We use a limited information environment to mimic the state of confusion in an experimental, repeated public goods game. The results show that reinforcement learning leads to dynamics similar to those observed in standard public goods games. However, closer inspection shows that individual decay...

We use a limited information environment to mimic the state of confusion in an experimental, repeated public goods game. The results show that reinforcement learning leads to dynamics similar to those observed in standard public goods games. However, closer inspection shows that individual decay...

We use a limited information environment to assess the role of confusion in the repeated voluntary contributions game. A comparison with play in a standard version of the game suggests, that the common claim that decision errors due to confused subjects biases estimates of cooperation upwards,...

We examine the effects of social preferences and beliefs about the social preferences of others in a simple leader-follower voluntary contributions game. We find that groups perform best when led by those who are reciprocally oriented. Part of the effect can be explained by a false consensus...

We examine the effects of social preferences and beliefs about the social preferences of others in a simple leader-follower voluntary contributions game. We find that groups perform best when led by those who are reciprocally oriented. Part of the effect can be explained by a false consensus...

We report an experiment comparing sequential and simultaneous contributions to a public good in a quasi-linear two-person setting (Varian, Journal of Public Economics, 1994). Our findings support the theoretical argument that sequential contributions result in lower overall provision than...

We examine the characteristics of effective leaders in a simple leader-follower voluntary contributions game. We focus on two factors: the individual's cooperativeness and the individual's beliefs about the cooperativeness of others. We find that groups perform best when led by those who are...