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The effects of endowment size and strategy method on third party punishment

Abstract

Numerous experiments have shown that people often engage in third-party punishment (3PP) of selfish behavior. This evidence has been used to argue that people respond to selfishness with anger, and get utility from punishing those who mistreat others. Elements of the standard 3PP experimental design, however, allow alternative explanations: it has been argued that 3PP could be motivated by envy (as selfish dictators earn high payoffs), or could be influenced by the use of the strategy method (which is known to influence second-party punishment). Here we test these alternatives by varying the third party’s endowment and the use of the strategy method, and measuring punishment. We find that while third parties do report more envy when they have lower endowments, neither manipulation significantly affects punishment. We also show that punishment is associated with ratings of anger but not of envy. Thus, our results suggest that 3PP is not an artifact of self-focused envy or use of the strategy method. Instead, our findings are consistent with the hypothesis that 3PP is motivated by anger.

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Notes

  1. Evidence of verbal third-party intervention in the field comes from Balafoutas and Nikiforakis (2012).

  2. For example, in the canonical 3PP study, participants played a dictator game with 3PP (Fehr and Fischbacher 2004). Actors received 10 monetary units, and could give up to half to the recipient. Then, third parties received 5 units to spend punishing the actor. Thus, selfish actors who gave less than half made more than 5 units, out-earning both the recipient and the third party.

  3. In psychology, this referred to as an “affective forecasting error”, or an error in predicting how one will feel in the future (Gilbert and Wilson 2007).

  4. Other research has also shown that subjects on MTurk show high test–retest reliability on a range of personality measures (Buhrmester et al. 2011) and demographics (Mason and Suri 2012; Rand 2012), at levels comparable to college undergraduates.

  5. This limited sensitivity to stake size in economic game experiments is also consistent with other findings regarding varying the stakes in the physical lab (Camerer and Hogarth 1999) (however, we note that while manipulations of stake size often have limited effects on mean game play, they do often influence observed variance).

  6. Although our emotion elicitations were necessarily unincentivized, there is a long tradition of using self-report emotion ratings in the social psychological literature and they have been shown to be reliable, and agree with peer ratings (Watson et al. 1988; Watson and Clark 1991). This method of measuring emotions has also been incorporated into experimental economics (Bosman and Van Winden 2002).

  7. Actors were recruited prior to third parties, so that the number of actors choosing to act selfishly or fairly was known prior to recruiting third parties. Accordingly, third parties were assigned to see selfish versus fair actor behavior in proportion to the actions of the actors. This allowed us to attached a correct 1-to-1 matching between actors and third parties.

  8. Predicting emotion ratings using an ordered probit model produces qualitatively identical results; thus, we report linear regressions for consistency across analyses and ease of interpretation of coefficients.

  9. Overall, 61% of subjects answered all comprehension questions correctly (mean number of questions correct = 3.34/4, with rates of comprehension on the four individual questions ranging from 75 to 93 %). Thus, while a relatively low proportion of subjects answered all questions correctly, we note that subjects did relatively well on each individual question, and emphasize that all of our main results hold when including all subjects and when including only comprehenders. Furthermore, this rate of comprehension failure is typical for economic game studies run on MTurk (e.g. Rand et al. 2012).

  10. Low endowment, strategy method condition N = 81; low endowment, hot condition N = 85; high endowment, strategy method condition N = 78; high endowment, hot condition N = 79.

  11. Our main results are robust, however, to analyzing all decisions (i.e. punishment of both selfish and fair behavior). When including all decisions, a regression finds no significant effect of a “low endowment” dummy (coeff = 0.063, n = 482, p = 0.813) or a “hot” dummy (coeff = 0.122, n = 482, p = 0.672), and a regression that adds an interaction term also finds no significant effect of the interaction (coeff = 0.241, n = 482, p = 0.675).

  12. We note that as in Experiment 1, our analyses predicting emotion ratings produce qualitatively equivalent results using ordered probit regressions; we thus again report only linear regression.

  13. High–high condition N = 52; low-low condition N = 57; low–high condition N = 44.

  14. One might argue that it is difficult to draw strong inferences from the finding that our manipulations of endowment and the strategy method did not influence punishment, because they were null results. However, we note that we replicated the null finding that endowments did not influence punishment in both Experiment 1 and 2. Furthermore, our endowment manipulation did have a significant positive effect on envy ratings, providing a positive control that demonstrates that subjects were sensitive to the manipulation. We also conduct a power analysis to assess the smallest effects of our endowment and strategy method manipulations that we could have detected with 80% probability in Experiment 1. We find that smallest detectable effects are (i) a 1.27-cent decrease in punishment in the high endowment relative to the low endowment condition, and (ii) a 1.32-cent decrease in punishment in the strategy method condition relative to the “hot” condition. Thus, while it is possible that we failed to detect a true but small effect of these variables on punishment, this analysis provides a likely upper bound for the size of these effects, and suggests that the use of low endowments or the strategy method cannot fully account for punishment in these conditions.

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Acknowledgments

We thank Gordon Kraft-Todd for assistance running the experiments, and gratefully acknowledge funding from the John Templeton Foundation.

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Correspondence to Jillian Jordan.

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Jordan, J., McAuliffe, K. & Rand, D. The effects of endowment size and strategy method on third party punishment. Exp Econ 19, 741–763 (2016). https://doi.org/10.1007/s10683-015-9466-8

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Keywords

  • Cooperation
  • Norm-enforcement
  • Strategy method
  • Emotions
  • Fairness
  • Economic games