Optimal policy with probabilistic equilibrium selection

This paper introduces an approach to the study of optimal government policy in economies characterized by a coordination problem and multiple equilibria. Such models are often criticized as not being useful for policy analysis because they fail to assign a unique prediction to each possible policy choice. We employ a selection mechanism that assigns, ex ante, a probability to each equilibrium indicating how likely it is to obtain. With this, the optimal policy is well defined. We show how such a mechanism can be derived as the natural result of an adaptive learning process. This approach generates a theory of how government policy affects the process of equilibrium selection; we illustrate this theory by applying it to problems related to the choice of technology and the optimal sales tax on Internet commerce.