jou rn al h om epa g e: www.elsev ier .com/ locate /soceco
roup composition and conditional cooperation
lexander Smithepartment of Social Science and Policy Studies, Worcester Polytechnic Institute (WPI), Social Science and Policy Studies, 100 Institute Road, Worcester, MA 01609, United States
r t i c l e i n f o
rticle history:eceived 7 September 2010eceived in revised form 4 April 2011ccepted 14 April 2011
EL classification:9041
a b s t r a c t
This paper examines how group composition affects conditional cooperation in public good games. Iden-tity was created using a team-building activity and subjects were assigned to groups of six with varyingproportions of subjects from two teams. Majority members contributed more to the public good thanminority members. However, contributions were mainly related to beliefs about the contributions ofothers, especially others from the same teams, rather than minority/majority status.
eywords:ublic good gameroup compositiononditional cooperation
dentityeciprocity
. Introduction
Public goods like environmental quality and law enforcementrovide a wide variety of welfare benefits. Unfortunately, someommunities are better at providing public goods than others.or example, population heterogeneity such as income inequalitynd ethnic diversity is associated with decreased local governmentpending on public services including education, roads, sewers andaste removal (Alesina et al., 1999). In less-developed countries,
unding for basic infrastructure including schools and wells is lowern communities that are ethnically diverse (Miguel and Gugerty,005). Relatedly, studies of individual behaviour show that hetero-eneity is associated with decreased propensities of volunteeringor non-profit organizations (Clark and Kim, 2009; Smith, 2010) andensus response rates (Vigdor, 2004), which are important deter-inants of federal transfers to communities.Though some people might be more likely to cooperate in the
rovision of public goods when they know that others are coop-rating, social effects are typically omitted from empirical papersn heterogeneity and cooperation. Estimates tend to be biased byultiple endogeneity problems (Manski, 1993, 2000). However,
ecent evidence from public good game experiments suggests thatooperation is conditional, with people contributing more whenhey believe others are contributing high amounts (Croson, 2007;
Fischbacher and Gaechter, 2010; Fischbacher et al., 2001). Onestudy (Croson, 2007) finds much stronger support for reciprocity asan explanation of contribution behaviour than for altruism, wherereciprocity is captured by the relationship between contributionsand beliefs. Another (Fischbacher and Gaechter, 2010) shows thatcontributions decline with repetition because of preferences forcontributing less than others are believed to be contributing. Bothstudies suggest that beliefs have an important role in determiningcooperation.
In our experiment, we created identity using a team-buildingactivity. Subjects were then assigned to groups of six with varyingproportions of subjects from two teams. Groups had either five sub-jects from one team and one from the other, four subjects from oneteam and two from the other, or three subjects from each team.Within these groups, subjects played a repeated voluntary con-tribution mechanism (VCM) linear public good game. In additionto making contribution decisions, subjects reported their beliefsabout the contributions of other subjects from their teams andfrom the other teams. Repetition of the game, with re-matchingin each round, meant that subjects served as majority and minoritymembers, and allowed for the updating of beliefs.
Using an experiment has three primary benefits over tradi-tional empirical methods. The first is getting a precise and accuratemeasure of cooperation, something hard to obtain from naturally
occurring data. When considering a parent volunteering at theirchild’s school, for example, it is difficult distinguishing betweenthe private and social benefits of their actions. The second benefitis that social effects are studied using beliefs about the cooperation
had to interact while answering the quiz. The aim was devel-oping a sense of common identity among the members of eachteam.2 Members of teams answering at least 12 of the 20 questions
A. Smith / The Journal of Soc
f others, avoiding the potential endogeneity issues associated withsing the actions of others. Finally, group composition is manipu-
ated exogenously, addressing the problem that in the real world,eople choose the community in which they live and their peers,
ncluding friends and co-workers.In the experiment, majority members contributed more than
inority members. However, contributions were mainly related toeliefs about the contributions of others, especially others fromhe same teams, rather than minority/majority status. As far aseliefs about the contributions of group members from the othereams, minority members made contributions increasing in theireliefs about the contributions of the majority, but the contribu-ions of majority members were unrelated to their beliefs about the
inority. Beliefs were mainly a function of experience in previousounds.
The results have important implications for the economics ofrganizations. First, workers identifying with a minority of theiro-workers have greater incentives for free-riding than workersdentifying with the majority, highlighting the importance of build-ng a common identity within organizations (Akerlof and Kranton,005). Among like-minded workers subscribing to the same orga-izational goals, goals can provide intrinsic motivation (Besleynd Ghatak, 2005), which is especially effective in the long runompared to extrinsic motivation provided by monetary rewardsBenabou and Tirole, 2003). Unfortunately, the results also suggestn economic rationale for discriminatory hiring practices. Potentialorkers who would identify with a minority of existing workers
re more likely to free-ride, giving managers greater incentive foriring people who would “fit in” with the current workforce.
The findings contribute to the literature on conditional cooper-tion, previously focusing on homogeneous groups (Croson, 2007;ischbacher and Gaechter, 2010; Fischbacher et al., 2001), and sug-est an explanation for why heterogeneity decreases cooperationAnderson et al., 2008; Castro, 2008; Oxoby and Spraggon, 2006;uffle and Sosis, 2006). Cooperation is closely related to beliefsbout the cooperation of others, which are adversely affected byeterogeneity.
The remainder of the paper is organized as follows. Section 2iscusses previous experiments on cooperation and heterogene-
ty. Section 3 describes the experiment and motivates hypotheses.ection 4 presents results and section 5 concludes.
. Related literature
In standard VCM linear public good games, subjects receivendowments and are randomly assigned to groups of n mem-ers. They choose contributions to a group account and the sumf the contributions is multiplied by ̨ ∈
(1/n, 1
), determining the
mount returned to each subject. The Nash equilibrium (underhe assumption of individual wealth maximization) is contributingothing, but total wealth is maximized when all subjects contributes much as possible.
Contributions typically average about 40% (see Ledyard (1995)or a survey). The results are robust, but there are differentxplanations for the cooperation. Andreoni examines the roles oftrategy (1988) and confusion (1995), concluding that altruism isn important factor. More recent research, however, argues thatontributions are mainly due to reciprocity. Many subjects areconditional cooperators,” making contributions conditional on theontributions of others when given the opportunity (Fischbachert al., 2001). In other experiments, contributions are increasing in
eliefs about the contributions of others (Croson, 2007; Fischbachernd Gaechter, 2010).
With respect to heterogeneity, there are many ways of creat-ng differences among subjects, including varying ̨ (Fisher et al.,
nomics 40 (2011) 616– 622 617
1995), show-up fees (Anderson et al., 2008) and endowments(Buckley and Croson, 2006; Chan et al., 1996; Cherry et al., 2005).Some authors examine the effects of identity. For example, Ruffleand Sosis (2006) find that members of the Israeli kibbutz, a soci-ety known for being universal cooperators, are more cooperativewhen grouped with each other than with city residents. A simi-lar experiment by Castro (2008) reports lower contributions whenBritish and Italian subjects are grouped together compared towhen they are in groups of subjects with the same national-ity.
Germane to experiments on heterogeneity, creating and pro-moting a common identity among subjects increases cooperation(Eckel and Grossman, 2005). Such findings are part of a growingeconomics literature on identity with origins in social psychology.Tajfel and Turner (1979) develop a theory of identity consisting ofthree components: categorization, identification and comparison.Categorization is the act of assigning people to groups, iden-tification is recognizing the groups to which one belongs andcomparison is the process of measuring one’s group(s) againstother groups. Regarding the effects of identity, research on inter-group discrimination argues that biases are moreso related tofavoritism toward others with the same affiliations than hos-tility toward people with different affiliations (Brewer, 1999).In economics, Akerlof and Kranton (2000) propose that identityaffects behaviour because people conform to the norms of thesocial groups with which they are affiliated, suggesting that iden-tity can foster cooperation in organizations (Akerlof and Kranton,2005) if members of organizations perceive themselves as socialgroups.
Cooperation also occurs in many environments other than pub-lic good games. For example, in a third-party punishment gameplayed between members of two tribal groups from Papua NewGuinea, dictators making unfair allocations are punished moreseverely when the punisher is from the same tribe as the recipi-ent than when the punisher is from the other tribe (Bernhard et al.,2006). In prisoner’s dilemma games played between members ofthe Swiss army, more cooperation occurs among officers from thesame platoons than among officers from different platoons (Goetteet al., 2006). Both results are consistent with findings that altru-ism and reciprocity are stronger among subjects sharing affiliations(Chen and Li, 2009), and that group membership and salience affectpreferences over outcomes (Charness et al., 2007).
3. The experiment
The experiment was a repeated public good game elicitingbeliefs and manipulating group composition. Sessions began bycreating identity using a team-building activity.1 Subjects wererandomly divided into two “teams” of six as they arrived at theexperiment. Teams were sent to separate rooms and asked toanswer quizzes consisting of 20 questions. The quizzes involvedunscrambling letters making words, determining the next numberin a sequence of numbers, matching celebrity stage names to realnames and matching three-letter airport codes to the cities the air-ports serve. Each team submitted one answer sheet, so members
1 Subjects could have simply been labeled as members of Teams 1 or 2, but pre-vious research finds that strong mechanisms such as group tasks have larger effectsof subsequent behaviour (Eckel and Grossman, 2005).
2 The process was similar to the identity-building activity used by McLeish andOxoby (2007).
6 io-Economics 40 (2011) 616– 622
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Table 1Summary statistics for the amounts contributed.
orrectly each received $5, otherwise they would have receivedothing.3
Following the quiz, subjects played 12 rounds of the public goodame in groups of six using endowments of $10. In Treatment 1,roups consisted of five subjects from one team and one from thether. In Treatment 2, groups had four subjects from one team andwo from the other, and in Treatment 3, groups consisted of three
embers from each team. A subject’s type was the number of sub-ects in her group from her team. Thus, Treatment 1 consisted ofypes 1 and 5 subjects, Treatment 2 of types 2 and 4 subjects, andreatment 3 of type 3 subjects.
Groups were re-matched at the start of each round. In theessions of Treatment 1, subjects were type 1 twice and type 50 times over the 12 rounds of the experiment. In Treatment 2,ubjects were type 2 four times and type 4 eight times, and inreatment 3, subjects were type 3 in every round. The proba-ility that a subject was re-matched with another subject fromer team was highest in Treatment 1, followed by Treatment 2nd then Treatment 3, possibly leading to spurious findings if theotential for reputation-building affects cooperation.4 However, aeta-analysis by Andreoni and Croson (2008) reports that con-
ributions are often similar under partner and stranger matching.hen contributions differ between the two matching schemes,
hey are higher under stranger matching just as often as they areigher under partner matching, suggesting that subjects do notngage in reputation-building in single finitely repeated publicood games.5
The re-matching incorporated a with-in subject design, withubjects in Treatment 1 serving as types 1 and 5 subjects,nd subjects in Treatment 2 as types 2 and 4 subjects. With-n subject comparisons are used for examining the effects of
inority/majority status. Subjects were informed of their types,ndicating minority/majority status, before making any decisions.
In each round, subjects chose contributions to the “communityccount” and guessed the average contributions of other groupembers from their teams (their “same-team” beliefs) and from
he other teams (their “other-team” beliefs).6,7 The sum of contri-utions was multiplied by 0.33, determining the amount returnedo each subject. Payoffs were the amounts subjects kept initiallylus their shares of the community account:
ir = 10 − cir + 0.336∑
j=1
cjr (1)
here cir is the contribution of subject i in round r and the summa-ion of contributions is taken over the six group members indexedy j. At the end of each round, subjects were informed of their pay-ffs and regarding the accuracy of their beliefs. Incentivizing the
licitation of beliefs, subjects received $1 for guesses within $1f the actual amounts, making earnings the sum of payoffs fromhe public good game and up to $2 for correct guesses.8 After the
3 All teams were successful on the quiz, giving all subjects the same accumulatedarnings when playing the public good game.4 Subjects were matched with others from their teams 40, 32 and 24 times out of
0 in Treatments 1, 2 and 3.5 Zelmer (2003) also reports results on partner versus stranger matching.6 Type 1 subjects were not asked their same-team beliefs. None of their other
roup members were from the same teams as them.7 Recent evidence suggests that eliciting beliefs affects behaviour (Gaechter
nd Renner, 2010). We conjecture that any such effects are constant across thereatments of our experiment. However, to our knowledge, there is no literaturexamining this issue.8 The incentive scheme for eliciting beliefs was chosen for its simplicity and ease
f understanding even though it was not strictly incentive compatible. Measure-ent error would lead to underestimating the strength of the relationships between
ontributions and beliefs. The results suggest that this was not a problem.
12 rounds, one round was randomly selected for determining finalearnings, which were the sum of $5 payments for success on thequiz and earnings in the randomly selected round. Earnings werenot accumulated across rounds; subjects played each round usingendowments of $10.
3.1. Hypotheses
Hypotheses are motivated by altruism (Becker, 1974) and reci-procity (Dufwenberg and Kirchsteiger, 2004; Rabin, 1993). First,suppose that altruism is an important determinant of cooperationand that subjects are more altruistic toward others from their teamsthan toward others from the other teams. Subjects will make highercontributions when more of their group members are from theirteams, suggesting that:
Hypothesis 1. Majority members contribute more than minoritymembers.
Hypothesis 1 is motivated by research on the role of altruism inpublic good games (Andreoni, 1988, 1995) and is consistent withfindings that subjects are more generous toward others with whomthey share affiliations (Chen and Li, 2009).
Next, suppose that reciprocity is strong among subjects fromthe same teams. Subjects will make contributions increasing intheir beliefs about the contributions of others from their teams. Ifreciprocity is weaker among subjects from different teams, beliefsabout the contributions of those from other teams will have smallereffects. Thus:
Hypothesis 2. Contributions are increasing in same-team beliefs,and to a lesser degree, in other-team beliefs.
Hypothesis 2 is consistent with experiments reporting thatsubjects make contributions increasing in their beliefs about thecontributions of others (Croson, 2007; Fischbacher and Gaechter,2010) and that reciprocity effects are stronger among subjects shar-ing affiliations than among subjects with different affiliations (Chenand Li, 2009).
4. Results
The experiment was programmed and conducted with theexperiment software z-Tree (Fischbacher, 2007) at the Universityof Calgary’s Behavioural and Experimental Economics Laboratoryusing subjects recruited from the undergraduate student body.There were three sessions of each of the three treatments, for atotal of nine sessions and 108 subjects. Sessions lasted about 75 minand average earnings were $18.90, with a standard deviation of$3.44. The minimum earnings were $8.67 and the maximum was$29.33.
The 108 subjects made 12 contribution decisions, giving 1296
observations. Mean contributions (measured in dollars) from eachround are plotted by treatment and subject type in Figs. 1 and 2.Summary statistics for the amounts contributed are given inTable 1. The pattern of contributions across treatments is suggestive
A. Smith / The Journal of Socio-Economics 40 (2011) 616– 622 619
Fig. 3. Scatterplot of contributions on same-team beliefs.
02
46
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0 2 4 6 8 10
between subjects and any autoregressive component in the errorstructure of the multiple observations from each subject.13 Theresults are reported in Table 2.
10 The subject type dummies capture the effects of group composition andminority/majority status. Independently identifying each effect requires imposingadditional structure on the model, such as assuming contributions are linear in groupcomposition and minority/majority status.
11 Variable definitions are given in Appendix A.12 There is no effect of same-team beliefs for type 1 subjects. They had no same-
Round
Fig. 2. Mean contributions (by type).
f a negative relationship between cooperation and polarizationMontalvo and Reynal-Querol, 2005; Reynal-Querol, 2002), givenhat polarization was lowest in Treatment 1, followed by Treat-
ent 2 and then Treatment 3.9 As a result, we study the effectsf minority/majority status using comparisons within treatments,voiding the confounding effects of variation in group composi-ion (polarization) across treatments. A Wilcoxon signed rank testp = 0.03), based on six independent observations (three sessionsach of Treatments 1 and 2), indicates that majority memberstypes 4 and 5 subjects) contribute more than minority mem-ers (types 1 and 2 subjects), consistent with Hypothesis 1. As fars the size of the differences, majority members in Treatments 1nd 2 contributed mean amounts 1.56 and 0.93 higher than theirinority member counterparts. This is economically significant
ecause each additional dollar contributed increased total wealthy a dollar. The contributions of type 3 subjects are shown foromparison.
Understanding the role of beliefs is important for explaining dif-erences between minority and majority members. Figs. 3 and 4lot contributions on same-team and other-team beliefs, where theize of each bubble is proportional to the number of observationsith the relevant set of coordinates. Contributions and same-team
eliefs are highly correlated (Spearman’s � = 0.62, p < 0.01), withany observations lying on or near the 45◦ line. The correlation
etween contributions and other-team beliefs is lower (Spearman’s = 0.31, p < 0.01), but still indicative of a positive relationship. Theorrelations support Hypothesis 2, that contributions are increasing
n same-team beliefs, and to a lesser degree, in other-team beliefs.
Regression analysis estimates the effects of beliefs. The contri-ution of each subject in each round is regressed on subject type
9 Note that Reynal-Querol (2002) and Montalvo and Reynal-Querol (2005) studyolarization leading to conflict over resources and/or rent-seeking. Our experimentid not include conflict of this nature. The conflict was solely the dilemma betweenooperating and free-riding.
Other−Team Belief
Fig. 4. Scatterplot of contributions on other-team beliefs.
dummy variables, the round and beliefs about the average con-tributions of other group members from the same team and fromthe other team.10,11 The effects of repetition and beliefs are esti-mated separately for each subject type using interaction effects.12
The cross-sectional time series model is estimated using feasiblegeneralized least squares (fGLS), accounting for heteroskedasticity
team beliefs.13 A Tobit model, accounting for the censored nature of the data, gives similar
results. Specifically, the estimates are qualitatively the same, but slightly larger,with somewhat higher statistical significance. As far as random and fixed effectsmodels, a Hausman test (p = 0.19) fails to reject the null hypothesis that the randomeffects model is unbiased. The random effects model with standard errors clus-tered by session gives very similar results to the ones we present, but finds slightlyhigher statistical significance for some of the variables. In addition to being themore conservative in terms of significance, the model presented can be estimatedwhile suppressing the regression constant, so that an intercept is estimated for eachsubject type and choosing a reference group is not necessary.
620 A. Smith / The Journal of Socio-Economics 40 (2011) 616– 622
using a team-building activity and subjects were assigned to groupsconsisting of varying proportions of subjects from each team. Inaddition to making contribution decisions, subjects reported their
16 Subjects knew act−1 and acot−1 because they were informed of the average con-tributions of their other group members from the same teams and from the other
�2 4472
** Significance at 5%.*** Significance at 1%.
Same-team beliefs have large effects, especially for majorityembers (types 4 and 5 subjects), for whom unit increases in
ame-team beliefs are associated with nearly one unit increases inontributions. The effects of same-team beliefs are larger than theffects of other-team beliefs for all subject types (t-test p < 0.01 invery case). Regarding other-team beliefs, the effects vary accord-ng to subject type. For minority members (types 1 and 2 subjects),ontributions are positively related to other-team beliefs, wheres for majority members (types 4 and 5 subjects), the relationships not significant (economically or statistically). Thus, other-teameliefs have significant effects only if the group includes a sufficientumber of members from the other team. Specifically, if the group
ncludes three or more members from the other team, other-teameliefs matter; otherwise, they do not. For subject types 2 and 3,he results are consistent with Hypothesis 2, that contributions arencreasing in same-team beliefs, and to a lesser degree, in other-eam beliefs. For subject types 4 and 5, contributions are increasingn same-team beliefs, but not in other-team beliefs. The effects ofepetition are small for all subject types.
Returning to the effects of minority/majority status, the sub-ect type coefficients indicate that being a minority member inreatments 1 or 2 was associated with contributing 0.41 or 0.26ore than the majority members. However, the differences are
mall in magnitude and not statistically significant (t-test p = 0.59nd 0.50), contrasting the findings from the previously reportedon-parametric test. The discrepancy is because of the differingethodologies. The non-parametric test does not control for differ-
nces in beliefs, where as the regression analysis does, suggestinghat differences between minority and majority members areue to differences in beliefs rather than minority/majority statuser se.
Focusing on beliefs, same-team beliefs are regressed on subjectype dummy variables, the round and the contributions of other
roup members from previous rounds.14 The results are reported inable 3.15 Specification (1) regresses same-team beliefs on subjectype dummies, the round and two variables capturing the con-
14 Observations from type 1 subjects are omitted because they had no same-teameliefs.15 We once again present results estimated by fGLS, but Tobit, random and fixedffects models give very similar estimates.
*** Significance at 1%.* Significance at 10%.
Standard errors in parentheses.
tributions of other group members from the previous round. Thevariable act−1 is the average contribution of other group membersin the previous round of the subject’s current type. The variableacot−1 is the average contribution of other group members inthe previous round of the type other than the subject’s currenttype.16 For example, suppose a subject was type 4 in round 8 andhad been type 2 in round 7. In round 8, act−1 was the averagecontribution of the subject’s type 4 group members in round 7and acot−1 was the contribution of the other type 2 member inround 7.17
The subject type coefficients have a large range, from 2.31 to3.49. An F-test of the null hypothesis that the four coefficients areequal is significant at 1%, suggesting that the effects of subject typeare statistically significant. Repetition, on the other hand, does nothave an especially large effect. The coefficients on act−1 (0.35) andacot−1 (0.06) indicate that subjects believed others would makecontributions increasing in the contributions of previous subjectsof the same type, and that the contributions of previous subjects ofthe other type had much smaller effects.18
The additional lags of the variable act included in specification(2) improve the model’s fit. In addition, the significance of the dif-ferences between the subject type coefficients decreases (p = 0.05),with the coefficients now ranging by only 0.26, compared to 1.18in specification (1). Finally, repetition has an even smaller effect,suggesting that after sufficient experience, same-team beliefs arerelated mainly to the contributions of previous subjects of the sametype.19
5. Conclusions
In this paper, we examine how group composition affects con-ditional cooperation in public good games. Identity was created
teams at the end of each round.17 If the subject was type 2 in round 7, her group had only one type 2 member other
than her. acot−1 was the average amount contributed by that one other person, orsimply the amount the person contributed.
18 A supplementary regression (not shown, but available upon request) adds asecond lag of the variable acot to specification (1). The effect is not significant.
19 The analysis of other-team beliefs is similar. Including variables capturing onlycontributions from the previous round, differences between subject types are largein magnitude. Including additional lags of previous contributions, other-team beliefsare primarily a function of the contributions of previous subjects of the same typeand differences between subject types diminish.
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A. Smith / The Journal of Soc
eliefs about the contributions of other subjects from their teamsnd from the other teams.
Majority members contributed more than minority members.owever, decisions were mainly related to beliefs about the con-
ributions of others, rather than minority/majority status. Forxample, contributions were increasing in beliefs about the con-ributions of other group members from the same teams. As fars beliefs about the contributions of group members from thether teams, the contributions of minority members were increas-ng in beliefs about the contributions of majority members, buthere was no significant relationship between the contributions
ajority members and beliefs about the minority, suggesting thatonditional cooperation among subjects with different affiliationsepends on the proportion of group members with the differingffiliation.
The results have important implications for policy. First, peo-le are more likely to cooperate in the provision of public goods
n their communities when identifying with a majority of the res-dents. Second, insofar as beliefs about the actions of others mightffect behaviour, it is the choices of similar individuals influenc-ng the decisions people make. Thus, public campaigns aimed atncreasing cooperation such as volunteering and charitable givingave the potential for being successful. The key is emphasizing theositive choices of people with whom the target audience relates.or example, promoting the volunteering of young people is a gooday of encouraging more young people to volunteer.
Finally, the strong relationship between cooperation and beliefsbout the cooperation of others with the same affiliations highlightshe importance of building common identities within organizationsAkerlof and Kranton, 2005). When people perceive themselves as
embers of the same social groups, the effects of small amounts ofdditional cooperation can propagate, inducing norms of increasedooperation throughout the organization.
cknowledgements
The author thanks John Boyce, Rachel Croson, Subhasish Dugar,obert Gazzale, Stuart Mestelman, Robert Oxoby, Jennifer Win-er, the anonymous referees and participants of the 2009 Canadianconomics Association meetings in Toronto and Economic Sciencessociation meetings in Tucson for excellent comments, sugges-
ions and encouragement.
ppendix A.
See Table A.1.
able A.1ariable definitions.
Variable Definition
type1 = 1 if subject is type 1; 0 otherwisetype2 = 1 if subject is type 2; 0 otherwisetype3 = 1 if subject is type 3; 0 otherwisetype4 = 1 if subject is type 4; 0 otherwisetype5 = 1 if subject is type 5; 0 otherwiseround = the round of the game (1–12)beliefst = the subject’s belief about the average contribution of
other group members from the same team as the subject(measured in $)
beliefot = the subject’s belief about the average contribution ofother group members from the other team (measured in $)
act−1 = the average amount contributed by the subject’s othergroup members in the previous round of the subject’s
current type (measured in $)
acot−1 = the average amount contributed by the subject’s othergroup members in the previous round of the type otherthan the subject’s current type (measured in $)
nomics 40 (2011) 616– 622 621
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