Government Policy and the Probability of Coordination Failures

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. We show how such a mechanism can be derived as the natural result of an adaptive learning process. This approach leads to a well-defined optimal policy problem, and has important implications for the conduct of government policy. We illustrate these implications using a simple model of technology adoption under network externalities.