title: Accidental outcomes guide punishment in a "trembling hand" game.
abstract: How do people respond to others' accidental behaviors? Reward and punishment for an accident might depend on the actor's intentions, or instead on the unintended outcomes she brings about. Yet, existing paradigms in experimental economics do not include the possibility of accidental monetary allocations. We explore the balance of outcomes and intentions in a two-player economic game where monetary allocations are made with a "trembling hand": that is, intentions and outcomes are sometimes mismatched. Player 1 allocates $10 between herself and Player 2 by rolling one of three dice. One die has a high probability of a selfish outcome, another has a high probability of a fair outcome, and the third has a high probability of a generous outcome. Based on Player 1's choice of die, Player 2 can infer her intentions. However, any of the three die can yield any of the three possible outcomes. Player 2 is given the opportunity to respond to Player 1's allocation by adding to or subtracting from Player 1's payoff. We find that Player 2's responses are influenced substantially by the accidental outcome of Player 1's roll of the die. Comparison to control conditions suggests that in contexts where the allocation is at least partially under the control of Player 1, Player 2 will punish Player 1 accountable for unintentional negative outcomes. In addition, Player 2's responses are influenced by Player 1's intention. However, Player 2 tends to modulate his responses substantially more for selfish intentions than for generous intentions. This novel economic game provides new insight into the psychological mechanisms underlying social preferences for fairness and retribution.
authors.affiliation: Department of Psychology, Harvard University, Cambridge, Massachusetts, USA. cushman@wjh.harvard.edu
authors.forename: Fiery
authors.initials: F
authors.lastname: Cushman
authors.forename: Anna
authors.initials: A
authors.lastname: Dreber
authors.forename: Ying
authors.initials: Y
authors.lastname: Wang
authors.forename: Jay
authors.initials: J
authors.lastname: Costa
mesh_terms: D000293:Adolescent; D000328:Adult; D000368:Aged; D001519:Behavior; D005717:Games, Experimental; D006801:Humans; D008875:Middle Aged; D011678:Punishment; D055815:Young Adult
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