Judgment and Decision Making, Vol. 15, No. 1, January 2020, pp. 1–6

Prosociality in the economic Dictator Game is associated with lessparochialism and greater willingness to vote for intergroup compromise
Mohsen Mosleh∗

Alexander J. Stewart†

Joshua B. Plotkin‡David G. Rand§

Abstract
Is prosociality parochial or universalist? To shed light on this issue, we examine the relationship between the amount ofmoney given to a stranger (giving in an incentivized Dictator Game) and intergroup attitudes and behavior in the context
of randomly assigned teams (a minimal group paradigm) among N = 4,846 Amazon Mechanical Turk workers. Using a
set of Dynamic Identity Diffusion Index measures, we find that participants who give more in the Dictator Game show lesspreferential identification with their team relative to the other team, and more identification with all participants regardless ofteam. Furthermore, in an incentivized Voter Game, participants who give more in the Dictator Game are more likely to support
compromise by voting for the opposing team in order to avoid deadlock. Together, these results suggest that – at least in thissubject pool and using these measures – prosociality is better characterized by universalism than parochialism.
Keywords: Prosociality, Dictator Game, Ingroup Bias, Intergroup Attitudes

1 Introduction

different populations have found that an individual’s choices
are correlated across various economic games that involve
paying costs to benefit others (i.e. the Dictator Game, Trust
Game, Prisoner’s Dilemma, Public Goods Game) (Böckler,
Tusche & Singer, 2016; Capraro, Jordan & Rand, 2014;
Littman et al., 2019; Reigstad, Strømland & Tinghög, 2017;
Yamagishi et al., 2013). Similarly, play in such economic
games has also been found to correlate with real-world
helping (Benz & Meier, 2008; Franzen & Pointner, 2013;
Peysakhovich, Nowak & Rand, 2014; Stoop, 2014). Thesefindings support the existence of a cooperative phenotype, inthat prosociality is not entirely context dependent but rather
seems to represent an underlying trait. Furthermore, it has
also been repeatedly observed that this cooperative phenotype does not extend to punishment - that is, people who are
more inclined to pay costs to help others are not typicallymore inclined to pay costs to punish others for being selfish(Böckler et al., 2016; Littman et al., 2019; Peysakhovich etal., 2014; Reigstad et al., 2017; Yamagishi et al., 2012).
Here, we probe another dimension of the cooperative
phenotype: how does prosociality relate to intergroup attitudes? Much theorizing in the social sciences (Aaldering,
Ten Velden, van Kleef & De Dreu, 2018; Böhm, Rusch, &Gürerk, 2016; de Dreu, 2010) sees prosociality as fundamentally parochial – that is, that prosociality is rooted in the tendency of people to favor members of their own group while
underweighting or ignoring harm to outsiders (SchwartzShea & Simmons, 1991). This tendency towards parochialism has been most famously demonstrated, for example, by“minimal group paradigm” experiments where participants
give more money to people who (ostensibly) prefer the same
abstract artist over those who prefer a different artist (Tajfel,
Billig, Bundy & Flament, 1971). Conversely, classical con-

The willingness to help others at a cost to oneself – often referred to as prosociality – is a central feature of human behavior. But prosociality seems to contradict both the economic
logic of rational self-interest and the evolutionary logic ofsurvival of the fittest, and it presents an enduring challenge
to economists and evolutionary game theorists. Thus, a great
deal of research across natural and social sciences has sought
to characterize prosocial behavior and explain its emergence.
One stream of such work has sought to provide an empirical definition of prosociality. This work explores theboundaries of prosociality by experimentally characterizing
the “cooperative phenotype,” identifying a cluster of prosocial behaviors that tend to co-occur. Several studies using
We acknowledge funding from the Defense Advanced Research Projects
Agency NGS2 program (grant D17AC00005; to all), the John Templeton
Foundation (to D.G.R.), the Army Research Office (grant W911NF–17–1–
0083; to J.B.P.) and the David & Lucile Packard Foundation (to J.B.P.).
The views, opinions, and findings expressed are those of the authors andshould not be interpreted as representing the official views or policies of the
Department of Defense or the US Government.
Copyright: © 2020. The authors license this article under the terms of
the Creative Commons Attribution 3.0 License.
∗ ORCID ID: 0000-0001-7313-5035. Sloan School of Management,
Massachusetts Institute of Technology, Cambridge, MA, USA. Email:mmosleh@mit.edu.
† ORCID ID: 0000–0001–5234–3871. Department of Biology, University of Houston, Houston, TX, USA.
‡ ORCID ID: 0000–0003–2349–6304. Department of Biology, University of Pennsylvania, Philadelphia, PA, USA.
§ ORCID ID: 0000–0001–8975–2783. Sloan School of Management,
Massachusetts Institute of Technology, Cambridge, MA, USA. Department
of Brain and Cognitive Sciences, Massachusetts Institute of Technology,
Cambridge, MA, USA.

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Judgment and Decision Making, Vol. 15, No. 1, January 2020

ceptions of altruism – dating back at least to the Enlightenment – invoke the principle of universalism, an “expanding
circle” whereby others are seen as worth of aid regardlessof their group membership, such that greater prosociality
should lead to less parochialism. Empirical studies aiming to differentiate between these accounts of prosociality
have thus far yielded mixed results. For example, different
studies have found an individual’s level of prosociality andtheir level of parochialism to be positively related (Abbink,
Brandts, Herrmann & Orzen, 2012; de Dreu, 2010), unrelated (Corr, Hargreaves Heap, Seger & Tsutsui, 2015), andnegatively related (Aaldering & Böhm, 2019; Fiedler, Hellmann, Dorrough & Glöckner, 2018; Thielmann & Böhm,
2016).
We aim to shed new light on this question by contributing more data regarding whether prosocial people are moreor less parochial. To do so, we use a classical “minimalgroups” paradigm in which participants are randomly assigned to meaningless teams (Tajfel et al., 1971), in order
to explore basic psychological parochialism rather than theidiosyncrasies of any particular intergroup conflict. Within
this paradigm, we assess parochialism in two different ways:(i) attitudinal measures of closeness with own team, otherteam, and all participants regardless of team; and (ii) a behavioral measure of willingness to vote for compromise withthe other team in an economic coordination game. We thencorrelate each of these measures with prosociality as measured by giving in an anonymous Dictator Game (DG), themost basic of the economic prosociality games shown tobe part of the cooperative phenotype (Peysakhovich et al.,2014).

2 Methods
Participants. Subjects were recruited from Amazon Mechanical Turk (N=4,846, 47% female, M age =32, 82% US
residence) to participate in an online experimental session.
Experiments were conducted from September 2017 throughMarch 2018. Each session of the experiment took up to 40
minutes. Participants in our study were paid a $3 show-up
fee plus a bonus of up to $2, depending on the outcome of
the game. These data were originally collected as part of a
research program that culminated in the studies described in
Stewart et al. (2019); however, this other research program
did not analyze the parochialism and prosociality measuresthat are the focus of the present paper. Furthermore, the various manipulations used in the prior work are not relevantto the current research question, and therefore we aggregate
over all experimental sessions and conditions in the present
analyses (our results are robust controlling for all manipulations/treatments in Stewart et al., 2019; see regression tablesin the Supplement).

Prosociality, parochialism, and intergroup compromise

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Parochialism/universalism measures. We used a minimal groups paradigm in which participants were randomly
assigned to either the yellow team or the purple team (immediately after they joined the experimental session, they
were informed to which team they were assigned and were
reminded of their assigned team throughout the game on the
top of their screen). Within this context, we examined both
attitudinal and behavioral measures of parochialism versus
universalism.
For our attitudinal measures, we examined the extent towhich participants identified with their own team, the otherteam, and all participants (both teams combined). We did sousing the Dynamic Identity Diffusion Index (DIFI) (Gómez
et al., 2011), a continuous identification measure that involves asking subjects to position a smaller circle representing oneself with respect to a bigger circle representing a
specified group. We used the distance between the centers of the two circles as our measure of identification; thedistance is inverted such that values range from −100 to
125, with −100 represents the least identification (greatest
distance) and 125 represents the highest identification (leastdistance). The circles were initialized to a value of −50. Subjects completed three such measures, asking them to position
themselves with respect to their own team, the other team,and the whole group (order randomized across subjects). To
measure attitudinal parochialism, we used the distance fromown team minus the distance from the opposing team. To
measure attitudinal universalism, we used the distance fromthe whole group.
For our behavioral measure, we examined participants’willingness to support intergroup compromise in the context
of an incentivized voter game (played in groups of 18–24
subjects, following the completion of the DIFI measures).
In the game, half of the players were on the yellow team andhalf were on the purple team. At any given time, each player
indicated an intention to either vote for yellow or purple.
Critically, players did not simply choose a color to vote for.
Instead, players’ votes were initialized as their assigned team,and then over the 4 minutes that the game lasted, each player
could dynamically change their intended vote at any time.
Furthermore, they were placed on a network and provided
real-time aggregated polling data indicating the fraction ofplayers in their network neighborhood intending to vote foryellow versus purple. Players were aware that polls only
show voting intentions of a subset of players (their neighbors)rather than the entire group. Thus, players could change
their voting intention in response to the information they
were given about how others planned to vote. A count-downtimer indicated the remaining time in the game. Each subject
was provided with real-time aggregated polling informationof the voting intentions of those subjects assigned to theirpolling group; their own current vote; and their assigned
team. A screenshot of the game interface is shown in Figure
1.

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Prosociality, parochialism, and intergroup compromise

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Figure 1: Screen-shot of player interface. During the voter game each player sees a screen reminding them of their assigned
team, their current vote, and the current state of the poll (both visually and in words). In addition, they are reminded that thepoll shows only a subset of the entire group’s voting intentions. Two colored buttons allow players to change their vote at any
time, with a single click.

Once the game ended, the final intention to vote selected byeach player was registered as his/her final vote. If a fractionof players greater than some pre-specified super-majority
threshold V (V>1/2) voted for one of the two colors, allmembers of the team corresponding to that color received
the maximum playoff B (B=$2) while all players in the otherteam received a lower payoff of b<B. If neither color received
enough votes to exceed the threshold V (V=60% or 70%
depending on the experimental condition and the portion of
the population from whom voting information is received;in 47% of sessions across all conditions this threshold wasmet), then all players received no payoff (an outcome werefer to as “deadlock”). In all experiments b>0 (b=$0.5-$1
depending on the experimental condition), which makes it
preferable (from a material payoff perspective) to reach aconsensus over ending up in deadlock.
To quantify players’ behavior in the voter game, we used
the model developed in Stewart et al. (2019). In this model(which was developed through a process of pilot testing andrefinement), the probability that a player selected the colorof the opposing team in a given timestep t is allowed to vary
based on the current state of the poll she is shown: whether
her team is winning (exceeding the supermajority V) in thepoll, the opposing team is winning in the poll, or deadlock is
occurring in the poll (neither color is above the supermajority
threshold). Furthermore, players have different probabilities
of voting for the opposing color in the early part of the gameversus the later part of the game. This results in a sixparameter strategy space [own team is winning, opposing
team is winning, deadlock] × [early phase of the game, latephase of the game]. For each player, these six values were
estimated based on her history of play in the game using
maximum likelihood estimation.1
1It is not possible to estimate all 6 values for all players – for example,
a player whose team was always winning in the poll will have missing data

As described in Stewart et al. (2019), there is a significant
relationship between players strategies and their associatedpolling information during the course of the game. Both in
the early and late stage of the game, almost all players intend
to vote for their assigned team when the poll they see suggests
their team is winning or that deadlock is occurring (whenthe poll projects deadlock, a player is more prone to votefor the opposing party late in the game, reflecting increased
urgency to reach some form of consensus). However, when
the poll suggests the opposing team is winning, many players
switch to voting for the opposing color both in the early andlate stage of the game – presumably in an effort to avoid
deadlock. Thus, we use a participant’s likelihood of voting
for the opposing color when the opposing team is winning asa measure of that participant’s willingness to compromise.
Voting for the opposing color can be seen as universalist,
because doing so reduces the chance of deadlock and thusincreases all players’ payoffs.2 Continuing to vote for yourown team’s color, conversely, can be seen as parochial, inthat it reduces the chance that the other team will – if one
cares about the relative payoffs of the two teams, then one
would prefer deadlock over the other team winning. Thus,
probability of voting for own versus opposing color provides
a behavioral measure of parochialism versus universalism;
and we obtain two such measures for each subject, one forthe early phase of the game and one for the late phase of thegame.
Prosociality measure. Following the end of the voter
game, after they were informed about the results of the game,
all subjects play a one-shot anonymous Dictator Game DG
with the following instruction: “Now that the main gamefor the other 4 strategy values.
2Voting for the opposing team’s color in this situation is also selfinterested.

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Figure 2: Parochialism and universalism as a function of DG giving. The size of the dots represents number of observations for each value of given in the DG. y axis shows average value of parochialism and universalism DIFI measures for allobservations of a given value of DG giving. Gray lines show 95% confidence internal based on the regression model fitted
on individual observations.

is over, you will do another interaction with a totally new
MTurk worker who did not play the earlier game. In thisinteraction, you are given an additional $0.40 towards yourbonus, and you decide how much (if any) to share withthe other person (who receives no bonus other than what
you give).” Then the subjects were asked to choose from{$0,0.05, . . . ,$0.40} to give in the DG. We used the amountgiven in the DG as our measure of prosociality.
Analysis. Unless otherwise noted, we used linear regressions with robust standard errors clustered on experimental
session (to account for the non-independence of observations
within the same session; see the code for details). We report
standardized betas (i.e. we z-score all variables, and reportresulting regression coefficients).

3 Results
We begin by confirming the expected relationship between
the attitudinal and behavioral measures of parochialism versus universalism. We find that the parochialism DIFI measure (i.e., the distance from assigned team minus the distance from opposing team) is significantly negatively related
to compromise (i.e., probability of voting for the opposing
color) in both the early β=−0.052, p=0.016) and late phase of
the voter game β=−0.064, p=0.002). Looking separately at

the measures of identification with own team and identification with the other team, we find that the negative relationshipbetween parochialism DIFI and compromise is mainly driven
by a positive relationship between compromise and identification with the other team β=0.065, p=0.007 in early stage ofthe game and β=0.081, p<0.001 in the later stage of the game)as opposed to by identification with own team β=−0.025,
p=0.242 in early stage of the game and β=−0.041, p=0.054
in the late stage of the game). There is also no interaction
between own team DIFI and other team DIFI β=−0.014,
p=0.565 in early stage of the game and β=−0.031, p=0.210
in the late stage of the game). Conversely, the universalism DIFI measure (i.e., the distance from the whole group)
is significantly positively related to compromise β=0.044,
p=0.054 in the early stage and β=0.057, p=0.024 in the latestage of the voter game).3
We now turn to our main question: Is prosociality
parochial or universal? If prosociality is parochial, we
should then expect giving in the DG with a completely anonymous stranger be positively related to the parochialism DIFIand negatively related to the universalism DIFI and the two
measures of compromise in the voter game. Conversely, if
prosociality is universalist, we should then expect DG giving be negatively related to the parochialism DIFI measure
3We note that the parochialism DIFI measure and the universalism DIFI
measure are actually positively correlated with each other, (pairwise correlation, r = 0.109, p<0.001).

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Figure 3: Compromise measures as a function of DG giving. The size of the dots represents number of observations foreach value of giving in the DG. y axis shows average value of compromise measures in the early and late phase of the game,for all observations of a given value of DG giving. Gray lines show 95% confidence internal based on the regression model
fitted on individual observations.

and positively related to the universalism DIFI measure andthe two measures of compromise in the voter game. We
find a consistent pattern of prosociality being universal: DG
giving is significantly negatively related to the parochialism
DIFI measure β=−0.061, p<0.001; Figure 2). Giving in the
DG is significantly positively related with both identification
with own team β=0.061, p<0.001) and identification with theother team β=0.129, p<0.001), with the negative relationshipwith parochialism resulting from the association with otherteam DIFI being stronger than own team DIFI. The positive
association with both own and other team DIFIs is further
evidence of prosociality being universal. Furthermore, wefind that DG giving is significantly positively related withthe universalism DIFI β=0.143, p<0.001; Figure 2).
Finally, DG giving is significantly positively related to theprobability of compromise in both early β=0.050, p=0.017)
and late β=0.077, p=0.002) phase of the voter game (Figure3). All results are qualitatively equivalent when including
age, gender, education, country of residence, and income, as
well as dummies for the outcome of the voter game and theexperimental treatments from which the data came the (seeSupplement for complete regression tables). The positive relationship between compromise and DG giving supports theinterpretation of compromise being driven by prosociality,
rather than by self-interest.

4 Discussion
We have provided evidence that the cooperation phenotype
extends to intergroup attitudes and behavior. In particular,
our results suggest that the prosocial tendencies capturedby the cooperative phenotype are universalist rather thanparochial. Furthermore, our novel behavioral measure basedon our voter game provides a window not just into one’s
own actions, but the decisions one makes about whether tosupport compromise at the level of the group. Our results
therefore contribute to the psychology of prosociality.
Of course, our investigation also has important limitations.
First, we used data collected on Amazon Mechanical Turk,
mostly from American subjects. Thus, it is important for
future work to test how our findings generalize to other populations, and to other tasks/measures. Furthermore, we used
minimal groups, rather than groups with real-world relevance. Thus, future research should test the generalizabilityof our results to more salient social groups. Additionally,
here we measured unconditional prosociality using a single measure, namely giving in the DG with an anonymous
player. Further research should study how our results generalize when considering different other measures that allow
one to distinguish different “types” of pro-social preferences(Charness & Rabin, 2002; Murphy, Ackermann & Handgraaf, 2011). We hope that the observations made here help
advance our understanding of why people are willing to pay
costs to help others.

Judgment and Decision Making, Vol. 15, No. 1, January 2020

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