If cooperation is likely punish mildly: Insights from economic experiments based on the snowdrift game
Luo-Luo Jiang, Matjaz Perc, Attila Szolnoki

TL;DR
This study investigates how the severity of punishment influences cooperation in social dilemmas, finding that mild punishment often suffices and can be more effective than severe sanctions, especially when cooperation is already likely.
Contribution
The paper provides experimental evidence that mild punishment is generally as effective as severe punishment in promoting cooperation, challenging the assumption that harsher sanctions are always better.
Findings
Severe punishment is only more effective under highly adverse conditions.
Mild punishment leads to higher average payoffs when cooperation is likely.
Small fines can motivate cooperation without the negative effects of large fines.
Abstract
Punishment may deter antisocial behavior. Yet to punish is costly, and the costs often do not offset the gains that are due to elevated levels of cooperation. However, the effectiveness of punishment depends not only on how costly it is, but also on the circumstances defining the social dilemma. Using the snowdrift game as the basis, we have conducted a series of economic experiments to determine whether severe punishment is more effective than mild punishment. We have observed that severe punishment is not necessarily more effective, even if the cost of punishment is identical in both cases. The benefits of severe punishment become evident only under extremely adverse conditions, when to cooperate is highly improbable in the absence of sanctions. If cooperation is likely, mild punishment is not less effective and leads to higher average payoffs, and is thus the much preferred…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
