tell significantly fewer selfish lies
(relative to selfish lies in the strangers treatment).6 Using a within-subject design,
we find that all the above results are robust when the same subjects play both with
strangers and with friends.
The remainder of this paper proceeds as follows. The next section presents
our experimental setup and the main differences from earlier experiments. Section 3
discusses the behavioral predictions. Section 4 presents the experimental procedure.
The main features of the data and the empirical results are presented in Section 5.
Section 6 discusses the robustness of the results. Section 7 summarizes and
concludes.
6
Specifically, 44% of the lies are selfish lies in the friends treatment and 67% of the lies are
selfish lies in the strangers treatment. The difference is significant at the 0.01 level.
4
2
Experimental setup
Our setting comprises a non strategic, four-outcome version of the cheap talk senderreceiver game by Crawford and Sobel (1982). In our game, there are four equally
likely states of the world, A, B, C, and D. Each state is mapped into four possible
payoff allocations for both the sender and the receiver. Table 1 I shows the allocation
payoffs. Nature moves first and determines the true state. The sender, and only the
sender, is informed about the true state and sends a binding message to the receiver
from the set of possible states. The sender can either tell the truth or lie. The
message determines which of the four payoff options is implemented. The sender
knows the payoff allocations but the receiver is never informed about what these
may be.
Table 1
ALLOCATION PAYOFFS
A
B
C
D
(20, 20)
(15, 30)
(30, 15)
(25, 25)
As alluded to earlier, each subject participates sequentially in two independent
games. The first one is a ranking game and the second is a message game that
implements our modified sender-receiver game. The ranking game itself is a modified
dictator game in which senders reveal their distributional preferences regarding the
four specified payoff allocations for both the sender and receiver. The ranking
choice is incentive-compatible with the highest ranked allocation having the highest
probability of being implemented. In particular, there is a 50% chance that players’
payoffs in the ranking game are given by the sender’s first preferred option, 25%
chance that players’ payoffs are given by the sender’s second preferred option, 15%
chance that the senders’ payoffs are given by the sender’s third preferred option,
and 10% chance that the senders’ payoffs are given by the sender’s fourth preferred
option.7
7
Our choice of these relative probabilities reflects our desire to incentivize the subjects in
revealing their true outcome preferences and in their understanding that their first choice will
be selected with a high likelihood. By the same token, we did not wish to put very little weight on
subjects’ third and fourth preferred outcomes to ensure that these did not become random choices.
In that sense, these probabilities could be tweaked a bit without significantly altering the ranking
5
Our treatment variable is the friendship ties that exist between the sender and
receiver. We compare two different treatments. One, the baseline, is the strangers
treatment (strangers) where participants are anonymously and randomly matched to
another participant. The other treatment is the friends treatment (friends) where
each participant is required to bring a friend to the experiment. Pairs of friends
remain matched throughout the whole duration of the experiment.
It should be noted that our design relates closely with that of Erat and Gneezy
(2009). Like the subjects in their experiment, our subjects play the sender-receiver
game only once. However, there are important differences between their design and
ours. First, we employ a non strategic version of the sender-receiver game which
eliminates the possibility of sophisticated deception given that the receiver has no
decisions to make. In our setting, the sender’s message is binding and both the
receiver’s, and sender’s, payoffs are determined by the sender’s message.8
Second, we do not have the same allocation associated with the true state. In
other words, our design allows for the “true state” to be subject specific in that
each state of nature in our setting is mapped into a different allocation. In order to
observe a sender’s truth telling behavior in different true states we use the strategy
method (see Selten, 1967). That is, senders, before observing the true state, have
to indicate, for each potential true state, which message they want to send. The
main advantage of using the strategy method is that, by getting the sender to pick a
vector of messages, we are able to disentangle lying aversion from outcome oriented
social preferences in a straightforward way. We discuss this topic in detail in the
next section. From a game-theoretic perspective the use of the strategy method
is comparable to the direct method, in which subjects would make a single choice
only for a realized true state. Behaviorally, it may affect subjects’ behavior (see, for
example Brosig et al., 2003; Güth et al., 2001). A priori, there is no reason to think
that truth-telling behavior would be affected one way or another by the use of the
strategy method, or that there would be an interaction effect between the use of the
method and our treatment variable – friendship. Also, a number of experimental
outcome displayed by the subjects.
8
In the Erat and Gneezy (2009) setting, the sender observes a roll of 6-sided dice and sends a
non-binding message about the outcome of the roll of the dice. The receiver is asked to pick an
integer between 1 and 6 and, if the number equals the true outcome, then option A is implemented,
otherwise option B is implemented. The 6-sided dice is used to reduce the strategic lying that can
potentially exist in the two-state setting (Gneezy, 2005).
6
studies show that the elicitation (i.e., strategy versus direct) method has limited
impact on people’s behavior, especially in low complexity settings, which is the case
in our non-strategic version of the sender receiver game (see Bosch-Domnech and
Silvestre, 2005; Brandts and Charness, 2000; Cason and Mui, 1998; Falk and Kosfeld,
2003; Oxoby and McLeish, 2004).
Also, we consider four payoff allocations instead of two, which allows us to
investigate not only whether subjects lie or tell the truth but also the types of lies
subjects choose to tell. In our design, the combination of four possible true states
and the four final payoff allocations allow us to classify the type of lies not only
according to the gains and losses incurred by both the sender and the receiver but
also according to the fairness of the final allocation. In particular, we classify lies as:
a selfish black unfair (fair) lie if it increases a player’s payoff at the expense of the
other player, while implementing inequity (equity); an altruistic unfair (fair) lie if
it decreases a player’s payoff, while increasing the other player’s payoff and creating
inequity (equity); a Pareto white lie if it increases both players payoff; and a spiteful
black lie if it decreases both players payoff.
3
3.1
Behavioral Predictions
The intensity of lying
Do subjects lie? How often do they lie? Do they lie more to friends or to strangers?
We operationalize our predictions in terms of two approaches. First, there is the
outcome oriented approach that assumes individuals care only about final outcomes.
Second, there is the procedural/moral approach where individuals are assumed to
care about the process through which outcomes are generated and, in particular,
whether the path itself is consistent with their moral beliefs.
If individuals focus merely on outcomes (outcome oriented subjects), their cost
of lying is zero and we expect them to lie whenever they have an incentive to do
so (this case corresponds to the economic types in Hurkens and Kartik (2009)).
However, the incentives for lying may differ across individuals. Selfish agents who
care only about their own monetary payoffs tell lies whenever it gives them a better
outcome, regardless of the consequences for others. Also, pro-social agents are
willing to tell a lie to implement an altruistic, more equal, or more efficient allocation,
7
depending on their social preferences.9 In our experiment, these types will lie three
out of four times and we should observe no differences between treatments. The
use of the strategy method, by eliciting a vector of messages for each individual,
allows us to draw a clear prediction in those cases where people have preferences
over payoff allocations. Under this assumption, within our experiment, the truth
is incentive compatible only once - when it coincides with an individual’s most
preferred allocation. Regardless of whether one is selfish or pro-social, everyone has
an incentive to lie a maximum of three times to implement her preferred allocation.
There should be no differences in the proportion of lies between the strangers and
the friends treatments.
Alternatively, consider that individuals have procedural and/or moral preferences. In this case, when deciding whether to tell a lie or tell the truth, individuals
will judge the morality of their actions and act accordingly.10 In case the morality of
lying is determined by its consequences, lying is right if and only if it leads to at least
as much good as telling the truth. Consistent with our earlier discussion, we would
expect that pro-social subjects will lie to implement their preferred “good” allocation. Selfish subjects, on the other hand, may refrain from telling a selfish black lie.
However, given our four-outcome sender-receiver game, it does not mean that they
will not lie at all. A selfish subject who cares about the consequences of lying can
lie in a morally acceptable way, for instance, by implementing his second preferred
choice.11 Therefore, similar to an outcome-preference, subjects in our experiment
are expected to lie three times in both the strangers and friends treatments. In case
subjects have a positive unconditional moral view against lying, they will trade off
9
Formally, pro-social behavior involves caring about the welfare and rights of others, feeling
concern and empathy for them, and acting in ways that benefit others.
10
The philosophical underpinnings of our investigation can be traced back to the theory of
Consequentialism that holds that the consequences of one’s conduct are the true basis for any
judgment about the morality of that conduct. From a consequentialist’s standpoint, therefore,
a morally right act is one that will produce a good outcome, or consequence. This view is
often captured in the saying:“The ends justify the means”. Distinct from consequentialism is
the idea of deontology that distinguishes the rightness or wrongness of one’s conduct from the
nature of the behavior itself rather than the outcomes of the conduct. The differences in the two
approaches lie more in the way moral dilemmas are approached than in the moral conclusions
reached. As a practical example, a consequentialist may argue that lying is wrong because of
the negative consequences produced by lying, though certain foreseeable consequences might make
lying acceptable. A deontologist, on the other hand, might argue that lying is always wrong,
regardless of any potential good that might come from lying.
11
This is in line with guilty aversion. Under guilty feeling individuals get disutility from hurting
others.
8
the benefits from lying with the moral costs of doing so and act accordingly. If the
cost is very high, as in case of extreme moral concerns, we expect these subjects to
never lie. If, on the other hand, the costs are moderate, the corresponding subjects’
probabilities of lying will decrease with the ranking order of their true allocation.
In other words, their probability of lying will increase with the net benefit of doing
so.12
Moreover, if the moral principal of not lying is considered to be universal,
and not selectively applied to people or acts, we should observe no differences
between treatments. A less strict, pluralist, moral view assumes individuals have
different duties among which fidelity (not lying, keeping promises), gratitude, and
beneficence (do good to others) play important roles. A lie is morally wrong, but
in case of conflict with some other duty (for instance, being fair to someone else),
individuals may lie. Depending on how individuals judge their duties, we may
observe individuals not lying at all, or doing so less than three times within the
context of our experiments. Under this less strict morality view, differences may be
found between friends and strangers treatments if the duty of gratitude for instance
surpasses the duty of being honest.13,14
12
Under procedural moral preferences individuals may suffer a negative utility from the act of
lying. Similarly, individuals may derive an extra utility for being honest. It is not our purpose in
this paper to distinguish between these two preferences.
13
The moral unconsequentialist approach corresponds to the deontological approach in moral
ethics field of philosophy. The first, more strict moral view corresponds to the absolute
deontological moral system (see work of Emmanuel Kant), which is characterized by individuals’
adherence to independent moral duties, and the duty of honesty is primordial. The second, less
strict moral view corresponds to the pluralist deontological system, which is characterized by a
multiplicity of duties (see the work of W. Ross). Another ethical moral approach is virtue ethics.
It emphasizes the moral character of the actor in contrast to duties or the consequences of actions.
Under this approach is less clear in which cases lies are permissible.
14
Both consequentialism and utilitarianism are, however, silent about relational considerations.
There is a general notion that certain relationships between people (for example, family, love,
and friendship) engender ethical obligations. And we may strengthen them with the appropriate
consequentialistic or utilitarian underpinnings. Relationships do not add anything new to these
fundamental ways of thinking but, rather, in certain circumstances, reinforce their considerations.
For the rule utilitarian moral types, lying to a friend is worse than lying to strangers, but friendship
as such does not dominate over the duty of honesty. It merely reflects a moral consideration, which
waxes and wanes depending on whom we are relating to.
9
3.2
The pattern of lies
We expect that subjects will tell different lies to friends relative to strangers. One
reason behind this prediction is the existence of other-regarding preferences (or
other-regarding moral duties) and the extent to which those preferences may vary
with friendship ties. In fact, extant experimental evidence indicates a more prosocial behavior towards friends than to strangers. For instance, Leider et al. (2009)
show that, under anonymity, subjects give at least 50% more surplus to friends than
to strangers. However, when decisions are non-anonymous, transfers increase an
additional 24% to friends in games with efficient transfers. Their results suggest
that it is not just the prospect of future interaction that is behind the more prosocial behavior towards friends but that people’s “baseline altruism” seems to be
higher for friends as well.15
In our experiment, we can infer our subjects’ social preferences for friends
and strangers by comparing their choices in the ranking game in both treatments.
In Appendix B, we formally present predictions for the ranking game under inequity
aversion and quasi-maximin preferences.16 Concerning the pattern of lies, assume,
first, the case where subjects care only about final allocations. A selfish type, and
someone who does not care sufficiently about the well-being of others, will always
lie if the true allocation does not maximize her own earnings. Therefore, these
selfish agents will lie whenever the truth differs from allocation C. If individuals
have altruistic preferences, dislike inequality, or have concerns about social welfare,
they will prefer allocation D, and they will lie in all other circumstances. In case
individuals exhibit more pro-social behavior towards friends, we expect to observe
more selfish black lies in the strangers treatment relative to the friends treatment.
Second, if subjects have moral concerns and exhibit stronger moral duties to friends,
we expect less selfish lies, in the friends treatment in particular.
15
Polzer et al. (2009) compare allocations to friends and strangers in an ultimatum game. They
report that a friend in the role of a receiver demands significantly less to reach an agreement
than a receiver stranger. Glaeser et al. (2000) match subjects at various social distances in a trust
game. They find that closer social distance increase both trust and trustworthiness. Reuben and
van Winden (2008) investigate the friendship effect on negative reciprocity and show that in a
three-player power-to-take game friends are more likely to punish the proposer and more likely to
coordinate their punishment.
16
Note that our non-anonymous friends treatment provides the total effect of “playing with a
friend” i.e., the combination of reputation considerations and the potential increase in intrinsic
social preferences.
10
Another explanation for the different pattern of lies across treatments may lie
in individuals’ concerns for social esteem. While procedural-moral preferences may
create an internal pressure in individuals for telling the truth, or only certain types
of lies, the concern for social esteem, may work as an external motivator. In case
individuals care about social esteem, they may suffer a non-pecuniary cost from
criticism, ostracism from others, loss of friendship, and/or feelings of shame when
they do not behave “properly” and such “inappropriateness” can be observed by
others.
In our experiment, subjects’ choices are unobservable by other subjects in both
treatments. Nevertheless, concerns for social esteem may arise (in expectation) in
the non-anonymous friends treatment relative to the anonymous stranger treatment.
For one, subjects may talk about the experimental results, and their choices, once
the experiment ends. Moreover, not only does anonymity vary between treatments
but the relational ties between subjects also differ. And if subjects receive utility
from what they think a “general other” thinks about them, they may get even more
utility from their friends’ judgment of their behavior and/or character.17
4
Experimental procedures
Our experimental sessions were conducted in the Vernon Smith Experimental
Economics Laboratory at Purdue University during June, August, and September of
2010. We used the z-Tree software (see Fischbacher, 2007) modified appropriately
for our purpose. Subjects were mainly undergraduates from disparate fields. On
average, a session lasted 50 minutes and the participants earned, on average, $14
dollars.
We conducted 6 sessions. Three of them comprised the Strangers treatment
(80 subjects) and the remaining three sessions comprised the Friends treatment (68
subjects). For the Strangers sessions, subjects were recruited individually and, at
the beginning of the experimental session, were randomly and anonymously matched
with another subject and remained matched with this subject for the duration of the
session. For the Friends sessions, we recruited pairs of students that had a friendship
tie and each pair of friends remained together for the duration of the session.
17
For experimental studies on social esteem see Andreoni and Bernheim (2009), Cox and Deck
(2005), Dana et al. (2006), Hoffman et al. (1996), and Tadelis (2008).
11
In all sessions, subjects’ participation comprised of two parts. Part I
implemented the Ranking Choice condition and part II implemented the Message
Condition. Given the non-strategic setting of both conditions, subjects were asked
to make decisions for both part I and part II assuming a sender’s role. Subjects were
informed that after they played part I and part II, half of the participants would be
assigned the role of sender and, the other half, the role of receiver, and that only
the decisions made by those in the role of a sender would be implemented.
Subjects started the experiment with general on-screen instructions followed
by instructions for part I. They also received a summary of the instructions on paper
for part I (see Appendix A). To ensure the experiment was understood, subjects
had to answer three quiz questions correctly before part I started. Thereafter, all
subjects made their ranking decisions for part I. When part I was over and before
learning about their earnings for this part, everyone received on-screen instructions
for part II, as well as a summary of the instructions on paper (see Appendix A).
Part II started after everyone answered three quiz questions correctly. All subjects
then made decisions for part II. Recall that subjects had to choose which message
to send for every potential true state before knowing the actual truth. In particular,
each subject had to state which message she wanted to send to the receiver for each
possible true state - A, B, C, D - each one corresponding to a payoff allocation (see
Table 1). The subject could either lie or tell the truth. The other person was never
informed as to whether the sender is telling the truth or lying. When everyone had
made their decisions, subjects were informed about the actual true state.
At the end of part II, subjects learned their role (sender or receiver) in the
whole experiment. Subjects who were selected to be senders had their decisions
for part I and part II implemented. In particular, if a subject was selected to be
a sender, her earnings, as well as the other’s person earnings, were determined by
her decisions; if the subject was selected to be a receiver, her earnings, as well as
those of the other parties’ earnings were determined by the other parties’ (sender)
decisions.
At the end of the experiment, after roles were revealed, the experimenter rolled
two 10-sided dice in front of each sender to select his/her earnings for part I in the
following way. If the dice roll turned out to be less than or equal to 50, the sender’s
first option was implemented; if the dice roll twas higher than 50 but less or equal
to 75 the sender’s second option was implemented; if the dice rolled was higher
12
than 75 but less than or equal to 90, the sender’s third option was implemented; if
the dice roll was higher than 90, the sender’s fourth option was implemented. The
receiver was only informed about his/her earnings for part I and never informed
about the sender’s ranking. For part II, the receiver never observed the vector of
the sender’s messages but only the message corresponding to the actual truth and
its corresponding payoff.
At the end of the experimental session, subjects learned of their payoffs for
parts I and II. No subject was ever informed about the choices of subjects in other
groups. Next, each participant learned of his/her own earnings in dollars, filled a
background questionnaire, and was individually, and privately, paid.
5
5.1
Empirical findings
The intensity of lying
The proportion of lies observed in both treatments is provided in Figure 1. In the
strangers treatment, there are 144 (47.4%) lies among a total of 304 messages. In
the friends treatment, the total number of lies were 90 (33.1%) out of a total of 272
messages. As can be seen in figure 1, the proportion of lies in both treatments is
significantly below 75% (also confirmed by a one-sided Binomial test, 𝑝 = 0.001).
Therefore, individuals tell, on average, fewer than three lies, which indicates that, on
aggregate, individuals do not behave as standard economic agents or as if they have
exclusively outcome-oriented social preferences. Individuals seem to dislike lying,
independent of the consequences of the act. On average, however, our univariate
results reveal a degree of lying aversion, that is stronger for friends than it is for
strangers. The difference between the proportion of lies in both treatments is
statistically significant (one-sided binomial test; 𝑧 = 1.74, 𝑝 < 0.05). To further
explore this result, we conduct a regression analysis of the likelihood of lying.
Specifically, Model I provides the effects of the treatment dummy variable friends.
Model II adds dummies for each possible true state (A being the excluded category),
and the interaction terms between the true state and the friends dummy as controls.
To account for the panel structure in our data (four messages for each subject) we
estimate a random effects probit model.
13
Figure 1
%
PROPORTION OF LIES BY TREATMENT
70
60
50
40
30
20
10
0
strangers
friends
Table 2 presents the results. First, our results confirm those obtained with the
binomial test: subjects in the friends treatment are less likely to lie than those in
the strangers treatment (Model I, 𝑝 = 0.004). Also, when the true outcome is A,
our results show that subjects do not lie significantly more in the friends treatment
relative to the strangers treatment. However, the probability of lying decreases
significantly in the friends treatment as compared to the strangers treatment when
the true state is D rather than A. In the strangers treatment, the probability of lying
increases if the true state is B instead of A and decreases if the true is C instead
of A. The same happens in the friends treatment although the differences between
treatments are not statistically significant.18
18
Background variables, such as gender and race are insignificant and hardly affect the other
coefficient estimates. We therefore provide a simpler model specification.
14
Table 2
RANDOM EFFECTS PROBIT REGRESSION WITH LYING AS DEPENDENT VARIABLE
constant
friends
B
C
D
friends*B
friends*C
friends*D
Coef.
−0.081
−0.447∗∗∗
−
−
−
−
−
−
Model I
Std. Err.
0.102
0.153
−
−
−
−
−
−
Coef.
0.112
−0.328
0.650∗∗∗
−0.673∗∗∗
−0.771∗∗∗
−0.323
0.218
−1.556∗∗∗
Model II
Std. Err.
0.192
0.286
0.239
0.228
0.234
0.349
0.346
0.481
*** Indicates significance at the 1%-level. There are 𝑁 = 576 observations in total, with
144 individuals and 4 observations per individual. The Wald statistic equals 𝜒2 = 8.52;
𝑝 = 0.0035 in Model I and 𝜒2 = 76.28; 𝑝 = 0.0000 in Model II.
The emergent aggregate picture presented above hides individual behavior
and possible heterogeneity. Not all individuals display lying aversion and some
individuals are willing to lie whenever the true allocation differs from their preferred
one. Table 3 shows the frequency of lies. Despite a considerable portion of
subjects appearing to behave as per the dictates of standard economic theory,
about 33% (29%) of individuals lie three times in the strangers (friends) treatment.
These percentages are significantly distinct from 100% (one-sided Binomial test,
𝑝 < 0.0014). The majority of subjects display a certain degree of lying aversion.
For instance, in the strangers (friends) treatment, 65% (71%) of the subjects lied
less than three times. A chi-square test reveals that there are significant differences
in the frequency distribution of the number of lies told between the strangers and
friends treatments (𝑝 < 0.001). The difference between treatments increases in
particular for those who never lie. In the strangers treatment, 15% of the subjects
never lie. A considerably larger proportion of those “moral types” is found in the
friends treatment. For example, about 40% of individuals never lie to a friend
(one-sided Binomial test, 𝑝 = 0.004).
15
Table 3
FREQUENCY OF LIES BY TREATMENT
Strangers
N=76
Friends
N=68
Never
Once
Twice
11
14.5%
27
39.7%
15
19.7%
12
17.6%
23
30.3%
9
13.2%
Three
times
25
32.9%
20
29.4%
Always
2
2.6%
0
0%
The dispersion in the frequency distribution of the number of lies shows that
individuals are heterogeneous. In one extreme, those with a low cost of lying, lie
whenever the true outcome differs from their first ranked preference. At the other
extreme, moral individuals with a high cost of lying, never lie. In between, there are
those individuals whose gains from lying increase if the true outcome is distanced
further from their preferred choice. The data appears to support this contention.
The correlation between ranking preferences, and the frequency of lies, is high for
those who lie once or twice (the intermediate liars; see Table C1, Appendix C).
Next, we investigate the relationship between lying aversion and social
preferences. First, in order to consider social preferences, we classify subjects
according to their first ranked choice in the ranking game.19 We expect the following.
If individuals are selfish, or they attribute a low weight to others’ payoffs, they
would rank C (30, 15) as their first choice; alternatively, if individuals are sufficiently
inequity averse, and/or care about total surplus, they would rank D (25, 25) as their
first choice. Pure altruistic individuals would choose B (15,30) as their preferred
allocation.
Table 4 presents the proportion of subjects who chose a particular allocation
as their most preferred option in the ranking game. In the strangers treatment,
there are 47% subjects that prefer the selfish allocation C and 43% that prefer the
fair allocation D. The percentage of subjects that prefer the allocation D in the
friends treatment is higher and equals 78% and relatively few subjects show selfish
preferences towards a friend (6%). Also, to analyze lying aversion, we present, for
19
In Appendix A we present the full ranking predictions for inequity aversion preferences (Fehr
and Schmidt, 1999) and Quasi-maximin preferences (Charness and Rabin, 2002). Table C3
in Appendix C presents the distribution of allocations’ choice by ranking preference.
16
each group of subjects, the proportion of lies told in relation to the number of lies
that subjects would have told if they had lied whenever they had an incentive for
doing so, i.e., three times. Independently of any social type, the proportion of lies
is lower than 1, and smaller in the friends treatment, as compared to the 𝑠𝑡𝑟𝑎𝑛𝑔𝑒𝑟𝑠
treatment. Moreover, fair-minded subjects appear to lie less than the selfish types.
We explore this finding further in Section 6.2 when considering a within-subject
experimental design.
Table 4
PROPORTION OF SUBJECTS AND LIES (IN RELATION TO THE INCENTIVE
COMPATIBLE LIES) BY SUBJECTS’ MOST PREFERRED OPTION
Strangers
Friends
Subjects (N=76)
Lies∗ (𝑁 = 144)
Subjects (N=68)
Lies∗ (𝑁 = 90)
A
(20,20)
0.039 (3)
0.33 (3)
0.132 (9)
0.22 (6)
B
(15,30)
0.053 (4)
0.83 (10)
0.029 (2)
0.33 (2)
C
(30,15)
0.474 (36)
0.67 (70)
0.059 (4)
0.58 (7)
D
(25,25)
0.434 (33)
0.59 (59)
0.779 (53)
0.47 (75)
* The proportion of lies is computed with respect to the number of lies that would have
been told if subjects would have lied three times. Lies proportions can be compared to 1.
5.2
The pattern of lies
To understand individuals’ motivations for lying we investigate their pattern of lies.
In particular, we examine the messages sent by those who lied.Table 5 provides the
results. As compared to strangers, friends are more likely to lie for a fair outcome
while they are less likely to lie for their own gains if they come at the cost of their
friends’ loses. In particular, a significantly higher proportion (44%) of lies in the
strangers treatment involve switching to message C, the selfish allocation (30, 15).
A significantly smaller fraction (7%) of lies involve switching to the same message in
the friends treatment (one-sided Binomial test, < 0.001). In contrast to this finding,
we show that there are 80% of lies in the friends treatment that implement the fair
allocation (25, 25) – a percentage that is significantly higher than the 44% observed
in the strangers treatment (one-sided Binomial test, 𝑝 < 0.001).
17
Table 5
UNCONDITIONAL MESSAGES SENT BY LIARS
Strangers
Number
A
of lies
(20,20)
144
7 (4.9%)
B
(15,30)
10 (6.9%)
C
(30,15)
63 (43.8%)
D
(25,25)
64 (44.4%)
Friends
90
5 (2.6%)
6 (6.7%)
72 (80.0%)
7 (7.7%)
In order to further investigate the pattern of lies observed in our experiment,
we adopt the Erat and Gneezy (2009) approach and classify lies according to the
gains and losses for both the sender and receiver that results, within our experiment,
in the sender choosing an allocation that is different from the truthful one. Recall
that in our sender-receiver game we have four possible true states and four possible
final allocations. As such, we may have one type of lie associated with a certain
level of gains and losses resulting from different combinations of true outcome and
the corresponding message sent. For example, a lie that results in a loss of 5 for the
sender and a gain of 10 to the receiver can result, within our experimental design,
in a truth state of A, (20, 20), and an actual message sent equal to B, (15, 30), as
well as from a true state equal to C, (30, 15), when the actual message sent happens
to be equal to D (25, 25). Given this, we classify lies not only according to gains
and losses but also according to the fairness of the final outcome given the true
allocation. Specifically, a fair (unfair) lie moves a sender and receiver from a state
of unequal (equal) outcome to a state of equal (unequal) outcome for both. Table 6
presents the fraction of lies per type of lie for both treatments.20
The pattern of lies told by subjects is significantly different between treatments
(𝜒2 test, 𝑝 < 0.001). For instance, there is a significantly lower proportion of
altruistic lies in the strangers treatment as compared to the friends treatment (20%
vs. 29%, 𝑧 = −1.320, 𝑝 = 0.094). More specifically, individuals are willing to forgo 5
experimental units in order to increase the others payoffs by 10 experimental units.
This implies that individuals do care about the others’ payoffs and that they are
willing to lie when lying implements a relatively equal allocation.
20
In the Appendix C, Table C2 shows the proportions of messages sent by true state and
treatment. The diagonal shows the proportion of subjects that told the truth for each true state.
18
When the true allocation is A, (20, 20), individuals can tell a Pareto white lie
by sending message D, (25, 25), yielding each participant 5 extra experimental units.
In the strangers treatment, 25% of the lies resulted in a Pareto improvement, while
this percentage equals to 34% in the friends treatment (𝑧 = 1.1630, 𝑝 = 0.122).21
A larger proportion of lies told in both the strangers and friends treatments
was of the selfish kind since they increase the sender’s payoff at the expense of
the receiver’s. The proportion of selfish lies was 44% in the friends treatment,
which is significantly smaller than the 67% in the corresponding strangers treatment
(𝑧 = 2.6128, 𝑝 = 0.005). However, not all of the selfish lies should be considered
equally selfish and the fairness of the final allocation should also be considered. From
all selfish lies in the strangers treatment, 45% implemented an unequal allocation
that favored the sender while only 22% implemented a fair allocation. In the friends
treatment, however, only 7% of the selfish lies could be considered unfair, while 38%
implemented an equal allocation.
Table 6
PROPORTION OF LIES PER TYPE OF LIE BY TREATMENT
Altruistic
lie
Selfish
lie
Fairness
of outcome
Gains/Losses True
[sender,receiver] allocation
Final
allocation
unfair
fair
unfair
fair
fair
unfair
fair
unfair
fair
fair
[-5,10]
B(15,30)
D(25,25)
B(15,30)
A(20,20)
B(15,30)
C(30,15)
A(20,20)
C(30,15)
D(25,25)
C(30,15)
D(25,25)
A(20,20)
Pareto white lie
Spite black lie
A(20,20)
C(30,15)
D(25,25)
C(30,15)
C(30,15)
D(25,25)
B(15,30)
A(20,20)
B(15,30)
B(15,30)
A(20,20)
D(25,25)
[-10,5]
[-15,15]
[5,-10]
[10,-5]
[15,-15]
[5,5]
[-5,-5]
Strangers
Robust
(144 lies)
0.7%
11.8%
1.4%
0.7%
4.9%
13.9%
3.5%
14.6%
18.8%
16.0%
13.2%
0.7%
Friends
Robust
(90 lies)
3.3%
21.1%
1.1%
2.2%
1.1%
0.0%
4.4%
4.4%
33.3%
2.2%
25.6%
1.1%
Next, we investigate whether different lies can be explained by the differences
in social preferences. Figure 2 shows the proportion of subjects that are classified
as selfish, inequity averse, and altruistic, according to their ranking preferences.
21
See Table C1 in Appendix C).
19
Figure 2 also presents the proportion of subjects who tell the truth for allocations
C, D, and B, the average proportion of subjects who tell a lie in order to implement
allocations C, D, and B22 , and the proportion of subjects who never lie.
Figure 2
PROPORTION OF LIES BY TREATMENT
100
90
% of subjects
80
70
60
50
40
30
Strangers
20
Friends
10
0
As stated before (see Table 4), there are more selfish types in the strangers
treatment and more inequity averse subjects in the friends treatment. Therefore, a
part of the truth-telling behavior is explained by social preferences. However, more
people appear to stick to the truth relative to those who have an incentive to do so.
We highlight two additional observations. First, there are very few subjects who rank
B as their first choice but, by the same token, a considerable fraction of subjects also
do not lie when B happens to be the true allocation (28% and 47% in the strangers
and friends treatments, respectively (𝑧 = −2.422, 𝑝 = 0.008). Discounting those
who never lie (15% and 40% in the strangers and friends treatments), it remains
that 13% of the subjects in the strangers treatment, and 7% of the subjects in the
friends treatment who could have lied chose to not do so. Therefore, there are
subjects who do not lie if this lie happens to reduce the other person’s payoff.
A second interesting finding relates to those who choose to stay with the truth
when it equals C. Subjects seemed to prefer fair allocations when they played with a
friend. However, a majority also did not lie when the unfair allocation, C, happened
22
In case of a lie, for each allocation, C, D, and B, we average the number of subjects that lie
for each of the other three possible allocations.
20
to be the true allocation. For a majority, the duty of not lying seems to be more
important than their perceived duty for being fair. Additionally, there appear to
be no significant differences between treatments. When the true outcome was C,
(30, 15), there was no significant difference between strangers telling the truth and
friends telling the truth (67% vs. 68%, 𝑧 = −0.064,𝑝 = 0.475). However, there
was a significant difference between strangers having an incentive to tell a lie and
friends having an incentive to tell a lie (49% vs. 91%, 𝑧 = −5.494, 𝑝 < 0.001. See
Table C4 in Appendix C). Thus, the truth-telling behavior with respect to C is
easily understandable in the strangers treatment. Subjects tell the truth because
it is incentive compatible and the remaining subjects are basically those who never
lie. That is, however, not the case for friends. Only 9% of subjects in the friends
treatment ranked C as their first option but 68% also did not lie when C was the
truth. Excluding those who never lied, there are still approximately 30% of subjects
who chose to tell the truth when they could have, in fact, lied. By examining
Table C1 in Appendix C we see that when A or D is the true outcome, the proportion
of subjects who chose to tell the truth in the friends treatment is explained by those
that have an incentive to not lie plus those who never lie. This truth-telling behavior
with respect to the true state C is, therefore, surprising.23
6
Robustness
We find significant differences between the friends and the strangers treatments
regarding subjects’ truth-telling and lying behavior. We believe that such differences
are attributable to the fact that individuals may feel different moral obligations
towards friends relative to strangers.24 However, we may question whether subjects
in both the strangers and the friends treatments are representative of the same
population. For example, it may be argued that subjects coming with a friend
to the experiment may be intrinsically more sociable than those coming alone to
the experiment. Put differently, is there a selection bias with those who come
23
It is possible that subjects could be embarrassed about looking selfish by revealing that they
prefer an unfair allocation. Therefore, while they do not explicitly lie to implement it, they are
also not willing to deviate from the truth in order to get it. In other words, lying is used as a cover
to justify, and obtain, a better outcome.
24
However, as stated earlier, we cannot exclude that individuals playing with friends could bring
inside the lab and to the one shot-game the reputation concerns they care about outside the lab.
21
with a friend relative to those who do not? To address this issue, we implemented
additional sessions in which subjects were recruited to come along with a friend but
participated sequentially in the strangers and friends treatments. More specifically,
at the beginning of the experiment, each subject was randomly and anonymously
paired with another subject who was not his/her friend and played both the ranking
and the modified sender-receiver game as described in Section 2. Once the strangers
treatment ended, however, in a surprising move, subjects were informed that they
were going to play both the ranking and the sender-receiver game again, but this
time with their respective friends. We refer to the additional within-subject strangers
and friends treatments as strangers robust and friends robust, respectively. For
these additional treatments, we conducted four extra sessions, with 78 participants
in total. Like in the strangers and friends treatments, participation was restricted
to one session and we ensured that these subjects had not participated in any of the
previous sessions.
The plan for this section is as follows. First, we investigate whether sample
selection explains our results. After that, we use the within-subject nature of
our robust treatments to further explore individual lying behavior with respect to
friendship.
6.1
Sample selection bias
The percentage of lies in the strangers robust (friends robust) treatment equals
46% (34%). A one-sided binomial test on the equality of proportions shows no
statistically significant difference at the 1% level between this proportion and the one
found in the earlier strangers (friends) treatment. We conclude similarly when we
incorporate the data from the strangers robust treatment into the regression Model
I of Table 2. In results presented in Table 7 (Model I), the regression intercept for
the strangers robust treatment is seen to be insignificant. Moreover, using the data
from the strangers robust treatment, instead of the strangers treatment, we get a
statistically significant coefficient for the friends dummy equal to −0.42. Hence, the
difference in the proportion of lies between the strangers and friends treatments is of
the same magnitude as the difference in the proportions of the strangers robust and
22
the friends treatments (see Model II, Table 7)25 . Model III presents the estimates
for the pooled data of the strangers robust and the strangers treatments.
Table 7
RANDOM EFFECTS PROBIT REGRESSION WITH LYING AS DEPENDENT VARIABLE
constant
friends
strangers robust
Model I
Coef.
−0.079
−0.438∗∗∗
−0.036
(N=888)
Std. Err.
0.098
0.147
0.139
Model II
Coef.
−0.123
−0.421∗∗∗
−
(N=584)
Std. Err.
0.107
0.160
−
Model III
Coef.
−0.098
−0.420∗∗∗
−
(N=888)
Std. Err.
0.069
0.130
−
*** Indicates significance at the 1%-level.* Indicates significance at the 10%-level. Also note
that the constant term proxies for strangers in the regressions. There are 𝑁 = 888 observations
in total, with 222 individuals and 4 observations per individual in Model I and III, 𝑁 = 584
observations in total, with 144 individuals and 4 observations per individual in Model II. The
Wald statistic equals 𝜒2 = 10.57, 𝑝 = 0.005 in Model I, 𝜒2 = 76.28, 𝑝 = 0.000 in Model II, and
𝜒2 = 10.51, 𝑝 = 0.001 in Model III.
Not only is the proportion of lies similar in both the strangers and the strangers
robust treatments, but also the frequency of lies in both treatments follows the same
pattern. Table 8 reports the frequency of lies for both the strangers robust and the
friends robust treatments. Compared to the results for the strangers treatment
in Table 3, a chi-square test of the equality of distributions shows no statistical
significance (𝑝 = 0.49). Concerning those who never lie, there is a higher proportion
in the strangers robust treatment (19.2%) relative to the proportion observed in
the strangers treatment (14.5%). However, a one-sided binomial test still shows a
statistically significant difference at the 1% level between the proportions of those
who never lie in the strangers robust and the friends treatments.
Table 8
FREQUENCY OF LIES BY TREATMENT
Strangers robust
N=78
Friends robust
N=78
Never
Once
Twice
15
19.2%
32
41.0%
11
14.1%
11
14.1%
26
33.3%
10
12.8%
25
Three
times
23
29.5%
24
30.8%
Always
3
3.8%
1
1.3%
We do not consider the data from the friends robust treatment in the regressions because
observations are not indepedendent from the strangers robust treatment
23
Related to the pattern of lies, we find a similar pattern in both the strangers
robust (see Table C5 in Appendix C) and the strangers treatments (see Table 4).
A chi-square test reveals no statistical significance (𝑝 = 0.27). More specifically,
comparing the messages sent in both the strangers and the strangers robust
treatments, we see that the proportion of messages that implement an equal
allocation, i.e., messages A and D, are relatively the same. There is a smaller
(higher) proportion of messages that provides a higher (lower) payoff to the sender
relative to the receiver in the strangers robust treatment. However, compared to
the proportion of liars for each possible message in both the strangers robust and
the friends treatments, we get the same results as before (see table 3) [i.e., they
are statistically similar as revealed by a one-sided binomial test]. We reach the
same conclusion when we consider the type of lies according to our classification.
Comparing tables 6 and C6 in Appendix C, we see no significant differences between
the distribution of lies between the strangers and the strangers robust treatments
(𝜒2 test, 𝑝 = 0.78), but a significant difference between the friends and the strangers
robust treatments (𝜒2 test, 𝑝 < 0.001). In sum, we do not see any evidence of sample
selection bias with our robustness checks.
6.2
Individual lying behavior and friendship
In this section, we explore individual lying behavior and friendship in more detail by
comparing the within-subject behavior in the strangers robust and friends robust
treatments. We generally classify subjects into two types based on the effect of
friendship on subjects’ lying/truth-telling behavior: those whose behavior remains
the same regardless of who they are playing with (the constant types) and the
switchers who change their behavior as a function of who they are playing with
(friends versus strangers). As seen in Figure 3, 26% of individuals choose to lie to
a stranger while always telling the truth to a friend. This result is consistent with
some individuals having an intermediate cost of lying that increases if they interact
with a friend instead of a stranger. A majority of subjects, however, seem to behave
similarly towards a friend or a stranger regarding their truth-telling behavior. For
24
instance, there are 15% of the subjects who never lie to either a stranger or a friend.26
By the same token, 55% of individuals lie to both a stranger and a friend. Notice
that this group includes those subjects who have a sufficiently low cost of lying when
interacting with friends as well as the economic types for whom it is irrelevant who
they lie to.
Figure 3
CLASSIFICATION OF SUBJECTS ACCORDING TO WHOM THEY TELL A LIE/TRUTH
3.8%
15.4%
constant truth-teller
25.6%
constant liar
lie to a stranger but not to
a friend
lie to a friend but not to a
stranger
55.2%
We see above that while a majority of subjects lie to both a friend and a
stranger, it is the frequency, and the pattern of lying, that are affected by friendship
ties. In Figure 4, we strengthen those findings by presenting the proportion of
subjects grouped by the number of lies told to both a stranger and a friend. The
diagonal represents the subjects who told exactly the same number of lies to both
a stranger and a friend.
From the figure we see that 36% (15% + 21%) of the subjects tell exactly
zero or three lies in both treatments. However, the majority of subjects tell a
different proportion of lies to a stranger relative to a friend. For instance, 40% lie
more frequently to a stranger and 12% lie more frequently to a friend. (Table C7
in Appendix C shows the exact proportions of subjects for each possible combination
of lies told to both a stranger and a friend).
26
At first blush, it appears that these constant truth-tellers may have a high cost of lying.
However, further thinking reveals that this group contains both those who have a high cost of
lying when interacting with friends and those whose moral concerns are independent of who they
are interacting with.
25
Figure 4
PROPORTION OF SUBJECTS RELATIVE TO THE NUMBER OF LIES TOLD TO BOTH A
STRANGER AND A FRIEND
Number of lies
told (friend)
4
0.01
0.12
3
0.21
2
0.08
0.4
1
0.04
0.15
1
2
3
4
Number of lies told (stranger)
The proportion of lies told to a stranger and a friend differs because the gains
from lying may differ for strangers and friends and/or the costs from lying may
depend on social ties. Figure 5 allows us to examine subjects’ lying behavior towards
a stranger and a friend while keeping the benefits of lying relatively similar.27
Specifically, on the y-axis we depict the most preferred allocation in the friends
robust treatment and, on the x-axis, the most preferred allocation in the strangers
robust treatment. And each dot on the diagonal represents the combination of
subjects’ first preferred allocation in the strangers robust and the friends robust
treatments. For each dot, we show: 1) the percentage of subjects who have that
particular combination of first preferred payoff allocations; 2) the actual number of
lies, as a fraction of the number of incentive compatible lies, subjects would have told
to strangers; 3) the actual number of lies, as a fraction of the number of incentive
compatible lies, subjects would have told to friends.28 For instance, consider the
27
Even though some subjects have similar preferences for friend and strangers the utility function
may still differ. For example, a subject may have selfish preferences towards a stranger and inequity
aversion preferences of Fehr and Schmidt type with a small 𝛽, implying that C is the most preferred
allocation for both a stranger and a friend, but the gains from choosing C will be smaller for a
friend than for a stranger (see function B1, Appendix B).
28
Recall that incentive compatible lying implies that subjects implement their preferred
allocation regardless of their social preference. Additionally, note that in the case of subjects
lying always, this fraction would be greater than 1. However, in our experiment, this case occurred
only once.
26
diagonal that highlights the proportion of subjects who have a similar incentive to
lie to a stranger and a friend (in addition to the proportion of lies told to both a
stranger and a friend). The cost of lying appears to be higher with friends than
strangers. For those subjects who prefer the allocation D (25, 25), the proportion of
incentive compatible lies is 0.52 and 0.42 with a stranger and friend, respectively.
Similarly, for those who prefer allocation C (30, 15), the proportion of incentive
compatible lies is 0.80 for strangers and 0.47 for friends.
Figure 5
PROPORTION OF SUBJECTS, PROPORTION OF LIES TOLD TO A STRANGER, AND
PROPORTION OF LIES TOLD TO A FRIEND BY SUBJECTS’ PREFERRED
ALLOCATION IN BOTH TREATMENTS
most preferred
D
allocation
(friend robust)
(0.038, 0.33, 0.11) (0.013, 1, 1) (0.269, 0.65, 0.49)
(0.474, 0.52, 0.42)
(0.013, 1.33, 0.67)
C
(0.013, 1, 1)
(0.128, 0.8, 0.47)
B
(0.013, 0, 0)
(0.013, 0.67, 0)
A
(0.026, 1, 1)
A
B
C
D most preferred allocation
(stranger robust)
Figure 5 also reveals a relationship between social preferences and deceptive
behavior. In particular, when subjects interact with a stranger, their costs of lying
seem to increase with their other-regarding preferences. More precisely, the costs are
low if subjects are selfish with both strangers and friends (i.e., they prefer allocation
C in both treatments). By the same token, the costs are higher if subjects are
pro-social towards friends and selfish towards strangers (i.e., they prefer D when
interacting with a friend and C when interacting with a stranger). Finally, costs
are at their highest when subjects are pro-social towards both friends and strangers
(i.e., they prefer D in both treatments). The proportion of incentive compatible
lies told to a stranger for the three pro-social types referred to above is 0.8, 0.65,
and 0.52, respectively. Nevertheless, the deceptive behavior displayed by subjects
27
when interacting with a friend appears to be independent of individuals’ social
preferences. The proportion of incentive compatible lies told to a friend for the three
pro-social types referred to above is 0.47, 0.49, and 0.42, respectively. Therefore, it
is interesting to note that the deceptive behavior of selfish individuals mimics those
with outcome-oriented social preferences only when subjects play with their friends
(0.47 is not statistical significant different from 0.52).
The individual pattern of lies also differs across subjects types- those who lie
only to strangers, only to friends, and those who lie both to strangers and to friends.
First, we examine the messages sent by those who lied. Table 9 provides the results
by comparing the messages sent by the “two switcher types” and the unconditional
liars.
Table 9
UNCONDITIONAL MESSAGES SENT BY LIARS
N.
of lies
Switch behavior
Constant liars
Lie only to
a stranger
Lie only to
a friend
strangers
robust
friends robust
A
(20,20)
B
(15,30)
C
(30,15)
D
(25,25)
36
2 (5.6%)
7 (19.4%)
9 (25.0%)
18 (50%)
7
0 (7.7%)
0 (2.6%)
0 (6.7%)
7 (80.0%)
108
5 (4.6%)
8 (7.4%)
44 (40.7%)
51 (47.2%)
100
7 (7.0%)
8 (8.0%)
21 (21.0%)
64 (64.0%)
From the table, we see that those who lied only to a friend did so in order
to implement the fair and more efficient allocation D (25, 25). For those who lied
only to strangers, 50% and 25% of their lies involved switching to allocation D and
C respectively. Among the unconditional liars, the majority of their lies involved
switching either to allocation C or D. The distribution of these two types of lies is
fairly similar in those cases where subjects interacted with strangers. However, the
majority of lies implied switching to allocation D in case subjects interacted with a
friend. Further, consider the fraction of lies (per type of lie) told by subjects to a
stranger and/or to a friend (see Table C6, Appendix C). A chi-square test of the
equality of distributions shows significant difference at the 1% level. Specifically,
our results show that there is a significantly lower proportion (12%) of altruistic
28
fair liars when subjects play with a stranger as compared to 22% (𝑝 < 0.001) when
playing with a friend. Overall, subjects also tell more selfish lies to strangers than
to friends (60% vs. 45%, 𝑝 = 0.007). In particular they tell more selfish and unfair
lies (defined earlier) to a stranger (24%) relative to a friend (8%). Subjects also tell
more Pareto improving white lies to friends than to strangers (23% vs. 17%). A
one-sided binomial test shows that of all the above differences in proportions are
significant at the 5% level.
7
Conclusion
In this study, we use a modified sender-receiver game - the message game - to
investigate the interaction between social ties and deceptive behavior and, in
particular, how social ties influence lying behavior. To do so, we compare a
treatment where each subject plays with another anonymous player, with a second
treatment where subjects play with a friend. Additionally, we extend the existing
structure of the message game by recording subjects’ messages corresponding to
each potential true state. This allows us to investigate the frequency of lying and
to draw inferences about the existence of different degrees of lying aversion. Third,
in our experimental design, subjects are allowed to choose among different types
of lies, which allow us the flexibility of studying different patterns of lies told to
both friends and strangers. We are also able to explore the relationship between
lying aversion, the type of lies told, and subjects’ social preferences. This is possible
within our design by comparing the subjects’ revealed choices in the message game
with choices made in the ranking game, in which they are required to rank, in an
incentivized way, four sets of payoffs both for themselves and the player they happen
to be matched with.
Our results suggest that individuals care not only about outcomes but also
appear to display procedural/moral preferences. In particular, individuals do not lie
merely for the sake of lying. Their moral concerns, and the respective truth-telling
behavior, are conditional on who they happen to be interacting with. A friendship
tie seems to increase the moral cost of lying and strengthen individuals’ preferences
for telling the truth. Our findings also confirm the existence of heterogeneity
in individuals’ other-regarding preferences in that we find a positive relationship
between social ties and social preferences. More pro-social individuals are less likely
29
to lie. Regardless of whom they interact with, a similar result obtains even if they
are non pro social but happen to be playing with friends. Friendship also influences
the type of lies individuals choose to tell. When choosing to lie, individuals not only
take into account the personal benefits he/she will get from lying but also weigh the
costs imposed on the other person he/she happens to be paired with. In particular,
he/she takes into consideration the overall fairness of the final outcome. Individuals
tell more selfish unfair lies to strangers and more selfish fair lies to friends. Also,
individuals choose to tell more altruistic lies to friends relative to strangers. To
ensure that our findings are not driven by any inherent sample selection bias, we
conduct additional robustness sessions were subjects were required to bring a friend
but played, both the ranking and message games, first with an anonymous player and
then with the friend they brought along. These results show that sample selection
is not an issue and actually serve to strengthen our findings and the resultant
conclusions.
An implication of our findings is as follows. As is well accepted, information
transmission is crucial for the well functioning of decentralized markets and
hierarchical corporate entities, such as firms. The existence of private information
and the incentive for individuals to lie or to hide the truth in their own interest,
often imply the use of mechanisms that make the truth incentive compatible and
agents’ incentives aligned. For example, relatively low tax rates, combined with
high penalties if caught, serve to reduce individuals’desires to cheat on their taxes
and create an equilibrium of truthful declaration of income/profits. However, such
an equilibrium has inherent disadvantages as well - like the collection of lower tax
revenues. The same holds, for instance, in an employer-worker setting, where the
employer must infer the worker’s unobservable actions from observing the division’s
profits. Merely, asking the worker about his effort is considered to be cheap talk,
adds no informational value to the employer’s performance appraisal, and calls,
for instance, for an appropriate incentive-lader payment. Our findings underscore
the fact that if workers have an intrinsic cost for lying, setting up of a feedback
”cheap” talk network could serve to design more efficient incentive compatible
contract mechanisms. Moreover, our results suggest that while hiring pro-social
workers might serve to provide a positive role in increasing truth-telling behavior
among the work force, establishing both formal and informal mechanisms to foster
the cultivation of closer bonds among workers might help even more.
30
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33
Appendix A
Summary of instructions(Friends treatment)
Thank you for participating in this experiment. During the experiment your earnings will
be calculated in points. At the end of the experiment these points will be converted into
dollars at the rate of: 1 point = 0.3 dollars. At the end of the experiment your overall
earnings will be exchanged into dollars, and you will be paid individually and privately in
cash. You are not allowed to do anything else not related to the experiment. Please do
not talk with anyone else.
You will be matched with your friend who comes along with you. You are
going to play two independent parts. In each part, you are going to make decisions that
determine your and your friend’s earnings. More specifically, first you will get instructions
for part 1 followed by three quiz questions to check your understanding of the instructions
and then you make your decisions for part 1. Quiz questions do not affect your payment.
Second, you will get instructions for part 2 followed by three quiz questions and then you
will make your decisions for part 2. After you make decisions for both part 1 and part
2, for each pair, one player will be randomly selected to be a sender and the other to be
a receiver. Everyone may be selected to be a sender (receiver) with 50% chance. The
sender’s decisions for both part 1 and part 2 will be implemented. In particular, if you are
the one selected to be a sender, your earnings and your friend’s earnings are determined
by your decisions; if you are selected to be a receiver, your earnings and your friend’s
earnings are determined by your friend’s decisions. Please note that all information that
you receive from us is for your private use. Again, you are not allowed to communicate
with other participants during the experiment. If you have a question, please raise your
hand and one of the experimenters will come to you to answer your question.
INSTRUCTIONS TO PART 1
You will observe four possible payoff options for you and your friend you are matched
with. In particular, you will observe the following table:
Option
A
B
C
D
Your earnings (points)
20
15
30
25
Your friend’s earnings (points)
20
30
15
25
You will be asked to fill in the following:
My
My
My
My
FIRST preferred option is: (50% chance of being implemented)
SECOND preferred option is: (25% chance of being implemented)
THIRD preferred option is: (15% chance of being implemented)
FOURTH preferred option is: (10% chance of being implemented)
Your friend you are matched with will NOT observe your ranking options. (You will
34
NOT observe your friend’s choices as well). At the end of the experiment everyone
will have 50% chance of being selected as a sender. If you are selected to be a sender,
the earnings for you and your friend in part 1 are determined by your decisions in
the following way: there will be a 50% chance that you (and your friend) will be paid
according to your first ranked option; 25% chance that you (and your friend) will be
paid according to your second ranked option; 15% chance that you (and your friend)
will be paid according to your third ranked option; 10% chance that you (and your
friend) will be paid according to your fourth ranked option. In particular, at the end
of the experiment, we are going to roll dice to determine the option to be implemented
in front of you. The result of dice roll could be any integer number 1 to 100, such as
1, 2, 3, 4, ...100. If the result of dice roll is lower than or equal to 50, your first option
will be implemented. If dice roll turns out to be higher than 50 but lower than or equal
to 75, your second preferred option will be implemented; if the number of dice roll is
higher than 75 but lower than or equal to 90, your third preferred option will be implemented; if the number is higher than 90, your fourth preferred option will be implemented.
INSTRUCTIONS TO PART 2
PART 2 is independent and not related to PART 1. In part 2 you will observe again
the four possible payoff options for you and your friend you are matched with. For each
person the computer will generate a roll of a 4-sided dice with alphabets A, B, C, and D
on each side, which denotes the option A, B, C, or D, respectively. You have to inform
your friend about the outcome of rolling the dice. You can either tell the truth or lie as
you like. Your friend will NOT know whether you are telling the truth or lying. More
specifically, you are requested to make a choice for each of four possible dice rolling
outcome the computer may generate. For example, you will get a statement like this :
“Suppose that the true outcome of rolling the dice is B”
Please choose the information you want to send to your friend:
“The
“The
“The
“The
true
true
true
true
outcome
outcome
outcome
outcome
of
of
of
of
rolling
rolling
rolling
rolling
the
the
the
the
dice
dice
dice
dice
is
is
is
is
B” (tell
A” (tell
C” (tell
D” (tell
the truth)
a lie)
a lie)
a lie)
There are four possible outcomes for the dice, so you will get four statements and
you have to make four possible choices without knowing the real outcome of the dice.
After your choices are made the real outcome of rolling the dice will be revealed only to you.
The choice you made for that specific dice outcome will determine the earnings for you
and your friend in case you are selected to be a sender. In case you are selected to be
a receiver the choice made by your friend will determine your earnings and your friend’s
earnings in part 2.
35
Appendix B
Formal analysis for behavioral predictions
for Ranking Condition
In this Appendix we present a formal analysis of behavioral predictions for ranking choice
condition assuming different models. First, consider players have outcome-oriented social
preferences and are motivated by inequality aversion as in ?. For a two-player game the
utility function equals:
{
(1 + 𝛼𝑖 )𝑚𝑖 − 𝛼𝑖 )𝑚𝑗 if 𝑚𝑖 ≤ 𝑚𝑗
𝑈𝑖 (𝑚) =
(B1)
(1 − 𝛽𝑖 )𝑚𝑖 + 𝛽𝑖 𝑚𝑗
if 𝑚𝑖 > 𝑚𝑗
where parameter 𝛼𝑖 measures the extent player 𝑖 dislikes disadvantageous inequality and
𝛽𝑖 measures the extent player 𝑖 dislikes advantageous inequality. The parameters follow
the restrictions 𝛼𝑖 ≥ 𝛽𝑖 1 and 0 ≤ 𝛼𝑖 < 1.
First, recall the four allocations considered: A(20,20); B(15,30), C(30,15), and
D,(25,25). Allocations B and C give the same inequality between players. Given that
player i dislikes more being behind than being ahead allocation B is at least equally
preferred to allocation C. Allocation A and D give the same inequality as well but allocation
D has a higher total endowment. As such, allocation D is strictly preferred to allocation
A. Therefore, the value of 𝛽𝑖 is decisive for ranking allocations A, C, and D. In case of
Fehr and Schmidt preferences, Player 𝑖 ranks the four allocations in the following way29
⎧

⎨𝐶 ≻ 𝐷 ≻ 𝐴 ≻ 𝐵 if 0 ≤ 𝛽𝑖 < 1/3
𝐹𝑆
𝑅𝑎𝑛𝑘𝑖 = 𝐷 ≻ 𝐶 ≻ 𝐴 ≻ 𝐵 if 1/3 ≤ 𝛽𝑖 < 2/3
(B2)

⎩
𝐷 ≻ 𝐴 ≻ 𝐶 ≻ 𝐵 if 𝛽𝑖 ≥ 2/3
Next assume that individuals have quasi-maximin preferences like in Charness and Rabin
(2002). Consider the homogenous and reciprocity-free version of their model. The utility
function for player 𝑖 is given by:
𝑈𝑖 (𝑚) = (1 − 𝜆)𝑚𝑖 + 𝜆[𝛿𝑚𝑖𝑛{𝑚𝑖 , 𝑚𝑗 } + (1 − 𝛿)(𝑚𝑖 + 𝑚𝑗 )]
(B3)
The parameter 𝜆 ∈ [0, 1] measures the extent player 𝑖 cares about social surplus
versus his own monetary payoff. Parameter 𝛿 ∈ [0, 1] gives the concern for the well-being
of the worst-ff player versus the concern for efficiency.
Allocation D is always preferred to allocation A. Allocation C is always preferred to
allocation B unless player i does not care about his own monetary payoff, i.e., 𝜆 = 1.
Allocation C and D are necessarily the two preferred allocations and allocations A
and B are the two least preferred allocations. In particular the possible rankings and
29
The same prediction can be derived with the Bolton and Ockenfels (2000) specification for
inequity aversion.
36
corresponding conditions are:
⎧

𝐶≻𝐷≻𝐴≻𝐵



⎨𝐷 ≻ 𝐶 ≻ 𝐴 ≻ 𝐵
𝑅𝑎𝑛𝑘𝑖𝐹 𝑆 =

𝐷≻𝐶≻𝐵≻𝐴



⎩𝐷 ≻ 𝐴 ≻ 𝐶 ≻ 𝐵
if
if
if
if
0 ≤ 𝜆 < 1/(𝛿 + 2)
1/(𝛿 + 2) ≤ 𝜆 < 2/(1 + 2𝛿) and 𝜆 < 1/(2 − 2𝛿)
(B4)
1/(1 − 2𝛿) ≤ 𝜆 < 1/(2 − 2𝛿) and 𝛿 ≤ 1/2
𝛿 > 2/(1 + 2𝛿) and 𝛿 < 1/(2 − 2𝛿) and 𝛿 ≥ 1/2
For outcome-oriented social preferences models like ? and Charness and Rabin (2002) it
is irrelevant if a player is dividing money with a stranger or a friend. Therefore, these
models do not give different predictions for strangers and friends treatments.
Appendix C
Tables
Table C1
PROPORTION OF LIES BY ALLOCATION RANK PREFERENCE
N
Strangers
76
Friends
68
N
Strangers
21
Friends
28
Rank 1
Rank 2
Rank 3
18
32
42
23.7%
42.1%
55.3%
5
25
31
7.4%
36.8%
45.6%
Subjects that lie once or twice
Rank 1
Rank 2
Rank 3
3
7
11
14.3%
33.3%
52.4%
2
6
14
7.1%
21.4%
50.0%
Rank 4
52
68.4%
29
42.6%
Rank 4
9
42.9%
26
92.9%
Table C2
MESSAGE SENT BY TRUE STATE AND TREATMENT
Truth
A(20,20)
B(15,30)
A(30,15)
B(25,25)
N
Strangers
Friends
Strangers
Friends
Strangers
Friends
Strangers
Friends
76
68
76
68
76
68
76
68
A
(20,20)
35 (46.1%)
38 (55.9%)
5 (6.6%)
4 (5.9%)
1 (1.3%)
2 (2.9%)
1 (1.3%)
1 (1.5%)
37
B
(15,30)
1 (1.3%)
3 (4.4%)
21 (27.6%)
32 (47.1%)
7 (9.2%)
1 (1.5%)
2 (2.6%)
1 (1.5%)
C
(30,15)
21 (27.6%)
4 (5.9%)
23 (30.3%)
2 (2.9%)
51 (67.1%)
46 (67.6%)
20 (26.3%)
0 (0.0%)
D
(25,25)
19 (25.0%)
23 (33.8%)
27 (35.5%)
30 (44.1%)
17 (22.4%)
19 (27.9%)
53 (69.7%)
66 (97.1%)
Table C3
DISTRIBUTION OF ALLOCATIONS’ CHOICE BY RANKING PREFERENCE
N
1
2
3
4
1
2
3
4
Strangers
N=76
Friends
N=68
A
3
14
55
4
10
19
19
20
B
1
1
7
67
3
11
23
31
C
39
22
13
2
6
28
23
11
D
33
39
1
3
49
10
3
6
Table C4
PROPORTION OF LIES BY MESSAGE AND RANKING INCENTIVE TO LIE
A
(20,20)
41
53.9%
73
96.10%
56.20%
30
44.10%
58
85.30%
51.70%
Lie
Strangers
N=76
Ranking incentive to lie
Lie/Ranking incentive
Lie
Friends
N=68
Ranking incentive to lie
Lie/Ranking incentive
B
(15,30)
55
72.4%
75
98.70%
73.30%
36
38.20%
65
95.60%
40.00%
C
(30,15)
25
32.9%
37
48.70%
67.60%
22
32.40%
62
91.20%
35.50%
D
(25,25)
23
30.3%
43
56.60%
53.50%
2
2.90%
19
27.90%
10.50%
Table C5
UNCONDITIONAL MESSAGES SENT BY LIARS (p-values)
Number
of lies
A
(20,20)
B
(15,30)
C
(30,15)
D
(25,25)
Strangers Robust
144
7 (4.9%)
15 (10.4%)
53 (36.8%)
69 (47.9%)
Friends Robust
107
7 (6.5%)
8 (7.5%)
21 (19.6%)
71 (66.4%)
38
Table C6
PROPORTION OF LIES PER TYPE OF LIE BY TREATMENT
Altruistic
lie
Selfish
lie
Fairness
of outcome
Gains/Losses
True
[sender,receiver] allocation
Final
allocation
unfair
fair
unfair
fair
fair
unfair
fair
unfair
fair
fair
[-5,10]
B(15,30)
D(25,25)
B(15,30)
A(20,20)
B(15,30)
C(30,15)
A(20,20)
C(30,15)
D(25,25)
C(30,15)
D(25,25)
A(20,20)
Pareto white lie
Spite black lie
A(20,20)
C(30,15)
D(25,25)
C(30,15)
C(30,15)
D(25,25)
B(15,30)
A(20,20)
B(15,30)
B(15,30)
A(20,20)
D(25,25)
[-10,5]
[-15,15]
[5,-10]
[10,-5]
[15,-15]
[5,5]
[-5,-5]
Strangers
Robust
(144 lies)
1.4%
11.1%
1.4%
0.7%
7.6%
9.7%
3.5%
13.9%
20.1%
13.2%
16.7%
0.7%
Table C7
PROPORTION OF SUBJECTS ACCORDING TO THE NUMBER OF LIES TOLD
TO BOTH A STRANGER AND A FRIEND
Strangers
Friends
Never
Once
Twice
Three times
Always
Never
Once
Twice
Three times
Always
12(15.4%)
1(1.3%)
0(0.0%)
2(2.6%)
0(0.0%)
7(9.0%)
3(3.8%)
1(1.3%)
0(0.0%)
0(0.0%)
10(12.8%)
5(6.4%)
6(7.7%)
5(6.4%)
0(0.0%)
3(3.8%)
2(2.6%)
2(2.6%)
16(20.5%)
0(0.0%)
0(0.0%)
0(0.0%)
1(1.3%)
1(1.3%)
1(1.3%)
39
Friends
Robust
(107 lies)
3.7%
19.6%
1.9%
2.8%
1.9%
2.8%
1.9%
5.6%
23.4%
11.2%
23.4%
1.9%