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. 2017 May 9;21(1):99–131. doi: 10.1007/s10683-017-9527-2

Table 8.

Determinants of peer punishment

Decision to punish (0 = no; 1 = yes)
Logit estimation
Prosocial punishment Antisocial punishment
Lab MTurk Pooled Pooled and controls Lab MTurk Pooled Pooled and controls
Punisher’s contribution 0.046 −0.003 0.011 −0.002 −0.143*** −0.153*** −0.142*** −0.130***
(0.051) (0.023) (0.022) (0.026) (0.024) (0.026) (0.018) (0.020)
Target’s contribution −0.059 −0.118*** −0.100*** −0.097*** −0.013 0.010 0.002 0.004
(0.038) (0.029) (0.023) (0.023) (0.025) (0.021) (0.015) (0.020)
Others’ avg. contribution 0.038 0.054*** 0.047*** 0.065*** −0.025 −0.019 −0.023 −0.017
(0.035) (0.019) (0.017) (0.017) (0.028) (0.024) (0.018) (0.019)
Received p in t−1 −0.034 −0.025 −0.028 −0.076** 0.129*** 0.069** 0.094*** 0.103***
(0.027) (0.045) (0.023) (0.032) (0.031) (0.034) (0.023) (0.025)
Period −0.117*** −0.111** −0.113*** −0.103*** 0.024 0.036 0.031 0.032
(0.039) (0.044) (0.032) (0.032) (0.062) (0.056) (0.041) (0.048)
Final period −0.115 −0.077 −0.077 −0.236 −1.800*** 0.595* −0.159 −0.014
(0.341) (0.366) (0.275) (0.313) (0.587) (0.340) (0.388) (0.434)
MTurk −0.855*** −0.983*** −1.132*** −1.983***
(0.307) (0.302) (0.347) (0.403)
Age 0.005 0.025
(0.017) (0.019)
Female −1.171*** −0.078
(0.260) (0.381)
Single child −0.320 0.099
(0.376) (0.457)
Foreign 1.403* −2.380***
(0.739) (0.628)
Membership 0.019 −0.838*
(0.288) (0.462)
Constant 0.206 0.202 0.854* 1.216* −0.560 −2.137*** −0.878** −1.101
(0.812) (0.393) (0.466) (0.712) (0.379) (0.682) (0.442) (0.682)
N 370 900 1270 1201 1790 6540 8330 7949
Chi2 27.51 38.98 48.60 109.88 111.55 85.36 187.39 254.26
Decision to punish (0 = no; 1 = yes)
Multilevel mixed effects estimation
Prosocial punishment Antisocial punishment
Lab MTurk Pooled Pooled and controls Lab MTurk Pooled Pooled and controls
Punisher’s contribution 0.000 0.003 0.002 0.000 −0.008*** −0.004*** −0.005*** −0.004***
(0.006) (0.005) (0.004) (0.004) (0.001) (0.001) (0.000) (0.000)
Target’s contribution −0.012*** −0.021*** −0.018*** −0.018*** 0.000 0.000 0.000 0.000
(0.004) (0.003) (0.002) (0.002) (0.002) (0.001) (0.001) (0.001)
Others’ avg. contribution 0.013*** 0.011*** 0.012*** 0.015*** 0.000 −0.001 −0.001 0.000
(0.005) (0.003) (0.003) (0.003) (0.001) (0.001) (0.001) (0.001)
Received p in t−1 −0.009 −0.004 −0.007 −0.012*** 0.010*** 0.003*** 0.004*** 0.004***
(0.005) (0.006) (0.004) (0.004) (0.001) (0.001) (0.001) (0.001)
Period −0.014 −0.011** −0.012*** −0.013*** 0.004* 0.001 0.001 0.001
(0.009) (0.005) (0.004) (0.004) (0.002) (0.001) (0.001) (0.001)
Final period −0.037 −0.045 −0.043 −0.040 −0.081*** 0.018*** 0.010* 0.011*
(0.086) (0.047) (0.041) (0.042) (0.019) (0.006) (0.006) (0.006)
MTurk −0.190*** −0.215*** −0.044*** −0.088***
(0.059) (0.072) (0.016) (0.018)
Age 0.001 0.001
(0.003) (0.001)
Female −0.204*** 0.001
(0.052) (0.011)
Single child −0.085 0.002
(0.076) (0.016)
Foreign 0.154 −0.071**
(0.105) (0.028)
Membership −0.070 −0.035**
(0.063) (0.014)
Constant 0.611*** 0.437*** 0.622*** 0.700*** 0.187*** 0.104*** 0.156*** 0.176***
(0.123) (0.092) (0.084) (0.122) (0.042) (0.016) (0.020) (0.027)
N 370 900 1270 1201 1790 6540 8330 7949
Chi2 24.64 98.78 129.04 168.92 138.89 116.77 197.44 226.82

Logit and Multilevel mixed effects estimation, which allows for individual and group differences, as well as for treatment-specific residuals. We split the analysis into two different types of punishment. Pro-social punishment includes instances where the punisher’s contribution to the public good in that round exceeded that of their target. Anti-social punishment includes instances where the target contributed at least as much as the punisher. ‘Punisher’s contribution’ is the contribution of the participant punishing; ‘Target’s contribution’ is the contribution of the punished participant; ‘Average contribution others’ is the mean contribution of the other two members of the group; ‘Received punishment in t−1′ is the punishment amount received from others in the previous period; ‘Period’ is the period number; ‘Final period’ is a dummy for the last period; ‘MTurk’ is a dummy for the MTurk sample; demographic controls are the same of Table 6. Robust standard errors clustered on groups for the Logit model

* p < 0.10; ** p < 0.05; *** p < 0.01