The economics of altruistic punishment and the maintenance of cooperation - PubMed (original) (raw)

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The economics of altruistic punishment and the maintenance of cooperation

Martijn Egas et al. Proc Biol Sci. 2008.

Abstract

Explaining the evolution and maintenance of cooperation among unrelated individuals is one of the fundamental problems in biology and the social sciences. Recent findings suggest that altruistic punishment is an important mechanism maintaining cooperation among humans. We experimentally explore the boundaries of altruistic punishment to maintain cooperation by varying both the cost and the impact of punishment, using an exceptionally extensive subject pool. Our results show that cooperation is only maintained if conditions for altruistic punishment are relatively favourable: low cost for the punisher and high impact on the punished. Our results indicate that punishment is strongly governed by its cost-to-impact ratio and that its effect on cooperation can be pinned down to one single variable: the threshold level of free-riding that goes unpunished. Additionally, actual pay-offs are the lowest when altruistic punishment maintains cooperation, because the pay-off destroyed through punishment exceeds the gains from increased cooperation. Our results are consistent with the interpretation that punishment decisions come from an amalgam of emotional response and cognitive cost-impact analysis and suggest that altruistic punishment alone can hardly maintain cooperation under multi-level natural selection. Uncovering the workings of altruistic punishment as has been done here is important because it helps predicting under which conditions altruistic punishment is expected to maintain cooperation.

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Figures

Figure 1

Figure 1

Changes over rounds in the average (±1 s.e.m.) contribution to the public good. In all five treatments, the initial contribution rate is approximately 9 EMU (45% of the endowment). Only in T13, cooperation increases over the six rounds of the experiment; in all other cases, cooperation is in clear decline (repeated-measures ANOVA, treatment: _F_4,42=11.522, _p_≪0.001; round: _F_5,210=18.146, _p_≪0.001; treatment×round: _F_20,42=4.056, _p_≪0.001). Tukey's post hoc tests showed that contributions in T13 differed from all other treatments, and that T33 differed from T31. Blue diamonds, T13; pink squares, T11; red triangles, T33; turquoise circles, T31; purple asterisk, T00.

Figure 2

Figure 2

Punishment characteristics as a function of the deviation in contribution. (a) Using four categories (0, 1–6, 7–13 and 14–20) of the deviation in contribution between the punisher and the punished participant, the size of each circle indicates the relative frequency of PPs allocated to participants with such deviations in contribution (data are based on all six rounds). Straight lines represent linear Tobit regressions for each of the four punishment treatments. PPs dealt out are significantly increasing with deviation in contribution. Slopes of the regression lines are not significantly different from each other. Estimated deviation thresholds (TH) up to which deviation in contribution goes unpunished are significantly different and have the order TH(T13)<TH(T11)<TH(T33)<TH(31). Statistical details in the electronic supplementary material, table S1. Turquoise circles, T31; red circles, T33; pink circles, T11; blue circles, T13. (b) Frequency of punishment of defecting participants (data are based on all six rounds). Logit regression analysis shows that the marginal likelihood that deviating participants are punished is significantly increasing with increasing deviation in contribution in all treatments. These marginal propensities to punish are the same in all treatments. Statistical details in the electronic supplementary material, table S2. Turquoise bars, T31; red bars, T33; pink bars, T11; blue bars, T13.

Figure 3

Figure 3

The monetary effect of punishment on punished participants. Using four categories (0, 1–6, 7–13 and 14–20) of the deviation in contribution, the size of each circle indicates the relative frequency of the monetary effect of punishment (in EMU) on participants with such deviations in contribution (data are based on all six rounds). Straight lines represent linear Tobit regressions for each of the four punishment treatments. Slopes of the regression lines are not significantly different from each other except for the comparison of T13 with T11. Estimated deviation thresholds (TH) up to which deviation in contribution goes unpunished are significantly different and have the order TH(T13)<TH(T11)=TH(T33)<TH(31). Statistical details in table S3 in the electronic supplementary material. Turquoise circles, T31; red circles, T33; pink circles, T11; blue circles, T13.

Figure 4

Figure 4

Altruistic punishment does not pay off. The average relative gains ((earnings in punishment treatment-earnings in no-punishment treatment)/earnings in no-punishment treatment) neither significantly increase nor decrease over the six rounds of the experiment. (Spearman rank-order correlation; T13: _ρ_=0.7143, _n_=6, _p_=0.1108; T11: _ρ_=−0.0857, _n_=6, _p_=0.8717; T33: _ρ_=0.0857, _n_=6, _p_=0.8717; T31: _ρ_=−0.7714, _n_=6, _p_=0.0724). Relative gains in round 6 are all significantly smaller than zero (p<0.02, two-sided _t_-tests). Blue diamonds, T13; pink squares, T11; red triangles, T33; turquoise circles, T31.

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