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Trust, Truth, Status and Identity: An Experimental Inquiry

Jeffrey V. Butler
Published Online: 2014-02-19 | DOI: https://doi.org/10.1515/bejte-2013-0026


To investigate how group-contingent non-pecuniary preferences are affected when one group occupies a position of higher status than another group, experimental participants were divided into two trivially distinct groups and then one of the groups was randomly assigned “high status.” Control sessions were also conducted in which no status distinction was introduced. In all sessions, participants subsequently played two games governed by distinct social norms: a trust game and a cheap talk game where lying was possible. In the control sessions, norm compliance was higher in same-group interactions, consistent with previous research demonstrating that normative obligations are often parochial. In treatment sessions, parochialism vanished and was replaced by noblesse oblige: members of high status groups exhibited more norm compliance in all of their interactions. Finally, in game roles not governed by an unambiguous social norm, identity had no direct impact on behavior. Considered together, the results suggest that the channel through which social identity directly impacts behavior is norm compliance and that the nature of this impact depends crucially on the relationship between involved groups.

Keywords: identity; status; social norm; experiment; group


  • Akerlof, G. 1980. “A Theory of Social Custom, of Which Unemployment May Be One Consequence.” Quarterly Journal of Economics 94:749–75.CrossrefGoogle Scholar

  • Akerlof, G. A., and R. E. Kranton. 2000. “Economics and Identity.” The Quarterly Journal of Economics 115:715–753.CrossrefGoogle Scholar

  • Ball, S., and C. Eckel. 1998. “The Economic Value of Status.” Journal of Socio-Economics 27:495–514.CrossrefGoogle Scholar

  • Ball, S., C. Eckel, P. Grossman, and W. Zame. 2001. “Status in Markets.” Quarterly Journal of Economics 116:161–88.CrossrefGoogle Scholar

  • Banfield, E. C. 1958. The Moral Basis of a Backward Society. Glencoe, IL: The Free Press.Google Scholar

  • Battigalli, P., and M. Dufwenberg. 2007. “Guilt in Games.” American Economic Review 97:170–6.CrossrefGoogle Scholar

  • Ben-Ner, A., B. P. McCall, M. Stephane, and H. Wang. 2009. “Identity and in-Group/Out-Group Differentiation in Work and Giving Behaviors: Experimental Evidence.” Journal of Economic Behavior and Organization 72:153–70.Web of ScienceCrossrefGoogle Scholar

  • Benjamin, D., J. Choi, and A. J. Strickland. 2010. “Social Identity and Preferences.” American Economic Review 100:1913–28.CrossrefGoogle Scholar

  • Berg, J., J. Dickhaut, and K. McCabe. 1995. “Trust, Reciprocity and Social History”. Games and Economic Behavior 10:122–142.CrossrefWeb of ScienceGoogle Scholar

  • Bernhard, H., U. Fischbacher, and E. Fehr. 2006. “Parochial Altruism in Humans.” Nature 442:912–15.CrossrefPubMedGoogle Scholar

  • Bolton, G. E., and A. Ockenfels. 2000. “ERC: A Theory of Equity, Reciprocity, and Competition.” The American Economic Review 90:166–93.CrossrefGoogle Scholar

  • Brandts, J., and G. Charness. 2011. “The Strategy versus the Direct-Response Method: A First Survey of Experimental Comparisons.” Experimental Economics 14:375–98.CrossrefWeb of ScienceGoogle Scholar

  • Brown, R. 2000. “Social Identity Theory: Past Achievements, Current Problems and Future Challenges.” European Journal of Social Psychology 30:745–78.CrossrefGoogle Scholar

  • Butler, J. V., P. Conzo, and M. Leroch. 2013. “Social Identity and Punishment.” EIEF Working Paper No. 1316.Google Scholar

  • Butler, J. V., P. Giuliano, and L. Guiso. 2012. “Trust and Cheating.” NBER Working Paper No. 18509.Google Scholar

  • Capra, M. 2004. “Mood-Driven Behavior in Strategic Interactions.” American Economic Review 94:367–71.CrossrefGoogle Scholar

  • Charness, G., and M. Dufwenberg. 2006. “Promises and Partnership.” Econometrica 74:1579–601.CrossrefGoogle Scholar

  • Charness, G., L. Rigotti, and A. Rustichini. 2007. “Individual Behavior and Group Membership.” American Economic Review 97:1340–52.Web of ScienceCrossrefGoogle Scholar

  • Chen, R., and Y. Chen. 2011. “The Potential of Social Identity for Equilibrium Selection.” American Economic Review 101:2562–89.CrossrefWeb of ScienceGoogle Scholar

  • Chen, Y., and X. Li. 2009. “Group Identity and Social Preferences.” American Economic Review 99:431–57.Web of ScienceCrossrefGoogle Scholar

  • Chen, Y., T. X. Liu, S. X. Li, and M. Shih. forthcoming. “Which Hat to Wear? Impact of Natural Identities on Coordination and Cooperation.” Games and Economic Behavior.Web of ScienceGoogle Scholar

  • Crawford, V. P., U. Gneezy, and Y. Rottenstreich. 2008. “The Power of Focal Points Is Limited: Even Minute Payoff Asymmetry May Yield Large Coordination Failures.” American Economic Review 98:1443–58.CrossrefWeb of ScienceGoogle Scholar

  • Danziger, S., J. Levav, and L. Avnaim-Pesso. 2011. “Extraneous Factors in Judicial Decisions.” Proceedings of the National Academy of Sciences 108:6889–92.Web of ScienceCrossrefGoogle Scholar

  • Eckel, C., and P. Grossman. 2005. “Managing Diversity by Creating Team Identity.” Journal of Economic Behavior and Organization 58:371–92.CrossrefGoogle Scholar

  • Fehr, E., and K. Schmidt. 1999. “A Theory of Fairness, Competition, and Cooperation.” The Quarterly Journal of Economics 114(3):817–68.CrossrefGoogle Scholar

  • Fershtman, C., and U. Gneezy. 2001. “Discrimination in a Segmented Society: An Experimental Approach.” Quarterly Journal of Economics 116:351–7.CrossrefGoogle Scholar

  • Fischbacher, U. 2007. “Z-Tree: Zurich Toolbox for Ready-Made Economic Experiments.” Experimental Economics 10:171–8.CrossrefGoogle Scholar

  • Gneezy, U. 2005. “Deception: The Role of Consequences.” American Economic Review 95:384–94.CrossrefGoogle Scholar

  • Guala, F., L. Mittone, and M. Ploner. 2013. “Group Membership, Team Preferences, and Expectations.” Journal of Economic Behavior and Organization 86:183–90.Web of ScienceCrossrefGoogle Scholar

  • Guiso, L., P. Sapienza, and L. Zingales. 2003. “People’s opium? Religion and economic attitudes.” Journal of monetary economics 50:225–282.CrossrefGoogle Scholar

  • Güth, W. M., V. Levati, and M. Ploner. 2008. “Social Identity and Trust: An Experimental Investigation.” Journal of Socio-Economics 37:1293–308.CrossrefGoogle Scholar

  • Hargreaves Heap, S. P., and D. J. Zizzo. 2009. “The Value of Groups.” The American Economic Review 99:295–323.CrossrefGoogle Scholar

  • Harris, D., B. Herrmann, and A. Kontoleon. 2010. “What Is the Nature and Social Norm within the Context of in-Group Favouritism?” Cambridge Working Papers in Economics No. (1062).Google Scholar

  • Hertel, G., and N. L. Kerr. 2001. “Priming in-Group Favoritism: The Impact of Normative Scripts in the Minimal Group Paradigm.” Journal of Experimental Social Psychology 37:316–24.CrossrefGoogle Scholar

  • Hoff, K., and P. Pandey. 2006. “Discrimination, Social Identity, and Durable Inequalities.” American Economic Review 96:206–11.CrossrefGoogle Scholar

  • Homans, G. C. 1950. The Human Group. New York: Harcourt, Brace.Google Scholar

  • Jetten, J., R. Spears, and A. S. R. Manstead. 1997. “Strength of Identification and Intergroup Differentiation: The Influence of Group Norms.” European Journal of Social Psychology 27:603–9.CrossrefGoogle Scholar

  • Jost, J. T., M. R. Banaji, and B. A. Nosek. 2004. “A Decade of System Justification Theory: Accumulated Evidence of Conscious and Unconscious Bolstering of the Status Quo.” Political Psychology 25:881–918.CrossrefGoogle Scholar

  • Kimbrough, E. O., and A. Vostroknutov. 2013. “Norms Make Preferences Social.” Discussion Papers dp13-01, Department of Economics, Simon Fraser University.Google Scholar

  • Kirchsteiger, G., L. Rigotti, and A. Rustichini. 2006. “Your Morals Might Be Your Moods.” Journal of Economic Behavior and Organization 59:155–72.CrossrefGoogle Scholar

  • Krupka, E. L., and R. A. Weber. 2013. “Identifying Social Norms Using Coordination Games: Why Does Dictator Game Sharing Vary?” Journal of the European Economic Association 11:495–524.Web of ScienceCrossrefGoogle Scholar

  • Kumru, C., and L. Vesterlund. 2008. “The Effect of Status on Voluntary Contribution.” UNSW Australian School of Business Research Paper No. 2008 ECON 02.Google Scholar

  • McLeish, K. N., and R. J. Oxoby. 2007. “Identity, Cooperation, and Punishment.” IZA Discussion Paper No. 2572.Google Scholar

  • Mullen, B., R. Brown, and C. Smith. 1992. “Ingroup Bias as a Function of Salience, Relevance and Status: An Integration.” European Journal of Social Psychology 22:103–22.CrossrefGoogle Scholar

  • Ostrom, E. 2000. “Collective Action and the Evolution of Social Norms.” The Journal of Economic Perspectives 14:137–58.CrossrefGoogle Scholar

  • Powell, J. L. 1984. “Least Absolute Deviations Estimation for the Censored Regression Model.” Journal of Econometrics 25:303–325.CrossrefGoogle Scholar

  • Schelling, T. 1960. The Strategy of Conflict. Cambridge, MA: Harvard University Press.Google Scholar

  • Tajfel, H., C. Flament, M. G. Billig, and R. F. Bundy. 1971. “Social Categorization and Intergroup Behavior.” European Journal of Social Psychology 1:149–77.CrossrefGoogle Scholar

  • Tsutsui, K., and D. J. Zizzo. forthcoming. “Group Status, Minorities and Trust.” Experimental Economics.Web of ScienceGoogle Scholar

  • Willer, R. 2009. “Groups Reward Individual Sacrifice: The Status Solution to the Collective Action Problem.” American Sociological Review 74:23–43.CrossrefWeb of ScienceGoogle Scholar

About the article

Published Online: 2014-02-19

Published in Print: 2014-01-01

However, there are a few important counter-examples and negative findings. In terms of counter-examples, McLeish and Oxoby (2008) find that individuals are more likely to levy costly punishment on in-group members for bad behavior than on out-group members, which seems inconsistent with treating in-group members better but is consistent with an evolutionary group-selection model for the existence of social norms (Bernhard, Fischbacher, and Fehr 2006). In terms of negative results, several studies find no effect of equal-but-different groups at all: Güth, Levatti, and Ploner (2008), as well many of the treatments in Charness, Rigotti, and Rustichini (2007) and Eckel and Grossman (2005).

The World Values Survey asks how justifiable such morally wrong behaviors as cheating on taxes or unjustly claiming government benefits are. Respondents answer on a scale from 1 (never justifiable) to 10 (always justifiable). The authors find that respondents who view themselves as belonging to a higher social class tend to rate these behaviors as less frequently justifiable.

This pattern is also consistent with the classical in-group bias results in the context of disinterested money division tasks, particularly if in-group bias is the norm (Harris, Herrmann, and Kontoleon 2010; Hertel and Kerr 2001; Jetten et al. 1997).

Two relevant examples: (i) “From everyone who has been given much, much will be demanded; and from the one who has been entrusted with much, much more will be asked.” Luke 12:48; (ii) “Not many of you should become teachers, my fellow believers, because you know that we who teach will be judged more strictly.” James 3:1.

Peter Parker’s uncle, in Stan Lee’s Spiderman, famously advises: “With great power comes great responsibility.”

The experimental literature in social psychology starts with Tajfel et al. (1971). See Mullen, Brown, and Smith (1992) or the references and discussion in Chen and Li (2009) for a nice overview of subsequent psychological research.

Also many of the treatments in Charness, Rigotti, and Rustichini (2007) and Eckel and Grossman (2005) yielded no significant evidence of in-group bias.

This phenomenon could also rationalize a wide array of seemingly unrelated or contradictory results concerning the effects of status in the experimental economics literature. For example, the hypothesis is consistent with the results in Ball et al. (2001) where prices in two-sided auctions favor high status experimental participants, if profit-maximization is the norm that governs that situation. It is also consistent with increased giving by high status players in public goods games (Kumru and Vesterlund 2008).

The refreshments were modest, consisting of a glass of water or lemonade as well as some snacks – crackers, cheese and grapes.

By reinforcing the random status assignment, I follow previous experimental work on status in the laboratory. For example, in Ball et al. (2001) a random status assignment was reinforced and made more salient by having low status participants clap for high status participants.

The number of rounds varied across sessions because of time constraints.

Even though participants were seated by color group, there were several people (8–10) in each color group in each session making the assumption of anonymity still plausible.

This differs slightly from the trust game in Berg, Dickhaut, and McCabe (1995), where both senders and receivers were endowed with $10.

The descriptive terms used here (reliable, lemon, buyer and seller) and later in the analysis of the truth game are for expositional purposes only. The state space and message space were actually {Heads, Tails}, each buyer’s action set was {Left, Right} and players were called “senders” and “receivers.” See the Appendix for experimental instructions.

Other equilibria are possible, including a perverse equilibrium in which the buyer believes the car is reliable whenever observing the message “lemon.” I discuss this equilibrium in the Appendix.

Relaxing this last assumption makes the algebra slightly messier and implies some lying even when the seller knows the car is reliable but adds little intuition.

Since money sent was tripled, the proportion returned can take values from 0 to 3. Excluded are observations where nothing was sent where the return ratio $Returned$Sent is undefined.

These similarities are striking given the differences in initial endowments in the current design not present in the original trust game experiments, already suggesting that distributional preferences alone cannot explain participant behavior.

Specifically, the marginal impact of a dollar sent on the average return ratio was 0.043 for low status receivers, while it was 0.043 + 0.106 = 0.149 for high status receivers – more than three times as large. Furthermore, in all but the least elaborate specification (column 1) the estimated marginal impact of one additional dollar sent on low status receivers’ return ratios is not significantly different from zero, indicating a strikingly weak concern for reciprocity on the part of low status receivers.

The following robustness checks were conducted (not reported, but available upon request): (i) including individual receiver random effects; (ii) clustering standard errors at the individual level rather than the session level; (iii) accounting for censoring using Tobit instead of OLS. In all of these alternate specifications: (i) high status receivers are significantly more reciprocal than low status receivers and (ii) senders’ group affiliation did not matter for behavior.

It might seem more natural to explain variation in behavior with individual heterogeneity in the weights placed on identity utility, αj, and ideals that do not vary by identity category. However, with this approach, it is difficult to simultaneously explain why high status receivers are less generous when sent a low amount and more generous when sent a high amount – a result that obtains below.

Censoring from above is also possible, but not quite as worrying as there are very few observations in the data where the maximum possible amount was returned.

The main error-term assumption required for CLAD to be consistent is that errors have median zero, which is quite a bit less restrictive than the standard assumption of normality and homoskedasticity. The tradeoff is that an assumption must be made about the data. Roughly speaking, there must be “enough” uncensored observations which is likely to be satisfied in the present case.

Individual random effects are used to take into account the fact that we have repeated observations on individuals where in some observations the individual is part of an in-group pairing and in some other observations the same individual is involved in an out-group pairing.

The regressions for the S-ID data roughly correspond to Table 3, column 1, as they do not control for sender status. The figure therefore represents a conservative estimate of how return ratio function slopes vary by status.

Of course, agent j’s ideal could also depend on her co-player’s social category, but since there was no evidence of this in the S-ID version of the experiment, this possibility is not modeled.

It looks rather out of place, but the 4 in α˜ is an artifact of factoring –2 out of (4s2r7) to get the expression in the parentheses into an rrIdeal(s) format. This is also where the 7/2 term in rIdeal comes from.

For direct supporting evidence on this point in the context of a dictator game with third-party punishment, see Butler, Conzo, and Leroch (2013).

The actual average difference in the data is $1.53. This does not necessarily imply that my model organizes the data poorly, however. The observed discrepancy between the model prediction and the data may result from several factors: senders’ ideals may vary by status, which I assume away for simplicity here; alternatively, αj may have a group-contingent component, which I again have assumed away for simplicity. For example, the pattern is consistent with low status receivers generally placing less weight on identity (α¯L<α¯H).

There is an important subset of economists who argue that the trust game has nothing to do with trust. Addressing this meta-critique of the trust game is beyond the scope of the current inquiry, but direct evidence that the trust game does involve trust is provided in Butler, Giuliano, and Guiso (2012).

This is not true for receivers, of course, because each round a receiver faces a potentially different choice: how much to return conditional on being sent x dollars, x=0,,7. Therefore, the simpler route of constructing one average reciprocity measure for each individual receiver would be problematic.

On average, high status senders sent $4.26, while low status senders sent $3.47. Using a one-tailed t-test the difference is significant at the 5% level (p = 0.042). Regressing individuals’ average send amounts on a dummy for high status senders yields a marginally significant difference (p = 0.064). Both of these tests involve 84 observations – one for each S-ID participant. The OLS regression uses robust standard errors clustered by session.

Again, these numbers are calculated using one (summary) observation per individual, for a total of 84 observations.

The increased trust exhibited by high status S-ID senders in the raw data is slightly smaller, at 22%, but still considerably larger than in-group bias in ID-only sessions.

That is to say, this dummy variable takes the value of 1 when the seller’s message matches his or her private information and 0 otherwise.

This equilibrium arises when buyers always believe the opposite of the message sent. Given these “incredulous” buyers, sellers pool on sending the message “lemon” irrespective of their private information, so that sellers lie about good information and tell the truth about bad information.

I thank an anonymous referee for suggesting this comparison, generally, and this efficiency measure specifically.

As an example, consider an interaction in which the trust game sender sends 3. The total earnings of both players would be 7 + 2* 3 = 13 since each dollar sent creates two extra dollars in surplus. Maximum total earnings occurs when the sender sends as much as possible, i.e. 7, yielding total earnings of 7 + 2* 7 = 21. The minimum possible total earnings (7) occurs when the sender sends 0. Thus, the efficiency of an interaction where a sender sends 3 is 1372170.43.

Pushing this intuition a bit further, if the proposed wealth effect resulted in an approximately uniform increase in generosity, we should see “wealthier participants” return a fixed amount more to their co-player for each amount initially sent than their poorer counterparts. Since this constant extra generosity would have greater impact on return ratios for low return amounts, this uniform extra generosity should imply flatter return ratio functions for high status/wealthier participants. This was exactly the opposite of the observed patterns.

A gift-exchange game is similar to the trust game. There are two players. One player moves first and chooses how much of a fixed sum of money to transfer to his or her co-player – player 2. Player 2 observes the amount transferred and decides how much “effort” to exert. Effort decreases player 2’s earnings but increases player 1’s earnings. Reciprocity is measured as the responsiveness of the effort decision to the transfer decision. Generosity is measured by the amount of effort exerted when the initial transfer is zero.

They also mirror, by the way, the hypothetically “wealthier” participants outlined above.

Citation Information: The B.E. Journal of Theoretical Economics, Volume 14, Issue 1, Pages 293–338, ISSN (Online) 1935-1704, ISSN (Print) 2194-6124, DOI: https://doi.org/10.1515/bejte-2013-0026.

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