Stochastic stability in best shot network games

The best shot game applied to networks is a discrete model of many processes of contribution to local public goods. It generally has a wide multiplicity of equilibria that we refine through stochastic stability. We show that, depending on how we define perturbations – i.e., possible mistakes that agents make – we can obtain very different sets of stochastically stable states. In particular and non-trivially, if we assume that the only possible source of error is that of a contributing agent that stops doing so, then the only stochastically stable states are Nash equilibria with the largest contribution.