The Evolution of Religion:
Mixed Signals Regarding the Costly
Signaling Theory of Religion
Olmo van den Akker (5843049)
March 14, 2014
Bachelor’s Thesis Economics
University of Amsterdam
Supervisor: Boris van Leeuwen
Number of words:
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Abstract
In this study, the costly signaling theory of religion was tested using 135 religious
participants. In accordance with the theory, it was found that participants who scored higher
on a costly signaling questionnaire, also scored higher on self-report items that measure
willingness to cooperate, altruism, received cooperation, and received trust. However, no
positive relationship was found when costly signaling was related to behavioral measures of
willingness to cooperate (cooperation in a prisoner’s dilemma) and altruism (donations in a
dictator game). When taking into account validity and robustness issues of the self-report
measures, it was concluded that there was not enough evidence for an association between
costly signaling and both willingness to cooperate and altruism. Further, these issues make
the positive associations between costly signaling and received trust, and between costly
signaling and received cooperation, only tentative. In all, the evidence for the costly signaling
theory of religion is mixed.
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Introduction
Studies show that presently more than 70% of the world population has some sort of religious
belief (World Values Association, 2009; Maoz & Henderson, 2013). The fact that religiosity
is so abundant is quite puzzling from an evolutionary perspective. This is because practicing
a religion often involves behaviors that can decrease an individual’s reproductive success or
chance of survival. Examples of this are the water and food deprivation during fasting periods,
sexual abstinence, either before marriage or completely, and health risks due to not taking
vaccines. Besides such specific examples there is also the non-trivial investment of time and
energy people make while practicing their religion (e.g. visiting church and saying daily
prayers). This time and energy could also be used in other, more fitness enhancing ways,
making religious activity seem quite wasteful from an evolutionary viewpoint. The fact that
practicing a religion can have adverse effects on an individual’s fitness raises the question
why religiosity is so prevalent after thousands of years of natural selection.
A solution to this evolutionary paradox can be found in the idea that some facets of
religion may entail fitness benefits that can overcome the previously mentioned fitness costs.
William Irons (1996; 2001) is one of the people who endorse this perspective. He proposes
the costly signaling theory of religion, which builds on the idea that religion is a means to
signal cooperative intent to others. In general, the costly signaling mechanism has been
proposed as a way to enhance cooperation and altruism, and can work with all kinds of
signaling devices (Gintis, Smith, & Bowles, 2002). The proposed mechanism functions as
follows. Let us suppose that an individual often makes personal investments in a specific
group setting. Examples of this are the participation in group meetings or the following of
certain group guidelines. Other members of the group can perceive these investments as
signals of loyalty and commitment to the group. These other members will subsequently be
more inclined to trust the signaling individual. On the basis of this trust, they are more likely
to cooperate with, and be helpful to this individual. This is because they trust this individual
to be cooperative and helpful himself. If most group-members signal their commitments in
this way, the group as a whole becomes more cooperative. This can confer an evolutionary
advantage over other groups since all kinds of activities that require effective cooperation can
increase the fitness of individuals. One can think for instance of improved hunting, increased
trade, and most importantly, more effective warfare (Irons, 1996). In short, signaling
cooperative intent can have beneficial effects on an individual’s fitness. Irons proposes that
this signaling can be effectively achieved through religious participation. Moreover, he
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argues that the fitness benefits that come with this religious participation are large enough to
outweigh the previously mentioned fitness costs. The fact that religiosity has these net fitness
benefits can explain why religiosity is so widespread throughout the world.
In developing his argument, Irons (1996) remains vague about why it is that religion
is such an effective means of signaling cooperative intent, and why no other means are
equally or more effective. Other authors did put forward specific arguments to explain this.
Most arguments focus on the importance of religious rituals, because people can signal their
loyalty and commitment to a group through participation in those rituals. Moreover, rituals
are an essential part of religious tradition all over the world. Alcorta and Sosis (2005) argue
that participation in rituals is an especially effective signaling device because most religious
rituals are formal, public, and very salient happenings. The formality, communality and
salience of rituals increase their visibility, and this makes them more effective as a signal.
Besides this, religious rituals are associated with highly emotional experiences. Emotions are
known for their memory enhancing capabilities (Willingham, 2007), which increase the
retention of religious signals even more. Dawkins (1976) emphasizes that religious rituals
often include counterintuitive concepts that violate the basic premises of laws of nature,
examples of which are resurrections, virgin births, and animism. These counterintuitive
concepts can easily grab people’s attention and will therefore be more easily memorized. This
better memorization of course makes for a more effective signal. Henrich (2009) adds to this
by emphasizing that supernatural entities, which play a major role in many religious rituals,
are often difficult to falsify. This means that rituals that include supernatural entities will
probably not be devalued, and therefore will consistently have a large signaling potential. A
final argument comes from Sosis (2003), who states that the multimodal nature of religious
ritual facilitates the transmission of signals. This argument is based on findings that signals
including multiple senses have a higher potential for memorization than signals including
only one sense (Rowe, 1999).
In all, it is plausible that partaking in religious rituals is very effective to signal
cooperative intent. Even though this is the case, the signaling mechanism has its weakness; it
is vulnerable to deception. The reason for this is that in many situations, it is difficult to
decide to what extent other parties actually put effort into a cooperative venture. In a hunting
group, you can never be sure whether someone is actually trying his best to catch a prey or
whether he is slacking to save energy (Hawkes, 1993). Likewise, for firms in a cartel
situation it is often impossible to predict whether the other firm will set their price upon the
collusive level or will set a lower price and take a larger share of the profits (Stigler, 1964). In
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cases like this, it can be tempting to signal to others that you intend to cooperate, but when
push comes to shove actually do not do so. In this way it is possible to reap the benefits from
the cooperative action (e.g. more food or higher profits) because the others believed your
good intentions and cooperated, but you will not incur the cost of putting effort in yourself.
Therefore, in situations where effort levels are not transparent, individuals in potentially
cooperative groups have an incentive to not cooperate and free ride on other people’s
cooperative actions. Whether or not they actually do so depends on many different factors,
among which are personality, the social environment, and the costs of free riding (Albanese,
& Van Fleet, 1985). When free riders exist, the cooperative actions of the other group
members are less fruitful and this can lead to the breakup of cooperation in the group. This
situation is dubbed the problem of collective action (Olson, 1971).
Luckily, the costly signaling mechanism includes a solution to this problem. The
solution is based on the assumption that some people are more committed to a group than
others, and will therefore be more likely to believe in and adhere to the group’s norms. With
regard to the costly signaling theory of religion, Sosis (2003) labels these types of people
‘believers’ and ‘skeptics’ respectively. It can be argued that believers are, in general, less
willing to free ride on the effort of group members. This is because cooperation and altruism
are prevalent norms in many religious groups. So, if the majority of signalers are believers
and not skeptics, there would be less free riding and sustainable cooperation can occur.
However, this situation could only arise if the cost of signaling (i.e. religious participation) is
lower for believers than it is for skeptics. It is reasonable to assume this is the case because
religious participation is intrinsically valuable to those who firmly believe in the norms of a
religious group. For example, people would have little problem with attending church every
day if they firmly believed it would ensure them a place in heaven. People who do not believe
that church attendance will ensure a place in heaven would be less willing to attend church
regularly; for these people the cost of signaling is higher. What this means is that many
skeptics will not use religious participation to signal cooperative intent. The majority of
signalers are therefore believers that have a low willingness to free ride. Sosis (2003) has
proven that when signals are sufficiently costly, the number of free riders is so low that a
stable cooperative state can be achieved. In conclusion, only if signals are sufficiently costly
can cooperative intentions be credibly signaled to others and can the signaling mechanism
lead to sustained cooperation in a group.
Because of the issue raised above, it is critical to make a clear distinction between
costly signals and non-costly signals. Sosis and Bressler (2003) propose that there are two
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types of costly signals. The first type are behaviors that are required by a group that entail
time, energetic, and/or financial costs that are not directed toward efficiently accomplishing
evolutionary goals. The participation in religious rituals or meetings is a good example of a
costly signal of this type, since it entails time and energy that could as well have been used
for fitness enhancing activities. The second type are behaviors that might have entailed
evolutionary benefits, but are restricted by group norms (e.g. sexual abstinence, and not
eating healthy foods due to religious guidelines). This study will focus on the first type of
costly signals because behavior that is exhibited can more readily be measured than behavior
that is not exhibited.
Besides an accurate definition of costly signals, it is also important to define the other
concepts that are of importance in the costly signaling mechanism: cooperation, and trust. In
the literature, there have been some different, sometimes inconsistent, definitions of
cooperation. Some studies, implicitly or explicitly, define cooperation as “personally costly
behavior that benefits others” (Lehmann & Keller, 2006; Ernest-Jones, Nettle, & Bateson,
2011; West, El Mouden, & Gardner, 2011). This is a broad definition of cooperation in the
sense that it incorporates phenomena like generosity and helping, that could also be labeled
as altruism. The costly signaling mechanism is also relevant for such altruistic behaviors, but
altruism will be defined separately in this study to avoid confusion. Cooperation will be
defined as “acts or instances of working or acting together for a common purpose or benefit.”
(Dictionary.com, 2013). An added advantage of this narrow definition is that it is more
similar to the de facto meaning of the term cooperation, which originates from the Latin
cooperationem, meaning ‘a working together’. In accordance with Gray (2007), altruism will
be defined as “behavior that helps another while it decreases the evolutionary success of
oneself”.
The remaining concept that needs defining is trust. This is a difficult task, since trust
has different connotations in different scientific disciplines. For this reason a broad definition
is used that is based on several disciplines: “Trust is a psychological state comprising the
intention to accept vulnerability based upon positive expectations of the intentions or
behavior of another.” (Rousseau, Sitkin, Burt, & Camerer, 1998). Only studies that used
definitions of cooperation, altruism, and trust similar to the ones formulated above were used
as a basis for the current study.
The costly signaling theory of religion makes four predictions that will be tested in
this study. A first prediction is that people who send out more costly signals have a higher
willingness to cooperate with others. This follows from two assumptions that are crucial for
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the sustainability of the costly signaling mechanism. First, the majority of the costly signalers
are believers because the signaling costs for believers are lower than the signaling costs for
skeptics. Second, believers are more willing to cooperate than skeptics because they place a
higher value on adherence to cooperative group norms.
In line with this first prediction, Ruffle and Sosis (2007) found that members of
religious kibbutzim were more cooperative in a common-pool resource dilemma game than
their secular counterparts. Moreover, the individuals in these kibbutzim who had the highest
frequency of ritual participation displayed the highest levels of cooperation. Further, Soler
(2012) used a tailor-made questionnaire to measure the level of costly signaling. He found
that people who scored higher on this questionnaire were more cooperative in a public good
game. Also, they claimed to be involved in more instances of intragroup cooperation.
The studies mentioned above intentionally set out to test the costly signaling theory of
religion. However, studies that investigated related subjects can be instructive as well. For
example, Ahmed (2009) found that students in India who were studying to become an imam
were more likely to cooperate in a public good game than were nonreligious students.
Similarly, Anderson, Mellor and Milyo (2010) found that higher attendance in organized
religious services was related to higher contributions in a public good game. On the other
hand, in studies by Anderson and Mellor (2009), and Paciotti et al. (2011), no relationship
was found between religious participation and contributions in public good experiments.
The costly signaling theory not only states that costly signalers are more cooperative,
but also that they are more altruistic. This second prediction follows from the theory because
a group where reciprocal altruism is the norm would have an evolutionary advantage over a
group with mainly selfish individuals. The literature on this prediction is limited, since many
studies do not use religious attendance or costly signaling as independent variables. Instead,
they focus on experimental manipulations where religious thoughts are manipulated (e.g.
Shariff & Norenzayan, 2007; Pichon, Boccato, & Saroglou, 2007). Since the costly signaling
theory is about actions and not about thoughts, these studies are not relevant. There are a few
studies that do focus on religious actions. These studies did not find the predicted relationship
between religious attendance and altruism (Eckel & Grossmann, 2004; Tan, 2006; Bulbulia &
Mahoney, 2008).
The third prediction is that people who send out more costly signals are perceived as
more trustworthy. This perceived trustworthiness will be labeled received trust in this study,
because it involves trust that is received from others. Regarding this third prediction, Edgell,
Gerteis, and Hartmann (2006) found that religiosity was positively associated with received
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trust. Adding to that, Tan and Vogel (2008) found that religious people were trusted more
than nonreligious people in a trust game. Equivalently, Orbell, Goldman, Mulford, and
Dawes (1992) found that both religious and nonreligious people believe that religious people
will cooperate more than nonreligious people in a prisoner’s dilemma game.
The fourth prediction of the costly signaling theory of religion is based on the
increased trust that stems from the third prediction. This fourth prediction is that third
parties are more likely to cooperate with people who send out more costly signals. This form
of cooperation will be labeled received cooperation because it involves cooperation that is
received from others. Not much research has been done regarding this prediction, but Soler
(2012) found that actively signaling participants elicited more instances of received
cooperation within their religious community.
The existing literature on the costly signaling mechanism of religion, although not
entirely consistent, does seem to underpin the theory to some extent. However, one can raise
doubts about how the studies have measured the level of costly signaling. This is because
almost all studies used attendance at religious meetings as their main independent variable.
By doing this, these studies ignored other relevant aspects of religious costly signaling like
the personal importance people attach to the religious meetings, and the intensity with which
they participate in them. This study will therefore use a questionnaire that incorporates not
only items on religious attendance, but also items on these other aspects.
Another point of critique on the existing literature is that many studies did not take
into account the possibility of omitted variable bias (Stock, & Watson, 2007). Omitted
variable bias occurs when variables that are correlated both with the dependent and
independent variable are excluded from a model. This is problematic because it could be the
case that these excluded variables are responsible for the variance in the dependent variable,
instead of the independent variable. For example, people who live in the countryside more
often attend religious meetings than people in more urban environments (Chalfant, & Heller,
1991). In addition, it could be the case that these people learn to be more cooperative because
small communities are largely dependent on close relations. This means that whether
someone is living in the countryside or not can account for a positive relationship between
religious attendance and willingness to cooperate. This is troublesome, because we are
interested in the causal relationship between religious attendance and willingness to
cooperate. Another variable for which this is the case is the number of siblings. Many
religious families are large, and it can be argued that cooperation and trust arise more
naturally in large families. Therefore, also the number of siblings can be a confounding
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variable. To avoid the risk of omitted variable bias, this study will take into account these two
potentially confounding variables.
As stated before, this study will focus on four predictions of the costly signaling
theory of religion that are related to willingness to cooperate, altruism, received trust, and
received cooperation. A specifically designed questionnaire is used to measure the level of
costly signaling of the participants. This questionnaire is loosely based on the questionnaire
employed by Soler (2012). Further, willingness to cooperate is measured using a prisoner’s
dilemma game. This game consists of two players that both have the option to cooperate or
not cooperate with the other player. The game has been extensively used by economists and
psychologists to measure people’s willingness to cooperate. Besides that, a dictator game is
used to measure the degree of altruism of the participants. In this dictator game participants
have the possibility to donate money to one of two charities. Finally, items on willingness to
cooperate, altruism, received trust, and received cooperation are included in an additional
questionnaire. Both the questionnaire, the prisoner’s dilemma, and the dictator game are part
of an online survey that was made available to a selective group of religious students.
Following the predictions of the costly signaling theory of religion, it is expected that
participants who score higher on the costly signaling questionnaire are also more likely to
cooperate in the prisoner’s dilemma, donate higher amounts in the dictator game, and score
higher on the items regarding willingness to cooperate, altruism received trust, and received
cooperation.
Method
Participants
A large part of the participants in this study were approached by contacting the boards of
various religious student fractions with the request of letting their members fill out the online
survey. The student fractions of which members participated were Navigators Student
Association Amsterdam, CSFR Amsterdam, and Islamic Student Association Ibn Firnas from
Delft. It is estimated that around 450 people were approached in this way, and that 105 chose
to participate. Other participants in this study were approached through a system called
‘Digitaal Proefpersoonpunten Management Systeem’, designed by the University of
Amsterdam specifically to find research participants. Those participants were approached that
in earlier, unrelated tests indicated some form of religious belief. It is estimated that this
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amounted to 300 approached students, of which approximately 60 chose to participate. All of
those that participated were paid a small sum of money. This amount varied from 1 to 5 euro
and depended on the choices the participants made in the experiment.
Materials
One of the ways willingness to cooperate was measured was through a standard prisoner’s
dilemma game. Participants had to play a 2-person game in which they had the choice to
either cooperate with the other player or not. They were told that the other player was another
participant that had to make exactly the same choice. The decision in the prisoner’s dilemma
was purposefully labeled as ‘cooperate’ or ‘not cooperate’ instead of the more neutral ‘choice
A’ and ‘choice B’ to make sure that the participants knew what the cooperative choice was.
Furthermore, it was emphasized that all players in the game were totally anonymous, so
participants did not know with whom they would be matched. The full instructions of the
prisoner’s dilemma game can be seen in Appendix A.
In the prisoner’s dilemma, fictional monetary units called neuros were used, where
each neuro corresponded to 2.5 eurocents. Participants could earn a minimum of 40 neuros (1
euro) and a maximum of 200 neuros (5 euro) with their decision. The full payoff table is
shown in Figure 1. Whether or not participants cooperated in the prisoner’s dilemma game
was taken as a measure of their willingness to cooperate.
Figure 1 *
The Prisoner’s Dilemma Game as Presented to the Participants
* the text is translated from Dutch
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Besides playing the prisoner’s dilemma game, participants also had to play a so-called
dictator game. In this game, participants were allocated 160 neuros and were given the choice
to keep this amount or to donate a percentage of it to a given charity. The participants could
decide for themselves what percentage they would like to donate. To see whether the level of
the donations varied with the type of the charity, participants faced either a religious charity,
The Salvation Army, or a secular charity, The Food Bank. Instructions of the dictator game
can be found in Appendix B.
Before playing both games, participants were told that they would only receive
payment for one of the games, and that it would be decided randomly which one this would
be. Payments were made through bank transfer, and therefore participants had to fill in their
bank account number at the end of the online survey. To assure their anonymity, they did not
need to fill in the name that corresponded to the bank account number.
There was also a game included in the online survey without a monetary payoff. In
this so-called snowy pictures task, 12 pictures were presented in which participants had to
discern a figure. In some pictures there was indeed a figure, in others there was not.
Participants had to state what figure they saw, if any, and how sure they were that they saw
this figure. This task was included as part of another study.
Aside from playing the games, participants had to fill in several questionnaires. One
questionnaire was designed to measure the main independent variable, the level of costly
signaling. The items in this questionnaire were loosely based on the items used by Soler
(2012). Because Soler’s questionnaire was developed for Brazilian participants of a wide age
range, the items were adjusted somewhat to make them more suitable for Dutch students. An
overview of the costly signaling items is shown in Table 1. Some items on the level of
religiosity of the participants were also included in the questionnaire. These can be seen in
Appendix C.
Another questionnaire included self-report items on prosocial behavior. Items that are
of relevance to the costly signaling theory of religion are those regarding willingness to
cooperate, altruism, received trust, and received cooperation. These items are shown in Table
2. The other items in this prosocial behavior questionnaire were relevant for another study
and were not included in Table 2.
The items of the costly signaling questionnaire, as well as the items on prosocial
behavior were Likert items with the following five answering possibilities: “I strongly
disagree”, “I disagree”, “I neither agree nor disagree”, “I agree”, and “I strongly agree”.
These answering possibilities corresponded to scores of 1, 2, 3, 4, and 5 respectively.
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A final questionnaire was used to elicit demographic information from the
participants. This questionnaire is shown in Appendix D.
Table 1 *
Items on Costly Signaling
Item Statement
1
I regularly attend religious activities
2
I often contribute to the organization of a religious activity
3
When there is a religious meeting, I wouldn’t want to miss it
4
Participating in religious rituals is not that important to me **
5
I sometimes go to a religious meetings, even though I prefer to do something else
6
I have given money to a religious organization or a religious charity
7
I have done volunteer work for a religious organization or a religious charity
8
When I go to a religious meeting, I want to participate in an active way
* the items are translated from Dutch
** item that is phrased contra-indicative and was recoded for the statistical analyses
Table 2 *
Items on Willingness to Cooperate, Altruism, Received Trust, and Received Cooperation
Variable
Item
Measures
Co1
I’m a person that likes to cooperate with others
Willingness to cooperate
Alt
I’m a generous person that likes to invest time and energy in others
Altruism
Tru
I have the feeling that other people trust me
Received trust
Co2
Other people like to cooperate with me
Received cooperation
* the items are translated from Dutch
Analysis
Because the choice made in the prisoner’s dilemma is dichotomous, a binary logistic
regression was carried out. Besides that, linear regression analyses were done to investigate
whether participants that showed more costly signaling donated more in the dictator game,
and scored higher on willingness to cooperate, altruism, received cooperation, and received
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trust. In all regressions, the same independent variables were used. The costly signaling
variable was the main predictor. The environment a participant grew up in, and the number of
siblings a participant grew up with, were control variables. Religious affiliation, level of
religiosity, financial situation, and gender were added to explore whether some groups
differed with regard to cooperation and trust.
Procedure
Participants got access to the online survey by clicking on a link that was made available to
them. After receiving some information about the study, participants indicated whether or not
they liked to participate. When they chose to participate, they were able to start with the first
part of the survey.
While developing the online survey, close attention was paid to the order in which the
tasks were presented. This was done to decrease the risk of carryover effects (Mook, 2001).
Carryover effects occur if exposure to one task changes a participant’s behavior in a later task.
This could be the case because people generally have a preference to behave consistently.
This preference is common because most people will have feelings of cognitive dissonance
when their beliefs, behaviors, or attitudes are inconsistent (Festinger, 1957). For example, if
the self-report questionnaire would be presented before the prisoner’s dilemma, it is possible
that participants who self-reported a high willingness to cooperate, would be more inclined to
cooperate in the prisoner’s dilemma because that is the consistent thing to do. If the
prisoner’s dilemma was presented first, participants who cooperated in the prisoner’s
dilemma may try to be consistent by self-reporting a higher willingness to cooperate. In this
way, the behavior of the participants would change due to the order of the tasks. It was
expected that these carryover effects would be smaller when the self-report questionnaire was
presented first. The reason for this is that there was money at stake in the prisoner’s dilemma
game. Because people tend to value money, this could deter them from changing their
behavior because of consistency concerns.
The final order of tasks is listed in Table 3. On average, the online survey took
approximately 15 minutes to finish.
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Table 3
Order in which the tasks were presented
Task
Type of task
Shown in
1
Demographic information questionnaire
Appendix D
2
Prosocial behavior questionnaire
Table 2 *
3
Prisoner’s dilemma
Figure 1 / Appendix A
4
Dictator game
Appendix B
5
Religiosity questionnaire
Appendix C
6
Snowy pictures task
-
* only the items relevant for the costly signaling theory of religion are shown
Results
Participants
A total number of 165 people participated in this study. Of these 165, all participants that did
not state themselves as religious were not taken into account in the analyses. This included 17
atheists, 7 agnostics, 5 deists (people that stated a belief in a supernatural entity but no
adherence to a specific religion) and 1 humanist. These 30 people were eliminated from the
analysis because the costly signaling mechanism is not relevant to them; they do not have a
religious group to signal their cooperative intent to. In all, 135 participants remained in the
analysis. Their average age was 21.98 (SD = 4.21). Of all the participants, 71.1 percent chose
to cooperate in the prisoner’s dilemma. The donations in the dictator game were on average
2.55 euro for The Salvation Army and 2.77 euro for The Food Bank. Finally, the participants
scored 3.73, 3.90, and 4.21 respectively on the items measuring willingness to cooperate,
received cooperation, and received trust. In Appendix E, descriptive statistics can be found
for different categories of participants.
Principal Component Analysis
First, a principal component analysis was carried out over the costly signaling items that can
be seen in Table 1. This was done to create an internally consistent measure of costly
signaling. In a principal component analysis, the correlations between various items are
inspected. If one of the items does not correlate well with the other items, this is an indication
that the item is measuring something different from what the other items are measuring. This
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item may then be deleted from the analysis to create a more consistent measure.
Only with a sufficiently large sample size, reliable results will be obtained from a
principal component analysis. Therefore, a Kaiser-Meyer-Olkin test was done to see if the
sample size is large enough. The KMO test statistics ranges from 0 to 1, where values over
0.5 correspond to a sufficiently large sample size (Field, 2009). The overall KMO proved to
be .86, which means the sample size in this study is more than sufficient to carry out a
principal component analysis.
The principal component analysis was carried out using Varimax rotation. The results
are shown in Table 4. It was found that two components had an Eigenvalue larger than 1. The
first component was able to explain a large part of the variation in the questionnaire
responses (49.46%). The second component was able to explain markedly less variation
(14.08%). Since the questionnaire was specifically developed to measure costly signaling, it
is reasonable to assume that the underlying trait of the first component is the level of costly
signaling. Items that are not significantly related to this component are probably measuring
some other trait. These items will therefore be excluded from the statistical analyses. An
often used cut-off point for determining what factor loading corresponds to a significantly
low relation is 0.5. Therefore, item 4 and 5 were eliminated from the analysis. However,
since the factor loading of item 4 did come close to the cut-off point level of 0.5, all statistical
analyses were also done including item 4. This was done to control for the possibility that an
arbitrary cut-off point influenced the results. The analyses including item 4 can be found in
Appendix F. The scores for each participant on the 6 leftover items were summed, and this
sum score was taken as a measure of the level of costly signaling of that participant.
The reliability analysis that was done over the 6 leftover items indicated that these
items have a good internal consistency, Cronbach’s α = .88. The internal consistency of all 8
items together was α = 0.83.
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Table 4
Rotated Component Matrix with Factor Loadings and Communalities of All Items, and the
Eigenvalues of Both Components (N=135)
Component 1
Component 2
Communality
Item 1
.91
-.08
.83
Item 2
.88
.01
.77
Item 3
.68
.38
.60
Item 4
.48
.47
.45
Item 5
.21
-.82
.72
Item 6
.76
-.08
.58
Item 7
.78
-.11
.62
Item 8
.67
.25
.51
Eigenvalue
3.96
1.13
Binary Logistic Regression
Before carrying out the binary logistic regression, the assumption of multicollinearity was
tested. There appeared to be no multicollinearity problems since the VIF for all variables was
< 2.50, well below the cautionary value of 10 as suggested by Field (2009).
In the binary logistic regression, cooperation in the prisoner’s dilemma was regressed
onto the costly signaling measure, level of religiosity, religious affiliation, gender, and
financial situation. When comparing different religious affiliations, the benchmark group was
the one with the highest N, the protestant participants. Number of siblings, and youth
environment were included in the model as control variables. The result of this regression can
be seen in Table 5. It was found that the level of costly signaling did not significantly predict
whether participants cooperated or not, Wald χ²(1) = 1.91, p = .17. The significance level
used in all regressions in this study is α = .05.
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Table 5
Beta Coefficients (B), Standard Errors (SE), Odds Ratios and Nagelkerke’s R² for the Binary
Logistic Regression on Cooperation in the Prisoner’s Dilemma (N=135)
B (SE)
Odds Ratio
CS
0.09 (0.07)
1.10
Religiosity
0.03 (0.133)
1.03
Male
-0.80 (0.44)
0.45
Financial Situation
0.13 (0.21)
1.14
Catholic
1.06 (0.84)
2.87
Undefined Christian
-0.56 (0.82)
0.57
Muslim
1.03 (0.88)
2.79
Buddhist
0.49 (1.11)
1.63
R²N
.13
Control variables: Number of Siblings, Youth Environment
* p < .05
** p < .01
Linear Regression on the Dictator Game Responses
For the linear regression on the dictator game responses, no problems of multicollinearity
were found in the pretests (all VIFs < 6.5). Also, there appeared to be no dependence of error
terms in the models. This was concluded because only random patterns were found when the
standardized residuals were plotted against the model variables.
The results show a positive association between the level of religiosity and altruism, t
= 2.91, p = .004, but no association between the level of costly signaling and altruism, t =
-0.55, p = 0.78. Furthermore, it was found that there was no difference between the donations
to the religious charity and the secular charity, t = -0.84, p = 0.40. Results of the linear
regression can be found in Table 6.
17
Table 6
Beta Coefficients (B), Standard Errors (SE), and R² of the Linear Regression on the Dictator
Game Responses (N=135)
B (SE)
CS
-0.43 (1.50)
Religiosity
9.48** (3.26)
Male
-9.19 (10.78)
Financial Situation
-1.95 (5.01)
Catholic
-16.51 (19.43)
Undefined Christian
-.60 (21.15)
Muslim
-11.69 (18.11)
Buddhist
-34.12 (25.59)
R²N
.25
Control variables: Number of Siblings, Youth Environment
* p < .05
** p < .01
Linear Regressions on the Self-Report Items
For the linear regressions on the self-report items, no problems of multicollinearity were
found in the pretests (all VIFs < 6.5). Also, there appeared to be no dependence of error terms
in the models. This was concluded because only random patterns were found when the
standardized residuals were plotted against the model variables.
The linear regressions revealed a significant positive relationship between the level of
costly signaling and willingness to cooperate, t = 2.30, p = .02, altruism, t = 2.10, p = .04,
received cooperation, t = 3.11, p = .002, and received trust, t = 2.80, p = .01.
When comparing different religious affiliations, it was found that catholic participants
scored higher on willingness to cooperate, t = 2.72, p = .01 and received trust, t = 3.82, p
< .001, than protestant participants. Buddhist participants also scored higher on received trust
than protestant participants, t = 2.18, p = .03. Furthermore, Muslim participants scored higher
than protestant participants on altruism, t = 3.02, p = .003. The results of the regressions can
be seen in Table 7.
18
Table 7
Beta Coefficients (B), Standard Errors (SE) and R² of the Linear Regressions on the SelfReport Items (N=135)
Co1
Alt
Tru
Co2
B (SE)
B (SE)
B (SE)
B (SE)
CS
0.05* (0.02)
0.04* (0.02)
0.05** (0.02)
0.05** (0.02)
Religiosity
-0.08 (0.05)
-0.09 (0.05)
0.01 (0.04)
-0.03 (0.04)
Male
0.12 (0.17)
-0.05 (0.15)
-0.08 (0.13)
-0.14 (0.12)
Financial Situation
0.02 (0.08)
-0.09 (0.07)
0.02 (0.06)
-0.02 (0.06)
Catholic
0.52 (0.30)
0.49 (0.27)
0.87** (0.23)
0.60** (0.22)
Undefined Christian
-0.10 (0.33)
-0.08 (0.30)
0.09 (0.25)
-0.03 (0.24)
Muslim
-0.16 (0.28)
0.76** (0.25)
0.41 (0.21)
0.08 (0.21)
Buddhist
0.33 (0.40)
0.59 (0.36)
0.66* (0.30)
0.44 (0.29)
.09
.17
.19
.12
R²
Control variables: Nunber of Siblings, Youth Environment
* p < .05
** p < .01
Conclusions and Discussion
In this study, four predictions of the costly signaling theory of religion (Irons, 1996; 2001)
were tested. The first two predictions were that people who more often send out costly signals
are both more willing to cooperate with others and more altruistic. Further, it was predicted
that third parties perceive costly signalers to be more trustworthy and are therefore more
willing to cooperate with them. It was found, through self-report questionnaires, that higher
levels of costly signaling were indeed associated with higher levels of willingness to
cooperate, altruism, received cooperation, and received trust. However, willingness to
cooperate and altruism did not seem to be related to costly signaling when behavioral
measures were used.
An interesting finding was that the level of costly signaling was associated with the
self-report measures of willingness to cooperate and altruism, but not with the behavioral
measures of those variables. This dichotomy makes it difficult to interpret the results and
raises questions about the validity of both the behavioral measures and the self-report
measures. The validity of a measure can be defined as the extent to which the measure
19
actually measures what it is supposed to measure (Mook, 2001). With regard to the validity
of the measures in this study, there are three points to be made.
First, it was possible to earn money in the prisoner’s dilemma game and the dictator
game, while this was not the case for the self-report items. It is reasonable to assume that
people think more deeply about what their true preferences are when money is at stake. And
because they do, tasks involving monetary payoffs (e.g. the prisoner’s dilemma game) can
induce responses that correspond more accurately with people’s actual preferences. In other
words, tasks involving monetary payoffs are more valid.
Second, the self-report measures used the terms cooperation and trust without
informing the participant about what is actually meant by these terms. We have seen
previously that there are multiple definitions of the terms cooperation and trust, and it is
therefore possible that participants interpreted these terms in different ways. If this was the
case, the responses of the participants would differ due to differences in their interpretations
and not due to differences in their willingness to cooperate, received cooperation, or received
trust. In other words, the self-report measures have a validity problem. A solution to this
problem would be to give a clear definition and some examples of cooperation and trust
before presenting the items.
Third, it must be emphasized that the self-report measures consist of only one item.
Due to this, it is possible that irrelevant factors had a large impact on the participant’s
responses. For example, a participant could be temporarily distracted or tired while answering
this one item. If that is the case, the response of the participant probably does not correspond
to his real preference. In other words, there is a validity problem. A solution to this problem
would be to use multiple items because it is unlikely that a participant is distracted or tired
while answering all of the items. The effects of distraction and tiredness will then have a
smaller impact and researchers can be more certain that the responses of the participants are
truly indicative of their actual preferences.
In short, there are several validity concerns regarding the self-report measures. These
validity concerns warrant caution when drawing conclusions from the results in this study.
While the positive relationships between costly signaling and both received trust and received
cooperation do seem to support the theory, the validity issues limit these relationships to
being tentative. Future research is required to substantiate the findings. This future research is
preferably done using either behavioral measures that include a monetary incentive, or selfreport measures that include multiple items and accurate definitions of trust and cooperation.
Regarding the self-report items on willingness to cooperate and altruism there is an
20
additional issue. As can be seen in Appendix F, the relationship between costly signaling and
willingness to cooperate, and the relationship between costly signaling and altruism are no
longer significant when item 4 is included in the analysis. This means that the arbitrary
choice to exclude item 4 from the main analysis had a large effect on the results. In other
words, the relationships are not very robust. This robustness issue and the previously
mentioned validity issues make it unwarranted to draw conclusions based on these self-report
measures. The conclusion on the relationship between costly signaling and willingness to
cooperate, and on the relationship between costly signaling and altruism will therefore be
drawn solely on the basis of the behavioral measures. It can be concluded that there is not
enough evidence for a relationship between costly signaling and both willingness to
cooperate and altruism.
Based on the discussion above, it can be concluded that two predictions of the costly
signaling theory of religion are tentatively supported, while two are not supported. The
evidence for the theory is therefore mixed and further research is necessary.
21
Appendix A - Instructions of the Prisoner’s Dilemma game (translated from Dutch)
The first task consists of making one single decision. You will be matched with a random
other participant, who has to make exactly the same choice as you. Your choice and the
choice of the other will determine both your earnings and the other’s earnings. You will make
your choices independently of each other, and probably at different times. Since your
earnings depend on the choice of the other person, it will only later become clear how much
money you will have earned in this task.
In a moment, you and the other participant will choose to cooperate or not cooperate with
each other. When both of you decide to cooperate, you will both receive 160 neuro. When
both of you decide not to cooperate, you will both receive 60 neuro. When you decide to
cooperate, and the other decides not to cooperate, you will receive 40 neuro and the other
receives 200 neuro. Finally, when you decide not to cooperate, and the other decides to
cooperate, you will receive 200 neuro and the other will receive 40 neuro.
Appendix B – Instructions of the Dictator Game (translated from Dutch)
The religious charity
In this task you’ll have the opportunity to make a monetary donation to a charity. The charity
in question is The Salvation Army. The Salvation Army is an evangelical movement that
provides practical help and professional care to those in need. The money that is donated to
Salvation’s Army will go to one of their social projects in The Netherlands. It is possible to
donate an amount between 0 and 160 neuro to this charity. You can keep the money you
don’t give away for yourself.
The secular charity
In this task you’ll have the opportunity to make a monetary donation to a charity. The charity
in question is The Food Bank. The Food Bank is a charitable movement that provides food
and water to those that are financially incapable of providing this for themselves. The money
that is donated to The Food Bank will go to one of the regional food banks in The
Netherlands. It is possible to donate an amount between 0 and 160 neuro to this charity. You
can keep the money you don’t give away for yourself.
22
Appendix C
Table 8 *
Items on the Level of Religiosity of the Participants
Item Statement
1
I see myself as a believer
2
Religion is only a small part of my life **
3
I believe in the existence of God or a higher power
* the items are translated from Dutch
** item that is phrased contra-indicatively and was recoded for the statistical analyses
Appendix D
Table 9 *
Questionnaire on Demographic Information of the Participant
Item
Answering possibilities
Gender
Male / Female
Age
(Open question)
Highest level of education
VMBO / HAVO / VWO / MBO / HBO / WO / other
I was born in …
The Netherlands / Morocco / Turkey / Surinam / other
My mother was born in …
The Netherlands / Morocco / Turkey / Surinam / other
My father was born in …
The Netherlands / Morocco / Turkey / Surinam / other
I was raised …
In the countryside / In a village / In a city
I grew up with … brothers and/or sisters
0 / 1 / 2 / 3 / 4 or more
I am currently in a relationship
Yes / No
I see myself as …
Protestant / Catholic / Muslim / Jewish / Atheist / other
In general, I have enough money to do
I strongly disagree / I disagree / I neither agree nor
the things I want to do
disagree / I agree / I strongly agree
* the items are translated from Dutch
23
Appendix E
Table 10
Proportion of Cooperators in the Prisoner’s Dilemma Game, Proportion of Money Donated in
the Dictator Game, and Mean Answers on the Self-report Items, by Gender
Gender
PD
DG
Co1
Alt
Tru
Co2
Female (N=90)
0.76
0.69
3.68
3.81
4.23
3.93
Male (N=45)
0.62
0.61
3.82
3.84
4.18
3.82
Table 11
Proportion of Cooperators in the Prisoner’s Dilemma Game, Proportion of Money Donated in
the Dictator Game, and Mean Answers on the Self-report Items, by Environment the
Participants Grew up in
Grew up
PD
DG
Co1
Alt
Tru
Co2
In the countryside (N=8)
0.75
0.59
3.75
3.38
4.13
3.75
In a village (N=55)
0.69
0.67
3.65
3.85
4.31
3.93
In a city (N=72)
0.72
0.67
3.78
3.85
4.15
3.89
Table 12
Proportion of Cooperators in the Prisoner’s Dilemma Game, Proportion of Money Donated in
the Dictator Game, and Mean Answers on the Self-report Items, by Number of Siblings
Siblings
PD
DG
Co1
Alt
Tru
Co2
0 (N=6)
0.83
0.33
3.67
3.67
4.33
3.83
1 (N=32)
0.72
0.65
3.59
3.91
4.16
3.91
2 (N=34)
0.62
0.59
3.71
3.79
4.24
3.85
3 (N=35)
0.71
0.73
3.77
3.86
4.17
3.91
4+ (N=28)
0.79
0.76
3.86
3.75
4.29
3.93
24
Table 13
Proportion of Cooperators in the Prisoner’s Dilemma Game, Proportion of Money Donated in
the Dictator Game, and Mean Answers on the Self-report Items, by Religious Affiliation
Religious Affiliation
PD
DG
Co1
Alt
Tru
Co2
Protestant (N=83)
0.70
0.72
3.73
3.70
4.12
3.87
Catholic (N=17)
0.76
0.42
3.82
3.94
4.41
4.00
Undefined Christian (N=8)
0.63
0.78
3.50
3.63
4.25
3.88
Muslim (N=12)
0.83
0.69
3.58
4.33
4.33
3.83
Buddhist (N=6)
0.67
0.28
4.00
4.17
4.33
4.00
Other Religion (N=9)
0.67
0.73
3.67
4.00
4.44
4.00
Table 14
Proportion of Cooperators in the Prisoner’s Dilemma Game, Proportion of Money Donated in
the Dictator Game, and Mean Answers on the Self-report Items, by Financial Situation
Financial situation
PD
DG
Co1
Alt
Tru
Co2
1 (N=3)
0.67
0.56
4.00
4.67
4.33
4.33
2 (N=21)
0.71
0.60
3.71
3.90
4.14
4.00
3 (N=20)
0.65
0.77
3.85
4.00
4.25
3.80
4 (N=71)
0.68
0.65
3.61
3.73
4.18
3.80
5 (N=20)
0.90
0.69
4.00
3.75
4.35
4.15
25
Appendix F – Statistical analyses including item 4
Table 15
Beta Coefficients (B), Standard Errors (SE), Odds Ratio’s and Nagelkerke’s R² for the Binary
Logistic Regression on Cooperation in the Prisoner’s Dilemma (N=135)
B (SE)
Odds Ratio
CS
0.08 (0.06)
1.08
Religiosity
0.03 (0.14)
1.03
Male
-0.77 (0.44)
0.46
Financial Situation
0.13 (0.21)
1.14
Catholic
0.94 (0.81)
2.57
Undefined Christian
-0.58 (0.82)
0.56
Muslim
0.92 (0.86)
2.51
Buddhist
0.49 (1.11)
1.63
R²N
.12
Control variables: Number of Siblings, Youth Environment
* p < .05
** p < .01
Table 16
Beta Coefficients (B), Standard Errors (SE), and R² of the Linear Regression on the Dictator
Game Responses (N=135)
B (SE)
CS
-.55 (1.34)
Religiosity
9.77** (3.13)
Male
-9.23 (10.75)
Financial Situation
-2.02 (5.01)
Catholic
-16.82 (18.91)
Undefined Christian
-0.55 (21.137)
Muslim
-11.47 (17.88)
Buddhist
-34.26 (25.57)
R²N
.25
Control variables: Number of Siblings, Youth Environment
* p < .05
** p < .01
26
Table 17
Beta Coefficients (B), Standard Errors (SE), and R² of the Linear Regressions on the SelfReport Items (N=135)
Co1
Alt
Tru
Co2
B (SE)
B (SE)
B (SE)
B (SE)
CS
0.03 (0.02)
0.03 (0.02)
0.04* (0.02)
0.05** (0.02)
Religiosity
-0.06 (0.05)
-0.08 (0.05)
0.01 (0.04)
-0.03 (0.04)
Male
0.14 (0.17)
-0.03 (0.15)
-0.06 (0.13)
-0.13 (0.12)
Financial Situation
0.02 (0.08)
-0.09 (0.07)
0.02 (0.06)
-0.02 (0.06)
Catholic
0.40 (0.30)
0.42 (0.27)
0.81** (0.22)
0.54* (0.22)
Undefined Christian
-0.11 (0.33)
-0.09 (0.30)
0.08 (0.25)
-0.05 (0.24)
Muslim
-0.24 (0.28)
0.71** (0.25)
0.35 (0.21)
0.03 (0.20)
Buddhist
0.31 (0.40)
0.58 (0.36)
0.65* (0.30)
0.44 (0.29)
.07
.16
.18
.11
R²
Control variables: Number of Siblings, Youth Environment
* p < .05
** p < .01
27
References
Ahmed, A. M. (2009). Are religious people more prosocial? A quasi‐experimental study
with madrasah pupils in a rural community in India. Journal for the Scientific Study
of Religion, 48(2), 368-374.
Albanese, R., & Van Fleet, D. D. (1985). Rational behavior in groups: The free-riding
tendency. The Academy of Management Review, 10(2), 244-255.
Alcorta, C. S., & Sosis, R. (2005). Ritual, emotion, and sacred symbols. Human
Nature, 16(4), 323-359.
Anderson, L. R., & Mellor, J. M. (2009). Religion and cooperation in a public goods
experiment. Economics Letters, 105(1), 58-60.
Anderson, L. R., Mellor, J. M., & Milyo, J. (2010). Did the devil make them do it? The
effects of religion in public good and trust games. Kyklos, 63(2), 163-175.
Bulbulia, J., & Mahoney, A. (2008). Religious solidarity: The hand grenade experiment.
Journal of Cognition and Culture, 8, 295-320.
Chalfant, H. P., & Heller, P. L. (1991). Rural/urban versus regional differences in religiosity.
Review of Religious Research, 33(1), 76-86.
Dawkins, R. (1976). The Selfish Gene. New York City: Oxford University Press.
Dictionary.com (2013). Cooperation. Retrieved October 2, 2013, from Dictionary.com
webite: http://dictionary.reference.com/browse/cooperation.
Edgell, P., Gerteis, J., & Hartmann, D. (2006). Atheists as other: Moral boundaries and
cultural membership in American society. American Sociological Review, 71(2), 211234.
Ernest-Jones, M., Nettle, D., & Bateson, M. (2011). Effects of eye images on everyday
cooperative behavior: A field experiment. Evolution and Human Behavior, 32(3),
172-178.
Festinger, L. (1957). A Theory of Cognitive Dissonance. Stanford University Press.
Field, A. (2009). Discovering Statistics using SPSS, (3rd ed.). New York: Sage.
Gintis, H., Smith, E. A., & Bowles, S. (2001). Costly signaling and cooperation. Journal of
Theoretical Biology, 213(1), 103-119.
Gray, P. (2007). Psychology (5th ed.). New York: Worth.
Hawkes, K. (1993). Why hunter-gatherers work: An ancient version of the problem of public
goods. Current Anthropology, 34(4), 341-361.
28
Henrich, J. (2009). The evolution of costly displays, cooperation, and religion: Credibility
enhancing displays and their implications for cultural evolution. Evolution and
Human Behavior, 30, 244-260.
Irons, W. (1996). Morality, religion, and human nature. In W. M. Richardson and W.
Wildman (Eds.), Religion and science: History, methods, dialogue (pp. 375-399).
New York: Routledge.
Irons, W. (2001). Religion as a hard-to-fake sign of commitment. In R. M. Nesse (Ed.),
Evolution and the capacity for commitment (pp. 292-309). New York: Russel Sage.
Lehmann, L., & Keller, L. (2006). The evolution of cooperation and altruism: A general
framework and a classification of models. Journal of evolutionary biology, 19(5),
1365-1376.
Maoz, Z., & Henderson, E. A. (2013). The World Religion Dataset, 1945-2010: Logic,
estimates and trends. International Interactions, 39(3), 265-291.
Mook, D. G. (2001). Psychological Research: The Ideas Behind the Methods, (1st ed.). New
York: W. W. Norton & Company.
Olson, M. (1971) [1965]. The logic of collective action: Public goods and the theory of
groups (Revised edition ed.). Harvard University Press.
Orbell, J., Goldman, M., Mulford, M., & Dawes, R. (1992). Religion, context, and constraint
toward strangers. Rationality and Society, 4(3), 291-307.
Pichon, I., Boccato, G., & Saroglou, V. (2007). Nonconscious influences of religion on
prosociality: A priming study. European Journal of Social Psychology, 37, 1032-1045.
Paciotti, B., Richerson, P., Baum, B., Lubell, M., Waring, T., McElreath, R., Efferson, C., &
Edsten, E. (2011). Are religious individuals more generous, trusting, and cooperative?
An experimental test of the effect of religion on prosociality. Research in Economic
Anthropology, 31, 267-305.
Rousseau, D. M., Sitkin, S. B., Burt, R. S., & Camerer, C. (1998). Not so different after all: A
cross-discipline view of trust. Academy of Management Review, 23(3), 393-404.
Rowe, C. (1999). Receiver psychology and the evolution of multicomponent signals. Animal
Behaviour, 58(5), 921-931.
Ruffle, B. J., & Sosis, R. (2007). Does it pay to pray? Costly ritual and cooperation. The BE
Journal of Economic Analysis & Policy, 7(1).
Shariff, A. F., Norenzayan, A. (2007). God is watching you: Priming God concepts increases
prosocial behavior in an anonymous economic game. Psychological Science, 18(9),
803-809.
29
Smith, E., & Mackie, D. M. (2007). Social Psychology, (3rd ed.). New York: Psychology
Press.
Soler, M. (2012). Costly signaling, ritual and cooperation: evidence from Candomblé, an
Afro-Brazilian religion. Evolution and Human Behavior, 33(4), 346-356.
Sosis, R. (2003). Why aren’t we all hutterites? Human nature, 14(2), 91-127.
Sosis, R., & Bressler, E. R. (2003). Cooperation and commune longevity: A test of the costly
signaling theory of religion. Cross-Cultural Research, 37(2), 211-239.
Stigler, G. J. (1964). A theory of oligopoly. Journal of Political Economy, 72(1), 44-61.
Stock, J. H., & Watson, M. W. (2007). Introduction to Econometrics, (2nd ed.). New Jersey:
Pearson International.
Tan, J. H. W., & Vogel, C. (2008). Religion and trust: An experimental study. Journal of
Economic Psychology, 29(6), 832-848.
West, S. A., El Mouden, C., & Gardner, A. (2011). Sixteen common misconceptions about
the evolution of cooperation in humans. Evolution and Human Behavior, 32(4), 231262.
Willingham, D. T. (2007). Cognition: The thinking animal, (3rd ed.). New Jersey: Pearson
International.
World Values Survey Association (2009). World Values Survey 2005. Retrieved from
http://www.worldvaluessurvey.org.
30