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Optimal policy with probabilistic equilibrium selection

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Abstract
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.

Suggested Citation

  • Huberto M. Ennis & Todd Keister, 2001. "Optimal policy with probabilistic equilibrium selection," Working Paper 01-03, Federal Reserve Bank of Richmond.
    • Handle: RePEc:fip:fedrwp:01-03
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    Cited by:

    1. Aubhik Khan & Robert G. King & Alexander L. Wolman, 2001. "The pitfalls of discretionary monetary policy," Working Papers 01-16, Federal Reserve Bank of Philadelphia.
    2. Aubhik Khan & Robert G. King & Alexander L. Wolman, 2001. "The pitfalls of monetary discretion," Working Paper 01-08, Federal Reserve Bank of Richmond.

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    Keywords

    Public policy; Electronic commerce; Equilibrium (Economics);
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