Learning, Expectations Formation, and the Pitfalls of Optimal Control Monetary Policy

Authors

Athanasios Orphanides

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2008-05 | April 1, 2008

This paper examines the robustness characteristics of optimal control policies derived under the assumption of rational expectations to alternative models of expectations. We assume that agents have imperfect knowledge about the precise structure of the economy and form expectations using a forecasting model that they continuously update based on incoming data. We find that the optimal control policy derived under the assumption of rational expectations can perform poorly when expectations deviate modestly from rational expectations. We then show that the optimal control policy can be made more robust by deemphasizing the stabilization of real economic activity and interest rates relative to inflation in the central bank loss function. That is, robustness to learning provides an incentive to employ a "conservative" central banker. We then examine two types of simple monetary policy rules from the literature that have been found to be robust to model misspecification in other contexts. We find that these policies are robust to empirically plausible parameterizations of the learning models and perform about as well or better than optimal control policies.

Article Citation

Orphanides, Athanasios, and John C. Williams. 2008. “Learning, Expectations Formation, and the Pitfalls of Optimal Control Monetary Policy,” Federal Reserve Bank of San Francisco Working Paper 2008-05. Available at https://doi.org/10.24148/wp2008-05

About the Author
John C. Williams served as President and Chief Executive Officer of the Federal Reserve Bank of San Francisco from March 1, 2011 to June 17, 2018. Dr. Williams was previously the executive vice president and director of research for the San Francisco bank, which he joined in 2002. He began his career in 1994 as an […] Learn more about John C. Williams