Abstract
Recent research argues “betrayal aversion” leads many people to avoid risk more when a person, rather than nature, determines the outcome of uncertainty. However, past studies indicate that factors unrelated to betrayal aversion, such as loss aversion, could contribute to differences between treatments. Using a novel experiment design to isolate betrayal aversion, one that varies how strategic uncertainty is resolved, we provide rigorous evidence supporting the detrimental impact of betrayal aversion. The impact is substantial: holding fixed the probability of betrayal, the possibility of knowing that one has been betrayed reduces investment by about one-third. We suggest emotion-regulation underlies these results and helps to explain the importance of impersonal, institution-mediated exchange in promoting economic efficiency.
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Notes
Tullock (1967) is the first paper, to our knowledge, to discuss and work through the implications of a sequential prisoner’s dilemma within a trust context.
In our case, emotion regulation can explain the actions people take to avoid the negative emotional experience of betrayal.
Jackson, p. 72.
Note that this game tree was not distributed to subjects, nor were the terms “trust”, “betray”, or “reciprocate”, used to describe the game. The instructions also contain neutral framing.
The strategy method has been shown to be effective in experiments like ours. In particular, Brandts and Charness (2011) report a meta-analysis and find that, in all studied cases, treatment effects found using the strategy method also were observed using direct-response. The decision to make the game simultaneous does not change the strategic nature of the game, and further ensures all investors and trustees that every trustee decision had some possibility of being realized. In a sequential environment, any trustee whose counterpart had already made a decision not to trust would know with certainty that their decision would not be implemented.
Supplement A through Supplement D provide transcripts of the instructions for all treatments.
The decisions from the few separated subjects have not been analyzed because their environment is not comparable to that of the other OPTION and KNOW treatments’ participants.
The instructions read as follows: “After the Room B participants make their decisions, the computer will assign either “U” or “D” to each of the ten numbers. The computer has been programmed to assign dollar values to each of the 10 numbers in the box according to the decisions made by the Room B participants. What this means is that the number of “U” choices made by the computer is exactly the same as the number of “U” choices made by the participants in room B. Also, the number of “D” choices made by the computer is exactly the same as the number of “D” choices made by the room B participants. (Note: while the number of “U” numbers and number of “D” numbers are the same as in the Room B decisions, which numbers are assigned “U” or “D” is randomly decided by the computer) For example: if five Room B participants choose “U”, then five of the numbers between 1 and 10 are randomly assigned to have the “U” payoff, and the remaining five numbers are assigned to the “D” payoff. (Note: the numbers used here are only an example and not necessarily representative of Room B decisions).”
Trustee instructions given to both trustees and investors in all treatments read as follows: “You will be anonymously assigned to a Room A counterpart who drew your number randomly from a box with the numbers 1 through 10 inside. This person will be your counterpart for the entire experiment. Your counterpart will make a decision that can affect your earnings in today’s experiment. He or she can choose for both of you to be paid $5. Another possibility is that he/she will let you determine both of your payoffs. If he/she chooses this option and you choose “U”, then you get paid $15 and he/she gets paid $15. If you choose “D”, then you get paid $28 and he/she gets paid $2. Your payoff will be determined in one of these two ways. Your counterpart can choose only one of the earnings methods. We will ask you to make your decision on “U” or “D” at the same time that your counterpart makes his or her choice. Your decision will only determine your payoff if your counterpart did not choose the option to give you $5.”
Note, however, that while the independent effects of social preferences are held constant between treatments, there may still be interactions between social preferences and betrayal aversion. Since the objective of this study is to identify whether betrayal aversion can have a negative effect on social exchange we do not attempt to control for these interactions, since betrayal aversion interacting with other preferences is captured by our hypotheses.
See Supplements C and D.
Based on where they sit in the lab.
As noted in footnote 8, the single “separated” investor in each DONTKNOW session (the one who participated in the KNOW or OPTION game) is excluded from our analysis. Our analysis does not exclude any trustee because all trustees in all treatments were in the same situation.
This implies that the expected value of choosing trust is significantly greater than the safe option (two tailed t-test p<0.05).
All of the p-values reported in the results section are from two-sided Mann-Whitney tests unless otherwise noted.
Conversely, result 1 (which shows the difference in trust between DONTKNOW and KNOW) can be interpreted as suggesting that for about a fourth of people (92%−65.38%=26.62%) the disutility associated with betrayal aversion exceeds the expected benefits of the monetary gamble. Overall, our three treatments suggest that at least 46% (26.62%+19.38%) of subjects hold sufficient betrayal aversion to influence economic decision making in our trust environment.
Note that if an investor trusts then the expected earnings of a pair of subjects is always 30 dollars regardless of the treatment. If an investor chooses a computer trust option the realized earnings of the pair could be either 17, 30, or 43 dollars, while the expected earnings from trust remains 30 dollars. We use expected earnings from trusting in a particular session for the earnings of an investor in order to have accurate reporting.
We thank Peter DeScioli and an anonymous reviewer for suggesting this treatment.
One-sided statistical tests are appropriate given our ex ante hypotheses specifically and necessarily locating trust in NOEXPOSURE between the KNOW and DONTKNOW treatments.
The questionnaire responses from investors to the question “How would you feel if your counterpart chose D?”, seem to support our view that subjects’ attitudes are consistent with betrayal aversion. Investors reported they would feel “angry”, “miffed”, “annoyed”, “sad” or “betrayed” if their trust was not reciprocated. One subject, who chose the computer option in OPTION, said betrayal by a human would leave him feeling, “[o]ffended, thus I didn’t choose that option.” On the other hand, a subject who “trusted” in DONTKNOW replied that if he did not receive the higher payoff, “I would feel neutral because it really is the computer which decides what letter I’m assigned,” and another indicated they would feel “Nothing, as my earnings are decided by computer.”
In the KNOW2 treatment, all investors had to read the instructions that explained how the computer made its decision as well as answer the quiz questions associated with the computer decision.
Pooling the KNOW and KNOW2 data together. The combined KNOW data reveals marginally fewer trusting than the 92% that trust in DONTKNOW (p<0.07) and significantly fewer trusting than the 100% in OPTION (p<0.01). The 85% of investors that trust in KNOW2 is not significantly different than the 92% that trust in DONTKNOW.
The presence of a computer might matter. For example, a reviewer suggests that computer effects may include reducing the influence of the negative emotions associated with betrayal aversion.
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Acknowledgements
We thank Ernst Fehr and Benjamin Schoefer for a valuable discussion that led to the experiment design reported in this paper. For helpful comments and suggestions, we thank Omar Al-Ubaydli, Vernon Smith, Virgil Storr, Bart Wilson, Erte Xiao, Richard Zeckhauser and participants in research seminars at ICES, the Mercatus Center, George Mason University, University of Lyon, University of Munich, University of Zurich, the International ESA 2008, and the SEA meetings 2008. Kail Padgitt and Adam Smith provided capable laboratory assistance. We gratefully acknowledge research support from the International Foundation for Research in Experimental Economics and the National Science Foundation Research Grant SES-0851250.
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Aimone, J.A., Houser, D. What you don’t know won’t hurt you: a laboratory analysis of betrayal aversion. Exp Econ 15, 571–588 (2012). https://doi.org/10.1007/s10683-012-9314-z
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DOI: https://doi.org/10.1007/s10683-012-9314-z